fast food causes obesity essay

Bulletin on Aging & Health

Do Fast Food Restaurants Contribute to Obesity?

Over the past thirty years, the prevalence of obesity and obesity-related diseases in the U.S. has risen sharply. Since the early 1970s, the share of children age 6 to 19 classified as overweight has more than tripled, from 5 percent to 17 percent, while the share of adults classified as overweight or obese rose from half to two-thirds of the population. Over this same period, the number of fast food restaurants more than doubled. Exposes such as "Supersize Me" and "Fast Food Nation" as well as reports in the popular press have frequently suggested that fast food is at least partly to blame for the U.S.'s rising obesity rates.

Despite the popularity of this view, it has been difficult to empirically establish a causal link between fast food and obesity. The simple fact that fast food restaurants and obesity have both increased over time is insufficient proof of this link, as are studies that rely on differences in fast food consumption across individuals, since people who eat more fast food may be prone to other behaviors that affect obesity.

In The Effect of Fast Food Restaurants on Obesity (NBER Working Paper 14721 ), researchers Janet Currie , Stefano DellaVigna , Enrico Moretti , and Vikram Pathania undertake a careful study of the effect of fast food on obesity using the exact geographic location of fast food restaurants. Specifically, the authors examine whether proximity to a fast food restaurant affects the obesity rates of 3 million school children and the weight gain of over 1 million pregnant women.

The authors have several strategies to overcome the concern that children whose school is close to a fast food restaurant may be more prone to obesity for other reasons. First, the authors compute whether the fast food restaurant is within 0.10, 0.25, or 0.50 miles of the school and test whether there is a differential effect by distance. Given that there is a fast food restaurant in the general area, whether the restaurant happens to be very close to the school is arguably random and thus a good way to identify the effect of fast food access on obesity. Second, the authors control for a rich set of school and neighborhood characteristics in their analysis and allow these to vary over time. Finally, the authors estimate models relating changes in obesity to changes in access to fast food restaurants, relying on schools that gain or lose a nearby fast food restaurant during the sample period to identify the effect of fast food access on obesity. The authors estimate their models using data on all California 9th graders for the years 1999 and 2001-2007.

In their analysis of pregnant women, the empirical approach is similar - the authors include women for whom they observe at least two births in their sample, so that they can examine whether changes in fast food access between one pregnancy and the next are associated with changes in the probability of excessive weight gain. The authors use Vital Statistics data from 1989 to 2003 for Michigan, New Jersey, and Texas, the states for which they were able to obtain confidential data with mothers' names and addresses.

Turning to the results, the authors find that proximity to a fast food restaurant significantly increases the risk of obesity. For children, having a fast food restaurant within 0.10 miles of school increases the probability of obesity by 1.7 percentage points, or 5.2 percent. Interestingly, there is no significant effect of having a restaurant 0.25 or 0.50 miles from the school. The effects of fast food access are larger for girls.

Is the magnitude of this finding reasonable? To probe this, the authors estimate how many additional calories would be needed to push enough students over the overweight threshold (85th percentile of the historical BMI, or body mass index, distribution) to generate the estimated 5.2 percent increase in obesity. They estimate this to be 30-100 calories per day (per student). Given the large number of calories in typical items from a fast food restaurant, the magnitudes seem plausible.

For pregnant women, having a restaurant within 0.10 miles increases the probability of gaining over 20 kilos during pregnancy by 0.2 percentage points, or 2.5 percent. Unlike for children, the effects are still discernable at 0.25 and 0.50 miles. The effects are largest for African American mothers and mothers with a high school education or less. For pregnant women, the estimated increase in calories needed to generate this effect is much smaller, only 1-4 additional calories per day.

The authors conduct several other interesting analyses. First, they explore the effect of other types of restaurants and find that only fast food restaurants affect obesity. Second, they ask whether the future presence of a fast-food restaurant is associated with greater obesity today. If that were the case, it would suggest that fast food restaurants locate in areas where obesity is trending up, providing an alternative explanation for the paper's findings. However, the authors find that only current fast food locations matter.

Overall, the study suggests that proximity to fast food significantly increases the risk of obesity. One possible explanation is that proximity to fast food reduces the costs of fast food, principally travel costs. A second explanation is that easier access to fast food tempts consumers who have self-control problems. The fact that the effects are larger for teens and fall off more quickly with distance suggests that travel costs are more important for teens than for pregnant women.

The policy implications of these findings are potentially important. As the authors conclude, "policies restricting access to fast food near schools could have significant effects on obesity among school children, but similar policies restricting the availability of fast food in residential areas are unlikely to have large effects on adults."

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Obesity and Fast Food

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There has been an exponential rise in the number of obese individuals especially in developed nations like United States and United Kingdom. Now obesity has become a public health problem in most nations.

Obesity is linked to several long term health conditions, premature death and illness including diabetes, heart disease, stroke, gall bladder disease, fatty liver, arthritis and joint disorders and some cancers.

Obesity and calorie intake

Studies have shown that this rise of obesity among the world population could be attributed to an increase in calorie intake coupled with lack of adequate physical activity.

Results from the analysis of data from the National Health and Nutrition Examination Survey (NHANES) indicate increases in quantity and energy density of foods consumed in the United States from 1976 through 1980 (NHANES II) and 1999 through 2002 (NHANES III).

Studies have shown that in the US per capita calorie intake increased by more than 300 kilocalories (kcal) among the entire population from 1985 through 2002. The numbers have only risen over the past decade.

Food choices

Food choices of individuals depend of several factors including:-

• environmental
• socioeconomic influences

The food choices affect energy intake and this interacts with the genetic and metabolic factors to finally determine the body weight and composition.

Energy imbalance

Obesity results from an imbalance between the amount of energy taken in, through eating and drinking, and the amount of energy spent on metabolism and physical activity. In children the energy is also spent in large parts in growth and development.

Studies have shown that over the past four decades, consumption of food eaten away from home has also risen alarmingly. It is well known that eating out may lead to excess calorie intake and increases the risk of obesity because of large portion sizes and increased energy density of foods.

Fast foods fall into this category of food. Fast foods are typically:-

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• high in calories
• high in fat
• high in saturated and trans fat
• high in sugar
• high in simple carbohydrates
• high in sodium (salt)

Fast food and BMI

Fast food is associated with higher body mass index, less successful weight-loss maintenance and weight gain.

Fast foods reduce the quality of diet and provide unhealthy choices especially among children and adolescents raising their risk of obesity.

Fast-food consumption costs were nearly $164.8 billion in 2010. This was a 3% rise from 2009.

Fast food and childhood obesity

Fast foods affect children and youth often worse than adults. This is because most of the fast foods are targeted towards children and there is a sustained pattern of eating fast foods and eating out.

Children with a sustained excess energy imbalance intake of approximately 2% result in the development of obesity over time.

A 2% imbalance could mean an excess of only about 30 kilocalories per day. This corresponds to two-thirds of a chocolate cookie, fewer than two French fries or one-fourth of a can of soda.

Eating out is another major contributor to childhood obesity. Studies show that calorie content of out-of-home meals that children consumed was 55% higher than that of in-home meals.

• http://www.cdc.gov/pcd/issues/2011/jul/pdf/10_0186.pdf
• http://www.aacorn.org/uploads/files/GrierJPublPolicyMarket07.pdf
• https://www.asu.edu/
• http://www.fastfoodmarketing.org/media/FastFoodFACTS_Report.pdf
• https://www.chicagobooth.edu/faculty/directory
• https://www.princeton.edu/
• http://bis.gov.uk/assets/foresight/docs/obesity/099-107.pdf

Further Reading

• All Obesity Content
• What is Obesity?
• Causes of Obesity and Overweight
• Obesity, What Can be Done?
• What is Body Mass Index (BMI)?

Last Updated: Jan 23, 2023

Dr. Ananya Mandal

Dr. Ananya Mandal is a doctor by profession, lecturer by vocation and a medical writer by passion. She specialized in Clinical Pharmacology after her bachelor's (MBBS). For her, health communication is not just writing complicated reviews for professionals but making medical knowledge understandable and available to the general public as well.

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I used to be seriously over weight.  I have complications with Type 2 Diabetes, hypertension, poor circulation in my legs.  Since I have lost 65 pounds since May of this year, my health has improved.  I rarely eat out and when I do, I chose healthier choices.  My best exercise is walking.  Obesity in children, teens and young adults can be reduced with a proper diet and exercise program.

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Causes and Effects of Fast Food: Essay Example

Essay about fast food: introduction, causes of fast food: essay body paragraph, effects of fast food: essay body paragraph, fast food causes and effects: conclusion, reference list.

Food is an integral part of any culture and society around the globe. Until the last century, most people used to eat fresh, home-cooked food. Eating was a process that required specific preparations. However, now, we see that they prefer to eat fast food such as pizza, hamburgers, or fried chicken.

These fast-food restaurants have become common on our streets, and people of all ages visit them. The popularity of these restaurants has increased internationally. There are many reasons why fast food has become popular, and fast food also has some serious effects on humans and society.

The basic question is, what made fast food so popular this last century? One answer would be that the change in lifestyle compared to before is a cause for this. It pushes workers or people to eat fast food than cook food themselves.

For instance, two working parents are a good example of this. Due to their jobs, they do not have time to cook for their children or even themselves. As a consequence, they find it easier to order from these fast food restaurants rather than cook. That is why they favor fast food over their own cooked food.

Another cause of fast food usage is long working hours, which may also lead people to eat outside the home. There are many fast-food businesses in our cities. Some are McDonald’s, Burger King, Pizza Hut, etc. We can make a long list with hundreds of names from these restaurants.

During the last couple of years, we saw a lot of advertisements and promotions for those restaurants. Nevertheless, there still remains a question of why they spend to promote ineffective food. What are the reasons for this? The answer is that fast food is easy to cook. It does not take long to cook, and it is readily available. The shareholders of these businesses have their own goals, that of the profits they get from these restaurants.

Above, we have seen the causes that may have led to the flourishing of the fast-food industry. However, what is more important, is its effects on society and human beings. The primary effect that fast food has on human beings is that it can get your health in danger status. First, fast food can cause vitamin deficiencies that may, in turn, help to cause diseases.

Obesity is one of the consequences of fast food on the human body. Obesity comes because fast food is the factor that enriches the body with fats. So people will become less healthy, less effective, and less productive, and this is the conclusion of obesity (Adams, 2007, pp. 155).

Another serious effect of the popularity of fast food presences is the loss of the family tradition of eating together. The family used to eat together, and thus they had the opportunity to talk with each other about daily problems.

Fast food also affects the income of the family. The conclusion is that fast food is more expensive than the food you cook for yourself.

In conclusion, it can be said that fast food has been born out of the modern way of living in our societies. Unfortunately, its effects on the human body and health are unfavorable. It also has other adverse effects on the income of a family. It would be best to avoid eating fast foods as much as possible.

Adams, C., 2007. Reframing the obesity debate: McDonald’s role may surprise you. Journal of Law, Medicine, and Ethics, no. 35: pp. 154-157.

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Cause and Effect of Fast Food: the Impact on Health and Society

Table of contents, causes of fast food consumption, effects on physical well-being, cultural and societal impact, economic considerations, promoting healthier lifestyles, conclusion: balancing convenience and health.

• Ludwig, D. S., Peterson, K. E., & Gortmaker, S. L. (2001). Relation between consumption of sugar-sweetened drinks and childhood obesity: a prospective, observational analysis. The Lancet, 357(9255), 505-508.
• Malik, V. S., Pan, A., Willett, W. C., & Hu, F. B. (2013). Sugar-sweetened beverages and weight gain in children and adults: a systematic review and meta-analysis. The American Journal of Clinical Nutrition, 98(4), 1084-1102.
• Story, M., Kaphingst, K. M., Robinson-O'Brien, R., & Glanz, K. (2008). Creating healthy food and eating environments: policy and environmental approaches. Annual Review of Public Health, 29, 253-272.
• Stuckler, D., McKee, M., Ebrahim, S., & Basu, S. (2012). Manufacturing epidemics: the role of global producers in increased consumption of unhealthy commodities including processed foods, alcohol, and tobacco. PLOS Medicine, 9(6), e1001235.
• World Health Organization. (2016). Report of the Commission on Ending Childhood Obesity. WHO Press.

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Fast Food Consumption and Health Risks

Do you know that 75¾% percent of the American population is likely to be obese by 2020? According to the Centers for Disease Control and Prevention, 36 percent of American adults and 17 percent of under 19 American youth are obese. Obesity has taken the form of an epidemic in the United States, leading to significant health problems. These include premature death and coronary disease, diabetes, fatty liver, asthma, etc. You may have heard that fast food consumption is one of the main causes of obesity. Fast food and obesity are known to be going hand in hand.

Let us look at the Fast food consumption causes and effects connection between fast food and obesity

• 72.4% and 34% of teenage students have used at least one fast-food form in recent months and weeks.
• The prevalence of BMI and WHR-based obesity was 21.3 percent (18.2 percent for females vs. 26.3 percent for males) and 33.2 percent (40.1 percent for females vs. 21.9 percent for males).
• Fast food intake was associated with WHR while not linked to BMI.
• Obesity/overweight based on BMI was linked to sandwich consumption by 35 percent, fried chicken by 40 percent, and pizza by more than 80 percent.
• The intake of calories from fast food decreased significantly with age.
• Non-Hispanic black adults ate a higher percentage of fast-food calories compared to non-Hispanic white and Hispanic adults.
• There was no difference in income status for all adults in calories eaten from fast food. However, the percentage of calories from fast food declined among young adults as incomes increased.
• The amount of total daily calories from fast food increased with an increase in weight.

Obesity and Calorie Intake

Studies have shown that this rise in obesity among the people of the world could be attributed to an elevated consumption of calories combined with a lack of sufficient physical activity. 

The National Nutrition and Health Examination Survey (NHANES) analysis shows an increase in the amount and energy density of food eaten in the United States from 1976 to 1980 (NHANES II) and from 1999 to 2002. (NHANES III).

Studies have shown that per capita calorie consumption in the US has risen in the population from 1985 to 2002 by more than 300 kilocalories (kcal). The numbers have only increased over the last decade.

Food Choices

Individual food choices depend on a variety of factors, including:-

• Environmental
• Socioeconomic influences

Food choices affect energy intake, working with physiological factors to determine body weight.

Why Does Fast Food Cause Obesity?

There are four basic causes why fast food is linked to obesity .

1. Unhealthful Ingredients

Much fast food contains a significant amount of sugar, fat, starch, and fewer minerals and vitamins. This means that you are taking a huge amount of unhealthy calories in fast food. This adds to weight gain and, ultimately, obesity. Most fast foods have excess sugar and fat levels that are directly related to increasing weight.

2. Larger Portions

Increased portion sizes further compound the unhealthy ingredients in fast food. They have risen in parallel with the average body weight from the 1970s to the present. While portions have become large, the person will always eat the whole meal regardless of whether he feels full. This means that people are eating larger portions of junk food, leading to abnormal weight gain.

3. Lower Cost

One of the biggest reasons people can’t avoid eating fast food is the low cost of food. The University of Washington performed research. According to it,  a diet containing 2,000 calories of fast food costs much less than a diet containing 2,000 calories of nutritious food. This makes it more affordable than a balanced diet. Thus, it is a leading cause of obesity in lower-income classes.

4. Convenience

Fast food restaurants provide ease. You can always find one in your house’s near area. And you can even get food easily delivered to your home. This makes it an easy alternative to making food at home using healthy ingredients.

Studies have shown that fast food consumption has risen at an alarming rate in the last four decades. This increased calorie consumption is the leading cause of obesity in the United States. If we do not control it, health issues will increase in the coming years. It is because more people will become obese eating unhealthy fast food.

Studies have shown that food intake consumed away from home has also increased alarmingly over the last four decades. It is well known that eating out can lead to excess calorie consumption. It will increase the risk of obesity due to large portion sizes and increased energy density.

Fast food is used in this type of food. Fast food is mainly:-

• high in calories, saturated/trans fat, sugar, simple carbs, and sodium

Fast Food and BMI

Fast food is linked with increased body mass indexes, less effective weight loss control, and weight gain. It reduces dietary quality and provides unhealthy choices, especially among children. Fast foods increase their risk of obe s ity .

The cost of fast food consumption in 2010 was almost $164.8 billion. This was a 3% increase from 2009.

Fast Food and Child Obesity

Fast food also impacts children and youth more than adults. This is because most fast foods are intended for children. There is a sustained pattern of fast food consumption and eating out.

Children with a sustained over-energy consumption of about 2% develop obesity over time .

A 2% imbalance may mean an excess of only around 30 kilocalories per day. This corresponds to two-thirds of a chocolate chip, less than two French fries, or one-fourth of a soda can.

Eating out is another main factor in childhood obesity. Studies show that the calorie content of out-of-home meals eaten by children was 55% higher.

How To Avoid Consumption Of Fast Food?

Fast food is the mainstay of many people’s diets. This is due to its low cost, widespread availability, and favorable taste. Fast food, though, also causes a variety of health problems and can sometimes be addictive. Fortunately, by eliminating the temptation to consume fast food and replacing it with healthier options, you can significantly reduce fast-food consumption and hopefully stop eating it completely.

• Plan your snack
• Think before you drink
• Base meals around protein
• Start your day on the right foot
• Make healthier swaps
• Practice mindful eating
• Buy less junk food
• Save takeaways as a treat
• Skip colored plates
• Break your routine
• Keep sweets out of sight
• Keep the healthy stuff handy
• Know your trigger foods
• Chew more than you need

The Bottom Line: Fast Food Consumption

As a concluding statement, fast food is the main cause of obesity. It is because fast food induces addiction, and fast food advertisements target youth. This increases childhood obesity. Fast food also results in the disappearance of nutritious meals and diets. The prevalence of obesity is further increased by the fact that they are widely accessible and cost-effective.

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Obesity as a Medical and Social Problem

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Definition and Overview

The World Health Organization (WHO) defines overweight and obesity as having “excessive fat accumulation that presents a risk to health.” There are various methods to calculate body fat , as each range in accuracy and can have limitations. Body mass index (BMI) is one tool used to screen for excessive body fat. A BMI value of more than 25 is categorized as overweight, and a BMI value of more than 30 is categorized as obese.

Why use BMI?

Health impacts.

There are negative health impacts associated with excess body fat. The WHO estimates that in 2019, 5 million deaths from noncommunicable diseases such as cardiovascular disease and diabetes were caused by a high BMI, and rates of obesity continue to grow globally in children and adults. [1] According to the Centers for Disease Control and Prevention in the U.S., 1 in 5 children and 1 in 3 adults has obesity. [2] Children with obesity are more likely to have obesity as adults and the associated risks of heart disease, high blood pressure, type 2 diabetes, and certain types of cancer.

A healthy amount of body fat in children and teens varies based on age as well as sex. The Centers for Disease Control and Prevention (CDC) developed growth charts for boys and girls ages 2-19 that show the distribution of BMI values at each age. [3] By the CDC’s definition, a child whose BMI falls between the 85th and 94th percentile for age and sex is considered overweight; a BMI at the 95th percentile or higher for age is considered obese. As the rates of obesity rise in children, there is also a category for severe obesity in which the BMI is 120% of the 95th percentile. The American Academy of Pediatrics provides more specific classifications of severe obesity:

• Class 2 Obesity: BMI ≥120% to <140% of the 95th percentile or BMI ≥35 to <40 kg/m 2
• Class 3 Obesity: BMI ≥140% of the 95th percentile or BMI ≥40 kg/m 2

Obesity can negatively affect nearly every system in a child’s body – the heart, lungs, muscles, bones, kidneys, digestive tract, and hormones that control blood sugar and puberty – and can also take a heavy social and emotional toll. Children with obesity may be burdened by stigma and discrimination from bullying, teasing and victimization. Youth with obesity have substantially higher odds of remaining overweight or obese into adulthood increasing their risk of disease and disability later in life. [4]

The risk of developing diabetes, heart disease, and other weight-related health risks increases with an increasing body mass index (BMI). But evidence shows that in some ethnic and racial groups, weight gain and higher fat mass even if BMI remains in the normal range can still increase health risks.

The Nurses’ Health Study tracked patterns of weight gain and type 2 diabetes (T2D) development in 78,000 U.S. women to see differences by ethnic group. [5] All women were healthy at the start of the study. After 20 years, researchers found that at the same BMI, Asians had more than twice the risk of developing T2D than Whites; Hispanics and Blacks also had higher risks of diabetes than Whites, but to a lesser degree. Increases in weight over time were more harmful in Asians than in other ethnic groups – for every 11 pounds Asians gained during adulthood, they had an 84% increased risk of T2D; Hispanics, Blacks, and Whites who gained weight also had higher risk, but to a much lesser degree than Asians. Other studies have found that even with a lower BMI than Whites, increasing weight in Asians with a BMI of 25 or higher increased risk of high blood pressure, T2D, and early death from all causes. [6-8]

One reason for this difference could be amount and location of body fat. Even with a lower BMI than other populations, Chinese and South Asians tend to carry higher abdominal fat than Whites, which increases the risk for T2D, cardiovascular disease, and other metabolic disorders. [9-11] In contrast, some studies have found that blacks have lower body fat and higher lean muscle mass than whites at the same BMI, and therefore at the same BMI, may be at lower risk of obesity-related diseases. [12,13]

For this reason, the World Health Organization and other organizations have recommended a lower BMI cutoff to classify obesity in Asian people (BMI of 25-27 or greater) as well as a smaller waist circumference to measure visceral fat. [9,14]

Weight gain of greater than 10 pounds in adulthood also increases disease risk (i.e., heart disease, high blood pressure, type 2 diabetes, gallstones) even in those whose BMI remains in the normal range, according to research from the Nurses’ Health Study and Health Professionals Follow-up Study. [15-19]

With the five leading causes of death – heart disease, cancer , chronic lower respiratory disease, cerebrovascular diseases such as stroke, and unintentional injuries – obesity is a major risk factor for the first four. [20] Obesity is also associated with other health conditions such as sleep apnea, fatty liver disease, gallstones, infertility, respiratory diseases, gastroesophageal reflux disease, and musculoskeletal disorders such as arthritis. No less real are the social and emotional effects of obesity which may include discrimination, lower quality of life, and susceptibility to depression.

Economic Impacts

Obesity costs the U.S. health care system almost $173 billion annually. [2] This includes money spent directly on medical care and prescription drugs related to obesity. In the workplace, research has shown that the number of sick days, short-term disability, and workers’ compensation days increase with increasing BMI. [21] Compared with an employee with a BMI of 25, an employee with a BMI of 35 has nearly double the risk of a disability or workers’ compensation claim. Perhaps one of the most surprising consequences of the current obesity epidemic in the U.S. is its impact on recruitment for the armed services, with data showing that 3 in 5 young adults carry too much weight to qualify for military service. [2]

According to the WHO, worldwide obesity rates are rising with 1 in 8 people, or more than 1 billion people, around the world living with obesity. [14] A Lancet review showed that global adult obesity doubled from 1990 to 2022, and adolescent obesity quadrupled. [22] As low to middle-income countries adopt unhealthy eating patterns and behaviors of industrialized nations such as less physical activity, so do their obesity rates. Specific regions including Polynesia, Micronesia, the Caribbean, the Middle East, and north Africa showed the greatest increases in obesity, as well as higher-income countries such as Chile. [22] Increased eating out of home, access to ultra-processed low-nutrient-dense foods, and sedentariness (e.g., sitting at work, driving instead of walking or bicycling) have contributed. Higher cost and limited access to healthy foods and decreased opportunities for play and sports may cause inequalities in obesity and could limit the impact of policies that target unhealthy foods. [22]

The NCD Risk Factor Collaboration visualizes the prevalence of obesity globally as well as changing obesity rates in various countries since 1990. Below are data summaries of obesity rates for both adults and children around the world:

In 2018, the United States had the highest prevalence of adult obesity among high-income Western countries worldwide. [23]   From 1999 through 2018, the age-adjusted prevalence of adults with obesity increased significantly from 31% to 42%. [24]. If trends continue, projections estimate that by 2030 nearly 50% of adults will have obesity, and nearly 1 in 4 adults will have severe obesity (BMI ≥35). [25]

Obesity disproportionately affects U.S. racial/ethnic minority populations. Compared to 42% of non-Hispanic whites, 50% of non-Hispanic Black and 45% of Hispanic adults have obesity. [24] There are considerable differences in obesity among non-Hispanic Black adults by sex, with 57% of non-Hispanic Black women having obesity compared to 41% of men. [24] Trends estimate that severe obesity may become the most common BMI category among non-Hispanic Black and low-income adults by 2030. [25]

Obesity rates in Canada are not as high as they are in the U.S., but Canada has seen dramatic increases over the past three decades. Obesity prevalence among Canadian adults increased from 9% in 1975 to 31% by 2016. [23] Indigenous populations in Canada are also disproportionately affected by the burden of obesity. [26]

The U.S. has among the highest childhood obesity rates in the world, with nearly 1 in 3 children with overweight or obesity. In 2015-2016, nearly 19% of children 2-19 years old had obesity, affecting an estimated 14 million children nationwide. Obesity prevalence was highest among adolescents 12-19 years old (21%) and lowest among preschool-aged children 2-5 years old (14%). [27] Recently, the prevalence of obesity declined among children ages 2-5 years old, held steady for children 6-11 years, and continued to rise among adolescents 12-19 years. [28,29] Current trends suggest that an alarming 57% of children currently between 2 and 19 years old will have obesity at age 35. [30]

Overweight and obesity disproportionally affects racial/ethnic minority populations, and such disparities exist as early as age 2 and persist into adulthood. [27,30] The highest obesity prevalence are among Hispanic (26%) and non-Hispanic Black children (22%), compared with the lowest prevalence among non-Hispanic White (14%) and non-Hispanic Asian (11%) children. [27]

Canada has also seen a rise in childhood obesity since the late 1970s. Obesity rates have more than doubled, and in some age groups, tripled. [31] But childhood obesity rates are lower there than they are in the U.S; in 2013, 10% of children ages 6-11 years old and 17% of children ages 12-17 had obesity. [32] Childhood obesity is significant among Canada’s Aboriginal groups. In a 2006 survey of Aboriginal Peoples in Canada, nearly 33% of children ages 6-8 had obesity, and 13% among children ages 9-14. [33]

Over the past several decades, obesity has become a significant health challenge in Latin America. While undernourishment persists among vulnerable groups, so do overweight and obesity. Each year, obesity among the population grows by 3.6 million individuals, and now exceeds undernourishment as the greatest nutritional threat. [34] Between 1975 and 2014, among the largest increases in BMI in regions worldwide occurred for men in central Latin America, and for women in Andean Latin America and the Caribbean. [35] In 2016, approximately 104 million adults in Latin America had obesity; 15% of men and 16% of women. [23] Countries with the highest prevalence of obesity included Bermuda (women 43%, men 30%) and Puerto Rico (women 42%, men 29%). [23]

While Latin America has shown significant progress in reducing child stunting due to undernourishment, prevalence of overweight and obesity due to malnutrition has grown to be among the highest in the world. [34] As a result, Latin American children have the dual burden of undernutrition coexisting with overweight and obesity. [36] In 2016, 15% of children ages 5-9 years and 10% of adolescents ages 10-19 years had obesity in Latin America and the Caribbean. [34] Among girls ages 5-19 years old, central Latin America demonstrated the highest increase of BMI per decade worldwide over the past 40 years. [37] Inequality further exacerbates overweight and obesity in populations with lower income, and among women, indigenous peoples, Afro-descendants, and rural families. [34]

Since 1975, obesity rates have been rising across Europe, though not as rapidly or as high as they are in the U.S. [35] Countries with the highest prevalence include Malta and the United Kingdom, hovering around 30% for both men and women. Countries with the lowest obesity prevalence include Austria, Sweden, Denmark, and Switzerland for women and Moldova and Russia for men (<20% for all). [23] The rise in women’s BMI in central and southwestern Europe has been among the lowest over the past 40 years, one of the few places worldwide that can report such a trend. [23,35]

Over the past several decades, many European countries had among the largest increases in the number of children and adolescents with obesity. [37] More recently, obesity has plateaued in many regions, particularly in eastern, northwestern, and southwestern Europe, but prevalence rates remain high in Mediterranean countries. [37,38] In Greece, Malta, and Cyprus, 16% of boys ages 5-19 have obesity, and 11% of girls in Greece and Malta. [37]  

Regional surveys and analyses demonstrate similar childhood obesity trends in Europe. A 2019 systematic review of 130 studies across 28 European countries assessed prevalence trends in overweight and obesity among 2-13-year-old children between 1999-2016. [39] The prevalence of overweight and obesity tended to decrease in the Iberian region and increase in the Mediterranean regions, with no significant changes in Atlantic or Central Europe. Although the overall prevalence of childhood overweight and obesity remains high, trends have stabilized in most European countries, but continues to rise in some Mediterranean countries. [39]

Undernutrition has historically received more public health attention in Africa than overnutrition. Yet today, obesity and associated chronic diseases have become a growing problem across the continent. Some have called it a “silent epidemic,” striking countries that are still struggling with the health and economic burdens of malnutrition, stunting, infectious disease, and high childhood mortality rates. [40]

Obesity prevalence is higher among African women compared with men, and can vary widely from country to country. For example in 2016, 41% of women in South Africa had obesity (higher than in U.S. women) compared with 16% of men. In stark contrast, the lowest prevalence of obesity was in Ethiopia for women (7.3%) and in Uganda for men (2%); prevalence of undernutrition exceeds that of overnutrition in these African countries among many others. [35]  Between 1975 and 2016, Botswana experienced the largest increases in obesity prevalence in these African regions, jumping from 5% to 31%. [35]

Hunger, underweight, and stunting have long been the more pressing child nutrition concerns across Africa. Even today, more children and adolescents are moderately or severely underweight than obese, particularly in central, east, and west Africa. [35] Yet here too, child obesity rates are on the rise, particularly in southern Africa. In 1975, less than 0.5% of girls and boys in South Africa had obesity, but by 2016 the prevalence jumped to 13% for girls and 10% for boys. [37]

Researchers have taken a closer look at obesity trends in the six Persian Gulf states (Oman, Bahrain, United Arab Emirates, Saudi Arabia, Qatar, and Kuwait), since these countries have seen tremendous increases in wealth since the discovery of oil reserves in the 1960s. [41] Even in 1975, obesity prevalence in Kuwait, Qatar, and the United Arab Emirates exceeded 20% among women, raking among the top 20 countries worldwide with the highest prevalence. Among men, Kuwait and Qatar also ranked among the top 20 countries with the highest prevalence in 1975, but only at 12%. [23] In 2016, the prevalence of obesity increased to 47% in Kuwait and 45% in Qatar for women, and to approximately 30% for men in both countries. The most significant increases have been observed in Saudi Arabia and Jordan, from 6% in 1975 to around 30% in 2016. [23]

The Middle East and north Africa have seen sharp increases in obesity since 1975, and this region now has among the highest prevalence of child and adolescent obesity worldwide. [38] Girls in Kuwait and Egypt and boys in Kuwait, Qatar, and Saudi Arabia have the highest obesity prevalence in the region, all hovering around 20% of the child and adolescent population. [37] In 1975, girls in the Middle East and north Africa had higher age-standardized BMI than boys, but by 2016 this gap shrank or reversed as boys gained more weight than girls. [37]

Some countries in Asia have the lowest obesity prevalence worldwide, yet here too it has become a serious problem across the region over the past four decades, even while underweight concerns persist. Japan and South Korea have among the lowest obesity prevalence in the world (<9%) for both men and women. However, recent trends in China are of special concern. Although obesity rates are still low overall, there has been a substantial increase from <1% in 1978, to 6% for women and 7% for men in 2016. [23] China is one of the most populous nations on the planet with more than 1.4 billion people, so even small percentage increases in obesity prevalence translate into millions more cases of chronic disease. Furthermore, Asians have a higher risk of weight-related diseases like type 2 diabetes at lower BMI levels , further exacerbating the health issues related to overweight and obesity.

South Asian countries like Bangladesh, India, and Pakistan have among the highest prevalence of moderate and severe underweight worldwide; 20% in girls and 29% in boys. Nevertheless, trends in mean BMI have significantly accelerated in east, south, and southeast Asia between 1975 and 2016. Although obesity prevalence remains relatively low in south Asia, their large populations add up to large numbers of children who have obesity.

Compared to south Asia, the prevalence of child and adolescent obesity is greater in high income Asia Pacific and east/southeast Asia, particularly among boys. [37,38] Obesity prevalence in Malaysia, Taiwan, and China for boys was less than 0.5% in 1975 and jumped to 15% in 2016. Girls in Asia have lower obesity prevalence compared to boys, but has still been increasing over time, most notably in Malaysia where obesity increased from 0.2% to 10% during this time period. [37]  

It’s important to note that in Asian adults, the health complications associated with overweight and obesity start at a lower BMI than seen in the U.S. and Europe; therefore these estimates of child obesity prevalence in Asia likely underestimate the true public health burden of obesity in Asia.

The top 13 countries with the highest obesity prevalence worldwide are located within Oceania. Eight of the countries exceed 45% obesity prevalence among men, and 13 countries exceed 50% among women. American Samoa and Nauru have the highest obesity prevalence among women (68%) worldwide; for men it is Nauru at 60%. Australia and New Zealand have lower prevalence in the region but still hover around 30% for both men and women. [23]

Of the top 13 countries with the highest child and adolescent obesity prevalence in 2016, 11 were located in Oceania. There was more than 30% obesity prevalence for both girls and boys in the Cook Islands, Nauru, Palau, and additionally for boys in Niue and American Samoa. [37]

High-income countries in Oceania, Australia and New Zealand have childhood obesity rates in the double digits, but there’s some evidence that rates have hit a plateau. In Australia, 13% of boys and 11% of girls have obesity; in New Zealand the prevalence is higher at 18% and 15% respectively. [37] Overweight and obesity prevalence is even higher in some of New Zealand’s ethnic groups (Maori, 37%; Pacific Islanders, 57%) but have largely unchanged since early 2000. [42]

Risk Factors

Various factors can influence body weight or greater weight gain in specific areas of the body. Some of these cannot be changed, but others may be modified:

• Non-modifiable risk factors (risk factors you can’t change): age, gender, genes, ethnic origin, and sometimes medications that change how energy is processed in the body leading to weight gain. There’s also strong evidence that having obesity in infancy or childhood increases the chances of remaining obese in adulthood.
• Risk factors that can be modified: food and beverages consumed, level of physical activity, daily screen time (increased screen time is associated with reduced physical activity time and also increases exposure to marketing of unhealthy foods/beverages), poor sleep hygiene, uncontrolled negative stress. While easier said than done, evidence has shown that addressing these factors as early as possible, even in childhood, may reduce the risk of developing obesity.

Obesity is complex and not just about being born with a certain body size, taking in more calories than the body needs, or burning extra calories through exercise to lose weight. It is often the result of a combination of several non-modifiable and modifiable risk factors. When looking at diet and food, which is often the focus with obesity, there are various factors to consider than just calories in/calories out:

• Living in a food environment that lacks access to healthy food choices or income-related barriers to regularly consuming a variety of healthy foods.
• Amount of low-nutrient ultra-processed foods and sugary beverages consumed, especially when displacing high-fiber whole foods, which can increase cravings .
• Eating behaviors such as skipping meals and eating heavy meals or snacks at night before bed.
• Overeating portions not from hunger but from stress or boredom.

The environments that surround us also play an important role, as they can make a modifiable risk factor a non-modifiable one. Examples are when someone does not have the ability to secure healthy food choices due to living in a food desert or a safe place to perform regular physical activity .

There are various risk factors for obesity, but not everyone with these risk factors develops obesity. And not everyone who has obesity develops health problems. In these cases, genes may play a role. Studies of siblings or twins show genetic factors that can determine weight and body size throughout life. [43] Some research suggests differences in genes in people who are of normal weight versus those carrying extra weight that may influence appetite control, metabolic rate, or even ability to change behavior. Gene-nutrient interactions can also promote obesity. For example, genes that increase risk of developing obesity have been reported to be stimulated by saturated fatty acids but not by unsaturated fatty acids . [43] The gut microbiome may also play a role in a person’s risk of developing obesity and chronic health conditions. [44]

However, obesity caused by mutations in a single gene, or monogenic obesity, is rare and is more likely influenced by changes in many different genes, called “common” obesity. Still, the modern obesity epidemic is largely fueled by environmental factors, with excess energy intake and low physical activity pinned as the main culprits. [45] First-degree family members (parents, siblings) who live together typically share similar environments that increase the risk of obesity, and health-related habits of parents are often passed onto their children. Examples include food choices, meal preparation methods (cooking at home vs. reliance on fast food), exercise, screen time, and sleep habits, as well as lack of access to outdoor green space.

These findings suggest that genetic factors make a small contribution to obesity risk, and that our genes are not our destiny. Many people who carry potential “obesity genes” do not become overweight, and healthy lifestyles can counteract these genetic effects.

Is Prevention Possible?

Many factors contribute to rising rates of obesity in children and adults. Among them, the abundance of low-priced, high-calorie ultra processed foods and sugary drinks; incessant marketing driving people to eat more; and an environment that reduces the need for regular physical activity.

Although preventing weight gain over the years of life may not be possible for everyone due to a variety of circumstances, there are strategies to reduce the amount of weight change by increasing awareness of modifiable risk factors and working toward healthy lifestyle behaviors.

However, focusing only on the individual (e.g., nutrition and lifestyle education, weight loss medications) has little impact on global obesity prevalence. Prevention requires a broader scope that addresses food systems and an obesogenic environment , including policy changes such as regulating the marketing of ultra-processed low-nutrient-dense foods and taxing items such as sugar-sweetened beverages.

Indeed, what sometimes gets lost in the discussion is that obesity is preventable . We can turn around the obesity epidemic by collaboratively creating an environment where the default option is the healthy choice.

Obesity prevention at the individual level and beyond

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Does Fast Food Cause Obesity?

Info: 2865 words (11 pages) Nursing Essay Published: 11th Feb 2020

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• www.news-medical.net/health/Obesity-and-Fast-Food.aspx.
• https://www.healthline.com/health/fast-food-effects-on-body#sodium
• https://consumer.healthday.com/vitamins-and-nutrition-information-27/food-and-nutrition-news-316/junk-food-not-to-blame-for-america-s-obesity-epidemic-study-704950.html

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Fast Food Pattern and Cardiometabolic Disorders: A Review of Current Studies

Zahra bahadoran.

1 Nutrition and Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran

Parvin Mirmiran

Fereidoun azizi.

2 Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran

Background: There are growing concern globally regarding the alarming trend of fast food consumption and its related cardiometabolic outcomes including overweight and obesity. This study aimed to review the current evidences available in relation to adverse effects of fast food pattern on cardiometa­bolic risk factors.

Methods: Relevant articles including epidemiological and clinical studies with appropriate design and good quality were obtained through searches of the Medline, PubMed, Scopus databases and Google scholar with related key words including "fast foods", "processed foods", "obesity", "overweight", "insulin resistance", "diabetes", "cardiovascular disease", "metabolic syndrome", "dyslipidemia" and "hypertension".

Results: Fast food consumption and out-of-home eating behavior is a main risk factor for lower diet quality, higher calorie and fat intake and lower micronutrients density of diet. Frequent consumption of fast foods was accompanied with overweight and abdominal fat gain, impaired insulin and glucose homeostasis, lipid and lipoprotein disorders, induction of systemic inflammation and oxidative stress. Higher fast food consumption also increases the risk of developmental diabetes, metabolic syndrome and cardiovascular disease.

Conclusion: This review provides further evidence warning us against the irreparable effects of fast food consumption on public health especially the increasing global burden of obesity and cardiovascu­lar diseases.

Introduction

A growing trend of fast food consumption along with alarming trend of cardiometabolic disorders is considered as a globally health problem. Although there is no agreement on the definition of fast food, it is mainly defined as "easily prepared processed food served in snack bars and restaurants as a quick meal or to be taken away" in dictionaries and encyclopedias; industrial foods such as canned foods or snacks may also considered as fast foods. 1 In the recent years, an increasing globally popularity have been developed regarding the fast foods and take-away foods marketing. Out-of-home meals and fast foods are rich in highly processed meat and refined carbohydrate, sodium, total fat, saturated and trans fatty acids, cholesterol, and poor in essential nutrients and dietary fibers; 2 the fast food pattern also has undesirable effects on overall diet quality especially in children and adolescents. 2 - 4 Fast food consumption and out-of-home eating behavior is a main risk factor for higher calorie and fat intake and lower micronutrients density of diet. 3 , 5 Frequent consumption of fast foods is one of the main reasons for rising trends of overweight and obesity, cardiovascular disease, type 2 diabetes and other metabolic abnormalities. 3 , 6 - 8 Higher availability of fast food services is associated with higher mortality and hospital admission rates for acute coronary heart disease as well as a higher risk of overweight and obesity. 9 , 10

Considering to growing interest to Western dietary patterns and trend of fast food consumption along with global burden of cardiovascular diseases, diabetes, obesity and hypertension, and the lack of a comprehensive review study on cardiometabolic outcomes of these dietary patterns, this study aimed to review the current evidence in relation to adverse effects of fast food patterns on non-communicable diseases with focusing on cardiometabolic risk factors.

Materials and Methods

This is a narrative review article. The original research articles were reviewed published in English from 1990 to 2014. To search the articles, a number of databases and search engines, including PubMed, Medline, Scopus and Google Scholar were used. The references of the articles were also reviewed to identify papers that are more relevant. Searches were conducted with the search terms “fast foods”, “processed foods”, “obesity”, “overweight”, “insulin resistance”, “diabetes”, “cardiovascular disease”, “metabolic syndrome”, “dyslipidemia” and “hypertension”. Relevant articles including both epidemiological including cohort, case-control, cross-sectional and clinical studies were assessed for initial eligibility. Studies with English language evaluated the association between fast food consumption with cardiometabolic risk factors, with appropriate design and good quality (e.g. accurate definition of exposure and outcome, study population, clearly defined statistical methods) were included.

Ethical consideration

Ethical issues which have been considered for this study was included prevention of selective reporting bias of the papers, and honesty in reporting of the results of the studies. Moreover, related references have been carefully cited throughout the manuscript.

Fast food consumption and the risk of overweight and obesity

The alarming trend in the acceleration of overweight and obesity is mainly attributed to changes in lifestyle determinants and environmental factors. A rapid on-going nutrition transition with progressive shift to a westernized diet, in particular higher consumption of industrial and processed foods, and sweetened beverages are major factors contributing to the global epidemic of obesity. 11 Among various dietary factors, out-of-home eating patterns and regular consumption of fast food have been proposed as determinant factors in the prevalence of obesity and severe weight gain over time; 12 , 13 an association which has been confirmed in both prospective and cross-sectional studies. In Table 1 , the associations of fast food consumption with anthropometric measures and risk of obesity in cohort and cross-sectional studies were reviewed.

Frequent consumption of fast food, ≥2 times/week, compared to <1 time/week, has been accompanied with ≥4.5 kg weight gain during a fifteen-year follow-up of US adolescents and young adults. 6

Participants of the Coronary Artery Risk Development in Young Adults (CARDIA) study who were in the highest compared to the lowest quartile of fast food consumption, had higher weight (adjusted mean=5.6 kg, 95% CI= 2.1-9.2), and waist circumference (adjusted mean=5.3 cm, 95% CI=2.8-7.9) after a 13-yrfollow-up; in this study, fast food intake was associated with 13-yrchanges in body weight (β=0.15, 95% CI= 0.06-0.24) and waist circumference (β=0.12, CI= 0.04-0.20). 7 A3-yrfollow-up of adults also showed that increased consumption of fast foods was associated with an increase in body mass index(BMI) change (β=0.05, 95% CI=0.01-0.09); each one unit increase in fast food consumption (1 time/wk) was associated with a 0.13 increase in BMI at baseline (β= 0.13, 95% CI: 0.04-0.22) and a 0.24 increase in BMI after 3years (β=0.24, 95% CI= 0.13-0.34). 14

Participants of the Coronary Artery Risk Development in Young Adults (CARDIA) study who were in the highest compared to the lowest quartile of fast food consumption, had higher weight (adjusted mean=5.6 kg, 95% CI= 2.1-9.2), and waist circumference (adjusted mean=5.3 cm, 95% CI=2.8-7.9) after a 13-yrfollow-up; in this study, fast food intake was associated with 13-yrchanges in body weight (β=0.15, 95% CI= 0.06-0.24) and waist circumference (β=0.12, CI= 0.04-0.20). 7 A3-yrfollow-up of adults also showed that increased consumption of fast foods was associated with an increase in body mass index (BMI) change (β=0.05, 95% CI=0.01-0.09); each one unit increase in fast food consumption (1 time/wk) was associated with a 0.13 increase in BMI at baseline (β= 0.13, 95% CI: 0.04-0.22) and a 0.24 increase in BMI after 3 years (β=0.24, 95% CI= 0.13-0.34) . 14

In a Mediterranean cohort study, a higher risk of weight gain (≥3 kg during a 5 past year) (OR=1.2, 95% CI=1-1.4) was observed in adults who consumed more hamburger, pizza, and sausages; a significantly greater weight gain during a 2-year follow-up was also observed in the highest compared to the lowest quintile of fast food consumption (0.77 kg vs. 0.47 kg). 15 A three-year follow-up of women also indicated that increased consumption of one fast food meal per week led to a 0.72 kg more weight gain. 21

Cross-sectional studies 2 , 16 , 20 - 22 also reported a positive association between consumption of fast food and the anthropometric measures in different populations and various age-groups; in school children, consumption of fast food was associated with a higher BMI Z-score (β=0.08, 95% CI=0.03-0.14), higher body fat (β=2.06, 95% CI=1.33-2.79) and an increased risk of obesity (OR=1.23, 95% CI=1.02-1.49). In a cross-sectional survey, frequency of fast food consumption was positively associated with body mass index (β=0.31, P =0.02), in adults. 16 The association of fast foods and BMI was β=0.39 and 0.85 in high- and low-income in young and middle-aged women, respectively. 22 In Singaporean adults, the risk of abdominal obesity was 1.24 (95% CI=1.03- 1.51) and 1.52 (95 % CI= 1.32- 1.77) in regular consumers and occasional consumers of fast food meals. 17 In the Michigan Behavioral Risk Factor Survey, the adjusted-odds of obesity in adults consuming ≥3 times/week compared to <1 time/week fast food meals was 1.81 (95% CI=1.35-2.44). 18 A significant association between fast food intake and BMI (β=0.104, P <0.01) as well as waist circumference (β=0.083, P <0.01) was observed among Iranian young adults. 19 In Mediterranean adults, the association of fast food consumption with BMI was estimated to be β=1.76 (95% CI=0. 22, 3.3), and the risk of obesity increased by 129% in >1 time/week fast food consumers, compared to non-consumers. 2 More interestingly, a health community survey in Michigan found a significant association between local concentrations of fast food outlets with BMI (β=3.21, P <0.001) and poor diet quality (β=2.67, P <0.008). 20

Findings of a study on 23182 adolescents in Finland showed an strong association between fast-food outlet near school with breakfast skipping and undesirable eating habits; in this study, proximity of a fast-food outlet was associated with increased risk of overweight (OR=1.25, 95% CI=1.03-1.52). 23 One study on the participants of National Health and Nutrition Examination Survey showed that fast food and full-service restaurant consumption, respectively, was associated with more energy, total fat and sodium intake as well as a decrease in daily intake of vitamin A, D, and K. 24 Fast-food consumption was also significantly associated with higher intake of total energy (β=72.5, P =0.005), empty calories (β=0.40, P =0.006) and BMI (β=0.73, P =0.011), and lower healthy eating index score (β= -1·23, P =0·012), vegetables (β=-0·14, P =0·004), whole grains (β=-0.39, P =0·005), fiber (β= -0.83, P =0·002), magnesium (β=-6·99, P =0·019) and potassium intakes (β=-57.5, P =0·016). 25

Fast food consumption and dyslipidemia

Another cardiometabolic risk factor regarding fast food pattern highlighted in the literature is impaired metabolism of lipids and lipoproteins. In Coronary Artery Risk Development in Young Adults (CARDIA), participants who consumed ≥2.5 compared to <0.5 meal/week of fast food meals, had higher levels of serum triglycerides (117±3.6 mg/dl vs. 95±5.2 mg/dl), and lower high-density lipoprotein cholesterol (HDL-C) (52.0±0.7 mg/dl vs. 57.5±1.1 mg/dl), over 13 years of follow-up; moreover, longitudinal associations (β coefficient ± SE) of weekly fast food consumption with 13-year changes of triglycerides (TG), low-density lipoprotein cholesterol (LDL-C) and HDL-C were β=0.24±0.40, β=0.16±0.14, and β=0.08±0.06), respectively. 7 A greater increase in 3-year changes of TG levels was found in Tehran Lipid and Glucose Study (TLGS) participants, who consumed more fast food meals at baseline (10.6% vs. 4.4% increase, in the fourth compared to first quartile of fast food intake); serum triglycerides to HDL-C ratio, an independent risk factor of cardiovascular disease, also increased in adults with higher compared to lower fast food intakes (3.7% vs. -5.5%, in the fourth compared to the first quartile). 8

A cross-sectional analyses in TLGS study also indicated that fast food consumption (g/week) was significantly associated with serum TG (β=0.07, P <0.05), HDL-C (β= -0.05, P <0.05) and atherogenic index of plasma (β=0.06, P <0.05) only in middle-age adults; a higher prevalence of hypertriglyceridemia was also observed in the highest compared to the lowest tertile of fast foods (42.3 vs. 34.2%). 19 Postprandial lipemia and lipid peroxidation increased after consumption of a fast food meal, compared to a healthy meal; triglyceride levels, malondialdehyde, and thiobarbituric acid reactive substances (TBARS) were significantly higher and HDL-C levels were significantly lower after fast food meal. 26

Fast food consumption and the risk of diabetes, metabolic syndrome and cardiovascular disease

The adverse effects of fast foods consumption on the development of metabolic abnormalities has been reported in several investigations. The associations of fast food consumption with the risk of insulin resistance, diabetes, metabolic syndrome and cardiovascular disease in cohort and cross-sectional studies were summarized in Table2 . A 15-yrfollow-up of American women showed that higher fast food intake ≥ 2 times resulted in greater insulin resistance. 6 In the CARDIA Study, participants in the 3 rd and 4 th , compared to the first quartile category, of fast food intakes at baseline, had greater odds of metabolic syndrome after 13-yrof follow-up (OR= 1.9, 95% CI= 1.11-3.26 and OR= 2.14, 95% CI= 1.24-3.70, in 3 rd and 4 th quartiles, respectively); homeostatic model assessment of insulin resistance (HOMA-IR) at final examination was also positively associated with fast food consumption at baseline (3.9±0.14 vs. 0.3±0.18 in the highest compared to the lowest quartile of fast foods).A one-follow-up of adults showed that higher consumption of processed meat products was independently associated with the incidence of metabolic syndrome (OR= 2.5, 95% CI= 1.0-6.2). 30

The prospective approach of TLGS also showed that the risk of metabolic syndrome in the highest, compared with the lowest, quartile of fast foods increased by 85% (OR=1.85, 95% CI=1.17–2.95); in this study, the adverse effects of fast food consumption were more pronounced in younger adults (<30 yr), and participants who had greater waist to hip ratio, consumed less phytochemical-rich foods or had low-fiber diet ( P <0.05). 8 Non-alcoholic fatty liver disease, a hepatic feature of metabolic syndrome, could be a result of fast food consumption. In an intervention study, 4-wkconsumption of fast food meals (≥2meals/day) in healthy subjects increased serum levels of alanin aminotransferase (22.1±11 U/l to 69.3±76 U/l), insulin resistance index (0.89±0.42 to 1.6±0.83) and hepatic triglyceride content (1.1±1.9% to 2.8±4.8%) as well as body fat percent (20.1±9.8% to 23.8±8.6%). 31

A prospective cohort of Singaporean women showed that consumption of fast food ≥2 times/wk increased the occurrence of type 2 diabetes (hazard ratio= 1.27, 95% CI= 1.03-1.54) and coronary heart disease mortality (hazard ratio = 1.56, 95% CI= 1.18-2.06). 27

Increased consumption of burger, fried chicken meals, sausage and other processed meat products as well as French fries was associated with an increased risk of developing type 2 diabetes mellitus; a prospective study of 84,555 women in the Nurses' Health Study indicated that higher intake of French fries increased the 20-years risk of diabetes by 21% (OR=1.21, 95% CI=1.09-1.33). 28 In Black Women's Health Study, the 10-year incidence rate of type 2 diabetes for higher intake of hamburgers and fried chicken (≥ 2 meals/week compared to none) was 1.40 (95% CI= 1.14, 1.73) and 1.68 (95% CI= 1.36, 2.08), respectively. 29 Meta-analysis of seven prospective cohorts found that higher consumption of processed meat increased the risk of type 2 diabetes by 19% (95% CI=1.11-1.27). 32

More interestingly, rather than the consumption of fast foods, the rate of accessibility to fast food services has been reported as a risk factor for cardiovascular disease; risk-adjusted outcomes in regions with high compared to low accessibility to fast food services were greater for mortality (OR= 2.52, 95% CI=1.54-4.13) and acute coronary hospitalizations (OR= 2.62, 95% CI=1.42-3.59). 9

This review provides further evidence warning us against the irreparable effects of fast food consumption on public health especially the increasing global burden of obesity and cardiovascular diseases. Frequent consumption of fast foods as well as out-of-home meals is a serious dietary risk factor for development of increasing trend of obesity and other related abnormalities. Higher consumption of fast foods has undesirable effects on dietary intake and overall diet quality, which leads to increased incidence of metabolic disorders including obesity, insulin resistance, type 2 diabetes as well as cardiovascular disorders.

Briefly, compared to non-consumers or <1 time/week, regular consumption of fast foods and out-of-home meals ≥1-3 times/week was associated with an 20-129%elevated risk of general and abdominal obesity. 9 , 15 , 17 , 18 Increased risk of type 2 diabetes and metabolic syndrome in subjects with higher consumption of fast foods (mean ≥ 2 times/week) was reported 27-68% and 85-150%, respectively. 7 , 8 , 14 , 27 - 29 Higher consumption of fast foods and higher exposure to multiple sources of accessible, cheap, energy-dense fast foods were also accompanied with a 56-162% increased risk of coronary heart disease mortality. 9 , 27

Several possible mechanisms have been suggested to explain undesirable effects of fast foods on health status. A main factor describing the obesity-induced properties of fast foods is a high-energy dense modality. Most fast foods have an extremely high energy density, approximately 158 to 163 kcal per 100 gram of food; it also has been estimated that a fast food meal typically has an energy density twice the recommended a healthy diet and contains approximately 236 kcal/100 g. 33

High energy density of foods may have adverse effects. 34 In children, consumption of fast foods compared to non-consumers, led to greater intake of energy (>187 kcal/day), energy density (0.3 kcal/g), total fat (9g/d), carbohydrate (24 g/d), and added sugar (26g/d). 35 In adults, participants in the highest compared to the lowest quartile of fast food consumption also had more energy intake (>460 kcal/d), total fat (>2.5% of total energy), and cholesterol (>30 mg/d). 8 The difference of calorie intake in fast food days, compared with non-fast food days was estimated to be within 400 kcal in overweight adolescents. 36

High-fat content and inappropriate composition of fatty acids of fast foods is a main dietary risk for chronic disease. Mean total fat percent of beef hamburgers, chips, chicken hamburgers and hot dogs has been reported within 35.83±10.68%, 35.84±8.66%, 23.02±5.07%, and 34.02±13.49%, respectively; 28-52% of total fat was estimated as saturated fat. 37

Large portion size, high amount of refined carbohydrates and added sugar, and high glycemic load are other characteristics that could explain the threatening properties of fast food meals. 38 In some of the most popular fast foods, trans fats were up to 24g/serving. 4 Higher content of industrially produced trans fatty acids in fast foods is an important component leading to weight gain, abdominal fat accumulation, development of insulin resistance and cardiovascular events. 39 Furthermore, sodium content of fast foods is often higher than recommended amounts; in some common fast food meals, salt content was reported to range from 4.4 to 9.1 gr per meal; 40 a high-salt diet besides increasing blood pressure also intensifies insulin resistance and metabolic syndrome features. 41

Some of the mechanisms that could explain the metabolic outcomes of fast foods have been investigated in clinical and experimental studies. Postprandial adverse metabolic disorders including lipemia, oxidative stress and pro-inflammatory processes after eating a fast food meal observed in a human study are other possible explanations for cardiometabolic outcomes of fast foods. 26 Compared to a healthy fast food meal (fiber rich sourdough rye bread, salad with vinegar, orange juice), a hamburger meal (hamburger, bacon, cola drink) was associated with higher postprandial serum levels of glucose and insulin. 42 , 43

In animal models, fast food diet induced a phenotype of non-alcoholic fatty liver and steatohepatitis; 43 in this study, fast food diet was accompanied with higher liver weight, serum concentration of aspartate aminotransferase, intra-acinar inflammation and development of steatosis. Higher expression of genes related to fibrosis, inflammation, endoplasmic reticulum stress, and lipoapoptosis also was induced by fast food diets; activated pathways of hepatocellular oxidative stress, profibrotic and pro-inflammatory pathways were observed. 44 After a fast food meal, a severe decrease in plasma antioxidant vitamins including vitamin A, E and C, and zinc, as well as iron accumulation was observed in rats; decreased levels of superoxide dismutase, reduced gluthathione, and higher levels of thiobarbituric acid reactive substances, lipoprotein oxidation susceptibility, C reactive protein and tumor necrosis factor-alpha were also observed. 44

This study was a narrative review and had some limitations, which should be considered; subjective nature of the search method, potential selection bias of the articles, probable missing of unpublished data and lack of using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to design and report of the study were the mains limitations. Further researches especially meta-analysis of current studies may provide a comprehensive and accurate picture for undesirable outcomes of fast food patterns. Moreover, further assessment of nutritional behaviors and social determinants of fast foods intakes among different populations could help to development of efficient health strategies.

Considering to growing interest to out-of-home meals and high prevalence of fast food consumption, food policies with an emphasis on providing healthy foods, and making nutritional information at fast-food restaurants may help consumers to order more healthful or lower-calorie foods.

Acknowledgments

The authors wish to thank Ms. N.Shiva for critical editing of English grammar and syntax.

Conflict of interest

There is no conflict of interest.

Citation: Bahadoran Z, Mirmiran P, Azizi F. Fast Food Pattern and Cardiometabolic Disorders: A Review of Current Studies. Health Promot Perspect 2015; 5(4): 231-240. doi: 10.15171/hpp.2015.028

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• http://orcid.org/0000-0002-5210-1538 Elisa Pineda 1 , 2 ,
• Jemima Stockton 3 ,
• Shaun Scholes 3 ,
• Camille Lassale 4 , 5 and
• Jennifer S Mindell 3
• 1 The George Institute for Global Health UK , Imperial College London , London , UK
• 2 School of Public Health , Imperial College London , London , UK
• 3 Research Department of Epidemiology and Public Health , University College London , London , UK
• 4 Barcelona Institute for Global Health (ISGlobal) , Barcelona , Spain
• 5 CIBER Physiopathology of Obesity and Nutrition (CIBEROBN) , Carlos III Health Institute (ISCIII) , Madrid , Spain
• Correspondence to Dr Elisa Pineda; e.pineda{at}imperial.ac.uk

Background Obesity is influenced by a complex, multifaceted system of determinants, including the food environment. Governments need evidence to act on improving the food environment. The aim of this study was to review the evidence from spatial environmental analyses and to conduct the first series of meta-analyses to assess the impact of the retail food environment on obesity.

Methods We performed a systematic review and random-effects meta-analyses, focusing on geographical–statistical methods to assess the associations between food outlet availability and obesity. We searched OvidSP-Medline, Scielo, Scopus and Google Scholar databases up to January 2022. The search terms included spatial analysis, obesity and the retail food environment. Effect sizes were pooled by random-effects meta-analyses separately according to food outlet type and geographical and statistical measures.

Findings Of the 4118 retrieved papers, we included 103 studies. Density (n=52, 50%) and linear and logistic regressions (n=68, 66%) were the main measures used to assess the association of the food environment with obesity. Multilevel or autocorrelation analyses were used in 35 (34%) studies. Fast-food outlet proximity was positively and significantly associated with obesity (OR: 1.15, 95% CI: 1.02 to 1.30, p=0.02). Fresh fruit and vegetable outlet density and supermarket proximity were inversely associated with obesity (OR: 0.93, 95% CI: 0.90 to 0.96, p<0.001; OR: 0.90, 95% CI: 0.82 to 0.98, p=0.02). No significant associations were found for restaurants, convenience stores or any of the body mass index measures.

Conclusions Food outlets which sell mostly unhealthy and ultra-processed foods were associated with higher levels of obesity, while fruit and vegetable availability and supermarket accessibility, which enable healthier food access, were related to lower levels of obesity. The regulation of food outlets through zoning laws may not be enough to tackle the burden of obesity. Regulations that focus on increasing the availability of healthy food within stores and ensure overall healthy food environments require further attention.

PROSPERO registration number CRD42018111652.

• Malnutrition

Data availability statement

All data relevant to the study are included in the article or uploaded as supplementary information.

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See:  https://creativecommons.org/licenses/by/4.0/ .

https://doi.org/10.1136/bmjnph-2023-000663

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WHAT IS ALREADY KNOWN ON THIS TOPIC

The food environment is a recognised key determinant for the prevention of obesity and other diet-related non-communicable diseases (NCDs). Multiple studies have identified inconsistent findings regarding the association between elements of the retail food environment and obesity. Variability in geographical and analytical methods has been pointed out as a potential cause for these discrepancies.

WHAT THIS STUDY ADDS

This systematic literature review and meta-analyses consolidates all the evidence and effect sizes to determine which elements of the retail food environment have the greatest impact on obesity. It stratigically considers elements of the retail food environment, along with geographical and statistical methods to provide increased statistical power, accuracy, and a comprehensive summary of findings regarding the association of the food environment with obesity.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

The evidence generated from this systematic review and meta-analyses can serve as a foundational tool for policymakers and researchers in developing programmes and interventions for the prevention of obesity and other diet-related NCDs. This study offers a quantitative and visual guide for identifying the retail food environment elements that require greater focus in strategies aimed at tackling obesity.

Introduction

The retail food environment and obesity.

Obesity, a critical risk factor for non-communicable diseases (NCDs), is prevalent in countries across all income levels, including low-, middle- and high-income nations. 1 2 Its prevalence is shaped by a complex array of determinants, notably the retail food environment and advertising landscapes. 3 Modern food environments are marked by the widespread availability and promotion of energy-dense, nutrient-poor foods. 4 For instance, the increase in food retailers has contributed to a significant rise in calorie availability, facilitating greater access to a wide array of food choices. 5 To combat structural overconsumption and curb the obesity epidemic, policy interventions must be enacted, even in the face of commercial interests. However, the specific influence of food environments on obesity, as distinct from individual behaviour, remains poorly defined. 6 7 There is a scarcity of evidence identifying the exact elements of food environments that contribute to obesity and could be targeted for change. 3 4 8 This review aims to enhance understanding of the analytical methods required to dissect the various components of the modern retail food environment in relation to obesity and to assess the impact of retail food environments on obesity levels.

Analysing the retail food environment

Spatial analysis, leveraging Geographic Information Systems (GIS), has become instrumental in exploring the interplay between the environment and health outcomes. It particularly aids in investigating the food environment by mapping the locations of food stores, examining their spatial distribution and assessing their impact on obesity and population health. This approach enables the study of how the proximity and density of food outlets relative to residential areas influence access to healthy versus unhealthy food options, thereby identifying key environmental factors and protective measures against obesity through spatial patterns. 9–12

Previous literature reviews

Previous literature reviews on the relationship between the retail food environment and obesity have underscored methodological issues that may affect the analysis and interpretation of how food environments influence health and dietary outcomes. There is a recognised need for precise, comprehensive evaluations, including standardised and validated measurement techniques and diverse approaches to assessing the retail food environment, as current methods exhibit considerable variability. 12–14 Essential aspects of retail food environment research involve confirming the location and type of food outlets through store audits (ground truthing), 13 considering the confounding effects of socioeconomic status 14 15 and using longitudinal studies to observe changes in the retail food environment and dietary choices over time. 15 16

Despite numerous studies investigating the retail food environment’s impact on obesity, systematic reviews and meta-analyses are scarce. 17–20 Previous analyses have often been restricted to specific regions or populations, with limited attention to the methodologies for measuring the retail food environment. 17–20 This paper undertakes a systematic review and meta-analyses to synthesise available evidence on the retail food environment’s role in obesity and diet-related NCDs, aiming to pinpoint elements that could be targeted by policy interventions. Furthermore, it critically assesses the methodological strategies used to study the global impact of the retail food environment on obesity.

Obesity and the food environment

The food environment encompasses physical, economic, political and sociocultural factors affecting dietary choices. 21 Glanz et al. ’s 22 model suggests that dietary intake is shaped by policy, environment, individual and behavioural factors. This includes the community nutrition environment (types of food stores, locations, and availability), which in this study we refer to as the 'retail food environment'; organisational settings (neighbourhood, school, workplace); and consumer aspects (food availability, placement, pricing, promotions, nutrition labelling). Key attributes defining the food environment are geographical access, availability, affordability and advertising. 23–25 While various factors contribute to obesity, environmental and policy measures can significantly improve the food environment, leading to widespread dietary changes and reduced obesity and disease rates. 26

We performed a systematic review and meta-analyses to assess the association of the retail food environment with adult obesity and to evaluate the geographical and statistical methods used. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed ( online supplemental figure S1 ). Search results were screened by two reviewers for eligibility. The review was registered in PROSPERO as CRD42018111652.

Supplemental material

Literature search strategy.

We conducted a literature search on 31 January 2022, spanning papers published from 1946 onwards, to identify studies focusing on the impact of the retail food environment on obesity through spatial analysis. Using OvidSP-Medline, Scopus and Google Scholar databases, we structured the search around three primary themes: the retail food environment, obesity and spatial analysis. Initially, each theme was explored individually, and subsequently, we employed the ‘AND’ operator to search them concurrently. Using the Population, Intervention, Control, Outcome (PICO) framework ( online supplemental table S1 ) for eligibility assessment, 27 we considered publications examining the influence of the retail food environment on adult obesity or body mass index (BMI) for inclusion in our systematic literature review and meta-analyses.

Our literature search strategy involved MeSH words, Boolean search terms and proximity searching characters ($, *, W, #) on Medline (OvidSP, 1946–current: 31 January 2022). The terms covered diverse aspects such as buffer, chain, convenience, density variations (denoted by densit*), desert, distance, eating habits (indicated by eat$), environmental factors, farmers’ markets, fast food, geography, geolocation, geospatial analysis, GIS (geographic information systems), global, grocery stores, increase, index, location, markets, access, provision, proximity, restaurants, retail, spatial considerations, stores, supermarkets, supply, BMI (body mass index), body mass, nutrition, obesity, overweight, positional factors, weight gain and overeating. Additionally, the search extended to Scopus and Google Scholar using the query “(ALL (obesity) AND ALL (food environment OR convenience store OR food retail) AND ALL (GIS OR spatial analysis OR geographic information systems))” as of 31 January 2022.

Risk of bias and quality assessment criteria

Risk of bias and quality were evaluated using a weighted quality score derived from the Cochrane risk-of-bias tool, the systematic review data collection procedures from The Guide to Community Preventive Services 28 and the food environment quality assessment by Williams et al . 29 Nine criteria were assessed: population representativeness, outcome validity, exposure representativeness, exposure source, retail food environment assessment method, physical activity assessment, study design, statistical methods and data temporality. Studies received one point for each criterion met ( online supplemental table S2 ).

Spatial and statistical methods and study design appraisal

Study design, statistical methods and models were explored and assessed according to their consideration of spatial clustering, 30 and according to their inclusion of confounders.

Meta-analysis

We performed random-effect meta-analyses to explore the link between the retail food environment and obesity, analysing data from various outlets including fast-food restaurants, convenience stores, supermarkets and farmers’ markets. We evaluated the retail food environment using density, proximity and the Retail Food Environment Index (RFEI)—the ratio of unhealthy to healthy food outlets. Our analyses focused on ORs for categorical outcomes and beta-coefficients (β) for continuous variables, combining similar measures for meta-analyses. We assessed the impact of the retail food environment on adult BMI (β) and obesity prevalence (ORs), selecting the most relevant estimate from studies providing multiple results to ensure observations remained independent. Only models adjusted for confounders were included. For comparability, we considered data within 1 mile buffers or equivalent, representing walkable distances. In longitudinal studies, the most recent data were used. When results were stratified by sex and socioeconomic position (SEP), we chose observations based on the largest sample size or prioritised women and low-income groups if sizes were equal. We reported effect sizes and 95% CIs for each study, using Stata V.16.0 for all statistical analyses. 31

We retrieved 4118 studies, and after applying inclusion and exclusion criteria, retained 103 articles yielding 526 data points ( online supplemental figure S1 ). These were categorised by statistical measure, geographical measure and food outlet type, with 437 data points used in meta-analyses and meta-regression. The analysis covered 16 countries, with 90% of the studies from high-income countries: 1 from Africa, 5 each from Asia, Latin America and Australia, 14 from Europe and 74 from North America, spanning from 2004 to 2021, predominantly between 2011 and 2017 (n=54, 52%) ( online supplemental table S3 ).

In terms of retail food environment measures, 52 (50%) studies evaluated density, 21 (20%) proximity, 3 (3%) both, 4 (4%) the RFEI or variants and 15 (15%) other measures like ratio and diversity. Most studies (n=77, 75%) assessed one geographical measure, 20 (19%) evaluated two and six (6%) assessed up to three. From the 526 data points that were extracted from all studies, fast-food outlets were the most examined (n=166, 32%), followed by supermarkets (n=102, 19%), restaurants (n=101, 19%) and convenience stores (n=61, 12%), fresh fruit and vegetable stores (n=17, 3%), grocery stores (n=14, 3%), specialty stores (n=8, 2%), supercentres (n=5, 1%), and farmers’ markets (n=4, 1%). A majority of the studies, 61% (n=63), accounted for walkability or physical activity as a confounder ( online supplemental table S4 ).

Associations varied by geographical area, underscoring the need for representative geographical selection. For example, Fan et al 32 found different associations between restaurants and obesity for men at the census tract level and for women at the block level. However, 64% (n=66) of studies did not perform ground truthing or verify retail food environment data ( online supplemental table S4 ).

Statistical and geographical methods

Of the studies analysed, 68 (66%) applied linear or logistic regression, while 35 (34%) used multilevel modelling or methods accounting for spatial factors and clustering ( online supplemental table S3 ). In terms of data sources for food outlet locations, 39 (38%) used government databases, 27 (26%) commercial databases, 14 (14%) conducted ground truthing, 23 (22%) employed various methods and 1 (1%) did not disclose their source. Among the studies employing multilevel modelling or spatial considerations, 26 (74%) identified positive correlations between the presence of food retailers selling foods high in fat, sugar and salt (HFSS) and obesity rates ( online supplemental table S3 ).

Study design

Of the 89 cross-sectional studies analysed, 59 (66%) discovered a correlation between obesity and food retailers specialising in unhealthy foods and beverages, such as convenience stores and fast-food outlets. Among the 14 longitudinal studies, half revealed a significant link between the presence of unhealthy food outlets and obesity (refer to online supplemental tables S3 and S4 for detailed findings).

Quality and bias assessment of studies

The mean quality score of the studies was low, at 4 out of 9 points, with the highest being 7. 33 34 Key limitations included the reliance on cross-sectional designs, the failure to account for clustering or to apply spatial methods in 30 (29%) studies, reliance on self-reported height and weight data in 34 (33%) studies and the use of inappropriate statistical methods in 43 (42%) studies ( online supplemental table S5 ). Studies deemed to have a high risk of bias were excluded from the meta-analyses.

In the meta-analyses conducted, significant heterogeneity was observed across the studies, stemming from variations in statistical methods, study designs, stratification by gender and ethnicity, geographical measures of the retail food environment, classifications of food outlets and the definitions used to measure or define obesity, thereby limiting the robustness of the pooled analyses. Despite these variances, the majority of the studies used BMI, derived from measured height and weight, as a primary indicator, reporting it either as a continuous variable (kg/m 2 ) or in categorical terms (overweight or obesity). However, there was a notable scarcity of studies disaggregating outcome data by critical demographic factors such as age group, gender, ethnicity or SEP, which is pivotal considering the diverse exposure to retail food environments experienced by these groups. 35 Results of the meta-analyses are presented below by measure of the retail food environment (ie, density and proximity) and statistical measures (ORs and Beta-coefficients─in the supplemental material).

The findings revealed that the density of fast-food outlets did not significantly influence obesity rates (OR: 1.01, 95% CI: 0.99 to 1.04, p=0.18), in contrast to proximity to fast-food outlets, which showed a significant association with obesity (OR: 1.15, 95% CI: 1.02 to 1.30, p=0.02) ( figure 1 ). Restaurant density’s correlation with obesity was marginally significant (OR: 0.92, 95% CI: 0.85 to 1.00, p=0.05), yet the literature lacked sufficient data to evaluate the impact of restaurant proximity ( figure 2 ). No significant relationship was identified between the density of convenience stores and obesity (OR: 1.02, 95% CI: 0.95 to 1.10, p=0.64), and a similar non-significant trend was observed for proximity to convenience stores (OR: 1.04, 95% CI: 0.97 to 1.11, p=0.31) ( figure 3 ).

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Fast-food outlet density and proximity and its association with obesity. REML, Restricted Maximum Likelihood.

Restaurant density and its association with obesity. REML, Restricted Maximum Likelihood.

Convenience store density and proximity and its association with obesity. REML, Restricted Maximum Likelihood.

Furthermore, supermarket density did not show a significant relationship with obesity (OR: 0.98, 95% CI: 0.92 to 1.05, p=0.53), whereas a significant inverse relationship was evident between supermarket proximity and obesity (OR: 0.90, 95% CI: 0.82 to 0.98, p=0.02) ( figure 4 ). An inverse association was also noted between the density of fresh fruit and vegetable stores and obesity (OR: 0.93, 95% CI: 0.90 to 0.96, p<0.001) ( figure 5 ), though data were insufficient to assess the impact of proximity to these outlets. The RFEI did not reveal any significant associations with obesity (OR: 1.00, 95% CI: 0.99 to 1.01, p=0.99) ( figure 6 ), and BMI as a continuous variable showed no association with any type of food outlet, indicating a nuanced and complex relationship between the retail food environment and obesity ( online supplemental figures S2–S7 ).

Supermarket density and proximity and its association with obesity. REML, Restricted Maximum Likelihood.

Fruit and vegetable store density and its association with obesity. REML, Restricted Maximum Likelihood.

Retail Food Environment Index (RFEI) and its association with obesity. REML, Restricted Maximum Likelihood.

The results of our systematic review and meta-analyses indicate a nuanced relationship between the retail food environment and obesity. Results for the association between the retail food environment and obesity varied significantly by type of food outlet, statistical measure and geographical measure. However, the pooled effect sizes show that proximity of fast-food outlets was associated with a higher risk of obesity, while proximity of supermarkets and fresh fruit and vegetable stores was associated with a lower risk of obesity.

Previous research highlights the crucial role of fruit and vegetable availability and affordability in fostering healthy eating habits and preventing obesity and chronic diseases. 36 Conversely, fast-food outlets predominantly offer ultra-processed foods—industrially processed items rich in fat, salt and/or sugar—whose consumption is associated with increased risks of obesity and chronic conditions. 37

The observed phenomenon can be attributed to the ease of access to different types of food outlets and their impact on dietary choices. Fast-food outlets, often closer to residential areas or on the pathways from school or the office to home, provide convenient access to high-calorie, processed foods, which can contribute to higher obesity rates among nearby residents. 14 Conversely, supermarkets, which are sometimes located further from residential areas, offer a broader range of healthier food options. When supermarkets are closer, it encourages the purchase and consumption of healthier foods, potentially reducing obesity risk. 38 This highlights the significant role of the retail food environment accessibility in influencing dietary behaviours and obesity prevalence.

In addition, socioeconomic area level may play a critical role in this context by influencing both access to and choices within the retail food environment. 39 Individuals living in lower socioeconomic areas may have more limited access to supermarkets offering a variety of healthy options due to cost or proximity, leading to a reliance on closer, often less expensive fast-food outlets. 39 This disparity can result in dietary patterns that contribute to higher obesity rates in these populations, underscoring the need for targeted interventions to improve access to healthy food options across all socioeconomic groups.

Importantly, while geographical measures such as proximity and density provide insights into the retail food environment or built food environment, they do not capture the complexities within food outlets that influence consumer choices. The 'in-store food environment', encompassing product placement, promotion strategies and food layout, plays a pivotal role in shaping dietary habits. Studies have demonstrated that strategic placement of healthy food options at eye level or in prominent store locations can significantly influence consumer purchases towards healthier choices. 40–43

A comprehensive approach, addressing both the proximity of various food outlet types and the intricate details of the in-store food environment, is essential for devising effective public health interventions aimed at reducing obesity. Future research and policy efforts should consider these dimensions of the food environment to develop more nuanced and impactful strategies for obesity prevention.

The UK is a pioneer in regulating the food environment, having introduced legislation to restrict the promotion and placement of HFSS foods within retail settings, both online and physical. 44 This legislation targets the influence of food retailers on consumer choices, particularly aiming to reduce the impact of price promotions on children’s food preferences by limiting promotions and strategic placement of HFSS products. This is a crucial step in promoting healthier eating habits and combating obesity and related health issues.

Additionally, in high-income countries, zoning powers allow local authorities to regulate food outlets’ location, and healthy food carts have been effectively deployed in urban areas to increase access to nutritious food. 18

Studies on the food environment can inform the creation of improved land use and public health policies, mitigating the negative effects of local food and nutrition environments on population health 45 Effective obesity reduction efforts should include policies or regulations to limit the availability of low-quality food in neighbourhoods, schools and other sensitive areas. However, the relationship between food outlets and obesity has shown inconsistent results, underscoring the need for solid evidence to guide government actions on enhancing the food environment.

This research significantly advances the evidence 18–20 by integrating a systematic review with meta-analyses to explore the retail food environment’s influence on obesity and BMI. This dual approach, not previously used for this topic, integrates geographical and statistical analyses and offers a comprehensive analysis of the relationship between food outlet types, BMI and obesity. Furthermore, this study is distinct as it includes analyses that employ spatial methodologies to explore the retail food environment’s components and their correlation with obesity, providing a comprehensive evidence base for policy formulation aimed at enhancing public health.

Implications for policymakers and urban planners

The observed association between fast-food outlet proximity and increased obesity risk emphasises the need for zoning regulations to manage their density in residential areas, schools and communal spaces. This strategic intervention becomes crucial in mitigating the obesity crisis. Our study discerns variations in associations among different food outlet types. While proximity of fast-food outlets correlates positively with obesity, proximity of supermarkets and fresh produce stores demonstrates an inverse relationship. Urban planners can influence health outcomes by strategically placing health-promoting outlets in residential areas, aligning with the concept of fostering a ‘healthy food environment’.

Beyond reaffirming existing knowledge, our study introduces novel insights into nuanced relationships between specific food outlets and obesity risk. Policymakers and urban planners can leverage this information to refine existing zoning laws based on prevalent food outlet types.

Our analysis also reveals a gap in the assessment of in-store food environments. Policymakers should focus on internal dynamics, implementing regulations targeting the arrangement and promotion of food items within stores to encourage healthier choices. Moreover, they should engage with town planners, health professionals and community representatives to develop comprehensive strategies. Collaborative efforts can lead to urban spaces that limit the impact of detrimental food outlets and food choices while promoting health and well-being. This aligns with the broader goal of fostering healthier communities, emphasising the importance of continued research and dialogue between academia and policymakers.

Strengths and limitations

This study’s primary strength lies in its comprehensive systematic search strategy, which involved querying multiple databases, imposing no publication date restrictions and conducting searches in two languages. Additionally, it uniquely explored and assessed geographical measures and statistical methods within a systematic literature review context and conducted a risk-of-bias assessment to objectively evaluate the reviewed literature.

By incorporating spatial analysis, this study addressed gaps in previous literature by elucidating the impact of food outlets’ geographical distribution on obesity rates. This approach enabled the identification of spatial patterns and correlations potentially overlooked in traditional epidemiological studies, thereby providing insight into the obesogenic environment.

Spatial analysis also enhanced the meta-analyses by facilitating the integration and comparison of findings from studies across different geographical scales and settings, thereby bolstering the robustness of our conclusions. This rigour in methodology supported evidence synthesis, offering a detailed overview of the retail food environment’s role in obesity.

Through a detailed spatial analysis, our study not only corroborates the significance of geographical factors in obesity prevalence but also underscores the need for targeted public health interventions. By pinpointing areas with high concentrations of unhealthy food outlets relative to healthy ones, policymakers and urban planners can devise more effective strategies aimed at improving the food environment and, subsequently, public health.

However, the study has limitations. The review focused on obesity in the adult population because of the diverse reviews already focused on children, and because of the important role that adults play in food outlet selection within a family setting. Focusing on adult populations is critical for chronic disease prevention and successful ageing. Only studies based on neighbourhood, rural or urban environments were considered. Studies that did not include an objective measure of obesity such as BMI via measured height and weight were excluded. However, many studies that used BMI and other measures of diet and obesity were considered. The identified exposures, measures and outcomes included in this study were the most reported in the literature. Although this may exclude other important obesity-related outcomes (eg, adiposity, fat mass, diet), focusing on BMI and obesity allowed a wider comparison between studies and could facilitate translation into policies and actions to regulate and improve the food environment.

Despite significant methodological diversity among the studies reviewed, the literature consistently identifies the food environment as a crucial factor in preventing obesity. Regions characterised by abundant fast-food outlets, limited supermarket access and scarce fresh fruit and vegetable stores tend to have higher obesity rates. While regulating access to healthier food options is necessary, it may not suffice to combat obesity on its own. Comprehensive strategies are also needed, including regulation of the in-store availability of unhealthy foods and the promotion of a food environment that supports healthy and affordable diets.

Ethics statements

Patient consent for publication.

Not applicable.

Ethics approval

Acknowledgments.

The authors wish to acknowledge Dr Clare Llewelyn and Professor Eric Brunner for their guidance and support on this study.

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Supplementary materials

Supplementary data.

This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

• Data supplement 1

X @elisap_ana

Contributors EP designed the study, collected and analysed the data, drafted the manuscript, and was responsible for the overall content as the guarantor. JS, SS, CL and JSM drafted and revised the draft and provided statistical advice.

Funding This study was funded by CONACYT, the National Council on Science and Technology in Mexico.

Competing interests None declared.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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Why the war on childhood obesity is failing

Sugar taxes and obesity drugs will not be enough.

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S UZIE JIMENEZ cried as she waited in the car park. Her 14-year-old son was in the emergency department, suffering from stomach pains. He felt humiliated when doctors in Austin, Texas, told him that because of his bigger body he would need to have a CT scan rather than an ultrasound. He was scared to tell them he weighed 360 pounds (163kg). A shortage of Wegovy had meant that despite being approved for the weight-loss drug, he had not yet been able to start it. Ms Jimenez, at times the sole breadwinner for her family of five, says they sometimes ate fast food for “comfort”.

Obesity is one of the world’s most serious public-health crises. It increases the risks of developing diabetes, heart disease, stroke and some cancers. Since 1990 global rates have doubled among adults and quadrupled among children. Today more than 1bn people, including 7% of girls and 9% of boys, are classified as obese (see chart). In 2019 it led to around 5m deaths, 20 times as many as malnutrition did. Obesity is no longer just a rich-world problem. Childhood rates are highest on the islands of the Pacific and the Caribbean, and rising fastest in developing countries such as Cambodia and Lesotho.

Most of the economic costs of obesity are borne by individuals, who take more time off work or miss more days of school, and are more likely to be low-paid or unemployed. Obese children are more often targets for bullies, too. But the burden on the state is also considerable. Last year the Institute for Fiscal Studies, a British think-tank, estimated the annual costs of overweight and obese adults through health-care expenditures, formal social care and inactivity at work, excluding those individual costs (which most studies do not). Even after discounting the grisly “savings” from related deaths, they amounted to about £32bn ($41bn), or 1% of Britain’s GDP .

Although telling adults what to eat and when to move can be seen as interfering, governments should try to prevent children becoming obese and encourage their weight-loss efforts. Early interventions could reap benefits later: children with obesity are five times more likely to be obese as adults than their slimmer peers. The trouble is, nobody knows how best to go about it. No country has ever managed to reduce obesity; the more successful ones have merely stemmed it. The problem is too complex to be solved by simple public-health measures or obesity drugs alone. The hunt is on to find evidence for interventions that work together, and quickly.

Behind rising obesity rates lies a mix of biological, economic and social factors. Much of the world is awash with highcalorie foods even as many people live sedentary lives. No single nutrient or food group is to blame, but items containing high proportions of refined wheat, sugar and vegetable oils are under the spotlight. Highly processed foods, which are widely accessible and relatively inexpensive, are the ultimate example.

At the same time, even in rich countries, many neighbourhoods lack fresh, healthy alternatives. In Texas the Department of Agriculture estimates that one in five people live in poor areas with limited access to nutritious foods. Children from such places are more likely to be obese than those from richer ones. Processed foods are convenient, take much less time to prepare and—calorie for calorie—work out cheaper, explains Samir Softic, a specialist in fatty-liver disease at Kentucky Children’s Hospital. His state has the second-highest rate of childhood obesity in America after West Virginia. It also has the second-highest number of fast-food outlets per person.

The evolution of the human body is another important factor. Losing weight is not simply a matter of reducing one’s calorie consumption. The body adapted to survive famines, not feasts, so it clings onto weight it gains. It then resists the loss of fat by reducing the amount of energy it needs to survive and by increasing hunger signals; it will fight to regain the lost weight for years. This is why most long-term efforts at significant weight loss fail.

Keeping track of trends is difficult. Body-mass index ( BMI ), which divides a person’s weight (in kilograms) by the square of their height (in metres), is fine as a common measure of obesity for most adults but inaccurate for brawny types, since it cannot distinguish between fat and muscle. It is not helpful in children, whose bodies are growing and changing. Boffins from the World Health Organisation consider a child obese if his or her BMI is more than two standard deviations above the median for their age using a model from 2007 as a reference—an imperfect measure. Experts also consider increases in associated childhood diseases. Globally, the age-standardised incidence rate of type-2 diabetes has jumped by 57% in 15- to 19-year-olds over the past 30 years.

Governments looking to cut childhood obesity have few models to draw on. Start in Amsterdam, which once seemed to have a smart strategy. The Dutch capital received international plaudits when rates of overweight and obese children fell from 21% to 18.5% between 2012 and 2015. The local government sought to change individual behaviour: it provided nutrition classes for parents and children in poor neighbourhoods, put children on care plans, offered free sports such as ice-skating and discouraged junk food in schools. But the results did not last. Rates ticked up slightly to 18.7% in 2017; then the municipality stopped publishing them.

Then there is Chile, where over half of 4- to 14-year-olds are overweight or obese. In 2016 the government slapped black warning labels, shaped like stop signs, on the front of packaged foods high in calories, sugar, saturated fat and salt. Eight other countries have since copied the move. Chile also introduced strict bans on the marketing of these foods to under-14s, and a programme of exercise and nutrition in schools. Despite all this, a study published this year in the Pan-American Journal of Public Health showed no change in prevalence rates in the three years after the legislation was enacted. (Professor Camila Corvalán, an adviser to the Chilean government on the scheme, cautions that it is too early to draw conclusions.)

Now consider Britain, which has experimented with a sugar tax of sorts. Its levy on sugar-sweetened drinks, implemented in 2018, has had mixed success. Big brands reformulated their products to avoid it, resulting in a drop in sugar consumption of 4.8g per day among children. Researchers at the University of Cambridge found a slight reduction in obesity rates among 10- to 11-year-old girls, though not in younger children or 10- to 11-year-old boys, who consume more of the beverages.

Selective taxes “can sometimes not give you the right outcomes”, argues Chris Hogg, global head of public affairs at Nestlé, the world’s largest food and drink company. For the best public-health outcomes, he reckons, it is better to have room for policies and guidance “to steer [the industry] in the direction that policymakers think makes most sense”. Such guidance has long been standard practice in places such as Britain. The drinks levy aside, all other industry measures to reduce childhood obesity in Britain have been voluntary and largely unsuccessful.

So what to try next? Most health professionals and policymakers argue that current measures do not go far enough. Public-health experts are trying to pull together a guide to sugar taxes. In the 70-odd countries where taxes on sweetened drinks have been tried, the biggest impacts were felt in poorer countries such as South Africa, where consumers are more sensitive to price changes. Some now want to broaden taxes to stop people shifting to other unhealthy products. Last year Danone, a big dairy company, called for a wider tax on foods that are high in fat, salt and sugar, arguing that regulation is the only way to get firms to make their products healthier.

Critics of sugar taxes and their ilk say they are regressive. Because the poor spend a higher share of their income on food, and so are more likely to buy cheap, highly processed items, they are also more likely to be hit by additional levies on them. To offset this, Barry Popkin of the University of North Carolina is working with countries in Latin America and Africa to develop subsidy regimes for fruit and vegetables. He reckons that warning labels with pictures on junk food, like the ones on cigarette packets, will be tried next.

Obesity drugs are another tool attracting attention. The market for GLP-1 medications such as Wegovy is expected to reach $100bn a year by 2030. But they cannot be the main solution for the world’s obese people: they cost too much. Jonathan Gruber, an American economist, reckons that buying them for the 40% of Americans with obesity would cost about $1trn a year, or roughly 4% of America’s GDP .

The price will probably drop eventually. But even then, many adults and youngsters will not want to take GLP-1 drugs. They cause side-effects such as nausea; one study found that after one year, just 32% of patients were still taking them. There are also growing concerns over rare side-effects such as pancreatitis and intestinal obstructions. Yet sustained use of these drugs is needed to keep the weight off, along with diet and lifestyle changes to maximise health.

Measured approach

Where else is there to turn? Japan offers a glimpse of how influential cultural mores can be. “As a whole, Japanese people are very health-conscious,” says Yokote Koutaro of the Japan Society for the Study of Obesity. Japanese diets have become more Westernised over the years, but people still eat traditional food, which tends to be fresh and is often relatively healthy. They also eat modest portions. Take McDonald’s, says Mr Yokote. If you order a large-size drink in Japan, you slurp less than if you ordered a “small” one in America.

Social norms and government nudges seem to be working. Japan lacks strict rules on labelling or advertising fatty foods. But its cities are walkable, and even convenience stores often stock nutritious options such as salads. The government has long required schools to serve balanced lunches. Its other interventions are sometimes intolerably nannyish: in 2008 it told companies to start measuring the waistlines of their employees.

There will be no single solution to fighting obesity in children. Taxes, regulation and obesity drugs will play a part, as will consumers. Governments need to evaluate interventions over the long term. The goal should be to ensure that making healthy choices is far easier than the alternative. The problem is getting there. ■

This article appeared in the International section of the print edition under the headline “Tipping the balance”

From the August 10th 2024 edition

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Understanding the Relationship Between Obesity and Osteoporosis

Obesity and bone health, obesity causes, osteoporosis causes, frequently asked questions.

Researchers are not exactly sure how obesity affects bone density, but recent studies have suggested that obesity and osteoporosis might be connected.

While obesity has been thought of in the past as protecting against osteoporosis, nearly 30% of people with osteoporosis are overweight or have obesity . People with obesity who also have osteoporosis might be more prone to fractures from low-impact movements.

While the findings from studies on obesity and osteoporosis have been inconsistent, researchers are looking at a possible link between the two that could lead to obesity becoming another factor that drives the onset of this type of bone disease .

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The long-held notion that carrying more weight means that a person has stronger bones is slowly being disproven. Recent reviews on the literature exploring obesity and bone health have found that several factors are at play when someone is carrying extra weight and what that means for their ability to maintain proper bone health.

A person’s body weight, fat volume, the formation and breakdown of bones, fat in bone marrow , and inflammation caused by immune cells (pro-inflammatory cytokines) are factors that need to be taken into account to address the connection between bone health and obesity.

Types of Fat

There are three types of fat: brown, white, and beige.

• Brown fat, or “good fat,” helps the body with temperature regulation.
• White fat accumulates in the body and can contribute to health conditions.
• Beige fat cells come from white fat and are typically found near the spine and collarbone.

Beige and brown fat can burn fat, while white fat stores it.

One research paper examined the effects that molecules produced by body fat (adipokines) have on bone cells. The paper also looked at the relationship between the continuous cycle of bone growth and breakdown (bone metabolism), white fat in bone marrow, and brown fat (the type of fat that converts food into body heat).

The findings showed a connection between obesity and bone metabolism; however, it’s not yet entirely clear what it is. What is known is that fat tissue interacts with bones by releasing certain cytokines in an attempt to regulate the health of the bones.

Bone marrow fat tissue also plays an important role in bone density and structure. The paper further found that because obesity is often correlated with nutrition imbalances (such as a lack of vitamin D, calcium, or phosphorous), it is hard to determine exactly why obesity impacts bone health.

Misconceptions

It has been a widely accepted notion that only frail, older adults develop osteoporosis; however, many factors contribute to the risk and onset of the disease.

Older adults (especially women) are at a high risk of osteoporosis, but recent research on obesity and osteoporosis has found that being frail is not necessarily a prerequisite for this type of bone disease.

Childhood Obesity

Decades of research on the connection between bone health and childhood obesity have found that it is a complex relationship.

Roughly 25% of a person’s bone mass is accrued during childhood. Studies have shown that because of how obesity affects bone mass as children grow, childhood obesity could increase both their risk for fractures as they get older as well as the development of osteoporosis.

Bone mass is thought to be reduced in children with obesity—a fact that’s contradictory to the previously held notion that larger children had higher bone mineral density.

It has also been found that if a child has a lower bone mass as they are growing, they will also have lower bone mass into adulthood, which could put them at a higher risk for osteoporosis in the future.

How Common Is Childhood Obesity?

According to the Centers for Disease Control and Prevention, roughly 14.4 million American children and adolescents have obesity—roughly 19.3% of the age group’s population in the United States.

The most basic cause of obesity is taking in more calories than your body needs—be it by eating more than your body needs for energy or not participating in enough physical activity to burn the excess calories.

However, many factors can contribute to the development of obesity, including:

• Smoking or using other substances
• Certain medical conditions or medications (e.g., polycystic ovary syndrome , antidepressants)
• Genetic response to changes in a person’s environment
• Food marketing and promotion where a person lives
• Lack of education on proper nutrition
• Lack of skills for preparing nutritious meals
• Community factors (e.g., lack of sidewalks or safe bike trails that may prevent safe walking)
• Societal factors or limitations (e.g., lack of supportive information on health-promoting habits and practices)

The causes of osteoporosis and obesity share some similarities. Smoking, lack of sufficient weight-bearing exercise, aging, diet, as well as certain medical conditions and medications can increase the risk for both osteoporosis and obesity.

There are also a few other known risk factors for osteoporosis:

• Low levels of estrogen
• Lack of vitamin D and calcium in the diet
• Sedentary lifestyle

Obesity and Osteoporosis Treatment 

Weight loss can be difficult, especially if a person has factors that affect their weight (like certain medical conditions or medications) or they have not been given the tools and support that they need.

Still, losing weight is often an important component, not just of managing or treating certain health conditions, but preventing them as well.

Lifestyle Changes

Safe and effective weight loss can be achieved by making a commitment to lifestyle changes that support a healthier weight. Often, these changes are small but still have an impact. Some lifestyle modifications that you can make as you work on losing weight include:

• Set small, realistic goals: If you have over 100 pounds to lose, making a plan might feel daunting or even impossible. However, making small goals for yourself (such as losing 10 pounds at a time) can help you stay motivated throughout the process.
• Choose a nutritious diet: Research shows that there is no one diet that is superior for weight loss. You have to pick the right diet for you. Options include low-calorie, low-carb, low-fat, high-fat, high-protein, or Mediterranean diets, or intermittent fasting. Generally, the best diet is the one you will stick to.
• Exercise more: Any exercise is better than no exercise at all. Research has shown that the best exercise for weight loss burns a lot of calories and is easy to stick with long term (which will be easier if you pick something you like doing). Examples of exercises that you might want to try include endurance training, high-intensity interval training, and weight or resistance training.

Safe Exercises

If you have obesity, osteoporosis, or both, getting regular physical activity can be beneficial, but there are some steps you will want to take to make sure that you are exercising safely with these conditions.

Exercising With Osteoporosis

Exercising when you have osteoporosis will help maintain your bone health, as well as your muscle mass. However, if you have weaker bones , there are some risks associated with certain types of exercise that can lead to a fracture.

Verywell / Jessica Olah

According to the National Osteoporosis Foundation, the following exercises are safe to do if you have osteoporosis:

• Posture exercises can help improve your posture and decrease the risk of breaking a bone in your spine.
• Strengthening exercises help strengthen the muscles around your bones.
• Balance exercises can help prevent falls.
• Functional exercises address problems you have in everyday life, such as not being able to walk up stairs.

If you find it hard to climb stairs, the National Osteoporosis Foundation suggests that you slowly introduce stairs as a basic exercise to help increase your ability.

Exercising With Obesity

People with obesity must take some precautions when they are exercising. For example, start with low-impact exercises, such as walking or swimming, to limit the stress on your body and joints.

You should ease into exercise slowly and build up to more strenuous activity over time. Examples of exercises you might want to try include:

• Water aerobics
• Stationary cycling

Talk to Your Doctor

Always speak to your doctor before starting a new exercise routine. They can help determine which exercises will be safe and the most beneficial for you.

Prescription medication for weight loss works in different ways. Some medications may cause you to feel full sooner, which leads you to eat fewer calories. Others hinder your body from absorbing the fat from the foods that you eat.

Typically, a prescription medication for weight loss is prescribed to people who have health issues related to obesity. While many people may think that taking medication to lose weight will eliminate the need for exercise and healthy eating, that is not true. The medications need to be taken to help a person live a healthier lifestyle.

Some prescription medications available to help with weight loss include:

• Orlistat: Works to reduce the amount of fat absorbed from the food you eat
• Phentermine-topiramate: A combination drug that lessens appetite
• Naltrexone-bupropion: A combination drug that helps to make you feel fuller faster
• Liraglutide: Regulates appetite
• Semaglutide: Regulates appetite
• Setmelanotide: Reduces appetite and increases metabolism

In some cases, people who need to lose weight will benefit from having surgery to help them meet their goals. However, a person must fall into the category of extreme obesity on the body mass index (BMI) scale to be considered for these procedures.

There are three main types of weight loss surgery :

• Adjustable gastric banding: During this surgery, a band filled with saltwater is placed around the upper part of the stomach. It is designed to make the stomach smaller, which helps a person consume less food.  
• Gastric sleeve: During this procedure, more than half of the stomach is removed. A sleeve or tube the size of a banana is left in the area. Similar to band surgery, this procedure shrinks the stomach to allow less food to be consumed.
• Gastric bypass: During gastric bypass surgery , the surgeon creates a smaller stomach by taking part of a person’s existing stomach and attaching it to the middle part of the small intestine. When a person eats, the food bypasses the rest of the stomach, which limits the amount of food the body digests and processes. This, in turn, reduces the calories that are absorbed.

Weight loss surgeries can be done with a large cut made in the abdomen (open) or with tools to enter the abdomen through several small cuts (laparoscopically). Laparoscopic surgery also uses cameras to help the surgeon see inside the abdomen.

Natural Treatments

Not many natural remedies are scientifically proven to help reduce weight, but a few have been investigated, including:

• Green tea: Drinking green tea (without any added sugar or milk) can help to increase the energy that your body expends and may help burn belly fat when combined with a nutritious diet and exercise regimen.
• Probiotics: Probiotics are “good” bacteria that can help improve digestive health. Research has shown that taking probiotics can help the body block the absorption of fat from the foods you eat and may help reduce your appetite.
• Mindfulness: Mindful eating is a practice where you work on being aware and present while you eat. Studies have shown that mindfulness at mealtimes can help decrease stress eating, as well as help people make more nutritious food choices and become more aware of their hunger cues.

Do Natural Remedies Really Work?

There is some clinical evidence to back up the claims that natural remedies can lead to weight loss, but they should be treated as an addition to a healthier lifestyle rather than a “cure-all” solution.

Modest weight loss may occur if you add in these natural remedies, but for long-term and lasting weight loss, you will need to implement more changes to your lifestyle and habits.

Many factors contribute to the development of osteoporosis, and to some extent, bone loss is a normal part of the aging process. However, research has shown that people with obesity tend to age faster (in fact, obesity may accelerate aging by over two years).

Combined with the recent research that suggests that obesity affects bone health, having obesity could also contribute to your risk of developing osteoporosis.

A Word From Verywell

There are ways to reduce your risk of obesity and osteoporosis, including eating a nutritious diet and getting more physically active. Talk to your doctor about the support you need to lose and maintain a weight that is most healthy for you.

Recent research has shown that obesity does have an effect on bone density. In particular, people with obesity have a lower bone density in relation to their body weight, as well as an increased risk of fractures.

Having excess body weight as a child can affect the development of bone, which can lead to an increase in bone frailty as a person ages. While there is limited research on childhood obesity and osteopenia, it is thought that there is a connection between bone density and being overweight or having obesity in childhood.

Eating a diet that is rich in the nutrients needed for strong bones (such as vitamin D and calcium) is a good place to start. Performing strength training exercises—as long as your doctor says they are safe for you—can also be helpful. Studies have shown that losing weight may help increase your bone mineral density.

Gkastaris K, Goulis DG, Potoupnis M, Anastasilakis AD, Kapetanos G. Obesity, osteoporosis and bone metabolism . J Musculoskelet Neuronal Interact . 2020;20(3):372-381

Nunes Cavalcante Castro BA, Torres Dos Reis Neto E, Szejnfeld VL, Marvulle V, de Medeiros Pinheiro M. Could obesity be considered as risk factor for non-vertebral low-impact fractures? Adv Rheumatol. 2018;58(1):42. doi:10.1186/s42358-018-0044-6

Hou J, He C, He W, Luo X, Li C. Obesity and bone health: a complex link . Front Cell Dev Biol. 2020;8:600181. doi:10.3389/fcell.2020.600181

Dimitri P. The impact of childhood obesity on skeletal health and development . J Obes Metab Syndr. 2019;28(1):4-17. doi:10.7570/jomes.2019.28.1.4

Centers for Disease Control and Prevention. Childhood obesity facts .

World Health Organization. Obesity and overweight .

Centers for Disease Control and Prevention. Adult obesity causes and consequences .

Koliaki C, Spinos T, Spinou M, Brinia M, Mitsopoulou C, Katsilambros N. Defining the optimal dietary approach for safe, effective and sustainable weight loss in overweight and obese adults . Healthcare (Basel). 2018;6(3):73. doi:10.3390/healthcare6030073

National Osteoporosis Foundation. Exercise to stay healthy .

National Institute of Diabetes and Digestive and Kidney Diseases. Prescription medications to treat overweight & obesity .

HealthLinkBC. Weight-loss surgery .

Jurgens TM, Whelan AM, Killian L, Doucette S, Kirk S, Foy E. Green tea for weight loss and weight maintenance in overweight or obese adults . Cochrane Database Syst Rev. 2012;12(12):CD008650. doi:10.1002/14651858.CD008650.pub2

Ogawa A, Kobayashi T, Sakai F, Kadooka Y, Kawasaki Y. Lactobacillus gasseri SBT2055 suppresses fatty acid release through enlargement of fat emulsion size in vitro and promotes fecal fat excretion in healthy Japanese subjects . Lipids Health Dis . 2015;14:20. doi:10.1186/s12944-015-0019-0

O'Reilly GA, Cook L, Spruijt-Metz D, Black DS. Mindfulness-based interventions for obesity-related eating behaviours: a literature review . Obes Rev. 2014;15(6):453-461. doi:10.1111/obr.12156

Fintini D, Cianfarani S, Cofini M, et al. The bones of children with obesity . Front Endocrinol (Lausanne). 2020;11:200. doi:10.3389/fendo.2020.00200

Hamilton KC, Fisher G, Roy JL, Gower BA, Hunter GR. The effects of weight loss on relative bone mineral density in premenopausal women . Obesity (Silver Spring). 2013;21(3):441-448. doi:10.1002/oby.20052

By Angelica Bottaro Bottaro has a Bachelor of Science in Psychology and an Advanced Diploma in Journalism. She is based in Canada.

More From Forbes

The unintended consequences of california’s $20 minimum wage for fast-food workers.

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(Robert Gauthier/Los Angeles Times via Getty Images)

California officials are reportedly considering a further increase to the recently implemented $20 minimum wage for fast-food workers. The California Food Council, which was established by Governor Gavin Newsom, is planning to propose an additional 3.5% raise for 2025 at their upcoming meeting in late July, according to Restaurant Business.

California’s minimum-wage law, which went into effect in April 2024, currently requires that fast-food restaurants with 60 or more locations nationwide increase their workers' pay to $20 an hour, which is $4 higher than the state’s minimum wage.

Additionally, it installed the Council, composed of industry representatives and restaurant workers, who are authorized to boost the wage annually by up to 3.5%, based on inflation. The Council also advises on health and safety standards for fast-food workers and combats issues like wage theft.

Although the bump in pay is intended to help improve the standard of living for more than half a million fast-food workers, there may be unintended consequences that could do more harm to these employees, including restaurant closures, job cuts, reduced hours and increased deployment of automation to bring down expenses.

Technologies To Replace Human Workers

There has been an increase in automation and self-service technology. Restaurants are deploying self-order kiosks, kitchen automation software and other labor-saving technologies to reduce reliance on human workers.

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A major Burger King franchisee in California confirmed plans to install kiosks at all locations in response to the $20 wage, Business Insider reported.

"We are installing kiosks in every single restaurant," Harsh Ghai, who owns 180 fast-food restaurants in California, including about 140 Burger King locations and numerous Taco Bell and Popeyes restaurants, told BI in an interview in early April.

Fast-food chains are adopting a range of AI, robotics and automation technologies across their customer-facing and back-end operations in order to reduce labor costs and address staffing shortages, while robotic kitchen assistants and software are automating more behind-the-scenes tasks.

Restaurants like McDonald's, Shake Shack, Panera Bread are deploying self-service kiosks that allow customers to place orders themselves, reducing the need for human cashiers.

The self-ordering systems offer improved precision in order-taking and tend to encourage higher spending from customers.

“Average kiosk sales see 10% higher checks than front counter sales and excellent profit flow-through,” Yum Brands CEO David Gibbs told investors last August.

The additional use of mobile apps for ordering and paying streamlines transactions and further reduces staffing needs. AI and automation are also being applied to back-office processes, like inventory management and scheduling, to increase efficiency.

Making Cuts And Reconsidering Plans

Some restaurants are cutting employee hours, having fewer workers per shift to control labor costs, while others are letting go of staff.

Michaela Mendelsohn, the CEO of Pollo West Corporation, one of the largest franchisees of California restaurant chain El Pollo Loco, who was also appointed to Newsom’s Fast Food Council, confirmed to Good Morning America in April that El Pollo Loco had to cut employee hours by 10% to reduce costs.

Moreover, Pizza Hut announced layoffs of over 1,200 delivery drivers in California due to the wage hike.

Chains, like Vitality Bowls , have streamlined menus by adding more pre-made items and eliminating labor-intensive offerings to reduce ingredient costs and prep work.

Some franchisees have reconsidered plans to open new locations in California due to the wage hike. Existing restaurants may close or pause hiring if they cannot sustain profitability with the increased labor costs.

Rubio's Coastal Grill has shut down 48 of its locations in California due to the high operational costs in the state.

"Making the decision to close a store is never an easy one," the company said in a statement. "The closings were brought about by the rising cost of doing business in California.

Higher Food Prices For Consumers

To offset the higher labor expenses, fast-food restaurants are raising menu prices for customers. According to Ghai, his restaurants usually implement annual price increases of 2% to 3%. However, in the past year, he has been forced to raise prices more significantly, between 8% and 10%.

He explained that most of this price hike is being used to offset the rising costs of food ingredients due to inflation. Ghai pointed out that these increases are not even sufficient to cover the additional labor expenses resulting from the recent minimum wage legislation.

Chipotle implemented a price increase of 6% to 7% on menu items in its approximately 500 California locations to offset the reduced profit margins resulting from the new minimum wage law.

Finding a balance between raising wages to improve the quality of life for workers and ensuring businesses remain profitable is a key challenge. The law's focus on large chains failed to take into account the impact on smaller, independent fast-food restaurants that might struggle to absorb high labor costs.

It's important to note that these are just some of the early observations. As more time passes, we'll have a clearer picture of its full impact on workers, businesses and consumers.

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Ultra-processed foods: the tobacco of the 21st century?

By Nicholas DeVito Aug. 14, 2024

A t the start of the clinic where I see patients with colorectal, stomach, pancreatic, and other gastrointestinal cancers, I remarked to a colleague, “Every new patient on my schedule is under 45.” She replied, “Three of mine are … this is too many young people with cancer.” We felt as though we were in the trenches and didn’t know where the bullets were coming from.

An estimated 40% of cancers in the United States are caused by risk factors that can be changed , including the use of tobacco products, a sedentary lifestyle , and consumption of ultra-processed food .

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While the rates of some types of cancer are declining, several gastrointestinal cancers are on the rise among people under age 50 . Even more worrisome: particularly in bile duct and stomach cancer, the rate increases with each younger generation . Unlike colon cancer, which can be detected by colonoscopy, there is currently no way to detect hidden stomach, pancreatic, or small bowel tumors, which means that prevention is the best strategy. Food can play a major role here, making one’s knowledge of ingredients, the American food system, and how what they eat affects their body critical for decreasing cancer incidence.

Dietary drivers of cancer have long been a topic of study . Although consumption of foods containing nitrate or nitrite preservatives, smoked or charred foods, and red meat have clear associations with cancer risk, the data are murky in other areas.

Related: Meet the billionaire media mogul who’s taking on the food industry

Ultra-processed food, including prepared meals, packaged snacks, soda, cereals, and a host of other items, has emerged as a potential cause for gastrointestinal cancers. Ultra-processed foods represent up to nearly three-quarters of the food consumed by Americans , a stark contrast with what even our recent relatives ate or what people in similar countries consume now. In a recent review of meta-analyses , a diet consisting of predominantly ultra-processed foods was associated with more than 30 health conditions, including colon, rectal, and pancreatic cancers; obesity, which also substantially raises the risk of cancer; as well as heart disease, diabetes, and other metabolic conditions.

These findings represent correlations, not causation, and dietary studies are fraught with challenges. Yet there is also evidence of direct toxicity from ultra-processed foods. They commonly contain additives such as emulsifiers, stabilizers, sweeteners, and colors, which have been shown in early studies to alter the composition of the gut microbiome and the permeability of the intestinal wall, promoting chronic inflammatory diseases that can further increase cancer risk.

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When tobacco use became widespread at the turn of the 20th century, rates of lung cancer began increasing in the 1920s, and continued on a terrible upward trend until the early 1990s. Tobacco companies waged a shrewd disinformation campaign that included funding doctors’ research and promoting false studies while hiding negative evidence. After long battles, the U.S. Food and Drug Administration was allowed to regulate tobacco products in 2009 .

A similar trend is developing with ultra-processed foods, the consumption of which has increased since 2000 . A lack of regulation in the U.S. has allowed additives that are “ generally recognized as safe ” to flood the food system. This differs from the European Union, where ingredients need to demonstrate safety before consumption . Ultra-processed foods are prominently displayed on grocery store end caps and gleefully (and sometimes deceptively) advertised.

While ultra-processed foods would be harder to target with regulations than tobacco, frameworks to increase recognition of ultra-processed foods have been developed. NOVA , for example, is a system that classifies foods into four groups, based on how much processing the food has undergone. Online tools are also being developed to help identify ultra-processed foods.

Collective efforts by health care providers, public health experts, governments, and other organizations were able to markedly reduced tobacco-related deaths . I believe the same can be done for ultra-processed foods.

Physicians and other health care providers should advise their patients to minimize consumption of ultra-processed foods, as they do now for fried foods, red meat, and sugary drinks. Grocery stores, restaurants, and other food vendors can label and separate ultra-processed foods from healthy options, placing more of the latter near registers to increase demand. This is not something grocery and other stores can do on their own: Consumers’ purchasing choices will affect decisions like this.

Regulations on food additives and processing have severely lagged in the United States compared to other countries . Local and state governments have the responsibility to work to eradicate food deserts, offering affordable, healthier choices than fast and ultra-processed foods in every ZIP code. The federal government can empower the FDA to more tightly control processing and additives while funding a multi-pronged strategy to address the content and availability of food. This is no small feat, and will require consumer awareness, a semblance of corporate responsibility, and broad advocacy for change.

Related: Cancer is rising among the young. Study suggests it’s because their cells are aging faster

The desire to protect Americans from substances that cause cancer and other diseases should transcend party affiliation and political motivation to overcome industrial lobbying efforts. This was possible with tobacco, and it is possible with food. To be sure, this will require Americans to make different choices about what they eat to prioritize their health over the profit of corporations and, at times, even their own convenience. The percentage of Americans who smoke has declined from a high of 45% in the 1950s to 12% today. Concerted efforts around ultra-processed foods could have a similar effect.

I hope to have a long career in oncology and eventually practice in an era where the U.S. has turned the tide against early-onset gastrointestinal cancers and few, if any, of my patients are under age 50.

Nicholas DeVito, M.D., is an assistant professor of medical oncology in the Division of Medical Oncology at Duke University Medical Center who focuses on gastrointestinal malignancies, immunotherapy research, and is a member of the Duke Cancer Institute. The author thanks Sarah Sammons, M. D. for her insightful comments and edits on this essay.

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Have an opinion on this essay submit a letter to the editor here ., about the author reprints, nicholas devito.

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Britain’s Violent Riots: What We Know

Officials had braced for more unrest on Wednesday, but the night’s anti-immigration protests were smaller, with counterprotesters dominating the streets instead.

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By Lynsey Chutel

After days of violent rioting set off by disinformation around a deadly stabbing rampage, the authorities in Britain had been bracing for more unrest on Wednesday. But by nightfall, large-scale anti-immigration demonstrations had not materialized, and only a few arrests had been made nationwide.

Instead, streets in cities across the country were filled with thousands of antiracism protesters, including in Liverpool, where by late evening, the counterdemonstration had taken on an almost celebratory tone.

Over the weekend, the anti-immigration protests, organized by far-right groups, had devolved into violence in more than a dozen towns and cities. And with messages on social media calling for wider protests and counterprotests on Wednesday, the British authorities were on high alert.

With tensions running high, Prime Minister Keir Starmer’s cabinet held emergency meetings to discuss what has become the first crisis of his recently elected government. Some 6,000 specialist public-order police officers were mobilized nationwide to respond to any disorder, and the authorities in several cities and towns stepped up patrols.

Wednesday was not trouble-free, however.

In Bristol, the police said there was one arrest after a brick was thrown at a police vehicle and a bottle was thrown. In the southern city of Portsmouth, police officers dispersed a small group of anti-immigration protesters who had blocked a roadway. And in Belfast, Northern Ireland, where there have been at least four nights of unrest, disorder continued, and the police service said it would bring in additional officers.

But overall, many expressed relief that the fears of wide-scale violence had not been realized.

Here’s what we know about the turmoil in Britain.

Where arrests have been reported

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