obesity management essay

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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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Article Contents

Introduction, defining obesity, prevention of obesity, obesity and disease, diet, exercise, and lifestyle in managing obesity, behavioral therapy in managing obesity, medication in managing obesity, surgery in managing obesity, where do we go from here, abbreviations:, acknowledgments, the science of obesity management: an endocrine society scientific statement.

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George A Bray, William E Heisel, Ashkan Afshin, Michael D Jensen, William H Dietz, Michael Long, Robert F Kushner, Stephen R Daniels, Thomas A Wadden, Adam G Tsai, Frank B Hu, John M Jakicic, Donna H Ryan, Bruce M Wolfe, Thomas H Inge, The Science of Obesity Management: An Endocrine Society Scientific Statement, Endocrine Reviews , Volume 39, Issue 2, April 2018, Pages 79–132, https://doi.org/10.1210/er.2017-00253

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The prevalence of obesity, measured by body mass index, has risen to unacceptable levels in both men and women in the United States and worldwide with resultant hazardous health implications. Genetic, environmental, and behavioral factors influence the development of obesity, and both the general public and health professionals stigmatize those who suffer from the disease. Obesity is associated with and contributes to a shortened life span, type 2 diabetes mellitus, cardiovascular disease, some cancers, kidney disease, obstructive sleep apnea, gout, osteoarthritis, and hepatobiliary disease, among others. Weight loss reduces all of these diseases in a dose-related manner—the more weight lost, the better the outcome. The phenotype of “medically healthy obesity” appears to be a transient state that progresses over time to an unhealthy phenotype, especially in children and adolescents. Weight loss is best achieved by reducing energy intake and increasing energy expenditure. Programs that are effective for weight loss include peer-reviewed and approved lifestyle modification programs, diets, commercial weight-loss programs, exercise programs, medications, and surgery. Over-the-counter herbal preparations that some patients use to treat obesity have limited, if any, data documenting their efficacy or safety, and there are few regulatory requirements. Weight regain is expected in all patients, especially when treatment is discontinued. When making treatment decisions, clinicians should consider body fat distribution and individual health risks in addition to body mass index.

What’s past is prologue

Some would say that the obesity epidemic began in the 1980s, but history provides a broader view ( 1–3 ). Evidence of obesity in humans can be found in primitive art that dates back to the Paleolithic age ( 4 ). Two thousand five hundred years ago, Hippocrates cautioned that sudden death is more common in those who are naturally fat than lean ( 5 ).

In 1760, the English physician Malcolm Flemyng wrote that obesity can be called a disease, because it obstructs the free exercise of the animal functions and can shorten life ( 6 ). In 1810, William Wadd (Secretary of the Royal College of Surgeons in London) stated that the increase of wealth and the refinement of modern times may have banished plague and pestilence, but it has introduced nervous disorders and increased the frequency of corpulence ( 7 ).

Modern concepts of the pathophysiology of obesity date back to the end of the 18th century when Antoine Lavoisier established that life was synonymous with oxidation ( 8 ). More than 100 years later, Atwater and Rosa ( 9 ) applied the laws of thermodynamics to human beings, and during the 20th century, researchers discovered that hypothalamic tumors and tumors of the pituitary gland could cause obesity ( 10–12 ).

Obesity treatments date as far back as Hippocrates, who recommended lifestyle changes to obese patients ( 13 , 14 ). Two thousand years later, William Banting (an undertaker living in London in the 19th century) wrote one of the first “popular” diet books ( 15 ).

“Drug” therapies can be traced back at least to the 10th century when Hisdai ibn Shaprut cured “Sancho the Fat” of obesity using theriac—a mixture of more than 64 ingredients ( 16 ).

The first English language texts dealing with obesity treatment were published in 1727 and 1760 and recommended chamomile soap and vinegar, as well as other remedies ( 6 , 17 , 18 ).

By the beginning of the 20th century, doctors were using a number of medications for treating obesity ( e.g. , thyroid extract, dinitrophenol, and amphetamine), often with unfortunate outcomes ( 19 ).

The discovery of leptin in 1994 ( 20 ) (a peptide produced in adipose tissue) marks the beginning of the “molecular era” for obesity. People who are deficient in this peptide become massively obese. Leptin replacement therapy completely reverses obesity for these individuals. However, leptin treatment has proven ineffective in the typical obese patient who is not leptin deficient.

Rapid advances in basic science related to maintaining an appropriate amount of body fat have provided insights into potential treatments for obesity. This newer understanding of the regulation of food intake and body weight provides the basis for promising future developments ( 21 , 22 ).

Headwinds in the management of obesity

Despite progress in understanding obesity, advancements in the clinical management of the disease struggle against several headwinds.

First, obesity is a stigmatized condition. The general public and health professionals often respond negatively to overweight persons, which can negatively affect treatment ( 23 ).

Second, the desire for the cosmetic effects of weight loss often far exceeds the desire for the health benefits associated with reducing weight ( 24–26 ). This may well account for the fact that there are more women seeking help in managing obesity than men, even though the health issues related to obesity are similar between the sexes ( 27–29 ).

Although a modest 5% to 10% weight loss has proven health benefits, it often does not provide the cosmetic benefit that patients are looking for. This results in a mismatch between the patient’s goals for weight loss and what diet and exercise can realistically achieve ( 30 ). The same is true with surgical approaches to weight loss; patients often value the appearance of lost weight much more than the health benefits ( 25 , 29 , 31–33 ).

This stigma of obesity as a cosmetic issue vs a health issue also affects how the U.S. Food and Drug Administration (FDA) reviews drugs that manage weight loss. The FDA holds antiobesity drugs to a higher standard of review than other drugs, requiring that the risks from these medications be very low compared with drugs of other classes ( 34 ).

Finally, the lack of reimbursement by health insurers has resulted in poor sales of drug therapies for obesity, which only further dampens the pharmaceutical industry’s interest in developing drug therapies for obesity ( 35 ).

Historically, the medical community defined excess weight and its associated health consequences using population-based anthropometric measurements, ( i.e. , sex-specific body weight and height using life insurance tables) ( 36 , 37 ). However, these data only represented insured individuals based on normative standards without considering adiposity, and clinicians eventually abandoned these tables in favor of body mass index (BMI), which is a measure of body weight adjusted for height [weight (kg)/height (m 2 )].

The National Institutes of Health and the World Health Organization have both adopted BMI as a criterion for defining obesity ( 36 , 38 ). This made interpretation simpler, eliminated the need for sex-specific height/weight tables, and provided a measurement that is better correlated with other estimates of adiposity. The measurement is based on the observation that body weight is proportional to the squared height in adults with normal body frames. In adults, classification systems ( 38 ) and obesity guidelines ( 39 , 40 ) define healthy body weight as a BMI between 18.5 and 24.9 kg/m 2 , overweight between 25.0 and 29.9 kg/m 2 , and obesity ≥30 kg/m 2 . In children and adolescents, the U.S. Centers for Disease Control and Prevention (CDC) BMI-for-age growth charts define overweight as a BMI at or above the 90th percentile of standard weight and obesity as a BMI above the 95th percentile of standard weight.

BMI provides the most useful population-level measurement of overweight and obesity, and numerous large population studies across multiple continents have demonstrated its utility as an estimate of risk ( 41–43 ). Additionally, current assessment and management guidelines from the United States, Canada, and Europe recommend measuring BMI as a first screening step in evaluating adult and pediatric patients for obesity ( 39 , 44–46 ).

Overweight and obesity are worldwide problems ( 1 ) that affect >100 million Americans or 68.5% of the adult population. The most recent data from the 2013 to 2014 U.S. National Health and Nutrition Examination Survey indicate that obesity (defined as BMI ≥ 30 kg/m 2 ) affects ∼35.0% of men and 40.4% of women in the United States ( 47 ). Among children and adolescents aged 2 to 19 years, the prevalence of obesity in 2011 to 2014 was 17.0% ( 47 ). Fig. 1 shows the percentage of U.S. men and women categorized as overweight, obese, or extremely obese between 1960 and 2012. The category of extreme obesity (BMI > 40 kg/m 2 ) shows the greatest proportional change and is the most difficult group to effectively treat without surgery.

Trends in the United States for adults with obesity or overweight, 1960–1962 to 2011–2012 ( 48 ).

Among adult men, the prevalence of obesity is: Hispanic, 37.9%; black, 38.0%; white, 34.7%; and Asian, 12.6%. In women, the prevalence of obesity is: black, 57.2%; Hispanic, 46.9%; white, 38.2%; and Asian, 12.4%. In children and adolescents, 17.0% of 2- to 19-year-olds are obese, with males and females equally affected ( 47 ). The prevalence of obesity among children and adolescents is: Hispanic, 21.9%; black, 19.5%; white, 14.7%; and Asian, 8.6% ( 47 ).

Limitations of the BMI

Although research had demonstrated the utility of BMI in assessing population-based mortality and disease-specific morbidity, there are two major limitations in using BMI alone to diagnose obesity in an individual.

The first is the inability of BMI to distinguish weight associated with muscle vs fat.

Population studies have demonstrated a high specificity of using BMI cutoff values to diagnose obesity but low sensitivity to identify adiposity, thus missing approximately half of people with excess fat ( 49 ). This is particularly concerning in the elderly population, where a reduced lean body mass (sarcopenia) might be misclassified as a healthy BMI ( 50 ). Dual-energy x-ray absorptiometry or air displacement plethysmography are both accurate methods to assess lean body mass and body fat, but they are expensive and thus impractical for routine clinical application.

Using bioelectric impedance to measure body water provides a relatively inexpensive measure of body fat mass vs fat-free mass (as body fat contains more water). However, this method has large interindividual variations, suggesting that this method may be insufficient for estimating individual body fat mass and fat-free mass ( 51 ).

BMI also does not distinguish body fat distribution, a known determinant of metabolic risk. Measuring fat distribution helps identify higher risk individuals, because increased visceral fat predicts the development of the metabolic syndrome, type 2 diabetes mellitus (T2DM), and total and cardiovascular mortality risk better than total body fat alone ( 52–55 ). Several anthropometric techniques are available to estimate the distribution of body fat, such as waist circumference alone, the ratio of waist circumference divided by hip circumference (waist-to-hip ratio ([WHR]), and the ratio of waist circumference divided by height (waist-to-height ratio). These measures have been associated with the risk of developing heart disease, T2DM, and other chronic problems associated with obesity ( 56 , 57 ). Combining waist circumference with BMI provides a way to incorporate weight distribution into measures of obesity. Studies have demonstrated a strong link between waist circumference and BMI for both cardiovascular disease (CVD) and T2DM ( 58 , 59 ). Waist circumference is most useful in individuals with a BMI of ≤35 kg/m 2 ( 39 ). However, despite its promise, most clinicians only use BMI and not waist circumference as a gauge of risk from obesity. Beyond recommending annual BMI and waist circumference testing, the American Association of Clinical Endocrinologists also recommends evaluating other potential associated events ( 60 ).

Genetic factors are involved in the relationship of waist circumference to risk of CVD or T2DM. A polygenic risk score for increased WHR adjusted for BMI was significantly associated with adverse cardiometabolic traits and higher risks for both T2DM and coronary heart disease ( 61 ). A 1 standard deviation increase in WHR adjusted for BMI was associated with a 77% higher risk of T2DM (odds ratio, 1.77 [95% confidence interval (CI), 1.57 to 2.00]) and a 46% higher risk of coronary heart disease [odds ratio, 1.46 (95% CI, 1.32 to 1.62)].

There has also been concern about the association between obesity and visceral or central adiposity among children and adolescents, which has led to suggestions for using waist circumference in pediatric patients as well ( 62 ). However, there are many issues with the implementation of this in routine pediatric practice, such as lack of standardized definitions of waist circumference and the inability of waist circumference to add much to the strong association between BMI and comorbidity in children ( 63 ). If clinicians are going to use waist circumference to help define obesity in children, it is likely that we will need population-based percentile values, similar to those for BMI ( 64–66 ).

Because of these limitations, BMI has also emerged as the most useful approach in children >2 years of age ( 46 ).

Are there metabolically healthy people with obesity?

In cross-sectional studies, many individuals with obesity do not manifest “associated” comorbidities, such as prediabetes, dyslipidemia, hypertension, or other comorbidities ( 67 ). These individuals often have a predominantly lower body fat distribution and normal insulin regulation of adipose tissue lipolysis ( 68 , 69 ). The phenotype “metabolically healthy obesity” (MHO) meets the standard BMI cutoff point for obesity (≥30 kg/m 2 ) but does not have other elements of the metabolic syndrome, such as insulin resistance ( 70 , 71 ). They have lower levels of visceral and ectopic fat, less liver steatosis ( 71 ), and a lower degree of systemic inflammation. Among the 27 studies identified by Rey-López et al. ( 72 ), there were 30 definitions of metabolic health that relied on four criteria: blood pressure (BP), high-density lipoprotein (HDL) cholesterol, triglycerides, and plasma glucose. BMI ≥ 30 kg m 2 was the main criterion for obesity. In this group of studies, the prevalence of MHO ranged between 6% and 75% ( 67 , 72–74 ).

Whereas short-term cross-sectional studies suggest that MHO men and women are not at increased risk of CVD, longitudinal studies suggest that this phenotype may not be benign, and that this group is at higher risk for increased carotid artery intima-media thickness, coronary calcification, impaired vasoreactivity, and/or other cardiovascular events, as well as all-cause mortality ( 70 , 75–79 ). Therefore, clinicians should view MHO as a transient or intermediary state that may progress over time to an unhealthy phenotype in many people. Cardiorespiratory fitness is one factor related to MHO. Research has shown that cardiorespiratory fitness lowers the risk of all-cause mortality for metabolically unhealthy individuals with obesity and those with and without the MHO phenotype ( 80–82 ), suggesting that the inclusion of cardiorespiratory fitness along with BMI and waist circumference may improve the assessment of risk status. Several systems are available for evaluating and staging obesity when assessing risk ( 80–84 ). Increasing physical activity might thus be a valuable recommendation for individuals with MHO. Additionally, clinicians should observe these individuals for the risk of developing cardiometabolic disease ( 80–86 ).

There also has been interest in whether children and adolescents can be obese but metabolically healthy. Some pediatric patients with obesity, even some with severe obesity, have few metabolic or clinical abnormalities ( 83 ). However, the presence of obesity tends to track from childhood to adolescence and on to adulthood. Thus, there is a high likelihood that a child with obesity will become an obese adult, often with the severity of obesity increasing over time with ongoing weight gain. This makes it likely that children and adolescents with obesity, even when metabolically healthy at presentation, will develop associated diseases over time.

Age and obesity

The current guidelines for assessing obesity among adults do not consider age as an independent criterion. However, there are physiological and functional changes that occur among the aging population that may confound the interpretation of BMI and risk estimates in older people. Body composition changes associated with aging include sarcopenia, reduced bone mineral density, and the accumulation of visceral fat; BMI alone will not detect these changes ( 84 ). BMI values associated with the lowest relative mortality are slightly higher in older than in younger adults, which is often misinterpreted to suggest that obesity is not as harmful in the elderly. BMI may be a less appropriate index in the elderly because of sarcopenia ( 87 ). Centrally located fat (waist circumference) and relative loss of fat-free mass may become more important than BMI in determining the health risk associated with obesity in the elderly ( 88 ). The importance of loss of muscle mass was clearly shown in the Health ABC Study where older adults with greater thigh muscle loss had a higher risk of mortality compared with those with preserved thigh muscle, which suggests that efforts should be made to “conserve” muscle mass in old age ( 89 ).

During childhood and adolescence, there are substantial changes in growth, body composition, and pubertal status. During periods of rapid growth, weight and height may be somewhat mismatched, with weight gain preceding growth in height. However, in the past three decades, children are often gaining weight at a pace much faster than what could be considered healthy or normal.

Another critical period is the time when growth in height ceases and caloric requirements decrease. If calorie intake does not adjust, weight gain is the likely result.

Furthermore, adolescence is a time of relative insulin resistance ( 90 ). Because of this insulin resistance, adolescents who are obese become more susceptible to the development of T2DM.

Recent trends suggest that we are making some progress in the prevention and control of the obesity epidemic using several strategies outlined below. First, the prevalence of obesity among 2- to 5-year-old children has decreased significantly since 2003 to 2004 ( 91 ). Second, it has plateaued among 6- to 11-year-olds ( 47 ). In contrast, however, obesity has continued to increase in adult women ( 47 ).

“A 2015 Cochrane review found that diet, exercise, or both reduced excessive gestational weight gain by an average of 20%.”

Strategies for preventing obesity in pregnancy

Three systematic reviews relating weight gain during pregnancy and pregnancy outcomes found that dietary interventions reduced gestational weight gain and the risks of preeclampsia, hypertension, and shoulder dystocia in infants. No differences occurred in the incidence of small-for-gestational-age infants as a result of these treatments ( 92–94 ).

A 2015 Cochrane review found that diet, exercise, or both reduced excessive gestational weight gain by an average of 20%. Dietary interventions—including low glycemic index diets, supervised or unsupervised exercise programs, and diet combined with exercise—all had comparable effects. Maternal hypertension was reduced, but preeclampsia was not. No differences were found between intervention and control groups in the risk of preterm births or macrosomia. However, a 15% reduction in macrosomia occurred among women who were overweight or had obesity. Newborn respiratory distress syndrome was also decreased in the intervention groups among mothers who were either overweight or obese ( 95 ). Maternal consumption of sugar-sweetened beverages, similar to maternal smoking, may also have long-term detrimental effects on their offspring. Gillman et al. ( 96 ) reported that at an average age of 7.7 years children of mothers who consumed two or more servings per day during the second trimester of pregnancy were both fatter and heavier. This provides an additional important piece of information to provide to the pregnant woman.

Strategies aimed at children

The two most important settings for the prevention of obesity in children and adolescents are early care and education (ECE) and schools. Children spend a lot of time in these settings, where there are great opportunities for instilling positive behaviors regarding nutrition and physical activity.

Early care and education

Although millions of young children are enrolled in ECE, there are only a few intervention studies on preventing or mitigating obesity in these settings ( 97 ). One of these studies is the Romp and Chomp Intervention conducted in Australia. This study used multiple ECE and community interventions directed at children 0 to 5 years of age. The interventions included logical and proven targets for weight control, such as reducing sugar-sweetened drinks and energy-dense foods, increasing fruit and vegetable intake and active play, and reducing television time. The study reported significant reductions in obesity prevalence in 2- and 3.5-year-old children compared with children who did not receive the interventions ( 98 ).

Because of the immense impact that policy and environmental changes in ECE could have on childhood obesity, widespread efforts are underway to develop and incorporate standards and programs to increase physical activity and improve diets in ECE settings ( 99 ). One such program is the U.S. Department of Agriculture’s Child and Adult Care Food Program, which helps child care institutions provide nutritious foods that contribute to the wellness, healthy growth, and development of young children ( 100 ).

A recent Cochrane meta-analysis of 37 studies (including 27,946 children) ( 101 ) found beneficial effects of a number of components of school-based interventions. These included: school curricula that incorporate healthy eating, physical activity, and body image; increased sessions for physical activity and the development of fundamental movement skills throughout the school week; improvements in the nutritional quality of the food that schools supply; environments and cultural practices that support children eating healthier foods and being active throughout each day; support for teachers and other staff to implement health promotion strategies and activities ( e.g. , professional development, capacity building activities); and parental support and home activities that encourage children to be more active, eat more nutritious foods, and spend less time in screen-based activities ( 101 ). Beneficial effects were most notable in children 6 to 12 years old.

A number of long-term studies lasting ≥12 months provide more specific information on the effects of school-based interventions. We summarized these in Table 1 ( 102–110 ).

Long-Term Studies or Preventive Interventions in Children and Adolescents

Abbreviations: PA, physical activity; PE, physical education; RCT, randomized controlled trial; TV, television.

Randomized controlled trials (RCTs) have shown that the reduction or elimination of sugar-sweetened drinks (often through the substitution of calorie-free beverages) has effectively reduced rates of weight gain in children and adolescents ( 111 ). These observations are consistent with the association between reductions in sugar-sweetened drinks and both the decrease in the prevalence of obesity in 2- to 5-year-old US children and the plateau in the prevalence of obesity in 2- to 19-year-old US children. The absence of a significant effect in several of these studies may indicate that a significant caloric deficit relative to the control condition was not established or sustained ( 112 ).

Compared with efforts in specific settings, clinical interventions aimed at prevention have had limited impact ( 113 ).

Strategies aimed at adults: worksites

In 2009, the Center for Disease Control’s Task Force on Community Preventive Services concluded that worksite health promotion programs that improved physical activity and/or nutrition were effective in reducing body weight and BMI ( 114 ). Studies were limited to those with at least 6 months of follow-up. A pooled effect of nine RCTs found a weight decrease of 1.3 kg, and a pooled effect of six RCTs found a decrease of 0.5 BMI units ( 115 ). Most of the studies combined informational and behavioral strategies to influence diet and physical activity; fewer studies modified the work environment ( e.g. , cafeteria, exercise facilities) to promote healthy choices. Recent efforts to reduce sugar-sweetened drink consumption in hospitals have effectively used labeling and choice architecture as environmental strategies to reduce sugar-sweetened drink consumption ( 116 , 117 ).

Strategies for preventing obesity aimed at the entire population

Population-based messages aimed at the public concerning food and exercise require individual commitment if they are to be effective ( 118 ). If individuals follow the advice in the message, this strategy would be sufficient to overcome the epidemic of obesity. However, positive nutritional messages are often dwarfed by alternative messages urging consumption of less healthful foods, and the built environment is often a barrier to healthful exercise behaviors.

One approach might be to re-engineer the built environment to displace car use with physically active transportation options (such as walking and biking) and increase the number of accessible healthful food options ( 106 ). A systematic review by Papas et al. ( 119 ) identified 20 studies that examined the association between obesity and the numbers of outlets for physical activity and food, 18 of which were cross-sectional. Seventeen of these studies found a significant relationship between the built environment (food outlets or physical activity opportunities) and the risk of obesity. The number of recreational facilities and likelihood of overweight in adolescents were significantly related. However, few studies have examined the impact of changes in the built environment with changes in the prevalence of obesity. One exception is a study of the impact of housing changes among people living in poverty. Moving from a high-poverty neighborhood to a neighborhood of lower poverty was associated with a reduced prevalence of severe obesity ( 120 ).

Use of public transit has also been associated with increased levels of physical activity ( 121 ). For example, the implementation of a light rail system in Charlotte, North Carolina, was associated with a higher odds of meeting the daily physical activity requirement and a lower BMI ( 122 ). Neighborhood walkability appears to have much the same effect ( 123 ).

Faith et al. ( 124 ) concluded that manipulating the ease of food access and/or restricting access to certain foods might influence food purchases, consumption, and possibly weight change, although this requires further research. In contrast, the food industry favors the hypothesis that obesity results from reduced levels of physical activity and strongly supports providing more places for people to exercise and more healthful food alternatives as a strategy to help overcome the obesity problem ( 118 , 125 ). However, the expense of healthy food items and limited access to healthful foods in many lower income communities pose significant challenges. To address access to healthful food options, the Healthy Food Financing Initiative introduced supermarkets to underserved communities. However, this did not increase the consumption of healthful foods ( 126 ). Ideally, improved access needs to be accompanied by pricing and promotion strategies to increase consumption of more healthful products.

Some of the strategies for introducing healthful food options include introducing farmer’s markets, subsidizing the availability of fresh fruits and vegetables to school children, lowering the cost of fruits and vegetables while increasing the price of high-fat or high-sugar foods in school or worksite cafeterias, and/or changing marketing strategies. These strategies, for the most part, increase fruit and vegetable consumption ( 127–132 ). Importantly, however, note that addressing fruit and vegetable consumption alone might not be enough, as the impact of fruit and vegetable consumption on obesity prevention is uncertain. However, increased fruit and vegetable consumption does confer significant health benefits. Diets high in fruits and vegetables and low in fat and sugar lowered BP across the range of salt intake in individuals who were maintaining their body weight ( 127 , 133 ).

Taxation provides another strategy to reduce consumption of less healthful products by increasing their price. Smed et al. ( 134 ) has shown that among Europeans, increasing the tax or reducing the subsidies on unhealthful items and reducing the tax on healthful items through the value-added tax system could shift consumption toward healthier foods ( 135 ). Because of their contribution to obesity, taxation of sugar-sweetened drinks has become a major focus in the United States. Although many municipalities have imposed sales taxes on sugar-sweetened drinks, this approach is less effective than an excise tax, which increases the price of the product on the shelf. In 2014, Berkeley, California, passed a sugar drink tax of $0.01 per ounce. A study of sugar-sweetened drinks in that city reported that consumption in low-income neighborhoods (compared with two neighboring communities) declined by 21% and water consumption increased by 63% ( 136 ). In January of 2014, Mexico imposed an excise tax of 1 peso per liter on sugar-sweetened beverages. Colchero et al. ( 137 ) reported that purchases of these taxed beverages decreased 5.5% in 2014 and 9.7% in 2015, yielding an average reduction of 7.6% during the study period. Whether this translates into improvements in health outcome is currently unknown.

Increasing physical activity

As indicated above, physical activity levels in both children and adults have declined substantially. Helping incorporate exercise into how people get from where they live to where they learn, work, shop, play, and pray has become a prominent strategy to reverse this trend. Table 2 lists 10 strategies that the CDC’s Guide for Community Preventive Services identified for increasing physical activity ( 138 ).

Evidence-Based Recommendations To Increase Physical Activity in Communities

The CDC has also released a convenient guide that focuses on how to implement these strategies ( 139 ).

China provides an interesting example of how urbanization and improved incomes reduces physical activity ( 140 , 141 ). As recently as 20 years ago, the bicycle was a major mode of transport for Chinese. Since then, the automobile has relegated bicycles to museums.

Obesity and risk of death

For many illnesses related to obesity, there is a curvilinear increase in risk as a function of weight ( Fig. 2 ) ( 142 ). The Global Burden of Disease project ( 142 ) reported this relationship between BMI and all-cause mortality in 239 prospective studies that included >10 million people with a median follow-up of 13.7 years. Nearly 4 million subjects who survived 5 years were free of chronic diseases at recruitment. There was a clear J-shaped relationship between the BMI of the 385,879 who died and all-cause mortality. The lowest mortality was with a BMI of 20.0 to 25.0 kg/m 2 . Below this (BMI, 18.5 to 20.0 kg/ m 2 ), mortality significantly increased by 13% [hazard ratio (HR), 1.13]. In the individuals with a BMI of 25.0 to 27.5 kg/m 2 , all-cause mortality increased by 7% (HR, 1.07), and with a BMI of 27.5 to 30.0 kg/m 2 , it increased by 20% (HR, 1.20). For grade-1 obesity (BMI 30.0 to <35.0 kg/m 2 ), all-cause mortality increased by 45% (HR, 1.45), and for grade-2 obesity (BMI, 35.0 to <40.0 kg/m 2 ), it increased by 94% (HR, 1.94). For those with grade-3 obesity (BMI, 40.0 to <60.0 kg/m 2 ), all-cause mortality rose by 176% (HR, 2.76). For each 5 BMI unit increase, total mortality rose by 30%, mortality from chronic kidney disease rose by 60%, and mortality from T2DM rose by 120% ( 41 ).

BMI and all-cause mortality. Vertical bars are 95% CI. The Global Mortality Collaboration, 2016 ( 142 ).

Just as weight gain can increase the risk of mortality, weight loss can reduce the risk of mortality in obese individuals. The results from the Swedish Obese Subjects Study (which compared long-term follow-up of obese patients after surgical intervention for obesity with a matched but unoperated control group) showed a 29% reduction in overall mortality after 10.9 years ( 143 ). Individuals in the Look AHEAD trial had a similar outcome after a median follow-up of 10.2 years. Those who lost at least 10% of their body weight in the first year of the study had a 21% lower risk of the primary CVD outcome [HR, 0.79 (95% CI, 0.64 to 0.98); P = 0.034] and a 24% reduced risk of the secondary outcome [HR, 0.76 (95% CI, 0.63 to 0.91); P = 0.003] compared with individuals who were weight stable or gained weight. Participants in the intensive lifestyle intervention group who lost at least 10% of their body weight had a 20% lower risk of the primary CVD outcome [HR, 0.80 (95% CI, 0.65 to 0.99); P = 0.039] and a 21% lower risk of the secondary CVD outcome [HR, 0.79 (95% CI, 0.66 to 0.95); P = 0.011] compared with the control group ( 144 ).

The mechanism of obesity-associated morbidity

The effects of obesity on the body appear to be mediated by several major pathways. Fig. 3 shows how obesity as a disease process might lead to a variety of other diseases ( 145 ).

A schematic model of the intermediary mechanisms for dyslipidemia, insulin resistance, T2DM, heart disease, hypertension, some forms of cancer, OSA, NAFLD, and osteoarthritis.

A variety of types of adipose tissue dysfunction clearly play a role in the genesis of many obesity-related diseases. These include impairments in adipocyte storage and release of fatty acids, overproduction or underproduction of “adipokines” and cytokines ( 146 ), hormonal conversion, and the adverse mechanical effects of greater tissue mass.

The pathology of obesity is closely linked with body fat distribution. Upper body/visceral or ectopic fat accumulation is a much better predictor of insulin resistance, dyslipidemia, and such than total fat. Visceral fat is considered one of the “ectopic” fat depots, along with hepatic, intramyocellular, intramuscular, and pericardial fat. Humans with the ability to respond to excess energy intake by recruiting new, healthy subcutaneous adipocytes are relatively protected from many of the metabolic consequences of obesity. Those without this ability will store excess fat in ectopic depots, including liver, visceral fat, and muscle ( 147 ). This is supported by the finding that larger subcutaneous fat cells are associated with more accumulation of visceral fat during overfeeding, because they cannot expand to store more fat ( 148 ).

One study reported that the predisposition for T2DM was associated with impaired recruitment of new adipose cells to store excess lipids in subcutaneous adipose tissue ( 149 ). Another study reported that adults who develop more leg adipocytes in response to overfeeding have a lesser increase in abdominal subcutaneous adipose size ( 150 ). Fabbrini et al. ( 151 ) showed that those with MHO are resistant to the adverse metabolic effects of moderate weight gain, whereas metabolically unhealthy people are predisposed to such adverse effects. These authors concluded that increased adipose tissue capacity for lipogenesis might help protect people with MHO from weight gain–induced metabolic dysfunction, at least with modest weight gain during shorter periods of time.

In addition to the known toxic effects of excess fatty acids, abnormalities in the hormonal function of adipose tissue may contribute to metabolic disease. Adiponectin is the most abundant peptide produced by adipose tissue ( 152 ). It improves insulin sensitivity and vascular function. Adiponectin concentrations are inversely related to adipocyte size and visceral fat mass. In contrast, most adipokines are secreted in larger quantities as fat cells increase in size.

Researchers have discovered a large number of adipokines, but their exact role in disease is often unknown. The angiotensinogen produced by adipose tissue is a precursor for angiotensin, which can contribute to the risk for hypertension. Additionally, the aromatase enzymes in adipose tissue can convert sterols (androstenedione) to estrogen, which may explain the greater risk of breast and endometrial cancer in women with obesity, particularly postmenopausal women with obesity where estrogens derived from fat are their principal source of estrogens ( 153 ).

Type 2 diabetes mellitus

There is overwhelming evidence that BMI, central adiposity, and the increase in body weight predict future T2DM ( 154 ). A meta-analysis of prospective studies provided evidence that as upper body adiposity increases, both the risk of the metabolic syndrome and of developing T2DM also increase ( 155 ). The duration of obesity in younger compared with older individuals is also associated with a greater risk for T2DM ( 156 ). Weight gain in adult life increases the risk of developing T2DM, particularly in the age range 25 to 40 years ( 157 ).

The duration of increased body weight is also a risk factor for T2DM. For a given level of excess BMI-years in the National Longitudinal Survey, younger individuals compared with older ones (and Hispanic and black compared with white individuals) had a higher risk of developing T2DM ( 153 ).

Weight loss is clearly beneficial in reducing the risk of converting to diabetes. In the Diabetes Prevention Program, a median weight loss of 5.5% during 2.8 years reduced the risk of converting from prediabetes to diabetes by 58% ( 158 ). Similarly, bariatric surgery has repeatedly reversed diabetes to normal glucose tolerance ( 159–161 ).

Certain forms of cancer are significantly increased in individuals who are overweight ( 162 , 163 ). Males face increased risk for neoplasms of the colon, rectum, and prostate. In women, cancers of the reproductive system, including breast ( 164 ), endometrium ( 165 ), and gallbladder, are more common. Women who gained 25 kg or more after age 18 were at increased risk of breast cancer (RR 1.45 P < 0.001). Women who gained 10 kg or more after menopause were also at increased risk for breast cancer compared with women whose weight remained stable. Women who lost and maintained ≥10 kg and who did not use postmenopausal hormones were at lower risk than those who maintained weight (RR, 0.43) ( 166 ).

Breast cancer is not only related to total body fat but also may have a more important relationship to central body fat ( 167 ). This relationship to body fat may also help explain why breast cancer risk is increased at age 75 in women in the highest vs the lowest quartile of BMI ( 168 ). Circulating, unconjugated estradiol may mediate the relationship between increased body fat and breast cancer ( 169 ), as well as the relationship between increased body fat and the risk of endometrial cancer ( 169 ).

Myocardial infarction

Many studies show that as BMI increases, there is an increased risk for heart disease ( 170 , 171 ) and heart failure ( 172 ). Data from the Nurses’ Health Study indicate that the risk for U.S. women developing coronary artery disease is increased 3.3-fold with a BMI > 29 kg/m 2 compared with women with a BMI < 21 kg/m 2 ( 173 ). A BMI of 27 to <29 kg/m 2 increases the relative risk to 1.8. Weight gain also strongly affects this risk at any initial BMI. That is, at all levels of initial BMI (and within BMI categories) there was a graded increase in risk of heart disease with increasing waist circumference. Similarly, within waist circumference categories there was an increased risk of heart disease with increasing BMI ( 171 ). Major risk of CVD was increased 6% for each 1.1 kg/m 2 increase in BMI among 6452 British men ( 174 ).

Central adiposity, as reflected in waist circumference, is also a strong predictor of the risk for CVD ( 173 ). When increased central adiposity is added to other components of the metabolic syndrome, the prediction is even higher. Using the National Health and Examination Survey data, Janssen et al. ( 175 ) showed that BMI predicted the risk of the metabolic syndrome in men. However, when BMI is adjusted for waist circumference as a continuous variable, waist circumference accounted for essentially all of the risk for the metabolic syndrome. In a meta-analysis including 10 studies, indices of abdominal obesity (including WHR and waist circumference) were better discriminators than BMI of cardiovascular risk factors, including T2DM, hypertension, and dyslipidemia ( 176 ).

Both atrial fibrillation ( 177 , 178 ) and congestive heart failure ( 170 , 179 ) have a higher risk in subjects who are overweight. In the Multi-Ethnic Study of Atherosclerosis, the risk of congestive heart failure in obesity was associated with elevated levels of inflammatory markers (interleukin-6 and C-reactive protein) and albuminuria ( 180 ).

Heart failure and the obesity paradox

Obesity increases the risk of heart failure, yet some studies have found that elevated BMI may improve survival in individuals who already have congestive heart failure, a phenomenon called “the obesity paradox” ( 181–183 ). This appears to contradict the curvilinear relationship of BMI to body weight ( 41 , 88–91 , 93 ).

One possible explanation is “selection bias.” This occurs when studies select individuals as higher risk because they are identified after the disease develops rather than before. A simple way to eliminate this bias is to match the start of exposure to the start of follow-up. The same is true regarding the effect of obesity on the risk of mortality ( 43 , 184–187 ). Alternatively, the obesity paradox may reflect some capacity of the individual with obesity to overcome cardiovascular risk. Still another explanation for this paradox may be the difference between what BMI tells us and what the underlying fat distribution is doing. In a recent study, Padwal et al. ( 187 ) found that BMI and body fat have different predictive values for cardiovascular risk. If fat is the culprit, then measuring BMI may lead to an erroneous conclusion ( 187 ).

Hypertension and stroke

Hypertension is a global public health problem. Roughly 1 billion people worldwide are estimated to have clinically significant elevations in BP ( 188 ), with ∼50 million of them in the United States ( 189 ). Hypertension is the most important of 67 risk factors for worldwide risk of coronary heart disease, stroke, renal disease, and all-cause mortality ( 29 ). Furthermore, antihypertensive therapy results in reductions of incidence of stroke, myocardial infarction, and heart failure ( 190 ).

Among hypertensive individuals who reduced their BP levels following a successful weight-loss intervention, those who maintained weight loss also maintained lower BP levels, and those who regained weight returned to their baseline BP levels ( 191 ). In a meta-analysis of 25 studies, Neter et al. ( 192 ) found that weight loss averaging 5.1 kg after diet and/or exercise programs reduced BP by 4.4/3.5 mm Hg (systolic BP/diastolic BP). The studies with weight losses >5 kg showed larger decreases in BP than those with less weight loss.

Obstructive sleep apnea

In contrast to the relatively benign effects of excess weight on most components of respiratory function, overweight predisposes to obstructive sleep apnea (OSA), which can be severe and life-threatening ( 193 ). OSA is more common in men than women. An increased snoring index and increased maximal nocturnal sound intensity are characteristic. Nocturnal oxygen saturation is significantly reduced ( 194 ). A study of obese patients with diabetes using polysomnography showed that 30.5% of the participants had moderate OSA, and 22.6% had the severe form. Waist circumference was significantly related to the presence of OSA, and severe OSA was most likely in individuals with a higher BMI ( 195 ). Independently of obesity, OSA is associated with features of the metabolic syndrome, including hypertension, T2DM, and increased cardiovascular risk, possibly mediated by stress responses and hypoxia. Excess daytime sleepiness is an important consequence and can be a risk for driving and other tasks that require alertness ( 195 ).

Hepatobiliary disease

Gallbladder disease.

Obesity is associated with an increased risk of gallbladder disease. In a meta-analysis of gallbladder disease and obesity, Aune et al. ( 165 ) reported that the risk of gallbladder disease increased even within normal BMI ranges. For each 5-unit increase in BMI, the relative risk of gallbladder disease increased 63%. For a 10 cm increase in waist circumference, the increase in relative risk was 46%.

Nonalcoholic fatty liver disease

Fatty liver disease is often associated with obesity ( 196 ). Excess liver fat without inflammation/hepatocellular injury is called nonalcoholic fatty liver disease (NAFLD), which may progress to nonalcoholic steatohepatitis (NASH) and eventually cirrhosis. The diagnosis of NAFLD requires evidence of excess liver fat in the absence of secondary causes. NASH is diagnosed when there is evidence of hepatocellular injury (most often in the context of fatty liver) and is of greater concern because it poses a genuine risk of progression to fibrosis, cirrhosis, greater risk for hepatocellular carcinoma, and cirrhosis-related liver failure.

The prevalence of NAFLD ranges from 6% to 30%, depending on the diagnostic approaches and populations studied. The estimated prevalence of NASH is 3% to 5%. Both liver fat and fibrosis were increased as a function of time in nonhuman primates fed a high-fructose diet vs nonhuman primates without the added fructose ( 197 ).

NAFLD is considered by some to be the hepatic manifestation of the metabolic syndrome ( 198 ). Fatty liver is extremely common in patients undergoing bariatric surgery (prevalence 84% to 96%). The prevalence of fatty liver in the United States has been increasing steadily from 1988 to 2008 with obesity as an independent predictor ( 199 ). In a meta-analysis of 21 studies (13 of which were prospective), Li et al. ( 200 ) found that obesity produced a 3.5-fold increased risk of developing NAFLD. Moreover, there was a dose response to rising BMI, with the relative risk increasing 1.20 for each 1 unit increase in BMI. Another meta-analysis ( 201 ) found that for each 1 unit increase in waist circumference, the odds ratio of NAFLD increased 1.07, and for each 1 unit increase in BMI, the odds ratio increased 1.25. The prevalence is greater in Hispanic than white populations and less in blacks than whites. NAFLD and NASH are also more common in persons with T2DM.

Gout and osteoarthritis

Aune et al. ( 202 ) reported on the relationship of BMI to the risk of gout in 10 prospective studies that included 27,944 cases of gout among a population of 215,739 (median follow-up of 10.5 years). The summary relative risk for a 5-unit increment in BMI was 1.55 for all studies combined (95% CI, 1.44 to 1.66). The summary relative risk per 5-unit increase in BMI was 1.62 for men (95% CI, 1.33 to 1.98) and 1.49 for women (95% CI, 1.32 to 1.68). The relative risks were 1.78, 2.67, 3.62, and 4.64 for persons with a BMI of 25, 30, 35, and 40 kg/m 2 , respectively, compared with persons with a BMI of 20 kg/m 2 . The study also associated increased risk with BMI in young adulthood, WHR, and weight gain from age 21 to 25 to midlife, but the analyses included few studies.

Osteoarthritis

Osteoarthritis is likewise significantly increased in individuals who are overweight or obese. The osteoarthritis that develops in the knees and ankles may be directly related to the trauma associated with the degree of excess body weight ( 203 ). However, the increased osteoarthritis in non–weight-bearing joints suggests that some components of the excess weight may alter cartilage and bone metabolism independent of weight bearing. Increased rates of osteoarthritis account for a significant component of the cost of overweight and for the associated disability ( 204 ). Okoro et al. ( 204 ) found that class-3 obesity (BMI > 40 kg/m 2 ) was associated with survey-reported disability among individuals >45 years of age who reported arthritis, as well as those who did not report arthritis.

Effects of obesity during pregnancy

A narrative analysis of 22 reviews on pregnancy in women with obesity ( 205 ) showed that gestational diabetes, preeclampsia, gestational hypertension, depression, instrumental and cesarean birth, and surgical-site infection are more likely to occur in pregnant women with obesity compared with women with a healthy weight. Obesity in pregnancy is also linked to greater risk of preterm birth, large-for-gestational-age babies, fetal defects, congenital anomalies, and perinatal death. Additionally, breastfeeding initiation rates are lower, and there is greater risk of early breastfeeding cessation in women with obesity compared with healthy-weight women.

Diet in managing obesity—food is more than calories

The idea that single food items or diets are able to promote and maintain weight loss has stimulated numerous studies to investigate different proportions of dietary fat, protein, or carbohydrates as weight-loss diets ( 206 ) ( Table 3 ). Underlying all of these dietary approaches, however, is the fact that to lose weight, energy balance must be negative. Although calories are the essential component of energy balance, and reducing them is important for weight loss, food consists of more than calories. When choosing a diet, it is important to select foods that you enjoy and substitute lower calorie healthy foods that can improve the quality of your diet. Macronutrient composition aside, a reduction of energy intake is still an essential component of the effectiveness of any diet. In the Diabetes Prevention Program, calorie reduction was the major predictor of weight loss ( 207 ). Reduced intake in fat was the second predictor, and physical activity was only an important predictor when the calorie intake was unchanged ( 207 ).

A Comparison of Various Diet Programs and Eating Plans to a Typical American Diet

Abbreviations: AHA, American Heart Association; ACC, American College of Cardiology; Carb, carbohydrate; RCT, randomized controlled trial; TOS, The Obesity Society.

A calorie deficit of 500 kcal/d produces a weekly deficit of ∼3500 kcal, which is roughly equivalent to the energy in 1 pound (0.45 kg) of fat tissue ( 208 ). Although this calculation would predict linear weight loss, weight loss is not linear; it is curvilinear. At the initial stage, weight loss tends to be more rapid, and then slows until it reaches a plateau ( 208–211 ). The initial reduction of calorie intake initiates a number of compensatory mechanisms, which tend to drive food intake up and reduce weight loss ( 212–214 ).

Several factors contribute to the different patterns of response during weight loss. The first is the initial rate of weight loss ( 215 ). In the Look AHEAD trial, a multicenter clinical trial in individuals with diabetes, those in the highest tertile of initial weight loss in the first 2 months had nearly twice as much weight loss at 4 and 8 years compared with those in the lowest tertile of weight loss in the first 2 months. This could be explained by the fact that adherence to any dietary program is critical to successful weight loss ( 211 , 216–218 ).

Genetic variation can also influence weight loss, as can the biological response to different diets ( 219 , 220 ). In both the Diabetes Prevention Program ( 219 , 220 ) and the Preventing Overweight Using Novel Dietary Strategies (POUNDS Lost) Study ( 220–227 ), individuals with the A genotype of the fat mass and obesity-associated ( FTO ) gene had greater weight loss when assigned the high-protein diets but not when eating the low-protein diets ( 222 ). Another analysis, which examined eight clinical trials in overweight or adults with obesity, reported that the FTO genotype did not modify the response to diet ( 228 ). Using genetic profiles may thus be of value in the future for developing personalized dietary regimens for managing obesity, but more evidence is needed for any clinical applications.

Very low–calorie diets

We define very low-calorie diets (VLCDs) as those having an energy level between 200 and 800 kcal/d. In a review comparing low-calorie diets with VLCDs, Tsai and Wadden ( 229 ) reported that VLCDs produced significantly greater short-term weight loss (16.1%) than did low-calorie diets (9.7%) but similar longer-term weight loss.

Carbohydrate subtypes, low-carbohydrate diets, and sugar-sweetened beverages

Carbohydrates, such as sugar or high-fructose corn syrup, create additional challenges to a weight-loss diet, because added sugar in beverages provides extra energy with reduced satiety, thus increasing the total energy intake ( 230 ).

“Genetic variation can also influence weight loss, as can the biological response to different diets.”

In a meta-analysis, Nordmann et al. ( 231 ) found that weight loss was greater at 6 months with low-carbohydrate diets (defined as carbohydrate intake of <60 g/d) but not at 12 months (compared with other diets). In a meta-analysis of longer trials by Tobias et al. ( 232 ), interventions with similar intensity led to a significantly greater weight loss of 1.15 kg on the low-carbohydrate diets. This is in line with a meta-analysis by Bueno et al. ( 233 ), which showed a greater weight loss of 0.91 kg with very low–carbohydrate ketogenic diets. Although both are statistically significant, the absolute difference in weight loss was quite small (∼1 kg weight reduction in a 100-kg individual). These studies over the long term are hindered by the participants’ lack of adherence to the prescribed dietary regimens.

To circumvent the problem of variable effects of dietary protein in evaluating low-carbohydrate and low-fat diets ( 234 ), Hall and Guo ( 235 ) performed a meta-analysis of isocaloric low-carbohydrate/high-fat diets vs high-carbohydrate/low-fat diets where protein consumption was held constant. This analysis included 32 studies (563 subjects total), which provided all food to the subjects. Dietary carbohydrate ranged from 1% to 83% and dietary fat from 4% to 84% of total energy intake. There was a small but significant 26 kcal/d weighted mean energy expenditure difference favoring the low-fat/high-carbohydrate diets (not shown) and a small but significant 16 g/d weighted mean body fat difference favoring the low-fat/high-carbohydrate diets ( Fig. 4 ) ( 235 ). This analysis does not support the concept of a metabolic advantage for lower carbohydrate, higher fat diets, suggesting that any benefits of such diets probably involve differences in energy intake.

Weight loss comparing isocaloric low-carbohydrate/high-fat and high-carbohydrate/low-fat diets where meals were provided and protein consumption was the same. 95% horizontal CI. CHO, carbohydrate; ES, effect size; LCL, lower confidence limit; UCL, upper confidence limit; WMD, weighted mean difference. See Hall and Guo, 2017 ( 235 ).

Dietary fat, energy density, and low-fat diets

For decades, dietary recommendations for weight loss have emphasized a reduction in fat intake because of its high-energy content (9 kcal/g) compared with carbohydrates (4 kcal/g) ( 236 ). A meta-analysis of six trials reported no significant differences between low-fat diets (20 to 30 g/d or 20% of total energy) vs other weight-loss diets in terms of sustained weight loss ( 237 ).

A recent systematic review and meta-analysis compared the effects of low-fat interventions (<30% total fat) vs other dietary interventions on long-term (≥1 year) weight changes. It found that when the groups differed by >5% fat content, the higher fat interventions led to slightly greater weight loss and better adherence, although the magnitude of the differences in weight loss was small ( 232 ). The important message is that “adherence” rather than a specific diet is the important ingredient in success.

Another strategy for reducing energy density (besides reducing dietary fat intake) is to substitute foods with higher water content. One trial has compared a reduced-fat diet to a diet with extra fruits and vegetables with lower energy density. In this trial, the addition of fruits and vegetables led to greater weight loss compared with lowering fat only ( 238 ). Diets with a higher intake of fruits and vegetables evolved into the Volumetrics diet ( 239 ). The efficacy of the Volumetrics diet warrants further investigation.

Low–glycemic index diets

The glycemic index is based on the rise in blood glucose in response to test foods ( 240 , 241 ). A meta-analysis by Thomas et al. ( 242 ) reported a significant but small difference in weight loss of 1.1 kg that favored low–glycemic index diets. Additionally, both total and low-density lipoprotein (LDL) cholesterol fell more with low–glycemic index diets. The long-term effects of low–glycemic index diets warrant further evaluation.

Fasting glucose may provide a clue to dietary selection. Hjorth et al. ( 243 ) have reported that individuals with higher fasting glucose who are prediabetic may respond better to a lower glycemic index diet with more fiber and whole grain.

High-protein diets

A 2-year study comparing 12% and 25% protein diets as part of a 30% fat diet ( 244 , 245 ) reported that weight loss during 24 weeks was substantially greater with the higher protein diet, and that this result was maintained up to 56 weeks but not at 104 weeks.

A meta-analysis of energy-restricted, high-protein/low-fat diets compared with standard-protein/low-fat diets showed that the high-protein diet was better at reducing body weight (−0.79 kg; 95% CI, −1.50 to −0.08 kg), fat mass (−0.87 kg; 95% CI, −1.26 to −0.48 kg), and triglycerides (−0.23 mmol/L; 95% CI, −0.33 to −0.12 mmol/L) and resulted in less of a decrease in fat-free mass (0.43 kg; 95% CI, 0.09 to 0.78 kg) and resting energy expenditure (595.5 kJ/d; 95% CI, 67.0 to 1124.1 kJ/d) ( 246 ). In the intent-to-treat analysis of the POUNDS Lost Study ( 218 ), which compared 15% and 25% protein diets, there was no difference in weight loss between these diets. However, those who adhered to a higher protein diet lost more weight. When this study used urinary nitrogen loss as a measure of protein intake, those with the greater increase in protein intake lost significantly more weight ( 247 ).

Mediterranean-style diets

Mediterranean-style diets are characterized by enhanced consumption of olive oil, nuts, whole grain, fruits, and vegetables. In diabetic individuals, the Mediterranean diet produced a greater weight loss during 4 years than did a low-fat diet ( 248 ). Another meta-analysis ( 249 ) reported that Mediterranean diets reduced body weight 2.2 kg compared with low-fat diets. The Prevención con Dieta Mediterránea (PREDIMED) study from Spain showed that consumption of a high-fat Mediterranean diet (41.8% calorie from fat) resulted in a 0.43 kg weight loss ( P = 0.043) and a 0.55 cm waist circumference reduction ( P = 0.48) vs a comparison diet (37.4% calorie from fat) during 4.8 years of follow-up ( 250 ).

Balanced-deficit diets

Diets with a reduced content of carbohydrates, proteins, and fat (so-called “balanced-deficit diets”) have been widely used in managing obesity. In a meta-analysis, Avenell et al. ( 251 ) reported that intervention diets with an average deficit of 600 kcal/d led to a weight loss of 5.31 kg compared with controls, and the weight-loss effect lasted up to 3 years.

In a 6-month intervention, the daily use of a commercially available portion-control plate was effective in promoting weight loss among patients with obesity and T2DM when compared with a usual-care dietary group. A meta-analysis of six studies using meal replacements showed more weight loss than low-calorie diets at 3 months ( 252 ). Data from another trial showed that portion control can increase diet quality while maintaining significant weight loss during 18 months ( 253 ).

Comparison of diets with different macronutrient composition

Several RCTs have compared diets head-to-head ( 216 , 218 , 231 , 254 , 255 ). We summarize these in Table 4 ( 216 , 218 , 254–262 ). These studies show improvements in hemoglobin A1c (HbA1c) in patients with T2DM and improvements in triglycerides and HDL cholesterol in the groups assigned to the low-carbohydrate diet arms. One trial randomized 169 individuals with obesity to one of four popular diets, including the Atkins diet ( 263 ), The Ornish diet ( 264 ), the Weight Watchers diet ( 265 ), and the Zone diet ( 266 ). At the end of 12 months, each diet produced similar weight losses (∼5 kg). Adherence to the diets was the single most important criterion of success in these trials. In one study, a low-fat diet was compared with a low-carbohydrate diet (Atkins diet) and a Mediterranean-style diet ( 255 ). Compared with the low-fat diet, individuals assigned to the Mediterranean diet and low-carbohydrate diet had significantly greater weight loss and maintenance by 24 months ( 255 ). In a meta-analysis of numerous popular diets that included 48 unique trials, low-carbohydrate diets performed equally with low-fat diets after 12 months, with the low-carbohydrate diets resulting in 7.25 kg of weight loss (95% CI, 5.33 to 9.25 kg) compared with 7.27 kg of weight loss in the low-fat diet groups (95% CI, 5.26 to 9.34 kg) ( 267 ).

Weight Losses from Randomized Controlled Trials That Compared Diets With Varying Macronutrient Compositions

Different letters (in superscript) indicate statistically significant differences ( P ≤ 0.05) in weight loss between groups.

Abbreviations: MR, meal replacements; VLDL, very low–density lipoprotein.

The POUNDS Lost Study (the largest trial examining macronutrient composition and weight loss) randomized participants to one of four diets, with 80% of patients providing data on body weight at the end of 2 years. The diets were: (1) 20% fat/15% protein; (2) 20% fat/25% protein; (3) 40% fat/15% protein; or (4) 40% fat/25% protein. The foods in all four diets were the same, although they differed in quantity. At the end of 6 months, 12 months, and 2 years, the weight loss was similar for all four diets ( 268 ); however, those who achieved the largest increase in protein intake lost more weight ( 247 ). The similarity of the mean weight loss in all four diet groups obscures the wide range of individual weight losses shown in Fig. 5 ( 243 ). The data from the POUNDS Lost Study are consistent with the recommendations of the American College of Cardiology/American Heart Association/Obesity Society Guideline for the Management of Overweight and Obesity in Adults, which states that “a variety of dietary approaches can produce weight loss in overweight and obese adults, and that the choice should be based on the patient’s preferences and health status” ( 39 ).

Weight change from baseline to 6 months for each individual participant in the four dietary assignment groups ranked from the largest loser on the left to the most weight gain on the right. (a) (n = 38) Adequate-protein/low-fat group (15% protein, 20% fat, 65% carbohydrate); (b) (n = 43) high-protein/low-fat group (25% protein, 20% fat, 55% carbohydrate); (c) (n = 28) high-protein/low-fat group (15% protein, 40% fat, 45% carbohydrate); (d) (n = 30) high-protein/high-fat group (25% protein, 40% fat, 35% carbohydrate).

Commercial programs for weight loss

In a meta-analysis, Gudzune et al. ( 269 ) reported that the Weight Watchers diet resulted in at least a 2.6% greater weight loss than those assigned to control/education after 12 months. The Jenny Craig diet resulted in a 4.9% greater weight loss during a 12-month period vs groups receiving control/education and counseling. The Nutrisystem diet resulted in a 3.8% greater weight loss at 3 months vs control/education and counseling. VLCDs (Health Management Resources, Medifast, and Optifast) resulted in a 4.0% greater short-term weight loss than counseling, and the weight-loss effect lasted up to 6 months. The Atkins diet (not technically a commercial program, but one with affiliated diet products) resulted in 0.1% to 2.9% greater weight loss at 12 months compared with counseling ( 269 ). The differences in the amount of weight loss among various commercial diets were relatively small, and the long-term effects of these diets on weight control and chronic disease risk are still unclear.

Maintenance of long-term weight loss

As previously discussed and illustrated in the Diabetes Prevention Program ( 158 , 270 ) and the Look AHEAD trial ( 271 ), maintaining weight loss is a challenge.

One study ( 272 , 273 ) assigned participants to weight loss with a VLCD for 4 weeks before randomizing them to either a control diet or study diet supplemented with 48.2 g/d of protein. At the end of 3 months, the group receiving the protein supplement (to bring protein to 18% of total energy) had a 50% reduction in body-weight regain.

Data from the Women’s Health Initiative indicate that reducing dietary fat intake may be of value for long-term weight maintenance ( 274 , 275 ). The study reported that body weight in the low-fat diet group and the control-diet group was similar after an average of 7.5 years of follow-up ( 274 ). However, those who maintained the lowest quintile of fat intake were 1.5 kg lighter compared with those in the top quintile of fat intake, who were 0.8 kg heavier after 7 years. A recent comprehensive meta-analysis indicated that long-term effects of low-fat diets on body weight depended on the intensity of intervention in the comparison group. When compared with other dietary interventions of similar intensity, evidence from RCTs does not support low-fat diets over other dietary interventions ( 232 ).

The National Weight Control Registry identifies additional strategies for maintaining weight loss ( 276 ), which include engaging in higher levels of physical activity ( e.g. , 225 to 300 min/wk), eating a low-fat, low-calorie diet (1200 to 1300 kcal/d for women), and weighing themselves frequently (once a week or more) ( 277 , 278 ).

Prediction of weight gain may also be related to the ability to metabolize carbohydrates. Subjects who had a higher positive carbohydrate balance on day 15, were inactive, and ate an isocaloric high-carbohydrate diet gained less fat mass during a 4-year follow-up period ( 279 ).

Future considerations/summary

Diets with many different macronutrient compositions can result in short-term weight loss. However, weight loss reaches a plateau within the first 3 to 6 months. After that, weight is regained and often returns to baseline by 1 to 2 years.

Maintenance of long-term weight loss is strongly influenced by the ability to adhere to the dietary program. Behavioral support can significantly improve outcomes. There are variations among individuals in the response to each diet, which are larger than the difference in mean weight loss between comparison diets. Clinicians should consider genetic differences regarding dietary response to weight loss, as personalized dietary regimens might improve the efficacy of long-term weight-loss regimens.

Current data indicate that some (but not all) individuals can achieve modest long-term weight loss with any one of the diets evaluated herein. Additional research is needed to identify optimal diets for weight control and long-term health, which should extend beyond macronutrient composition and examine food quality and overall dietary patterns, as well as factors that can improve long-term compliance. The Nurses Health Study and Health Professionals Follow-up Study reported that improving diet quality was associated with less weight gain, especially in younger women or individuals who are overweight ( 280 ).

Exercise in managing obesity

There is a significant body of evidence supporting the effect of physical activity in both short-term and long-term weight loss in adults ( 216 , 218 , 254–262 ).

The main components of energy expenditure (by order of magnitude) are resting energy expenditure, physical activity, and the thermic effect of food. Resting energy expenditure is the amount of energy required for a 24-hour period by the body during resting conditions. Physical activity is composed of both nonexercise activity thermogenesis and thermogenesis due to volitional activity of muscle groups. The thermic effect of food is the amount of energy (above the resting rate) used for processing and storing food.

Energy expenditure from physical activity is directly related to body weight. However, it is unclear to what extent reductions in energy expenditure from physical activity relate to the epidemic of obesity that has developed during the last 30 years. Most measurements of energy expenditure are not precise or easy to use. Therefore, reliable longitudinal data are lacking.

Two recent studies have concluded that the current epidemic of obesity is more the result of an increase of energy intake than a decrease in energy expenditure ( 281–283 ), but this is not the universal opinion ( 280 ).

Genetic factors of physical activity

There is an important genetic component associated with the extent to which individuals engage in physical activity ( 284 ). In a study examining regular exercise among identical and fraternal twins that included both same and opposite sex pairs, environmental factors shared by children at age 13 accounted for 78% to 84% of sports participation, whereas genetic differences provided almost no contribution. By age 17 to 18 the genetic influences represented 36% of the variance in the level of participation in sports, and by age 18 to 20, genetic factors accounted for almost all (85%) of the differences in participation in sports ( 284 , 285 ).

Resistance vs aerobic exercise

Although most research on the effects of physical activity on body weight has focused on aerobic types of physical activity, there is also evidence suggesting that resistance exercise may have some effect on weight loss. Resistance exercise may influence body weight by increasing lean body mass, which will result in an increase in resting metabolic rate. Resistance exercise also improves one’s strength, which may result in more free-living physical activity and thus increased total daily energy expenditure ( 286 ). However, the vast majority of data indicate that resistance exercise only results in minimal reductions in body weight or body fatness ( 286–288 ).

Vigorous vs moderate exercise

A study of >4500 adults from the U.S. National Health and Nutrition Examination Survey showed that greater physical activity was associated with a lower BMI ( 289 ). This relationship only existed with moderate- to vigorous-intensity physical activity and not with low-intensity physical activity. These data imply that there is an intensity threshold of physical activity that is necessary to affect body weight and prevent excessive weight gain.

Physical activity declines with age

Despite the benefit of physical activity in weight loss, physical activity appears to decline during adolescence and remains low in most adults ( 290 , 291 ). In a longitudinal study of adolescent girls, the level of activity declined in both black and white girls each year during adolescence. By age 17, black girls engaged in almost no spontaneous physical activity and white girls only engaged in very modest amounts of spontaneous physical activity ( 292 ). We do not have a comparable study in adolescent males.

Sedentary behavior

There is keen interest in the influence of sedentary behavior on a variety of health-related outcomes, including overweight and obesity. Energy expenditure in occupational activities has declined by ∼140 kcal/d since 1960 in the United States, and this reduction in energy expenditure accounts for a significant portion of the increase in mean U.S. body weights for women and men since 1960 ( 293 ).

Much of the early literature in this area focused on the association between television viewing as an indicator of sedentary behavior and the risk of obesity. Television viewing is positively associated with the risk of gaining weight and the development of obesity ( 294 , 295 ).

Treatment of patients who are overweight or obese using exercise with and without diet

Studies on obesity have evaluated exercise as a sole treatment, in combination with diets, and as a way to maintain weight loss. Östman et al. ( 296 ) performed a Medline search for studies related to physical exercise and overweight and identified six relevant RCTs. Five had a treatment interval of 12 months, and all had a dropout rate of <40%. Table 5 ( 296–304 ) has been adapted from this study with the addition of two newer trials, one 16 months long and one 8 months long. The effects from diet are significantly greater than those from exercise, but increasing physical activity may have important benefits on improving BP and cardiometabolic risk factors.

Clinical Trials of Exercise in Individuals Who Are Overweight or Obese

Abbreviations: BW, body weight; DXA, dual x-ray absorptiometry; TG, triglyceride; VAT, visceral adipose tissue.

Adapted and updated from Östman et al., 2004 ( 296 ).

Behavioral modifications and/or lifestyle interventions have been an important part of weight-loss programs for more than half a century ( 305–307 ). Data from two large RCTs, the Look AHEAD trial and the Diabetes Prevention Program, support the efficacy of these approaches. These studies are the gold standard and are notable for the frequency of contact, the emphasis on individualizing therapy, and the long-term emphasis on maintaining weight loss. Fig. 6 shows data from the Look AHEAD trial. The best outcomes are with frequent, face-to-face interventions. However, incorporating this in primary care is challenging.

Mean (±SE) weight losses during 8 years for participants randomly assigned to an intensive lifestyle intervention or diabetes support and education (usual-care group). Differences between groups were significant ( P < 0.001) at all years. DSE, diabetes support and education; ILI, intensive lifestyle intervention.

In a meta-analysis of behavioral weight-loss programs, LeBlanc et al. ( 308 ) reported a mean weight loss of −3.01 kg (95% CI, −4.02 to −2.01 kg) favoring the behavioral strategy, but the range of mean values was quite large (−0.71 to −8.30 kg).

Lifestyle interventions may also be effective for preventing weight regain ( 269 , 309 ). Patients who participated in group sessions every other week for 1 year after weight reduction maintained 13 kg of their 13.2 kg end-of-treatment weight loss ( 309 ). The most successful patients monitor their weight frequently and respond quickly to small increases in weight ( 276 ). This can be daily or several times a week, but some daily variation (−0.5 to 1.0 kg) is to be expected from fluctuations in body water.

Lifestyle methods

Self-monitoring.

Self-monitoring involves recording the type and amount of foods and beverages consumed, along with their calorie content and weight gain. Self-monitoring helps patients identify their eating patterns (including times and places associated with consumption) and also helps patients select targets for reducing calorie intake ( 310 ) ( Table 6 ).

Key Components of Comprehensive Behavioral Weight-Loss Interventions to Achieve a 7% to 10% Weight Loss

Stimulus control

Techniques of stimulus control teach patients to manage external cues, such as the sight or smell of food, as well as times, places, and events associated with eating ( 278 , 310 ). By decreasing exposure to problem foods, patients are less likely to overeat.

Goal setting

Goal setting helps patients make objective, measurable changes in eating, activity, and related behaviors ( 278 , 310 ). They are guided in setting specific targets for calorie intake, minutes of physical activity, and frequency of self-monitoring.

Problem solving

Problem solving teaches patients to analyze challenges they have in adhering to their diet and activity prescriptions ( 278 , 310 , 311 ). Patients learn to identify a number of possible solutions to the problem, pick the most promising one, and then implement it. They learn to identify cognitive distortions ( e.g. , “I will never be able to lose weight because I ate that dessert”) and to replace them with rational responses ( e.g. , “One hundred fifty calories of cake is not going to hinder my weight loss, particularly if I walk after dinner”) ( 312 ). It is important for patients to remember that the 150 calories needs to be “subtracted” in the future either with exercise or by reducing intake of some other carbohydrate/fat-containing foods.

Short-term efficacy

The structured behavioral programs, as described above, produce an average loss of 7 to 10 kg in the first 6 months but with great variability. Some lose no weight; others lose >10%. Seven to 10 kg weight loss is generally equivalent to a reduction of 7% to 10% of initial weight, because 100 kg is the average weight for patients in many studies ( 38 , 307 ). Patients require a high-intensity intervention to achieve these losses; lower intensity treatment is not as effective ( 38 ). Approximately 50% to 70% of patients achieve a ≥5% reduction in initial weight, a criterion for clinically meaningful weight loss ( 38 ). Individuals with the best attendance and greatest consistency in keeping self-monitoring records achieve the largest weight losses ( 277 ).

New developments in the delivery of behavioral treatment

Telephone-delivered programs.

Sherwood et al. ( 313 ) demonstrated that during a 6-month period, patients who received 20 intervention session phone calls lost an average of 4.9 kg; those who received 10 intervention calls lost 3.2 kg, and those who were self-directed lost 2.3 kg. Appel et al. ( 133 ) reported that a group that received weekly telephone coaching for 3 months, an Internet program for recording food intake and physical activity, and monthly coaching for an additional 18 months lost a mean of 6.1 kg at 6 months. The weight loss was generally well maintained at 24 months (4.6 kg) and was not significantly different than what another group achieved using an intensive in-person intervention (5.1 kg at 24 months) ( 133 ).

Perri et al. ( 314 ) demonstrated that women who were enrolled in extended-care programs that included problem-solving counseling delivered in 26 biweekly sessions via telephone or face-to-face regained only 1.2 kg in 1 year of treatment, vs 3.7 kg for those in a newsletter-only group.

“By decreasing exposure to problem foods, patients are less likely to overeat.”

Several studies that used structured dietary interventions ( i.e. , meal replacements and/or portion-controlled entrees) reported roughly equivalent weight losses when the same behavioral intervention was delivered in person or by telephone ( 315–317 ).

Digitally-delivered programs

Tate et al. ( 318 ) demonstrated that patients who were provided with a directory of Internet resources for weight management and also received 24 weekly lessons over 6 months via e-mail (where patients submitted their food and activity records online and received online feedback from an interventionist) lost 4.1 kg vs patients who only received the directory. In a 1-year follow-up study, Tate et al. ( 318 ) demonstrated that patients assigned to a low-intensity Internet intervention with the addition of weekly behavioral counseling lost 4.4 kg, whereas those receiving only the low-intensity Internet intervention lost 2.0 kg.

Harvey-Berino et al. ( 319 ) compared the same 24-session intervention provided either via Internet or on site. In 6 months, the on-site program resulted in 8.0 kg weight loss vs 5.5 kg for the Internet-only group.

These studies underscore the importance of patients keeping records of their food intake and physical activity and receiving feedback from a trained interventionist. Educational instruction ( i.e. , information) alone is not sufficient to induce clinically meaningful weight loss.

These studies also suggest that the most successful Internet programs are those in which therapists provide weekly e-mail feedback to patients. However, on-site behavioral programs still provide better results ( 320 ).

The reduced efficacy of Internet programs, however, is offset by the potentially greater accessibility and affordability of this approach, compared with traditional behavioral treatment.

Despite their popularity, little is known about the effectiveness of smart-phone applications for weight management. A recent study that compared usual primary care with or without the MyFitnessPal application revealed essentially no weight-loss difference between the two approaches during 6 months ( 321 ).

Early history

Medications for managing obesity have a long and checkered history ( 322 ). Treatment in the 18th century included soap ( 6 , 17 ) and vinegar mixed with a number of purgatives ( 18 ). Some treatments also used tobacco, a strategy people still use today to prevent weight gain.

In the late 19th and early to mid-20th century, three major groups of medications came into use: thyroid hormone, dinitrophenol, and amphetamine. Clinicians prescribed both thyroid extract and dinitrophenol (a product of the aniline dye industry) until negative side effects became evident ( 19 ).

Amphetamine became popular after 1937 when Nathanson ( 323 ) noted that 10 of 40 patients treated with amphetamine for narcolepsy had marked loss of appetite and weight. However, the abuse potential of amphetamines soon became apparent ( 324 ), and clinicians stopped prescribing them as a way to manage obesity.

Aminorex, another member of the amphetamine-like group, emerged in Austria and Switzerland in 1968, but it was removed from the market in 1972 due to associated pulmonary hypertension ( 325 ). Table 7 lists several drugs for obesity management that were associated with significant detrimental side effects ( 326 ).

Some Medications Used in the Past for Managing Body Weight That Were Withdrawn or Are Not Approved in the United States

From the end of World War II through 1994, there was considerable research on monoaminergic drugs. Researchers discovered that injecting norepinephrine into the central nervous system of experimental animals reduced food intake and activated thermogenesis. This resulted in a search for thermogenic drugs that could work through monoaminergic receptors.

During this period, researchers also synthesized many derivatives of amphetamine for treating obesity ( 327 ), along with serotonergic drugs and multiple monoamine reuptake inhibitors.

More recent drug development: continuing difficulties

The discovery of leptin in 1994 ( 20 ) marks the beginning of modern approaches to identifying drugs for treating obesity. Leptin is a peptide made primarily in adipose tissue. Its absence is associated with massive obesity in animals and human beings. Treatment with leptin reverses the obesity caused by leptin deficiency, indicating that there is a clear-cut molecular–genetic mechanism and a highly effective treatment of at least one type of obesity. However, because leptin failed to show adequate weight loss in obese persons who are not leptin deficient, trials were stopped ( 328 , 329 ). The discovery of leptin opened a flood of research to discover new treatments, some of which were withdrawn from the market due to health risks ( 22 ).

Medications approved by the FDA for treating obesity

In Table 8 ( 330 ) we list medications that are FDA approved for weight management in patients with obesity and divide them into two groups. First are the agents approved for long-term treatment of obesity. These include orlistat, lorcaserin, liraglutide, the combination of phentermine/topiramate extended release (PHEN/TPM ER), and the combination of naltrexone and bupropion sustained release (SR).

Drugs Approved by the FDA for Managing Patients With Obesity

Abbreviation: DEA, Drug Enforcement Agency.

See Bray and Ryan, 2012 ( 330 ).

The second group consists of older, sympathomimetic drugs that are FDA approved for short-term use, usually considered <12 weeks. The FDA did not use modern standards to evaluate these “short-term” medications for safety and efficacy. The FDA approved them using only data from small, short-term studies, and there are no cardiovascular outcome studies for these agents.

Importantly, note that in all the clinical trials evaluating these agents, the drug-vs-placebo study also included lifestyle interventions, such as diet and/or exercise, which contribute to the overall weight loss reported.

Also important to note, these drugs are all contraindicated for pregnant women, as is weight loss per se . Because weight loss can increase fertility, all women in a weight-management program that use medications should be cautioned about the need for contraception. If pregnancy does occur while a patient is taking any of these medications, the patient should immediately stop the medication and contact a medical professional.

Listed below are brief assessments of these drugs’ action, efficacy, and safety. More detailed information is in Figs. 7 ( 331 ) and 8 and Table 8 .

Diagram of the sites within the central nervous system where medications can have their effects. See Apovian et al. , 2015 ( 331 ).

Randomized controlled trial data showing weight loss with orlistat, lorcaserin, liraglutide, phentermine/topiramate, and naltrexone/bupropion. NB, naltrexone/bupropion; Phen, phentermine; SE, standard error; SR, sustained release; tid, three times a day; Top, topiramate.

Orlistat is a potent and selective inhibitor of pancreatic lipase that reduces intestinal digestion of fat. One clinical trial resulted in weight loss of 9% of body weight at 1 year, compared with ∼5.5% in the placebo group ( 332 ) ( Fig. 8 ). Another study achieved a weight loss of 11% compared with 6% in the placebo-treated group and a reduction of 37% in the development of T2DM in patients who had impaired glucose tolerance ( 333 ). In a meta-analysis of 31 studies using orlistat ( Table 9 ), the maximal weight loss (by modeling) was −6.65 kg, and half the maximal effect occurred by 35.4 weeks ( 334 ).

Weight Loss Associated With Use of Orlistat, Lorcaserin, Liraglutide, Topiramate/Phentermine, and Naltrexone/Bupropion

Maximal weight loss is the modeled maximal effect and does not contain the placebo effect.

Data are from Dong et al., 2017 ( 334 ).

Orlistat is the only medication the FDA approved for weight management in adolescents with obesity ( 335 ). Adherence to orlistat use falls off rapidly after initial prescription ( 336 ). Orlistat can cause small but significant decreases in fat-soluble vitamins, and clinicians should advise patients to take vitamin supplements. Rare cases of severe liver injury have been reported with patients taking orlistat. A causal relationship has not been established, but patients who take orlistat should contact their health care provider if itching, jaundice, pale color stools, or anorexia develop ( 330 ).

Lorcaserin selectively targets the serotonin-2c receptors to reduce food intake ( 337 ), but it has low affinity for the serotonin-2b receptors on heart valves.

The three clinical studies that provided the data for lorcaserin’s approval reported modest weight loss (see Fig. 8 for one of these trials). In a meta-analysis of five studies using lorcaserin ( Table 9 ), the maximal weight loss (by modeling) was −5.39 kg, and half the maximal effect occurred by 19.3 weeks ( 334 ). They also showed improvements in cardiovascular risk factors ( 338–341 ).

In preclinical toxicology studies in rats, there were more brain and mammary tumors. This may reflect the fact that the drug does not reach the high concentrations in the central nervous system of human beings that is does in rats ( 341 ).

Liraglutide

Liraglutide is a GLP-1 agonist that has a 97% homology to GLP-1. The molecular change extends the circulating half-life from 1 to 2 minutes to 13 hours. Clinicians prescribe this drug in combination with a reduced-calorie diet and increased physical activity for chronic weight management in adult patients with an initial BMI of >30 kg/m 2 or in adult patients with a BMI of >27 kg/m 2 who have T2DM, hypertension, or dyslipidemia.

One study ( 342 ) that administered daily subcutaneous injections of liraglutide at 1.2, 1.8, 2.4, or 3.0 mg produced mean weight losses of 3.8, 5.4, 6.1, and 7.8 kg, respectively, after 1 year of treatment, compared with a loss of 2.0 kg in the placebo-treated group and 3.9 kg in the orlistat-treated comparator group. Another larger trial reported that after 56 weeks, liraglutide reduced body weight by 8.4 kg compared with 2.8 kg in the placebo-treated group (on average) ( 343 ) (see Fig. 8 ). In another trial ( 344 ), those receiving liraglutide for weight maintenance (after initially losing weight from a low-calorie diet) lost an additional 6.8 kg compared with no additional weight loss in the placebo group. Furthermore, only about half of the placebo group was able to maintain the weight they lost due to diet. In a meta-analysis of three studies using liraglutide ( Table 9 ), the maximal weight loss (by modeling) was −7.68 kg, and half the maximal effect occurred by 12.7 weeks ( 334 ).

Liraglutide is contraindicated in people with a family history of medullary thyroid carcinoma or multiple endocrine neoplasia syndrome type 2. Clinicians should not prescribe liraglutide for patients with a history of pancreatitis and should discontinue liraglutide if acute pancreatitis develops. If weight loss does not exceed 4% by 16 weeks, patients should stop taking liraglutide. Two cardiovascular outcome trials studied liraglutide (1.8 mg/d) ( 345 ) and the long-acting version, semaglutide (0.5 or 1.0 mg weekly) ( 346 ). In patients with T2DM, liraglutide lowered the rate of the first occurrence of death from cardiovascular causes, nonfatal myocardial infarction, or nonfatal stroke ( 345 ). Semaglutide lowered the rate of cardiovascular death, nonfatal myocardial infarction, or nonfatal stroke ( 346 ).

PHEN/TPM ER

PHEN/TPM ER has lower doses of phentermine than clinicians usually prescribe for phentermine alone. Phentermine acts to reduce appetite through increasing norepinephrine in the hypothalamus. Topiramate may reduce appetite through its effect on GABA receptors.

Two clinical studies ( 347 , 348 ) provided the efficacy and safety data for the approval of PHEN/TPM ER ( 341 ) (see Fig. 8 for one of these trials). The patients in these two studies had higher risk profiles due to excess weight. PHEN/TPM ER produced weight losses of 9.3% and 10.7% with the middle and high doses, respectively, compared with 2.2% in the placebo group. This weight loss is larger than observed in clinical trials with single drugs ( 349 ). In a meta-analysis of six studies using phentermine/topiramate ( Table 9 ), the maximal weight loss (by modeling) was 15.6 kg, and half the maximal effect occurred by 29.8 weeks (some of which was related to the titration schedule) ( 334 ).

Improvements in BP, glycemic measures, HDL cholesterol, and triglycerides occurred with both the recommended and the top doses of the medication in these trials ( 347 , 348 ). Improvements in risk factors were related to the amount of weight loss. In patients with OSA, this combination reduced the severity of symptoms ( 349 ).

Taking topiramate in the first trimester of pregnancy may increase risk of cleft lip/cleft palate in infants. Therefore, clinicians must inform women of childbearing potential of this risk and conduct a pregnancy test before prescribing PHEN/TPM ER. Glaucoma is a rare side effect of topiramate, and the drug is contraindicated in glaucoma. PHEN/TPM ER is also contraindicated in hyperthyroidism within 14 days of treatment with monoamine oxidase inhibitors and in patients with hypersensitivity to any of the ingredients in the medication. Topiramate is a carbonic anhydrase inhibitor that often produces tingling in the fingers and may change the taste for carbonated beverages. Other potential issues include risk of kidney stones (associated with topiramate) and increased heart rate in patients susceptible to phentermine.

Naltrexone/bupropion combination

Bupropion is approved as a single agent for depression and for smoking cessation. It reduces food intake by acting on adrenergic and dopaminergic receptors in the hypothalamus. It has a modest effect on weight loss. Bupropion stimulates the pro-opiomelanocortin neurons in the hypothalamus to produce pro-opiomelanocortin, which is further processed to produce both α -melanocyte stimulating hormone (which reduces food intake) and β -endorphin (which stimulates feeding). Naltrexone blocks this effect of β -endorphin, thus allowing the inhibitory effects of α -melanocyte stimulating hormone to reduce food intake by acting on the melanocortin-4 receptor system ( 350 ).

Three studies of the combination drug naltrexone/bupropion provided the basis for its approval.

In one study ( 351 ), weight loss at 56 weeks was 5.0% for a lower dose of naltrexone/bupropion (16 mg per day/360 mg per day) and 6.1% for a higher dose (32 mg per day/360 mg per day), compared with placebo. Treatment also improved waist circumference, fasting glucose, fasting insulin, homeostasis assessment model of insulin resistance (HOMA-IR), and HDL cholesterol, but there was a transient increase in BP.

In a second study that included an intensive behavioral modification program ( 352 ), weight loss at 56 weeks was about 9% for naltrexone/bupropion (32 mg per day/360 mg per day) vs about 1.8% ( Fig. 8 ) for placebo. The study also reported significant improvements in weight, waist circumference, insulin, homeostatic model assessment of insulin resistance, HDL cholesterol, triglycerides, and quality of life.

In a third study, weight loss at week 56 was 6.4% with naltrexone/bupropion (32 mg per day/360 mg per day) compared with 1.2% with placebo ( 353 ). As in the other studies, there were improvements in cardiometabolic risk markers, weight-related quality of life, and control of eating.

Finally, naltrexone/bupropion use in patients with T2DM resulted in significantly greater weight reduction (5.0% vs 1.8% in the placebo group) and significantly greater reductions in HbA1c (−0.6 vs −0.1%; P < 0.001) ( 354 ). There was also improvement in triglycerides and HDL cholesterol compared with placebo.

Efficacy of weight loss with the naltrexone/bupropion combination at 1 year is higher than lorcaserin but not as high as PHEN/TPM ER and is associated with improvements in risk factors ( 350 , 351 , 355 ). In a meta-analysis of six studies using naltrexone/bupropion ( Table 9 ), the maximal weight loss (by modeling) was −13.2 kg, and half the maximal effect occurred by 35.2 weeks (probably related to the titration schedule) ( 334 ).

Because bupropion increases pulse and both bupropion and naltrexone increase BP, an ongoing study is examining cardiovascular outcomes ( 345 ).

Comparison of medications approved for chronic weight management

There are no head-to-head comparisons of these medications. However, there is an analysis of 28 RCTs of weight-loss medications that included trials with orlistat, lorcaserin, liraglutide, naltrexone/bupropion, and PHEN/TPM ER. The inclusion criteria and background lifestyle interventions differed across studies, so we must interpret results with caution.

Attrition rates were 30% to 45% across these trials. All five agents were associated with significantly greater weight loss at 1 year than placebo. Collectively, these studies reported a weight loss of >5% in 23% of patients treated with placebo, 44% of patients treated with orlistat, 49% of patients treated with lorcaserin, 55% of patients treated with naltrexone/bupropion SR, 63% of patients treated with liraglutide, and 75% of patients treated with PHEN/TPM ER. The highest odds ratio for treatment-related discontinuation of the trial was with liraglutide and naltrexone/bupropion ( 356 ).

Drugs approved by the FDA for short-term treatment of patients with obesity

We group the sympathomimetic drugs benzphetamine, diethylpropion, phendimetrazine, and phentermine together, because they are noradrenergic drugs that the FDA tested and approved before 1973. The U.S. Drug Enforcement Agency classifies phentermine and diethylpropion as schedule IV drugs and benzphetamine and phendimetrazine as schedule III drugs. This regulatory classification indicates the government’s idea that these drugs have the potential for abuse, although this potential appears to be low ( 322 ). These drugs are approved for only a “few weeks” (usually 12 weeks).

Phentermine

Efficacy of phentermine..

The FDA approved phentermine as a single agent in 1959, and it remains the most commonly prescribed drug for weight loss in the United States ( 350 ). There are few current data to evaluate its long-term efficacy.

A 6-month study of phentermine reported that 15 mg/d resulted in 4.6% weight loss at 6 months compared with 2.1% for placebo ( 341 ). In another 6-month study of phentermine, weight loss was 5.5% for phentermine at 7.5 mg/d and 6.1% for phentermine at 15 mg/d compared with 1.7% for the placebo group ( 357 ). Finally, a study from Korea ( 358 ) reported that after 12 weeks, mean weight loss for phentermine was 8.1 ± 3.9 kg vs 1.7 ± 2.9 kg for placebo patients. Weight loss with phentermine may not be greatly enhanced by increasing doses beyond 15 mg ( 353 ).

Safety of phentermine.

Phentermine is part of a group of drugs called sympathomimetic drugs. These drugs produce central excitation, manifested as dry mouth, insomnia, or nervousness. This effect is most obvious shortly after the drug is started and wanes substantially with continued use. Sympathomimetic drugs may also increase heart rate and BP. The prescribing information usually recommends that the drugs not be given to individuals with a history of CVD ( 358–360 ).

Lacking good quantitative measures of the effects of sympathomimetic drugs on heart rate and pulse, we recommend caution in prescribing drugs in this group. According to the Endocrine Society Guidelines ( 331 ), clinicians should not prescribe sympathomimetic drugs to persons with a history of CVD and elevated BP.

Best practices for medications approved for weight management

The 2013 American Heart Association/American College of Cardiology/The Obesity Society “guideline for the management of overweight and obesity in adults” ( 39 ) and the 2015 Endocrine Society clinical practice guideline on obesity pharmacotherapy ( 331 ) both agree that clinicians may consider prescribing weight-reducing drug therapies for patients who: (1) struggle to achieve weight goals, (2) meet label indications (BMI > 30 kg/m 2 or BMI > 27 kg/m 2 with comorbidity), and (3) need to lose weight for health reasons (such as osteoarthritis, prediabetes, fatty liver, or other conditions). Furthermore, the American Association of Clinical Endocrinologists/American College of Endocrinology “comprehensive clinical practice guidelines for medical care of patients with obesity” from 2016 ( 60 ) indicate that clinicians may consider pharmacotherapy as a first-line treatment of weight reduction if patients present with one or more severe comorbidities and would benefit from weight loss of ≥10%. Those guidelines do not require that patients fail lifestyle therapy before clinicians prescribe medications.

Medicating the patient for other chronic conditions who is also overweight or obese

For patients who are overweight or obese, the 2015 Endocrine Society clinical practice guidelines on obesity pharmacotherapy ( 331 ) recommended that providers consider body weight when prescribing medications for other chronic health conditions, so that at-risk patients can avoid medications that promote weight gain. The guideline recommends that patients use medications that are weight neutral or associated with weight loss.

In managing patients with obesity, the guideline also advises that providers review medications at every visit and discuss weight effects with patients, so that patients at risk for weight gain can share in the decision process when choosing medications. Additionally, the guideline cautions against prescribing medications known to be associated with weight loss if they have no proven beneficial effect on the patient’s other identified health issues ( 331 ).

What is the current status of clinical adoption of medications for chronic weight management?

According to the Awareness, Care and Treatment in Obesity Management study ( 345 ), there are a number of misconceptions regarding obesity shared by providers and patients alike, specifically that obesity is not a disease, that patients have the primary responsibility for their problem and for its treatment, that prevention is more important than treatment, and that the risks of treatment should be low.

At present, the FDA has approved nine agents (five for long-term use and four for short-term use). For newer drugs, the time since approval of these medications is too short to know whether and how they will be used. However, older data (which predate the current medication landscape) indicate there are some serious concerns about how diet medications are used, such as: patients using prescription weight-loss pills who do not meet the BMI criterion for these medications; family, friends, and other nonphysicians providing medications; the use of nonprescription diet products; using pills after they were withdrawn from the market; low 1-year persistent use rates; and co-using narcotic and antidepressants ( 35 , 336 , 361 , 362 ).

Dietary supplements, over-the-counter products, and other treatments with unproven efficacy and unknown safety

The Dietary Supplement Health Education Act of 1994 provided the framework for an expansion in the use of non–FDA-approved, over-the-counter products in the United States billed as “dietary supplements.” As a result, there has been a proliferation in the use of these products.

This legislation helped undercut the credibility of legitimate weight-management practices by allowing the promotion of agents that are often unsafe, ineffective, and have unproven health claims. As long as the claim is not for disease treatment per se , and products are generally recognized as safe, they can be promoted for health claims. These agents are regulated by the U.S. Federal Trade Commission but not by the FDA, and thus they do not undergo the rigorous testing and review exercised by the FDA when it approves pharmaceutical preparations for patients who are overweight or obese.

Blanck et al. ( 363 ) reported that 15.2% of adults (20.6% of women and 9.7% of men) have used a weight-loss supplement, and 8.7% have used one in the past year (11.3% of women and 6.0% of men). Almost 10% (10.2%) used them for ≥12 months.

Pillitteri et al. ( 364 ) reported that females, the young, the less educated, and those with lower incomes are more likely to use these products. Many respondents thought that dietary supplements are safer than prescription drugs, and many overestimated the degree of regulatory screening of these products.

Clinicians should be aware and knowledgeable about these products when they begin discussing weight management with patients, since patients have likely taken them or may currently be taking them. Table 10 ( 365 ) provides a list of herbal and complementary medications and treatments that claim to improve weight loss. Evidence to support the effectiveness for weight loss or the safety of these preparations is usually nonexistent. Moreover, variability in the composition of these products adds an additional uncertainty to their use. We thus think that the public would be better served if the dietary supplements were held to a higher standard and were overseen by the FDA.

Complementary and Over-the-Counter Products Used for Weight Loss

See National Institutes of Health, Office of Dietary Supplements, 2015 ( 365 ).

Drug targets

Effective drugs to treat obesity have been slow to arise, but efforts are still underway to develop novel, effective, and transformative medications that would have the effect on treating obesity that statins had for high cholesterol or thiazides had for hypertension ( 366 ).

Surgical strategies (including the use of medical devices) for the purpose of inducing and maintaining clinically significant weight loss have emerged and evolved during the last 50 years. Surgeons performed ∼196,000 bariatric procedures in 2015 in the United States.

Sleeve gastrectomy (SG) is the most common procedure (53.8%), followed by Roux-en-Y gastric bypass (RYGB), 23.1%; laparoscopic adjustable gastric banding (LAGB), 5.7%; biliopancreatic diversion with or without duodenal switch, 0.6%; and revision and others, 16.8% ( 367 ). SG and RYGB together are the most popular procedures (77%), whereas LAGB has become less popular due to poor long-term results. We list the three most common surgical procedures in Fig. 9 ( 368 ).

The three most commonly performed bariatric surgical operations. (a) The laparoscopic gastric band is placed around the upper stomach to restrict the transit of ingested food. (b) Laparoscopic sleeve gastrectomy involves separation of the greater curvature from the omentum and splenic attachments. (c) RYGB involves the rearrangement of the alimentary canal, such that injected food bypasses most of the stomach, all of the duodenum, and a portion of the proximal jejunum. See Nielsen et al. , 2014 ( 368 ).

Evidence now indicates that that some of these bariatric procedures (which were intended to either physically limit the ingestion of food or produce malabsorption of energy-containing nutrients) actually produce durable weight loss and health benefits by altering metabolic processes, reducing appetite, and inducing satiety early after meal ingestion.

Sleeve gastrectomy

In SG, surgeons use a linear cutting stapler to make a narrow gastric tube along the lesser curvature of the stomach and remove the remaining 75% to 80% of the gastric body and fundus ( 369 , 370 ).

The lack of gastrojejunal anastomosis has theoretic benefits, such as reducing the risk of micronutrient deficiencies and peptic ulcer disease. Although some restriction of food intake may occur, gastric emptying is accelerated.

Roux-en-Y gastric bypass

RYGB refers to procedures in which a small (∼30 to 60 mL) gastric pouch is created just distal to the gastroesophageal junction with a stapling device. Most of the stomach is therefore disconnected (but not excised) from the alimentary stream.

The small gastric pouch is the restrictive component of this procedure. RYGB permits ingested food to pass directly from the esophagus through the small stomach pouch and proceed directly into the jejunum, with little or no gastric or duodenal phase of digestion, because food never enters the body of the stomach or the duodenum.

RYGB became a predominant weight-loss procedure in the 1990s and is used worldwide today. The development and demonstration of the safety and efficacy of minimally invasive (laparoscopic) techniques, the recognition of severe obesity as a disease, and the health benefits of bariatric surgery have led to a progressive increase in the number of gastric bypass procedures performed ( 143 , 160 , 371 , 372 ).

Laparoscopic adjustable gastric banding

LAGB constricts the upper stomach by placing a mechanical device encircling the stomach just beyond the gastroesophageal junction, thus creating a small (30 to 60 mL) pouch. The tightness of the band is adjusted by inflating a linear balloon fixed within the wall of the band. The balloon is connected to a subcutaneous port, so clinicians can tighten the band via a relatively simple percutaneous injection procedure. The band is intended to reduce the amount of food consumed ( 373 ).

Biliopancreatic diversion with (or without) duodenal switch

Biliopancreatic diversion with or without duodenal switch is a complex procedure in which ∼80% of the body of the stomach is resected, creating a tubular stomach (SG) based on the lesser curvature of the stomach. An anastomosis between the proximal duodenum and bypassed intestine creates a degree of malabsorption of nutrients. This procedure is infrequently performed because of a relatively high incidence of short-term and long-term complications, including micronutrient deficiencies ( 369 ).

Vagal blockade

In this procedure, leads are placed about the vagal trunks at the diaphragm to produce intermittent vagal blockade. Weight loss occurs by reducing appetite and inducing early satiety. The intermittent blockade is designed to avoid the neural adaptation that occurred with truncal vagatomy for peptic ulcer disease. Weight loss, although modest, is superior to sham-treated controls yet less successful than conventional surgical procedures, such as SG and gastric bypass ( 374 ). Despite a better safety profile than adjustable banding, intermittent vagal blockade has limited efficacy. This coupled with adverse events make it a less desirable intervention for resolving obesity and associated comorbidities ( 375 ).

Gastrointestinal endoscopic interventions or devices

Several devices, placed either by gastrointestinal endoscopy or suturing procedures, have become available. The FDA approved two gastric balloons in 2015 and another in 2016. Clinicians can fill the Orbera intragastric balloon system with 400 to 700 mL of saline. The ReShape integrated dual balloon system contains two connected, saline-filled balloons. In 2016 the FDA approved the Obalon balloon system, which expands with air after insertion. Technical improvements to these devices have resulted in a favorable safety profile ( 376 ). The present protocol requires removal of the intragastric balloon 3 to 6 months after placement, which is a limitation to the long-term efficacy of this intervention. The balloon can be replaced for those who regain weight ( 377 ). In August 2017, the FDA sent a letter to health care providers noting seven deaths associated with liquid-filled intragastric balloon systems used to treat obesity. Four of the reports involved the Orbera intragastric balloon system and one with the ReShape integrated dual balloon system. Two earlier deaths were also noted.

Researchers have also developed a specially designed percutaneous gastrostomy tube and apparatus, called the AspireAssist device, that allows patients to directly remove ingested food from the stomach ( 378 ). After 1 year with this device, patients lost 12.1% compared with 3.6% in the control group. This aspiration technique requires available facilities to discard the aspirated food and is not for everyone.

Additionally, endoscopic placement of a duodenal–jejunal luminal sleeve is under evaluation ( 379 ). In a study that examined endoscopic ablation of duodenal mucosa to enhance glycemic control of T2DM ( 380 ), reduction of HbA1c persisted 6 months after ablation.

Liposuction

Liposuction (also known as lipoplasty or suction-assisted lipectomy) is the most common esthetic procedure performed in the United States, with >400,000 cases performed annually ( 381 ). Although not generally considered to be a bariatric procedure, clinicians remove and contour subcutaneous fat by aspiration after injecting physiologic saline. As techniques have improved, it is now possible to remove significant amounts of subcutaneous adipose tissue without affecting the amount of visceral fat. In a study to examine the effects of this procedure, Klein et al. ( 381 ) studied seven diabetic women who were overweight and eight women with normal glucose tolerance that were overweight before and after liposuction. One week after assessing insulin sensitivity, the subjects underwent large volume tumescent liposuction, which consists of removing >4 L of aspirate injected into the fat beneath the skin. There was a significant loss of subcutaneous fat, but no change in the visceral fat. Subjects were reassessed 10 to 12 weeks after the surgery. The nondiabetic women lost 6.3 kg of body weight and 9.1 kg of body fat, which reduced body fat by 6.3%. The diabetic women had a similar response with a weight loss of 7.9 kg, a reduction in body fat of 10.5 kg, and a reduction in percentage fat of 6.7%. Waist circumference was also significantly reduced. Despite these significant reductions in body fat, there were no changes in BP, lipids, or cytokines (tumor necrosis factor- α , interleukin-6), or C-reactive protein. There was also no improvement in insulin sensitivity, suggesting that removal of subcutaneous adipose tissue without reducing ectopic fat depots has little influence on the risk factors related to being overweight.

Indications for bariatric surgery

Criteria for bariatric surgery.

The National Institutes of Health Consensus Panel in 1991 established the initial criteria for surgical interventions for obesity ( 382 ). The panel concluded that individuals with BMI ≥ 35 kg/m 2 with a related comorbidity or BMI ≥ 40 kg/m 2 were appropriate candidates for bariatric surgery. An additional criterion was failure of medical treatment to accomplish sustained weight loss. These criteria have been variably interpreted for many years but have remained essentially unchanged until the present.

In evaluating the outcome for any procedure, we need criteria for “successful” treatment. Weight loss is highly variable with all interventions. For example, intense lifestyle interventions in the Look AHEAD trial produced an average of 8.6% weight loss at 1 year and ∼5% at 4 years. However, this average covers considerable variability. In this study, the bottom 25% of participants lost <3% of their body weight in contrast to the top 25% who lost 12 kg ( Fig. 10b ) ( 383 ).

(a) Percentage weight trajectories. See Courcoulas et al., 2013 ( 383 ). (b) Percentage of participants in the intensive lifestyle intervention and diabetes support and education groups who achieved different categorical weight losses at year 8. See Look AHEAD Research Group, 2014 ( 271 ).

During active weight loss after surgery, BP decreases to a point where antihypertensive drugs may be discontinued. In addition, the requirement for hypoglycemic medications in patients with T2DM may also be diminished or discontinued. However, after weight stabilization, the results are less clear, as hypertension commonly reoccurs. Additionally, if weight is regained, comorbidities that were present at baseline may reappear. As a result, the question of what constitutes “successful medical therapy” is open to interpretation. Therefore, additional criteria for surgical interventions should include an understanding of operative risk and the ability to manage obesity and comorbid disease after surgery.

A recent joint statement by international diabetes organizations has indicated that bariatric or metabolic surgery procedures are a consideration for patients with poorly controlled T2DM and a BMI of 30 to 35 kg/m 2 ( 380 ). The Endocrine Society has also released pediatric guidelines for bariatric surgery ( 62 ).

Preoperative assessment

Preoperative assessment of potential bariatric surgical candidates includes confirming the patient’s understanding of the basic procedure(s) proposed and what he or she needs to do to help make the treatment successful. It also includes determining the patient’s dedication and motivation to make the behavioral changes necessary for a satisfactory outcome. Fig. 11 ( 384 ) contains a flowchart for managing bariatric patients with obesity.

Obesity management flow. Summarized from the 2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults ( 39 ). * refers to comorbid conditions. Reproduced with permission from Beamish et al ., 2016 ( 384 ).

The patient must also understand the risks associated with the procedure, and clinicians need to assess all related comorbid conditions and manage these conditions preoperatively. At a minimum, clinicians should meet standard guidelines for cancer screening, given the increased risk for common cancers in those with obesity (including breast and colon cancers). Clinicians should also identify and correct micronutrient deficiencies.

Many centers require preoperative weight loss, which may decrease the risk of perioperative medical complications of anesthesia and abdominal surgery. However, the role of preoperative weight loss in determining longer term outcomes (such as weight loss beyond 1 year) has not been demonstrated.

Outcomes of bariatric surgery

There is little or no disagreement about the benefits of weight loss among individuals with severe obesity, particularly those with comorbid conditions. These benefits, however, must be considered in the context of potential surgical complications. A population-based study in 2004 reported 2% mortality after RYGB ( 385 ). In response, the bariatric surgical community enacted several changes to improve safety. This included identifying the importance of surgeon experience and the experience of the particular surgical center; the establishment of pathways, care protocols, and quality initiatives; and the incorporation of all these aspects of care into the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program administered by the American Society for Metabolic and Bariatric Surgery and the American College of Surgeons.

The addition of laparoscopic procedures also contributed to improved safety. Recently, the Longitudinal Assessment of Bariatric Surgery (LABORATORIES) (a multicenter bariatric surgery research consortium funded by the National Institutes of Health) reported a 30-day overall bariatric surgery mortality rate of 0.3%. For laparoscopic RYGB, it reported a 30-day mortality rate of 0.2% ( 386 ).

A serious complication occurred in 4.1% of all patients. Factors that predicted a major complication include high BMI, extreme OSA, inability to walk 200 feet, and a history of deep vein thrombosis. Other studies have reported different risk profiles. Studies consistently report that the experience of both the surgeon and the surgical center are predictors of safety ( 386 ).

Mid-term and longer term complications have been well described, although determining their incidence is limited by a progressively greater number of patients lost to follow-up ( 387 ). These include, but are not limited to, intestinal obstruction, marginal ulcer, ventral hernia, and gallstones. Metabolic complications reported include nephrolithiasis, osteoporosis, and hypoglycemia. Mineral and vitamin deficiencies and weight regain are reported in variable numbers of patients. Micronutrient deficiencies following gastric bypass include: iron, 33% to 55%; calcium/vitamin D, 24% to 60%; vitamin B 12 , 24% to 70%; copper, 10% to 15%; and thiamine, <5% ( 388 ). Established guidelines recommend routine nutrient supplementation to include multivitamins, vitamin B 12 , iron, minerals, calcium, and vitamin D ( 389 , 390 ).

Perioperative complications specific to LAGB are less frequent, with near zero mortality. Longer term complications, however, continue to occur at a rate of ∼2% per year. These longer term complications include erosion of the gastric wall by the band and slippage or herniation of the body of the stomach, thereby creating obstructions within the band. Inadequate weight loss is the most common cause of LAGB failure. Complications following other device placement procedures occur but are infrequent and generally less severe. However, there is a tradeoff between reduced complication rates and the severity of complications vs efficacy of weight loss.

In summary, both perioperative and longer term complications occur after all bariatric surgical procedures. Multiple steps have been taken in recent years to reduce perioperative mortality and serious complications. Prospective data collection, analysis, and reporting to individual centers through the accreditation program will continue to identify complications and stimulate appropriate quality improvement initiatives.

Weight loss

The high degree of variability of weight loss following all interventions (including intense lifestyle intervention, medications, and virtually all bariatric surgical procedures) speaks to the complexity of severe obesity ( Fig. 10a and 10b ). We can define obesity in terms of excess weight represented by BMI. However, the genetic, behavioral, and environmental factors that underlie excessive weight gain in life are exceedingly complex and variable.

The same factors influence variability observed in the weight-loss phenotypes following surgery. After RYGB, for example, the LABORATORIES Consortium reported patterns of similar and rapid weight loss among patients 6 months after surgery by stratifying weight loss into five separate trajectories, ranging from 12% to 45% total body weight loss 3 years after surgery ( 391 ) ( Fig. 10a ). These weight-loss trajectories persist through 7 years ( 391 ).

Weight loss following LAGB is similarly variable, but only one-half of the total body weight loss seen with RYGB is seen after LAGB (on average). Thus, the commonly reported mean weight loss among populations undergoing bariatric surgery is of limited use for predicting results for individuals who are contemplating surgical treatment.

There have been many efforts to identify preoperative clinical predictors of postoperative weight loss. However, although research has established some statistical correlations, the extent of the variability explained by a number of clinical covariates has been disappointing ( 391 ).

The single best predictors of sustained postoperative weight loss (identified by the LABORATORIES Consortium) are postoperative eating and lifestyle behaviors. Specifically, subjects who self-monitor ( e.g. , frequent weighing), avoid eating when full, and who avoid snacking between meals appear to experience the greatest weight loss ( 392 ). The weight loss following RYGB, compared with interventions other than surgery ( Fig. 10a and 10b ), demonstrates that even the poorest weight loss following gastric bypass is comparable to the best reported weight loss for nonsurgical interventions ( 393 ). A third study found changes from baseline after 5 years in the surgical groups were superior to the changes seen with medical therapy. Body weight decreased 23% with gastric bypass, 19% with SG, and 5% with drug therapies ( 161 ). We must interpret these outcomes with the caveat that the requirement for surgical intervention is the failure of patients to accomplish sustained weight loss via other means, thereby creating a selected population.

Related outcomes/remission of T2DM

The remarkable remission of T2DM following RYGB has generated much interest given the prevalence of T2DM and the severity of this disease ( 394 , 395 ) ( Table 11 ) ( 396 , 397 ).

Weight Loss and Reversal of Diabetes Mellitus after Metabolic/Bariatric Surgery

Including data from Buchwald et al. , 2009 ( 396 ) and Bray, 2011 ( 397 ).

Analysis of the data from the LABORATORIES Consortium has demonstrated that both weight loss and the neuroendocrine effects specific to gastric bypass contribute to the remission of T2DM ( 159 ). The durability of the remission in many participants was sustained through year 7 ( 391 ).

The Swedish Obese Subjects study reported that ∼50% of gastric bypass patients who were in T2DM remission at year 2 had recurrence by year 10 ( 160 ). Weight loss in these groups is shown in Fig. 12 . Gastric banding was the predominant procedure in the Swedish Obese Subjects trial. This suggests that maintaining weight loss, as well as the incretin stimulation associated with RYGB, contributes to the durability of the remission. Reports of T2DM remission among patients with considerably less severe obesity (BMI 27 to 40 kg/m 2 ) have led to several RCTs in this patient population ( 398 ).

Mean weight change percentages from baseline for controls and the three surgery groups during 20 years in the Swedish obese subjects study. Data shown for controls obtaining usual care and for surgery patients obtaining banding, vertically banded gastroplasty, or gastric bypass at baseline. Percentage weight changes from the baseline examination and onward are based on data available on 1 July 2011. Error bars represent 95% CIs. Vertical error bars represent SEM. GBP, gastric bypass; VBG, vertically banded gastroplasty. See Sjöström et al., 2012 ( 393 ).

Most recently, SG has taken a dominant place in the spectrum of procedures used for weight loss worldwide ( 399 , 400 ). Although the weight loss and T2DM remission following SG appear to be slightly less than that following gastric bypass, lower perioperative complication rates, shorter lengths of stay, and lower costs have made SG an attractive bariatric surgical procedure ( 395 , 401 ). The mechanism and durability of this improved glycemic control, including the role of diet-induced weight loss, have not been determined ( 60 ).

Overall, there is considerable evidence favoring RYGB, LAGB, and now SG as superior methods for controlling or inducing remission of T2DM, vs intense medical treatment ( 380 ). As a result, the term “metabolic” surgery has become popular. The concept that clinicians should consider surgical intervention for patients with poorly controlled T2DM and patient with less severe obesity (class I) with T2DM (rather than having BMI be the primary indication for surgery) has gained widespread international support ( 380 ). Remission of dyslipidemia is also seen in most patients following effective surgical weight loss, whereas remission of hypertension is less frequent.

Bariatric/metabolic surgery in adolescents

Owing to the lack of effectiveness of nonsurgical options for treating severe obesity in young patients and the demonstrated safety and efficacy of bariatric surgery in adults, clinicians increasingly use surgical procedures to induce weight loss in selected adolescents with severe obesity. The rationale for and expectation of bariatric treatment in adolescents are to provide significant and durable weight reduction, correct existing health problems, and prevent expected comorbidities in those at risk.

Lifestyle modification and even pharmacotherapy in adolescents with severe obesity are associated with unsatisfactory outcomes, and any weight reduction seen may not be sustained. Conversely, growing evidence indicates that surgery results in 25% to 35% weight reduction in severely obese adolescents. In the Teen-LABORATORIES study, SG and RYGB were the most commonly performed procedures in adolescents, and 3-year outcomes demonstrated a similar weight loss of nearly 30% for these procedures ( 402 ).

The lower complexity of SG and the lower theoretical risk of at least some micronutrient deficiencies associated with RYGB make SG an attractive option for most adolescents, despite fewer published studies of SG in adolescent age groups.

In 2017, investigators in the United States ( 403 ) and Sweden ( 404 ) simultaneously reported long-term outcomes for weight loss and comorbidities in adolescents who underwent RYGB. Eight-year (United States) and 5-year (Sweden) post-RYGB surgery follow-up assessments indicated 30% and 28% BMI reductions, respectively. Both research groups documented important improvements in health.

In the U.S. study, remission of T2DM occurred in 88% (n = 7). The study did not report any incident T2DM during the 8 years. The study also reported dyslipidemia remission in 64% (n = 29) and incident dyslipidemia in four of eight subjects who did not have dyslipidemia at baseline. The study reported hypertension remission in 76% (n = 19) and incident hypertension in only 10% (3 of 29) participants without hypertension at baseline.

The Swedish study reported similar health improvements, with remission of comorbid conditions in 74% to 100% of participants. The study reported remission of T2DM in 3 of 3 participants, disturbed glucose homeostasis in 18 of 21, dyslipidemia in 43 of 52, elevated BP in 11 of 12, inflammation (high-sensitivity C-reactive protein ≥ 2 mg/L) in 45 of 61, and elevated liver enzymes in 19 of 19 participants.

Both studies also reported long-term nutritional effects. The U.S. study reported mild anemia in 46% (n = 25), hyperparathyroidism in 45% (n = 22), and low vitamin B12 levels in 16% (n = 8) at long-term follow-up. At 5 years in the Swedish study, 63% (46 of 73) had vitamin D (25-hydroxy vitamin D) insufficiency (<50 nmol/L) and 66% (51 of 77) had low ferritin and/or iron levels. The prevalence of anemia rose from 10% (8 of 78) to 32% (25 of 77), and 22% had low vitamin B12 levels.

In summary, the two long-term, prospective studies demonstrate excellent durability of weight loss and response of comorbidities for adolescents who have RYGB surgery. These studies also reported the typical nutritional consequences of RYGB that we see in studies in adults, and this must be taken into consideration when counseling patients about long-term risks of RYGB.

Current expert opinion recommends that clinicians should use criteria similar to those used for adults when selecting adolescents for weight-loss surgery ( 399 , 405 ). Surgery is generally recommended for adolescents with a BMI ≥ 40 kg/m 2 and a weight-related comorbid condition or impairment in quality of life. It is also recommended for those with a BMI of ≥35 kg/m 2 with significant current comorbidities, such as T2DM, dyslipidemia, OSA, hypertension, NASH, or pseudotumor cerebri ( 395 , 400 ).

In this Endocrine Society Scientific statement titled “The Science of Obesity Management: An Endocrine Society Scientific Statement,” we have documented the rising prevalence of obesity in both men and women in the United States and worldwide with resultant hazardous health implications. The prevalence of obesity is correlated with income disparity both between developed countries and between the states of the United States ( 406 ).

Obesity results in part from environmental and behavioral factors, and both the public and health care professionals alike stigmatize the condition. The opportunity to move from a neighborhood with a high level of poverty to one with a lower level of poverty was associated with modest but potentially important reductions in the prevalence of extreme obesity and diabetes ( 120 ), supporting the relationship between income inequality and obesity. Because the prevalence of obesity has strong social and environmental components, this may provide a basis for future approaches. The study by Christakis and Fowler ( 407 ) showed that “friends” of an individual with obesity were more likely to also be obese.

Obesity is lower when there are more opportunities for physical activity as part of everyday life, as shown by the slower rise in obesity among more active individuals during 10 years ( 123 ). Sleep time is a modifiable behavior, and the observation that preschool-aged children with early weekday bedtimes were one-half as likely as children with late bedtimes to be obese as adolescents offers further opportunities for intervention in the environment ( 408 ). These observations may provide the potential for more effective preventive strategies utilizing social engineering.

Genetic factors also play a role. Recently, insufficiency in the gene TRIM28 was shown to produce polyphenic obesity in both mice and humans. In this setting, both lean and obese phenotypes can arise from identical genotypes through dysregulation of an imprinted gene network ( 409 ). This finding and other genetic research into the mechanisms behind obesity may provide new genetic strategies for helping this segment of the population.

The hazards of obesity are many, including a shortened life span, T2DM, CVD, some cancers, kidney disease, OSA, gout, osteoarthritis, and hepatobiliary disease, among others. As might be expected, weight loss reduces all of these diseases in a dose-related manner.

The phenotype of MHO appears to be a transient state that progresses over time to an unhealthy phenotype, especially in children and adolescents. Understanding in more detail how complications of obesity develop will provide new opportunities for prevention of these negative outcomes.

Of particular interest are reports that two diabetes medications (liraglutide and empagliflozin) ( 345 , 410 ) also produce weight loss and are cardioprotective. Particularly striking is the fact that these two drugs reduce cardiovascular death to a greater extent than statins. This opens a whole new paradigm for managing patients with obesity and diabetes in relationship to their complications.

One of the unexplained issues in all treatment strategies is the marked variability in response of any form of treatment of obesity. Efforts to understand the biological basis of this variability may provide new insights into its treatment. The POUNDS Lost Study population of 811 individuals randomized to one of four diets (20% vs 40% fat and 15% vs 25% protein) has provided many genetic clues to help us better understand factors that modulate dietary response ( 206 , 411 ). The ability to combine several measures to predict responses to environmental factors may expand the option for personalized medicine. An algorithm that integrates blood parameters, dietary habits, anthropometrics, physical activity, and gut microbiota measured in a sample cohort ( 412 ) showed that these factors accurately predict personalized postprandial glycemic response to real-life meals. Similar strategies might well be developed for obesity. Many genes affect the response to diets, opening the possibility of “personalized medicine” for managing obesity.

The public commonly uses over-the-counter herbal preparations to manage obesity, but evidence documenting their efficacy or safety is usually absent. We think that the public would be well served by more regulatory requirements regarding sale and use of these products.

We can expect to see weight regain in all patients when they discontinue obesity treatments. When making treatment decisions, clinicians should consider body fat distribution and individual health risks in addition to BMI. Because all treatments have considerable variability in their outcome, it is important to know when to stop treatment as well as when to begin. Surgical strategies have demonstrated greater weight loss that outlasts other treatment options.

As the knowledge base underpinning obesity continues to expand, the options for treating patients with obesity should also expand, offering hope for future conquest of this problem. One fascinating new strategy is the combination of peptides acting on receptors in the gastrointestinal track into a single molecule acting on two or more receptors, called coagonists and triagonists. Using glucagon-like peptide-1, glucagon, and glucose-insulin peptide as the background for these molecules, peptides have been shown to enhance weight loss and the decline in glucose, opening a fascinating new horizon ( 413 , 414 ).

Finally, improved techniques for modulating food transit through the gastrointestinal track and its absorption also offer new strategies for dealing with the devastating epidemic posed by obesity. It is clear that food is more than calories and that dietary choices and diet quality play a role in long-term weight change ( 415 ), and this provides other opportunities for public health programs. The so-called “obesogens” in the food supply offer another opportunity for making the food supply less likely to contribute to obesity ( 416 ). Control of obesity is the most important public health strategy for the prevention of diabetes and its devastating consequences. With all of these opportunities on the horizon, we are optimistic about the future of treatment and prevention of obesity.

body mass index

blood pressure

Centers for Disease Control and Prevention

confidence interval

cardiovascular disease

early care and education

extended release

Food and Drug Administration

hemoglobin A1c

high-density lipoprotein

hazard ratio

laparoscopic adjustable gastric banding

low-density lipoprotein

metabolically healthy obesity

nonalcoholic fatty liver disease

nonalcoholic steatohepatitis

obstructive sleep apnea

phentermine/topiramate extended release

randomized controlled trial

sleeve gastrectomy

sustained release

type 2 diabetes mellitus

very low–calorie diet

waist-to-hip ratio.

We acknowledge science writer Eric A. Vohr for his contribution to this scientific statement.

Financial Support:  Work on this paper was supported in part by Bill and Melinda Gates Foundation Grant OPP1070441 to A.A., National Institutes of Health Grants DK40484 and DK45343 to M.D.J., and by National Institutes of Health Grant DK046200 to F.B.H.

Disclaimer Statement:   The Endocrine Society develops scientific statements to be of assistance to clinicians by providing guidance and recommendations for particular areas of practice. One should not consider this scientific statement inclusive of all proper approaches or methods or exclusive of others. It cannot guarantee any specific outcome, nor does it establish a standard of care. It is not intended to dictate the treatment of a particular patient. Health care providers must make treatment decisions based on their best judgment and each patient’s individual circumstances, needs, and preferences. The Endocrine Society makes no warranty, express or implied, regarding this scientific statement and specifically excludes any warranties of merchantability and fitness for a particular use or purpose. The Endocrine Society shall not be liable for direct, indirect, special, incidental, or consequential damages related to the use of the information contained herein.

Disclosure Summary:  G.B. is on the Herbalife Nutrition Advisory Council, is a consultant to Medifast, and is a consultant to Novo Nordisk. M.D.J. serves as a consultant to Novo Nordisk, Merck, and Jannsen, serves on the advisory board of Weight Watchers International, and serves on the board of directors of the Partnership for a Healthier America. R.F.K. serves on the advisory board to Novo Nordisk, Weight Watchers, Retrofit, and Zafgen. S.R.D. serves as a consultant for Sanofi and is on the Data Monitoring Committee for Novo Nordisk. T.A.W. serves on advisory boards for Novo Nordisk, Nutrisystem, and Weight Watchers, and has received grant support on behalf of the University of Pennsylvania from Eisai Pharmaceutical, Novo Nordisk, and Weight Watchers. F.B.H. receives research support from Metagenics and the California Walnut Commission. J.M.J. reports personal fees from Weight Watchers International for serving on the Scientific Advisory Board. D.H.R. serves as consultant to Novo Nordisk, Orexigen, Janssen, Merck, Astra Xenica, and KVK Tech, serves as speaker for Novo Nordisk, Orexigen, Eisai, and Kwang Dong, and has an equity position in Scientific Intake and Gila Therapeutics. The remaining authors have nothing to disclose.

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• Review Article
• Published: 07 May 2024

Epidemiology and Population Health

Obesity: a 100 year perspective

• George A. Bray   ORCID: orcid.org/0000-0001-9945-8772 1  

International Journal of Obesity ( 2024 ) Cite this article

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This review has examined the scientific basis for our current understanding of obesity that has developed over the past 100 plus years. Obesity was defined as an excess of body fat. Methods of establishing population and individual changes in levels of excess fat are discussed. Fat cells are important storage site for excess nutrients and their size and number affect the response to insulin and other hormones. Obesity as a reflection of a positive fat balance is influenced by a number of genetic and environmental factors and phenotypes of obesity can be developed from several perspectives, some of which have been elaborated here. Food intake is essential for maintenance of human health and for the storage of fat, both in normal amounts and in obesity in excess amounts. Treatment approaches have taken several forms. There have been numerous diets, behavioral approaches, along with the development of medications.. Bariatric/metabolic surgery provides the standard for successful weight loss and has been shown to have important effects on future health. Because so many people are classified with obesity, the problem has taken on important public health dimensions. In addition to the scientific background, obesity through publications and organizations has developed its own identity. While studying the problem of obesity this reviewer developed several aphorisms about the problem that are elaborated in the final section of this paper.

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Bray, G.A. Obesity: a 100 year perspective. Int J Obes (2024). https://doi.org/10.1038/s41366-024-01530-6

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Received : 13 November 2023

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Published : 07 May 2024

DOI : https://doi.org/10.1038/s41366-024-01530-6

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• Effectiveness of...

Effectiveness of weight management interventions for adults delivered in primary care: systematic review and meta-analysis of randomised controlled trials

• Related content
• Peer review
• Claire D Madigan , senior research associate 1 ,
• Henrietta E Graham , doctoral candidate 1 ,
• Elizabeth Sturgiss , NHMRC investigator 2 ,
• Victoria E Kettle , research associate 1 ,
• Kajal Gokal , senior research associate 1 ,
• Greg Biddle , research associate 1 ,
• Gemma M J Taylor , reader 3 ,
• Amanda J Daley , professor of behavioural medicine 1
• 1 Centre for Lifestyle Medicine and Behaviour (CLiMB), The School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough LE11 3TU, UK
• 2 School of Primary and Allied Health Care, Monash University, Melbourne, Australia
• 3 Department of Psychology, Addiction and Mental Health Group, University of Bath, Bath, UK
• Correspondence to: C D Madigan c.madigan{at}lboro.ac.uk (or @claire_wm and @lboroclimb on Twitter)
• Accepted 26 April 2022

Objective To examine the effectiveness of behavioural weight management interventions for adults with obesity delivered in primary care.

Design Systematic review and meta-analysis of randomised controlled trials.

Eligibility criteria for selection of studies Randomised controlled trials of behavioural weight management interventions for adults with a body mass index ≥25 delivered in primary care compared with no treatment, attention control, or minimal intervention and weight change at ≥12 months follow-up.

Data sources Trials from a previous systematic review were extracted and the search completed using the Cochrane Central Register of Controlled Trials, Medline, PubMed, and PsychINFO from 1 January 2018 to 19 August 2021.

Data extraction and synthesis Two reviewers independently identified eligible studies, extracted data, and assessed risk of bias using the Cochrane risk of bias tool. Meta-analyses were conducted with random effects models, and a pooled mean difference for both weight (kg) and waist circumference (cm) were calculated.

Main outcome measures Primary outcome was weight change from baseline to 12 months. Secondary outcome was weight change from baseline to ≥24 months. Change in waist circumference was assessed at 12 months.

Results 34 trials were included: 14 were additional, from a previous review. 27 trials (n=8000) were included in the primary outcome of weight change at 12 month follow-up. The mean difference between the intervention and comparator groups at 12 months was −2.3 kg (95% confidence interval −3.0 to −1.6 kg, I 2 =88%, P<0.001), favouring the intervention group. At ≥24 months (13 trials, n=5011) the mean difference in weight change was −1.8 kg (−2.8 to −0.8 kg, I 2 =88%, P<0.001) favouring the intervention. The mean difference in waist circumference (18 trials, n=5288) was −2.5 cm (−3.2 to −1.8 cm, I 2 =69%, P<0.001) in favour of the intervention at 12 months.

Conclusions Behavioural weight management interventions for adults with obesity delivered in primary care are effective for weight loss and could be offered to members of the public.

Systematic review registration PROSPERO CRD42021275529.

Introduction

Obesity is associated with an increased risk of diseases such as cancer, type 2 diabetes, and heart disease, leading to early mortality. 1 2 3 More recently, obesity is a risk factor for worse outcomes with covid-19. 4 5 Because of this increased risk, health agencies and governments worldwide are focused on finding effective ways to help people lose weight. 6

Primary care is an ideal setting for delivering weight management services, and international guidelines recommend that doctors should opportunistically screen and encourage patients to lose weight. 7 8 On average, most people consult a primary care doctor four times yearly, providing opportunities for weight management interventions. 9 10 A systematic review of randomised controlled trials by LeBlanc et al identified behavioural interventions that could potentially be delivered in primary care, or involved referral of patients by primary care professionals, were effective for weight loss at 12-18 months follow-up (−2.4 kg, 95% confidence interval −2.9 to−1.9 kg). 11 However, this review included trials with interventions that the review authors considered directly transferrable to primary care, but not all interventions involved primary care practitioners. The review included interventions that were entirely delivered by university research employees, meaning implementation of these interventions might differ if offered in primary care, as has been the case in other implementation research of weight management interventions, where effects were smaller. 12 As many similar trials have been published after this review, an updated review would be useful to guide health policy.

We examined the effectiveness of weight loss interventions delivered in primary care on measures of body composition (weight and waist circumference). We also identified characteristics of effective weight management programmes for policy makers to consider.

This systematic review was registered on PROSPERO and is reported according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement. 13 14

Eligibility criteria

We considered studies to be eligible for inclusion if they were randomised controlled trials, comprised adult participants (≥18 years), and evaluated behavioural weight management interventions delivered in primary care that focused on weight loss. A primary care setting was broadly defined as the first point of contact with the healthcare system, providing accessible, continued, comprehensive, and coordinated care, focused on long term health. 15 Delivery in primary care was defined as the majority of the intervention being delivered by medical and non-medical clinicians within the primary care setting. Table 1 lists the inclusion and exclusion criteria.

Study inclusion and exclusion criteria

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We extracted studies from the systematic review by LeBlanc et al that met our inclusion criteria. 11 We also searched the exclusions in this review because the researchers excluded interventions specifically for diabetes management, low quality trials, and only included studies from an Organisation for Economic Co-operation and Development country, limiting the scope of the findings.

We searched for studies in the Cochrane Central Register of Controlled Trials, Medline, PubMed, and PsychINFO from 1 January 2018 to 19 August 2021 (see supplementary file 1). Reference lists of previous reviews 16 17 18 19 20 21 and included trials were hand searched.

Data extraction

Results were uploaded to Covidence, 22 a software platform used for screening, and duplicates removed. Two independent reviewers screened study titles, abstracts, and full texts. Disagreements were discussed and resolved by a third reviewer. All decisions were recorded in Covidence, and reviewers were blinded to each other’s decisions. Covidence calculates proportionate agreement as a measure of inter-rater reliability, and data are reported separately by title or abstract screening and full text screening. One reviewer extracted data on study characteristics (see supplementary table 1) and two authors independently extracted data on weight outcomes. We contacted the authors of four included trials (from the updated search) for further information. 23 24 25 26

Outcomes, summary measures, and synthesis of results

The primary outcome was weight change from baseline to 12 months. Secondary outcomes were weight change from baseline to ≥24 months and from baseline to last follow-up (to include as many trials as possible), and waist circumference from baseline to 12 months. Supplementary file 2 details the prespecified subgroup analysis that we were unable to complete. The prespecified subgroup analyses that could be completed were type of healthcare professional who delivered the intervention, country, intensity of the intervention, and risk of bias rating.

Healthcare professional delivering intervention —From the data we were able to compare subgroups by type of healthcare professional: nurses, 24 26 27 28 general practitioners, 23 29 30 31 and non-medical practitioners (eg, health coaches). 32 33 34 35 36 37 38 39 Some of the interventions delivered by non-medical practitioners were supported, but not predominantly delivered, by GPs. Other interventions were delivered by a combination of several different practitioners—for example, it was not possible to determine whether a nurse or dietitian delivered the intervention. In the subgroup analysis of practitioner delivery, we refer to this group as “other.”

Country —We explored the effectiveness of interventions by country. Only countries with three or more trials were included in subgroup analyses (United Kingdom, United States, and Spain).

Intensity of interventions —As the median number of contacts was 12, we categorised intervention groups according to whether ≤11 or ≥12 contacts were required.

Risk of bias rating —Studies were classified as being at low, unclear, and high risk of bias. Risk of bias was explored as a potential influence on the results.

Meta-analyses

Meta-analyses were conducted using Review Manager 5.4. 40 As we expected the treatment effects to differ because of the diversity of intervention components and comparator conditions, we used random effects models. A pooled mean difference was calculated for each analysis, and variance in heterogeneity between studies was compared using the I 2 and τ 2 statistics. We generated funnel plots to evaluate small study effects. If more than two intervention groups existed, we divided the number of participants in the comparator group by the number of intervention groups and analysed each individually. Nine trials were cluster randomised controlled trials. The trials had adjusted their results for clustering, or adjustment had been made in the previous systematic review by LeBlanc et al. 11 One trial did not report change in weight by group. 26 We calculated the mean weight change and standard deviation using a standard formula, which imputes a correlation for the baseline and follow-up weights. 41 42 In a non-prespecified analysis, we conducted univariate and multivariable metaregression (in Stata) using a random effects model to examine the association between number of sessions and type of interventionalist on study effect estimates.

Risk of bias

Two authors independently assessed the risk of bias using the Cochrane risk of bias tool v2. 43 For incomplete outcome data we defined a high risk of bias as ≥20% attrition. Disagreements were resolved by discussion or consultation with a third author.

Patient and public involvement

The study idea was discussed with patients and members of the public. They were not, however, included in discussions about the design or conduct of the study.

The search identified 11 609 unique study titles or abstracts after duplicates were removed ( fig 1 ). After screening, 97 full text articles were assessed for eligibility. The proportionate agreement ranged from 0.94 to 1.0 for screening of titles or abstracts and was 0.84 for full text screening. Fourteen new trials met the inclusion criteria. Twenty one studies from the review by LeBlanc et al met our eligibility criteria and one study from another systematic review was considered eligible and included. 44 Some studies had follow-up studies (ie, two publications) that were found in both the second and the first search; hence the total number of trials was 34 and not 36. Of the 34 trials, 27 (n=8000 participants) were included in the primary outcome meta-analysis of weight change from baseline to 12 months, 13 (n=5011) in the secondary outcome from baseline to ≥24 months, and 30 (n=8938) in the secondary outcome for weight change from baseline to last follow-up. Baseline weight was accounted for in 18 of these trials, but in 14 24 26 29 30 31 32 44 45 46 47 48 49 50 51 it was unclear or the trials did not consider baseline weight. Eighteen trials (n=5288) were included in the analysis of change in waist circumference at 12 months.

Studies included in systematic review of effectiveness of behavioural weight management interventions in primary care. *Studies were merged in Covidence if they were from same trial

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Study characteristics

Included trials (see supplementary table 1) were individual randomised controlled trials (n=25) 24 25 26 27 28 29 32 33 34 35 38 39 41 44 45 46 47 50 51 52 53 54 55 56 59 or cluster randomised controlled trials (n=9). 23 30 31 36 37 48 49 57 58 Most were conducted in the US (n=14), 29 30 31 32 33 34 35 36 37 45 48 51 54 55 UK (n=7), 27 28 38 41 47 57 58 and Spain (n=4). 25 44 46 49 The median number of participants was 276 (range 50-864).

Four trials included only women (average 65.9% of women). 31 48 51 59 The mean BMI at baseline was 35.2 (SD 4.2) and mean age was 48 (SD 9.7) years. The interventions lasted between one session (with participants subsequently following the programme unassisted for three months) and several sessions over three years (median 12 months). The follow-up period ranged from 12 months to three years (median 12 months). Most trials excluded participants who had lost weight in the past six months and were taking drugs that affected weight.

Meta-analysis

Overall, 27 trials were included in the primary meta-analysis of weight change from baseline to 12 months. Three trials could not be included in the primary analysis as data on weight were only available at two and three years and not 12 months follow-up, but we included these trials in the secondary analyses of last follow-up and ≥24 months follow-up. 26 44 50 Four trials could not be included in the meta-analysis as they did not present data in a way that could be synthesised (ie, measures of dispersion). 25 52 53 58 The mean difference was −2.3 kg (95% confidence interval −3.0 to −1.6 kg, I 2 =88%, τ 2 =3.38; P<0.001) in favour of the intervention group ( fig 2 ). We found no evidence of publication bias (see supplementary fig 1). Absolute weight change was −3.7 (SD 6.1) kg in the intervention group and −1.4 (SD 5.5) kg in the comparator group.

Mean difference in weight at 12 months by weight management programme in primary care (intervention) or no treatment, different content, or minimal intervention (control). SD=standard deviation

Supplementary file 2 provides a summary of the main subgroup analyses.

Weight change

The mean difference in weight change at the last follow-up was −1.9 kg (95% confidence interval −2.5 to −1.3 kg, I 2 =81%, τ 2 =2.15; P<0.001). Absolute weight change was −3.2 (SD 6.4) kg in the intervention group and −1.2 (SD 6.0) kg in the comparator group (see supplementary figs 2 and 3).

At the 24 month follow-up the mean difference in weight change was −1.8 kg (−2.8 to −0.8 kg, I 2 =88%, τ 2 =3.13; P<0.001) (see supplementary fig 4). As the weight change data did not differ between the last follow-up and ≥24 months, we used the weight data from the last follow-up in subgroup analyses.

In subgroup analyses of type of interventionalist, differences were significant (P=0.005) between non-medical practitioners, GPs, nurses, and other people who delivered interventions (see supplementary fig 2).

Participants who had ≥12 contacts during interventions lost significantly more weight than those with fewer contacts (see supplementary fig 6). The association remained after adjustment for type of interventionalist.

Waist circumference

The mean difference in waist circumference was −2.5 cm (95% confidence interval −3.2 to −1.8 cm, I 2 =69%, τ 2 =1.73; P<0.001) in favour of the intervention at 12 months ( fig 3 ). Absolute changes were −3.7 cm (SD 7.8 cm) in the intervention group and −1.3 cm (SD 7.3) in the comparator group.

Mean difference in waist circumference at 12 months. SD=standard deviation

Risk of bias was considered to be low in nine trials, 24 33 34 35 39 41 47 55 56 unclear in 12 trials, 25 27 28 29 32 45 46 50 51 52 54 59 and high in 13 trials 23 26 30 31 36 37 38 44 48 49 53 57 58 ( fig 4 ). No significant (P=0.65) differences were found in subgroup analyses according to level of risk of bias from baseline to 12 months (see supplementary fig 7).

Risk of bias in included studies

Worldwide, governments are trying to find the most effective services to help people lose weight to improve the health of populations. We found weight management interventions delivered by primary care practitioners result in effective weight loss and reduction in waist circumference and these interventions should be considered part of the services offered to help people manage their weight. A greater number of contacts between patients and healthcare professionals led to more weight loss, and interventions should be designed to include at least 12 contacts (face-to-face or by telephone, or both). Evidence suggests that interventions delivered by non-medical practitioners were as effective as those delivered by GPs (both showed statistically significant weight loss). It is also possible that more contacts were made with non-medical interventionalists, which might partially explain this result, although the metaregression analysis suggested the effect remained after adjustment for type of interventionalist. Because most comparator groups had fewer contacts than intervention groups, it is not known whether the effects of the interventions are related to contact with interventionalists or to the content of the intervention itself.

Although we did not determine the costs of the programme, it is likely that interventions delivered by non-medical practitioners would be cheaper than GP and nurse led programmes. 41 Most of the interventions delivered by non-medical practitioners involved endorsement and supervision from GPs (ie, a recommendation or checking in to see how patients were progressing), and these should be considered when implementing these types of weight management interventions in primary care settings. Our findings suggest that a combination of practitioners would be most effective because GPs might not have the time for 12 consultations to support weight management.

Although the 2.3 kg greater weight loss in the intervention group may seem modest, just 2-5% in weight loss is associated with improvements in systolic blood pressure and glucose and triglyceride levels. 60 The confidence intervals suggest a potential range of weight loss and that these interventions might not provide as much benefit to those with a higher BMI. Patients might not find an average weight loss of 3.7 kg attractive, as many would prefer to lose more weight; explaining to patients the benefits of small weight losses to health would be important.

Strengths and limitations of this review

Our conclusions are based on a large sample of about 8000 participants, and 12 of these trials were published since 2018. It was occasionally difficult to distinguish who delivered the interventions and how they were implemented. We therefore made some assumptions at the screening stage about whether the interventionalists were primary care practitioners or if most of the interventions were delivered in primary care. These discussions were resolved by consensus. All included trials measured weight, and we excluded those that used self-reported data. Dropout rates are important in weight management interventions as those who do less well are less likely to be followed-up. We found that participants in trials with an attrition rate of 20% or more lost less weight and we are confident that those with high attrition rates have not inflated the results. Trials were mainly conducted in socially economic developed countries, so our findings might not be applicable to all countries. The meta-analyses showed statistically significant heterogeneity, and our prespecified subgroups analysis explained some, but not all, of the variance.

Comparison with other studies

The mean difference of −2.3 kg in favour of the intervention group at 12 months is similar to the findings in the review by LeBlanc et al, who reported a reduction of −2.4 kg in participants who received a weight management intervention in a range of settings, including primary care, universities, and the community. 11 61 This is important because the review by LeBlanc et al included interventions that were not exclusively conducted in primary care or by primary care practitioners. Trials conducted in university or hospital settings are not typically representative of primary care populations and are often more intensive than trials conducted in primary care as a result of less constraints on time. Thus, our review provides encouraging findings for the implementation of weight management interventions delivered in primary care. The findings are of a similar magnitude to those found in a trial by Ahern et al that tested primary care referral to a commercial programme, with a difference of −2.7 kg (95% confidence interval −3.9 to −1.5 kg) reported at 12 month follow-up. 62 The trial by Ahern et al also found a difference in waist circumference of −4.1 cm (95% confidence interval −5.5 to −2.3 cm) in favour of the intervention group at 12 months. Our finding was smaller at −2.5 cm (95% confidence interval −3.2 to −1.8 cm). Some evidence suggests clinical benefits from a reduction of 3 cm in waist circumference, particularly in decreased glucose levels, and the intervention groups showed a 3.7 cm absolute change in waist circumference. 63

Policy implications and conclusions

Weight management interventions delivered in primary care are effective and should be part of services offered to members of the public to help them manage weight. As about 39% of the world’s population is living with obesity, helping people to manage their weight is an enormous task. 64 Primary care offers good reach into the community as the first point of contact in the healthcare system and the remit to provide whole person care across the life course. 65 When developing weight management interventions, it is important to reflect on resource availability within primary care settings to ensure patients’ needs can be met within existing healthcare systems. 66

We did not examine the equity of interventions, but primary care interventions may offer an additional service and potentially help those who would not attend a programme delivered outside of primary care. Interventions should consist of 12 or more contacts, and these findings are based on a mixture of telephone and face-to-face sessions. Previous evidence suggests that GPs find it difficult to raise the issue of weight with patients and are pessimistic about the success of weight loss interventions. 67 Therefore, interventions should be implemented with appropriate training for primary care practitioners so that they feel confident about helping patients to manage their weight. 68

Unanswered questions and future research

A range of effective interventions are available in primary care settings to help people manage their weight, but we found substantial heterogeneity. It was beyond the scope of this systematic review to examine the specific components of the interventions that may be associated with greater weight loss, but this could be investigated by future research. We do not know whether these interventions are universally suitable and will decrease or increase health inequalities. As the data are most likely collected in trials, an individual patient meta-analysis is now needed to explore characteristics or factors that might explain the variance. Most of the interventions excluded people prescribed drugs that affect weight gain, such as antipsychotics, glucocorticoids, and some antidepressants. This population might benefit from help with managing their weight owing to the side effects of these drug classes on weight gain, although we do not know whether the weight management interventions we investigated would be effective in this population. 69

What is already known on this topic

Referral by primary care to behavioural weight management programmes is effective, but the effectiveness of weight management interventions delivered by primary care is not known

Systematic reviews have provided evidence for weight management interventions, but the latest review of primary care delivered interventions was published in 2014

Factors such as intensity and delivery mechanisms have not been investigated and could influence the effectiveness of weight management interventions delivered by primary care

What this study adds

Weight management interventions delivered by primary care are effective and can help patients to better manage their weight

At least 12 contacts (telephone or face to face) are needed to deliver weight management programmes in primary care

Some evidence suggests that weight loss after weight management interventions delivered by non-medical practitioners in primary care (often endorsed and supervised by doctors) is similar to that delivered by clinician led programmes

Ethics statements

Ethical approval.

Not required.

Data availability statement

Additional data are available in the supplementary files.

Contributors: CDM and AJD conceived the study, with support from ES. CDM conducted the search with support from HEG. CDM, AJD, ES, HEG, KG, GB, and VEK completed the screening and full text identification. CDM and VEK completed the risk of bias assessment. CDM extracted data for the primary outcome and study characteristics. HEJ, GB, and KG extracted primary outcome data. CDM completed the analysis in RevMan, and GMJT completed the metaregression analysis in Stata. CDM drafted the paper with AJD. All authors provided comments on the paper. CDM acts as guarantor. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.

Funding: AJD is supported by a National Institute for Health and Care Research (NIHR) research professorship award. This research was supported by the NIHR Leicester Biomedical Research Centre. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, or the Department of Health and Social Care. ES’s salary is supported by an investigator grant (National Health and Medical Research Council, Australia). GT is supported by a Cancer Research UK fellowship. The funders had no role in considering the study design or in the collection, analysis, interpretation of data, writing of the report, or decision to submit the article for publication.

Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/disclosure-of-interest/ and declare: This research was supported by the National Institute for Health and Care Research Leicester Biomedical Research Centre; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years, no other relationships or activities that could appear to have influenced the submitted work.

The lead author (CDM) affirms that the manuscript is an honest, accurate, and transparent account of the study being reported, and that no important aspects of the study have been omitted.

Dissemination to participants and related patient and public communities: We plan to disseminate these research findings to a wider community through press releases, featuring on the Centre for Lifestyle Medicine and Behaviour website ( www.lboro.ac.uk/research/climb/ ) via our policy networks, through social media platforms, and presentation at conferences.

Provenance and peer review: Not commissioned; externally peer reviewed.

This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/ .

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Overweight and Obesity Prevalence and Management Essay

A brief review of the clinical health issue.

Obesity is a major public health problem that is recognized as one of the leading causes of mortality worldwide. Obesity and overweight are two of the most common disorders that cause additional medical conditions and lead to a variety of chronic diseases, such as diabetes, cancer, metabolic disorder, and coronary heart disease (Safaei et al., 2021). In 2030, the WHO predicts that 30 percent of deaths will be caused by lifestyle illnesses, which can be avoided by identifying and treating related risk factors and implementing behavioral engagement programs (Safaei et al., 2021). In order to decrease the malignant nature of overweight and obesity and the growing tendency of such diseases, more research and regulations are required.

Critical Forecasting and Boundary Spanning Factors

Adult individuals’ overweight and severe obesity rates grew from 1999 to 2000 to 2017-2018. The danger of the disease is not only in the rapid growth but the complications. Obesity-related issues, including cardiovascular disease and terminal kidney disease, will be found among those who are severely obese (CDC, 2022). As of now, there is no simple answer to how obesity can be managed and what initiatives must be taken. It is a complicated matter that necessitates a comprehensive solution.

What This Issue Looks Like Going Forward

In order to build a culture that nurtures healthy behaviors, policymakers, federal and municipal institutions, corporate, educational, and community activists, childcare, and healthcare experts must collaborate. As a result, it can be seen that obesity has a growing tendency, and this poses a threat to the nation and requires more attention both from scientists and the government, without which the danger of the disease will only increase.

Stakeholders

Among the stakeholders in the given plan are the patients and healthcare providers. With both patient and clinician efforts, it will be possible to see which measures provide the most beneficial results. The results of the trial will be the recommendations to the policymakers on approaches to reducing the growing tendency of obesity and overweight. Thus, the parties will be incentivized on both individual and broader scopes. For example, patients who participate in the trial must have the aforementioned medical conditions. For medical providers, the incentive will be the determination of the most efficient approaches to treating obesity and overweight.

Who are they?

Stakeholders typically include attending physicians, other hospital staff, and the patients; sometimes, pharmaceutical companies are included (these are, however, common cases of medical research). The country is the most important stakeholder, which ensures significant insurance premiums.

What do I need from them?

Direct stakeholders (physicians, staff, and patients) must carefully follow the rules during the trial. Without discipline, it will be impossible to get adequate results. Physicians must follow all predetermined standards and algorithms.

How will I convince them to help?

The organization of the trial will be entirely the responsibility of the scientists and will not affect either the physicians assisting in the research or the patients. All work during the test will be under strict control and fixation, both in electronic form and on paper. Patients will be able to see the result if they wish and receive it in their hands.

Strategic measures

Among the strategic measures of the trial will be the number of participants, their obesity-related health issues, Body Mass Index (BMI), and participation in clinical and non-clinical programs.

The Body Mass Index will be considered one of the fundamental measurements since it shows both the existing obesity and the risk and exposure. During the test, the mass index of the case will be measured two to three times.

Obesity-related health issues are an essential subject to study and a severe measurement that clinicians should approach responsibly. It includes hereditary cases of obesity, eating habits, and mental diseases associated with eating behavior. Possibly, later consideration should be given to adding the social aspects of obesity to these questions.

Managerial Issues

Management issues will first relate to personnel management during the test. The calculation of the results must be kept in electronic form and subsequently printed on paper. All results data must be encrypted and protected by reliable software. Patients must be confident in their and the results’ privacy. Additional costs should be provided for in case of emergencies. All hospital staff and physicians must voluntarily participate in the trial and be prepared for extra work.

Staff Concerns for the Proposal

As for the staff, the medical professional team will participate in the trial to gather the data and provide patient care. Among the issues that might arise might be the understaffed shifts to collect the data.

The costs (budget) will include the expenses for the usage of electronic records to monitor the changes in patients’ conditions.

The structure to fulfill the proposal

The trial structure will consist of the comparison of patients with obesity and obesity-related medical conditions. The comparison will focus on the improvements and efficiency levels in patients who use non-clinical and clinical programs.

Ethical Issues

The ethical issues involve the usage of the personal information of patients, which leads to the matter of confidentiality. In this case, patients who will participate in the trial will have to sign a form of agreement. Moreover, there is an ethical issue regarding the balance between the quality of patient care and efficiency. The focus will be on efficiency rather than quality, in the given situation.

CDC. (2022). Causes of obesity . Centers for Disease Control and Prevention. Web.

Safaei, M., Sundararajan, E. A., Driss, M., Boulila, W., & Shapi’i, A. (2021). A systematic literature review on obesity: Understanding the causes & consequences of obesity and reviewing various machine learning approaches used to predict obesity. Computers in Biology and Medicine , 136 , 1-17.

• Chicago (A-D)
• Chicago (N-B)

IvyPanda. (2023, September 28). Overweight and Obesity Prevalence and Management. https://ivypanda.com/essays/overweight-and-obesity-prevalence-and-management/

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IvyPanda . 2023. "Overweight and Obesity Prevalence and Management." September 28, 2023. https://ivypanda.com/essays/overweight-and-obesity-prevalence-and-management/.

1. IvyPanda . "Overweight and Obesity Prevalence and Management." September 28, 2023. https://ivypanda.com/essays/overweight-and-obesity-prevalence-and-management/.

Bibliography

IvyPanda . "Overweight and Obesity Prevalence and Management." September 28, 2023. https://ivypanda.com/essays/overweight-and-obesity-prevalence-and-management/.

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Obesity in children is rising dramatically, and it comes with major – and sometimes lifelong – health consequences

2023 California Health Equity Fellow, University of Southern California

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In the past two decades, children have become more obese and have developed obesity at a younger age. A 2020 report found that 14.7 million children and adolescents in the U.S. live with obesity.

Because obesity is a known risk factor for serious health problems , its rapid increase during the COVID-19 pandemic raised alarms.

Without intervention, many obese adolescents will remain obese as adults. Even before adulthood, some children will have serious health problems beginning in their preteen years.

To address these issues, in early 2023, the American Academy of Pediatrics released its first new obesity management guidelines in 15 years.

I am a pediatric gastroenterologist who sees children in the largest public hospital in California, and I have witnessed a clear trend over the last two decades. Early in my practice, I only occasionally saw a child with a complication of obesity; now I see multiple referrals each month. Some of these children have severe obesity and several health complications that require multiple specialists.

These observations prompted my reporting for the California Health Equity Fellowship at the University of Southern California.

It’s important to note that not all children who carry extra weight are unhealthy. But evidence supports that obesity, especially severe obesity, requires further assessment.

How obesity is measured

The World Health Organization defines obesity as “abnormal or excessive fat accumulation that presents a risk to health.”

Measuring fat composition requires specialized equipment that is not available in a regular doctor’s office. Therefore most clinicians use body measurements to screen for obesity.

One method is body mass index, or BMI, a calculation based on a child’s height and weight compared to age- and sex-matched peers. BMI doesn’t measure body fat, but when BMI is high , it correlates with total body fat.

According to the American Academy of Pediatrics , a child qualifies as overweight at a BMI between the 85th and 95th percentile . Obese is defined as a BMI above the 95th percentile . Other screens for obesity include waist circumference and skin-fold thickness , but these methods are less common.

Because many children exceeded the limits of existing growth charts, in 2022 the Centers for Disease Control and Prevention introduced extended growth charts for severe obesity. Severe obesity occurs when a child reaches the 120th percentile or has a BMI over 35. For instance, a 6-year-old boy who is 48 inches tall and is 110 pounds would meet criteria for severe obesity because his BMI is 139th percentile.

Severe obesity carries a heightened risk of liver disease, cardiovascular disease and metabolic problems such as diabetes. As of 2016, almost 8% of children ages 2 to 19 had severe obesity .

Other health problems associated with severe obesity include obstructive sleep apnea , bone and joint problems that can cause early arthritis, high blood pressure and kidney disease . Many of these problems occur together.

How obesity affects the liver

The liver disease associated with obesity is called nonalcoholic fatty liver disease . To store excess dietary fat and sugar, the liver’s cells fill with fat. Excess carbohydrates in particular get processed into substances similar to the breakdown products of alcohols . Under the microscope, a pediatric fatty liver looks similar to a liver with alcohol damage.

Occasionally children with fatty liver are not obese; however, the greatest risk factor for fatty liver is obesity. At the same BMI, Hispanic and Asian children are more susceptible to fatty liver disease than Black and white children. Weight reduction or reducing the consumption of fructose, a naturally occurring sugar and common food additive – even without significant weight loss – improves fatty liver.

Fatty liver is the most common chronic liver disease in children and adults. In Southern California, pediatric fatty liver doubled from 2009 to 2018. The disease can progress rapidly in children, and some will have liver scarring after only a few years.

Although few children currently require liver transplants for fatty liver, it is the most rapidly increasing reason for transplantation in young adults . Fatty liver is the second-most common reason for liver transplantation in the U.S., and it will be the leading cause in the future .

Links between obesity and diabetes

Fatty liver is implicated in metabolic syndrome , a group of conditions that cluster together and increase the risk of cardiovascular disease and diabetes.

In a telephone interview, Dr. Barry Reiner, a pediatric endocrinologist, voiced his concerns to me about obesity and diabetes.

“When I started my practice, I had never heard of type 2 diabetes in children,” says Reiner. “Now, depending on which part of the U.S., between a quarter and a third of new cases of diabetes are type 2.”

Type 1 diabetes is an autoimmune disease previously called juvenile-onset diabetes. Conversely, type 2 diabetes was historically considered an adult disease.

However, type 2 diabetes is increasing in children, and obesity is the major risk factor . While both types of diabetes have genetic and lifestyle influences, type 2 is more modifiable through diet and exercise.

By 2060, the number of people under 20 with type 2 diabetes will increase by 700% . Black, Latino, Asian, Pacific Islander and Native American/Alaska Native children will have more type 2 diabetes diagnoses than white children.

“The seriousness of type 2 diabetes in children is underestimated,” says Reiner. He added that many people express a misconception that type 2 diabetes is a mild, slow-moving disease.

Reiner pointed to an important study showing that type 2 diabetes acquired in childhood can rapidly progress . As early as 10 to 12 years after their childhood diagnosis, patients developed nerve damage, kidney problems and vision damage. By 15 years after diagnosis, at an average age of 27, almost 70% of the patients had high blood pressure .

Most patients had more than one complication. Although rare, a few patients experienced heart attacks and strokes. When people with childhood onset diabetes became pregnant, 24% delivered premature infants, over double the rate in the general population .

Heart health

Cardiovascular changes associated with obesity and severe obesity can also increase a child’s lifetime chance of heart attacks and strokes. Carrying extra weight at 6 to 7 years old can result in higher blood pressure, cholesterol and artery stiffness by 11 to 12 years of age . Obesity changes the structure of the heart , making the muscle thicken and expand.

Although still uncommon, more people in their 20s, 30s and 40s are having strokes and heart attacks than a few decades ago. Although many factors may contribute to heart attack and stroke, obesity adds to that risk.

Talk about being healthy, not focusing on weight

Venus Kalami, a registered dietitian, spoke with me about the environmental and societal influences on childhood obesity.

“Food, diet, lifestyle and weight are often a proxy for something greater going on in someone’s life,” says Kalami.

Factors beyond a child’s control, including depression , access to healthy food and walkable neighborhoods , contribute to obesity.

Parents may wonder how to help children without introducing shame or blame. First, conversations about weight and food should be age appropriate.

“A 6-year-old does not need to be thinking about their weight,” says Kalami. She adds that even preteens and teenagers should not be focusing on their weight, though they likely already are.

Even “good-natured” teasing is harmful. Avoid diet talk, and instead discuss health. Kalami recommends that adults explain how healthy habits can improve mood, focus or kids’ performance in a favorite activity.

“A 12-year-old isn’t always going to know what is healthy,” Kalami said. “Help them pick what’s available and make the best choice, which may not be the perfect choice.”

Any weight talk, either criticism or compliments for weight loss, may backfire, she adds. Praising a child for their weight loss can reinforce a negative cycle of disordered eating. Instead, cheer the child’s better health and good choices.

Dr. Muneeza Mirza, a pediatrician, recommends that parents model healthful behavior.

“Changes should be made for the whole family,” says Mirza. “It shouldn’t be considered a punishment for that kid.”

• Cardiovascular disease
• Kidney disease
• Cardiovascular health
• Obesity epidemic
• High blood pressure
• World Health Organization (WHO)
• American Academy of Pediatrics
• Centers for Disease Control and Prevention (CDC)
• Body mass index
• Weight stigma

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Guest Essay

A Year on Ozempic Taught Me We’re Thinking About Obesity All Wrong

By Johann Hari

Mr. Hari is a British journalist and the author of “Magic Pill: The Extraordinary Benefits — and Disturbing Risks — of the New Weight Loss Drugs.”

Ever since I was a teenager, I have dreamed of shedding a lot of weight. So when I shrank from 203 pounds to 161 in a year, I was baffled by my feelings. I was taking Ozempic, and I was haunted by the sense that I was cheating and doing something immoral.

I’m not the only one. In the United States (where I now split my time), over 70 percent of people are overweight or obese, and according to one poll, 47 percent of respondents said they were willing to pay to take the new weight-loss drugs. It’s not hard to see why. They cause users to lose an average of 10 to 20 percent of their body weight, and clinical trials suggest that the next generation of drugs (probably available soon) leads to a 24 percent loss, on average. Yet as more and more people take drugs like Ozempic, Wegovy and Mounjaro, we get more confused as a culture, bombarding anyone in the public eye who takes them with brutal shaming.

This is happening because we are trapped in a set of old stories about what obesity is and the morally acceptable ways to overcome it. But the fact that so many of us are turning to the new weight-loss drugs can be an opportunity to find a way out of that trap of shame and stigma — and to a more truthful story.

In my lifetime, obesity has exploded, from being rare to almost being the norm. I was born in 1979, and by the time I was 21, obesity rates in the United States had more than doubled . They have skyrocketed since. The obvious question is, why? And how do these new weight-loss drugs work? The answer to both lies in one word: satiety. It’s a concept that we don’t use much in everyday life but that we’ve all experienced at some point. It describes the sensation of having had enough and not wanting any more.

The primary reason we have gained weight at a pace unprecedented in human history is that our diets have radically changed in ways that have deeply undermined our ability to feel sated. My father grew up in a village in the Swiss mountains, where he ate fresh, whole foods that had been cooked from scratch and prepared on the day they were eaten. But in the 30 years between his childhood and mine, in the suburbs of London, the nature of food transformed across the Western world. He was horrified to see that almost everything I ate was reheated and heavily processed. The evidence is clear that the kind of food my father grew up eating quickly makes you feel full. But the kind of food I grew up eating, much of which is made in factories, often with artificial chemicals, left me feeling empty and as if I had a hole in my stomach. In a recent study of what American children eat, ultraprocessed food was found to make up 67 percent of their daily diet. This kind of food makes you want to eat more and more. Satiety comes late, if at all.

One scientific experiment — which I have nicknamed Cheesecake Park — seemed to me to crystallize this effect. Paul Kenny, a neuroscientist at Mount Sinai Hospital in New York, grew up in Ireland. After he moved in 2000 to the United States, when he was in his 20s, he gained 30 pounds in two years. He began to wonder if the American diet has some kind of strange effect on our brains and our cravings, so he designed an experiment to test it. He and his colleague Paul Johnson raised a group of rats in a cage and gave them an abundant supply of healthy, balanced rat chow made out of the kind of food rats had been eating for a very long time. The rats would eat it when they were hungry, and then they seemed to feel sated and stopped. They did not become fat.

But then Dr. Kenny and his colleague exposed the rats to an American diet: fried bacon, Snickers bars, cheesecake and other treats. They went crazy for it. The rats would hurl themselves into the cheesecake, gorge themselves and emerge with their faces and whiskers totally slicked with it. They quickly lost almost all interest in the healthy food, and the restraint they used to show around healthy food disappeared. Within six weeks, their obesity rates soared.

After this change, Dr. Kenny and his colleague tweaked the experiment again (in a way that seems cruel to me, a former KFC addict). They took all the processed food away and gave the rats their old healthy diet. Dr. Kenny was confident that they would eat more of it, proving that processed food had expanded their appetites. But something stranger happened. It was as though the rats no longer recognized healthy food as food at all, and they barely ate it. Only when they were starving did they reluctantly start to consume it again.

Though Dr. Kenny’s study was in rats, we can see forms of this behavior everywhere. We are all living in Cheesecake Park — and the satiety-stealing effect of industrially assembled food is evidently what has created the need for these medications. Drugs like Ozempic work precisely by making us feel full. Carel le Roux, a scientist whose research was important to the development of these drugs, says they boost what he and others once called “satiety hormones.”

Once you understand this context, it becomes clear that processed and ultraprocessed food create a raging hole of hunger, and these treatments can repair that hole. Michael Lowe, a professor of psychology at Drexel University who has studied hunger for 40 years, told me the drugs are “an artificial solution to an artificial problem.”

Yet we have reacted to this crisis largely caused by the food industry as if it were caused only by individual moral dereliction. I felt like a failure for being fat and was furious with myself for it. Why do we turn our anger inward and not outward at the main cause of the crisis? And by extension, why do we seek to shame people taking Ozempic but not those who, say, take drugs to lower their blood pressure?

The answer, I think, lies in two very old notions. The first is the belief that obesity is a sin. When Pope Gregory I laid out the seven deadly sins in the sixth century, one of them was gluttony, usually illustrated with grotesque-seeming images of overweight people. Sin requires punishment before you can get to redemption. Think about the competition show “The Biggest Loser,” on which obese people starve and perform extreme forms of exercise in visible agony in order to demonstrate their repentance.

The second idea is that we are all in a competition when it comes to weight. Ours is a society full of people fighting against the forces in our food that are making us fatter. It is often painful to do this: You have to tolerate hunger or engage in extreme forms of exercise. It feels like a contest in which each thin person creates additional pressure on others to do the same. Looked at in this way, people on Ozempic can resemble athletes like the cyclist Lance Armstrong who used performance-enhancing drugs. Those who manage their weight without drugs might think, “I worked hard for this, and you get it for as little as a weekly jab?”

We can’t find our way to a sane, nontoxic conversation about obesity or Ozempic until we bring these rarely spoken thoughts into the open and reckon with them. You’re not a sinner for gaining weight. You’re a typical product of a dysfunctional environment that makes it very hard to feel full. If you are angry about these drugs, remember the competition isn’t between you and your neighbor who’s on weight-loss drugs. It’s between you and a food industry constantly designing new ways to undermine your satiety. If anyone is the cheat here, it’s that industry. We should be united in a struggle against it and its products, not against desperate people trying to find a way out of this trap.

There are extraordinary benefits as well as disturbing risks associated with weight-loss drugs. Reducing or reversing obesity hugely boosts health, on average: We know from years of studying bariatric surgery that it slashes the risks of cancer, heart disease and diabetes-related death. Early indications are that the new anti-obesity drugs are moving people in a similar radically healthier direction, massively reducing the risk of heart attack or stroke. But these drugs may increase the risk for thyroid cancer. I am worried they diminish muscle mass and fear they may supercharge eating disorders. This is a complex picture in which the evidence has to be weighed very carefully.

But we can’t do that if we remain lost in stories inherited from premodern popes or in a senseless competition that leaves us all, in the end, losers. Do we want these weight loss drugs to be another opportunity to tear one another down? Or do we want to realize that the food industry has profoundly altered the appetites of us all — leaving us trapped in the same cage, scrambling to find a way out?

Johann Hari is a British journalist and the author of “Magic Pill: The Extraordinary Benefits — and Disturbing Risks — of the New Weight Loss Drugs,” among other books.

Source photographs by seamartini, The Washington Post, and Zana Munteanu via Getty Images.

The Times is committed to publishing a diversity of letters to the editor. We’d like to hear what you think about this or any of our articles. Here are some tips . And here’s our email: [email protected] .

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Overweight and Obesity

31.6% of idaho adults have obesity (2021 )  , 67 .4% of idaho adults are overweight  or have obesity (2021 )  .

of Idaho youth age 10- 17 have obesity

(2020-2021)

OBESITY AND  PUBLIC HEALTH  

Idaho, like most states, is seeing a steady increase in the percentage of its population that is overweight or obese. According to the Idaho Behavioral Risk Factor Surveillance System ( BRFSS ), the percentage of Idaho adults aged 18 and older who report having obesity has increased from 20.5 percent in 2001 to 31.6 percent in 2021.

Idaho youth are also experiencing increased obesity rates. In 2021, 28.1 percent of Idaho high school students described themselves as slightly or very overweight, and 11.9 percent were obese (Youth Risk Behavior Survey).( 1)  When looking at population groups in Idaho, those who are Hispanic, Latino, American Indian and Alaskan Native experience the highest rates of obesi ty. Rates also vary by location and county. In 2020, Shoshone county had an estimated obesity rate of 40 percent while the rate was 27 percent for people living in Valley  and Blaine counties.( 2)

Upstream socioeconomic and environmental determinants of health, such as poverty, housing, education, food access and healthcare access, can systematically influence individual behaviors that have an impact on weight and associated health outcomes. Obesity and overweight are important to address due to increased risk of co-morbid chronic conditions, such as heart disease, hypertension, high blood cholesterol, diabetes, and some cancers. Most importantly, these health issues are largely manageable and preventable when people are supported by community environments, systems and policies that promote health and well-being.

The State of Childhood Obesity Report, released in November 2 022, critiques an over-reliance on Body Mass Index (BMI), “when we use BMI to put large-bodied pe ople, including children, into categories of “obese” or “overweight,” we inadvertently activate weight-based stigma. This can cause lasting psychological trauma in kids – manifested through low self-esteem, stress, anxiety, isolation and eating disorders – which in turn contributes to poor health outcomes.” The report goes on to suggest new approaches to measuring health with consideration for nutritional adequacy, upstream factors affecting food supply, nutritional assistance and indicators of food quality and availability. The COVID-19 pandemic was a stark reminder that low-income families, those who quit or lost jobs, and children who rely on school meal programs faced challenges accessing healthy food. Income and food insecurity are significant contributing factors in rising obesity rates. (3)  

RISK REDUCTION STRATEGIES 

All levels of government can play a role in prioritizing health, improving equity and reducing health disparities. Sustained and impactful policies, systems, and environmental strategies should take place where children live, learn, and play, such as healthier childcare settings, schools, and communities.(4)

The Idaho Physical Activity and Nutrition (IPAN) Program, housed within the Division of Public Health, works with local public health districts and community partners on obesity prevention initiatives that make healthy choices easier. These initiatives include childhood obesity prevention in Early Care and Education (ECE), nutrition and physical activity in schools, worksite wellness and food insecurity.

The Idaho Physical Activity and Nutrition Program (IPAN) is working with the following partners to support obesity prevention efforts statewide:

Local public health districts

Healthy Eating, Active Living (HEAL) Idaho Network

Idaho Hunger Relief Task Force

SNAP-Ed Program

Maternal and Child Health (MCH) Program

  2021 Idaho Youth Risk Behavior Survey, September 2022. Idaho Department of Education. Accessed January 30, 2023. Retrieved from: https://www.sde.idaho.gov/student-engagement/school-health/files/youth/Youth-Risk-Behavior-Survey-Results-2021.pdf

  2023 County Health Rankings Idaho Data Sourced from 2020 Behavioral Risk Factor Surveillance System

  State of Childhood Obesity Report : Meeting the Moment, Learning from Leaders at the Forefront of Change.  November 2022. Robert Wood Johnson Foundation. Accessed January 30, 2023. Retrieved from: Meeting the Moment:ange Learning From Leaders at the Forefront of Ch (stateofchildhoodobesity.org)

Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Pro motion, Division of Population Health. BRFSS Prevalence & Trends Data [online]. 2015. [accessed Sep 02, 2020]. URL: https://www.cdc.gov/brfss/brfssprevalence/

Obesity and Metabolism

Subject Area and Category

• Endocrinology
• Endocrinology, Diabetes and Metabolism
• Internal Medicine
• Public Health, Environmental and Occupational Health
• Nutrition and Dietetics

Endocrinology Research Centre (Moscow)

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20718713, 23065524

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