essay obesity among youngsters is a serious illness

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Essay on Obesity

List of essays on obesity, essay on obesity – short essay (essay 1 – 150 words), essay on obesity (essay 2 – 250 words), essay on obesity – written in english (essay 3 – 300 words), essay on obesity – for school students (class 5, 6, 7, 8, 9, 10, 11 and 12 standard) (essay 4 – 400 words), essay on obesity – for college students (essay 5 – 500 words), essay on obesity – with causes and treatment (essay 6 – 600 words), essay on obesity – for science students (essay 7 – 750 words), essay on obesity – long essay for medical students (essay 8 – 1000 words).

Obesity is a chronic health condition in which the body fat reaches abnormal level. Obesity occurs when we consume much more amount of food than our body really needs on a daily basis. In other words, when the intake of calories is greater than the calories we burn out, it gives rise to obesity.

Audience: The below given essays are exclusively written for school students (Class 5, 6, 7, 8, 9, 10, 11 and 12 Standard), college, science and medical students.

Introduction:

Obesity means being excessively fat. A person would be said to be obese if his or her body mass index is beyond 30. Such a person has a body fat rate that is disproportionate to his body mass.

Obesity and the Body Mass Index:

The body mass index is calculated considering the weight and height of a person. Thus, it is a scientific way of determining the appropriate weight of any person. When the body mass index of a person indicates that he or she is obese, it exposes the person to make health risk.

Stopping Obesity:

There are two major ways to get the body mass index of a person to a moderate rate. The first is to maintain a strict diet. The second is to engage in regular physical exercise. These two approaches are aimed at reducing the amount of fat in the body.

Conclusion:

Obesity can lead to sudden death, heart attack, diabetes and may unwanted illnesses. Stop it by making healthy choices.

Obesity has become a big concern for the youth of today’s generation. Obesity is defined as a medical condition in which an individual gains excessive body fat. When the Body Mass Index (BMI) of a person is over 30, he/ she is termed as obese.

Obesity can be a genetic problem or a disorder that is caused due to unhealthy lifestyle habits of a person. Physical inactivity and the environment in which an individual lives, are also the factors that leads to obesity. It is also seen that when some individuals are in stress or depression, they start cultivating unhealthy eating habits which eventually leads to obesity. Medications like steroids is yet another reason for obesity.

Obesity has several serious health issues associated with it. Some of the impacts of obesity are diabetes, increase of cholesterol level, high blood pressure, etc. Social impacts of obesity includes loss of confidence in an individual, lowering of self-esteem, etc.

The risks of obesity needs to be prevented. This can be done by adopting healthy eating habits, doing some physical exercise regularly, avoiding stress, etc. Individuals should work on weight reduction in order to avoid obesity.

Obesity is indeed a health concern and needs to be prioritized. The management of obesity revolves around healthy eating habits and physical activity. Obesity, if not controlled in its initial stage can cause many severe health issues. So it is wiser to exercise daily and maintain a healthy lifestyle rather than being the victim of obesity.

Obesity can be defined as the clinical condition where accumulation of excessive fat takes place in the adipose tissue leading to worsening of health condition. Usually, the fat is deposited around the trunk and also the waist of the body or even around the periphery.

Obesity is actually a disease that has been spreading far and wide. It is preventable and certain measures are to be taken to curb it to a greater extend. Both in the developing and developed countries, obesity has been growing far and wide affecting the young and the old equally.

The alarming increase in obesity has resulted in stimulated death rate and health issues among the people. There are several methods adopted to lose weight and they include different diet types, physical activity and certain changes in the current lifestyle. Many of the companies are into minting money with the concept of inviting people to fight obesity.

In patients associated with increased risk factor related to obesity, there are certain drug therapies and other procedures adopted to lose weight. There are certain cost effective ways introduced by several companies to enable clinic-based weight loss programs.

Obesity can lead to premature death and even cause Type 2 Diabetes Mellitus. Cardiovascular diseases have also become the part and parcel of obese people. It includes stroke, hypertension, gall bladder disease, coronary heart disease and even cancers like breast cancer, prostate cancer, endometrial cancer and colon cancer. Other less severe arising due to obesity includes osteoarthritis, gastro-esophageal reflux disease and even infertility.

Hence, serious measures are to be taken to fight against this dreadful phenomenon that is spreading its wings far and wide. Giving proper education on benefits of staying fit and mindful eating is as important as curbing this issue. Utmost importance must be given to healthy eating habits right from the small age so that they follow the same until the end of their life.

Obesity is majorly a lifestyle disease attributed to the extra accumulation of fat in the body leading to negative health effects on a person. Ironically, although prevalent at a large scale in many countries, including India, it is one of the most neglect health problems. It is more often ignored even if told by the doctor that the person is obese. Only when people start acquiring other health issues such as heart disease, blood pressure or diabetes, they start taking the problem of obesity seriously.

Obesity Statistics in India:

As per a report, India happens to figure as the third country in the world with the most obese people. This should be a troubling fact for India. However, we are yet to see concrete measures being adopted by the people to remain fit.

Causes of Obesity:

Sedentary lifestyle, alcohol, junk food, medications and some diseases such as hypothyroidism are considered as the factors which lead to obesity. Even children seem to be glued to televisions, laptops and video games which have taken away the urge for physical activities from them. Adding to this, the consumption of junk food has further aggravated the growing problem of obesity in children.

In the case of adults, most of the professions of today make use of computers which again makes people sit for long hours in one place. Also, the hectic lifestyle of today makes it difficult for people to spare time for physical activities and people usually remain stressed most of the times. All this has contributed significantly to the rise of obesity in India.

Obesity and BMI:

Body Mass Index (BMI) is the measure which allows a person to calculate how to fit he or she is. In other words, the BMI tells you if you are obese or not. BMI is calculated by dividing the weight of a person in kg with the square of his / her height in metres. The number thus obtained is called the BMI. A BMI of less than 25 is considered optimal. However, if a person has a BMI over 30 he/she is termed as obese.

What is a matter of concern is that with growing urbanisation there has been a rapid increase of obese people in India? It is of utmost importance to consider this health issue a serious threat to the future of our country as a healthy body is important for a healthy soul. We should all be mindful of what we eat and what effect it has on our body. It is our utmost duty to educate not just ourselves but others as well about this serious health hazard.

Obesity can be defined as a condition (medical) that is the accumulation of body fat to an extent that the excess fat begins to have a lot of negative effects on the health of the individual. Obesity is determined by examining the body mass index (BMI) of the person. The BMI is gotten by dividing the weight of the person in kilogram by the height of the person squared.

When the BMI of a person is more than 30, the person is classified as being obese, when the BMI falls between 25 and 30, the person is said to be overweight. In a few countries in East Asia, lower values for the BMI are used. Obesity has been proven to influence the likelihood and risk of many conditions and disease, most especially diabetes of type 2, cardiovascular diseases, sleeplessness that is obstructive, depression, osteoarthritis and some cancer types.

In most cases, obesity is caused through a combination of genetic susceptibility, a lack of or inadequate physical activity, excessive intake of food. Some cases of obesity are primarily caused by mental disorder, medications, endocrine disorders or genes. There is no medical data to support the fact that people suffering from obesity eat very little but gain a lot of weight because of slower metabolism. It has been discovered that an obese person usually expends much more energy than other people as a result of the required energy that is needed to maintain a body mass that is increased.

It is very possible to prevent obesity with a combination of personal choices and social changes. The major treatments are exercising and a change in diet. We can improve the quality of our diet by reducing our consumption of foods that are energy-dense like those that are high in sugars or fat and by trying to increase our dietary fibre intake.

We can also accompany the appropriate diet with the use of medications to help in reducing appetite and decreasing the absorption of fat. If medication, exercise and diet are not yielding any positive results, surgery or gastric balloon can also be carried out to decrease the volume of the stomach and also reduce the intestines’ length which leads to the feel of the person get full early or a reduction in the ability to get and absorb different nutrients from a food.

Obesity is the leading cause of ill-health and death all over the world that is preventable. The rate of obesity in children and adults has drastically increased. In 2015, a whopping 12 percent of adults which is about 600 million and about 100 million children all around the world were found to be obese.

It has also been discovered that women are more obese than men. A lot of government and private institutions and bodies have stated that obesity is top of the list of the most difficult and serious problems of public health that we have in the world today. In the world we live today, there is a lot of stigmatisation of obese people.

We all know how troubling the problem of obesity truly is. It is mainly a form of a medical condition wherein the body tends to accumulate excessive fat which in turn has negative repercussions on the health of an individual.

Given the current lifestyle and dietary style, it has become more common than ever. More and more people are being diagnosed with obesity. Such is its prevalence that it has been termed as an epidemic in the USA. Those who suffer from obesity are at a much higher risk of diabetes, heart diseases and even cancer.

In order to gain a deeper understanding of obesity, it is important to learn what the key causes of obesity are. In a layman term, if your calorie consumption exceeds what you burn because of daily activities and exercises, it is likely to lead to obesity. It is caused over a prolonged period of time when your calorie intake keeps exceeding the calories burned.

Here are some of the key causes which are known to be the driving factors for obesity.

If your diet tends to be rich in fat and contains massive calorie intake, you are all set to suffer from obesity.

Sedentary Lifestyle:

With most people sticking to their desk jobs and living a sedentary lifestyle, the body tends to get obese easily.

Of course, the genetic framework has a lot to do with obesity. If your parents are obese, the chance of you being obese is quite high.

The weight which women gain during their pregnancy can be very hard to shed and this is often one of the top causes of obesity.

Sleep Cycle:

If you are not getting an adequate amount of sleep, it can have an impact on the hormones which might trigger hunger signals. Overall, these linked events tend to make you obese.

Hormonal Disorder:

There are several hormonal changes which are known to be direct causes of obesity. The imbalance of the thyroid stimulating hormone, for instance, is one of the key factors when it comes to obesity.

Now that we know the key causes, let us look at the possible ways by which you can handle it.

Treatment for Obesity:

As strange as it may sound, the treatment for obesity is really simple. All you need to do is follow the right diet and back it with an adequate amount of exercise. If you can succeed in doing so, it will give you the perfect head-start into your journey of getting in shape and bidding goodbye to obesity.

There are a lot of different kinds and styles of diet plans for obesity which are available. You can choose the one which you deem fit. We recommend not opting for crash dieting as it is known to have several repercussions and can make your body terribly weak.

The key here is to stick to a balanced diet which can help you retain the essential nutrients, minerals, and, vitamins and shed the unwanted fat and carbs.

Just like the diet, there are several workout plans for obesity which are available. It is upon you to find out which of the workout plan seems to be apt for you. Choose cardio exercises and dance routines like Zumba to shed the unwanted body weight. Yoga is yet another method to get rid of obesity.

So, follow a blend of these and you will be able to deal with the trouble of obesity in no time. We believe that following these tips will help you get rid of obesity and stay in shape.

Obesity and overweight is a top health concern in the world due to the impact it has on the lives of individuals. Obesity is defined as a condition in which an individual has excessive body fat and is measured using the body mass index (BMI) such that, when an individual’s BMI is above 30, he or she is termed obese. The BMI is calculated using body weight and height and it is different for all individuals.

Obesity has been determined as a risk factor for many diseases. It results from dietary habits, genetics, and lifestyle habits including physical inactivity. Obesity can be prevented so that individuals do not end up having serious complications and health problems. Chronic illnesses like diabetes, heart diseases and relate to obesity in terms of causes and complications.

Factors Influencing Obesity:

Obesity is not only as a result of lifestyle habits as most people put it. There are other important factors that influence obesity. Genetics is one of those factors. A person could be born with genes that predispose them to obesity and they will also have difficulty in losing weight because it is an inborn factor.

The environment also influences obesity because the diet is similar in certain environs. In certain environments, like school, the food available is fast foods and the chances of getting healthy foods is very low, leading to obesity. Also, physical inactivity is an environmental factor for obesity because some places have no fields or tracks where people can jog or maybe the place is very unsafe and people rarely go out to exercise.

Mental health affects the eating habits of individuals. There is a habit of stress eating when a person is depressed and it could result in overweight or obesity if the person remains unhealthy for long period of time.

The overall health of individuals also matter. If a person is unwell and is prescribed with steroids, they may end up being obese. Steroidal medications enable weight gain as a side effect.

Complications of Obesity:

Obesity is a health concern because its complications are severe. Significant social and health problems are experienced by obese people. Socially, they will be bullied and their self-esteem will be low as they will perceive themselves as unworthy.

Chronic illnesses like diabetes results from obesity. Diabetes type 2 has been directly linked to obesity. This condition involves the increased blood sugars in the body and body cells are not responding to insulin as they should. The insulin in the body could also be inadequate due to decreased production. High blood sugar concentrations result in symptoms like frequent hunger, thirst and urination. The symptoms of complicated stages of diabetes type 2 include loss of vision, renal failure and heart failure and eventually death. The importance of having a normal BMI is the ability of the body to control blood sugars.

Another complication is the heightened blood pressures. Obesity has been defined as excessive body fat. The body fat accumulates in blood vessels making them narrow. Narrow blood vessels cause the blood pressures to rise. Increased blood pressure causes the heart to start failing in its physiological functions. Heart failure is the end result in this condition of increased blood pressures.

There is a significant increase in cholesterol in blood of people who are obese. High blood cholesterol levels causes the deposition of fats in various parts of the body and organs. Deposition of fats in the heart and blood vessels result in heart diseases. There are other conditions that result from hypercholesterolemia.

Other chronic illnesses like cancer can also arise from obesity because inflammation of body cells and tissues occurs in order to store fats in obese people. This could result in abnormal growths and alteration of cell morphology. The abnormal growths could be cancerous.

Management of Obesity:

For the people at risk of developing obesity, prevention methods can be implemented. Prevention included a healthy diet and physical activity. The diet and physical activity patterns should be regular and realizable to avoid strains that could result in complications.

Some risk factors for obesity are non-modifiable for example genetics. When a person in genetically predisposed, the lifestyle modifications may be have help.

For the individuals who are already obese, they can work on weight reduction through healthy diets and physical exercises.

In conclusion, obesity is indeed a major health concern because the health complications are very serious. Factors influencing obesity are both modifiable and non-modifiable. The management of obesity revolves around diet and physical activity and so it is important to remain fit.

In olden days, obesity used to affect only adults. However, in the present time, obesity has become a worldwide problem that hits the kids as well. Let’s find out the most prevalent causes of obesity.

Factors Causing Obesity:

Obesity can be due to genetic factors. If a person’s family has a history of obesity, chances are high that he/ she would also be affected by obesity, sooner or later in life.

The second reason is having a poor lifestyle. Now, there are a variety of factors that fall under the category of poor lifestyle. An excessive diet, i.e., eating more than you need is a definite way to attain the stage of obesity. Needless to say, the extra calories are changed into fat and cause obesity.

Junk foods, fried foods, refined foods with high fats and sugar are also responsible for causing obesity in both adults and kids. Lack of physical activity prevents the burning of extra calories, again, leading us all to the path of obesity.

But sometimes, there may also be some indirect causes of obesity. The secondary reasons could be related to our mental and psychological health. Depression, anxiety, stress, and emotional troubles are well-known factors of obesity.

Physical ailments such as hypothyroidism, ovarian cysts, and diabetes often complicate the physical condition and play a massive role in abnormal weight gain.

Moreover, certain medications, such as steroids, antidepressants, and contraceptive pills, have been seen interfering with the metabolic activities of the body. As a result, the long-term use of such drugs can cause obesity. Adding to that, regular consumption of alcohol and smoking are also connected to the condition of obesity.

Harmful Effects of Obesity:

On the surface, obesity may look like a single problem. But, in reality, it is the mother of several major health issues. Obesity simply means excessive fat depositing into our body including the arteries. The drastic consequence of such high cholesterol levels shows up in the form of heart attacks and other life-threatening cardiac troubles.

The fat deposition also hampers the elasticity of the arteries. That means obesity can cause havoc in our body by altering the blood pressure to an abnormal range. And this is just the tip of the iceberg. Obesity is known to create an endless list of problems.

In extreme cases, this disorder gives birth to acute diseases like diabetes and cancer. The weight gain due to obesity puts a lot of pressure on the bones of the body, especially of the legs. This, in turn, makes our bones weak and disturbs their smooth movement. A person suffering from obesity also has higher chances of developing infertility issues and sleep troubles.

Many obese people are seen to be struggling with breathing problems too. In the chronic form, the condition can grow into asthma. The psychological effects of obesity are another serious topic. You can say that obesity and depression form a loop. The more a person is obese, the worse is his/ her depression stage.

How to Control and Treat Obesity:

The simplest and most effective way, to begin with, is changing our diet. There are two factors to consider in the diet plan. First is what and what not to eat. Second is how much to eat.

If you really want to get rid of obesity, include more and more green vegetables in your diet. Spinach, beans, kale, broccoli, cauliflower, asparagus, etc., have enough vitamins and minerals and quite low calories. Other healthier options are mushrooms, pumpkin, beetroots, and sweet potatoes, etc.

Opt for fresh fruits, especially citrus fruits, and berries. Oranges, grapes, pomegranate, pineapple, cherries, strawberries, lime, and cranberries are good for the body. They have low sugar content and are also helpful in strengthening our immune system. Eating the whole fruits is a more preferable way in comparison to gulping the fruit juices. Fruits, when eaten whole, have more fibers and less sugar.

Consuming a big bowl of salad is also great for dealing with the obesity problem. A salad that includes fibrous foods such as carrots, radish, lettuce, tomatoes, works better at satiating the hunger pangs without the risk of weight gain.

A high protein diet of eggs, fish, lean meats, etc., is an excellent choice to get rid of obesity. Take enough of omega fatty acids. Remember to drink plenty of water. Keeping yourself hydrated is a smart way to avoid overeating. Water also helps in removing the toxins and excess fat from the body.

As much as possible, avoid fats, sugars, refined flours, and oily foods to keep the weight in control. Control your portion size. Replace the three heavy meals with small and frequent meals during the day. Snacking on sugarless smoothies, dry fruits, etc., is much recommended.

Regular exercise plays an indispensable role in tackling the obesity problem. Whenever possible, walk to the market, take stairs instead of a lift. Physical activity can be in any other form. It could be a favorite hobby like swimming, cycling, lawn tennis, or light jogging.

Meditation and yoga are quite powerful practices to drive away the stress, depression and thus, obesity. But in more serious cases, meeting a physician is the most appropriate strategy. Sometimes, the right medicines and surgical procedures are necessary to control the health condition.

Obesity is spreading like an epidemic, haunting both the adults and the kids. Although genetic factors and other physical ailments play a role, the problem is mostly caused by a reckless lifestyle.

By changing our way of living, we can surely take control of our health. In other words, it would be possible to eliminate the condition of obesity from our lives completely by leading a healthy lifestyle.

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Obesity in Teens

What is obesity in teens?

Obesity is when a teen has too much body fat. Obesity is a serious, long-term disease.

What causes obesity in a teen?

In many ways, childhood obesity is a puzzling disease. Doctors do not fully understand how the body controls weight and body fat. On one hand, the cause seems simple. If a person takes in more calories than he or she uses for energy, then he or she will gain weight.

But a teen's obesity can be caused by a combination of things. It can be linked to:

• Socioeconomic issues
• How the body turns food into energy (metabolism)
• Not getting enough sleep
• Lifestyle choices

Some endocrine disorders, diseases, and medicines may also have a strong effect on a child’s weight.

Which teens are at risk for obesity?

Things that may put your teen at risk for obesity are:

• Genes. Obesity may be passed down through families. Having even one obese parent may raise a child’s risk for it. Experts are looking at the link between genes, the ever-changing environment, and obesity.
• Metabolism. Each person’s body uses energy differently. Metabolism and hormones don’t affect everyone the same way. They may play a role in weight gain in children and teens.
• Socioeconomic factors. There is a strong tie between economic status and obesity. Obesity is more common among low-income people. In some places, people may have limited access to affordable healthy foods. Or they may not have a safe place to exercise.
• Lifestyle choices. Overeating and an inactive lifestyle both contribute to obesity. A diet full of sugary, high-fat, and refined foods can lead to weight gain. So can a lack of regular exercise. In children, watching TV and sitting at a computer can play a part.

What are the symptoms of obesity in a teen?

Too much body fat is the main symptom of obesity. But it’s hard to directly measure body fat. A guideline called the body mass index (BMI) is used to estimate it. The BMI uses a teen’s weight and height to come up with a result. The result is then compared with standards for children of the same gender between the ages of 2 and 20.

A teen who is overweight has a BMI between the 85th and 95th percentile for age and gender. He or she is obese if the BMI is greater than the 95th percentile for age and gender.

How is obesity diagnosed in a teen?

Obesity is diagnosed by a healthcare provider. BMI is often used to define obesity in teens. It has 2 categories:

• BMIs at the 95th percentile or more for age and gender, or BMIs of more than 30, whichever is smaller. BMI findings in this category mean the child should have a full health checkup.
• Family history of cardiovascular disease, high cholesterol, diabetes, and obesity
• High blood pressure
• Total cholesterol level
• Large gains in BMI from year to year
• Concerns about weight, including the child’s own concerns about being overweight

How is obesity treated in a teen?

Treatment depends on your teen’s symptoms, age, and health. It also depends on how severe the condition is.

Treatment for obesity may include:

• Diet counseling
• Changes to diet and amount of calories eaten
• More physical activity or an exercise program
• Behavior changes
• Individual or group therapy that focuses on changing behaviors and facing feelings linked to weight and normal developmental issues
• Support and encouragement for making changes and following recommended treatments

Treatment often involves the help of a nutritionist, mental health professionals, and an exercise specialist. Your teen’s treatment goals should be realistic. They should focus on a modest cutting back of calories, changing eating habits, and adding more physical activity.

What are possible complications of obesity in a teen?

Obesity can affect your teen’s health in a number of ways. These include:

• High blood pressure and high cholesterol. These are risk factors for heart disease.
• Diabetes. Obesity is the major cause of type 2 diabetes. It can cause resistance to insulin, the hormone that controls blood sugar. When obesity causes insulin resistance, blood sugar becomes higher than normal.
• Joint problems, such as osteoarthritis. Obesity can affect the knees and hips because of the stress placed on the joints by extra weight.
• Sleep apnea and breathing problems. Sleep apnea causes people to stop breathing for brief periods. It interrupts sleep throughout the night and causes sleepiness during the day. It also causes heavy snoring. The risk for other breathing problems such as asthma is higher in an obese child.
• Psychosocial effects. Modern culture often sees overly thin people as the ideal in body size. Because of this, people who are overweight or obese often suffer disadvantages. They may be blamed for their condition. They may be seen as lazy or weak-willed. Obese children can have low self-esteem that affects their social life and emotional health.

What can I do to help prevent obesity in a teen?

Young people often become overweight or obese because they have poor eating habits and aren’t active enough. Genes also play a role.

Here are some tips to help your teen stay at a healthy weight:

• Focus on the whole family.  Slowly work to change your family’s eating habits and activity levels. Don’t focus on a child’s weight.
• Be a role model. Parents who eat healthy foods and are physically active set an example. Their child is more likely to do the same.
• Encourage physical activity. Children should get at least 60 minutes of physical activity each day.
• Limit screen time. Cut your teen’s screen time to less than 2 hours a day in front of the TV and computer.
• Have healthy snacks on hand. Keep the refrigerator stocked with fat-free or low-fat milk instead of soft drinks. Offer fresh fruit and vegetables instead of snacks high in sugar and fat.
• Aim for 5 or more. Serve at least 5 servings of fruits and vegetables each day.
• Drink more water. Encourage teens to have water instead of drinks with added sugar. Limit your child’s intake of soft drinks, sports drinks, and fruit juice drinks.
• Get enough sleep. Encourage teens to get more sleep every night. Earlier bedtimes have been found to decrease rates of obesity.

Key points about obesity in teens

• Obesity is a long-term disease. It’s when a teen has too much body fat.
• Many things can lead to childhood obesity. These include genes and lifestyle choices.
• Body mass index (BMI) is used to diagnose obesity. It’s based on a child’s weight and height.
• Treatment may include diet counseling, exercise, therapy, and support.
• Obesity can lead to many other health problems. Some of these are heart disease, type 2 diabetes, and joint problems.
• Obesity can be prevented with healthy lifestyle choices like being more physically active and eating more fruits and vegetables.

Tips to help you get the most from a visit to your child’s healthcare provider:

• Know the reason for the visit and what you want to happen.
• Before your visit, write down questions you want answered.
• At the visit, write down the name of a new diagnosis, and any new medicines, treatments, or tests. Also write down any new instructions your provider gives you for your child.
• Know why a new medicine or treatment is prescribed and how it will help your child. Also know what the side effects are.
• Ask if your child’s condition can be treated in other ways.
• Know why a test or procedure is recommended and what the results could mean.
• Know what to expect if your child does not take the medicine or have the test or procedure.
• If your child has a follow-up appointment, write down the date, time, and purpose for that visit.
• Know how you can contact your child’s provider after office hours. This is important if your child becomes ill and you have questions or need advice.

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• Published: 18 May 2023

Child and adolescent obesity

• Natalie B. Lister   ORCID: orcid.org/0000-0002-9148-8632 1 , 2 ,
• Louise A. Baur   ORCID: orcid.org/0000-0002-4521-9482 1 , 3 , 4 ,
• Janine F. Felix 5 , 6 ,
• Andrew J. Hill   ORCID: orcid.org/0000-0003-3192-0427 7 ,
• Claude Marcus   ORCID: orcid.org/0000-0003-0890-2650 8 ,
• Thomas Reinehr   ORCID: orcid.org/0000-0002-4351-1834 9 ,
• Carolyn Summerbell 10 &
• Martin Wabitsch   ORCID: orcid.org/0000-0001-6795-8430 11  

Nature Reviews Disease Primers volume  9 , Article number:  24 ( 2023 ) Cite this article

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The prevalence of child and adolescent obesity has plateaued at high levels in most high-income countries and is increasing in many low-income and middle-income countries. Obesity arises when a mix of genetic and epigenetic factors, behavioural risk patterns and broader environmental and sociocultural influences affect the two body weight regulation systems: energy homeostasis, including leptin and gastrointestinal tract signals, operating predominantly at an unconscious level, and cognitive–emotional control that is regulated by higher brain centres, operating at a conscious level. Health-related quality of life is reduced in those with obesity. Comorbidities of obesity, including type 2 diabetes mellitus, fatty liver disease and depression, are more likely in adolescents and in those with severe obesity. Treatment incorporates a respectful, stigma-free and family-based approach involving multiple components, and addresses dietary, physical activity, sedentary and sleep behaviours. In adolescents in particular, adjunctive therapies can be valuable, such as more intensive dietary therapies, pharmacotherapy and bariatric surgery. Prevention of obesity requires a whole-system approach and joined-up policy initiatives across government departments. Development and implementation of interventions to prevent paediatric obesity in children should focus on interventions that are feasible, effective and likely to reduce gaps in health inequalities.

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Introduction

The prevalence of child and adolescent obesity remains high and continues to rise in low-income and middle-income countries (LMICs) at a time when these regions are also contending with under-nutrition in its various forms 1 , 2 . In addition, during the COVID-19 pandemic, children and adolescents with obesity have been more likely to have severe COVID-19 requiring hospitalization and mechanical ventilation 3 . At the same time, the pandemic was associated with rising levels of childhood obesity in many countries. These developments are concerning, considering that recognition is also growing that paediatric obesity is associated with a range of immediate and long-term negative health outcomes, a decreased quality of life 4 , 5 , an increased presentation to health services 6 and increased economic costs to individuals and society 7 .

Body weight is regulated by a range of energy homeostatic and cognitive–emotional processes and a multifactorial interplay of complex regulatory circuits 8 . Paediatric obesity arises when multiple environmental factors — covering preconception and prenatal exposures, as well as broader changes in the food and physical activity environments — disturb these regulatory processes; these influences are now widespread in most countries 9 .

The treatment of obesity includes management of obesity-associated complications, a developmentally sensitive approach, family engagement, and support for long-term behaviour changes in diet, physical activity, sedentary behaviours and sleep 10 . New evidence highlights the role, in adolescents with more severe obesity, of bariatric surgery 11 and pharmacotherapy, particularly the potential for glucagon-like peptide 1 (GLP1) receptor agonists 12 .

Obesity prevention requires a whole-system approach, with policies across all government and community sectors systematically taking health into account, avoiding harmful health impacts and decreasing inequity. Programmatic prevention interventions operating ‘downstream’ at the level of the child and family, as well as ‘upstream’ interventions at the level of the community and broader society, are required if a step change in tackling childhood obesity is to be realized 13 , 14 .

In this Primer, we provide an overview of the epidemiology, causes, pathophysiology and consequences of child and adolescent obesity. We discuss diagnostic considerations, as well as approaches to its prevention and management. Furthermore, we summarize effects of paediatric obesity on quality of life, and open research questions.

Epidemiology

Definition and prevalence.

The World Health Organization (WHO) defines obesity as “abnormal or excessive fat accumulation that presents a risk to health” 15 . Paediatric obesity is defined epidemiologically using BMI, which is adjusted for age and sex because of the physiological changes in BMI during growth 16 . Global prevalence of paediatric obesity has risen markedly over the past four decades, initially in high-income countries (HICs), but now also in many LMICs 1 .

Despite attempts to standardize the epidemiological classification, several definitions of paediatric obesity are in use; hence, care is needed when comparing prevalence rates. The 2006 WHO Child Growth Standard, for children aged 0 to 5 years, is based on longitudinal observations of multiethnic populations of children with optimal infant feeding and child-rearing conditions 17 . The 2007 WHO Growth Reference is used for the age group 5–19 years 18 , and the 2000 US Centers for Disease Control and Prevention (CDC) Growth Charts for the age group 2–20 years 19 . The WHO and CDC definitions based on BMI-for-age charts are widely used, including in clinical practice. By contrast, the International Obesity Task Force (IOTF) definition, developed from nationally representative BMI data for the age group 2–18 years from six countries, is used exclusively for epidemiological studies 20 .

For the age group 5–19 years, between 1975 and 2016, the global prevalence of obesity (BMI >2 standard deviations (SD) above the median of the WHO growth reference) increased around eightfold to 5.6% in girls and 7.8% in boys 1 . Rates have plateaued at high levels in many HICs but have accelerated in other regions, particularly in parts of Asia. For the age group 2–4 years, between 1980 and 2015, obesity prevalence (IOTF definition, equivalent to an adult BMI of ≥30 kg/m 2 ) increased from 3.9% to 7.2% in boys and from 3.7% to 6.4% in girls 21 . Obesity prevalence is highest in Polynesia and Micronesia, the Middle East and North Africa, the Caribbean and the USA (Fig.  1 ). Variations in prevalence probably reflect different background levels of obesogenic environments, or the sum total of the physical, economic, policy, social and cultural factors that promote obesity 22 . Obesogenic environments include those with decreased active transport options, a ubiquity of food marketing directed towards children, and reduced costs and increased availability of nutrient-poor, energy-dense foods. Particularly in LMICs, the growth of urbanization, new forms of technology and global trade have led to reduced physical activity at work and leisure, a shift towards Western diets, and the expansion of transnational food and beverage companies to shape local food systems 23 .

Maps showing the proportions of children and adolescents living with overweight or obesity (part  a , boys; part b , girls) according to latest available data from the Global Obesity Observatory . Data might not be comparable between countries owing to differences in survey methodology.

The reasons for varying sex differences in prevalence in different countries are unclear but may relate to cultural variations in parental feeding practices for boys and girls and societal ideals of body size 24 . In 2016, obesity in the age group 5–19 years was more prevalent in girls than in boys in sub-Saharan Africa, Oceania and some middle-income countries in other regions, whereas it was more prevalent in boys than in girls in all HICs, and in East and South-East Asia 21 . Ethnic and racial differences in obesity prevalence within countries are often assumed to mirror variations in social deprivation and other social determinants of obesity. However, an independent effect of ethnicity even after adjustment for socioeconomic status has been documented in the UK, with Black and Asian boys in primary school having higher prevalence of obesity than white boys 25 .

Among individuals with obesity, very high BMI values have become more common in the past 15 years. The prevalence of severe obesity (BMI ≥120% of the 95th percentile (CDC definition), or ≥35 kg/m 2 at any age 26 , 27 ) has increased in many HICs, accounting for one-quarter to one-third of those with obesity 28 , 29 . Future health risks of paediatric obesity in adulthood are well documented. For example, in a data linkage prospective study in Israel with 2.3 million participants who had BMI measured at age 17 years, those with obesity (≥95th percentile BMI for age) had a much higher risk of death from coronary heart disease (HR 4.9, 95% CI 3.9–6.1), stroke (HR 2.6, 95% CI 1.7–4.1) and sudden death (HR 2.1, 95% CI 1.5–2.9) compared with those whose BMI fell between the 5th and 24th percentiles 30 .

Causes and risk factors

Early life is a critical period for childhood obesity development 9 , 31 , 32 , 33 . According to the Developmental Origins of Health and Disease framework, the early life environment may affect organ structure and function and influence health in later life 34 , 35 . Meta-analyses have shown that preconception and prenatal environmental exposures, including high maternal pre-pregnancy BMI and, to a lesser extent, gestational weight gain, as well as gestational diabetes and maternal smoking, are associated with childhood obesity, potentially through effects on the in utero environment 33 , 36 , 37 , 38 . Paternal obesity is also associated with childhood obesity 33 . Birthweight, reflecting fetal growth, is a proxy for in utero exposures. Both low and high birthweights are associated with later adiposity, with high birthweight linked to increased BMI and low birthweight to central obesity 33 , 39 .

Growth trajectories in early life are important determinants of later adiposity. Rapid weight gain in early childhood is associated with obesity in adolescence 32 . Also, later age and higher BMI at adiposity peak (the usual peak in BMI around 9 months of age), as well as earlier age at adiposity rebound (the lowest BMI reached between 4 and 7 years of age), are associated with increased adolescent and adult BMI 40 , 41 . Specific early life nutritional factors, including a lower protein content in formula food, are consistently associated with a lower risk of childhood obesity 42 , 43 . These also include longer breastfeeding duration, which is generally associated with a lower risk of childhood obesity 42 . However, some controversy exists, as these effects are affected by multiple sociodemographic confounding factors and their underlying mechanisms remain uncertain 44 . Some studies comparing higher and lower infant formula protein content have reported that the higher protein group have a greater risk of subsequent obesity, especially in early childhood 41 , 42 ; however, one study with a follow-up period until age 11 years found no significant difference in the risk of obesity, but an increased risk of overweight in the high protein group was still observed 42 , 43 , 45 . A high intake of sugar-sweetened beverages is associated with childhood obesity 33 , 46 .

Many other behavioural factors are associated with an increased risk of childhood obesity, including increased screen time, short sleep duration and poor sleep quality 33 , 47 , reductions in physical activity 48 and increased intake of energy-dense micronutrient-poor foods 49 . These have been influenced by multiple changes in the past few decades in the broader social, economic, political and physical environments, including the widespread marketing of food and beverages to children, the loss of walkable green spaces in many urban environments, the rise in motorized transport, rapid changes in the use of technology, and the move away from traditional foods to ultraprocessed foods.

Obesity prevalence is inextricably linked to relative social inequality, with data suggesting a shift in prevalence over time towards those living with socioeconomic disadvantage, and thus contributes to social inequalities. In HICs, being in lower social strata is associated with a higher risk of obesity, even in infants and young children 50 , whereas the opposite relationship occurs in middle-income countries 51 . In low-income countries, the relationship is variable, and the obesity burden seems to be across socioeconomic groups 52 , 53 .

Overall, many environmental, lifestyle, behavioural and social factors in early life are associated with childhood obesity. These factors cannot be seen in isolation but are part of a complex interplay of exposures that jointly contribute to increased obesity risk. In addition to multiple prenatal and postnatal environmental factors, genetic variants also have a role in the development of childhood obesity (see section Mechanisms/pathophysiology).

Comorbidities and complications

Childhood obesity is associated with a wide range of short-term comorbidities (Fig.  2 ). In addition, childhood obesity tracks into adolescence and adulthood and is associated with complications across the life course 32 , 41 , 54 , 55 .

Obesity in children and adolescents can be accompanied by various other pathologies. In addition, childhood obesity is associated with complications and disorders that manifest in adulthood (red box).

Increased BMI, especially in adolescence, is linked to a higher risk of many health outcomes, including metabolic disorders, such as raised fasting glucose, impaired glucose tolerance, type 2 diabetes mellitus (T2DM), metabolic syndrome and fatty liver disease 56 , 57 , 58 , 59 . Other well-recognized obesity-associated complications include coronary heart disease, asthma, obstructive sleep apnoea syndrome (itself associated with metabolic dysfunction and inflammation) 60 , orthopaedic complications and a range of mental health outcomes including depression and low self-esteem 27 , 55 , 57 , 61 , 62 , 63 .

A 2019 systematic review showed that children and adolescents with obesity are 1.4 times more likely to have prediabetes, 1.7 times more likely to have asthma, 4.4 times more likely to have high blood pressure and 26.1 times more likely to have fatty liver disease than those with a healthy weight 64 . In 2016, it was estimated that, at a global level by 2025, childhood obesity would lead to 12 million children aged 5–17 years with glucose intolerance, 4 million with T2DM, 27 million with hypertension and 38 million with fatty liver disease 65 . These high prevalence rates have implications for both paediatric and adult health services.

Mechanisms/pathophysiology

Body weight regulation.

Body weight is regulated within narrow limits by homeostatic and cognitive–emotional processes and a multifactorial interplay of hormones and messenger substances in complex regulatory circuits (Fig.  3 ). When these regulatory circuits are disturbed, an imbalance between energy intake and expenditure leads to obesity or to poor weight gain. As weight loss is much harder to achieve than weight gain in the long term due to the regulation circuits discussed below, the development of obesity is encouraged by modern living conditions, which enable underlying predispositions for obesity to become manifest 8 , 66 .

Body weight is predominantly regulated by two systems: energy homeostasis and cognitive–emotional control. Both homeostatic and non-homeostatic signals are processed in the brain, involving multiple hormone and receptor cascades 217 , 218 , 219 . This overview depicts the best-known regulatory pathways. The homeostatic system, which is mainly regulated by brain centres in the hypothalamus and brainstem, operates on an unconscious level. Both long-term signals from the energy store in adipose tissue (for example, leptin) and short-term hunger and satiety signals from the gastrointestinal tract signal the current nutrient status. During gastric distension or after the release of gastrointestinal hormones (multiple receptors are involved) and insulin, a temporary feeling of fullness is induced. The non-homeostatic or hedonic system is regulated by higher-level brain centres and operates at the conscious level. After integration in the thalamus, homeostatic signals are combined with stimuli from the environment, experiences and emotions; emotional and cognitive impulses are then induced to control food intake. Regulation of energy homeostasis in the hypothalamus involves two neuron types of the arcuate nucleus: neurons producing neuropeptide Y (NPY) and agouti-related peptide (AgRP) and neurons producing pro-opiomelanocortin (POMC). Leptin stimulates these neurons via specific leptin receptors (LEPR) inducing anabolic effects in case of decreasing leptin levels and catabolic effects in case of increasing leptin levels. Leptin inhibits the production of NPY and AgRP, whereas low leptin levels stimulate AgRP and NPY production resulting in the feeling of hunger. Leptin directly stimulates POMC production in POMC neurons. POMC is cleaved into different hormone polypeptides including α-melanocyte-stimulating hormone which in turn activates melanocortin 4 receptors (MC4R) of cells in the nucleus paraventricularis of the hypothalamus, leading to the feeling of satiety. CART, cocaine and amphetamine responsive transcript; IR, insulin receptor.

In principle, there are two main systems in the brain which regulate body weight 8 , 66 (Fig.  3 ): energy homeostasis and cognitive–emotional control. Energy homeostasis is predominantly regulated by brain centres in the hypothalamus and brainstem and operates at an unconscious level. Both long-term signals from the adipose tissue energy stores and short-term hunger and satiety signals from the gastrointestinal tract signal the current nutrient status 8 , 66 . For example, negative energy balance leading to reduced fat mass results in reduced leptin levels, a permanently reduced urge to exercise and an increased feeling of hunger. During gastric distension or after the release of gastrointestinal hormones and insulin, a temporary feeling of fullness is induced 8 , 66 . Cognitive–emotional control is regulated by higher brain centres and operates at a conscious level. Here, the homeostatic signals are combined with stimuli from the environment (sight, smell and taste of food), experiences and emotions 8 , 66 . Disorders at the level of cognitive–emotional control mechanisms include emotional eating as well as eating disorders. For example, the reward areas in the brain of people with overweight are more strongly activated by high-calorie foods than those in the brain of people with normal weight 67 . Both systems interact with each other, and the cognitive–emotional system is strongly influenced by the homeostatic control circuits.

Disturbances in the regulatory circuits of energy homeostasis can be genetically determined, can result from disease or injury to the regulatory centres involved, or can be caused by prenatal programming 8 , 66 . If the target value of body weight has been shifted, the organism tries by all means (hunger, drive) to reach the desired higher weight. These disturbed signals of the homeostatic system can have an imperative, irresistible character, so that a conscious influence on food intake is no longer effectively possible 8 , 66 . The most important disturbances of energy homeostasis are listed in Table  1 .

The leptin pathway

The peptide hormone leptin is primarily produced by fat cells. Its production depends on the amount of adipose tissue and the energy balance. A negative energy balance during fasting results in a reduction of circulating leptin levels by 50% after 24 h (ref. 68 ). In a state of weight loss, leptin production is reduced 69 . In the brain, leptin stimulates two neuron types of the arcuate nucleus in the hypothalamus via specific leptin receptors: neurons producing neuropeptide Y (NPY) and agouti-related peptide (AgRP) and neurons producing pro-opiomelanocortin (POMC). High leptin levels inhibit the production of NPY and AgRP, whereas low leptin levels stimulate AgRP and NPY production. By contrast, leptin directly stimulates POMC production in POMC neurons (Fig.  3 ). POMC is a hormone precursor that is cleaved into different hormone polypeptides by specific enzymes, such as prohormone convertase 1 (PCSK1). This releases α-melanocyte-stimulating hormone (α-MSH) which in turn activates melanocortin 4 receptors (MC4R) of cells in the nucleus paraventricularis of the hypothalamus, leading to the feeling of satiety. Rare, functionally relevant mutations in the genes for leptin and leptin receptor, POMC , PCSK1/3 or MC4R lead to extreme obesity in early childhood. These forms of obesity are potential indications for specific pharmacological treatments, for example setmelanotide 70 , 71 . MC4R mutations are the most common cause of monogenic obesity, as heterozygous mutations can be symptomatic depending on the functional impairment and with variable penetrance and expression. Other genes have been identified, in which rare heterozygous pathological variants are also associated with early onset obesity (Table  1 ).

Pathological changes in adipose tissue

Adipose tissue can be classified into two types, white and brown adipose tissue. White adipose tissue comprises unilocular fat cells and brown adipose tissue contains multilocular fat cells, which are rich in mitochondria 72 . A third type of adipocyte, beige adipocytes, within the white adipose tissue are induced by prolonged exposure to cold or adrenergic signalling, and show a brown adipocyte-like morphology 72 . White adipose tissue has a large potential to change its volume to store energy and meet the metabolic demands of the body. The storage capacity and metabolic function of adipose tissue depend on the anatomical location of the adipose tissue depot. Predominant enlargement of white adipose tissue in the visceral, intra-abdominal area (central obesity) is associated with insulin resistance and an increased risk of metabolic disease development before puberty. Accumulation of adipose tissue in the hips and flanks has no adverse effect and may be protective against metabolic syndrome. In those with obesity, adipose tissue is characterized by an increased number of adipocytes (hyperplasia), which originate from tissue-resident mesenchymal stem cells, and by enlarged adipocytes (hypertrophy) 73 . Adipocytes with a very large diameter reach the limit of the maximal oxygen diffusion distance, resulting in hypoxia, the development of an inflammatory expression profile (characterized by, for example, leptin, TNF and IL-6) and adipocyte necrosis, triggering the recruitment of leukocytes. Resident macrophages switch from the anti-inflammatory M2 phenotype to a pro-inflammatory M1 phenotype, which is associated with insulin resistance, further promoting local sterile inflammation and the development of fibrotic adipose tissue. This process limits the expandability of the adipose tissue for further storage of triglycerides. In the patient, the increase in fat mass in obesity is associated with insulin resistance and systemic low-grade inflammation characterized by elevated serum levels of C-reactive protein and pro-inflammatory cytokines. The limitation of adipose tissue expandability results in storage of triglycerides in other organs, such as the liver, muscle and pancreas 74 .

Genetics and epigenetics in the general population

Twin studies have found heritability estimates for BMI of up to 70% 75 , 76 . In contrast to rare monogenic forms of obesity, which are often caused by a single genetic defect with a large effect, the genetic background of childhood obesity in the general population is shaped by the joint effects of many common genetic variants, each of which individually makes a small contribution to the phenotype. For adult BMI, genome-wide association studies, which examine associations of millions of such variants across the genome at the same time, have identified around 1,000 genetic loci 77 . The largest genome-wide association studies in children, which include much smaller sample sizes of up to 60,000 children, have identified 25 genetic loci for childhood BMI and 18 for childhood obesity, the majority of which overlap 78 , 79 . There is also a clear overlap with genetic loci identified in adults, for example for FTO , MC4R and TMEM18 , but this overlap is not complete, some loci are specific to early life BMI, or have a relatively larger contribution in childhood 78 , 79 , 80 . These findings suggest that biological mechanisms underlying obesity in childhood are mostly similar to those in adulthood, but the relative influence of these mechanisms may differ at different phases of life.

The role of epigenetic processes in childhood and adolescent obesity has gained increasing attention. In children, several studies found associations between DNA methylation and BMI 81 , 82 , 83 , 84 , but a meta-analysis including data from >4,000 children identified only minimal associations 85 . Most studies support the hypothesis that DNA methylation changes are predominantly a consequence rather than a cause of obesity, which may explain the lower number of identified (up to 12) associations in children, in whom duration of exposure to a higher BMI is shorter than in adults, in whom associations with DNA methylation at hundreds of sites have been identified 85 , 86 , 87 . In addition to DNA methylation, some specific circulating microRNAs have been found to be associated with obesity in childhood 84 .

The field of epigenetic studies in childhood obesity is relatively young and evolving quickly. Future studies will need to focus on defining robust associations in blood as well as other tissues and on identifying cause-and-effect relationships. In addition, other omics, such as metabolomics and proteomics, are promising areas that may contribute to an improved aetiological understanding or may provide biological signatures that can be used as predictive or prognostic markers of childhood obesity and its comorbidities.

Parental obesity and childhood obesity

There is an established link between increased parental BMI and increased childhood BMI 88 , 89 . This link may be due to shared genetics, shared environment, a direct intrauterine effect of maternal BMI or a combination of these factors. In the case of shared genetics, the child inherits BMI-increasing genetic variants from one or both parents. Shared environmental factors, such as diet or lifestyle, may also contribute to an increased BMI in both parents and child. In addition, maternal obesity might create an intrauterine environment that programmes metabolic processes in the fetus, which increases the risk of childhood obesity. Some studies show larger effects of maternal than paternal BMI, indicating a potential causal intrauterine mechanism of maternal obesity, but evidence showing similar maternal and paternal effects is increasing. The data may indicate that there is only a limited direct intrauterine effect of maternal obesity on childhood obesity; rather, genetic effects inherited from the mother or father, or both, and/or shared environmental factors may contribute to childhood obesity risk 90 , 91 , 92 , 93 , 94 , 95 .

Diagnosis, screening and prevention

Diagnostic work-up.

The extent of overweight in clinical practice is estimated using BMI based on national charts 96 , 97 , 98 , 99 , 100 . Of note, the clinical classification of overweight or obesity differ depending on the BMI charts used and national recommendations; hence, local guidelines should be referred to. For example, the US CDC Growth Charts and several others use the 85th and 95th centile cut-points to denote overweight and obesity, respectively 19 . The WHO Growth Reference for children aged 5–19 years defines cut-points for overweight and obesity as a BMI-for-age greater than +1 and +2 SDs for BMI for age, respectively 18 . For children <5 years of age, overweight and obesity are defined as weight-for-height greater than +2 and +3 SDs, respectively, above the WHO Child Growth Standards median 17 . The IOTF and many countries in Europe use cut-points of 85th, 90th and 97th to define overweight, obesity and extreme obesity 26 .

BMI as an indirect measurement of body fat has some limitations; for example, pronounced muscle tissue leads to an increase in BMI, and BMI is not independent of height. In addition, people of different ethnicities may have different cut-points for obesity risk; for example, cardiometabolic risk occurs at lower BMI values in individuals with south Asian than in those with European ancestry 101 . Thus, BMI is best seen as a convenient screening tool that is supplemented by clinical assessment and investigations.

Other measures of body fat may help differentiate between fat mass and other tissues. Some of these tools are prone to low reliability, such as body impedance analyses (high day-to-day variation and dependent on level of fluid consumption) or skinfold thickness (high inter-observer variation), or are more expensive or invasive, such as MRI, CT or dual-energy X-ray absorptiometry, than simpler measures of body composition or BMI assessment.

Primary diseases rarely cause obesity in children and adolescents (<2%) 102 . However, treatable diseases should be excluded in those with obesity. A suggested diagnostic work-up is summarized in Fig.  4 . Routine measurement of thyroid-stimulating hormone (TSH) is not recommended 96 . Moderately elevated TSH levels (usually <10 IU/l) are frequently observed in obesity and are a consequence, and not a cause, of obesity 103 . In a growing child with normal height velocity, a normal BMI at the age of 2 years and normal cognitive development, no further diagnostic steps are necessary to exclude primary diseases 96 , 104 .

Concerning findings from a detailed medical history and physical examination will lead to further examinations. In individuals with early onset, extreme obesity (before age 3 years) and signs of hyperphagia, serum leptin level should be measured to rule out the extremely rare condition of congenital leptin deficiency. In individuals with normal or high leptin levels, genetic testing is indicated to search for monogenetic obesity. In individuals with intellectual disability, a syndromic disease may be present. Signs of impaired growth velocity or the history of central nervous system trauma or surgery will result in deeper endocrine evaluation and/or brain MRI. BDNF , brain-derived neurotropic factor; FT4, free thyroxin; KSR2 , kinase suppressor of ras 2; MC4R , melanocortin 4 receptor; POMC , pro-opiomelanocortin; SH2B1 , Src-homology 2 (SH2) B adapter protein 1; SIM1 , single-minded homologue 1; TSH, thyroid-stimulating hormone.

Clinical findings which need no further examination include pseudogynaecomastia (adipose tissue mimicking breast development; differentiated from breast tissue by ultrasonography), striae (caused by rapid weight increase) and a hidden penis in suprapubic adipose tissue (differentiated from micropenis by measurement of stretched penis length while pressing down on the suprapubic adipose tissue) 96 , 105 . Girls with obesity tend to have an earlier puberty onset (usually at around 8–9 years of age) and boys with severe obesity may have a delayed puberty onset (usually at around 13–14 years of age) 106 . Thus, if pubertal onset is slightly premature in girls or slightly delayed in boys, no further endocrine assessment is necessary.

Assessment of obesity-associated comorbidities

A waist to height ratio of >0.5 is a simple tool to identify central obesity 107 , 108 . Screening for cardiometabolic risk factors and fatty liver disease is recommended, especially in adolescents, and in those with more severe obesity or central adiposity, a strong family history of T2DM or premature heart disease, or relevant clinical symptoms, such as high blood pressure or acanthosis nigricans 96 , 97 , 98 , 99 , 109 . Investigations generally include fasting glucose levels, lipid profile, liver function and glycated haemoglobin, and might include an oral glucose tolerance test, polysomnography, and additional endocrine tests for polycystic ovary syndrome 96 , 97 , 98 , 99 .

T2DM in children and adolescents often occurs in the presence of a strong family history and may not be related to obesity severity 110 . T2DM onset usually occurs during puberty, a physiological state associated with increased insulin resistance 111 and, therefore, screening for T2DM should be considered in children and adolescents with obesity and at least one risk factor (family history of T2DM or features of metabolic syndrome) starting at pubertal onset 112 . As maturity-onset diabetes of the young (MODY) type II and type III are more frequent than T2DM in children and adolescents in many ethnicities, genetic screening for MODY may be appropriate 112 . Furthermore, type 1 diabetes mellitus (T1DM) should be excluded by measurement of autoantibodies in any individual with suspected diabetes with obesity. The differentiation of T2DM from MODY and T1DM is important as the diabetes treatment approaches differ 112 .

Several comorbidities of obesity should be considered if specific symptoms occur 96 , 109 . For polycystic ovary syndrome in hirsute adolescent girls with oligomenorrhoea or amenorrhoea, moderately increased testosterone levels and decreased sex hormone binding globulin levels are typical laboratory findings 113 . Obstructive sleep apnoea can occur in those with more severe obesity and who snore, have daytime somnolence or witnessed apnoeas. Diagnosis is made by polysomnography 114 . Minor orthopaedic disorders, such as flat feet and genu valgum, are frequent in children and adolescents with obesity and may cause pain. Major orthopaedic complications include slipped capital femoral epiphyses (acute and chronic), which manifest with hip and knee pain in young adolescents and are characterized by reduced range of hip rotation and waddling gait; and Blount disease (tibia vara), typically occurring in children aged 2–5 years 105 , 115 . In addition, children and adolescents with extreme obesity frequently have increased dyspnoea and decreased exercise capacity. A heightened demand for ventilation, elevated work of breathing, respiratory muscle inefficiency and diminished respiratory compliance are caused by increased truncal fat mass. This may result in a decreased functional residual capacity and expiratory reserve volume, ventilation to perfusion ratio abnormalities and hypoxaemia, especially when supine. However, conventional respiratory function tests are only mildly affected by obesity except in extreme cases 116 . Furthermore, gallstones should be suspected in the context of abdominal pain after rapid weight loss, which can be readily diagnosed via abdominal ultrasonography 105 . Finally, pseudotumor cerebri may present with chronic headache, and depression may present with flat affect, chronic fatigue and sleep problems 105 .

Obesity in adolescents can also be associated with disordered eating, eating disorders and other psychological disorders 117 , 118 . If suspected, assessment by a mental health professional is recommended.

A comprehensive approach

The 2016 report of the WHO Commission on Ending Childhood Obesity stated that progress in tackling childhood obesity has been slow and inconsistent, with obesity prevention requiring a whole-of-government approach in which policies across all sectors systematically take health into account, avoiding harmful health impacts and, therefore, improving population health and health equity 13 , 119 . The focus in developing and implementing interventions to prevent obesity in children should be on interventions that are feasible, effective and likely to reduce health inequalities 14 . Importantly, the voices of children and adolescents living with social disadvantage and those from minority groups must be heard if such interventions are to be effective and reduce inequalities 120 .

Figure  5 presents a system for the prevention of childhood obesity within different domains of the socioecological model 121 and highlights opportunities for interventions. These domains can be described on a continuum, from (most downstream) individual and interpersonal (including parents, peers and wider family) through to organizational (including health care and schools), community (including food, activity and environment), society (including media and finally cultural norms) and (most upstream) public policy (from local to national level). Interventions to prevent childhood obesity can be classified on the Nuffield intervention ladder 122 . This framework was proposed by the Nuffield Council on Bioethics in 2007 (ref. 122 ) and distributes interventions on the ladder steps depending on the degree of agency required by the individual to make the behavioural changes that are the aim of the intervention. The bottom step of the ladder includes interventions that provide information, which requires the highest agency and relies on a child, adolescent and/or family choosing (and their ability to choose) to act on that information and change behaviour. The next steps of the ladder are interventions that enable choice, guide choice through changing the default policy, guide choice through incentives, guide choice through disincentives, or restrict choice. On the top-most step of the ladder (lowest agency required) are interventions that eliminate choice.

This schematic integrates interventions that were included in a Cochrane review 127 of 153 randomized controlled trials of interventions to prevent obesity in children and are high on the Nuffield intervention ladder 122 . The Nuffield intervention ladder distributes interventions depending on the degree of agency required for the behavioural changes that are the aim of the intervention. The socioecological model 121 comprises different domains (or levels) from the individual up to public policy. Interventions targeting the individual and interpersonal domains can be described as downstream interventions, and interventions within public policy can be described as the highest level of upstream interventions. Within each of these domains, arrow symbols with colours corresponding to the Nuffield intervention ladder category are used to show interventions that were both included in the Cochrane review 127 and that guide, restrict or eliminate choice as defined by the Nuffield intervention ladder 122 . Upstream interventions, and interventions on the top steps of the Nuffield ladder, are more likely to reduce inequalities. NGO, non-governmental organization.

Downstream and high-agency interventions (on the bottom steps of the Nuffield ladder) are more likely to result in intervention-generated inequalities 123 . This has been elegantly described and evidenced, with examples from the obesity prevention literature 124 , 125 . A particularly strong example is a systematic review of 38 interventions to promote healthy eating that showed that food price (an upstream and low-agency intervention) seemed to decrease inequalities, all interventions that combined taxes and subsidies consistently decreased inequalities, and downstream high-agency interventions, especially dietary counselling, seemed to increase inequalities 126 .

Effectiveness of prevention interventions

A 2019 Cochrane review of interventions to prevent obesity in children 127 included 153 randomized controlled trials (RCTs), mainly in HICs (12% were from middle-income countries). Of these RCTs, 56% tested interventions in children aged 6–12 years, 24% in children aged 0–5 years, and 20% in adolescents aged 13–18 years. The review showed that diet-only interventions to prevent obesity in children were generally ineffective across all ages. Interventions combining diet and physical activity resulted in modest benefits in children aged 0–12 years but not in adolescents. However, physical activity-only interventions to prevent obesity were effective in school-age children (aged 5–18 years). Whether the interventions were likely to work equitably in all children was investigated in 13 RCTs. These RCTs did not indicate that the strategies increased inequalities, although most of the 13 RCTs included relatively homogeneous groups of children from disadvantaged backgrounds.

The potential for negative unintended consequences of obesity prevention interventions has received much attention 128 . The Cochrane review 127 investigated whether children were harmed by any of the strategies; for example, by having injuries, losing too much weight or developing damaging views about themselves and their weight. Of the few RCTs that did monitor these outcomes, none found any harms in participants.

Intervention levels

Most interventions (58%) of RCTs in the Cochrane review aimed to change individual lifestyle factors via education-based approaches (that is, simply provide information) 129 . In relation to the socioecological model, only 11 RCTs were set in the food and physical activity environment domain, and child care, preschools and schools were the most common targets for interventions. Of note, no RCTs were conducted in a faith-based setting 130 . Table  2 highlights examples of upstream interventions that involve more than simply providing information and their classification on the Nuffield intervention ladder.

Different settings for interventions to prevent childhood obesity, including preschools and schools, primary health care, community settings and national policy, offer different opportunities for reach and effectiveness, and a reduction in inequalities.

Preschools and schools are key settings for public policy interventions for childhood obesity prevention, and mandatory and voluntary food standards and guidance on physical education are in place in many countries. Individual schools are tasked with translating and implementing these standards and guidance for their local context. Successful implementation of a whole-school approach, such as that used in the WHO Nutrition-Friendly Schools Initiative 131 , is a key factor in the effectiveness of interventions. Careful consideration should be given to how school culture can, and needs to, be shifted by working with schools to tailor the approach and manage possible staff capacity issues, and by building relationships within and outside the school gates to enhance sustainability 132 , 133 .

Primary health care offers opportunities for guidance for obesity prevention, especially from early childhood to puberty. Parent-targeted interventions conducted by clinicians in health-care or community settings have the strongest level of evidence for their effectiveness in reducing BMI z -score at age 2 years 134 . These interventions include group programmes, clinic nurse consultations, mobile phone text support or nurse home visiting, and focusing on healthy infant feeding, healthy childhood feeding behaviours and screen time.

A prospective individual participant data meta-analysis of four RCTs involving 2,196 mother–baby dyads, and involving nurse home visiting or group programmes, resulted in a small but significant reduction in BMI in infants in the intervention groups compared with control infants at age 18–24 months 134 . Improvements were also seen in television viewing time, breastfeeding duration and feeding practices. Interventions were more effective in settings with limited provision of maternal and child health services in the community. However, effectiveness diminished by age 5 years without further intervention, highlighting the need for ongoing interventions at each life stage 135 . Evidence exists that short-duration interventions targeting sleep in very early childhood may be more effective than nutrition-targeted interventions in influencing child BMI at age 5 years 136 .

Primary care clinicians can provide anticipatory guidance, as a form of primary prevention, to older children, adolescents and their families, aiming to support healthy weight and weight-related behaviours. Clinical guidelines recommend that clinicians monitor growth regularly, and provide guidance on healthy eating patterns, physical activity, sedentary behaviours and sleep patterns 97 , 100 . Very few paediatric trials have investigated whether this opportunistic screening and advice is effective in obesity prevention 100 . A 2021 review of registered RCTs for the prevention of obesity in infancy found 29 trials 137 , of which most were delivered, or were planned to be delivered, in community health-care settings, such as nurse-led clinics. At the time of publication, 11 trials had reported child weight-related outcomes, two of which showed a small but significant beneficial effect on BMI at age 2 years, and one found significant improvements in the prevalence of obesity but not BMI. Many of the trials showed improvements in practices, such as breastfeeding and screen time.

At the community level, local public policy should be mindful of the geography of the area (such as urban or rural) and population demographics. Adolescents usually have more freedom in food and beverage choices made outside the home than younger children. In addition, physical activity levels usually decline and sedentary behaviours rise during adolescence, particularly in girls 138 , 139 . These behavioural changes offer both opportunities and barriers for those developing community interventions. On a national societal level, public policies for interventions to prevent obesity in children include the control of advertising of foods and beverages high in fat, sugar and/or salt in some countries. Industry and the media, including social media, can have a considerable influence on the food and physical activity behaviours of children 13 , 119 .

Public policy may target interventions at all domains from the individual to the societal level. The main focus of interventions in most national public policies relies on the ability of individuals to make the behavioural changes that are the aim of the intervention (high-agency interventions) at the individual level (downstream interventions). An equal focus on low-agency and upstream interventions is required if a step change in tackling childhood obesity is to be realized 140 , 141 .

COVID-19 and obesity

Early indications in several countries show rising levels of childhood obesity, and an increase in inequalities in childhood obesity during the COVID-19 pandemic 142 . The substantial disruptions in nutrition and lifestyle habits of children during and since the pandemic include social isolation and addiction to screens 143 . Under-nutrition is expected to worsen in poor countries, but obesity rates could increase in middle-income countries and HICs, especially among vulnerable groups, widening the gap in health and social inequalities 143 . Public health approaches at national, regional and local levels should include strategies that not only prevent obesity and under-nutrition, but also reduce health inequalities.

In summary, although most trials of obesity prevention have occurred at the level of the individual, the immediate family, school or community, effective prevention of obesity will require greater investment in upstream, low-agency interventions.

Treatment goals

Treatment should be centred on the individual and stigma-free (Box  1 ) and may aim for a reduction in overweight and improvement in associated comorbidities and health behaviours. Clinical considerations when determining a treatment approach should include age, severity of overweight and the presence of associated complications 144 , 145 .

Box 1 Strategies for minimizing weight stigma in health care 220 , 221 , 222

Minimizing weight bias in the education of health-care professionals

Improved education of health professionals:

pay attention to the implicit and explicit communication of social norms

include coverage of the broader determinants of obesity

include discussion of harms caused by social and cultural norms and messages concerning body weight

provide opportunities to practise non-stigmatizing care throughout education

Provide causal information focusing on the genetic and/or socioenvironmental determinants of weight.

Provide empathy-invoking interventions, emphasizing size acceptance, respect and human dignity.

Provide a weight-inclusive approach, by emphasizing that all individuals, regardless of size, have the right to equal health care.

Addressing health facility infrastructure and processes

Provide appropriately sized chairs, blood pressure cuffs, weight scales, beds, toilets, showers and gowns.

Use non-stigmatizing language in signage, descriptions of clinical services and other documentation.

Providing clinical leadership and using appropriate language within health-care settings

Senior clinicians and managers should role-model supportive and non-biased behaviours towards people with obesity and indicate that they do not tolerate weight-based discrimination in any form.

Staff should identify the language that individuals prefer in referring to obesity.

Use person-first language, for example a ‘person with obesity’ rather than ‘an obese person’.

Treatment guidelines

Clinical guidelines advise that first-line management incorporates a family-based multicomponent approach that addresses dietary, physical activity, sedentary and sleep behaviours 97 , 99 , 109 , 146 . This approach is foundational, with adjunctive therapies, especially pharmacotherapy and bariatric surgery, indicated under specific circumstances, usually in adolescents with more severe obesity 144 , 145 . Guideline recommendations vary greatly among countries and are influenced by current evidence, and functionality and resourcing of local health systems. Hence, availability and feasibility of therapies differs internationally. In usual clinical practice, interventions may have poorer outcomes than is observed in original studies or anticipated in evidence-based guidelines 147 because implementation of guidelines is more challenging in resource-constrained environments 148 . In addition, clinical trials are less likely to include patients with specialized needs, such as children from culturally diverse populations, those living with social disadvantage, children with complex health problems, and those with severe obesity 149 , 150 .

Behavioural interventions

There are marked differences in individual responses to behavioural interventions, and overall weight change outcomes are often modest. In children aged 6–11 years, a 2017 Cochrane review 150 found that mean BMI z -scores were reduced in those involved in behaviour-changing interventions compared with those receiving usual care or no treatment by only 0.06 units (37 trials; 4,019 participants; low-quality evidence) at the latest follow-up (median 10 months after the end of active intervention). In adolescents aged 12–17 years, another 2017 Cochrane review 149 found that multicomponent behavioural interventions resulted in a mean reduction in weight of 3.67 kg (20 trials; 1,993 participants) and reduction in BMI of 1.18 kg/m 2 (28 trials; 2,774 participants). These effects were maintained at the 24-month follow-up. A 2012 systematic review found significant improvements in LDL cholesterol triglycerides and blood pressure up to 1 year from baseline following lifestyle interventions in children and adolescents 151 .

Family-based behavioural interventions are recommended in national level clinical practice guidelines 97 , 100 , 146 , 152 . They are an important element of intensive health behaviour and lifestyle treatments (IHBLTs) 109 . Family-based approaches use behavioural techniques, such as goal setting, parental monitoring or modelling, taught in family sessions or in individual sessions separately to children and care givers, depending on the child’s developmental level. The priority is to encourage the whole family to engage in healthier behaviours that result in dietary improvement, greater physical activity, and less sedentariness. This includes making changes to the family food environment and requires parental monitoring.

Family-based interventions differ in philosophy and implementation from those based on family systems theory and therapy 153 . All are intensive interventions that require multiple contact hours (26 or more) with trained specialists delivered over an extended period of time (6–12 months) 10 . Changing family lifestyle habits is challenging and expensive, and the therapeutic expertise is not widely available. Moving interventions to primary care settings, delivered by trained health coaches, and supplemented by remote contact (for example by phone), will improve access and equity 154 .

Very few interventions use single psychological approaches. Most effective IHBLTs are multicomponent and intensive (many sessions), and include face-to-face contact. There has been interest in motivational interviewing as an approach to delivery 155 . As client-centred counselling, this places the young person at the centre of their behaviour change. Fundamental to motivational interviewing is the practitioner partnership that helps the young person and/or parents to explore ambivalence to change, consolidate commitment to change, and develop a plan based on their own insights and expertise. Evidence reviews generally support the view that motivational interviewing reduces BMI. Longer interventions (>4 months), those that assess and report on intervention fidelity, and those that target both diet and physical activity are most effective 155 , 156 .

More intensive dietary interventions

Some individuals benefit from more intensive interventions 98 , 144 , 157 , 158 , which include very low-energy diets, very low-carbohydrate diets and intermittent energy restriction 159 . These interventions usually aim for weight loss and are only recommended for adolescents who have reached their final height. These diets are not recommended for long periods of time due to challenges in achieving nutritional adequacy 158 , 160 , and lack of long-term safety data 158 , 161 . However, intensive dietary interventions may be considered when conventional treatment is unsuccessful, or when adolescents with comorbidities or severe obesity require rapid or substantial weight loss 98 . A 2019 systematic review of very low-energy diets in children and adolescents found a mean reduction in body weight of −5.3 kg (seven studies) at the latest follow‐up, ranging from 5 to 14.5 months from baseline 161 .

Pharmacological treatment

Until the early 2020s the only drug approved in many jurisdictions for the treatment of obesity in adolescents was orlistat, a gastrointestinal lipase inhibitor resulting in reduced uptake of lipids and, thereby, a reduced total energy intake 162 . However, the modest effect on weight in combination with gastrointestinal adverse effects limit its usefulness overall 163 .

A new generation of drugs has been developed for the treatment of both T2DM and obesity. These drugs are based on gastrointestinal peptides with effects both locally and in the central nervous system. GLP1 is an incretin that reduces appetite and slows gastric motility. The GLP1 receptor agonist liraglutide is approved for the treatment of obesity in those aged 12 years and older both in the USA and Europe 164 , 165 . Liraglutide, delivered subcutaneously daily at a higher dose than used for T2DM resulted in a 5% better BMI reduction than placebo after 12 months 166 . A 2022 trial of semaglutide, another GLP1 receptor agonist, delivered subcutaneously weekly in adolescents demonstrated 16% weight loss after 68 weeks of treatment, with modest adverse events and a low drop-out rate 12 . Tirzepatide, an agonist of both GLP1 and glucose-dependent insulinotropic polypeptide (GIP), is approved by the FDA for the treatment of T2DM in adults 167 . Subcutaneous tirzepatide weekly in adults with obesity resulted in ~20% weight loss over 72 weeks 168 . Of note, GIP alone increases appetite, but the complex receptor–agonist interaction results in downregulation of the GIP receptors 169 , illustrating why slightly modified agonists exert different effects. A study of the use of tirzepatide in adolescents with T2DM has been initiated but results are not expected before 2027 (ref. 170 ). No trials of tirzepatide are currently underway in adolescents with obesity but without T2DM.

Hypothalamic obesity is difficult to treat. Setmelanotide is a MC4R agonist that reduces weight and improves quality of life in most people with LEPR and POMC mutations 71 . In trials of setmelanotide, 8 of 10 participants with POMC deficiency and 5 of 11 with LEPR deficiency had weight loss of at least 10% at ~1 year. The mean percentage change in most hunger score from baseline was −27.1% and −43.7% in those with POMC deficiency and leptin receptor deficiency, respectively 71 .

In the near future, effective new drugs with, hopefully, an acceptable safety profile will be available that will change the way we treat and set goals for paediatric obesity treatment 171 .

Bariatric surgery

Bariatric surgery is the most potent treatment for obesity in adolescents with severe obesity. The types of surgery most frequently used are sleeve gastrectomy and gastric bypass, both of which reduce appetite 172 . Mechanisms of action are complex, involving changes in gastrointestinal hormones, neural signalling, bile acid metabolism and gut microbiota 173 . Sleeve gastrectomy is a more straightforward procedure and the need for vitamin supplementation is lower than with gastric bypass. However, long-term weight loss may be greater after gastric bypass surgery 174 .

Prospective long-term studies demonstrate beneficial effects of both sleeve gastrectomy and gastric bypass on weight loss and comorbidities in adolescents with severe obesity 175 , 176 . In a 5-year follow-up period, in 161 participants in the US TEEN-LABS study who underwent gastric bypass, mean BMI declined from 50 to 37 kg/m 2 (ref. 11 ). In a Swedish prospective study in 81 adolescents who underwent gastric bypass, the mean decrease in BMI at 5 years was 13.1 kg/m 2 (baseline BMI 45.5 kg/m 2 ) compared with a BMI increase of 3.1 kg/m 2 in the control group 176 . Both studies showed marked inter-individual variations. Negative adverse effects, including gastrointestinal problems, vitamin deficits and reduction in lean body mass, are similar in adults and adolescents. Most surgical complications following bariatric surgery in the paediatric population are minor, occurring in the early postoperative time frame, but 8% of patients may have major perioperative complications 177 . Up to one-quarter of patients may require subsequent related procedures within 5 years 109 . However, many adolescents with severe obesity also have social and psychological problems, highlighting the need for routine and long-term monitoring 109 , 178 .

Recommendations for bariatric surgery in adolescents differ considerably among countries, with information on long-term outcomes emerging rapidly. In many countries, bariatric surgery is recommended only from Tanner pubertal stage 3–4 and beyond, and only in children with severe obesity and cardiometabolic comorbidities 177 . The 2023 American Academy of Pediatrics clinical practice guidelines recommend that bariatric surgery be considered in adolescents ≥13 years of age with a BMI of ≥35 kg/m 2 or 120% of the 95th percentile for age and sex, whichever is lower, as well as clinically significant disease, such as T2DM, non-alcoholic fatty liver disease, major orthopaedic complications, obstructive sleep apnoea, the presence of cardiometabolic risk, or depressed quality of life 109 . For those with a BMI of ≥40 kg/m 2 or 140% of the 95th percentile for age and sex, bariatric surgery is indicated regardless of the presence of comorbidities. Potential contraindications to surgery include correctable causes of obesity, pregnancy and ongoing substance use disorder. The guidelines comment that further evaluation, undertaken by multidisciplinary centres that offer bariatric surgery for adolescents, should determine the capacity of the patient and family to understand the risks and benefits of surgery and to adhere to the required lifestyle changes before and after surgery.

Long-term weight outcomes

Few paediatric studies have investigated long-term weight maintenance after the initial, more intensive, weight loss phase. A 2018 systematic review of 11 studies in children and adolescents showed that a diverse range of maintenance interventions, including support via face-to-face psychobehavioural therapies, individual physician consultations, or adjunctive therapeutic contact via newsletters, mobile phone text or e-mail, led to stabilization of BMI z -score compared with control participants, who had increases in BMI z -score 179 . Interventions that are web-based or use mobile devices may be particularly useful in young people 180 .

One concern is weight regain which occurs after bariatric surgery in general 181 but may be more prevalent in adolescents 176 . For example, in a Swedish prospective study, after 5 years, 25–30% of participants fulfilled the definitions of low surgical treatment effectiveness, which was associated with poorer metabolic outcomes 176 . As with adults, prevention of weight regain for most at-risk individuals might be possible with the combination of lifestyle support and pharmacological treatment 182 . Further weight maintenance strategies and long-term outcomes are discussed in the 2023 American Academy of Pediatrics clinical practice guidelines 109 . The appropriate role and timing of other therapies for long-term weight loss maintenance, such as anti-obesity medications, more intensive dietary interventions and bariatric surgery, are areas for future research.

In summary, management of obesity in childhood and adolescence requires intensive interventions. Emerging pharmacological therapies demonstrate greater short-term effectiveness than behavioural interventions; however, long-term outcomes at ≥2 years remain an important area for future research.

Quality of life

Weight bias describes the negative attitudes to, beliefs about and behaviour towards people with obesity 183 . It can lead to stigma causing exclusion, and discrimination in work, school and health care, and contributes to the inequities common in people with obesity 184 . Weight bias also affects social engagement and psychological well-being of children.

Children and adolescents with obesity score lower overall on health-related quality of life (HRQoL) 4 , 5 . In measures that assess domains of functioning, most score lower in physical functioning, physical/general health and psychosocial areas, such as appearance, and social acceptance and functioning. HRQoL is lowest in treatment-seeking children and in those with more extreme obesity 185 . Weight loss interventions generally increase HRQoL independent of the extent of weight loss 186 , especially in the domains most affected. However, changes in weight and HRQoL are often not strongly correlated. This may reflect a lag in the physical and/or psychosocial benefit from weight change, or the extent of change that is needed to drive change in a child’s self-perception.

Similar observations apply to the literature on self-esteem. Global self-worth is reduced in children and adolescents with obesity, as is satisfaction with physical appearance, athletic competence and social acceptance 187 . Data from intensive interventions suggest the psychological benefit of weight loss may be as dependent on some feature of the treatment environment or supportive social network as the weight loss itself 188 . This may include the daily company of others with obesity, making new friendships, and experienced improvements in newly prioritized competences.

There is a bidirectional relationship between HRQoL and obesity 189 , something also accepted in the relationship with mood disorder. Obesity increases the risk of depression and vice versa, albeit over a longer period of time and which may only become apparent in adulthood 190 . Obesity also presents an increased risk of anxiety 191 .

Structured and professionally delivered weight management interventions ameliorate mood disorder symptoms 192 and improve self-esteem 193 . Regular and extended support are important components beyond losing weight. Such interventions do not increase the risk of eating disorders 194 . This is despite a recognition that binge eating disorder is present in up to 5% of adolescents with overweight or obesity 195 . They are five times more likely to have binge eating symptoms than those with average weight. Importantly, adolescents who do not have access to professionally delivered weight management may be more likely to engage in self-directed dieting, which is implicated in eating disorder development 196 .

The literature linking childhood obesity with either attention deficit hyperactivity disorder or autism spectrum disorder is complex and the relationship is uncertain. The association seems to be clearer in adults but the mechanisms and their causal directions remain unclear 109 , 197 . Young children with obesity, especially boys, are more likely to be parent-rated as having behavioural problems 198 . This may be a response to the behaviour of others rather than reflect clinical diagnoses such as attention deficit hyperactivity disorder or autism spectrum disorder. Conduct and peer relationship problems co-occur in children, regardless of their weight.

Children with obesity experience more social rejection. They receive fewer friendship nominations and more peer rejections, most pronounced in those with severe obesity 199 . This continues through adolescence and beyond. Children with obesity are more likely to report being victimized 200 . Younger children may respond by being perpetrators themselves. While it is assumed that children are victimized because of their weight, very few studies have looked at the nature or reason behind victimization. A substantial proportion of children with obesity fail to identify themselves as being fat-teased 187 . Although the stigma associated with obesity should be anticipated in children, especially in those most overweight, it would be inappropriate to see all as victims. A better understanding of children’s resilience is needed.

Many gaps remain in basic, translational and clinical research in child and adolescent obesity. The mechanisms (genetic, epigenetic, environmental and social) behind the overwhelming association between parental obesity and child and adolescent obesity are still unclear given the paradoxically weak association in BMI between adopted children and their parents in combination with the modest effect size of known genetic loci associated with obesity 201 .

Early manifestation of extreme obesity in childhood suggests a strong biological basis for disturbances of homeostatic weight regulation. Deep genotyping (including next-generation sequencing) and epigenetic analyses in these patients will reveal new genetic causes and causal pathways as a basis for the development of mechanism-based treatments. Future work aiming to understand the mechanisms underlying the development of childhood obesity should consider the complex biopsychosocial interactions and take a systems approach to understanding causal pathways leading to childhood obesity to contribute to evidence-based prevention and treatment strategies.

Long-term outcome data to better determine the risks of eating disorders are required. Although symptoms improve during obesity treatment in most adolescents, screening and monitoring for disordered eating is recommended in those presenting for treatment 202 and effective tools for use in clinical practice are required. A limited number of tools are validated to identify binge eating disorder in youth with obesity 203 but further research is needed to screen appropriately for the full spectrum of eating disorder diagnoses in obesity treatment seeking youth 203 . Recent reviews provide additional detail regarding eating disorder risk in child and adolescent obesity 117 , 202 , 204 .

Most studies of paediatric obesity treatment have been undertaken in HICs and predominantly middle-class populations. However, research is needed to determine which strategies are best suited for those in LMICs and low-resource settings, for priority population groups including indigenous peoples, migrant populations and those living with social disadvantage, and for children with neurobehavioural and psychiatric disorders. We currently have a limited understanding of how best to target treatment pathways for different levels of genetic risk, age, developmental level, obesity severity, and cardiometabolic and psychological risk. Current outcomes for behavioural interventions are relatively modest and improved treatment outcomes are needed to address the potentially severe long-term health outcomes of paediatric obesity. Studies also need to include longer follow-up periods after an intervention, record all adverse events, incorporate cost-effectiveness analyses and have improved process evaluation.

Other areas in need of research include the role of new anti-obesity medications especially in adolescents, long-term outcomes following bariatric surgery and implementation of digital support systems to optimize outcomes and reduce costs of behavioural change interventions 205 . We must also better understand and tackle the barriers to implementation of treatment in real-life clinical settings, including the role of training of health professionals. Importantly, treatment studies of all kinds must engage people with lived experience — adolescents, parents and families — to understand what outcomes and elements of treatment are most valued.

Obesity prevention is challenging because it requires a multilevel, multisectoral approach that addresses inequity, involves many stakeholders and addresses both the upstream and the downstream factors influencing obesity risk. Some evidence exists of effectiveness of prevention interventions operating at the level of the child, family and school, but the very poor progress overall in modifying obesity prevalence globally highlights many areas in need of research and evidence implementation. Studies are needed especially in LMICs, particularly in the context of the nutrition transition and the double burden of malnutrition. A focus on intergenerational research, rather than the age-based focus of current work, is also needed. Systems research approaches should be used, addressing the broader food and physical activity environments, and links to climate change 206 . In all studies, strategies are needed that enable co-production with relevant communities, long-term follow-up, process evaluation and cost-effectiveness analyses. In the next few years, research and practice priorities must include a focus on intervention strategies in the earliest phases of life, including during pregnancy. The effects of COVID-19 and cost of living crises in many countries are leading to widening health inequalities 207 and this will further challenge obesity prevention interventions. Available resourcing for prevention interventions may become further constrained, requiring innovative solutions across agendas, with clear identification of co-benefits. For example, public health interventions for other diseases, such as dental caries or depression, or other societal concerns, such as urban congestion or climate change, may also act as obesity prevention strategies. Ultimately, to implement obesity prevention, societal changes are needed in terms of urban planning, social structures and health-care access.

Future high-quality paediatric obesity research can be enabled through strategies that support data sharing, which avoids research waste and bias, and enables new research questions to be addressed. Such approaches require leadership, careful engagement of multiple research teams, and resourcing. Four national or regional level paediatric weight registries exist 208 , 209 , 210 , 211 , which are all based in North America or Europe. Such registries should be established in other countries, especially in low-resource settings, even if challenging 208 . Another data-sharing approach is through individual participant data meta-analyses of intervention trials, which can include prospectively collected data 212 and are quite distinct from systematic reviews of aggregate data. Two recent examples are the Transforming Obesity Prevention in Childhood (TOPCHILD) Collaboration, which includes early interventions to prevent obesity in the first 2 years of life 213 , and the Eating Disorders in Weight-Related Therapy (EDIT) Collaboration, which aims to identify characteristics of individuals or trials that increase or protect against eating disorder risk following obesity treatment 214 . Formal data linkage studies, especially those joining up routine administrative datasets, enable longer-term and broader outcome measures to be assessed than is possible with standard clinical or public health intervention studies.

Collaborative research will also be enhanced through the use of agreed core outcome sets, supporting data harmonization. The Edmonton Obesity Staging System – Paediatric 215 is one option for paediatric obesity treatment. A core outcome set for early intervention trials to prevent obesity in childhood (COS-EPOCH) has been recently established 216 . These efforts incorporate a balance between wanting and needing to share data and adhering to privacy protection regulations. Objective end points are ideal, including directly measured physical activity and body composition.

Collaborative efforts and a systems approach are paramount to understand, prevent and manage child and adolescent obesity. Research funding and health policies should focus on feasible, effective and equitable interventions.

NCD Risk Factor Collaboration. Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128·9 million children, adolescents, and adults. Lancet https://doi.org/10.1016/S0140-6736(17)32129-3 (2017).

Article   Google Scholar  

Popkin, B. M., Corvalan, C. & Grummer-Strawn, L. M. Dynamics of the double burden of malnutrition and the changing nutrition reality. Lancet 395 , 65–74 (2020).

Article   PubMed   Google Scholar  

Kompaniyets, L. et al. Underlying medical conditions associated with severe COVID-19 illness among children. JAMA Netw. Open 4 , e2111182 (2021).

Article   PubMed   PubMed Central   Google Scholar  

Griffiths, L. J., Parsons, T. J. & Hill, A. J. Self‐esteem and quality of life in obese children and adolescents: a systematic review. Int. J. Pediatr. Obes. 5 , 282–304 (2010).

Buttitta, M., Iliescu, C., Rousseau, A. & Guerrien, A. Quality of life in overweight and obese children and adolescents: a literature review. Qual. Life Res. 23 , 1117–1139 (2014).

Hayes, A. et al. Early childhood obesity: association with healthcare expenditure in Australia. Obesity 24 , 1752–1758 (2016).

Marcus, C., Danielsson, P. & Hagman, E. Pediatric obesity – long-term consequences and effect of weight loss. J. Intern. Med. 292 , 870–891 (2022).

Berthoud, H. R., Morrison, C. D. & Münzberg, H. The obesity epidemic in the face of homeostatic body weight regulation: what went wrong and how can it be fixed? Physiol. Behav. 222 , 112959 (2020).

Article   CAS   PubMed   PubMed Central   Google Scholar  

World Health Organization. Report of the commission on ending childhood obesity. WHO https://www.who.int/publications/i/item/9789241510066 (2016). This report from the WHO on approaches to childhood and adolescent obesity has six main recommendations for governments, covering food and physical activity, age-based settings and provision of weight management for those with obesity.

O’Connor, E. A. et al. Screening for obesity and intervention for weight management in children and adolescents: evidence report and systematic review for the US Preventive Services Task Force. JAMA 317 , 2427–2444 (2017).

Inge, T. H. et al. Five-year outcomes of gastric bypass in adolescents as compared with adults. N. Engl. J. Med. 380 , 2136–2145 (2019).

Weghuber, D. et al. Once-weekly semaglutide in adolescents with obesity. N. Engl. J. Med. https://doi.org/10.1056/NEJMoa2208601 (2022). To our knowledge, the first RCT of semaglutide 2.4 mg, administered weekly by subcutaneous injection, in adolescents with obesity.

World Health Organization. Report of the Commission on Ending Childhood Obesity: Implementation Plan: Executive Summary (WHO, 2017).

Hillier-Brown, F. C. et al. A systematic review of the effectiveness of individual, community and societal level interventions at reducing socioeconomic inequalities in obesity amongst children. BMC Public Health 14 , 834 (2014).

World Health Organization. Obesity. WHO https://www.who.int/health-topics/obesity#tab=tab_1 (2023).

Mei, Z. et al. Validity of body mass index compared with other body-composition screening indexes for the assessment of body fatness in children and adolescents. Am. J. Clin. Nutr. 75 , 978–985 (2002).

Article   CAS   PubMed   Google Scholar  

World Health Organization. Child growth standards. WHO https://www.who.int/tools/child-growth-standards/standards (2006).

World Health Organization. Growth reference data for 5–19 years. WHO https://www.who.int/tools/growth-reference-data-for-5to19-years (2007).

National Center for Health Statistics. CDC growth charts. Centers for Disease Control and Prevention http://www.cdc.gov/growthcharts/ (2022).

Cole, T. J., Bellizzi, M. C., Flegal, K. M. & Dietz, W. H. Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ 320 , 1240 (2000).

Di Cesare, M. et al. The epidemiological burden of obesity in childhood: a worldwide epidemic requiring urgent action. BMC Med. 17 , 212 (2019).

Swinburn, B., Egger, G. & Raza, F. Dissecting obesogenic environments: the development and application of a framework for identifying and prioritizing environmental interventions for obesity. Prev. Med. 29 , 563–570 (1999).

Ford, N. D., Patel, S. A. & Narayan, K. V. Obesity in low-and middle-income countries: burden, drivers, and emerging challenges. Annu. Rev. Public Health 38 , 145–164 (2017).

Shah, B., Tombeau Cost, K., Fuller, A., Birken, C. S. & Anderson, L. N. Sex and gender differences in childhood obesity: contributing to the research agenda. BMJ Nutr. Prev. Health 3 , 387–390 (2020).

Public Health England. Research and analysis: differences in child obesity by ethnic group. GOV.UK https://www.gov.uk/government/publications/differences-in-child-obesity-by-ethnic-group/differences-in-child-obesity-by-ethnic-group#data (2019).

Cole, T. J. & Lobstein, T. Extended international (IOTF) body mass index cut‐offs for thinness, overweight and obesity. Pediatr. Obes. 7 , 284–294 (2012).

Kelly, A. S. et al. Severe obesity in children and adolescents: identification, associated health risks, and treatment approaches: a scientific statement from the American Heart Association. Circulation 128 , 1689–1712 (2013).

Garnett, S. P., Baur, L. A., Jones, A. M. & Hardy, L. L. Trends in the prevalence of morbid and severe obesity in Australian children aged 7–15 years, 1985-2012. PLoS ONE 11 , e0154879 (2016).

Spinelli, A. et al. Prevalence of severe obesity among primary school children in 21 European countries. Obes. Facts 12 , 244–258 (2019).

Twig, G. et al. Body-Mass Index in 2.3 million adolescents and cardiovascular death in adulthood. N. Engl. J. Med. 374 , 2430–2440 (2016).

González-Muniesa, P. et al. Obesity. Nat. Rev. Dis. Primers   3 , 17034 (2017).

Geserick, M. et al. Acceleration of BMI in early childhood and risk of sustained obesity. N. Engl. J. Med. 379 , 1303–1312 (2018).

Larqué, E. et al. From conception to infancy – early risk factors for childhood obesity. Nat. Rev. Endocrinol. 15 , 456–478 (2019).

Barker, D. J. Fetal origins of coronary heart disease. Br. Med. J. 311 , 171–174 (1995).

Article   CAS   Google Scholar  

Gluckman, P. D., Hanson, M. A., Cooper, C. & Thornburg, K. L. Effect of in utero and early-life conditions on adult health and disease. N. Engl. J. Med. 359 , 61–73 (2008).

Philips, E. M. et al. Changes in parental smoking during pregnancy and risks of adverse birth outcomes and childhood overweight in Europe and North America: an individual participant data meta-analysis of 229,000 singleton births. PLoS Med. 17 , e1003182 (2020).

Voerman, E. et al. Maternal body mass index, gestational weight gain, and the risk of overweight and obesity across childhood: an individual participant data meta-analysis. PLoS Med. 16 , e1002744 (2019). Individual participant data meta-analysis of >160,000 mothers and their children on the associations of maternal BMI and gestational weight gain and childhood overweight or obesity.

McIntyre, H. D. et al. Gestational diabetes mellitus. Nat. Rev. Dis. Primers   5 , 47 (2019).

Oken, E. & Gillman, M. W. Fetal origins of obesity. Obes. Res. 11 , 496–506 (2003).

Hughes, A. R., Sherriff, A., Ness, A. R. & Reilly, J. J. Timing of adiposity rebound and adiposity in adolescence. Pediatrics 134 , e1354–e1361 (2014).

Rolland-Cachera, M. F. et al. Tracking the development of adiposity from one month of age to adulthood. Ann. Hum. Biol. 14 , 219–229 (1987).

Koletzko, B. et al. Prevention of childhood obesity: a position paper of the Global Federation of International Societies of Paediatric Gastroenterology, Hepatology and Nutrition (FISPGHAN). J. Pediatr. Gastroenterol. Nutr. 70 , 702–710 (2020).

Weber, M. et al. Lower protein content in infant formula reduces BMI and obesity risk at school age: follow-up of a randomized trial. Am. J. Clin. Nutr. 99 , 1041–1051 (2014).

Cope, M. B. & Allison, D. B. Critical review of the World Health Organization’s (WHO) 2007 report on ‘evidence of the long‐term effects of breastfeeding: systematic reviews and meta‐analysis’ with respect to obesity. Obes. Rev. 9 , 594–605 (2008).

Totzauer, M. et al. Different protein intake in the first year and its effects on adiposity rebound and obesity throughout childhood: 11 years follow‐up of a randomized controlled trial. Pediatr. Obes. 17 , e12961 (2022).

Deren, K. et al. Consumption of sugar-sweetened beverages in paediatric age: a position paper of the European academy of paediatrics and the European Childhood Obesity Group. Ann. Nutr. Metab. 74 , 296–302 (2019).

Felső, R., Lohner, S., Hollódy, K., Erhardt, É. & Molnár, D. Relationship between sleep duration and childhood obesity: systematic review including the potential underlying mechanisms. Nutr. Metab. Cardiovasc. Dis. 27 , 751–761 (2017).

Farooq, A. et al. Longitudinal changes in moderate‐to‐vigorous‐intensity physical activity in children and adolescents: a systematic review and meta‐analysis. Obes. Rev. 21 , e12953 (2020).

Mahumud, R. A. et al. Association of dietary intake, physical activity, and sedentary behaviours with overweight and obesity among 282,213 adolescents in 89 low and middle income to high-income countries. Int. J. Obes. 45 , 2404–2418 (2021).

Ballon, M. et al. Socioeconomic inequalities in weight, height and body mass index from birth to 5 years. Int. J. Obes. 42 , 1671–1679 (2018).

Buoncristiano, M. et al. Socioeconomic inequalities in overweight and obesity among 6- to 9-year-old children in 24 countries from the World Health Organization European region. Obes. Rev. 22 , e13213 (2021).

Jiwani, S. S. et al. The shift of obesity burden by socioeconomic status between 1998 and 2017 in Latin America and the Caribbean: a cross-sectional series study. Lancet Glob. Health 7 , e1644–e1654 (2019).

Monteiro, C. A., Conde, W. L., Lu, B. & Popkin, B. M. Obesity and inequities in health in the developing world. Int. J. Obes. 28 , 1181–1186 (2004).

Guo, S. S. & Chumlea, W. C. Tracking of body mass index in children in relation to overweight in adulthood. Am. J. Clin. Nutr. 70 , 145S–148S (1999).

Aarestrup, J. et al. Birthweight, childhood overweight, height and growth and adult cancer risks: a review of studies using the Copenhagen School Health Records Register. Int. J. Obes. 44 , 1546–1560 (2020).

Eslam, M. et al. Defining paediatric metabolic (dysfunction)-associated fatty liver disease: an international expert consensus statement. Lancet Gastroenterol. Hepatol. 6 , 864–873 (2021).

Daniels, S. R. et al. Overweight in children and adolescents: pathophysiology, consequences, prevention, and treatment. Circulation 111 , 1999–2012 (2005).

Cioana, M. et al. The prevalence of obesity among children with type 2 diabetes: a systematic review and meta-analysis. JAMA Netw. Open 5 , e2247186 (2022).

Gepstein, V. & Weiss, R. Obesity as the main risk factor for metabolic syndrome in children. Front. Endocrinol. 10 , 568 (2019).

Kuvat, N., Tanriverdi, H. & Armutcu, F. The relationship between obstructive sleep apnea syndrome and obesity: a new perspective on the pathogenesis in terms of organ crosstalk. Clin. Respir. J. 14 , 595–604 (2020).

Baker, J. L., Olsen, L. W. & Sorensen, T. I. Childhood body-mass index and the risk of coronary heart disease in adulthood. N. Engl. J. Med. 357 , 2329–2337 (2007).

Bjerregaard, L. G. et al. Change in overweight from childhood to early adulthood and risk of type 2 diabetes. N. Engl. J. Med. 378 , 1302–1312 (2018).

Kelsey, M. M., Zaepfel, A., Bjornstad, P. & Nadeau, K. J. Age-related consequences of childhood obesity. Gerontology 60 , 222–228 (2014).

Sharma, V. et al. A systematic review and meta-analysis estimating the population prevalence of comorbidities in children and adolescents aged 5 to 18 years. Obes. Rev. 20 , 1341–1349 (2019).

Lobstein, T. & Jackson-Leach, R. Planning for the worst: estimates of obesity and comorbidities in school-age children in 2025. Pediatr. Obes. 11 , 321–325 (2016).

Berthoud, H. R., Münzberg, H. & Morrison, C. D. Blaming the brain for obesity: integration of hedonic and homeostatic mechanisms. Gastroenterology 152 , 1728–1738 (2017).

Devoto, F. et al. Hungry brains: a meta-analytical review of brain activation imaging studies on food perception and appetite in obese individuals. Neurosci. Biobehav. Rev. 94 , 271–285 (2018).

Blum, W. F., Englaro, P., Attanasio, A. M., Kiess, W. & Rascher, W. Human and clinical perspectives on leptin. Proc. Nutr. Soc. 57 , 477–485 (1998).

Friedman, J. M. Leptin and the endocrine control of energy balance. Nat. Metab. 1 , 754–764 (2019).

Kühnen, P. et al. Proopiomelanocortin deficiency treated with a melanocortin-4 receptor agonist. N. Engl. J. Med. 375 , 240–246 (2016).

Clément, K. et al. Efficacy and safety of setmelanotide, an MC4R agonist, in individuals with severe obesity due to LEPR or POMC deficiency: single-arm, open-label, multicentre, phase 3 trials. Lancet Diabetes Endocrinol. 8 , 960–970 (2020).

Rosen, E. D. & Spiegelman, B. M. What we talk about when we talk about fat. Cell 156 , 20–44 (2014).

Fischer-Posovszky, P., Roos, J., Zoller, V. & Wabitsch, M. in Pediatric Obesity: Etiology, Pathogenesis and Treatment (ed. Freemark, M. S.) 81–93 (Springer, 2018).

Hammarstedt, A., Gogg, S., Hedjazifar, S., Nerstedt, A. & Smith, U. Impaired adipogenesis and dysfunctional adipose tissue in human hypertrophic obesity. Physiol. Rev. 98 , 1911–1941 (2018).

Silventoinen, K. et al. Genetic and environmental effects on body mass index from infancy to the onset of adulthood: an individual-based pooled analysis of 45 twin cohorts participating in the collaborative project of development of anthropometrical measures in twins (CODATwins) study. Am. J. Clin. Nutr. 104 , 371–379 (2016).

Silventoinen, K. et al. Differences in genetic and environmental variation in adult BMI by sex, age, time period, and region: an individual-based pooled analysis of 40 twin cohorts. Am. J. Clin. Nutr. 106 , 457–466 (2017).

Yengo, L. et al. Meta-analysis of genome-wide association studies for height and body mass index in approximately 700000 individuals of European ancestry. Hum. Mol. Genet. 27 , 3641–3649 (2018).

Vogelezang, S. et al. Novel loci for childhood body mass index and shared heritability with adult cardiometabolic traits. PLoS Genet. 16 , e1008718 (2020).

Bradfield, J. P. et al. A trans-ancestral meta-analysis of genome-wide association studies reveals loci associated with childhood obesity. Hum. Mol. Genet. 28 , 3327–3338 (2019). To our knowledge, currently the largest genome-wide association study meta-analysis on childhood obesity in >13,000 individuals with obesity and >15,500 controls.

Couto Alves, A. et al. GWAS on longitudinal growth traits reveals different genetic factors influencing infant, child, and adult BMI. Sci. Adv. 5 , eaaw3095 (2019).

Ding, X. et al. Genome-wide screen of DNA methylation identifies novel markers in childhood obesity. Gene 566 , 74–83 (2015).

Huang, R. C. et al. Genome-wide methylation analysis identifies differentially methylated CpG loci associated with severe obesity in childhood. Epigenetics 10 , 995–1005 (2015).

Rzehak, P. et al. DNA-methylation and body composition in preschool children: epigenome-wide-analysis in the European Childhood Obesity Project (CHOP)-Study. Sci. Rep. 7 , 14349 (2017).

Alfano, R. et al. Perspectives and challenges of epigenetic determinants of childhood obesity: a systematic review. Obes. Rev. 23 , e13389 (2022).

Vehmeijer, F. O. L. et al. DNA methylation and body mass index from birth to adolescence: meta-analyses of epigenome-wide association studies. Genome Med. 12 , 105 (2020). Meta-analysis of epigenome-wide association studies of childhood BMI in >4,000 children.

Richmond, R. C. et al. DNA methylation and BMI: investigating identified methylation sites at HIF3A in a causal framework. Diabetes 65 , 1231–1244 (2016).

Wahl, S. et al. Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity. Nature 541 , 81–86 (2017).

Kivimäki, M. et al. Substantial intergenerational increases in body mass index are not explained by the fetal overnutrition hypothesis: the Cardiovascular Risk in Young Finns Study. Am. J. Clin. Nutr. 86 , 1509–1514 (2007).

Whitaker, R. C., Wright, J. A., Pepe, M. S., Seidel, K. D. & Dietz, W. H. Predicting obesity in young adulthood from childhood and parental obesity. N. Engl. J. Med. 337 , 869–873 (1997).

Davey Smith, G., Steer, C., Leary, S. & Ness, A. Is there an intrauterine influence on obesity? Evidence from parent child associations in the Avon Longitudinal Study of Parents and Children (ALSPAC). Arch. Dis. Child. 92 , 876–880 (2007).

Fleten, C. et al. Parent-offspring body mass index associations in the Norwegian Mother and Child Cohort Study: a family-based approach to studying the role of the intrauterine environment in childhood adiposity. Am. J. Epidemiol. 176 , 83–92 (2012).

Gaillard, R. et al. Childhood cardiometabolic outcomes of maternal obesity during pregnancy: the Generation R Study. Hypertension 63 , 683–691 (2014).

Lawlor, D. A. et al. Exploring the developmental overnutrition hypothesis using parental-offspring associations and FTO as an instrumental variable. PLoS Med. 5 , e33 (2008).

Patro, B. et al. Maternal and paternal body mass index and offspring obesity: a systematic review. Ann. Nutr. Metab. 63 , 32–41 (2013).

Sorensen, T. et al. Comparison of associations of maternal peri-pregnancy and paternal anthropometrics with child anthropometrics from birth through age 7 y assessed in the Danish National Birth Cohort. Am. J. Clin. Nutr. 104 , 389–396 (2016).

Styne, D. M. et al. Pediatric obesity – assessment, treatment, and prevention: an Endocrine Society Clinical Practice guideline. J. Clin. Endocrinol. Metab. 102 , 709–757 (2017).

National Institute for Health and Care Excellence. Obesity: identification, assessment and managenent: clinical guideline [CG189]. NICE https://www.nice.org.uk/guidance/cg189 (2022). A high quality clinical practice guideline for obesity management.

Barlow, S. E. Expert Committee Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: summary report. Pediatrics 120 (Suppl. 4), S164–S192 (2007).

Canadian Task Force on Preventive Health Care. Recommendations for growth monitoring, and prevention and management of overweight and obesity in children and youth in primary care. Can. Med. Assoc. J. 187 , 411–421 (2015).

US Preventive Services Task Force. Screening for obesity in children and adolescents: US Preventive Services Task Force recommendation statement. JAMA 317 , 2417–2426 (2017).

McConnell-Nzunga, J. et al. Classification of obesity varies between body mass index and direct measures of body fat in boys and girls of Asian and European ancestry. Meas. Phys. Educ. Exerc. Sci. 22 , 154–166 (2018).

Reinehr, T. et al. Definable somatic disorders in overweight children and adolescents. J. Pediatr. 150 , 618–622.e5 (2007).

Reinehr, T. Thyroid function in the nutritionally obese child and adolescent. Curr. Opin. Pediatr. 23 , 415–420 (2011).

Kohlsdorf, K. et al. Early childhood BMI trajectories in monogenic obesity due to leptin, leptin receptor, and melanocortin 4 receptor deficiency. Int. J. Obes. 42 , 1602–1609 (2018).

Armstrong, S. et al. Physical examination findings among children and adolescents with obesity: an evidence-based review. Pediatrics 137 , e20151766 (2016).

Reinehr, T. & Roth, C. L. Is there a causal relationship between obesity and puberty? Lancet Child Adolesc. Health 3 , 44–54 (2019).

Garnett, S. P., Baur, L. A. & Cowell, C. T. Waist-to-height ratio: a simple option for determining excess central adiposity in young people. Int. J. Obes. 32 , 1028–1030 (2008).

Maffeis, C., Banzato, C., Talamini, G. & Obesity Study Group of the Italian Society of Pediatric Endocrinology and Diabetology. Waist-to-height ratio, a useful index to identify high metabolic risk in overweight children. J. Pediatr. 152 , 207–213.e2 (2008).

Hampl, S. E. et al. Clinical practice guideline for the evaluation and treatment of children and adolescents with obesity. Pediatrics 151 , e2022060640 (2023). A new, comprehensive clinical practice guideline outlining current recommendations on assessment and treatment of children and adolescents with obesity.

Reinehr, T. et al. Comparison of cardiovascular risk factors between children and adolescents with classes III and IV obesity: findings from the APV cohort. Int. J. Obes. 45 , 1061–1073 (2021).

Reinehr, T. Metabolic syndrome in children and adolescents: a critical approach considering the interaction between pubertal stage and insulin resistance. Curr. Diabetes Rep. 16 , 8 (2016).

Zeitler, P. et al. ISPAD Clinical Practice Consensus Guidelines 2018: type 2 diabetes mellitus in youth. Pediatr. Diabetes 19 , 28–46 (2018).

Ibáñez, L. et al. An International Consortium update: pathophysiology, diagnosis, and treatment of polycystic ovarian syndrome in adolescence. Horm. Res. Paediatr. 88 , 371–395 (2017).

Brockmann, P. E., Schaefer, C., Poets, A., Poets, C. F. & Urschitz, M. S. Diagnosis of obstructive sleep apnea in children: a systematic review. Sleep Med. Rev. 17 , 331–340 (2013).

Taylor, E. D. et al. Orthopedic complications of overweight in children and adolescents. Pediatrics 117 , 2167–2174 (2006).

Winck, A. D. et al. Effects of obesity on lung volume and capacity in children and adolescents: a systematic review. Rev. Paul. Pediatr. 34 , 510–517 (2016).

PubMed   PubMed Central   Google Scholar  

Jebeile, H., Lister, N., Baur, L., Garnett, S. & Paxton, S. J. Eating disorder risk in adolescents with obesity. Obes. Rev. 22 , e13173 (2021).

Quek, Y. H., Tam, W. W. S., Zhang, M. W. B. & Ho, R. C. M. Exploring the association between childhood and adolescent obesity and depression: a meta-analysis. Obes. Rev. 18 , 742–754 (2017).

World Health Organization. Consideration of the Evidence on Childhood Obesity for the Commission on Ending Childhood Obesity . Report of the Ad Hoc Working Group on Science and Evidence for Ending Childhood Obesity (WHO, 2016).

Pickett, K. et al. The Child of the North: building a fairer future after COVID-19. The Northern Health Science Alliance and N8 Research Partnership https://www.thenhsa.co.uk/app/uploads/2022/01/Child-of-the-North-Report-FINAL-1.pdf (2021).

Bronfenbrenner, U. Toward an experimental ecology of human development. Am. Psychol. 32 , 513–531 (1977).

Nuffield Council on Bioethics. Public Health: Ethical Issues (Nuffield Council on Bioethics, 2007).

Lorenc, T., Petticrew, M., Welch, V. & Tugwell, P. What types of interventions generate inequalities? Evidence from systematic reviews. J. Epidemiol. Community Health 67 , 190–193 (2013).

Adams, J., Mytton, O., White, M. & Monsivais, P. Why are some population interventions for diet and obesity more equitable and effective than others? The role of individual agency. PLoS Med. 13 , e1001990 (2016).

Backholer, K. et al. A framework for evaluating the impact of obesity prevention strategies on socioeconomic inequalities in weight. Am. J. Public Health 104 , e43–e50 (2014).

McGill, R. et al. Are interventions to promote healthy eating equally effective for all? Systematic review of socioeconomic inequalities in impact. BMC Public Health 15 , 457 (2015).

Brown, T. et al. Interventions for preventing obesity in children. Cochrane Database Syst. Rev. 7 , Cd001871 (2019). A Cochrane review involving 153 RCTs of diet and/or physical activity interventions to prevent obesity in children and adolescents, highlighting varying effectiveness of interventions in different age groups.

PubMed   Google Scholar  

Le, L. K.-D. et al. Prevention of high body mass index and eating disorders: a systematic review and meta-analysis. Eat. Weight Disord. 27 , 2989–3003 (2022).

Nobles, J., Summerbell, C., Brown, T., Jago, R. & Moore, T. A secondary analysis of the childhood obesity prevention Cochrane Review through a wider determinants of health lens: implications for research funders, researchers, policymakers and practitioners. Int. J. Behav. Nutr. Phys. Act. 18 , 22 (2021).

Rai, K. K., Dogra, S. A., Barber, S., Adab, P. & Summerbell, C. A scoping review and systematic mapping of health promotion interventions associated with obesity in Islamic religious settings in the UK. Obes. Rev. 20 , 1231–1261 (2019).

World Health Organization. Nutrition Action in Schools: A Review of Evidence Related to the Nutrition-Friendly Schools Initiative (WHO, 2021).

Daly-Smith, A. et al. Using a multi-stakeholder experience-based design process to co-develop the Creating Active Schools Framework. Int. J. Behav. Nutr. Phys. Act. 17 , 13 (2020).

Tibbitts, B. et al. Considerations for individual-level versus whole-school physical activity interventions: stakeholder perspectives. Int. J. Environ. Res. Public Health https://doi.org/10.3390/ijerph18147628 (2021).

Askie, L. M. et al. Interventions commenced by early infancy to prevent childhood obesity-The EPOCH Collaboration: an individual participant data prospective meta-analysis of four randomized controlled trials. Pediatr. Obes. 15 , e12618 (2020). To our knowledge, the first prospective individual participant data meta-analysis showing that interventions commencing in late pregnancy or very early childhood are associated with healthier BMI z -score at age 18–24 months.

Seidler, A. L. et al. Examining the sustainability of effects of early childhood obesity prevention interventions: follow-up of the EPOCH individual participant data prospective meta-analysis. Pediatr. Obes. 17 , e12919 (2022).

Taylor, R. W. et al. Sleep, nutrition, and physical activity interventions to prevent obesity in infancy: follow-up of the prevention of overweight in infancy (POI) randomized controlled trial at ages 3.5 and 5 y. Am. J. Clin. Nutr. 108 , 228–236 (2018).

Mihrshahi, S. et al. A review of registered randomized controlled trials for the prevention of obesity in infancy. Int. J. Environ. Res. Public Health 18 , 2444 (2021).

Farooq, M. A. et al. Timing of the decline in physical activity in childhood and adolescence: Gateshead Millennium Cohort Study. Br. J. Sports Med. 52 , 1002–1006 (2018).

van Sluijs, E. M. F. et al. Physical activity behaviours in adolescence: current evidence and opportunities for intervention. Lancet 398 , 429–442 (2021).

Griffin, N. et al. A critique of the English national policy from a social determinants of health perspective using a realist and problem representation approach: the ‘Childhood Obesity: a plan for action’ (2016, 2018, 2019). BMC Public Health 21 , 2284 (2021).

Knai, C., Lobstein, T., Petticrew, M., Rutter, H. & Savona, N. England’s childhood obesity action plan II. Br. Med. J. 362 , k3098 (2018).

World Health Organization. WHO European Regional Obesity Report 2022 (WHO, 2022).

Zemrani, B., Gehri, M., Masserey, E., Knob, C. & Pellaton, R. A hidden side of the COVID-19 pandemic in children: the double burden of undernutrition and overnutrition. Int. J. Equity Health 20 , 44 (2021).

Alman, K. L. et al. Dietetic management of obesity and severe obesity in children and adolescents: a scoping review of guidelines. Obes. Rev. https://doi.org/10.1111/obr.13132 (2020).

Pfeiffle, S. et al. Current recommendations for nutritional management of overweight and obesity in children and adolescents: a structured framework. Nutrients https://doi.org/10.3390/nu11020362 (2019).

Scottish Intercollegiate Guidelines Network. Management of obesity. A National Clinical Guideline . SIGN 115 (SIGN, 2010).

Reinehr, T. et al. Two-year follow-up in 21,784 overweight children and adolescents with lifestyle intervention. Obesity 17 , 1196–1199 (2009).

Ells, L. J. et al. Interventions for treating children and adolescents with overweight and obesity: an overview of Cochrane reviews. Int. J. Obes. 42 , 1823–1833 (2018).

Al‐Khudairy, L. et al. Diet, physical activity and behavioural interventions for the treatment of overweight or obese adolescents aged 12 to 17 years. Cochrane Database Syst. Rev. 6 , CD012691 (2017). One of three Cochrane reviews looking at lifestyle treatment of paediatric obesity, in this case in adolescents, which identified 44 completed trials, finding low quality evidence of improvements in BMI and moderate quality evidence of improvements in weight.

Mead, E. et al. Diet, physical activity and behavioural interventions for the treatment of overweight or obese children from the age of 6 to 11 years. Cochrane Database Syst. Rev. 6 , CD012651 (2017). A Cochrane Review, involving 70 RCTs, showing that multicomponent behavioural interventions can lead to small, short-term reductions in BMI and related measures in children aged 6–11 years with obesity.

Ho, M. et al. Effectiveness of lifestyle interventions in child obesity: systematic review with meta-analysis. Pediatrics 130 , e1647–e1671 (2012). To our knowledge, the first systematic review of lifestyle interventions in children and adolescents with obesity to show improvements in cardiometabolic outcomes (LDL cholesterol, triglycerides, fasting insulin and blood pressure), as well as weight.

Clinical Practice Guideline Panel. Clinical practice guideline for multicomponent behavioral treatment of obesity and overweight in children and adolescents: current state of the evidence and research needs. American Psychological Association https://www.apa.org/obesity-guideline/clinical-practice-guideline.pdf (2018).

Nowicka, P. & Flodmark, C. E. Family therapy as a model for treating childhood obesity: useful tools for clinicians. Clin. Child. Psychol. Psychiatry 16 , 129–145 (2011).

Wilfley, D. E. et al. Improving access and systems of care for evidence-based childhood obesity treatment: conference key findings and next steps. Obesity 25 , 16–29 (2017).

Amiri, P. et al. Does motivational interviewing improve the weight management process in adolescents? A systematic review and meta-analysis. Int. J. Behav. Med. 29 , 78–103 (2022).

Kao, T. A., Ling, J., Hawn, R. & Vu, C. The effects of motivational interviewing on children’s body mass index and fat distributions: a systematic review and meta-analysis. Obes. Rev. 22 , e13308 (2021).

Hassapidou, M. et al. European Association for the Study of Obesity (EASO) position statement on medical nutrition therapy for the management of overweight and obesity in children and adolescents developed in collaboration with the European Federation of the Associations of Dietitians (EFAD). Obes. Facts https://doi.org/10.1159/000527540 (2022).

Hoelscher, D. M., Kirk, S., Ritchie, L. & Cunningham-Sabo, L. Position of the Academy of Nutrition and Dietetics: interventions for the prevention and treatment of pediatric overweight and obesity. J. Acad. Nutr. Diet. 113 , 1375–1394 (2013).

Hoare, J. K., Jebeile, H., Garnett, S. P. & Lister, N. B. Novel dietary interventions for adolescents with obesity: a narrative review. Pediatr. Obes. 16 , e12798 (2021).

Lister, N. et al. Nutritional adequacy of diets for adolescents with overweight and obesity: considerations for dietetic practice. Eur. J. Clin. Nutr. 71 , 646–651 (2017).

Andela, S. et al. Efficacy of very low-energy diet programs for weight loss: a systematic review with meta-analysis of intervention studies in children and adolescents with obesity. Obes. Rev. 20 , 871–882 (2019).

Srivastava, G. & Apovian, C. M. Current pharmacotherapy for obesity. Nat. Rev. Endocrinol. 14 , 12–24 (2018).

Apperley, L. J. et al. Childhood obesity: a review of current and future management options. Clin. Endocrinol. 96 , 288–301 (2022).

European Medicines Agency. Saxenda. European Medicines Agency https://www.ema.europa.eu/en/medicines/human/EPAR/saxenda (2022).

US Food and Drug Administration. FDA approves weight management drug for patients aged 12 and older. FDA https://www.fda.gov/drugs/news-events-human-drugs/fda-approves-weight-management-drug-patients-aged-12-and-older (2021).

Kelly, A. S. et al. A randomized, controlled trial of liraglutide for adolescents with obesity. N. Engl. J. Med. 382 , 2117–2128 (2020). To our knowledge, the first RCT of liraglutide, administered daily via subcutaneous injection, in adolescents with obesity.

US Food and Drug Administration. FDA approves novel, dual-targeted treatment for type 2 iabetes. FDA https://www.fda.gov/news-events/press-announcements/fda-approves-novel-dual-targeted-treatment-type-2-diabetes (2022).

Jastreboff, A. M. et al. Tirzepatide once weekly for the treatment of obesity. N. Engl. J. Med. 387 , 205–216 (2022).

Holst, J. J. & Rosenkilde, M. M. GIP as a therapeutic target in diabetes and obesity: insight from incretin co-agonists. J. Clin. Endocrinol. Metab. https://doi.org/10.1210/clinem/dgaa327 (2020).

US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/study/NCT05260021 (2023).

Müller, T. D., Blüher, M., Tschöp, M. H. & DiMarchi, R. D. Anti-obesity drug discovery: advances and challenges. Nat. Rev. Drug Discov. 21 , 201–223 (2022).

Chalklin, C. G., Ryan Harper, E. G. & Beamish, A. J. Metabolic and bariatric surgery in adolescents. Curr. Obes. Rep. 10 , 61–69 (2021).

Albaugh, V. L. et al. Regulation of body weight: lessons learned from bariatric surgery. Mol. Metab. https://doi.org/10.1016/j.molmet.2022.101517 (2022).

Uhe, I. et al. Roux-en-Y gastric bypass, sleeve gastrectomy, or one-anastomosis gastric bypass? A systematic review and meta-analysis of randomized-controlled trials. Obesity 30 , 614–627 (2022).

Inge, T. H. et al. Long-term outcomes of bariatric surgery in adolescents with severe obesity (FABS-5+): a prospective follow-up analysis. Lancet Diabetes Endocrinol. 5 , 165–173 (2017).

Olbers, T. et al. Laparoscopic Roux-en-Y gastric bypass in adolescents with severe obesity (AMOS): a prospective, 5-year, Swedish nationwide study. Lancet Diabetes Endocrinol. https://doi.org/10.1016/S2213-8587(16)30424-7 (2017).

Pratt, J. S. et al. ASMBS pediatric metabolic and bariatric surgery guidelines, 2018. Surg. Obes. Relat. Dis. 14 , 882–901 (2018).

Jarvholm, K. et al. 5-year mental health and eating pattern outcomes following bariatric surgery in adolescents: a prospective cohort study. Lancet Child Adolesc. Health 4 , 210–219 (2020).

Van Der Heijden, L., Feskens, E. & Janse, A. Maintenance interventions for overweight or obesity in children: a systematic review and meta‐analysis. Obes. Rev. 19 , 798–809 (2018).

Park, J., Park, M.-J. & Seo, Y.-G. Effectiveness of information and communication technology on obesity in childhood and adolescence: systematic review and meta-analysis. J. Med. Internet Res. 23 , e29003 (2021).

Brissman, M., Beamish, A. J., Olbers, T. & Marcus, C. Prevalence of insufficient weight loss 5 years after Roux-en-Y gastric bypass: metabolic consequences and prediction estimates: a prospective registry study. BMJ Open 11 , e046407 (2021).

El Ansari, W. & Elhag, W. Weight regain and insufficient weight loss after bariatric surgery: definitions, prevalence, mechanisms, predictors, prevention and management strategies, and knowledge gaps – a scoping review. Obes. Surg. 31 , 1755–1766 (2021).

World Health Organization Regional Office for Europe. Weight Bias and Obesity Stigma: Considerations for the WHO European Region (WHO, 2017).

Puhl, R. M. & Latner, J. D. Stigma, obesity, and the health of the nation’s children. Psychol. Bull. 133 , 557–580 (2007).

Black, W. R. et al. Health-related quality of life across recent pediatric obesity classification recommendations. Children 8 , 303 (2021).

Finne, E., Reinehr, T., Schaefer, A., Winkel, K. & Kolip, P. Changes in self-reported and parent-reported health-related quality of life in overweight children and adolescents participating in an outpatient training: findings from a 12-month follow-up study. Health Qual. Life Outcomes 11 , 1 (2013).

Hill, A. J. Obesity in children and the ‘myth of psychological maladjustment’: self-esteem in the spotlight. Curr. Obes. Rep. 6 , 63–70 (2017).

McGregor, S., McKenna, J., Gately, P. & Hill, A. J. Self‐esteem outcomes over a summer camp for obese youth. Pediatr. Obes. 11 , 500–505 (2016).

Jansen, P., Mensah, F., Clifford, S., Nicholson, J. & Wake, M. Bidirectional associations between overweight and health-related quality of life from 4–11 years: longitudinal study of Australian children. Int. J. Obes. 37 , 1307–1313 (2013).

Mannan, M., Mamun, A., Doi, S. & Clavarino, A. Is there a bi-directional relationship between depression and obesity among adult men and women? Systematic review and bias-adjusted meta analysis. Asian J. Psychiatr. 21 , 51–66 (2016).

Lindberg, L., Hagman, E., Danielsson, P., Marcus, C. & Persson, M. Anxiety and depression in children and adolescents with obesity: a nationwide study in Sweden. BMC Med. 18 , 30 (2020).

Jebeile, H. et al. Association of pediatric obesity treatment, including a dietary component, with change in depression and anxiety: a systematic review and meta-analysis. JAMA Pediatr. 173 , e192841 (2019).

Gow, M. L. et al. Pediatric obesity treatment, self‐esteem, and body image: a systematic review with meta‐analysis. Pediatr. Obes. 15 , e12600 (2020).

Jebeile, H. et al. Treatment of obesity, with a dietary component, and eating disorder risk in children and adolescents: a systematic review with meta-analysis. Obes. Rev. 20 , 1287–1298 (2019). To our knowledge, the first systematic review to show that structured and professionally led weight management interventions in children and adolescents with obesity are associated with reductions in eating disorder risk and symptoms.

Kjeldbjerg, M. L. & Clausen, L. Prevalence of binge-eating disorder among children and adolescents: a systematic review and meta-analysis. Eur. Child Adolesc. Psychiatry https://doi.org/10.1007/s00787-021-01850-2 (2021).

Patton, G. C., Selzer, R., Coffey, C., Carlin, J. B. & Wolfe, R. Onset of adolescent eating disorders: population based cohort study over 3 years. BMJ 318 , 765–768 (1999).

Cortese, S. The association between ADHD and obesity: intriguing, progressively more investigated, but still puzzling. Brain Sci. 9 , 256 (2019).

Griffiths, L. J., Dezateux, C. & Hill, A. Is obesity associated with emotional and behavioural problems in children? Findings from the Millennium Cohort Study. Int. J. Pediatr. Obes. 6 , e423–e432 (2011).

Harrist, A. W. et al. The social and emotional lives of overweight, obese, and severely obese children. Child. Dev. 87 , 1564–1580 (2016).

Van Geel, M., Vedder, P. & Tanilon, J. Are overweight and obese youths more often bullied by their peers? A meta-analysis on the relation between weight status and bullying. Int. J. Obes. 38 , 1263–1267 (2014).

Albuquerque, D., Nóbrega, C., Manco, L. & Padez, C. The contribution of genetics and environment to obesity. Br. Med. Bull. 123 , 159–173 (2017).

Rancourt, D. & McCullough, M. B. Overlap in eating disorders and obesity in adolescence. Curr. Diabetes Rep. 15 , 78 (2015).

House, E. T. et al. Identifying eating disorders in adolescents and adults with overweight or obesity: a systematic review of screening questionnaires. Int. J. Eat. Disord. 55 , 1171–1193 (2022).

Lister, N. B., Baur, L. A., Paxton, S. J. & Jebeile, H. Contextualising eating disorder concerns for paediatric obesity treatment. Curr. Obes. Rep. 10 , 322–331 (2021).

Hagman, E. et al. Effect of an interactive mobile health support system and daily weight measurements for pediatric obesity treatment, a 1-year pragmatical clinical trial. Int. J. Obes. 46 , 1527–1533 (2022).

Swinburn, B. A. et al. The global syndemic of obesity, undernutrition, and climate change: The Lancet commission report. Lancet 393 , 791–846 (2019).

Whitehead, M., Taylor-Robinson, D. & Barr, B. Poverty, health, and covid-19. Br. Med. J. 372 , n376 (2021).

Morrison, K. M. et al. The CANadian Pediatric Weight Management Registry (CANPWR): lessons learned from developing and initiating a national, multi-centre study embedded in pediatric clinical practice. BMC Pediatr. 18 , 237 (2018).

Kirk, S. et al. Establishment of the pediatric obesity weight evaluation registry: a national research collaborative for identifying the optimal assessment and treatment of pediatric obesity. Child. Obes. 13 , 9–17 (2017).

Hagman, E., Danielsson, P., Lindberg, L. & Marcus, C., BORIS Steering Committee. Paediatric obesity treatment during 14 years in Sweden: lessons from the Swedish Childhood Obesity Treatment Register – BORIS. Pediatr. Obes. 15 , e12626 (2020).

Bohn, B. et al. Changing characteristics of obese children and adolescents entering pediatric lifestyle intervention programs in Germany over the last 11 years: an adiposity patients registry multicenter analysis of 65,453 children and adolescents. Obes. Facts 10 , 517–530 (2017).

Seidler, A. L. et al. A guide to prospective meta-analysis. BMJ 367 , l5342 (2019).

Hunter, K. E. et al. Transforming obesity prevention for children (TOPCHILD) collaboration: protocol for a systematic review with individual participant data meta-analysis of behavioural interventions for the prevention of early childhood obesity. BMJ Open 12 , e048166 (2022).

Lister, N. B. et al. Eating disorders in weight-related therapy (EDIT) collaboration: rationale and study design. Nutr. Res. Rev. https://doi.org/10.1017/S0954422423000045 (2023).

Hadjiyannakis, S. et al. Obesity class versus the Edmonton Obesity Staging System for Pediatrics to define health risk in childhood obesity: results from the CANPWR cross-sectional study. Lancet Child Adolesc. Health 3 , 398–407 (2019).

Brown, V. et al. Core outcome set for early intervention trials to prevent obesity in childhood (COS-EPOCH): agreement on “what” to measure. Int. J. Obes. 46 , 1867–1874 (2022). A stakeholder-informed study that identified the minimum outcomes recommended for collecting and reporting in obesity prevention trials in early childhood.

Han, J. C., Lawlor, D. A. & Kimm, S. Y. Childhood obesity. Lancet 375 , 1737–1748 (2010).

Shin, A. C., Zheng, H. & Berthoud, H. R. An expanded view of energy homeostasis: neural integration of metabolic, cognitive, and emotional drives to eat. Physiol. Behav. 97 , 572–580 (2009).

Lennerz, B., Wabitsch, M. & Eser, K. Ätiologie und genese [German]. Berufl. Rehabil. 1 , 14 (2014).

Google Scholar  

Pont, S. J., Puhl, R., Cook, S. R. & Slusser, W. Stigma experienced by children and adolescents with obesity. Pediatrics 140 , e20173034 (2017).

Talumaa, B., Brown, A., Batterham, R. L. & Kalea, A. Z. Effective strategies in ending weight stigma in healthcare. Obes. Rev. 23 , e13494 (2022).

Rubino, F. et al. Joint international consensus statement for ending stigma of obesity. Nat. Med. 26 , 485–497 (2020).

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Children’s Hospital Westmead Clinical School, Sydney Medical School, The University of Sydney, Sydney, New South Wales, Australia

Natalie B. Lister & Louise A. Baur

Institute of Endocrinology and Diabetes, The Children’s Hospital at Westmead, Sydney, New South Wales, Australia

Natalie B. Lister

Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia

Louise A. Baur

Weight Management Services, The Children’s Hospital at Westmead, Sydney, New South Wales, Australia

The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands

Janine F. Felix

Department of Paediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands

Institute of Health Sciences, School of Medicine, University of Leeds, Leeds, UK

Andrew J. Hill

Division of Paediatrics, Department of Clinical Science Intervention and Technology, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden

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Introduction (L.A.B., J.F.F. and N.B.L.); Epidemiology (L.A.B. and J.F.F.); Mechanisms/pathophysiology (L.A.B., J.F.F., T.R. and M.W.); Diagnosis, screening and prevention (L.A.B., N.B.L., T.R., C.S. and M.W.); Management (L.A.B., N.B.L., A.J.H., C.M. and T.R.); Quality of life (L.A.B., N.B.L. and A.J.H.); Outlook (L.A.B., N.B.L., J.F.F., A.J.H., C.M., T.R., C.S. and M.W.); Overview of the Primer (L.A.B. and N.B.L.).

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A.J.H. reports receiving payment for consultancy advice for Slimming World (UK). L.A.B. reports receiving honoraria for speaking in forums organized by Novo Nordisk in relation to management of adolescent obesity and the ACTION-Teens study, which is sponsored by Novo Nordisk. L.A.B. is the Australian lead of the study. T.R. received funding from the German Federal Ministry of Education and Research (BMBF; 01GI1120A/B) as part of the German Competence Network Obesity (Consortium ‘Youth with Extreme Obesity’). T.R. receives payment for consultancy advice related to pharmacological treatment of obesity from Novo Nordisk and Lilly, as well as honoraria for lectures in symposia organized by Novo Nordisk, Novartis and Merck. C.M. receives payments for consultancy advice and advisory board participation from Novo Nordisk, Oriflame Wellness, DeFaire AB and Itrim AB. C.M. also receives honoraria for speaking at meetings organized by Novo Nordisk and Astra Zeneca. C.M. is a shareholder and founder of Evira AB, a company that develops and sells systems for digital support for weight loss, and receives grants from Novo Nordisk for epidemiological studies of the effects of weight loss on future heath. M.W. received funding from the German Federal Ministry of Education and Research (BMBF; 01GI1120A/B) as part of the German Competence Network Obesity (Consortium ‘Youth with Extreme Obesity’). M.W. receives payment for consultancy advice related to pharmacological treatment of obesity from Novo Nordisk, Regeneron, Boehringer Ingelheim and LG Chem, as well as honoraria for speaking in symposia organized by Novo Nordisk, Rhythm Pharmaceuticals and Infectopharm. M.W. is principal investigator in phase II and phase III studies of setmelanotide sponsored by Rhythm Pharmaceuticals. N.B.L., J.F.F. and C.S. declare no competing interests.

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Lister, N.B., Baur, L.A., Felix, J.F. et al. Child and adolescent obesity. Nat Rev Dis Primers 9 , 24 (2023). https://doi.org/10.1038/s41572-023-00435-4

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Health Encyclopedia

Preventing obesity in children, teens, and adults, facts about obesity.

Obesity is a long-term (chronic) disease. It affects growing numbers of children, teens, and adults. Obesity rates among children in the U.S. have doubled since 1980. They have tripled for teens. About 19 out of 100 children ages 2 to 19 are obese. More than 7 out of 20 adults are obese.

Healthcare providers are seeing more of these obesity-related problems in children and teens:

Type 2 diabetes starting at a younger age

Heart and blood vessel disease

Obesity-related depression and social isolation

The longer a person is obese, the more they are at risk for problems. Many chronic diseases are linked to obesity. Obesity may be hard to treat. That's why prevention is very important.

Preventing obesity in children is vital. This is because childhood obesity is more likely to last into adulthood. An obese person has a high risk of diabetes, high blood pressure, and heart disease.

Breastfed babies are less likely to become overweight. And the longer babies are breastfed, the less likely they are to be overweight as they grow older. But many babies fed with formula do grow up to be adults of healthy weight. If your child was not breastfed, it doesn't mean that they can't have a healthy weight. Talk with your child’s healthcare provider if you have concerns.

Children and teens

Young people can become obese from poor eating habits, lack of physical activity, and not getting enough sleep. Genes can also affect a child's weight.

To help prevent obesity in children and teens:

Don’t just focus on a child's weight. Work to change family eating habits and activity levels over time.

Be a role model. Parents who eat healthy foods and do physical activity set an example. A child is more likely to do the same.

Encourage physical activity. Children ages 3 to 5 should have active play each day. Children ages 6 to 17 should have at least 60 minutes of medium physical activity most days of the week. More than 60 minutes of activity may help with weight loss and keeping a healthy weight.

Reduce screen time. The American Academy of Pediatrics (AAP) does not recommend screen time for children under the ages of 18 to 24 months. AAP recommends a 1-hour screen time limit for children ages 2 to 5. And AAP recommends an appropriate parent-monitored media use plan for older children. Do not allow screens in your child's room. Have your child stop using screens at least 1 hour before bed.

Encourage children to eat only when hungry. Tell them to eat slowly.

Don't use food as a reward. Don't keep food away from your child as a punishment.

Serve healthy foods and drinks. These include fat-free or low-fat milk, fresh fruit, and vegetables. Don't buy soft drinks or snacks that are high in sugar and fat.

Fill half of your child's plate with fruits and vegetables. Recommended serving sizes vary based on age, sex, height, weight and physical activity levels. Go to https://www.myplate.gov/myplate-plan to see your child's personalized diet recommendations.

Encourage your child to drink water instead of drinks with added sugar. These include soft drinks, sports drinks, and fruit juice drinks.

Promote good sleep with a consistent bedtime routine. Preschoolers need 11 to 13 hours of sleep per day, including naps. Children ages 6 to 12 need 9 to 12 hours of uninterrupted sleep a night. And teens ages 13 to 18 need 8 to 10 hours.

Good eating habits and physical activity can help prevent obesity. Tips for adults include:

Keep a food diary. Write down what you eat, where you eat, and how you feel before and after you eat.

Make half your plate and vegetables. Recommended serving sizes vary based on age, sex, height, weight and physical activity levels. Go to https://www.myplate.gov/myplate-plan to see your personalized diet recommendations.

Choose whole-grain foods. These include brown rice and whole-wheat bread. Don't eat foods made with refined white sugar, flour, high-fructose corn syrup, or saturated fat.

Weigh and measure food. This is so you can learn healthy portion sizes. For instance, a 3-ounce serving of meat is the size of a deck of cards. Don't order super-sized menu items.

Learn to read food nutrition labels and use them. Keep the number of portions you are really eating in mind.

Balance your food checkbook. If you eat more calories than you burn, you will gain weight. Weigh yourself each week.

Don't eat foods that are high in energy density. This means foods that have a lot of calories in small amounts. For instance, a cheeseburger with fries can have as much as 1,000 calories and 30 or more grams of fat. Order a grilled chicken sandwich or a plain hamburger and a small salad with low-fat dressing instead. You can avoid hundreds of calories and lower your fat intake. For dessert, have a serving of fruit, yogurt, a small piece of angel food cake, or a piece of dark chocolate.

Reduce portion sizes. Using a smaller plate can help you do this.

Exercise each week. Aim for at least 150 minutes of medium to intense physical activity per week. For instance, this can be 30 minutes of exercise 5 days a week. Examples of medium-intensity exercise are walking a 15-minute mile. Or weeding and hoeing a garden. Running is a more intense activity.

Build activity into your day. Look for ways to get 10 or 15 minutes of some type of activity during the day. Walk around the block. Walk up and down a few flights of stairs.

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IELTS essay, topic: Children these days are suffering from obesity, why and how can it be solved?

• IELTS Essays - Band 8

Modern children are suffering from the diseases that were once considered to be meant for adults only. Obesity is a major disease prevalent among children. What are its causes and what solutions can be offered?

Nowadays, the increasing rate of overweight children and adults is a worldwide health issue. Obesity is a major problem which is increasing day by day in children. There are various reasons behind it. This essay will discuss the causes of obesity and offer some solutions.

The first cause of obesity is junk food. It is often seen that mostly children are fond of burgers, pizzas, noodles and . These types of foods are easily available to them in school canteens. Children love to purchase chips, , ice-cream for lunch. Moreover, in this modern era, parents are working and they do not have time to cook at home. Parents often buy dinner for their children instead of preparing food at home. This calorie-rich diet is making children obese. This problem can be solved by teaching children to cook healthy foods for themselves and banning junk foods and fizzy drinks in schools. This diet can be replaced by milk, juice and fruits for lunch.

The second cause of obesity is . It is true that the use of computers and television is increasing children. They spend most of their time watching television or playing video games on a computer. This technological advancement has reduced the level of physical activity in this specific age group. This issue can be resolved by encouraging children to do physical exercises. Parents can take their children to park to encourage playing with friends. Furthermore, schools can add sports in their curriculum to maintain physical fitness in their students.

To sum up, it is clear that main causes of obesity are unhealthy eating and not enough physical activities. This ailment can be prevented and treated by healthy eating and physical exercises.

This is a good essay. There are only a few minor errors that could have been easily prevented by proofreading this essay one last time before submission (mouse over the words underlined in blue shows corrections). Overall, this work seems worthy of IELTS Band 8. Keep up the good work! Click here to see more IELTS essays of Band 8

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This is nice… I need 8 + standard writing task t material… Plz help me

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Research Article

Interventions for obesity among schoolchildren: A systematic review and meta-analyses

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Validation, Writing – review & editing

Affiliation Unit of Sports Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Wilayah Persekutuan, Malaysia

Roles Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Validation, Writing – original draft

* E-mail: [email protected]

Affiliation Department of Family Medicine, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia

• Mohamad Shariff A. Hamid, 
• Shariff Ghazali Sazlina

• Published: January 9, 2019
• https://doi.org/10.1371/journal.pone.0209746
• Reader Comments

Childhood overweight and obesity has emerged as a major public health threat worldwide with challenges in its management. This review assessed the effectiveness of interventions for childhood overweight and obesity.

A systematic literature search was conducted using CINAHL, EMBASE, Ovid MEDLINE, PsycINFO and SPORTDiscus databases to retrieve articles published from 1st January 2000 to 31 st December 2017. Randomised controlled trials (RCTs) and quasi-experimental studies comparing different strategies in managing overweight and obesity among schoolchildren (6 to 12 years of age) were included. The main outcomes of interest were reductions in weight related variables included anthropometry and body composition measurements. All variables were analysed using random effects meta-analyses.

Fourteen studies were reviewed, 13 were RCTs and one was a quasi-experimental study. The risk of bias for randomisation was low risk for all of RCTs except for one, which was unclear. The risk of bias for randomisation was high for the quasi-experimental study. Most interventions incorporated lifestyle changes and behavioural strategies such as coping and problem solving skills with family involvement. The meta-analyses did not show significant effects of the intervention in reducing weight related outcomes when compared with controls.

Meta-analyses of the selected studies did not show significant effects of the interventions on weight related outcomes among overweight and obese schoolchildren when compared with controls. The role of interdisciplinary team approaches with family involvement using behaviour and lifestyle strategies to curb obesity among schoolchildren is important.

Citation: A. Hamid MS, Sazlina SG (2019) Interventions for obesity among schoolchildren: A systematic review and meta-analyses. PLoS ONE 14(1): e0209746. https://doi.org/10.1371/journal.pone.0209746

Editor: Shahrad Taheri, Weill Cornell Medical College in Qatar, QATAR

Received: April 24, 2018; Accepted: December 11, 2018; Published: January 9, 2019

Copyright: © 2019 A. Hamid, Sazlina. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper.

Funding: We would like to thank Universiti Putra Malaysia for their support in conducting this review.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Childhood overweight and obesity is a serious public health problem worldwide in the 21 st century. The prevalence of overweight and obesity has increased in almost all countries worldwide especially in economically developed countries [ 1 – 3 ].

The traditional perception that a heavy child is a healthy child has changed based on evidence that overweight and obesity in childhood is associated with a wide range of serious health complications [ 4 ]. Overweight and obese children are more likely to have cardiovascular (e.g. hypertension, heart disease, high cholesterol), metabolic (e.g. type 2 diabetes), and psychosocial illnesses (e.g. eating disorders, depression and low self-esteem) than their normal-weight counterparts [ 1 ]. Also, children who were overweight and obese are at greater risk of premature illness and death in later life [ 5 ].

The United Nations International Children’s Emergency Fund (UNICEF) defined overweight and obesity as excessive and unbalanced nutrition to a point at which health is adversely affected [ 6 ]. The aetiology and pathogenesis of overweight and obesity often involve complex interaction between genetic makeup and environmental factors. Adoption of sedentary behaviour (physical inactivity, watching television and sitting in front of computer) combined with excess caloric consumption are examples of the environmental factors that are potentially modifiable in the battle against overweight and obesity [ 7 , 8 ].

While the fundamental principles of weight management in children might seems straightforward through reduction in energy intake and increase energy expenditure, the results of current intervention studies on childhood overweight and obesity prevention are variable. A systematic review and meta-analyses on the management of obesity among children less than 18 years of age concluded that lifestyle interventions may lead to improvements in weight and cardio-metabolic outcomes [ 9 ]. However, the evidence is limited on the optimal duration of the intervention and its long-term effectiveness. A more recent review conducted in 2015 that focused only on pre-school childhood obesity (<6 years of age) found multidisciplinary and intensive interventions have some evidence of efficacy in reducing body fat and fat mass [ 10 ]. Therefore, the objective of this review was to examine the effectiveness of interventions (including dietary, physical activity and behavioural interventions) in reducing weight related outcomes among overweight and obese children 6 to 12 years of age. It is hoped that the results from this review would provide information and guide medical practitioners and health policymakers on the management of childhood overweight and obesity.

Materials and methods

A systematic review was conducted to explore the current approaches on managing overweight and obesity among schoolchildren. The review question was: How effective are current intervention(s) in reducing weight related outcomes including anthropometry and body composition among overweight or obese schoolchildren?” This review was registered with the International prospective register of systematic reviews (PROSPERO) CRD42016037918 [ https://www.crd.york.ac.uk/prospero ].

Study selection

The study design considered in this review included randomised controlled trials (RCTs) and quasi-experimental studies. We included studies that compared strategies on the management of overweight and obesity among schoolchildren aged between 6 and 12 years of age to usual care or minimal advice. Overweight or obese were defined based on several criteria, including BMI z-scores (or standard deviation (SD) scores) [ 11 ], BMI percentile [ 12 ], BMI cut-offs based on age and gender [ 13 ] and percentage of weight for height [ 14 ]. However, studies that classified overweight or obese using other definitions were also considered. The primary outcome of this review was a change in weight related outcomes, which included anthropometry (including weight, standard body mass index (BMI) in kg/m 2 , BMI percentile, BMI z-scores and standard deviation scores, percent of overweight, weight for height percentage, waist circumference) and body composition (including lean body mass, body fat and fat mass).

The secondary outcomes measured were changes in physical activity and dietary behaviour. Physical activity assessed using physical activity questionnaires, and/or activity monitors (such as accelerometer and pedometer) as well as assessment of sedentary activities were considered in this review. Studies reporting changes in dietary intake including carbohydrate and fat intake as well as caloric estimates were included. We excluded studies that focused on interventions for preschool age groups or adolescent, interventions on prevention of obesity, on drug treatment of obesity or on normal weight children.

Studies that included school-based or non-school based (home, clinic or community) interventions were reviewed. Interventions could include one or a combination of: (1) one-to-one or group counselling or advice, (2) self-directed or prescribed physical activity programmes (with or without supervisions), (3) dietary intervention or 4) behavioural strategies. Interventions delivered by one or more providers (healthcare providers, exercise professionals, or dietitians) were considered. There was no restriction on the type and content of the control group. Interventions could be compared with usual care (no active intervention), participants listed on waiting list or those who received minimal advice.

Data sources & search strategy

Studies were electronically searched using EBSCOhost interface for Medline, CINAHL, Psychology and Behavioural Sciences Collection and SPORTDiscus, and EMBASE databases. We adhered to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines [ 15 ]. The search strategy performed using the Medical Subject Heading (MeSH) terms and keywords. For children, search was done using the MeSH term child and the keywords child$ OR children. For overweight we used a combination of MeSH terms as follows: overweight OR obesity OR pediatric obesity. Diet [MeSH] OR diet, food and nutrition [MeSH] were used for diet and exercise [MeSH] OR physical activity for exercise and behavior therapy [MeSH]. For anthropometry we used body mass index [MeSH] OR body composition [MeSH] OR anthropometry [MeSH].

Peer-reviewed published articles between 1st January 2000 and 31 st December 2017 were used. Published systematic reviews on the management of obesity among schoolchildren were used as the source of randomised controlled trials (RCTs). Potential eligible studies were hand searched from the reference lists of review articles and included studies. We limited the search to include studies that involved children between 6 and 12 years of age. All the titles, abstracts, and full-text of each study retrieved from the search were screened by both reviewers using a standardized form for study eligibility. In cases where there was any doubt on the paper eligibility, the issue was resolved through discussion until a consensus was reached. In view of limited resources for translation, articles that were published in the English language were considered in this review.

Data extraction

The titles and abstracts of all studies retrieved were reviewed following the criteria for study selection to decide if the full-text manuscripts were required for further evaluation. Each full-text article retrieved was evaluated systematically according to the study’s: (1) objective (on the effectiveness of interventions), (2) characteristics of the study (study design, participants’ age, behavioural theoretical model, and sample size), (3) contents of the intervention (intervention strategies, intervention provider, length of intervention and follow-up contacts), (4) targeted outcome/s and (5) major findings.

Methodological quality assessment of individual studies

Each selected study was evaluated for its methodological quality using the Cochrane Collaboration tool for assessing the risk of bias (the Cochrane Handbook for Systematic Review of Interventions) [ 16 ]. It covers: a) sequence generation b) allocation concealment c) blinding d) incomplete outcome data (e.g. dropouts and withdrawals) e) selective outcome reporting and f) other areas of bias. For each domain in the tool, the procedures undertaken for each study were described. Each study was rated as ‘high’, ‘low’ or ‘unclear’ risk of bias based on a judgement of the gathered information. These judgements were made independently by two review authors based on the predetermined criteria and later discussed in a meeting until a consensus achieved.

Data synthesis and analyses

We conducted a narrative synthesis based on the primary and secondary outcomes of this review. The primary outcome measures were pooled and calculated using the statistical software RevMan 5.3, according to the Cochrane Handbook for Systematic Reviews of Interventions [ 16 ]. Attempts to contact the authors to obtain the raw data for data analysis was made but to no avail. The results of the BMI z-score, waist circumference and body fat percentage were analysed using weighted or standardized mean differences as a measure of effect size, with 95% confidence intervals. Since the participant demographics and clinical settings differed among studies, we assumed the presence of heterogeneity a priori. Therefore, we used a random-effects model to pool the results. We assessed heterogeneity using the Cochran’s Q statistic of heterogeneity with reported p-value and the degree of inconsistency across studies was quantified using I 2 . In studies with three arm RCTs, each of the intervention group was analysed independently and compared with the control group. A funnel plot was performed to determine the presence of potential publication bias using the statistical software RevMan 5.3.

Literature search

Three hundreds and two articles were identified through the five databases and cross referencing. Twenty were removed due to duplication. After screening the titles and abstracts, 69 full-text articles were retrieved and assessed for eligibility. Fifty-five articles were excluded because they did not fulfil the selection criteria. The reasons for exclusion included participants age were not between 6 and 12 years of age (n = 35), studies identified were neither RCT nor quasi (n = 13), the comparison group was with normal weight children (n = 1), intervention focused on diabetes prevention (n = 1), not an original research article (n = 2), not in English language (n = 1), and data presented was on cost-analysis (n = 1). A total of 14 articles were included in the narrative synthesis and eight were included in the meta-analyses. The flow diagram for the study selection is described in Fig 1 .

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Characteristics of selected studies

Table 1 summarises the characteristics of the selected studies. Thirteen RCTs [ 17 – 29 ] and one three-arm quasi-experimental study were reviewed [ 30 ]. Three RCTs were conducted in North America [ 17 , 22 , 25 ], three in Israel [ 27 , 28 , 30 ], the remaining studies were conducted in Netherlands [ 18 ], Norway [ 25 ], Finland [ 21 ], New Zealand [ 23 ], United Kingdom [ 29 ], Australia [ 20 ] and Malaysia [ 24 ]. As for the study setting, three studies were conducted in the community [ 27 – 29 ], five in the hospitals [ 18 – 20 , 26 , 30 ], and three in the clinics [ 17 , 24 , 25 ], of which two were in academic research clinics [ 17 , 24 ]. Two studies were home-based [ 22 , 23 ], and another was conducted in school [ 21 ].

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Five studies recruited children who were overweight or obese [ 17 , 18 , 22 , 23 , 25 ], while nine recruited only obese children [ 19 – 21 , 24 , 26 – 30 ]. All studies except one excluded participants with comorbidities [ 25 ]. Most studies used BMI percentile to classify overweight or obese [ 17 , 19 , 22 , 24 , 25 , 27 – 30 ]. Three studies used BMI z-scores [ 18 , 20 , 26 ], one used weight for height percentage [ 21 ] and one used the International Obesity Task Force cut points [ 23 ] to classify overweight or obese. Interestingly, the definition used to classify overweight and obese differs in the included studies despite using the same measures. For example, some studies defined obese as BMI percentile >94 th centile [ 22 , 28 , 30 ] while others as BMI percentile >98 th centile [ 27 , 29 ].

All studies had interventions that integrated interdisciplinary approaches involving parent or family. Selected studies incorporated either a combination of behavioural strategies, physical activity, and dietary component [ 17 – 19 , 21 , 24 , 25 , 29 ], behavioural strategies and physical activity [ 22 , 23 ] or physical activity and dietary component without behavioural strategies [ 20 , 26 – 28 , 30 ]. All interventions were delivered by a group of healthcare providers (psychologist, dietitian/nutritionist, physical/sport therapist) except in one study where the intervention was delivered by a clinical psychology graduate student [ 17 ]. One study used short message services [ 18 ], while another used an automated interactive voice response system [ 25 ] to maintain behavioural change. Only five studies incorporated health behavioural theories in their interventions, namely social learning and cognitive theory [ 29 ] alone or combined with behavioural theories or models [ 18 , 23 ], social ecological theory [ 25 ] or the trans-theoretical model [ 30 ]. The duration of intervention varied between 8 weeks and 12 months. In nine studies participants and their families were followed up for 12 to 24 months [ 17 – 21 , 25 , 26 , 29 , 30 ]. Six RCTs were compared with usual care or wait-listed groups [ 17 , 19 , 20 , 23 , 24 , 29 ] while the others were compared with groups that received minimal advice.

All studies assessed weight related measurements as their primary outcomes. Seven studies used BMI z-scores [ 17 , 18 , 20 , 23 – 26 ] and two studies included standard BMI (kg/m 2 ) [ 17 , 22 ] as their primary outcomes. Other studies also included body fat [ 26 ], percentage of overweight [ 17 , 19 ] and weight for height percentage [ 21 ] as their primary outcomes. Six studies measured body composition such as body fat, fat mass and lean body mass as their outcomes [ 19 , 23 , 26 – 29 ]. Five studies measured waist circumference as their outcome [ 19 , 20 , 23 , 29 , 30 ]. One study measured skinfold thickness as their outcome [ 27 ]. However, 11 studies presented more than one weight related outcomes as their outcome measures [ 17 , 19 – 21 , 23 , 24 , 26 – 30 ].

Eight studies measured changes in physical activity and sedentary behaviour including screen time [ 17 , 22 – 25 , 27 – 29 ]. In three studies, the level of physical activity was measured using the accelerometers [ 17 , 22 , 24 ]. Seven studies measured changes in dietary intake including consumptions of unhealthy snacks as outcomes [ 17 , 18 , 22 , 23 , 25 , 26 , 28 ].

Study quality

The risk of bias for randomisation was unclear and low for all 13 RCTs [ 17 – 29 ]. The risk of bias for randomisation among quasi-experimental studies was high as expected. The quasi-experimental study stated random assignment of participants in their interventions. However, details on the randomisation technique was not elaborated [ 30 ].The allocation concealment was described in six (43%) studies [ 18 , 20 – 24 ]. Blinding of participant and personnel was lacking in all studies as anticipated because of the nature of the interventions. In addressing detection bias, blinding of outcome assessment was unclear in most studies. In three studies the outcome measures were performed by assessors blinded to participants’ grouping [ 20 , 22 , 24 ]. The risk for incomplete outcome data was low for all studies except for one [ 29 ]. Sacher et. al (2010) declared loss to follow-up among their participants but did not apply intention to treat analysis [ 29 ]. The proportion of studies with low, unclear and high risk of bias is presented in Fig 2 .

https://doi.org/10.1371/journal.pone.0209746.g002

Effect of interventions compared with controls

Five studies that incorporated behavioural strategies with exercise and dietary interventions reported positive effects on the weight related outcomes [ 17 , 19 , 21 , 25 , 29 ]. Other studies that included behavioural skills and exercise alone [ 22 ] or combination of exercise and dietary interventions [ 27 , 28 , 30 ] also reported positive effects on the weight related outcomes. Of the seven RCTs that measured BMI z-score, four showed significant reductions among participants in the intervention compared to controls [ 17 , 21 , 25 , 29 ]. Three of these studies showed reductions at 6-months follow up [ 17 , 25 , 29 ], of which two studies delivered their interventions in groups sessions [ 25 , 29 ]. Two studies that incorporated family group sessions of behavioural strategies with exercise and dietary interventions showed no reductions in the BMI z-scores when compared to control groups [ 18 , 24 ]. One of these RCTs used SMS to encourage self-monitoring and provided personalised feedback [ 18 ]. Two RCTs that measured BMI percentile also showed reductions at post-intervention when compared to their controls [ 27 , 28 ]. Both studies incorporated group-based diet and physical activity programs with family engagement. The quasi experimental study found dietary intervention alone or combined with physical activities leads to significant reductions in BMI z-scores compared to exercise intervention alone [ 30 ].

Four out of eight RCTs showed increased physical activity in the intervention group compared to the control [ 22 , 27 – 29 ]. One study also showed reduction in sedentary activity among participants in the intervention group. The change was sustained at 6-months follow-up [ 29 ]. Seven RCTs measured dietary intake behaviour as their outcomes, which included carbohydrate and fat intake as well as estimation of caloric intake [ 13 – 16 , 18 , 19 ]. Only two studies showed significant reductions in dietary or caloric intake when compared to the control groups at post-intervention, however, they did not follow up the participants [ 22 , 23 ]. One study showed reductions in fat and caloric intake from snacks and reduction in snack intake during watching television [ 22 ].

All community-based intervention studies reported positive effects on changes of BMI z-score, BMI percentile, waist circumference and/or skinfolds, as well as improvement in sedentary behaviours [ 27 – 29 ]. However, only one study followed participants up to 12 months and showed sustained effects on these outcomes [ 29 ]. One of the three hospital-based studies [ 29 ], one of the two home-based [ 22 ], and each of the clinic-based [ 17 ] and school-based [ 21 ] interventions reported positive effects on the outcomes.

We performed meta-analyses to determine the effect of interventions on changes in BMI z-score, waist circumference and body fat percentage based on different intervention strategies. Some of the selected studies varied in their primary outcomes, therefore, data from studies with similar outcomes were pooled and analysed. Data from eight RCTs (n = 969 participants) were pooled to determine the effects of intervention strategies on the changes of BMI z-scores. However, two of the studies were 3-arm RCTs, which we analysed each intervention separately. No statistically significant difference was found between intervention and controls (standardised mean difference = - 0.14; 95% CI = - 0.87, 0.60; p = 0.72) (see Fig 3 ) [ 17 , 18 , 20 , 23 – 26 , 29 ]. A meta-analyses on three RCTs (n = 434 participants) did not show significant positive effects of any intervention strategies on the changes of waist circumference compared to controls (standardised mean difference = -0.25; 95% CI = -0.51, 0.01; p = 0.06) (see Fig 4 ) [ 20 , 23 , 29 ]. Five RCTs (n = 463 participants) pooled data showed no significant difference in the changes of body fat percentage between intervention and control (standardised mean difference = 0.30; 95% CI = - 0.17, 0.76; p = 0.21) (see Fig 5 ) [ 23 , 26 – 29 ].

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https://doi.org/10.1371/journal.pone.0209746.g004

https://doi.org/10.1371/journal.pone.0209746.g005

We only present a funnel plot for the BMI z-score outcome but not for the BMI percentile and body fat percentage. This is because a funnel plot with fewer than 10 studies in a meta-analysis would lead to low power of analysis to distinguish the chance from real asymmetry [ 31 ]. Fig 6 depicts the funnel plot for the meta-analysis on the effects of the intervention on the changes in BMI z-score of the selected studies in our review. There was an asymmetry of the plot to suggest presence of publication bias.

https://doi.org/10.1371/journal.pone.0209746.g006

We conducted this review to evaluate the effectiveness of interventions on weight related outcomes (BMI z-score, BMI percentile and body fat percentage) and lifestyle outcomes (physical and sedentary activities, and dietary behaviour) among overweight or obese schoolchildren.

Our narrative synthesis found studies that incorporated behavioural lifestyle interventions reported positive effects on weight related outcomes. Previous reviews and meta-analyses reported interventions that incorporate lifestyle modifications including dietary restriction, physical activities (exercise) alone or in combination leads to larger effects on BMI, BMI z-scores and body composition, as well as reduced unhealthy dietary intake when compared to controls [ 9 , 32 , 33 ]. Moreover, a previous systematic review found addition of pharmacological intervention to behavioural lifestyle intervention led to only small effects on BMI and BMI z-score. [ 33 ]. Hence, this emphasised that behavioural lifestyle modification is utmost important in the management of obesity in children.

Studies that integrated behavioural skills into the lifestyle modifications intervention showed positive effects on the reductions of BMI z-scores, BMI percentile, waist circumference and body fat, as well as improved physical, sedentary and dietary behaviours. The parents of children in the trials were taught coping and problem-solving skills, which could have facilitated the weight reduction, hence, improved outcomes. A previous case control study that examined family functioning, expressed emotion and coping skills found mothers’ negative expressed emotion and coping skills were related to the child being overweight [ 34 ]. Hence, such behavioural skills should be incorporated as strategies in the management of obesity in children.

In this review, all studies that engaged family members in their intervention showed positive effects on weight related outcomes. Such findings are consistent with previous reviews which reported family based interventions with parental involvement led to reductions in BMI, BMI z-scores and body composition [ 32 , 35 ]. The engagement of parents in these trials facilitated their children in choosing healthier behaviour in addition to acting as role models for their children.

In most studies with positive effects, the delivery of the intervention involved interdisciplinary approaches involving various healthcare practitioners including dietitians, psychologists and physical or sports therapists. Moreover, in some of these studies, intervention sessions were conducted in groups. A previous systematic review on childhood obesity showed that behavioural lifestyle interventions delivered by trained specialised interventionists were effective for obesity [ 36 ]. Continuous external support from other people, or professionals may be important in achieving and maintaining goals.

Our review found that the studies were set in various settings, including in the community, school, home and the hospital. All community-based interventions reported positive effects on the primary outcomes. Our findings are consistent with previous systematic reviews which reported positive outcomes from combined lifestyle interventions (diet and physical activity) delivered in the community [ 36 ]. It was anticipated that community-based interventions would be more cost-effective compared to clinic or hospital settings. An economic evaluation on 10 RCTs reported lifestyle interventions are potentially cost-effective for obese children between 10 and 11 years of age. Its impact on health benefits and cost-savings however, would only be evident in their 6 th or 7 th decade of life [ 37 ].

The outcome measured in majority of the studies varied. Various reference datasets for weight related outcomes were used, which led to different definitions of obesity in children. The BMI z-score was often used as an outcome measure in children, however, its role in childhood obesity has been challenged. In children aged less than 9 years, BMI z-score is a weak to moderate predictor of total fat mass and body fat percentage [ 38 ]. In addition, it is also a weak predictor of total body fat changes over time with poor specificity [ 39 , 40 ]. Hence, in clinical practice, changes in body composition among obese children should not solely be monitored using BMI z-score.

Our meta-analyses showed the effects of interventions on BMI z-score, waist circumference and body fat measurements were inconclusive for the management of childhood obesity. We are not able to make comparison with a previous review [ 9 ] as they pooled standard BMI data rather than BMI z-score, waist circumference or body fat. Further their review also included adolescents. The inconclusive findings from our meta-analyses could be due to differences in intervention strategies.

Our review provides insight into the impact of lifestyle interventions combined with behavioural strategies in reducing the weight related outcomes among overweight and obese schoolchildren. The involvement of family members in the treatment of overweight and obesity could not be overemphasised. The intervention one chooses would depend on the resources in the school and the community. Using dedicated personnel to deliver the intervention was effective, but the cost and human resources demand would be high. In addition, strategies attempting to reduce unhealthy behaviours such as reducing sedentary behaviours and adopting healthy dietary intake seem to be more effective. Parents could be trained and empowered to promote the lifestyle changes required for the management of obesity in children [ 41 ].

This review included both randomized and non-randomized controlled trials to provide more comprehensive views of various interventions aimed to reduce weight related outcomes. We also evaluated the effects of intervention on waist circumference and body fat percentage not just on BMI measures as these parameters are commonly monitored in clinical practice. Several limitations need to be mentioned in this review. Even though we have employed an extensive search strategy, we limited the publications to English language only, due to limited resources. Hence, the effectiveness of the interventions could be overrepresented. Our review only included RCTs and quasi-experimental studies, and not cohort studies. The latter study design would provide a better reflection of clinical practice. Our search strategy was specific for diet, nutrition and physical activity interventions. Hence, publications that used term such as weight management were not captured. Most studies included in this review had high or unclear risk of bias with regards to the allocation concealment and blinding of the assessors. Therefore, the findings reported should be interpreted with caution. Most studies also had high or unclear risk of bias for blinding of participants and personnel. However, these were unavoidable in view of the nature of the intervention. In addition, unpublished studies were not identified, thus, publication bias is possible. The funnel plot showed presence of possible publication bias which could be attributed to studies with small sample size and possibly with negative results were not published. Cost-effectiveness of interventions were not included in this review, which is an important aspect to consider when choosing an intervention. Hence, it should be considered in future reviews.

Our meta-analyses showed that current interventions for the management of obesity among schoolchildren on weight related outcomes were inconclusive. However, based on the narrative synthesis, the role for behavioural lifestyle interventions with interdisciplinary team approaches and family involvement is crucial to curb obesity among schoolchildren. But more robust studies are needed to determine its effectiveness.

Supporting information

S1 file. prisma checklist..

https://doi.org/10.1371/journal.pone.0209746.s001

• View Article
• PubMed/NCBI
• Google Scholar
• 6. ASEAN/UNICEF/WHO. Regional report on nutrition security in ASEAN, Volume 2. Bangkok, UNICEF; 2016. Available from: http://asean.org/?static_post=regional-report-nutrition-security-asean-volume-2
• 11. World Health Organization. WHO | BMI-for-age (5–19 years). WHO. 2017 [cited 2018 Sep 7]. Available from: http://www.who.int/growthref/who2007_bmi_for_age/en/
• 12. Centers for Disease Control and Prevention. Defining childhood obesity. Available from: https://www.cdc.gov/obesity/childhood/defining.htmlCe
• 16. Higgins JPT, Green. Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0. The Cochrane Collaboration; 2011.

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Dietary and Lifestyle Risk Factors of Obesity Among Young Adults: A Scoping Review of Observational Studies

• Published: 01 December 2023
• Volume 12 , pages 733–743, ( 2023 )

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• Ke Xin Lee 1 ,
• Kia Fatt Quek 1 &
• Amutha Ramadas 1  

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Purpose of Review

Obesity is a growing public health concern worldwide, especially among young adults. This scoping review aims to identify and summarize the current evidence on dietary and lifestyle risk factors associated with obesity among young adults.

Recent Findings

A scoping review was performed using the PRISMA-ScR guidelines. A systematic search of five electronic databases published from inception to October 2023 was conducted. A total of 46 observational studies met the inclusion criteria and were included in the review. The findings suggest that high intake of energy-dense foods, unhealthy eating habits, poor sleep quality, and increased screen time were significant risk factors for obesity among young adults. In contrast, the association between obesity and sedentary behavior, low physical activity levels, alcohol consumption, and smoking habits was inconclusive.

The reviewed evidence suggests that unhealthy dietary habits and lifestyle behaviors are associated with an increased risk of obesity among young adults. The findings highlight the need for further research on these modifiable risk factors to prevent and manage obesity among young adults.

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Data Availability

Data related to this review are available within the article and as supplementary materials.

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WHO Consultation on Obesity, World Health Organization. Obesity: Preventing and managing the global epidemic. Report of a WHO Consultation. World Health Organ Tech Rep Ser. 2000;894:i–xii, 1–253.

Swinburn BA, Sacks G, Hall KD, McPherson K, Finegood DT, Moodie ML, Gortmaker SL. The global obesity pandemic: Shaped by global drivers and local environments. Lancet. 2011;378(9793):804–14. https://doi.org/10.1016/S0140-6736(11)60813-1 .

Article   PubMed   Google Scholar  

National Heart, Lung, and Blood Institute. Overweight and obesity: Causes and risk factors. 2022. https://www.nhlbi.nih.gov/health/overweight-and-obesity/causes . Accessed 17 Nov 2023.

World Obesity Federation. World Obesity Atlas 2023. https://data.worldobesity.org/publications/?cat=19 . Accessed 17 Nov 2023.

Ellison-Barnes A, Johnson S, Gudzune K. Trends in obesity prevalence among adults aged 18 through 25 years, 1976–2018. JAMA. 2021;326(20):2073–4. https://doi.org/10.1001/jama.2021.16685 .

Article   PubMed   PubMed Central   Google Scholar  

Poobalan A, Aucott L. Obesity among young adults in developing countries: A systematic overview. Curr Obes Rep. 2016;5(1):2–13. https://doi.org/10.1007/s13679-016-0187-x .

Arnett JJ. Emerging adulthood. A theory of development from the late teens through the twenties. Am Psychol. 2000;55(5):469–80.

Lanoye A, Brown KL, LaRose JG. The transition into young adulthood: A critical period for weight control. Curr Diab Rep. 2017;17(11):114. https://doi.org/10.1007/s11892-017-0938-4 .

Poobalan AS, Aucott LS, Precious E, Crombie IK, Smith WC. Weight loss interventions in young people (18 to 25 year olds): A systematic review. Obes Rev. 2010;11(8):580–92. https://doi.org/10.1111/j.1467-789X.2009.00673.x .

Article   CAS   PubMed   Google Scholar  

Cheng HL, Medlow S, Steinbeck K. The health consequences of obesity in young adulthood. Curr Obes Rep. 2016;5:30–7. https://doi.org/10.1007/s13679-016-0190-2 .

Parcel GS, Muraskin LD, Endert CM. Community education. Study group report. J Adolesc Health Care. 1988;9(6 Suppl):41S-45S. https://doi.org/10.1016/0197-0070(88)90008-3

Tricco AC, Lillie E, Zarin W, O’Brien KK, Colquhoun H, Levac D, et al. PRISMA extension for scoping reviews (PRISMA-ScR): Checklist and explanation. Ann Intern Med. 2018;169(7):467–73. https://doi.org/10.7326/M18-0850 .

Cilliers J, Senekal M, Kunneke E. The association between the body mass index of first-year female university students and their weight-related perceptions and practices, psychological health, physical activity and other physical health indicators. Public Health Nutr. 2006;9(2):234–43. https://doi.org/10.1079/phn2005846

Nisar N, Qadri MH, Fatima K, Perveen S. Dietary habits and lifestyle among the students of a private Medical University Karachi. J Pak Med Assoc. 2009;59(2):98–101.

PubMed   Google Scholar  

Al-Rethaiaa AS, Fahmy AEA, Al-Shwaiyat NM. Obesity and eating habits among college students in Saudi Arabia: A cross-sectional study. Nutr J. 2010;9:39. https://doi.org/10.1186/1475-2891-9-39 .

Hayatbakhsh MR, O’Callaghan MJ, Mamun AA, Williams GM, Clavarino A, Najman JM. Cannabis use and obesity and young adults. Am J Drug Alcohol Abuse. 2010;36(6):350–6. https://doi.org/10.3109/00952990.2010.500438 .

Elebiary H. Prevalence of overweight and obesity in relation to lifestyle among Saudi Arabian female nursing students. Med J Cairo Univ. 2010;78:377–85.

Google Scholar  

Chock T. The influence of body mass index, sex, and race on college students’ optimistic bias for lifestyle healthfulness. J Nutr Educ Behav. 2011;43(5):331–8. https://doi.org/10.1016/j.jneb.2010.09.016 .

Stanziano DC, Butler-Ajibade P. Differences in health-related behaviors and body mass index risk categories in African American women in college. J Natl Med Assoc. 2011;103(1):4–8. https://doi.org/10.1016/s0027-9684(15)30236-4

Gunes FE, Bekiroglu N, Imeryuz N, Agirbasli M. Relation between eating habits and a high body mass index among freshman students: A cross-sectional study. J Am Coll Nutr. 2012;31(3):167–74. https://doi.org/10.1080/07315724.2012.10720024 .

Al-Kilani H, Waly M, Yousef R. Trends of obesity and overweight among college students in Oman: A cross-sectional study. Sultan Qaboos Univ Med J. 2012;12(1):69–76. https://doi.org/10.12816/0003090

Ekuni D, Furuta M, Tomofuji T, Irie K, Azuma T, Iwasaki Y, et al. Effects of eating behaviors on being overweight in Japanese University students: A cross-sectional survey at the Okayama University. Asia Pac J Public Health. 2013;25(4):326–34. https://doi.org/10.1177/1010539511425702 .

Musaiger AO, Al-Mannai M. Role of obesity and media in body weight concern among female university students in Kuwait. Eat Behav. 2013;14(2):229–32. https://doi.org/10.1016/j.eatbeh.2012.12.004 .

Wronka I, Suliga E, Pawliñska-Chmara R. Evaluation of lifestyle of underweight, normal weight and overweight young women. Coll Antropol. 2013;37(2):359–65.

Khalaf A, Westergren A, Berggren V, Ekblom Ö, Al-Hazzaa HM. Prevalence and association of female weight status and dietary habits with sociodemographic factors: A cross-sectional study in Saudi Arabia. Public Health Nutr. 2015;18(5):784–96. https://doi.org/10.1017/S1368980014001797 .

Quick V, Byrd-Bredbenner C, White AA, Brown O, Colby S, Shoff S, et al. Eat, sleep, work, play: Associations of weight status and health-related behaviors among young adult college students. Am J Health Promot. 2014;29(2):e64-72. https://doi.org/10.4278/ajhp.130327-QUAN-130 .

Shi H, Jiang B, Sim JDW, Chum ZZ, Ali NB, Toh MH. Factors associated with obesity: A case–control study of young adult Singaporean males. Mil Med. 2014;179(10):1158–65. https://doi.org/10.7205/MILMED-D-14-00064 .

Anand T, Grover S, Tanwar S, Kumar R, Meena G, Ingle G. Accuracy of body weight perceptions among students in a medical school in Central Delhi. India Educ Health. 2015;28(1):96–100. https://doi.org/10.4103/1357-6283.161948 .

Article   Google Scholar  

de Jesus Saucedo Molina T, Cortes JZ, Villalon L, Irecta AP, Hernandez RL. Prevalence of risk factors associated to eating disorders in university students. Psicologia y Salud. 2015;25(2):243–51.

Majeed F. Association of BMI with diet and physical activity of female medical students at the University of Dammam. Kingdom of Saudi Arabia JTUMED. 2015;10(2):188–96. https://doi.org/10.1016/j.jtumed.2014.11.004 .

Musaiger AO, Hammad SS, Tayyem RF, Qatatsheh AA. Sociodemographic and dietary factors associated with obesity among female university students in Jordan. Int K Adolesc Med Health. 2015;27(3):299–305. https://doi.org/10.1515/ijamh-2014-0029 .

Pengpid S, Peltzer K. Prevalence of overweight and underweight and its associated factors among male and female university students in Thailand. Homo. 2015;66(2):176–86. https://doi.org/10.1016/j.jchb.2014.11.002 .

Rangel Caballero LG, Rojas Sánchez LZ, Gamboa Delgado EM. Overweight and obesity in Colombian college students and its association with physical activity. Nutr Hosp. 2015;31(2):629–36. https://doi.org/10.3305/nh.2015.31.2.7757 .

Santiago JCdS, Moreira TMM, Florencio RS. Association between overweight and characteristics of young adult students: Support for nursing care. Rev Lat Am Entermagem. 2015;23(2):250–8. https://doi.org/10.1590/0104-1169.0174.2549

• Thomée S, Lissner L, Hagberg M, Grimby-Ekman A. Leisure time computer use and overweight development in young adults - A prospective study. BMC Public Health. 2015;15(1): 839. https://doi.org/10.1186/s12889-015-2131-5 . This was a large-scale prospective study that showed a significant risk for obesity in young adult female gamers .

El-Kassas G, Ziade F. Exploration of the dietary and lifestyle behaviors and weight status and their self-perceptions among health sciences university students in North Lebanon. Biomed Res Int. 2016;2016:9762396. https://doi.org/10.1155/2016/9762396 .

Sa J, Heimdal J, Sbrocco T, Seo DC, Nelson B. Overweight and physical inactivity among African American students at a historically black university. J Natl Med Assoc. 2016;108(1):77–85. https://doi.org/10.1016/j.jnma.2015.12.010 .

Senekal M, Lasker GL, van Velden L, Laubscher R, Temple NJ. Weight-loss strategies of South African female university students and comparison of weight management-related characteristics between dieters and non-dieters. BMC Public Health. 2016;16:918. https://doi.org/10.1186/s12889-016-3576-x .

Campos-Uscanga Y, Gutiérrez-Ospina G, Morales-Romero J, Romo-González T. Self-regulation of eating and physical activity is lower in obese female college students as compared to their normal weight counterparts. Eat Weight Disord. 2017;22(2):311–9. https://doi.org/10.1007/s40519-016-0338-9 .

Saeed E, Assiri AM, AwadEljack I, Aljasser AS, Alhuzimi AM, Assiri AA, et al. Obesity and associated risk factors among students of health colleges of King Saud University, Saudi Arabia: A cross-sectional study. J Pak Med Assoc. 2017;67(3):355–9.

Alhakbany MA, Alzamil HA, Alabdullatif WA, Aldekhyyel SN, Alsuhaibani MN, Al-Hazzaa HM. Lifestyle habits in relation to overweight and obesity among Saudi women attending health science colleges. J Epidemiol Glob Health. 2018;8(1–2):13–9. https://doi.org/10.2991/j.jegh.2018.09.100 .

Hossain S, Hossain M, Anjum A, Ahmed F, Hossain M, Uddin M. Risk modeling of non-communicable diseases using sociodemographic characteristics, lifestyle and family disease history among university students in Bangladesh. J Public Health. 2018;26(5):531–43. https://doi.org/10.1007/s10389-018-0895-7 .

• Kristicevic T, Stefan L, Sporis G. The associations between sleep duration and sleep quality with body-mass index in a large sample of young adults. Int J Environ Res Public Health. 2018;15(4):758. https://doi.org/10.3390/ijerph15040758 . This large cross-sectional study demonstrated the association between both, long and short sleep duration, as well as poor sleep quality with obesity in young adults .

Zhang Y, Liu D, Sheng L, Xiao H, Yao M, Chao Y, et al. Chronotype and sleep duration are associated with stimulant consumption and BMI among Chinese undergraduates. Sleep Biol Rhythms. 2018;16(2):211–22. https://doi.org/10.1007/s41105-017-0142-6 .

Amani R, Parohan M, Jomehzadeh N, Haghighizadeh MH. Dietary and biochemical characteristics associated with normal-weight obesity. Int J Vitam Nutr Res. 2019;89(5–6):331–6. https://doi.org/10.1024/0300-9831/a000477 .

Hanson AJ, Kattelmann KK, McCormack LA, Zhou W, Brown ON, Horacek TM, et al. Cooking and meal planning as predictors of fruit and vegetable intake and BMI in first-year college students. Int J Environ Res Public Health. 2019;16(14):2462. https://doi.org/10.3390/ijerph16142462 .

Abdelhafez AI, Akhter F, Alsultan AA, Jalal SM, Ali A. Dietary practices and barriers to adherence to healthy eating among King Faisal University students. Int J Environ Res Public Health. 2020;17(23):1–12. https://doi.org/10.1016/j.eatbeh.2012.12.004 .

Nguyen LPT, Nguyen BX, Ngo TT, Nguyen YHN, Phan HT. Correlations between excessive body mass index, body perception, physical activity, and respiratory functions among youths in an urban setting of Vietnam. Biomed Res Int. 2020;2020:9627605. https://doi.org/10.1155/2020/9627605 .

Yang Y, Miao Q, Zhu X, Qin L, Gong W, Zhang S, et al. Sleeping time, BMI, and body fat in Chinese freshmen and their interrelation. Obes Facts. 2020;13(2):179–90. https://doi.org/10.1159/000506078 .

Prioreschi A, Wrottesley SV, Norris SA. Physical activity levels, food insecurity and dietary behaviours in women from Soweto. South Africa J Community Health. 2021;46(1):156–64. https://doi.org/10.1007/s10900-020-00861-5 .

Alam BF, Abbasi N, Hussain T, Khan MA, Chaudhary MAG, Ijaz F. Relationship of BMI with the diet, physical activity and oral hygiene practices amongst the dental students. BMC Oral Health. 2022;22(1):311. https://doi.org/10.1186/s12903-022-02318-8 .

Arslan M, Ayhan NY, Çolak H, Sarıyer ET, Çevik E. The effect of chronotype on addictive eating behavior and BMI among university students: A cross-sectional study. Nutrients. 2022;14(14). https://doi.org/10.3390/nu14142907

Banna MHA, Brazendale K, Hasan M, Khan MSI, Sayeed A, Kundu S. Factors associated with overweight and obesity among Bangladeshi university students: A case-control study. J Am Coll Health. 2022;70(8):2327–33. https://doi.org/10.1080/07448481.2020.1851695 .

Flisco VDC, O’Shea C, Ing CT, Boushey CJ, Pokhrel P. Ethnic differences in fast-food advertising exposure and body mass index among Asian American/Pacific Islander and White young adults. Obes Res Clin Pract. 2022;16(4):295–300. https://doi.org/10.1016/j.orcp.2022.07.004 .

Prieto-González P, Sánchez-Infante J, Fernández-Galván LM. Association between adherence to the Mediterranean diet and anthropometric and health variables in college-aged males. Nutrients. 2022;14(17):3471. https://doi.org/10.3390/nu14173471 .

Sompa SI, Zettergren A, Ekström S, Upadhyay S, Ganguly K, Georgelis A, et al. Predictors of electronic cigarette use and its association with respiratory health and obesity in young adulthood in Sweden; Findings from the population-based birth cohort BAMSE. Environ Res. 2022;208: 112760. https://doi.org/10.1016/j.envres.2022.112760 .

Aynehchi A, Saleh-Ghadimi S, Dehghan P. The association of self-efficacy and coping strategies with body mass index is mediated by eating behaviors and dietary intake among young females: A structural-equation modeling approach. PLoS ONE. 2023;18(1): e0279364. https://doi.org/10.1371/journal.pone.0279364 .

Article   CAS   PubMed   PubMed Central   Google Scholar  

Lin X, Liu H. A study on the effects of health behavior and sports participation on female college students’ body mass index and healthy promoting lifestyle. Front Public Health. 2023;10:1069219. https://doi.org/10.3389/fpubh.2022.1069219 .

• Patel SA, Ali MK, Alam D, Yan LL, Levitt NS, Bernabe-Ortiz A, et al. Obesity and its relation with diabetes and hypertension: A cross-sectional study across 4 geographical regions. Glob Heart. 2016;11(1):71-9.e4. https://doi.org/10.1016/j.gheart.2016.01.003 . This article elucidates data from different regions to reconfirm the importance of BMI and waist circumference as predictors of diabetes and hypertension .

Liberali R, Del Castanhel F, Kupek E, Assis MAA. Latent class analysis of lifestyle risk factors and association with overweight and/or obesity in children and adolescents: Systematic review. Child Obes. 2021;17(1):2–15. https://doi.org/10.1089/chi.2020.0115 .

Marconcin P, Ihle A, Werneck AO, Gouveia ER, Ferrari G, Peralta M, et al. The association of healthy lifestyle behaviors with overweight and obesity among older adults from 21 countries. Nutrients. 2021;13(2):315. https://doi.org/10.3390/nu13020315 .

Biddle SJH, García Bengoechea E, Pedisic Z, Bennie J, Vergeer I, Wiesner G. Screen time, other sedentary behaviours, and obesity risk in adults: A review of reviews. Curr Obes Rep. 2017;6(2):134–47. https://doi.org/10.1007/s13679-017-0256-9 .

•• Malik VS, Hu FB. The role of sugar-sweetened beverages in the global epidemics of obesity and chronic diseases. Nat Rev Endocrinol. 2022;18(4):205–18. https://doi.org/10.1038/s41574-021-00627-6 . A review that discussed the wide impact of sugar-sweetened beverages on health, including obesity .

Elizabeth L, Machado P, Zinöcker M, Baker P, Lawrence M. Ultra-processed foods and health outcomes: A narrative review. Nutrients. 2020;12(7):1955. https://doi.org/10.3390/nu12071955 .

Rouhani MH, Salehi-Abargouei A, Surkan PJ, Azadbakht L. Is there a relationship between red or processed meat intake and obesity? A systematic review and meta-analysis of observational studies. Obes Rev. 2014;15(9):740–8. https://doi.org/10.1111/obr.12172 .

•• Daneshzad E, Askari M, Moradi M, et al. Red meat, overweight and obesity: A systematic review and meta-analysis of observational studies. Clin Nutr ESPEN. 2021;45:66–74. https://doi.org/10.1016/j.clnesp.2021.07.028 . A recent meta-analysis that found no significant association between red meat intake and obesity .

Jiang K, Zhang Z, Fullington LA, Huang TT, Kaliszewski C, Wei J, et al. Dietary patterns and obesity in Chinese adults: A systematic review and meta-analysis. Nutrients. 2022;14(22):4911. https://doi.org/10.3390/nu14224911 .

Suter PM. Is alcohol consumption a risk factor for weight gain and obesity? Crit Rev Clin Lab Sci. 2005;42(3):197–227. https://doi.org/10.1080/10408360590913542 .

Traversy G, Chaput J-P. Alcohol consumption and obesity: An update. Curr Obes Rep. 2015;4(1):122–30. https://doi.org/10.1007/s13679-014-0129-4 .

Sogari G, Velez-Argumedo C, Gómez MI, Mora C. College students and eating habits: A study using an ecological model for healthy behavior. Nutrients. 2018;10(12):1823. https://doi.org/10.3390/nu10121823 .

Lopez-Minguez J, Gómez-Abellán P, Garaulet M. Timing of breakfast, lunch, and dinner. Effects on obesity and metabolic risk. Nutrients. 2019;11(11): 2624. https://doi.org/10.3390/nu11112624

Watanabe Y, Saito I, Henmi I, Yoshimura K, Maruyama K, Yamauchi K, et al. Skipping breakfast is correlated with obesity. J Rural Med. 2014;9(2):51–8. https://doi.org/10.2185/jrm.2887 .

•• Desbouys L, Méjean C, De Henauw S, Castetbon K. Socio-economic and cultural disparities in diet among adolescents and young adults: A systematic review. Public Health Nutr. 2020;23(5):843–60. https://doi.org/10.1017/S1368980019002362 . The review discussed influence of socioeconomic status on the association between diet and obesity .

Martin JC, Moran LJ, Harrison CL. Diet quality and its effect on weight gain prevention in young adults: A narrative review. Semin Reprod Med. 2020;38(06):407–13. https://doi.org/10.1055/s-0041-1723776 .

Sharareh P, Leili T, Abbas M, Jalal P, Ali G. Determining correlates of the average number of cigarette smoking among college students using count regression models. Sci Rep. 2020;10(1):8874. https://doi.org/10.1038/s41598-020-65813-4 .

Chiolero A, Faeh D, Paccaud F, Cornuz J. Consequences of smoking for body weight, body fat distribution, and insulin resistance. Am J Clin Nutr. 2008;87(4):801–9. https://doi.org/10.1093/ajcn/87.4.801 .

Dare S, Mackay DF, Pell JP. Relationship between smoking and obesity: A cross-sectional study of 499,504 middle-aged adults in the UK general population. PLoS ONE. 2015;10(4): e0123579. https://doi.org/10.1371/journal.pone.0123579 .

• Carreras-Torres R, Johansson M, Haycock PC, Relton CL, Davey Smith G, Brennan P, et al. Role of obesity in smoking behaviour: Mendelian randomisation study in UK Biobank BMJ. 2018;361: k1767. https://doi.org/10.1136/bmj.k1767 . The article discussed the potential bidirectional relationship between obesity and smoking .

Oppert JM, Bellicha A, Ciangura C. Physical activity in management of persons with obesity. Eur J Intern Med. 2021;93:8–12. https://doi.org/10.1016/j.ejim.2021.04.028 .

Pfisterer J, Rausch C, Wohlfarth D, Bachert P, Jekauc D, Wunsch K. Effectiveness of physical-activity-based interventions targeting overweight and obesity among university students-A systematic review. Int J Environ Res Public Health. 2022;19(15):9427. https://doi.org/10.3390/ijerph19159427 .

Kallio P, Pahkala K, Heinonen OJ, Tammelin TH, Pälve K, Hirvensalo M, et al. Physical inactivity from youth to adulthood and adult cardiometabolic risk profile. Prev Med. 2021;145: 106433. https://doi.org/10.1016/j.ypmed.2021.106433 .

Nagata JM, Smith N, Alsamman S, Lee CM, Dooley EE, Kiss O, et al. Association of physical activity and screen time with body mass index among US adolescents. JAMA Netw Open. 2023;6(2): e2255466. https://doi.org/10.1001/jamanetworkopen.2022.55466 .

Kolovos S, Jimenez-Moreno AC, Pinedo-Villanueva R, Cassidy S, Zavala GA. Association of sleep, screen time and physical activity with overweight and obesity in Mexico. Eat Weight Disord. 2021;26(1):169–79. https://doi.org/10.1007/s40519-019-00841-2 .

Liao Y, Harada K, Shibata A, Ishii K, Oka K, Nakamura Y, et al. Joint associations of physical activity and screen time with overweight among Japanese adults. Int J Behav Nutr Phys Act. 2011;8:131. https://doi.org/10.1186/1479-5868-8-131 .

Robinson TN, Banda JA, Hale L, Lu AS, Fleming-Milici F, Calvert SL, et al. Screen media exposure and obesity in children and adolescents. Pediatrics. 2017;140(Suppl 2):S97-s101. https://doi.org/10.1542/peds.2016-1758K .

Primack C. Obesity and sleep. Nurs Clin North Am. 2021;56(4):565–72. https://doi.org/10.1016/j.cnur.2021.07.012 .

Antza C, Kostopoulos G, Mostafa S, Nirantharakumar K, Tahrani A. The links between sleep duration, obesity and type 2 diabetes mellitus. J Endocrinol. 2021;252(2):125–41. https://doi.org/10.1530/JOE-21-0155 .

Chaput JP, McHill AW, Cox RC, Broussard JL, Dutil C, da Costa BG, et al. The role of insufficient sleep and circadian misalignment in obesity. Nat Rev Endocrinol. 2023;19(2):82–97. https://doi.org/10.1038/s41574-022-00747-7 .

Beccuti G, Pannain S. Sleep and obesity. Curr Opin Clin Nutr Metab Care. 2011;14(4):402–12. https://doi.org/10.1097/MCO.0b013e3283479109 .

Zimberg IZ, Dâmaso A, Del Re M, Carneiro Am, de Sá Souza H, de Lira F, et al. Short sleep duration and obesity: Mechanisms and future perspectives. Cell Biochem Funct. 2012;30(6):524–9. https://doi.org/10.1002/cbf.2832

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Lee, K.X., Quek, K.F. & Ramadas, A. Dietary and Lifestyle Risk Factors of Obesity Among Young Adults: A Scoping Review of Observational Studies. Curr Nutr Rep 12 , 733–743 (2023). https://doi.org/10.1007/s13668-023-00513-9

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Junk food-induced obesity- a growing threat to youngsters during the pandemic

Introduction.

Obesity has been declared an epidemic that does not discriminate based on age, gender, or ethnicity and thus needs urgent containment and management. Since the third wave of COVID-19 is expected to affect children the most, these children and adolescents should be more cautious while having junk foods, during covid situations due to the compromise of Immunity in the individuals and further exacerbating the organ damage.

Methodology

A PAN India survey organized by the Centre for Science and Environment (CSE) among 13,274 children between the ages 9–14 years reported that 93% of the children ate packed food and 68% consumed packaged sweetened beverages more than once a week, and 53% ate these products at least once in a day. Almost 25% of the School going children take ultra-processed food with high levels of sugar, salt, fat, such as pizza and burgers, from fast food outlets more than once a week. Children and adolescents who consume more junk food or addicted to such consumption might be even more vulnerable during the third wave, which will significantly affect the younger category.

There is an urgent need to spread awareness among children and young adults about these adverse effects of junk food. There is no better time than now to build a supportive environment nurturing children and young adults in society and promising good health.

1. Introduction

Obesity has been declared as epidemic that does not discriminate based on age, gender, or ethnicity and thus needs urgent containment and management. Cardiovascular complications are a global threat with the rapid increase in the prevalence of obesity; by 2025, it is expected to reachupto 18% in men and 21% in women by forbidding heavy burden upon individuals, societies, and health care systems. Heart attack survivors with excess fat around their waist are at increased risk of another cardiac arrest, according to the journal of the European Society of Cardiology (Mohammadi H et al., 2020).

In the modern era, obesity is linked with various factors enhancing the production of cortisol, such as Food consumption with a high glycaemic index, chronic stress, and change in sleep patterns ( Knutson et al., 2010 ; Cohen and Janicki-Deverts, 2012 ). The burden of non-communicable disease has become a major threat globally, attributing to physical inactivity, unhealthy dietary habits, unhealthy lifestyle, and smoking. It is also observed that food with high levels of fat content is preferred to non-fat food by people ( Visschers and Siegrist, 2010 ). Based on the reports, more than one-third of the adults eat junk food several times a week ( Bauer et al., 2009 ). Studies have proven that Junk food tends to cause obesity (central adiposity), a primary concern of heart diseases and other non-communicable diseases ( Rouhani et al., 2012 ; Musaiger, 2014 ). Poor nutrition could result in reduced Immunity, susceptibility to several oral and systemic diseases, impaired physical and mental growth, and reduced efficiency (Bhattacharya, P. T et al., 2016).

Greater than 60% of the overweight child population seem to have at least one added risk factor of cardiovascular disease (Raised blood pressure, hyperlipidemia, hyperinsulinemia), and more than 20% of the obese children have two or more risk factors. The United States National Centre for Health Statistics suggests that nearly 15% of adolescents are overweight or obese, and treatment is harder in adults than children ( International Life Sciences Institutes, 2000 ). It is observed that an adolescent is often negligible to his health due to improper awareness and a busy work schedule. With more than 14.4 million obese children, India has the second-largest obese child population in the world. By 2025 it is anticipated to reach a stunning 17 million.

Since the third wave of COVID-19 is expected to affect children the mostly, it is, therefore, advisable for these children and adolescents who eat Junk foods to be more cautious during Covid situations due to the compromise of Immunity in the individuals and further exacerbating the organ damage.

2. Junk foods overview

Children find themselves amidst a way of living that has been metamorphized to suit the new jet-setting age and the food is no exception to this. Over the last two decades, the variability of healthy eating advice has become a cliché, leading to an alarming increase in the trend of consumption of fast food and sweetened beverages in Indian children. On average, the fast-food industry is growing 40% per year ( Joseph et al., 2015 ). A PAN India survey organized by the Centre for Science and Environment (CSE) among 13,274 children between the ages 9–14 years reported that 93% of the children ate packed food and 68% consumed packaged sweetened beverages more than once a week, and 53% ate these products at least once in a day. Almost 25% of the School going children take ultra-processed food with high levels of sugar, salt, fat, such as pizza and burgers, from fast food outlets more than once a week ( Bhushan et al., 2017 ). The most commonly consumed junk food items are bakery products, beverages, burgers, caffeinated drinks, chips, chocolates, noodles, pizza, soft drinks, and sugar-sweetened drinks. Harmful effects of Junk foods include Overweight/Obesity, Cardiometabolic risk, High blood pressure, Behavioural symptoms and Dental caries.

3. Highly consumed junk foods

Habitual physically inactive lifestyle, advertisements, media, and consumption of junk food have contributed significantly towards causing obesity in children and adolescents. Various list of Junk foods and their associated components showing the impact on health is mentioned in Table 1 .

List of Junk foods and its associated components showing impact on health.

4. Impact of junk foods on body weight

The rates of overweight and obesity have increased tremendously over the past few decades as a health epidemic in most parts of the world ( Mancino and Kinsey, 2008 ; LaCaille et al., 2011 ; Allom and Mullan, 2014 ). High consumption of Junk Foods contributes to the overweight among School-aged children in India from 9.7% to 13.9% over a decade ( Ranjani et al., 2016 ). The potential adverse effects on weight status in younger population include Physical inactivity and unhealthy dietary habits and, consequently, the future health of adults ( Hutchesson et al., 2015 ; Allom and Mullan, 2014 ). High intake of fried foods and artificially sweetened drinks are found to be directly linked with high body mass index and obesity in children. Additionally, diets with elevated amounts of Junk food have very little quantity of nutrients ( Goel et al., 2013 ; Harnack et al., 1999 ).

5. Preclinical evidences of junk food and its effect

The preclinical data is essential in collecting the safety of drug, iterative testing, and the feasibility of experiment which is given in Table 2 . In a study conducted in 1991, brown and white adipose tissue in high fat and junk diet and chow-fed rats with dorsomedial hypothalamic lesion rats ( Bernardis and Bellinger, 1991 ). The animals were grouped as high fat and control rats as group 1 and 3, whereas chow diet and control were grouped as group 2 and 4. He found that obesity is not only linked to calories but rather the sort of calories consumed, brown adipose tissue weight, lipid content, protein and turnover of NE are indicators of metabolic activity and thermogenesis that are unreliable. Oginsky et al. (2016) proposed that intake of junk food shows a rapid and long-lasting increase in NAc CP-AMPA receptors for food addiction. In general, mesolimbic circuits responsiveness is intensified in rats that are vulnerable to diet-induced obesity.

Pre-clinical and clinical evidence of Junk food and its effect.

Additionally, junk food was found to increase NAc CP-AMPAR function in obesity-susceptible rats. AMPA upregulation occurred more promptly in obesity-susceptible rats and preceded the development of obesity. Cocaine-induced locomotion was seen, and post-junk-food deprivation, cocaine-induced movement was enhanced in Junk-Food-Gainers than in the Non-Gainers, i.e., Junk-Food gainers were more sensitized when compared to non-gainers. He concluded that it will be significant to determine the extent to which these food-induced changes occurring in the striatal function could be part of normal, adaptive processes vs maladaptive, ‘addictive-like behaviors. A study conducted on 2010 by StephanieA stated in a study that a junk food diet in pregnancy and lactation promotes Non-alcoholic fatty liver in the rat offspring. It was observed that those junk food-fed mothers moved to an exclusive chow diet from weaning which resulted in the increase of triglyceride compared to the CCC group at the end of adolescence. The histological analysis did not disclose any signs of fibrosis or inflammation confirmed by unaffected TNF-alpha, IL-6, Collagen, and keratin expressions, suggesting that although they showed NAFLD signs, they did not suffer from NASH. He also mentioned that exacerbated steatosis in those offsprings did not coexist with an increase in carnitine palmitoyltransferase I (Cpt1a) mRNA expression, which might be an indicator of mitochondrial Beta-oxidation saturation leading to further lipid accumulation in the liver. In 2008 an observation was made on off springs of Junk food-fed mothers in pregnancy and lactation exhibited aggravated adiposity, which is highly found in females ( Bayol et al., 2008 ).

The perirenal fat pad mass linked to body weight was greater in the offsprings fed with junk food throughout the study than those fed with junk food diet postweaning. The increase in adiposity is associated with the weight gain previously reported in the same animals. The study on gene expression and changes in adipose tissue cellularity showed that an increase in IGF-1 transcription indicated higher proliferation of pre-adipocyte in females fed with junk food diet after weaning compared to males. Gugusheff et al., 2013 studied extensively the effects of prenatal junk food exposure on food preferences of offspring and how fat deposition can be alleviated by enhanced nutrition during lactation ( Gugusheff et al., 2013 ). He found that habitual cafeteria diet during the suckling period, independent of dietary exposure before birth, led to the development of diet-induced obesity in females and an increase in preference for appetizing foods in male offspring in young adulthood. The animals were given free access to the cafeteria diet. Female offspring suckled by JF dams had increased fat mass compared to those offspring suckled by control dams independent of the diet consumed by the mother during pregnancy. It is to be noted that it took place in the absence of high food consumption, suggesting that these animals had an enhanced propensity to accumulate fat in the body.

6. Clinical evidence of junk food and its effect

The clinical data collection is very much helped by the quality of information generated, which plays a significant part in yielding the study results whose clinical data are given in Table 2 .

Zahedi et al. (2014) studied the relationship between junk food consumption and mental health in a Sample of Iranian Children and Adolescents ( Zahedi et al., 2014 ). In this study, a notable link between junk food consumption and mental health problems in children and adolescents was observed. Students that consumed junk food daily were more likely to be subjected to mental health problems. The Western Australian Pregnancy Cohort Study proposed that the Western dietary pattern of increased consumption of takeaway foods, red meat, and confectionary was significantly associated with poor behavioral outcomes in adolescents. Similarly, two cohort studies in adolescents instigated that increased intake of unhealthy foods like sweets, savory snacks, sweetened soft drinks, chocolate, and fast foods was associated with a high risk of behavioral problems and mental distress such as anxiety worthlessness, and dizziness.

Azemati et al., 2020 studied an association between consumption of junk food and cardiometabolic risk factors in Iranian children and adolescent population ( Azemati et al., 2020 ). A population-based study in Korea showed that fast food consumption was linked to metabolic syndrome in adolescents. The study demonstrated that sweet dietary habits were positively related to metabolic syndrome, and those under junk food consumption were more likely to be overweight. Junk foods are found to be associated with obesity due to their high energy content and the amount of fat present or free sugar, chemical additives, and sodium with the presence of a low amount of micronutrients and fiber. Among junk foods, intake of sweetened beverages is in close relationship with weight fluctuations as it can increase food intake through decreasing satiety mechanisms. In Conclusion, junk food intake among Iranian children and adolescents had undesirable effects on cardiometabolic risk factors. Thus, enhancing knowledge of junk foods among adolescents is one of the possible ways to help them to make healthy food choices and get rid of overweight and obesity.

Zhu et al. (2019) investigated on the current situation and influencing factors on consuming junk foods among children and adolescents in Beijing city ( Zhu et al., 2019 ). He used a questionnaire survey method to survey the junk food habits and their effects. One month before the survey, all individuals have an intake of one type or the other junk foods. Mostly they didn't have an understanding of nutrition, and mostly they have misunderstandings about nutritional value and effect on the human body. Their behavior is affected mainly by personal factors like physiological, psychological, social, family factors, and the food itself. In Conclusion, children and adolescents in Haidian District ate different types of junk food, and the safety, nutritional issues of junk food should be paid great attention to prevent and control the risk factors of children and adolescents eating junk food. Payab et al. (2015) studied the relationship between junk food consumption with high blood pressure and obesity in Iranian children and adolescents ( Payab et al., 2015 ).

This study showed significant link between sweet consumption and both general and abdominal obesity. Nonetheless, there was no meaningful relationship between sweets consumption and high blood pressure. Several studies also showed that in general, central obesity is inversely associated with healthy dietary habits, while the Western dietary habits (refined grains, Red meat, sweets, desserts, pizza, French fries, and soft drinks) were directly linked to obesity.

7. Junk food and compromised immune system

• i) Effect of Junk foods on the signaling pathway

The intake of appetizing food is primarily under the control of the limbic system and stimulates endogenous opioids release, which binds to the opioid receptors present in the ventral tegmental area (VTA). VTA activates dopaminergic neurons in the brain, and in the nucleus accumbent, the site of dopamine release to potentiate dopamine signaling pathway ( Bergevin et al., 2002 ; Fields and Margolis, 2015 ; Berridge, 1996 ). The stimulation of the dopamine signaling pathway by opioid interactions is thought to be involved in the mediation of the short-term pleasurable sensation linked with the consumption of appetizing food ( Bodnar et al., 2005 ; Bodnar, 2015 ). It is observed that a reduction in MuR expression in the offspring of dams maintained on a junk food diet during pregnancy and lactation is present in the VTA at the weaning stage, i.e., 3 weeks after birth ( Gugusheff et al., 2013 ). Nonetheless, MuR expression in the NAcis found in elevated levels during the first postnatal week and declining to adult levels over the next two weeks ( Tong et al., 2000 ).

• ii) Effect of Junk foods on Immunity

Micronutrients like trace elements, antioxidants, and vitamins play a significant role in the regenerative process, coping with existing oxidative stress in the body tissues and providing Immunity against pathogens ( Chapple et al., 2007 ; Enwonwu et al., 2002 ). Obesity in the early years of life alters the immune system by inducing changes in cytokines concentrations and proteins and the number and function of the immune cells, ultimately leading to a pro-inflammatory condition, leading to the onset or exacerbation of numerous diseases like asthma, atopic dermatitis, allergy and sleep apnea ( Kelishadi et al., 2017 ). Various per- and polyfluorinated substances (PFAS)might affect growth, infantile behavior, learning, and older children. It also lowers the chance of pregnancy, interferes with the defense of natural hormones, increases the cholesterol levels, reduces vaccine-induced immune protection in children, and increase the risk of cancer ( Velez et al., 2015 ; Grandjean et al., 2017 ; Bach et al., 2015 ). Various reports from the conducted human studies conclude that some PFAS can take as long as 8–9 years to get cleared from the body ( Bartell et al., 2010 ). It can also cross the placental barrier and be secreted through breastmilk ( Mondal et al., 2013 ; Kingsley et al., 2018 ). It was observed that the immune response was impaired in children, especially cellular to influenza virus, and also inadequate vaccine responses were seen when they were obese ( Green and Beck, 2017 ). Thus, the importance of nutrition must be considered when it comes to Immunity. Similarly, there is enhanced knowledge about food, nutritional habits, and other lifestyle aspects, which are essential in aiding the proper functioning of the immune system ( Gombart et al., 2020 ).

In concern with obesity, there is a negative relationship between BMI and the intake of trace elements identified in obese people ( Farhat et al., 2019 ). Therefore, obesity has a strong correlation with an increased risk of infectious diseases accompanied by severe complications, elevated critical illnesses, and prolonged hospitalization ( Ritter et al., 2020 ). Systemic inflammatory reactions occur in covid 19 due to cytokine storms which leads to the imbalance of the immune system observed in obesity, and it contributes to a worse clinical outcome. Adipocytokines, mainly leptin, play an integral role in Immunity, as they influence the number and the function of immune cells through direct effects on cell metabolism ( Kim and Nam, 2020 ).

8. Influence of junk food during COVID-19 pandemic

COVID-19 lockdown had drastically altered the regular food pattern. When compared before pandemic, it shows both negative and beneficial impact on dietary practice associated with poor lifestyle management such as lack of physical activity and obesity. Nonetheless, poor eating habits were noticed such as changes in meal frequency and increased snacking with comfort foods (food bringing emotional comfort). It shows that alteration in dietary habits during the pandemic are at higher risk of further complications ( Bohlouli et al., 2021 ).

Since junk food tends to impact the immune system, it poses a greater risk during the pandemic. Children and adolescents who consume more junk food or are addicted to such consumption might be even more vulnerable during the third wave, which will especially affect the younger category (Janssen et al., 2021; Preethi et al., 2021 ).

9. Conclusion

Overweight and obesity are predominantly associated with numerous cardiac complications and are mostly mediated through the risk of metabolic syndrome. Obesity, like other malnutritional states, is known to impair immune function by altering leucocyte count as well as cell-mediated responses and causes organ damage. Not only is it causing physiological repressions, but it has significant psychological manifestations-that can damage a child's intellect and personality. Covibesity associated individuals are more prone to alteration of the immune system, and thus those people having junk food habits should be more cautious in this pandemic by maintaining health hygiene and getting vaccinated. It is to be noted that junk foods and packaging materials have drastic outcomes on health by impairing the immune system.

Thus, a combination of junk food, physical inactivity, and constant psychological stressors on children and adolescents during the pandemic makes them more vulnerable to increased weight along with decreased Immunity and thus an increased chance of infectivity during the third wave of COVID-19. There is an urgent need to spread awareness among children and young adults about these adverse effects of junk food, and they are not a good substitute for good healthy nourishment. There is no better time than now to build a supportive environment nurturing children and young adults in society and promising good health.

CRediT authorship contribution statement

AS: Methodology and Writing.

DD: Data curation and Review.

NG: Investigation and Resource.

LP: Writing and Editing.

SS: Conceptualization and Supervision.

This research received no grant from any funding agency.

Declaration of competing interest

The authors declare no conflict of interest, financial or otherwise.

Acknowledgement

We extend our sincere thanks to all the health care professionals.

• Allom V., Mullan B. Maintaining healthy eating behaviour: experiences and perceptions of young adults. Nutr. Food Sci. 2014; 44 :156–167. [ Google Scholar ]
• Anderko L., Pennea E. Exposures to per-and polyfluoroalkyl substances (PFAS): potential risks to reproductive and children's health. Curr. Probl. Pediatr. Adolesc. Health Care. 2020; 50 (2):100760. doi: 10.1016/j.cppeds.2020.100760. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Azemati B., Kelishadi R., Ahadi Z., Shafiee G., Taheri M., Ziaodini H., et al. Association between junk food consumption and cardiometabolic risk factors in a national sample of Iranian children and adolescents population: the CASPIAN-V study. Eat. Weight Disord. 2020; 25 (2):329–335. doi: 10.1007/s40519-018-0591-1. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bach C.C., Bech B.H., Brix N., Nohr E.A., Bonde J.P.E., Henriksen T.B. Perfluoroalkyl and polyfluoroalkyl substances and human fetal growth: a systematic review. Crit. Rev. Toxicol. 2015; 45 (1):53–67. doi: 10.3109/10408444.2014.952400. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bartell S.M., Calafat A.M., Lyu C., Kato K., Ryan P.B., Steenland K. Rate of decline in serum PFOA concentrations after granular activated carbon filtration at two public water systems in Ohio and West Virginia. Environ. Health Perspect. 2010; 118 (2):222–228. doi: 10.1289/ehp.0901252. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bauer K.W., Larson N.I., Nelson M.C., Story M., Neumark-Sztainer D. Socio-environmental, personal and behavioural predictors of fast-food intake among adolescents. Publ. Health Nutr. 2009; 12 (10):1767–1774. doi: 10.1017/S1368980008004394. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bayol S.A., Simbi B.H., Bertrand J.A., Stickland N.C. Offspring from mothers fed a 'junk food' diet in pregnancy and lactation exhibit exacerbated adiposity that is more pronounced in females. J. Physiol. (Lond.) 2008; 586 (13):3219–3230. doi: 10.1113/jphysiol.2008.153817. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bergevin A., Girardot D., Bourque M.J., Trudeau L.E. Presynaptic mu-opioid receptors regulate a late step of the secretory process in rat ventral tegmental area GABAergic neurons. Neuropharmacology. 2002; 42 (8):1065–1078. doi: 10.1016/s0028-3908(02)00061-8. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bernardis L.L., Bellinger L.L. Brown (BAT) and white (WAT) adipose tissue in high-fat junk food (HFJF) and chow-fed rats with dorsomedial hypothalamic lesions (DMNL rats) Behav. Brain Res. 1991; 43 (2):191–195. doi: 10.1016/s0166-4328(05)80070-1. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Berridge K.C. Food reward: brain substrates of wanting and liking. Neurosci. Biobehav. Rev. 1996; 20 :1–25. [ PubMed ] [ Google Scholar ]
• Bhushan, C., Taneja, S., Khurana, A. Centre for Science and Environment, New Delhi, Burden Of Packaged Food on Schoolchildren: Based on the CSE Survey ‘Know Your Diet’ 2017. http://www.india environmentportal.org.in/files/file/Burden%20of%20 Packaged%20Food%20on%20School%20Children.pdf. (Accessed 20 January 2019).
• Bodnar R.J. Endogenous opioids and feeding behavior: a decade of further progress (2004–2014). A Festschrift to Dr. Abba Kastin. Peptides. 2015; 72 :20–33. doi: 10.1016/j.peptides.2015.03.019. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bodnar R.J., Lamonte N., Israel Y., Kandov Y., Ackerman T.F., Khaimova E. Reciprocal opioid–opioid interactions between the ventral tegmental area and nucleus accumbens regions in mediating agonist-induced feeding in rats. Peptides. 2005; 26 :621–629. doi: 10.1016/j.peptides.2004.11.007. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bohlouli J., Moravejolahkami A.R., Ganjali Dashti M., Balouch Zehi Z., Hojjati Kermani M.A., Borzoo-Isfahani M., Bahreini-Esfahani N. COVID-19 and fast foods consumption: a review. Int. J. Food Prop. 2021; 24 (1):203–209. doi: 10.1080/10942912.2021.1873364. [ CrossRef ] [ Google Scholar ]
• Bordbar H., Soleymani F., Nadimi E., Yahyavi S.S., Fazelian-Dehkordi K. A quantitative study on the protective effects of resveratrol against bisphenol A-induced hepatotoxicity in rats: a stereological study. Iran. J. Med. Sci. 2021; 46 (3):218–227. doi: 10.30476/ijms.2020.83308.1233. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Chapman C.L., Grigoryan T., Vargas N.T., Reed E.L., Kueck P.J., Pietrafesa L.D., et al. High-fructose corn syrup-sweetened soft drink consumption increases vascular resistance in the kidneys at rest and during sympathetic activation. Am. J. Physiol. Ren. Physiol. 2020; 318 (4):F1053–F1065. doi: 10.1152/ajprenal.00374.2019. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Chapple I.L., Brock G.R., Milward M.R., Ling N., Matthews J.B. Compromised GCF total antioxidant capacity in periodontitis: cause or effect? J. Clin. Periodontol. 2007; 34 (2):103–110. [ PubMed ] [ Google Scholar ]
• Cohen S., Janicki-Deverts D. Who's stressed? Distributions of psychological stress in the United States in probability samples from 1983, 2006, and 2009. J. Appl. Soc. Psychol. 2012; 42 :1320–1334. doi: 10.1111/j.1559-1816.2012.00900.x. [ CrossRef ] [ Google Scholar ]
• DeChristopher L.R., Auerbach B.J., Tucker K.L. High fructose corn syrup, excess-free-fructose, and risk of coronary heart disease among African Americans- the Jackson Heart Study. BMC Nutr. 2020; 6 (1):70. doi: 10.1186/s40795-020-00396-x. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Enwonwu C.O., Phillips R.S., Falkler W.A., Jr. Nutrition and oral infectious diseases: state of the science. Comp. Cont. Educ. Dent. 2002; 23 (5):431–448. [ PubMed ] [ Google Scholar ]
• Farhat G., Lees E., Macdonald-Clarke C., Amirabdollahian F. Inadequacies of micronutrient intake in normal weight and overweight young adults aged 18–25 years: a cross-sectional study. Publ. Health. 2019; 167 :70–77. doi: 10.1016/j.puhe.2018.10.016. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Fields H.L., Margolis E.B. Understanding opioid reward. Trends Neurosci. 2015; 38 :217–225. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Goel S., Kaur T., Gupta M. Increasing proclivity for junk food among overweight adolescent girls in district Kurukshetra, India. Int. Res. J. Biol. Sci. 2013; 2 :80–84. [ Google Scholar ]
• Gombart A.F., Pierre A., Maggini S. A Review of micronutrients and the immune system–Working in harmony to reduce the risk of infection. Nutrients. 2020; 12 :236. doi: 10.3390/nu12010236. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Grandjean P., Heilmann C., Weihe P., et al. Estimated exposures to perfluorinated compounds in infancy predict attenuated vaccine antibody concentrations at age 5-years. J. Immunot. 2017; 14 (1):188–195. doi: 10.1080/1547691X.2017.1360968. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Green W.D., Beck M.A. Obesity impairs the adaptive immune response to Influenza virus. Ann. Am. Thorac. Soc. 2017; 14 :S406–S409. doi: 10.1513/AnnalsATS.201706-447AW. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Gugusheff J.R., Ong Z.Y., Muhlhausler B.S. A maternal junk-food diet reduces sensitivity to the opioid antagonist naloxone in offspring postweaning. Faseb. J. 2013; 27 :1275–1284. [ PubMed ] [ Google Scholar ]
• Ham J., Lim W., Park S., Bae H., You S., Song G. Synthetic phenolic antioxidant propyl gallate induces male infertility through disruption of calcium homeostasis and mitochondrial function. Environ. Pollut. 2019; 248 :845–856. doi: 10.1016/j.envpol.2019.02.087. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Harnack L., Stang J., Story M. Soft drink consumption among US children and adolescents: nutritional consequences. J. Am. Diet Assoc. 1999; 99 :436–441. [ PubMed ] [ Google Scholar ]
• Holick M.F. Vitamin D: a millennium perspective. J. Cell. Biochem. 2003; 88 (2):296e307. [ PubMed ] [ Google Scholar ]
• Hurley S., Goldberg D., Wang M., Park J.S., Petreas M., Bernstein L., et al. Breast cancer risk and serum levels of per- and poly-fluoroalkyl substances: a case-control study nested in the California Teachers Study. Environ. Health. 2018; 17 (1):83. doi: 10.1186/s12940-018-0426-6. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hutchesson M.J., Rollo M.E., Krukowski R., Ells L., Harvey J., Morgan P.J., et al. eHealth interventions for the prevention and treatment of overweight and obesity in adults: a systematic review with meta-analysis. Obes. Rev. 2015; 16 :376–392. doi: 10.1111/obr.12268. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• International Life Sciences Institutes . vol. 2. International Life Science Institute; USA: 2000. Preventing childhood obesity is a current research focus: initiatives cooperate to share information and stem epidemic; p. 5. (The PAN Report: Physical Activity and Nutrition). [ Google Scholar ]
• Islam M.A., Amin M.N., Siddiqui S.A., Hossain M.P., Sultana F., Kabir M.R. Trans fatty acids and lipid profile: a serious risk factor to cardiovascular disease, cancer and diabetes. Diabetes Metabol. Syndr. 2019; 13 (2):1643–1647. doi: 10.1016/j.dsx.2019.03.033. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Joseph N., Nelliyani M., Rai S., Babu Y.P.R., Kotian S.M., Ghosh T., et al. Fast food consumption pattern and its association with overweight among high school boys in Mangalore city of southern India. J. Clin. Res. 2015; 9 :LC13–17. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Kelishadi R., Roufarshbaf M., Soheili S., Payghambarzadeh F., Masjedi M. Association of childhood obesity and the immune system: a systematic review of reviews. Child. Obes. 2017; 13 :332–346. doi: 10.1089/chi.2016.0176. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kim J., Nam J.H. Insight into the relationship between obesity-induced low-level chronic inflammation and COVID-19 infection. Int. J. Obes. 2020; 44 :1541–1542. doi: 10.1038/s41366-020-0602-y. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kim C.W., Cho J.H., Leem J.H., Ryu J.S., Lee H.L., Hong Y.C. Occupational asthma due to azodicarbonamide. Yonsei Med. J. 2004; 45 (2):325–329. doi: 10.3349/ymj.2004.45.2.325. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kingsley S.L., Eliot M.N., Kelsey K.T., et al. Variability and predictors of serum perfluoroalkyl substance concentrations during pregnancy and early childhood. Environ. Res. 2018; 165 :247–257. doi: 10.1016/j.envres.2018.04.033. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Knutson K.L., Van Cauter E., Rathouz P.J., DeLeire T. Trends in the prevalence of short sleepers in the USA: 1975-2006. Sleep. 2010; 33 (1):37–45. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• LaCaille L.J., Nichols Dauner K.N., Krambeer R.J., Pedersen J. Psychosocial and environmental determinants of eating behaviors, physical activity, and weight change among college students: a qualitative analysis. J. Am. Coll. Health. 2011; 59 :531–538. [ PubMed ] [ Google Scholar ]
• Lee H.P., Gourley L., Duffy S.W., Estéve J., Lee J., Day N.E. Dietary effects on breast-cancer risk in Singapore. Lancet. 1991; 337 (8751):1197–1200. doi: 10.1016/0140-6736(91)92867-2. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Lemkey-Johnston N., Reynolds W.A. Nature and extent of brain lesions in mice related to ingestion of monosodium glutamate. J. Neuropathol. Exp. Neurol. 1974; 33 (1):74e97. [ PubMed ] [ Google Scholar ]
• Li J., Qu M., Wang M., Yue Y., Chen Z., Liu R., et al. Reproductive toxicity and underlying mechanisms of di(2-ethylhexyl) phthalate in nematode Caenorhabditis elegans. J Environ Sci-China. 2021; 105 :1–10. doi: 10.1016/j.jes.2020.12.016. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Mancino L., Kinsey J. USDA, Economic Research Service; Washington, DC, USA: 2008. Dietary Knowledge Enough? Hunger, Stress, and Other Roadblocks to Healthy Eating 2008. [ Google Scholar ]
• Mondal D., Weldon R.H., Armstrong B.G., et al. Breastfeeding: a potential excretion route for mothers and implications for infant exposure to perfluoroalkyl acids. Environ. Health Perspect. 2013; 122 (2):187–192. doi: 10.1289/ehp.1306613. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Musaiger A.O. Consumption, health attitudes and perception toward fast food among Arab consumers in Kuwait: gender differences. Global J. Health Sci. 2014; 6 (6):136–143. doi: 10.5539/gjhs.v6n6p136. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Oginsky M.F., Goforth P.B., Nobile C.W., Lopez-Santiago L.F., Ferrario C.R. Eating 'junk-food' produces rapid and long-lasting increases in NAc CP-AMPA receptors: implications for enhanced cue-induced motivation and food addiction. Neuropsychopharmacology. 2016; 41 (13):2977–2986. doi: 10.1038/npp.2016.111. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Olney J.W., Sharpe L.G., Feigin R.D. Glutamate induced brain damage in infant primates. Glutamate-induced brain damage in infant primates. J. Neuropathol. Exp. Neurol. 1972; 31 (3):464e488. doi: 10.1097/00005072-197207000-00006. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Orozco-Guillien A.O., Muñoz-Manrique C., Reyes-López M.A., Perichat-Perera O., Miranda-Araujo O., D'Alessandro C., et al. Quality or quantity of proteins in the diet for CKD patients: does "junk food" make a difference? Lessons from a high-risk pregnancy. Kidney Blood Press. Res. 2021; 46 (1):1–10. doi: 10.1159/000511539. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Payab M., Kelishadi R., Qorbani M., Motlagh M.E., Ranjbar S.H., Ardalan G.…Heshmat R. Association of junk food consumption with high blood pressure and obesity in Iranian children and adolescents: the CASPIAN-IV Study. J. Pediatr. 2015; 91 (2):196–205. doi: 10.1016/j.jped.2014.07.006. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Preethi L., Ganamurali N., Dhanasekaran D., Sabarathinam S. Therapeutic use of Guggulsterone in COVID-19 induced obesity (COVIBESITY) and significant role in immunomodulatory effect. Obes. Med. 2021; 24 :100346. doi: 10.1016/j.obmed.2021.100346. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Ranjani H., Mehreen T.S., Pradeepa R., Anjana R.M., Garg R., Anand K., et al. Epidemiology of childhood overweight & obesity in India: a systematic review. Indian J. Med. Res. 2016; 143 :160–174. doi: 10.4103/0971-5916.180203. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Ritter A., Kreis N.N., Louwen F., Yuan J. Obesity and COVID-19: molecular mechanisms linking both pandemics. Int. J. Mol. Sci. 2020; 21 (16):5793. doi: 10.3390/ijms21165793. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Rouhani M.H., Mirseifinezhad M., Omrani N., Esmaillzadeh A., Azadbakht L. Fast food consumption, quality of diet, and obesity among isfahanian adolescent girls. J. Obes. 2012; 2012 :597924. doi: 10.1155/2012/597924. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Soliman M.M., Aldhahrani A., Alghamdi Y.S., Said A.M. Impact of Thymus vulgaris extract on sodium nitrite-induced alteration of renal redox and oxidative stress: biochemical, molecular, and immunohistochemical study. J. Food Biochem. 2021 doi: 10.1111/jfbc.13630. (Online ahead of print) [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Tong Y., Chabot J.G., Shen S.H., O'Dowd B.F., George S.R., Quirion R. Ontogenic profile of the expression of the mu opioid receptor gene in the rat telencephalon and diencephalon: an in situ hybridization study. J. Chem. Neuroanat. 2000; 18 (4):209–222. doi: 10.1016/s0891-0618(00)00043-0. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Velez M.P., Arbuckle T.E., Fraser W.D. Maternal exposure to perfluorinated chemicals and reduced fecundity: the MIREC study. Hum. Reprod. 2015; 30 (3):701–709. doi: 10.1093/humrep/deu350. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Visschers V.H.M., Siegrist M. When reduced fat increases preference. How fat reduction in nutrition tables and numeracy skills affect food choices. Appetite. 2010; 55 (3):730–733. doi: 10.1016/j.appet.2010.09.001. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Wang T., Xu F., Song L., Li J., Wang Q. Bisphenol A exposure prenatally delays bone development and bone mass accumulation in female rat offspring via the ERβ/HDAC5/TGFβ signaling pathway. Toxicology. 2021; 458 :152830. doi: 10.1016/j.tox.2021.152830. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Yang C., Lim W., Bazer F.W., Song G. Propyl gallate induces cell death and inhibits invasion of human trophoblasts by blocking the AKT and mitogen-activated protein kinase pathways. Food Chem. Toxicol. 2017; 109 (Pt 1):497–504. doi: 10.1016/j.fct.2017.09.049. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Ye J., Wang X.H., Sang Y.X., Liu Q. Assessment of the determination of azodicarbonamide and its decomposition product semicarbazide: investigation of variation in flour and flour products. J. Agric. Food Chem. 2011; 59 (17):9313–9318. doi: 10.1021/jf201819x. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Zahedi H., Kelishadi R., Heshmat R., Motlagh M.E., Ranjbar S.H., Ardalan G., et al. Association between junk food consumption and mental health in a national sample of Iranian children and adolescents: the CASPIAN-IV study. Nutrition. 2014; 30 (11–12):1391–1397. doi: 10.1016/j.nut.2014.04.014. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Zhang C., Wu X.C., Li S., Dou L.J., Zhou L., Wang F.H., et al. Perinatal low-dose bisphenol AF exposure impairs synaptic plasticity and cognitive function of adult offspring in a sex-dependent manner. Sci. Total Environ. 2021; 788 :147918. doi: 10.1016/j.scitotenv.2021.147918. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Zhu Y., Bo Y., Liu Y. Dietary total fat, fatty acids intake, and risk of cardiovascular disease: a dose-response meta-analysis of cohort studies. Lipids Health Dis. 2019; 18 (1):91. doi: 10.1186/s12944-019-1035-2. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]