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Obesity research: Moving from bench to bedside to population

Affiliation Diabetes Research Program, Department of Medicine, New York University Grossman School of Medicine, New York, New York, United States of America

Ann Marie Schmidt

Published: December 4, 2023

https://doi.org/10.1371/journal.pbio.3002448
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Globally, obesity is on the rise. Research over the past 20 years has highlighted the far-reaching multisystem complications of obesity, but a better understanding of its complex pathogenesis is needed to identify safe and lasting solutions.

Citation: Schmidt AM (2023) Obesity research: Moving from bench to bedside to population. PLoS Biol 21(12): e3002448. https://doi.org/10.1371/journal.pbio.3002448

Copyright: © 2023 Ann Marie Schmidt. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: AMS received funding from U.S. Public Health Service (grants 2P01HL131481 and P01HL146367). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The author has declared that no competing interests exist.

Abbreviations: EDC, endocrine disruptor chemical; GIP, gastric inhibitory polypeptide; GLP1, glucagon-like peptide 1; HFCS, high-fructose corn syrup

This article is part of the PLOS Biology 20th anniversary collection.

Obesity is a multifaceted disorder, affecting individuals across their life span, with increased prevalence in persons from underrepresented groups. The complexity of obesity is underscored by the multiple hypotheses proposed to pinpoint its seminal mechanisms, such as the “energy balance” hypothesis and the “carbohydrate–insulin” model. It is generally accepted that host (including genetic factors)–environment interactions have critical roles in this disease. The recently framed “fructose survival hypothesis” proposes that high-fructose corn syrup (HFCS), through reduction in the cellular content of ATP, stimulates glycolysis and reduces mitochondrial oxidative phosphorylation, processes that stimulate hunger, foraging, weight gain, and fat accumulation [ 1 ]. The marked upswing in the use of HFCS in beverages and foods, beginning in the 1980s, has coincided with the rising prevalence of obesity.

The past few decades of scientific progress have dramatically transformed our understanding of pathogenic mechanisms of obesity ( Fig 1 ). Fundamental roles for inflammation were unveiled by the discovery that tumor necrosis factor-α contributed to insulin resistance and the risk for type 2 diabetes in obesity [ 2 ]. Recent work has ascribed contributory roles for multiple immune cell types, such as monocytes/macrophages, neutrophils, T cells, B cells, dendritic cells, and mast cells, in disturbances in glucose and insulin homeostasis in obesity. In the central nervous system, microglia and their interactions with hypothalamic neurons affect food intake, energy expenditure, and insulin sensitivity. In addition to cell-specific contributions of central and peripheral immune cells in obesity, roles for interorgan communication have been described. Extracellular vesicles emitted from immune cells and from adipocytes, as examples, are potent transmitters of obesogenic species that transfer diverse cargo, including microRNAs, proteins, metabolites, lipids, and organelles (such as mitochondria) to distant organs, affecting functions such as insulin sensitivity and, strikingly, cognition, through connections to the brain [ 3 ].

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Basic, clinical/translational, and epidemiological research has made great strides in the past few decades in uncovering novel components of cell-intrinsic, intercellular, and interorgan communications that contribute to the pathogenesis of obesity. Both endogenous and exogenous (environmental) stressors contribute to the myriad of metabolic perturbations that impact energy intake and expenditure; mediate innate disturbances in the multiple cell types affected in obesity in metabolic organelles and organs, including in immune cells; and impair beneficial interkingdom interactions of the mammalian host with the gut microbiome. The past few decades have also witnessed remarkable efforts to successfully treat obesity, such as the use of the incretin agonists and bariatric surgery. Yet, these and other strategies may be accompanied by resistance to weight loss, weight regain, adverse effects of interventions, and the challenges of lifelong implementation. Hence, through leveraging novel discoveries from the bench to the bedside to the population, additional strategies to prevent obesity and weight regain post-weight loss, such as the use of “wearables,” with potential for implementation of immediate and personalized behavior modifications, may hold great promise as complementary strategies to prevent and identify lasting treatments for obesity. Figure created with BioRender.

https://doi.org/10.1371/journal.pbio.3002448.g001

Beyond intercellular communication mediated by extracellular vesicles, the discovery of interactions between the host and the gut microbiome has suggested important roles for this interkingdom axis in obesity. Although disturbances in commensal gut microbiota species and their causal links to obesity are still debated, transplantation studies have demonstrated relationships between Firmicutes/Bacteroidetes ratios and obesity [ 4 ]. Evidence supports the concept that modulation of gut microbiota phyla modulates fundamental activities, such as thermogenesis and bile acid and lipid metabolism. Furthermore, compelling discoveries during the past few decades have illustrated specific mechanisms within adipocytes that exert profound effects on organismal homeostasis, such as adipose creatine metabolism, transforming growth factor/SMAD signaling, fibrosis [ 5 ], hypoxia and angiogenesis, mitochondrial dysfunction, cellular senescence, impairments in autophagy, and modulation of the circadian rhythm. Collectively, these recent discoveries set the stage for the identification of potential new therapeutic approaches in obesity.

Although the above discoveries focus largely on perturbations in energy metabolism (energy intake and expenditure) as drivers of obesity, a recently published study suggests that revisiting the timeline of obesogenic forces in 20th and 21st century society may be required. The authors tracked 320,962 Danish schoolchildren (born during 1930 to 1976) and 205,153 Danish male military conscripts (born during 1939 to 1959). Although the overall trend of the percentiles of the distributions of body mass index were linear across the years of birth, with percentiles below the 75th being nearly stable, those above the 75th percentile demonstrated a steadily steeper rise the more extreme the percentile; this was noted in the schoolchildren and the military conscripts [ 6 ]. The authors concluded that the emergence of the obesity epidemic might have preceded the appearance of the factors typically ascribed to mediating the obesogenic transformation of society by several decades. What are these underlying factors and their yet-to-be-discovered mechanisms?

First, in terms of endogenous factors relevant to individuals, stressors such as insufficient sleep and psychosocial stress may impact substrate metabolism, circulating appetite hormones, hunger, satiety, and weight gain [ 7 ]. Reduced access to healthy foods rich in vegetables and fruits but easy access to ultraprocessed ingredients in “food deserts” and “food swamps” caused excessive caloric intake and weight gain in clinical studies [ 8 ]. Second, exogenous environmental stresses have been associated with obesity. For example, air pollution has been directly linked to adipose tissue dysfunction [ 9 ], and ubiquitous endocrine disruptor chemicals (EDCs) such as bisphenols and phthalates (found in many items of daily life including plastics, food, clothing, cosmetics, and paper) are linked to metabolic dysfunction and the development of obesity [ 10 ]. Hence, factors specific to individuals and their environment may exacerbate their predisposition to obesity.

In addition to the effects of exposure to endogenous and exogenous stressors on the risk of obesity, transgenerational (passed through generations without direct exposure of stimulant) and intergenerational (direct exposure across generations) transmission of these stressors has also been demonstrated. A leading proposed mechanism is through epigenetic modulation of the genome, which then predisposes affected offspring to exacerbated responses to obesogenic conditions such as diet. A recent study suggested that transmission of disease risk might be mediated through transfer of maternal oocyte-derived dysfunctional mitochondria from mothers with obesity [ 11 ]. Additional mechanisms imparting obesogenic “memory” may be evoked through “trained immunity.”

Strikingly, the work of the past few decades has resulted in profound triumphs in the treatment of obesity. Multiple approved glucagon-like peptide 1 (GLP1) and gastric inhibitory polypeptide (GIP) agonists [ 12 ] (alone or in combinations) induce highly significant weight loss in persons with obesity [ 13 ]. However, adverse effects of these agents, such as pancreatitis and biliary disorders, have been reported [ 14 ]. Therefore, the long-term safety and tolerability of these drugs is yet to be determined. In addition to pharmacological agents, bariatric surgery has led to significant weight loss as well. However, efforts to induce weight loss through reduction in caloric intake and increased physical activity, pharmacological approaches, and bariatric surgery may not mediate long-term cures in obesity on account of resistance to weight loss, weight regain, adverse effects of interventions, and the challenges of lifelong implementation of these measures.

Where might efforts in combating obesity lie in the next decades? At the level of basic and translational science, the heterogeneity of metabolic organs could be uncovered through state-of-the-art spatial “omics” and single-cell RNA sequencing approaches. For example, analogous to the deepening understanding of the great diversity in immune cell subsets in homeostasis and disease, adipocyte heterogeneity has also been suggested, which may reflect nuances in pathogenesis and treatment approaches. Further, approaches to bolster brown fat and thermogenesis may offer promise to combat evolutionary forces to hoard and store fat. A better understanding of which interorgan communications may drive obesity will require intensive profiling of extracellular vesicles shed from multiple metabolic organs to identify their cargo and, critically, their destinations. In the three-dimensional space, the generation of organs-on-a-chip may facilitate the discovery of intermetabolic organ communications and their perturbations in the pathogenesis of obesity and the screening of new therapies.

Looking to prevention, recent epidemiological studies suggest that efforts to tackle obesity require intervention at multiple levels. The institution of public health policies to reduce air pollution and the vast employment of EDCs in common household products could impact the obesity epidemic. Where possible, the availability of fresh, healthy foods in lieu of highly processed foods may be of benefit. At the individual level, focused attention on day-to-day behaviors may yield long-term benefit in stemming the tide of obesity. “Wearable” devices that continuously monitor the quantity, timing, and patterns of food intake, physical activity, sleep duration and quality, and glycemic variability might stimulate on-the-spot and personalized behavior modulation to contribute to the prevention of obesity or of maintenance of the weight-reduced state.

Given the involvement of experts with wide-ranging expertise in the science of obesity, from basic science, through clinical/translational research to epidemiology and public health, it is reasonable to anticipate that the work of the next 2 decades will integrate burgeoning multidisciplinary discoveries to drive improved efforts to treat and prevent obesity.

Acknowledgments

The author is grateful to Ms. Latoya Woods of the Diabetes Research Program for assistance with the preparation of the manuscript and to Ms. Kristen Dancel-Manning for preparation of the Figure accompanying the manuscript.

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Obesity as a disease: a white paper on evidence and arguments commissioned by the Council of the Obesity Society

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1 Department of Biostatistics and Clinical Nutrition Research Center, University of Alabama at Birmingham, Birmingham, Alabama, USA. [email protected]
PMID: 18464753
DOI: 10.1038/oby.2008.231

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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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Tackling unhealthy...

Tackling unhealthy food and obesity: how far will the new Labour government go?

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Peer review
Adam Briggs , senior policy fellow ,
Grace Everest , policy fellow
The Health Foundation, London, UK
Correspondence to: A Briggs: adam.briggs{at}health.org.uk .

The King’s speech confirmed Labour’s manifesto commitments to “restrict the advertising of junk food to children along with the sale of high caffeine energy drinks to children.” 1 2 It’s a welcome signal that Labour is taking childhood obesity seriously. Although it will be rightly applauded, more still needs to be done to reverse persistently high obesity rates and entrenched inequalities.

Data from the National Childhood Measurement Programme show that in 2022-23, more than one in five (21%) children aged 4-5 years and one in three (37%) children aged 10-11 years were living with either overweight or obesity. 3

Both rates are lower than in 2021-22, but they are still higher among children aged 10-11 years than before the pandemic and stark inequalities persist. Rates of obesity among 4-5 year olds living in the 10% most deprived areas in the country are 12%—twice as high as in the least deprived areas where rates are just 6%. For children aged 10-11 years the difference is even greater, with rates of 30% in the most deprived areas compared with 13% in the least. 3

Reversing long standing increases in child and adult obesity—and improving people’s diets by making it easier for everyone to access healthy food—would be hugely beneficial to the nation’s health and to society as a whole.

Children and adults with obesity are more likely to develop conditions such as diabetes, heart disease, and joint disease. In turn, these conditions are contributing to rising rates of economic inactivity among working age adults in the UK and are estimated to have cost the NHS £11bn in 2021. 4 5 As well as causing obesity, unhealthy food is associated with a number of diseases independent of weight. For example, sugar sweetened beverages are associated with risk of developing diabetes, 6 and there is growing evidence linking ultra-processed foods to a range of adverse health outcomes. 7

Restricting unhealthy food advertising and banning high caffeine drink sales are policies from the previous Conservative government that were never implemented. 8 Both will help to start tackling some of the key commercial drivers of poor diet and ill health. Indeed, the previous government’s own consultation suggested that banning junk food adverts on television after 9 pm and online could lead to around £2bn in health benefits alone. 9

The need for wider action

Obesity and consumption of unhealthy food are shaped by wider social, economic, and environmental factors. For example, people living in the 20% most deprived areas of England are over four times more likely to have limited access to green space than people living in the least deprived areas, yet have five times the density of fast food outlets. 10 11 Having limited finances may mean living somewhere where there aren’t nearby shops selling fresh food, not having a car or being able to afford public transport to access them, and not having the time to prepare and cook meals because of working multiple jobs or having caring responsibilities.

Tackling these wider factors within the food and drink sector means greater recognition of the role that food and drink corporations play in influencing individual behaviour, and bolder use of tax and regulation such as expanding the Soft Drink Industry Levy to include unhealthy food, as well as measures to restrict industry interference in policy making. 12

More specific local policies to support councils should include changes to planning law to help local authorities limit the opening of unhealthy takeaways (as promised in Labour’s Child Health Action Plan), updating national planning guidance to ensure health is given greater weight in planning decisions, and introducing new powers for local authorities to restrict junk food advertising on non-council owned billboards. 13

Taking a whole government approach

Beyond specific risk factors such as unhealthy food—and the welcome action on limiting tobacco sales—measures also need to tackle the building blocks of health such as a fair income, secure employment, and quality housing. This will need a whole government approach. 12 Legislation announced in the King’s speech to increase provision of high quality homes and improve renters’ rights are important steps in the right direction. It is also promising to see a child poverty strategy being developed to help keep families out of poverty longer term, supported by a child poverty unit. More immediately the two-child limit and benefit cap should be ended.

Local and regional authorities also have crucial roles across many of these wider social and environmental factors, yet councils have been hit by substantial cuts to their spending power alongside rising costs of delivering services. Local authority public health budgets, for example, have been cut by 28% per person in real terms since 2015-16 with funding increasingly misaligned with local needs. 14 Providing more sustainable local funding, with multi-year settlements, will be key to reversing long term declines in service provision and tackling skilled workforce shortages in areas such as trading standards, licensing, and planning.

UK life expectancy gains have stalled, the burden of preventable ill health is rising, and inequalities are widening. A mission led government presents an opportunity not just to tackle obesity, but to reverse these trends more broadly. Labour’s early intention to take direct action on childhood obesity is a positive signal, but more will be needed in the coming years to make a step change in improving the nation’s health and tackling inequalities.

Competing interests: none declared.

Provenance: Commissioned, not externally peer reviewed.

↵ Prime Minister’s Office. 10 Downing Street and His Majesty King Charles III. The King’s Speech 2024. 2024. https://www.gov.uk/government/speeches/the-kings-speech-2024
↵ Labour Party. Change: Labour Party Manifesto 2024. 2024. https://labour.org.uk/change/my-plan-for-change/
↵ NHS Digital. National Child Measurement Programme, England, 2022/23 School Year. NHS England. 2023. Available from: https://digital.nhs.uk/data-and-information/publications/statistical/national-child-measurement-programme/2022-23-school-year/age
↵ Atwell S, Vriend M, Rocks C, et al. What we know about the UK’s working-age health challenge. The Health Foundation. 2023. https://www.health.org.uk/publications/long-reads/what-we-know-about-the-uk-s-working-age-health-challenge
↵ Frontier Economics. Estimating the full costs of obesity. 2022. https://www.frontier-economics.com/uk/en/news-and-insights/news/news-article/?nodeId=20358
Imamura F ,
O’Connor L ,
↵ Everest G, Marshall L, Fraser C, Briggs A. Addressing the leading risk factors for ill health. Health Foundation. 2022. https://www.health.org.uk/publications/reports/addressing-the-leading-risk-factors-for-ill-health
↵ Department of Health and Social Care and Department for Digital. Culture, Media and Sport. Consultation outcome: further advertising restrictions for products high in fat, salt and sugar. 2019. https://www.gov.uk/government/consultations/further-advertising-restrictions-for-products-high-in-fat-salt-and-sugar
↵ Health Foundation. Inequalities in access to green space. 2024. https://www.health.org.uk/evidence-hub/our-surroundings/green-space/inequalities-in-access-to-green-space
↵ Public Health England. England’s poorest areas are fast food hotspots. 2018. https://www.gov.uk/government/news/englands-poorest-areas-are-fast-food-hotspots
↵ Marshall L, Bibby J, Briggs A. How can the next government take prevention from rhetoric to reality? The Health Foundation. 2024. https://www.health.org.uk/publications/long-reads/how-can-the-next-government-take-prevention-from-rhetoric-to-reality
↵ Dun-Campbell K, Ewbank L, Burale H, Briggs A. Addressing the leading risk factors for ill health – supporting local government to more. Health Foundation. 2024. https://www.health.org.uk/publications/reports/addressing-the-leading-risk-factors-for-ill-health-supporting-local-government-to-do-more
↵ Finch D, Gazillo A, Vriend M. Investing in the public health grant. What it is and why greater investment is needed. Health Foundation. 2024. https://www.health.org.uk/news-and-comment/charts-and-infographics/public-health-grant-what-it-is-and-why-greater-investment-is-needed

Introduction
Conclusions
Article Information

a Includes 10 individuals for whom the site enrollment closed and 1 who was lost to follow-up.

b See Table 3 and eTable 4 in Supplement 2 for the details of the adverse events that led to treatment discontinuation.

c The most common reasons for participant withdrawal included participant no longer wished to participate, participant unavailable to attend visits, participant moved out of state or country, and personal or family issues.

d Guided by the treatment regimen estimand.

Observed mean values from the full analysis set are shown. Error bars represent 95% CI for the mean. The dashed vertical line at week 36 represents the randomization point. Analysis of covariance using the full analysis set with hybrid imputation least-square mean values at week 88 is also shown on the right. See eTable 3 in Supplement 2 for corresponding data for the efficacy estimand.

Trial protocol

eAppendix 1. Eligibility criteria

eAppendix 2. Concomitant medications

eAppendix 3. Statistical analyses

eTable 1. Additional demographics and clinical characteristics (randomized population)

eTable 2. Changes during the tirzepatide lead-in treatment period (randomized population)

eTable 3. Primary and secondary end points (efficacy estimand)

eTable 4. Adverse events during the tirzepatide lead-in treatment period (week 0 to 36)

eTable 5. COVID-19-related adverse events

eTable 6. Reported deaths during the entire study

eTable 7. Additional safety measures during the double-blind period (safety analysis set)

eTable 8. Vital signs abnormalities during the double-blind period (safety analysis set)

eFigure 1. SURMOUNT-4 study design

eFigure 2. Effect of tirzepatide maximum tolerated dose (10 or 15 mg) compared with placebo on efficacy outcomes in the SURMOUNT-4 trial

eFigure 3. Cumulative distribution plot of the percent change in weight (efficacy estimand)

eFigure 4. Time, during the 52-week double-blind period (week 36 to 88 in the entire study), to first occurrence of participant returning to >95% baseline body weight if already lost ≥5% since week 0

eFigure 5. Box plot of the percent change in body weight over time during the entire study

eFigure 6. Waterfall plot of the percent change in body weight from week 0 to 88

eFigure 7. Body weight over time during the entire study

eFigure 8. Change in blood pressure over time during the entire study

eFigure 9. Incidence of nausea, vomiting, and diarrhea over time during the tirzepatide lead-in treatment period

eFigure 10. Incidence of nausea, vomiting, and diarrhea over time during the double-blind period (safety analysis set)

Statistical analysis

Nonauthor collaborators

Data sharing statement

Tirzepatide vs Insulin Lispro Added to Basal Insulin in Type 2 Diabetes JAMA Original Investigation November 7, 2023 This study examines the efficacy and safety of tirzepatide vs insulin lispro adjunctive therapy to insulin glargine among those receiving basal insulin with inadequately controlled type 2 diabetes. Julio Rosenstock, MD; Juan P. Frías, MD; Helena W. Rodbard, MD; Santiago Tofé, MD; Emmalee Sears, MS; Ruth Huh, PhD; Laura Fernández Landó, MD; Hiren Patel, MPharm
What to Know About Zepbound, the Newest Antiobesity Drug JAMA Medical News & Perspectives December 12, 2023 This Medical News article discusses the November 8 US Food and Drug Administration approval of the drug tirzepatide for chronic weight management in people with obesity or overweight with weight-related conditions. Jennifer Abbasi
Direct-to-Consumer Drug Company Pharmacies JAMA Viewpoint March 26, 2024 The recent launch of direct-to-consumer pharmacy LillyDirect prompts the author of this Viewpoint to consider why it was created and also to raise concerns about allowing manufacturers to sell their drugs directly to patients. Benjamin N. Rome, MD, MPH
Tirzepatide for Maintenance of Weight Reduction in Adults With Obesity—Reply JAMA Comment & Response May 21, 2024 Louis J. Aronne, MD; SURMOUNT-4 Investigators
Tirzepatide for Maintenance of Weight Reduction in Adults with Obesity JAMA Comment & Response May 21, 2024 Yifan Xiao, BS; Jiahao Meng, BS; Shuguang Gao, MD
Effect of Tirzepatide in Chinese Adults With Obesity JAMA Original Investigation May 31, 2024 This randomized clinical trial investigates the safety and efficacy of treatment with once-weekly tirzepatide for weight reduction in Chinese adults with overweight or obesity without diabetes over a 52-week period. Lin Zhao, MD; Zhifeng Cheng, MD; Yibing Lu, MD; Ming Liu, MD; Hong Chen, MD; Min Zhang, MD; Rui Wang, MD; Yuan Yuan, PhD; Xiaoying Li, MD

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CME & MOC

Aronne LJ , Sattar N , Horn DB, et al. Continued Treatment With Tirzepatide for Maintenance of Weight Reduction in Adults With Obesity : The SURMOUNT-4 Randomized Clinical Trial . JAMA. 2024;331(1):38–48. doi:10.1001/jama.2023.24945

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Continued Treatment With Tirzepatide for Maintenance of Weight Reduction in Adults With Obesity : The SURMOUNT-4 Randomized Clinical Trial

1 Comprehensive Weight Control Center, Division of Endocrinology, Diabetes, and Metabolism, Weill Cornell Medicine, New York, New York
2 BHF Glasgow Cardiovascular Research Centre, School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, United Kingdom
3 University of Texas Center for Obesity Medicine and Metabolic Performance, Department of Surgery, University of Texas McGovern Medical School, Houston
4 Louisville Metabolic and Atherosclerosis Research Center, Louisville, Kentucky
5 McMaster University, and Wharton Weight Management Clinic, York University, Toronto, Ontario, Canada
6 Department of Family Medicine, China Medical University Hospital, Taichung, Taiwan
7 Eli Lilly and Company, Indianapolis, Indiana
8 Eli Lilly and Company, Moscow, Russia
Original Investigation Tirzepatide vs Insulin Lispro Added to Basal Insulin in Type 2 Diabetes Julio Rosenstock, MD; Juan P. Frías, MD; Helena W. Rodbard, MD; Santiago Tofé, MD; Emmalee Sears, MS; Ruth Huh, PhD; Laura Fernández Landó, MD; Hiren Patel, MPharm JAMA
Medical News & Perspectives What to Know About Zepbound, the Newest Antiobesity Drug Jennifer Abbasi JAMA
Viewpoint Direct-to-Consumer Drug Company Pharmacies Benjamin N. Rome, MD, MPH JAMA
Comment & Response Tirzepatide for Maintenance of Weight Reduction in Adults With Obesity—Reply Louis J. Aronne, MD; SURMOUNT-4 Investigators JAMA
Comment & Response Tirzepatide for Maintenance of Weight Reduction in Adults with Obesity Yifan Xiao, BS; Jiahao Meng, BS; Shuguang Gao, MD JAMA
Original Investigation Effect of Tirzepatide in Chinese Adults With Obesity Lin Zhao, MD; Zhifeng Cheng, MD; Yibing Lu, MD; Ming Liu, MD; Hong Chen, MD; Min Zhang, MD; Rui Wang, MD; Yuan Yuan, PhD; Xiaoying Li, MD JAMA

Question Does once-weekly subcutaneous tirzepatide with diet and physical activity affect maintenance of body weight reduction in individuals with obesity or overweight?

Findings After 36 weeks of open-label maximum tolerated dose of tirzepatide (10 or 15 mg), adults (n = 670) with obesity or overweight (without diabetes) experienced a mean weight reduction of 20.9%. From randomization (at week 36), those switched to placebo experienced a 14% weight regain and those continuing tirzepatide experienced an additional 5.5% weight reduction during the 52-week double-blind period.

Meaning In participants with obesity/overweight, withdrawing tirzepatide led to substantial regain of lost weight, whereas continued treatment maintained and augmented initial weight reduction.

Importance The effect of continued treatment with tirzepatide on maintaining initial weight reduction is unknown.

Objective To assess the effect of tirzepatide, with diet and physical activity, on the maintenance of weight reduction.

Design, Setting, and Participants This phase 3, randomized withdrawal clinical trial conducted at 70 sites in 4 countries with a 36-week, open-label tirzepatide lead-in period followed by a 52-week, double-blind, placebo-controlled period included adults with a body mass index greater than or equal to 30 or greater than or equal to 27 and a weight-related complication, excluding diabetes.

Interventions Participants (n = 783) enrolled in an open-label lead-in period received once-weekly subcutaneous maximum tolerated dose (10 or 15 mg) of tirzepatide for 36 weeks. At week 36, a total of 670 participants were randomized (1:1) to continue receiving tirzepatide (n = 335) or switch to placebo (n = 335) for 52 weeks.

Main Outcomes and Measures The primary end point was the mean percent change in weight from week 36 (randomization) to week 88. Key secondary end points included the proportion of participants at week 88 who maintained at least 80% of the weight loss during the lead-in period.

Results Participants (n = 670; mean age, 48 years; 473 [71%] women; mean weight, 107.3 kg) who completed the 36-week lead-in period experienced a mean weight reduction of 20.9%. The mean percent weight change from week 36 to week 88 was −5.5% with tirzepatide vs 14.0% with placebo (difference, −19.4% [95% CI, −21.2% to −17.7%]; P < .001). Overall, 300 participants (89.5%) receiving tirzepatide at 88 weeks maintained at least 80% of the weight loss during the lead-in period compared with 16.6% receiving placebo ( P < .001). The overall mean weight reduction from week 0 to 88 was 25.3% for tirzepatide and 9.9% for placebo. The most common adverse events were mostly mild to moderate gastrointestinal events, which occurred more commonly with tirzepatide vs placebo.

Conclusions and Relevance In participants with obesity or overweight, withdrawing tirzepatide led to substantial regain of lost weight, whereas continued treatment maintained and augmented initial weight reduction.

Trial Registration ClinicalTrials.gov Identifier: NCT04660643

Obesity is a serious chronic, progressive, and relapsing disease. 1 Lifestyle interventions are a cornerstone of obesity management; however, sustaining weight reduction achieved through lifestyle-based caloric restriction is challenging.

Therefore, current guidelines recommend adjunctive antiobesity medications to promote weight reduction, facilitate weight maintenance, and improve health outcomes in people with obesity. 2 - 4 Randomized withdrawal studies of antiobesity medications to date have consistently demonstrated clinically significant body weight regain with cessation of therapy. 5 , 6 There is also evidence that antiobesity medications, including long-acting glucagon-like peptide-1 (GLP-1) receptor agonists, naltrexone/bupropion, phentermine/topiramate, and orlistat, may help maintenance of achieved weight reduction. 5 , 7 - 12

Tirzepatide is a single molecule that combines glucose-dependent insulinotropic polypeptide (GIP) and GLP-1 receptor agonism 13 resulting in synergistic effects on appetite, food intake, and metabolic function. 14 - 16 Tirzepatide is approved in many countries, including the US, EU, and Japan, as a once-weekly subcutaneous injectable for type 2 diabetes and for the treatment of obesity in the US and UK. 16 - 18 In a placebo-controlled trial of participants with obesity or overweight without diabetes, tirzepatide led to mean reductions in body weight up to 20.9% after 72 weeks of treatment. 17 , 18

The aim of the SURMOUNT-4 trial was to investigate the effect of continued treatment with the maximum tolerated dose (ie, 10 or 15 mg) of once-weekly tirzepatide, compared with placebo, on the maintenance of weight reduction following an initial open-label lead-in treatment period in participants with obesity or overweight.

SURMOUNT-4 was a phase 3 randomized withdrawal study with a 36-week, open-label tirzepatide lead-in period followed by a 52-week, double-blind, placebo-controlled period conducted at 70 sites in Argentina, Brazil, Taiwan, and the US. The trial started on March 29, 2021, and finished on May 18, 2023. The study protocol ( Supplement 1 ) was approved by the ethical review board at each site and was followed according to local regulations and the principles of the Declaration of Helsinki, Council of International Organizations of Medical Sciences International Ethical Guidelines, and Good Clinical Practice guidelines. Written informed consent was obtained from all participants before participation in this study.

Eligible participants (18 years or older) had a body mass index (BMI) greater than or equal to 30 or greater than or equal to 27 and at least 1 weight-related complication (ie, hypertension, dyslipidemia, obstructive sleep apnea, or cardiovascular disease). Key exclusion criteria included diabetes, prior or planned surgical treatment for obesity, and treatment with a medication that promotes weight loss within 3 months prior to enrollment. Full eligibility criteria are shown in eAppendix 1 in Supplement 2 . The study was not designed to represent the racial diversity of each of the participating countries. Race and ethnicity were self-reported by participants in this study using fixed selection categories.

Tirzepatide was administered once weekly as a subcutaneous injection. During the 36-week, open-label lead-in period, the starting dose of tirzepatide was 2.5 mg and was increased by 2.5 mg every 4 weeks until a maximum tolerated dose of 10 or 15 mg was achieved (eFigure 1 in Supplement 2 ). Throughout the study, gastrointestinal symptoms were managed by dietary counseling, symptomatic medications per the investigator’s discretion, or skipping of a single dose of treatment as described in the protocol ( Supplement 1 ). During the lead-in period, if these mitigations were not successful, a cycle of tirzepatide dose deescalation and reescalation (in 2.5-mg increments) was allowed. At the end of the lead-in period, participants who attained the maximum tolerated dose of tirzepatide (10 or 15 mg) were randomized in a 1:1 ratio by a computer-generated random sequence using an interactive web-response system to either continue receiving the maximum tolerated dose of tirzepatide or switch to matching placebo for an additional 52 weeks. Randomization was stratified by country, sex, maximum tolerated dose of tirzepatide, and percent weight reduction at week 36 (<10% vs ≥10%). Dose adjustments were not permitted during the double-blind treatment period.

Quiz Ref ID All participants received lifestyle counseling by a qualified health care professional throughout the study to encourage adherence to a healthy 500 kcal/d deficit diet and at least 150 minutes of physical activity per week. The use of concomitant medications is described in eAppendix 2 in Supplement 2 .

The primary end point was the percent change in body weight from randomization (week 36) to week 88. Key secondary end points capturing weight maintenance and regain, respectively, were the proportion of participants at week 88 maintaining at least 80% of the body weight loss during the 36-week open-label period and time during the 52-week double-blind treatment period to first occurrence of participants returning to greater than 95% baseline body weight for those who lost at least 5% during the open-label lead-in period. Key secondary end points also included change in absolute body weight and waist circumference during the double-blind period (week 36 to 88) and the proportion of participants achieving weight reduction thresholds of at least 5%, at least 10%, at least 15%, and at least 20% since enrollment (week 0 to 88); the proportion of participants achieving at least 25% weight reduction from week 0 to 88 was a prespecified exploratory end point.

Additional secondary end points included change from randomization (week 36) to week 88 and from enrollment (week 0) to week 88 in cardiometabolic risk factors including glycemic parameters, fasting insulin, lipids, blood pressure, and patient-reported outcomes measured by the Short Form-36 Version 2 Health Survey (SF-36 v2) acute form and Impact of Weight on Quality of Life-Lite-Clinical Trials Version (IWQOL-Lite-CT).

Safety assessments included treatment-emergent adverse events, serious adverse events, and early discontinuation of study drug due to adverse events during the tirzepatide lead-in treatment period (weeks 0-36), the double-blind period (weeks 36-88), and safety follow-up period. Cases of major adverse cardiovascular events, acute pancreatitis, and deaths were reviewed by an independent external adjudication committee.

A sample size of 600 randomized participants provided greater than 90% power to demonstrate superiority of maximum tolerated dose of tirzepatide vs placebo for the primary end point at a 2-sided significance level of .05 using a 2-sample t test. The calculation assumed a dropout rate of up to 25%, a difference between treatment groups of at least 6% in mean percent change in body weight from randomization (week 36) to week 88, and a common SD of 8% based on data from 2 phase 2 trials. 19 , 20

Unless stated otherwise, efficacy end points were analyzed using the full analysis set (data obtained during the double-blind period, regardless of adherence to study drug) and the efficacy analysis set (data obtained during the double-blind period, excluding data after discontinuation of study drug). Assessment of adverse events and laboratory parameters used the safety analysis set (data obtained during the double-blind period and safety follow-up period, regardless of adherence to study drug). All results from statistical analyses were accompanied by 2-sided 95% CIs and corresponding P values (statistical significance was defined as P < .05). Statistical analyses were performed using SAS version 9.4 (SAS Institute).

Two estimands (treatment regimen estimand and efficacy estimand) were used to assess efficacy from different perspectives and accounted for intercurrent events and missing data. 21 The treatment regimen estimand was conducted on the full analysis set representing the mean treatment effect of tirzepatide relative to placebo for all participants who had undergone randomization, regardless of treatment adherence. If intercurrent events led to missing data, the missingness was assumed to be related to treatment, except for intercurrent events solely due to COVID-19, for which missing at random was assumed. The efficacy estimand was conducted on the efficacy analysis set representing the mean treatment effect of tirzepatide relative to placebo for all participants who had undergone randomization if the treatment was administered as intended (ie, excluding the data collected after study drug discontinuation). Continuous end points were analyzed using an analysis of covariance model for the treatment regimen estimand and a mixed model for repeated measures for the efficacy estimand, and categorical end points were analyzed by logistic regression for both estimands (treatment difference was assessed by odds ratio). Details on statistical analysis methods, estimands, and handling of missing values are provided in eAppendix 3 in Supplement 2 and the statistical analysis plan ( Supplement 3 ). All reported results are for the treatment regimen estimand unless stated otherwise. The type I error rate was controlled within each estimand independently for evaluation of primary and key secondary end points with a graphical approach (eAppendix 3 in Supplement 2 ). Because of the potential for type I error due to multiple comparisons, findings for analyses of additional secondary end points should be interpreted as exploratory.

A total of 952 patients were screened and 783 were enrolled in the 36-week open-label tirzepatide lead-in treatment period. Among enrolled participants, 113 discontinued the study drug during the lead-in period, most commonly due to an adverse event or participant withdrawal ( Figure 1 ). A total of 670 participants (92.7% achieved a maximum tolerated dose of 15 mg and 7.3% achieved a maximum tolerated dose of 10 mg) were randomized to continue receiving the maximum tolerated dose of tirzepatide (n = 335) or switch to receiving placebo (n = 335). Of the randomized participants, 600 (89.6%) completed the study and 575 (85.8%) completed the study while receiving the study drug. Withdrawal and “other” (mainly in the placebo group as lack of efficacy) were the most common reasons for premature study drug discontinuation during the double-blind period ( Figure 1 ).

Most randomized participants were women (70.6%) and White (80.1%), with an overall mean age of 48 years, body weight of 107.3 kg, BMI of 38.4, and waist circumference of 115.2 cm at enrollment (week 0; Table 1 ). The mean duration of obesity was 15.5 years and 69.4% participants had 1 or more weight-related complication (eTable 1 in Supplement 2 ), with hypertension and dyslipidemia being the most prevalent ( Table 1 ). Demographics and clinical characteristics at randomization (week 36) were similar across tirzepatide and placebo groups, with overall mean body weight of 85.2 kg, BMI of 30.5, and waist circumference of 97.5 cm.

During the open-label tirzepatide lead-in period (week 0 to 36), randomized participants achieved a mean weight reduction of 20.9%, with reductions in BMI and waist circumference and improvements in blood pressure, glycemic parameters, lipid levels, and patient-reported outcomes (eTable 2 in Supplement 2 ).

Quiz Ref ID For the treatment regimen estimand, the mean percent change in weight from week 36 to week 88 was −5.5% with tirzepatide vs 14.0% with placebo (difference, −19.4% [95% CI, −21.2% to −17.7%]; P < .001; Table 2 ; eFigure 2A in Supplement 2 ). For the efficacy estimand, corresponding changes were −6.7% with tirzepatide vs 14.8% with placebo (difference, −21.4% [95% CI, −22.9% to −20.0%]; P < .001; eTable 3 and eFigure 3 in Supplement 2 ).

At week 88, a significantly greater percentage of participants who continued receiving tirzepatide vs placebo maintained at least 80% of the body weight loss during the 36-week open-label tirzepatide lead-in treatment period (89.5% vs 16.6%; P < .001; treatment regimen estimand; Table 2 ; eFigure 2B in Supplement 2 ). Consistent results were observed when using the efficacy estimand (eTable 3 in Supplement 2 ). Time-to-event analysis showed that continued tirzepatide treatment during the double-blind period reduced the risk of returning to greater than 95% baseline body weight for those who had already lost at least 5% since week 0 by approximately 98% compared with placebo (hazard ratio, 0.02 [95% CI, 0.01 to 0.06]; P < .001) for the treatment regimen estimand, which was consistent with the results for the efficacy estimand (eFigure 4 in Supplement 2 ). The mean change from week 36 to week 88 in body weight and waist circumference is presented in Table 2 for the treatment regimen estimand and in eTable 3 in Supplement 2 for the efficacy estimand.

Relative to placebo, tirzepatide was associated with significant improvements from randomization at week 36 to week 88 in BMI, hemoglobin A 1c , fasting glucose, insulin, lipid levels, and systolic and diastolic blood pressure ( P < .001 for all except P = .014 for high-density lipoprotein cholesterol and P = .008 for free fatty acids) (eTable 3 in Supplement 2 ; efficacy estimand). Significant improvements were observed in the SF-36 v2 physical functioning, role-physical, role-emotional, and mental health domain scores and IWQOL-Lite-CT physical function composite scores with tirzepatide vs placebo from week 36 to week 88 ( P < .001 for all except P = .015 for SF-36 v2 role-physical score and P = .001 for SF-36 v2 role-emotional score) (eTable 3 in Supplement 2 ; efficacy estimand).

A significantly greater percentage of participants continuing tirzepatide vs placebo met the weight reduction thresholds of at least 5% (97.3% vs 70.3%), at least 10% (92.1% vs 46.2%), at least 15% (84.1% vs 25.9%), and at least 20% (69.5% vs 12.6%) from week 0 to week 88 ( P < .001 for all; treatment regimen estimand; Table 2 ; eFigure 2C in Supplement 2 ). Consistent results were observed when using the efficacy estimand (eTable 3 in Supplement 2 ).

Compared with placebo, tirzepatide was associated with improvements throughout the entire study (from week 0 to week 88) in body weight, BMI, cardiometabolic parameters (waist circumference, hemoglobin A 1c , fasting glucose, insulin, lipid levels, and systolic and diastolic blood pressure), and patient-reported outcomes ( P < .001 for all except P = .004 for free fatty acids and P = .064 for high-density lipoprotein cholesterol) ( Figure 2 and eTable 3, eFigure 3, and eFigure 5-8 in Supplement 2 ).

A greater percentage of participants continuing tirzepatide vs placebo achieved the prespecified exploratory end point of at least 25% weight reduction from week 0 to week 88 with the treatment regimen estimand (54.5% vs 5.0%; P < .001; Table 2 and eFigure 2C in Supplement 2 ) and the efficacy estimand (eTable 3 in Supplement 2 ).

A total of 81.0% of participants reported at least 1 treatment-emergent adverse event during the tirzepatide lead-in treatment period, with the most frequent events being gastrointestinal (nausea [35.5%], diarrhea, [21.1%], constipation [20.7%], and vomiting [16.3%]; eTable 4 in Supplement 2 ). During the double-blind period, 60.3% of participants continuing tirzepatide reported at least 1 treatment-emergent adverse event compared with 55.8% of participants who switched to placebo ( Table 3 ). The most frequent treatment-emergent adverse events during the double-blind period were COVID-19 and gastrointestinal disorders. Gastrointestinal events were more common in the tirzepatide group than in the placebo group (diarrhea, 10.7% vs 4.8%; nausea, 8.1% vs 2.7%; and vomiting, 5.7% vs 1.2%; Table 3 ). Most gastrointestinal events were mild to moderate in severity, and incidence of new events decreased over time in tirzepatide-treated participants during the lead-in period and leveled off during the double-blind period (eFigure 9 and eFigure 10 in Supplement 2 ).

Treatment discontinuation due to an adverse event occurred in 7.0% of enrolled participants during the tirzepatide lead-in treatment period, mainly due to gastrointestinal events (eTable 4 in Supplement 2 ). Quiz Ref ID During the double-blind period, treatment discontinuation due to an adverse event occurred in 1.8% of participants in the tirzepatide group and 0.9% in placebo group ( Table 3 ).

Overall, 16 participants (2.0%) reported serious adverse events during the lead-in period (eTable 4 in Supplement 2 ) and 10 (3.0%) during the double-blind period, with similar percentages across treatment groups ( Table 3 ). There was 1 death reported during the tirzepatide lead-in treatment period due to COVID-19 pneumonia and 2 deaths reported during the double-blind period (1 in the tirzepatide group due to congestive heart failure and 1 in the placebo group due to adenocarcinoma of the colon; eTable 6 in Supplement 2 ). None of the deaths were considered by investigators to be related to the study drug.

There were no adjudication-confirmed cases of pancreatitis reported during the study ( Table 3 ; eTable 4 in Supplement 2 ). Cholelithiasis was reported in 7 participants (0.9%) during the tirzepatide lead-in treatment period (eTable 4 in Supplement 2 ) and in 1 participant (0.3%) in both the tirzepatide group and placebo group during the double-blind period ( Table 3 ). Acute cholecystitis was reported in 4 participants (0.5%) during the tirzepatide lead-in treatment period (eTable 4 in Supplement 2 ) and in 3 (0.9%) in the placebo group during the double-blind period ( Table 3 ). No cases of medullary thyroid carcinoma or pancreatic cancer were reported.

Other adverse events of special interest are described in Table 3 and eTable 4 in Supplement 2 and additional safety variables are described in eTable 7 and eTable 8 in Supplement 2 .

The SURMOUNT-4 trial results emphasize the need to continue pharmacotherapy to prevent weight regain and ensure the maintenance of weight reduction and its associated cardiometabolic benefits. 22 At least 5 trials (including the present study) across various classes of medications, including potent antiobesity medications such as semaglutide, have demonstrated that weight is substantially regained after cessation of pharmacotherapy. 5 , 6 , 23 , 24

The consistency of these data across therapeutic classes spanning more than 2 decades suggests that obesity is a chronic metabolic condition similar to type 2 diabetes and hypertension requiring long-term therapy in most patients.

A notable finding in the SURMOUNT-4 trial is that after switching to placebo for 1 year, participants ended the study with substantial body weight reduction (9.9%). However, much of their initial improvement in cardiometabolic risk factors had been reversed. Further studies are needed to understand the potential long-term benefits and risks (ie, legacy effects) of such short-term therapy.

The health benefits seen with continued treatment with the maximum tolerated dose of tirzepatide during this study were achieved with a safety profile consistent with that previously reported in SURMOUNT and SURPASS trials and in studies of incretin-based therapies approved for the treatment of obesity and overweight. 18 , 25 - 32

The strengths of this study include its large sample size and the randomized withdrawal design. The duration of the open-label lead-in period allowed the study to assess the maintenance of body weight reduction. Dose escalation protocols during the open-label lead-in period helped to maximize tolerability and reflect dose adjustment strategies that may be helpful to future prescribers.

This study has limitations. First, the design of this study did not allow dose adjustments after randomization and did not evaluate the effects of intensive behavioral therapy on the maintenance of body weight reduction. Second, those who tolerated initial treatment with 10-mg or 15-mg tirzepatide may represent a subgroup of the general population.

After achieving clinically meaningful weight reduction during a 36-week tirzepatide lead-in treatment period, adults with obesity or overweight who continued treatment with maximum tolerated dose tirzepatide for an additional 52 weeks demonstrated superior weight maintenance and continued weight reduction compared to those who switched to placebo.

Accepted for Publication: November 11, 2023.

Published Online: December 11, 2023. doi:10.1001/jama.2023.24945

Corresponding Author: Louis J. Aronne, MD, Comprehensive Weight Control Center, Division of Endocrinology, Diabetes, and Metabolism, Weill Cornell Medicine, 1305 York Ave, Fourth Floor, New York, NY 10065 ( [email protected] ).

Author Contributions: Dr Aronne had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Aronne, Lin, Ahmad, Zhang, Bunck, Murphy.

Acquisition, analysis, or interpretation of data: Aronne, Sattar, Horn, Bays, Wharton, Ahmad, Liao, Bunck, Jouravskaya, Murphy.

Drafting of the manuscript: Aronne, Ahmad, Liao, Bunck, Murphy.

Critical review of the manuscript for important intellectual content: Aronne, Sattar, Horn, Bays, Wharton, Lin, Ahmad, Zhang, Bunck, Jouravskaya, Murphy.

Statistical analysis: Ahmad, Zhang, Liao, Bunck.

Obtained funding: Bunck.

Administrative, technical, or material support: Bays, Lin, Bunck, Murphy.

Supervision: Aronne, Horn, Ahmad, Bunck, Murphy.

Other - Served as a principal investigator in the trial: Horn.

Other - Responsible medical officer for the SURMOUNT program: Bunck.

Conflict of Interest Disclosures: Dr Aronne reported receiving grants or personal fees from Altimmune, AstraZeneca, Boehringer Ingelheim, Eli Lilly, ERX, Gelesis, Intellihealth, Jamieson Wellness, Janssen, Novo Nordisk, Optum, Pfizer, Senda Biosciences and Versanis and being a shareholder of Allurion, ERX Pharmaceuticals, Gelesis, Intellihealth, and Jamieson Wellness. Dr Sattar reported receiving personal fees or grants from Abbott Laboratories, Amgen, AstraZeneca, Boehringer, Eli Lilly, Hanmi Pharmaceuticals, Janssen, Merck Sharp & Dohme, Novartis, Novo Nordisk, Pfizer, Roche, and Sanofi outside the submitted work. Dr Horn reported research funding from Lilly and Novo Nordisk during the conduct of the study and personal fees from Eli Lilly, Novo Nordisk, and Gelesis outside the submitted work. Dr Bays reported receiving grants from Eli Lilly during the conduct of the study and grants from 89 Bio, Alon Medtech/Epitomee, Altimmune, Amgen, Boehringer Ingelheim, Kallyope, Novo Nordisk, Pfizer, Shionogi, Viking, and Vivus and personal fees from Altimmune, Amgen, Boehringer Ingelheim, and Eli Lilly outside the submitted work. Dr Wharton reported receiving nonfinancial support from Eli Lilly during the conduct of the study and personal fees from Novo Nordisk, Boehringer Ingelheim, Biohaven, Bausch Health Canada, and Eli Lilly outside the submitted work. Dr Ahmad reported being an employee and shareholder of Eli Lilly and Company during the conduct of the study. Dr Zhang reported being an employee and shareholder of Eli Lilly and Company during the conduct of the study. Dr Liao reported being an employee and shareholder of Eli Lilly and Company during the conduct of the study. Dr Bunck reported being an employee and shareholder of Eli Lilly and Company during the conduct of the study. Dr Murphy reported being an employee and shareholder of Eli Lilly and Company during the conduct of the study. No other disclosures were reported.

Funding/Support: This study was sponsored by Eli Lilly and Company.

Role of the Funder/Sponsor: Eli Lilly and Company was involved in the study design and conduct; data collection, management, analyses, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. The sponsor did not have the right to veto publication or to control the decision regarding to which journal the manuscript was submitted. Final decisions resided with the authors, which included employees of the sponsor.

Group Information: The SURMOUNT-4 Investigators are listed in Supplement 5 .

Meeting Presentation: Part of the data from this study was presented at the 59th European Association for Study of Diabetes; October 2-6, 2023.

Data Sharing Statement: See Supplement 4 .

Additional Contributions: We thank the participants and the study coordinators who cared for them. We thank Amelia Torcello Gomez, PhD, for her writing and editorial assistance, for which she was compensated as part of her salary as an employee of Eli Lilly and Company.

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Glob Pediatr Health

Childhood and Adolescent Obesity in the United States: A Public Health Concern

Adekunle sanyaolu.

1 Federal Ministry of Health, Abuja, Nigeria

Chuku Okorie

2 Essex County College, Newark, NJ, USA

3 Saint James School of Medicine, Anguilla, British West Indies

Jennifer Locke

Saif rehman.

Childhood and adolescent obesity have reached epidemic levels in the United States. Currently, about 17% of US children are presenting with obesity. Obesity can affect all aspects of the children including their psychological as well as cardiovascular health; also, their overall physical health is affected. The association between obesity and other conditions makes it a public health concern for children and adolescents. Due to the increase in the prevalence of obesity among children, a variety of research studies have been conducted to discover what associations and risk factors increase the probability that a child will present with obesity. While a complete picture of all the risk factors associated with obesity remains elusive, the combination of diet, exercise, physiological factors, and psychological factors is important in the control and prevention of childhood obesity; thus, all researchers agree that prevention is the key strategy for controlling the current problem. Primary prevention methods are aimed at educating the child and family, as well as encouraging appropriate diet and exercise from a young age through adulthood, while secondary prevention is targeted at lessening the effect of childhood obesity to prevent the child from continuing the unhealthy habits and obesity into adulthood. A combination of both primary and secondary prevention is necessary to achieve the best results. This review article highlights the health implications including physiological and psychological factors comorbidities, as well as the epidemiology, risk factors, prevention, and control of childhood and adolescent obesity in the United States.

Introduction

Childhood and adolescent obesity have reached epidemic levels in the United States, affecting the lives of millions of people. In the past 3 decades, the prevalence of childhood obesity has more than doubled in children and tripled in adolescents. 1 The latest data from the National Health and Nutrition Examination Survey show that the prevalence of obesity among US children and adolescents was 18.5% in 2015-2016. Overall, the prevalence of obesity among adolescents (12-19 years; 20.6%) and school-aged children (6-11 years; 18.4%) was higher than among preschool-aged children (2-5 years; 13.9%). School-aged boys (20.4%) had a higher prevalence of obesity than preschool-aged boys (14.3%). Adolescent girls (20.9%) had a higher prevalence of obesity than preschool-aged girls (13.5%; Figure 1 ). 1 Moreover, the rates of obesity have been steadily rising from 1999-2000 through 2015-2016 ( Figure 2 ). 1 According to Ahmad et al, 80% of adolescents aged 10 to 14 years, 25% of children younger than the age of 5 years, and 50% of children aged 6 to 9 years with obesity are at risk of remaining adults with obesity. 2

An external file that holds a picture, illustration, etc.
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Prevalence of obesity among children and adolescents aged 2 to 19 years, by sex and age: the United States, 2015-2016.

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Object name is 10.1177_2333794X19891305-fig2.jpg

Trends in obesity prevalence among children and adolescents aged 2 to 19 years: the United States, 1999-2000 through 2015-2016.

Obesity can affect all aspects of children and adolescents including but not limited to their psychological health and cardiovascular health and also their overall physical health. 3 The association between obesity and morbid outcomes makes it a public health concern for children and adolescents. 4 Obesity has an enormous impact on both physical and psychological health. Consequently, it is associated with several comorbidity conditions such as hypertension, hyperlipidemia, diabetes, sleep apnea, poor self-esteem, and even serious forms of depression. 5 In addition, children with obesity who were followed-up to adulthood were much more likely to suffer from cardiovascular and digestive diseases. 3 The increase in body fat also exposes the children to increase in the risk of numerous forms of cancers, such as breast, colon, esophageal, kidney, and pancreatic cancers. 6

Due to its public health significance, the increasing trend in childhood obesity needs to be closely monitored. 7 However, these trends have proved to be challenging to quantify and compare. While there are many factors and areas to consider when discussing obesity in children and adolescents, there are a few trends that are evident in recent studies. For example, the prevalence of obesity varies among ethnic groups, age, sex, education levels, and socioeconomic status. A report published by the National Center for Health Statistics using data from the National Health and Nutrition Examination Survey provides the most recent national estimates from 2015 to 2016 on obesity prevalence by sex, age, race, and overall estimates from 1999-2000 through 2015-2016. 1 Prevalence of obesity among non-Hispanic black (22.0%) and Hispanic (25.8%) children and adolescents aged 2 to 19 years was higher than among both non-Hispanic white (14.1%) and non-Hispanic Asian (11.0%) children and adolescents. There were no significant differences in the prevalence of obesity between non-Hispanic white and non-Hispanic Asian children and adolescents or between non-Hispanic black and Hispanic children and adolescents. The pattern among girls was similar to the pattern in all children and adolescents. The prevalence of obesity was 25.1% in non-Hispanic black, 23.6% in Hispanic, 13.5% in non-Hispanic white, and 10.1% in non-Hispanic Asian girls. The pattern among boys was similar to the pattern in all children and adolescents except that Hispanic boys (28.0%) had a higher prevalence of obesity than non-Hispanic black boys (19.0%; Figure 3 ). 1 This review article is aimed at studying the health implications including physical and psychological factors and comorbidities, as well as the epidemiology, risk factors, prevention, and control of childhood and adolescent obesity in the United States.

An external file that holds a picture, illustration, etc.
Object name is 10.1177_2333794X19891305-fig3.jpg

Prevalence of obesity among children and adolescents aged 2 to 19 years, by sex and race and Hispanic origin: the United States, 2015-2016.

Methodology

We performed a literature search using online electronic databases (PubMed, MedlinePlus, Mendeley, Google Scholar, Research Gate, Global Health, and Scopus) using the keywords “childhood,” “adolescents,” “obesity,” “BMI,” and “overweight.” Articles were retrieved and selected based on relevance to the research question.

Ethical Approval and Informed Consent

Ethics approval and informed consent were not required for this narrative review.

Definition of Childhood Obesity

Defining obesity requires a suitable measurement of body fat and an appropriate cutoff range. 8 Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared, rounded to 1 decimal place. Obesity in children and adolescents was defined as a BMI of greater than or equal to the age- and sex-specific 95th percentile and overweight with a BMI between the 85th and 95th percentiles of the 2000 Centers for Disease Control and Prevention (CDC) growth charts. 9

However, the use of the BMI percentile according to the age/sex of the CDC growth charts for very high BMIs can result in estimates that differ substantially from those that are observed, 10 , 11 and this constrains the maximum BMI that is attainable at given sex and age. 12 , 13 These limitations have resulted in the classification of severe obesity as a BMI ≥120% of the 95th percentile rather than a percentile greater than the 95th percentile. 11 , 14 A BMI of 120% of the 95th percentile corresponds to a BMI of ~35 among 16 to 18 year olds.

Physiology of Energy Regulation and Obesity

Obesity is a chronic multifactorial disease, characterized by an excessive accumulation of adipose tissue, commonly as a result of excessive food intake and/or low energy expenditure. Obesity can be triggered by genetic, psychological, lifestyle, nutritional, environmental, and hormonal factors. 15

Obesity is found in individuals that are susceptible genetically and involves the biological defense of an elevated body fat mass, the mechanism of which could be explained in part by interactions between brain reward and homeostatic circuits, inflammatory signaling, accumulation of lipid metabolites, or other mechanisms that impair hypothalamic neurons. 16

Normal energy regulation physiology is under tight neurohormonal control. The neurohormonal control is performed in the central nervous system through neuroendocrine connections, in which circulating peripheral hormones, such as leptin and insulin, provide signals to specialized neurons of the hypothalamus reflecting body fat stores and induces appropriate responses to maintain the stability of these stores. The hypothalamic region is where the center of the regulation of hunger and satiety is located. Some of them target the activity of endogenous peptides, such as ghrelin, pancreatic polypeptide, 17 peptide YY, and neuropeptide Y, 18 as well as their receptors.

The physiology of energy regulation may result in obesity in susceptible people when it goes awry from genetic and environmental modulators. There is strong evidence of the majority of obesity cases that are associated with central resistance to both leptin and insulin actions. 19 , 20 The environmental modulators equally play critical roles in obesity. Changes in the circadian clock are associated with temporal alterations in feeding behavior and increased weight gain. 21 Stress interferes with cognitive processes such as executive function and self-regulation. Second, stress can affect behavior by inducing overeating and consumption of foods that are high in calories, fat, or sugar; by decreasing physical activity; and by shortening sleep. Third, stress triggers physiological changes in the hypothalamic-pituitary-adrenal axis, reward processing in the brain, and possibly the gut microbiome. Finally, stress can stimulate the production of biochemical hormones and peptides such as leptin, ghrelin, and neuropeptide Y. 17

The lateral hypothalamus (LH) plays a fundamental role in regulating feeding and reward-related behaviors; however, the contributions of neuronal subpopulations in the LH are yet to be identified thoroughly. 22 The LH has also been associated with other aspects of body weight regulation, such as physical activity and thermogenesis. 23 The LH contains a heterogeneous assembly of neuronal cell populations, in which γ-aminobutyric acid (GABA) neurons predominate. 23 LH GABA neurons are known to mediate multiple behaviors important for body weight regulation, thus altering energy expenditure. 23

Etiology and Risk Factors

Excess body fat is a major health concern in childhood and adolescent populations. The dramatic increase in childhood obesity foreshadows the serious health consequences of their adult life. As obesity begins from childhood and spans through adult life, it becomes increasingly more difficult to treat successfully. Being able to identify the risk factors and potential causes of childhood obesity is one of the best strategies for preventing the epidemic. 24

According to the Morbidity and Mortality Weekly Report released in 2011, there is an acceptance that there is no single cause of childhood obesity and that energy imbalance is just a part of the numerous factors. 25 Many children have a discrepancy between what is taken in and what is expended. 26 For example, children with obesity consume approximately 1000 calories more than what is necessary for their body to function healthily and to be able to participate in regular physical activities. Over 10 years, there will be an excess of 57 pounds of unnecessary weight. With excessive caloric intake, as well as sedentary lifestyles, childhood obesity will continue to rise if no changes are implemented. Adding daily physical activity, better sleep patterns, as well as dietary changes can help decrease the number of excess calories and help with obesity-related problems in the future.

Also, during childhood, excess fat accumulates when the increase in caloric intake exceeds the total energy expenditure. 26 Furthermore, children living in the United States today compared with children living in the 1900s are participating in more than 6 hours per day activities on social media. This includes but is not limited to traditional television, video gaming, and blogging/Facebook activities. An additional economic rationalization for the increase in childhood obesity is technology. In other words, Americans can now eat more in less time.

In a study, Cutler et al found that an increase in consumption of food tends to be related to technology innovation in food production and transportation. Technology has thus made it increasingly possible for firms to mass prepare food and ship to consumers for ready consumption, thereby taking advantage of scale economies in food preparation. The result of this change has been a significant reduction in the time costs for food production. These lower time costs have led to increased food consumption and, ultimately, increased weights. 27 Eliminating the time cost of food preparation disproportionately increases consumption for hyperbolic discounters because time delay is a particularly important mechanism for discouraging those individuals from consuming. 27 Society today prefers immediate satisfaction with regard to food and convenience over the long-term goals of living a long, healthy life. The availability of high-caloric, less-expensive food coupled with the extensive advertisement and easy accessibility of these foods has contributed immensely to the rising trend of obesity. 28 For example, there have been reductions in the price of McDonalds and Coca-Cola (5.44% and 34.89%, respectively) between 1990 and 2007, while there was about a 17% increase in the price of fruits and vegetables between 1997 and 2003. 29

Likewise, only 16% of children walk or bike to school today as compared with 42% in the late 1960s. However, the distance, convenience, weather, scanty sidewalks, and anxiety about crimes against children could all contribute to this difference. Furthermore, with elementary, middle, and high school combined, only 13.8% of these schools provide adequate daily physical education classes for at least 4 hours a week. 30

Some other potential risk factors have been reported through research studies that involve issues that affect the child in utero and childhood. Table 1 represents potential risk factors and confounders of childhood obesity. 31

Potential Risk Factors of Childhood Obesity.

Family characteristics	Parent’s BMI during pregnancy
	Number of siblings of the child at 18 months
	The ethnicity of the child
	Age of the mother at delivery
Childhood lifestyle	Time spent watching TV
	Time in the car per day (weekdays/weekend)
	Duration of night sleep
	Dietary pattern
Infant feeding	Breast feeding/formula feeding
	Age of introduction to solid foods
Intrauterine and perinatal factors	Birthweight
	Sex
	Maternal parity
	Maternal smoking during pregnancy (28-32 weeks)
	Season of birth (winter, summer, fall, spring)
	Number of fetuses
Other	Maternal social class (SES)
	Maternal education
	Energy intake of the child

Abbreviations: BMI, body mass index; SES, socioeconomic status.

Catalano et al argues that maternal BMI before conception, independent of maternal glucose status or birth weight, is a strong predictor of childhood obesity. 32 Infants at the highest quarter for weight at 8 and 18 months are more likely to become children with obesity at age 7, than children in the lower quarters. Certain behaviors have been linked to childhood obesity and overweight; these are a lack of physical activity and unhealthy eating patterns (eating more food away from home, drinking more sugar-sweetened drinks, and snacking more frequently), resulting in excess energy intake. 22 , 31 In addition, when one parent presents with obesity, there is an increased potential for the child to become obese over the years. Naturally, the risk is higher for the children when both parents present with obesity. Furthermore, a study that followed children over time observed that children who got less sleep <10.5 hours at age 3 were 45% more likely to be children with obesity at the age of 7, than children who got greater than 12 hours of sleep during their first 3 years of life. 33 , 34

While all the above-mentioned factors are informative, there is still the need for further research concerning childhood and adolescent obesity and obesity in general. Risk factors for obesity in childhood are still somewhat uncertain, and evidence-based research for preventative strategies is lacking. Moreover, effective action to prevent the childhood obesity epidemic requires evidence-based on early life risk factors, and this evidence, unfortunately, is still incomplete. Furthermore, a research study has attempted to capture the complete picture of childhood obesity early life course risk factors. In the study, they identified that parental BMI and gestational weight gain among other factors should be considered in prevention programs. 35

Health Effects of Childhood Obesity

Childhood obesity is known to have a significant impact on both physical and psychological health. Sahoo et al stated that “childhood obesity can profoundly affect children’s physical health, social and emotional well-being, as well as self-esteem.” They associated poor academic performance and a lower quality of life experienced by the child with childhood obesity. They also stated that “metabolic, cardiovascular, orthopedic, neurological, hepatic, pulmonary, and menstrual disorders among others are consequences of childhood obesity.” 36 There are many health consequences of childhood obesity, and three of the more common ones are sleep apnea, diabetes, and cardiovascular diseases. 36

Psychological Consequences of Obesity

Several studies related to childhood and adolescent obesity have focused primarily on physiological consequences. Other studies have been conducted regarding the association between psychiatric disorders and obesity; these have resulted in conflict due to obesity being found to be an insignificant factor for psychopathology. However, a comparative study by Britz et al found that high rates of mood, anxiety, somatoform, and eating disorders were detected among children with obesity. The study also observed that most psychiatric disorders began after the onset of obesity. In this large population-based study, it was found that a staggering 60% of females and 35% of males reported that they have engaged in binge eating and expressed a lack of control over their diet. 37

Goldfield et al conducted a study among 1400 adolescents with obesity, overweight, and normal weight in grades 7 to 12. Their BMIs, as determined by the International Obesity Task Force, were the criteria used to define each group. Each participant completed a questionnaire on body images, eating behaviors, and moods. Adolescents with obesity reported significantly higher body dissatisfaction, social isolation, depression symptoms, anhedonia, and negative self-esteem than those of normal weight. 38 There is widespread stigmatization of people with obesity that causes harm rather than the intention to motivate people to lose weight. Stigma contributes to behaviors such as binge eating, social isolation, avoidance of health care services, decreased physical activity, and increased weight gain, which worsens obesity and creates additional barriers to healthy behavior change. 39 Weight-based bullying in youth is considered a common, serious problem in many countries. 40 In a study conducted by O’Brien et al, to test whether the association between weight stigma experiences and disordered eating behaviors, that is, emotional eating, uncontrolled eating, and loss-of-control eating, are mediated by weight bias internalization and psychological distress among 634 undergraduate university students, and results of statistical analyses showed that weight stigma was significantly associated with all measures of disordered eating, and with weight bias internalization and psychological distress. 41

Asthma and Obesity

There is mounting evidence that childhood obesity is a risk factor for the development of asthma. 42 A research study was conducted by Belamarich et al to investigate 1322 children aged 4 to 9 years with asthma. Obesity, as defined by the CDC, is the BMI, with weight and height being greater than the 95th percentile. This was the criteria used to identify the 249 children with obesity, while the BMI between the 5th and 95th percentile identified the children who were not obese. After a baseline assessment was done, the 9-month study found that the children with obesity had a higher number of days of wheezing over 2 weeks (4.0 vs 3.4) and as well had more unscheduled emergency hospital visits (39% vs 31%). 42

Obesity directly correlates with the severity of asthma, as well as poor response to corticosteroids. 43 In fact, children with obesity who also have a history of asthma are more challenging to control and linked to worse quality of life. 44 A prospective trial found that weight loss in patients with obesity and a history of asthma can significantly aid them to control the asthma attacks. 43

Chronic Inflammation and Childhood Obesity

Lumeng and Saltiel reported that obesity in children affects multiple organ systems and predisposes them to diseases. The effect of obesity on the tissue can manifest in the development of insulin-resistant type 2 diabetes, the risk of cancer, and pulmonary diseases. 45

The inflammatory response to obesity triggers pathogens, systematic increases in circulatory inflammatory cytokines, and acute-phase reactants (eg, C-reactive proteins), which inflames the tissues. This is often caused by the activation of tissue leukocytes. Chronic inflammation in children with obesity can induce meta-inflammation that is unique when compared with other inflammatory paradigms (eg, infection, autoimmune diseases). 45 Researchers have reported that children with obesity are at risk of lifelong meta-inflammation. In these children, the inflammatory markers are elevated as early as in the third year of life. 45 , 46 This has been linked to heart disease later in life. 19 The long-term consequences of such findings can cause cumulative vascular damage that correlates with the increased weight status. 47

The short-term and long-term effects of obesity on the health of children is a significant concern because of the negative psychological and health consequences. 46 The potential negative psychological outcomes are depressive symptoms, poor body image, low self-esteem, a risk for eating disorders, and behavior and learning problems. Additional negative health consequences include insulin resistance, type 2 diabetes, asthma, hypertension, high total, and low-density lipoprotein cholesterol and triglyceride levels in the blood, low high-density lipoprotein cholesterol levels in the blood, sleep apnea, early puberty, orthopedic problems, and nonalcoholic steatohepatitis 46 , 47 ( Figure 4 ). Children with obesity are more likely to become adults with obesity, thus increasing their risk for several diseases before they even reach their teen years. 48

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Object name is 10.1177_2333794X19891305-fig4.jpg

Comorbidities and potential health consequences of childhood obesity. 47

Prevention and Control

There are two primary components to the prevention and control of childhood obesity.

The first is to educate parents on proper nutritional requirements for their children and the second is to implement the learned information. Educating parents on proper nutrition and dietary caloric intake requirements for their children is at the forefront for the prevention of obesity; however, the way the information is disseminated may affect the usefulness of the information. For example, one of the main limitations to the education of parents about childhood obesity is that typically written information is used as the conduit to health information and disease prevention. 49 The Growing Right Onto Wellness (GROW) trial used a systematic assessment of patient education material that was used for the prevention of childhood obesity in the low health literate population. 49 Results suggest that the average readability is of grade 6 level (SMOG [Simple Measure of Gobbledygook] Index 5.63 ± 0.76 and Fry graph 6.0 ± 0.85) and that adjustment of education material must be done for low health literate populations to adequately comprehend educational material and maintain motivation on the prevention of childhood obesity. 49 A similar study was conducted to further support this improvement when using color-coordinated diagrams to help parents visualize instead of trying to comprehend with numbers and words. It proved to be successful as parents were able to see where they were going wrong and make the necessary changes in their children’s diet. 49

Similarly, the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development conducted a study on 744 adolescents and parents, and analyzed data to determine if parental (maternal and paternal, individually) reactions to children’s behavior was related to childhood obesity. 50 The study concluded that informing parents that their attitude toward their children’s behaviors will play a prominent role in preventing childhood obesity. 50 Parental education on nutrition, health, and the involvement of politicians, physicians, and school personnel are key for the prevention of childhood obesity. However, community and educational institutions have begun legislating and incorporating programs such as providing healthy foods at schools and also health information sessions directed toward young individuals, aimed at preventing childhood obesity in the United States and Canada. 51

Another effective prevention measure against childhood obesity is the awareness of parents on the meal and snack portion sizes. In a systematic review conducted on the effects of portion size manipulation with children and portion education/training interventions on dietary intake with parents, it was determined that the ability of adults to accurately estimate portion size improved following education/training. 52 Education of parents and children on diet requirements has its limitations in that the information must be easy to understand and be easily accessible in order to be practical. Making the available education materials easier to understand from just tables and numbers to more relatable aspects such as colors or figures, parents were able to visualize the changes they need to make whether it is with regard to portion sizes or even seeing how much childhood obesity is present in their family. Although much of the literature provided to parents is targeted to help those with lower numeracy skills, many parents benefited from the information being comparative from right/wrong and good/bad with regard to dieting. 49

The study recommended that proper educational materials, including useful and understandable literature, be used to control meal portion sizes and to help parents identify when children are at risk of obesity. Similarly, healthy eating practices should be taught by schools as a mandatory and essential method in the prevention of childhood obesity. 52

The implementation of healthy eating practices and adequate exercise regimes are essential in the prevention and control of childhood obesity. For example, information from systematic reviews, randomized controlled trials, and well-designed observational studies indicate that evidence-based prevention and control of childhood obesity can be accomplished with the collaboration of community/school, primary health care, and home-based/family-based interventions that involve both physical activity and dietary component. 53 In particular, the control of children with obesity is of significant value, as is the prevention of obesity. Two randomized control trials of 182 families were conducted from November 2005 to September 2007, and they studied the efficacy of US pediatric obesity treatment guidelines in children aged 4 to 9 years with a standardized BMI (ZBMI) greater than the 85 percentile. 54 Briefly, Trial 1 studied the impact on ZBMI by reducing snack foods and sugar-sweetened beverages and increasing fruits, vegetables, and low-fat dairy. 54 Trial 2 studied the impact on ZBMI by decreasing sugar-sweetened beverages and increasing physical activity and increasing low-fat milk consumption and reducing television watching. In Trial 1, the resulting ZBMI reduced within 6 months, and this was maintained through to the 12th month (ΔZBMI 0-12 months = −0.12 ± 0.22). 53 In Trial 2, the resulting ZBMI reduced within 6 months and continued to improve till the 12 months (ΔZBMI 0-12 months = −0.16 ± 0.31). 50

A similar cluster-randomized trial in England studied the effects of the reduction of carbonated beverages on the number of children with obesity in 29 classes (644 children). 51 Results indicate that a decrease of 0.6 glasses of carbonated drinks (250 mL) over three days per week decreased the number of children with obesity by 0.2%, while the control group increased by 7.5% (mean difference = 7.7%, 2.2% to 13.1%) at 12 months. However, diet control is only one component of the control and prevention of childhood obesity, while adequate exercise is another. 55

A systematic review and meta-analyses of the impact of diet and exercise programs (single or combined) was done on their effects on metabolic risk reduction in the pediatric population. 56 Analyses indicated that the addition of exercise to dietary intervention led to greater improvements in the levels of high-density lipoprotein cholesterol (3.86 mg/dL; 95% confidence interval [CI] = 2.70 to 4.63), fasting glucose (−2.16 mg/dL; 95% CI = −3.78 to −0.72), and fasting insulin (−2.75 µIU/mL; 95% CI = −4.50 to −1.00) over 6 months. 56 Diet and exercise are both important factors in the control and prevention of childhood obesity. It is our recommendation that parents and community (teachers and doctors) should be involved in identifying children at risk based on their BMI and participate in implementing practices such as good diet control through the reduction of sugary drinks, fatty foods, and also encouraging safe exercise programs to prevent and control childhood obesity in the society. 56

While all of the previous data express the more obvious prevention methods with regard to childhood obesity, it is imperative to note that ensuring that the whole family is involved in the intervention will yield the greatest results. 2 All current studies indicate that families must be included in childhood treatment of obesity. However, for the success of the child’s weight loss program, it is vital that the parents understand that the causes of obesity are often a mixture of four factors: genetic causes, parental habits, overeating, and poor exercise habits. Thus, instilling some responsibility on the parents and informing them that controlled food preparation, diet control, and family participation in physical activities will all assist in the treatment and control of obesity in their children. 2

Childhood obesity has increased significantly in recent decades and has quickly become a public health crisis in the United States and all over the world. Its increase in prevalence has provoked widespread research efforts to identify the factors that contributed to these changes. 57 Obesity starts with an imbalance between caloric intake and caloric expenditure. 58 Children with obesity are at greater risk of adult obesity; therefore, if we can educate and improve the health habits of families even before they start having children, this can help reduce the increasing rate of childhood obesity in the United States. Parents and caregivers with proper education on the causes and consequences of childhood obesity can help prevent childhood obesity by providing healthy meals and snacks, daily physical activity, and nutrition education to their family members. 59 Families need to take the approach of not adapting to their family being on a diet but more of a healthy lifestyle. A family’s home environment can influence children at a young age; therefore, making changes starting in the household early can educate and influence them to grow up healthy. Although prevention programs may be more expensive in the short term, the long-term benefits acquired through prevention are much more likely to save an even greater amount of health care costs. Not only will the children have a better childhood and self-esteem, but prevention programs can also decrease the incidence of cardiovascular diseases, diabetes, stroke, and possibly cancers in adulthood. 60 The overall need to decrease the obesity rate will help children and their families in the generations to come by building a healthy lifestyle and environment. In order to tackle the climbing obesity rate, overall health and lifestyle needs to be a priority as they balance one with the other. 49 While effective interventions to thwart childhood obesity still remain elusive, the sustainability of the interventions already in place will enable children and their families to adopt these important health behaviors as lifelong practices and improve their health. 58

Treatment of Obesity and the Physiology of Energy Regulation

As discussed previously, a variety of mechanisms participate in weight regulation and the development of obesity in children, including genetics, developmental influences (“metabolic programming” or epigenetics), individual and family health behaviors, and environmental factors. Among these potential mechanisms, only environmental factors are potentially modifiable during childhood and adolescence.

Unfortunately, despite intensive lifestyle modifications and support for healthy practices within the children’s environment, some children will continue to struggle with extreme excess weight and associated comorbidities. 61 , 62 Therefore, a combination of pharmacotherapy and lifestyle modification can be considered. 61 Overweight children should not be treated with medications unless significant, severe comorbidities persist despite lifestyle modification. The use of pharmacotherapy should also be considered in overweight children with a strong family history of type 2 diabetes or cardiovascular risk factors. Constant bidirectional communication between the brain and the gastrointestinal tract, as well as the brain and other relevant tissues (ie, adipose tissue, pancreas, and liver), ensures that the brain constantly perceives and responds accordingly to the energy status/needs of the body. This elegant biological system is subject to disruption by a toxic obesogenic environment, leading to syndromes such as leptin and insulin resistance, and ultimately further exposing individuals who are obese to further weight gain and type 2 diabetes mellitus. Currently, the only Food and Drug Administration–approved prescription drug indicated for the treatment of pediatric obesity is orlistat (Xenical; Genentech USA, Inc, South San Francisco, CA). 63 Orlistat works by inhibiting gastric and pancreatic lipases, the enzymes that break down triglycerides in the intestine. Moreover, imaging studies in humans are beginning to examine the influence that higher- order/hedonic brain regions have on homeostatic areas, as well as their responsiveness to homeostatic peripheral signals. With a greater understanding of these mechanisms, the field moves closer to understanding and eventually treating the casualties of obesity.

The number of children with obesity in the United States has increased substantially over the years; due to its public health significance, the increasing trends need to be closely monitored. While a complete picture of all the risk factors associated with obesity remains elusive, many of the studies agreed that prevention is the key strategy for controlling the current problem. Since the combination of diet, exercise, and physiological and psychological factors are all important factors in the control and prevention of childhood obesity, primary prevention methods should be aimed at educating the child and family and encouraging appropriate diet and exercise from a young age through adulthood while secondary prevention should be targeted at lessening the effect of childhood obesity by preventing the child from continuing unhealthy habits and obesity into adulthood. A combination of primary and secondary prevention is necessary to achieve the best results. Thus, a combined implementation of both types of preventions can significantly help lower the current prevalence of childhood and adolescent obesity in the United States. Failure to take appropriate actions could lead to serious public health consequences.

Author Contributions: AS: Contributed to conception and design; drafted manuscript; gave final approval; agrees to be accountable for all aspects of work ensuring integrity and accuracy.

XQ: Contributed to the acquisition, analysis, and interpretation.

JL: Contributed to the acquisition, analysis, and interpretation.

SR: Contributed to the acquisition, analysis, and interpretation.

Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.

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Research Briefing
Published: 09 August 2024

Years lived with and years lost to multiple long-term condition combinations that include diabetes

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We introduced time-based metrics to analyze multiple long-term condition (MLTC) combinations of two or more conditions that include diabetes, among adults in England. We calculated the median age of MLTC onset and years of life lived with and lost to the MLTC, and examined MLTC burdens from both individual perspectives and community perspectives.

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Pearson-Stuttard, J. et al. Trends in predominant causes of death in individuals with and without diabetes in England from 2001 to 2018: an epidemiological analysis of linked primary care records. Lancet Diabetes Endocrinol. 9 , 165–173 (2021). This paper reports a decline in cardiovascular mortality, accompanied by a diversification in the causes of death, in people with diabetes.

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Misra, S. et al. Current insights and emerging trends in early-onset type 2 diabetes. Lancet Diabetes Endocrinol. 11 , 768–782 (2023). This paper reports on the increasing prevalence of early-onset type 2 diabetes and its impact on future risk of multimorbidity.

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Outcomes Based Healthcare. NHS England segmentation dataset reference guide. outcomesbasedhealthcare https://go.nature.com/3WKayH9 (2018). This reference guide gives details on source datasets used to derive the segmentation dataset, the conditions included and the accuracy of coding.

Valabhji, J. et al. Prevalence of multiple long-term conditions (multimorbidity) in England: a whole population study of over 60 million people. J. R. Soc. Med. 117 , 104–117 (2024). This paper reports the prevalence of multiple long-term conditions at the population level in England, stratified by age, sex, socioeconomic status and ethnicity.

Ho, I. S. S. et al. Measuring multimorbidity in research: Delphi consensus study. BMJ Med. 1 , e000247 (2022). This paper developed international consensus on the definition and measurement of multimorbidity in research.

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This is a summary of: Gregg, E. W. et al. The burden of diabetes-associated multiple long-term conditions on years of life spent and lost. Nat. Med . https://doi.org/10.1038/s41591-024-03123-2 (2024).

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WHAT IS ALREADY KNOWN ON THIS TOPIC

WHAT THIS STUDY ADDS

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

Introduction

Analysing the retail food environment

Previous literature reviews

Obesity and the food environment

Supplemental material

Risk of bias and quality assessment criteria

Spatial and statistical methods and study design appraisal

Meta-analysis

Statistical and geographical methods

Study design

Quality and bias assessment of studies

Implications for policymakers and urban planners

Strengths and limitations

Ethics statements

Ethics approval

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Tackling unhealthy food and obesity: how far will the new Labour government go?

The need for wider action

Taking a whole government approach

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Introduction

Methodology

Ethical Approval and Informed Consent

Definition of Childhood Obesity

Physiology of Energy Regulation and Obesity

Etiology and Risk Factors

Health Effects of Childhood Obesity

Psychological Consequences of Obesity

Asthma and Obesity

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Prevention and Control

Treatment of Obesity and the Physiology of Energy Regulation

Years lived with and years lost to multiple long-term condition combinations that include diabetes

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