Overweight is a physiological condition defined by the World Health Organization as abnormal or excessive fat accumulation that presents a health risk, typically measured in adults by a body mass index (BMI) of 25.0 to 29.9 kilograms per square meter.[1][2] This metric, calculated as weight in kilograms divided by height in meters squared, serves as a population-level screening tool despite limitations in distinguishing between fat and lean mass or accounting for body composition variations.[3]Globally, overweight prevalence has risen dramatically, contributing to the combined overweight and obesity rates affecting over two-fifths of adults as of recent estimates, with more than one billion individuals classified as obese alone in 2022.[4][5] In the United States, approximately 30.7% of adults fall into the overweight category, separate from the 40.3% deemed obese during 2021–2023.[6][7] This epidemic correlates with urbanization, sedentary lifestyles, and processed food availability, though empirical data underscore a fundamental caloric imbalance as the proximal cause—intake exceeding expenditure over time.[8]Causal factors include genetic heritability (estimated at 40–70%), but behavioral elements like insufficient physical activity and high-energy-density diets predominate in modifiable risk, with evidence from longitudinal studies showing sustained energy surplus drives adipose tissue expansion.[8][9] Health consequences encompass increased incidence of type 2 diabetes, hypertension, dyslipidemia, and cardiovascular events, with meta-analyses confirming dose-dependent risks even within the overweight BMI range, independent of smoking or other confounders.[10][11] Controversies persist regarding BMI's precision for athletes or metabolically healthy overweight individuals, yet population data affirm excess adiposity's role in systemic inflammation and insulin resistance as key mediators of morbidity.[12]
Definition and Classification
Body Mass Index Criteria
Body mass index (BMI) is calculated as an individual's body weight in kilograms divided by the square of their height in meters (kg/m²).[13] The World Health Organization (WHO) and Centers for Disease Control and Prevention (CDC) classify adults aged 20 years and older as overweight when their BMI falls between 25.0 and 29.9 kg/m².[14][3]These thresholds originated from epidemiological studies linking BMI ranges to increased mortality and morbidity risks, with the 25 kg/m² cutoff for overweight established through analyses of population data by researchers including Ancel Keys in the 1970s, later formalized by WHO expert consultations in the 1990s.[15] For obesity, BMI is subdivided into classes: class 1 (30.0–34.9 kg/m²), class 2 (35.0–39.9 kg/m²), and class 3 (≥40.0 kg/m²), reflecting escalating health risks.[3][16]
BMI Category
BMI Range (kg/m²)
Underweight
<18.5
Normal weight
18.5–24.9
Overweight
25.0–29.9
Obesity (Class 1)
30.0–34.9
Obesity (Class 2)
35.0–39.9
Obesity (Class 3)
≥40.0
WHO recognizes ethnic-specific adjustments due to varying body compositions; for example, overweight thresholds are lowered to ≥23 kg/m² for Asian populations based on higher risks at lower BMIs observed in regional studies.[17] These criteria apply primarily to adults; pediatric classifications use age- and sex-specific percentiles rather than fixed BMI values.[18]
Limitations and Alternative Metrics
Body mass index (BMI) fails to differentiate between fat mass and lean mass, leading to misclassification of individuals with high muscle content, such as athletes, as overweight or obese despite low adiposity levels.[19] This limitation arises because BMI is a height-weight ratio proxy rather than a direct measure of body composition, resulting in overestimation of risk for muscular populations and underestimation for those with sarcopenic obesity, where fat replaces muscle.[20] Additionally, BMI does not account for fat distribution, overlooking the greater health risks posed by visceral adipose tissue accumulation in the abdomen compared to peripheral subcutaneous fat.[21]BMI's predictive accuracy for adverse outcomes varies by age, sex, ethnicity, and socioeconomic factors; for instance, it underperforms in older adults due to age-related muscle loss and in certain ethnic groups with higher body fat at equivalent BMI levels, such as Asian populations.[19] The American Medical Association has recommended against relying solely on BMI for obesity assessment, citing its inability to capture metabolic health or the "obesity paradox," where some overweight individuals exhibit lower mortality than normal-weight counterparts with poor fitness.[22] At a population level, BMI correlates with body fat and health risks but lacks precision for individual clinical decisions, prompting calls for integrated metrics.[23]Waist circumference (WC) serves as an alternative by directly measuring abdominal obesity, a stronger predictor of cardiometabolic risks like type 2 diabetes and cardiovascular disease than BMI, as it reflects visceral fat volume independently of total body weight.[24] Thresholds include greater than 102 cm for men and 88 cm for women in Western populations, though adjustments for ethnicity improve accuracy.[25] Waist-to-hip ratio (WHR), calculated as WC divided by hip circumference, further refines this by assessing fat distribution patterns; values exceeding 0.90 for men and 0.85 for women indicate central adiposity and outperform BMI in forecasting all-cause mortality and liver-related outcomes.[26][27]Waist-to-height ratio (WHtR), obtained by dividing WC by height, provides a simple, ethnicity-agnostic metric with a universal threshold of 0.5 signaling elevated risk, demonstrating superior prediction of hypertension and physical performance decline over BMI or WHR in prospective cohorts.[28] Body fat percentage (BF%), measured via methods like dual-energy X-ray absorptiometry (DEXA) or bioelectrical impedance analysis (BIA), offers direct quantification of adiposity; for adults, thresholds above 25% for men and 32% for women denote excess fat, correlating more closely with metabolic dysfunction than BMI in diverse populations.[29] Emerging indices like the body roundness index (BRI), which incorporates WC and height into a geometric model of fat distribution, show promise in clinical validation for risk stratification beyond BMI.[30]
Combining these metrics with BMI enhances overall accuracy, as recommended in recent guidelines emphasizing multifactorial assessment for personalized health risk evaluation.[31]
Biological Foundations
Evolutionary Purpose of Fat Storage
Adipose tissue in humans primarily functions as a dynamic energyreservoir, storing excess caloric intake as triglycerides to sustain survival during periods of food scarcity, a selective pressure dominant in Pleistocene environments characterized by intermittent famines and variable resource availability.[32] This adaptation allowed ancestral populations to endure extended low-energy states, with physiological mechanisms like insulin-mediated lipogenesis promoting efficient fat deposition during feast phases.[33] Comparative analyses across mammals indicate that such storage buffered against starvation risks, conferring reproductive advantages to individuals capable of maintaining homeostasis amid caloric deficits.[34]Humans exhibit uniquely high baseline adiposity relative to other primates—averaging 15-20% body fat in non-obese adults versus under 5% in lean chimpanzees—likely evolved to support energetically costly traits like expanded brain size (comprising 2% of body mass but demanding 20% of basal metabolic rate) and prolonged offspring dependency.[35] Gluteofemoral subcutaneous fat depots, particularly in females, provide localized reserves of polyunsaturated fatty acids essential for fetal and neonatal brain development, enhancing offspring viability in hunter-gatherer contexts.[32] Bipedalism further necessitated fat cushions for joint protection and endurance during long-distance foraging, with evolutionary models suggesting optimal fat levels balanced energy surplus against mobility costs.[33]The thrifty gene hypothesis, proposed by James Neel in 1962, posits that genetic variants favoring rapid fat accrual and insulin resistance were positively selected in ancestral populations facing feast-famine cycles, explaining modern obesity predispositions under constant abundance.[36] While genome-wide association studies have identified alleles linked to metabolic thriftiness, such as those influencing leptin signaling, direct causal evidence remains limited, with critiques highlighting insufficient population-level support from candidate gene analyses and alternative explanations like drift or predation trade-offs.[37][38] Mathematical simulations indicate that thrifty traits yield fitness benefits only when paired with behavioral cues for overconsumption, underscoring context-dependence.[39]Beyond energy, fat storage offered ancillary purposes: thermal insulation against cold exposure in migratory hominins, mechanical padding for vital organs during falls or combat, and endocrine regulation via adipokines like adiponectin to modulate inflammation and reproduction.[32] These multifaceted roles optimized survival in paleoenvironments, where moderate adiposity (e.g., 20-25% in females) correlated with higher fertility and longevity, though excess risked heightened predation or infection vulnerability.[33] In sum, fat accumulation represented a calibrated evolutionary strategy for resilience, maladaptive primarily in post-agricultural surpluses.[34]
Genetic and Metabolic Variations
Heritability estimates for body mass index (BMI) and obesity, derived from twin, family, and adoption studies, range from 40% to 70%, indicating a substantial genetic component to individual differences in body weight.[40][41] Genome-wide association studies (GWAS) have identified over 1,000 genetic loci associated with adiposity traits, though these collectively explain only a modest portion of variance, underscoring the polygenic nature of common overweight and obesity.[40] Rare monogenic forms, such as those involving mutations in the melanocortin 4 receptor (MC4R) gene, account for up to 5% of severe early-onset obesity cases and are characterized by hyperphagia, increased linear growth, and reduced energy expenditure due to impaired hypothalamic signaling.[42][43]The fat mass and obesity-associated (FTO) gene represents one of the strongest common genetic contributors, with risk alleles (e.g., rs9939609) linked to 20-30% increased odds of obesity through mechanisms enhancing appetite and reducing satiety, independent of physical activity levels.[44][45] These variants influence hypothalamic expression and RNA demethylation processes that modulate energy homeostasis, with homozygous carriers showing approximately 1-3 kg higher body weight on average across populations.[46] Other loci, including those near MC4R, BDNF, and POMC, overlap with monogenic pathways, suggesting shared biological mechanisms like leptin-melanocortin signaling disruptions that favor fat storage over expenditure.[47]Metabolic variations, often genetically influenced, include differences in resting energy expenditure (REE) and basal metabolic rate (BMR), which account for 60-75% of daily energy needs and vary by up to 20-30% between individuals matched for age, sex, and body composition.[48] Fat-free mass explains the largest share of BMR variance (about 60-70%), but residual differences persist due to factors like thyroid hormone levels and familial aggregation, with lower REE observed in some overweight-prone families potentially exacerbating positive energy balance.[49][50] However, longitudinal data indicate that sub-predicted BMR does not consistently predict greater weight gain, suggesting metabolic adaptations interact dynamically with dietary intake rather than acting as a sole causal driver.[51]The thrifty gene hypothesis posits that alleles promoting efficient energy conservation and fat deposition conferred survival advantages during ancestral periods of feast-famine cycles but now contribute to overweight in energy-abundant environments; evidence includes population-specific variants in Pima Indians and some GWAS hits, though the idea remains debated due to inconsistent famine-selection signatures in human genomes.[52][53] Overall, genetic and metabolic factors predispose but do not determine overweight, as effect sizes are small and require environmental triggers like caloric surplus for phenotypic expression.[40]
Primary Causes
Energy Balance and Dietary Factors
Overweight arises from a sustained positive energy balance, wherein chronic excess of energy intake over expenditure results in adipose tissue accumulation. This fundamental principle, rooted in the first law of thermodynamics applied to human physiology, posits that body weight stability requires energy intake to match total daily energy expenditure, which includes basal metabolic rate, physical activity, and thermic effects of food. Empirical data from doubly labeled water studies confirm that population-level weight gain correlates with rising energy intake rather than declining expenditure, as evidenced by stable or slightly increased physical activity trends amid escalating obesity rates since the 1970s.[54][55]Dietary factors predominantly drive this imbalance by influencing intake volume, palatability, and metabolic responses. Ultra-processed foods, characterized by high levels of added sugars, refined starches, unhealthy fats, and low fiber, promote overconsumption through hyper-palatability and rapid digestibility, leading to higher caloric intake without compensatory satiety signals. Prospective cohort studies and randomized trials link higher ultra-processed food consumption—often exceeding 50% of daily calories in Western diets—to a 20-50% increased risk of overweight, independent of total energyintake. Conversely, diets rich in whole foods such as vegetables, fruits, legumes, and nuts exhibit inverse associations with overweight risk, attributed to greater fiber content and lower energy density that enhance satiation per calorie consumed.[56][57][58]Debates persist regarding macronutrient composition's role beyond total calories. The conventional energy balance model emphasizes overeating as the primary driver, with dietary excess directly causing fat storage regardless of source. However, the carbohydrate-insulin model proposes that high-glycemic-load carbohydrates—prevalent in refined grains and sugars—elevate postprandial insulin, partitioning nutrients toward fat storage and suppressing fat oxidation, thereby fostering a feedback loop of increased hunger and intake. Controlled feeding studies show that low-glycemic diets can reduce ad libitum energy intake by 200-500 kcal/day compared to high-glycemic equivalents, supporting causal effects of carbohydrate quality on energy balance, though large-scale trials yield mixed results challenging full endorsement of this paradigm.[59][60][61]Environmental shifts, including wider availability of energy-dense, processed foods since the late 20th century, amplify these dietary influences. National surveys indicate that average daily caloric intake rose by 200-300 kcal from the 1970s to 2000s, coinciding with processed food proliferation, while expenditure changes explain only a fraction of the attributable variance in population weight gain. These patterns underscore dietary composition's outsized contribution to positive energy balance, beyond mere caloric surplus.[62][63]
Behavioral and Lifestyle Influences
Sedentary behavior, defined as prolonged periods of sitting or reclining with low energy expenditure, independently contributes to overweight independent of overall physical activity levels. A meta-analysis of 111,851 individuals with obesity reported a combined prevalence of sedentary behavior at 31% (95% CI, 23-41%), highlighting its commonality in this population. Longitudinal evidence indicates that high levels of sedentary time, such as television watching, elevate the risk of obesity and type 2 diabetes in women.[64][65]Low physical activity exacerbates energy imbalance and promotes weight gain over time. In a 20-year prospective study, adults maintaining high physical activity levels experienced smaller increases in BMI (0.08 units less) and waist circumference (0.77 cm less) compared to those with low activity. Systematic reviews of longitudinal data confirm that moderate-to-vigorous physical activity minimizes weight gain in adults, with inverse associations observed between activity changes and BMI increases.[66][67][68]Short sleep duration is associated with elevated overweight risk through mechanisms including hormonal dysregulation of appetite. Population-based studies show short sleep linked to higher BMI and obesity prevalence, with one analysis finding females with short sleep facing 2.59 times higher obesity odds compared to normal sleepers. Prospective data further tie shorter durations to central obesity, though long sleep shows weaker or null associations.[69][70][71]Chronic stress influences overweight via emotional eating and cortisol-mediated fat storage. Human studies demonstrate that acute and chronic stress exposure triggers binge eating, particularly of high-calorie foods, contributing to positive energy balance. Longitudinal research links long-term stress to higher obesity levels, with affected individuals showing greater propensity for overeating in response to negative affect.[72][73][74]In adolescents and children, excessive screen time correlates with overweight through reduced activity and increased snacking. Systematic reviews and meta-analyses establish screen time as a risk factor, with highest exposure categories showing 1.2 times greater obesity odds; dose-response analyses confirm positive associations without clear thresholds. Interventions targeting screen reduction alone, however, yield limited direct effects on body weight, underscoring multifactorial influences.[75][76][77]
Environmental and Genetic Contributors
Twin studies indicate that genetic factors account for 40-80% of the variance in body mass index (BMI), with heritability estimates varying by age, sex, and population. For instance, a 1990 study of monozygotic twins reared apart found that genetic influences on BMI were substantial, while shared childhood environment had minimal impact. More recent analyses confirm this, showing heritability increasing from adolescence to adulthood, with genetic contributions explaining up to 70% of BMI stability over time.[78][79][80]Specific genetic variants strongly associate with overweight risk. The FTO gene's rs9939609 polymorphism is linked to higher BMI and obesity across ethnic groups, influencing appetite regulation and fat mass. Similarly, MC4R gene mutations, particularly rs17782313, contribute to monogenic obesity by disrupting melanocortin signaling in the hypothalamus, leading to hyperphagia; rare variants account for 2-5% of severe early-onset cases. Genome-wide association studies have identified over 1,000 loci influencing BMI, underscoring polygenic inheritance, though individual variants explain only small effect sizes. Gene-environment interactions modulate these effects, with heritability of BMI higher in low-obesogenic settings.[81][82][40][83]Environmental contributors extend beyond individual diet and activity to broader obesogenic contexts that promote energy surplus. Urban designs favoring sedentary transport, such as car-dependent infrastructure, correlate with higher BMI prevalence compared to walkable communities. Food environments rich in ultra-processed, high-calorie options—facilitated by aggressive marketing and availability—drive overconsumption, independent of personal choices. Socioeconomic disparities amplify this, with lower-income areas often featuring denser fast-food outlets and fewer healthy alternatives.[84][57][85]Chemical exposures, including endocrine-disrupting compounds (EDCs) like bisphenol A (BPA) and phthalates, elevate obesity risk by altering adipogenesis, lipid metabolism, and appetite control. Prenatal or early-life EDC exposure associates with increased fat mass in cohort studies, potentially via peroxisome proliferator-activated receptor gamma activation in adipose tissue. Air pollution and traffic noise also link to weight gain; particulate matter induces inflammation and hypothalamic dysregulation, while bedroom noise disrupts sleep, indirectly promoting obesity through elevated cortisol. Chronic sleep restriction, common in shift-work or screen-heavy lifestyles, impairs leptin sensitivity and boosts ghrelin, fostering hunger and metabolic inefficiency. Stress responses, via glucocorticoid elevation, similarly favor visceral fat accumulation. These factors interact with genetics, as susceptible individuals in high-exposure environments show amplified BMI variance.[86][87][88][89]
Health Consequences
Disease Risks and Mechanisms
Overweight, defined as a body mass index (BMI) of 25.0–29.9 kg/m², is associated with elevated risks of several chronic diseases, including type 2 diabetes, cardiovascular disease, and certain cancers, though the magnitude of risk is generally lower than for obesity (BMI ≥30 kg/m²).[90] A systematic review of prospective studies found that overweight individuals have a 1.3- to 1.5-fold increased risk of developing type 2 diabetes compared to those with normal BMI, driven by progressive beta-cell dysfunction and insulin resistance.[90] For cardiovascular disease, meta-analyses indicate that overweight confers a 20–40% higher relative risk of coronary artery disease events, independent of other factors like smoking or hypertension, with risks manifesting through accelerated atherosclerosis.[91] Overweight also elevates the incidence of osteoarthritis, particularly in weight-bearing joints, by 1.5- to 2-fold due to mechanical overload on cartilage.[92]The primary mechanisms linking overweight to metabolic diseases involve adipose tissue expansion and dysfunction, leading to ectopic fat deposition in liver and muscle, which impairs insulin signaling.[93] Excess adiposity promotes chronic low-grade inflammation via macrophage infiltration into adipose tissue, elevating pro-inflammatory cytokines such as tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6), which exacerbate insulin resistance and endothelial dysfunction.[94] Dysregulated adipokine secretion—characterized by increased leptin (promoting appetite and angiogenesis) and decreased adiponectin (which normally enhances insulin sensitivity)—further contributes to hyperglycemia and hyperinsulinemia, creating a feedback loop that heightens type 2 diabetes risk.[93]In cardiovascular pathology, overweight-induced visceral fat accumulation correlates with dyslipidemia (elevated triglycerides and small, dense LDL particles) and hypertension, fostering plaque formation through oxidative stress and vascular smooth muscle proliferation.[91] Hemodynamic changes, including increased blood volume and cardiac output, strain the myocardium, predisposing to left ventricular hypertrophy and heart failure with preserved ejection fraction.[95] For cancer, mechanisms include hyperinsulinemia stimulating cell proliferation via insulin-like growth factor-1 (IGF-1) pathways, alongside estrogen excess from aromatization in adipose tissue, which is implicated in postmenopausal breast and endometrial cancers; epidemiological data link overweight to a 10–20% increased risk for these malignancies.[94] Additionally, obesity-related inflammation activates nuclear factor-kappa B (NF-κB) signaling, promoting oncogenesis in colorectal and other sites.[96] These pathways underscore a causal continuum where even moderate excess adiposity initiates systemic perturbations favoring disease onset.[97]
Mortality and the Overweight Paradox
The overweight paradox denotes the recurrent observation in clinical cohorts with chronic illnesses—such as cardiovascular disease, cancer, or infections—where overweight individuals (BMI 25.0–29.9 kg/m²) show reduced all-cause mortality relative to normal-weight counterparts (BMI 18.5–24.9 kg/m²).[98][99] This pattern, often extending to mild obesity, has been documented across meta-analyses; for example, in acute coronary syndrome patients, overweight status conferred a mortality relative risk of 0.70 (95% CI 0.64–0.76).[98] Comparable inverse associations appear in ST-elevation myocardial infarction post-percutaneous coronary intervention (lower short-term mortality in overweight/obese), pneumonia (reduced risk in overweight/obese), and catheter-related thrombosis (obesity paradox with lower all-cause mortality).[100][101][102]In general populations without baseline disease, however, no such paradox exists; prospective data from millions of participants reveal a J-shaped BMI-mortality curve, with minimal risk at BMI 20–25 kg/m² and graded elevations thereafter, yielding hazard ratios of 1.07 (95% CI 1.04–1.10) for overweight and higher for obesity, even excluding smokers and early deaths.30175-1/fulltext)[103][104]Explanations for the clinical paradox emphasize artifacts over causality: reverse causation, where occult disease induces pre-diagnostic weight loss (misclassifying high-risk individuals as normal weight), and smoking-related confounding (thinner smokers inflate normal-weight mortality).[105][106] Conditioning on disease onset introduces collider bias, amplifying spurious protections for higher BMI.[107] Sensitivity analyses excluding deaths within 5–10 years or adjusting for weight history often nullify the effect, restoring alignment with adiposity's pathogenic role in inflammation, insulin resistance, and cardiorespiratory strain.[105]30175-1/fulltext)Alternative interpretations invoke body composition—higher muscle mass in some overweight individuals conferring resilience—or metabolic reserves aiding recovery, but BMI's inability to differentiate fat from lean mass limits these claims, and fat-centric risks predominate in mechanistic studies.[108][99] Thus, the paradox underscores measurement pitfalls rather than upending evidence that sustained overweight elevates long-term mortality via cumulative metabolic burden.[109]30288-2/fulltext)
Potential Protective Effects in Specific Contexts
In patients with heart failure, overweight body mass index (BMI) levels (25–29.9 kg/m²) have been associated with lower all-cause mortality compared to normal BMI (18.5–24.9 kg/m²), a pattern observed across multiple meta-analyses of cohort studies involving thousands of participants.[110] This counterintuitive survival advantage, part of the broader obesity paradox, persists after adjustments for age, sex, and comorbidities, though potential confounders like cardiorespiratory fitness or reverse causation—where sicker patients lose weight prior to diagnosis—may contribute.[111] Proposed mechanisms include greater metabolic reserves during catabolic states and reduced frailty, but randomized evidence remains absent, limiting causal attribution.[112]Among individuals with chronic obstructive pulmonary disease (COPD), overweight BMI correlates with improved survival rates relative to underweight or normal BMI groups, as evidenced by longitudinal analyses of clinical registries.[113] For instance, a study of over 5,000 COPD patients found that those overweight had a 20–30% lower risk of respiratory mortality, potentially due to enhanced nutritional status buffering against exacerbations or muscle wasting.[114] This effect holds in adjusted models accounting for lung function and smoking history, though it diminishes in severe obesity (BMI ≥30 kg/m²), suggesting a U-shaped risk curve specific to moderate excess weight.[115] Critics attribute part of this to diagnostic biases, such as underestimation of airflow obstruction in overweight patients, but empirical data consistently show hazard ratios below 1.0 for overweight categories.[116]In older adults, overweight BMI appears protective against mortality linked to frailty, with cohort studies reporting 15–25% reduced all-cause death risks compared to normal BMI in community-dwelling individuals aged 65 and above.[117] This association strengthens in frail subgroups, where excess adiposity may provide energy buffers against sarcopenia and falls, as supported by analyses of over 10,000 elderly participants followed for up to a decade.[118] For example, higher BMI mitigated postsurgical mortality risks in geriatric patients undergoing major procedures, independent of comorbidities.[119] However, midlife obesity elevates later frailty incidence, indicating context-specific benefits rather than universal protection, with visceral fat distribution modulating outcomes more than BMI alone.[120]Overweight BMI also correlates with better outcomes in trauma and critical illness settings, where meta-analyses of registry data show overweight patients experiencing 10–20% lower in-hospital mortality than normal-weight counterparts, possibly from adipose-derived energy during hypermetabolic stress.[121] Similar patterns emerge in select infections and acute respiratory distress syndrome, though recent trials question robustness amid ventilator challenges in obesity.[122] These findings, drawn from diverse populations, highlight overweight's role in resilience under acute catabolic demands but underscore the need for prospective studies to disentangle selection effects from true causality.[112]
Epidemiology and Trends
Global and Regional Prevalence
In 2022, 43% of adults aged 18 years and older worldwide—equivalent to approximately 2.5 billion individuals—were overweight, defined by a body mass index (BMI) of 25 kg/m² or greater.[4][123] This encompasses both the overweight range (BMI 25–29.9 kg/m²) and obesity (BMI ≥30 kg/m²), with the latter affecting 16% of adults or about 890 million people.[4] Among children and adolescents, prevalence is lower but increasing; an estimated 159 million aged 5–19 years were overweight or obese in 2022, representing over 8% for obesity alone in that group.[4][124] These figures derive from modeled estimates incorporating population surveys and vital registration data, though underreporting in low-resource settings may underestimate true burdens.02750-2/fulltext)Prevalence exhibits stark regional variations, driven by differences in dietary patterns, urbanization, and socioeconomic factors. In the WHO Region of the Americas, 67.5% of adults were overweight or obese in 2022, the highest regional rate, with country-level examples including the United States where over 70% of adults exceed BMI 25 based on national surveys.[125][6] In contrast, rates remain lower in the WHO African Region, with age-standardized overweight prevalence typically below 30%, though rapid urbanization is accelerating increases in urban populations.00355-1/fulltext) High prevalences also characterize parts of the Eastern Mediterranean and Western Pacific regions, particularly Oceania, where some nations exceed 80% adult overweight due to imported processed foods and genetic predispositions to fat storage.00355-1/fulltext)Within regions, disparities persist by sex, age, and income level; for instance, women often show higher obesity sub-prevalence globally (17% vs. 14% in men), while high-income countries report overweight rates over 60% across adults aged 30–70.[4] 00355-1/fulltext) Data from the NCD Risk Factor Collaboration highlight that, as of 2021, over 2.1 billion adults aged 25 and older were affected globally, with the largest absolute numbers in China (over 400 million) and India (over 180 million), reflecting population size despite varying per capita rates.[126] These estimates, drawn from over 3,000 representative surveys, underscore the need for context-specific BMI interpretations, as standard cutoffs may overestimate risk in some Asian populations with higher body fat at lower BMIs.00355-1/fulltext)
Historical Rise and Recent Shifts
In the United States, adult obesity prevalence (BMI ≥30 kg/m²) stood at approximately 13% during 1960–1962, while overweight (BMI 25–29.9 kg/m²) affected about 31% of adults.[127] By 2017–2018, obesity had surged to 42.4%, with severe obesity (BMI ≥40 kg/m²) reaching 9.2%, whereas overweight prevalence remained relatively stable at around 31%.[6] This pattern reflects a broader shift where excess adiposity transitioned from moderate overweight to clinical obesity, tripling overall rates of BMI ≥30 over six decades.[128]Globally, overweight and obesity rates exhibited a marked escalation beginning in the late 20th century, with adult obesity prevalence more than tripling from 1975 to 2022.[129] The World Health Organization reports that obesity among adults more than doubled between 1990 and 2022, driven initially by transitions in high-income nations and subsequently accelerating in low- and middle-income countries amid urbanization and dietary shifts.[4] By 2021, an estimated 43.4% of adults worldwide were overweight or obese, up from lower baselines in the mid-20th century when caloric availability averaged around 2,200 kcal per person daily in the 1960s.[5][130]Recent trends indicate a plateau or deceleration in obesity rates among adults in several high-income countries since the early 2010s, contrasting with continued rises elsewhere. In the US, adult obesity stabilized at approximately 40.3% from 2021–2023, following a peak estimate of 41.9% in 2020 and no significant growth from prior years.[7] Similar stabilizations have occurred in parts of Europe and other developed regions, with evidence suggesting a slowdown in the overall epidemic trajectory over the past decade.[131] For children and adolescents in economically advanced countries, prevalence has leveled off since around 2000–2010, potentially due to public health interventions targeting early-life factors, though global youth rates continue to climb.[132][133] Forecasts project sustained increases in developing regions, with global adult overweight and obesity potentially reaching 57.4% by mid-century absent major reversals.[134]
Prevention and Treatment Strategies
Lifestyle Modifications
Lifestyle modifications represent the foundational approach to managing overweight, centering on achievable caloric deficits through dietary restraint and enhanced energy expenditure via physical activity, with behavioral techniques to foster long-term adherence. Comprehensive programs combining these elements typically yield 5-10% body weight reduction in the first year among adults with overweight, though maintenance beyond 12 months averages 3-5% without reinforcement.[135][136]Dietary strategies prioritize moderate caloric restriction of 500-1,000 kcal per day below maintenance needs, which promotes gradual fat loss of 0.5-1 kg weekly while minimizing muscle catabolism and metabolic adaptation. Meta-analyses indicate that low-calorie diets, irrespective of macronutrient ratios (e.g., low-fat versus low-carbohydrate), produce comparable short-term weight reductions of 8-10% over 6-12 months, with superiority emerging in adherence-friendly patterns like Mediterranean-style eating that emphasize nutrient-dense whole foods over processed items.[137][138] Long-term efficacy hinges on personalization to avoid compensatory hyperphagia, as unrestricted low-fat approaches often underperform due to higher glycemic loads stimulating insulin spikes and hunger.[139]Incorporating physical activity amplifies dietary effects by increasing total daily energy expenditure and preserving lean body mass, with guidelines endorsing 150-300 minutes weekly of moderate aerobic exercise (e.g., brisk walking or cycling) plus two sessions of resistancetraining. Systematic reviews confirm that such regimens alone induce modest weight loss of 1-3 kg over 6-12 months in overweight individuals, but combined with diet, they enhance fat-specific reductions by 20-30% and mitigate regain risk through improved insulin sensitivity and appetite regulation.[140][141]Resistance exercises particularly counteract sarcopenia, as aerobic-only protocols show limited impact on body composition without strength components.[142]Behavioral interventions, often delivered via structured programs like cognitive-behavioral therapy or intensive lifestyle coaching, target habit formation through self-monitoring (e.g., food diaries), goal-setting, and stimulus control to curb environmental cues for overeating. These yield sustained outcomes by boosting compliance, with trials demonstrating 2-4 kg greater long-term weight loss compared to diet-exercise alone, though dropout rates exceed 20-30% without social support or digital tracking tools.[143][144]Auxiliary factors such as sleep optimization (aiming for 7-9 hours nightly) and stress reduction via mindfulness or routine disruption minimization address neuroendocrine drivers of adiposity, as chronicsleep restriction elevates ghrelin and cortisol, fostering 300-500 extra daily calories via heightened appetite.[145][146] Interventions improving these domains independently support 1-2 kg additional loss, underscoring their role in holistic management despite secondary emphasis in protocols.[147] Overall, while initial successes are common, recidivism affects 80% within five years, necessitating indefinite vigilance rooted in caloric thermodynamics over fad-driven narratives.[148]
Medical Interventions and Efficacy
Medical interventions for overweight primarily encompass pharmacotherapies approved for individuals with a body mass index (BMI) of 27 or higher accompanied by at least one weight-related comorbidity, such as hypertension, dyslipidemia, or prediabetes, though efficacy data often derive from trials including those with obesity (BMI ≥30).[149] These agents function via mechanisms including appetite suppression, delayed gastric emptying, reduced fat absorption, or central nervous system modulation of hunger signals, and are intended as adjuncts to lifestyle modifications rather than standalone cures.[149] Long-term maintenance typically requires indefinite use, as discontinuation frequently results in substantial weight regain, with trials showing 50-70% of lost weight returning within one year off therapy.[150]Glucagon-like peptide-1 (GLP-1) receptor agonists and dual GLP-1/glucose-dependent insulinotropic polypeptide (GIP) agonists represent the most efficacious class, achieving placebo-adjusted total body weight loss (TBWL) of 11-20% over 52-104 weeks in randomized controlled trials (RCTs).[151]Semaglutide (2.4 mg weekly) yields a mean TBWL of approximately 15% at 68 weeks, with 68% of participants achieving ≥5% loss and 44% ≥10% at two years; in the four-year SELECT trial among those without diabetes, on-treatment loss averaged 11.7%, though in-trial results (including dropouts) were 10.2%.[152][150]Tirzepatide (up to 15 mg weekly) demonstrates superior outcomes, with 16-21% placebo-adjusted TBWL and up to 90% achieving ≥5% loss, outperforming semaglutide in head-to-head comparisons for obesity without diabetes.[151][153]Liraglutide (3 mg daily), an earlier GLP-1 agonist, produces 4-8% TBWL, with 65% reaching ≥5% loss but lower rates for ≥10%.[151] Gastrointestinal adverse effects, including nausea and vomiting, occur in 20-40% of users, contributing to discontinuation rates of 15-25%, though cardiovascular risk reduction has been observed with semaglutide.[150][149]Older and combination pharmacotherapies offer more modest efficacy. Orlistat (120 mg three times daily), a lipase inhibitor reducing dietary fat absorption by about 30%, results in 2-3% placebo-adjusted TBWL over one year, with 30% achieving ≥5% loss but higher gastrointestinal side effects like steatorrhea limiting adherence.[151] Phentermine, a short-term sympathomimetic appetite suppressant (typically ≤12 weeks), induces 5-10% initial loss but lacks robust long-term data due to regulatory restrictions and potential cardiovascular risks.[154] The phentermine-topiramate extended-release combination achieves 8-9% TBWL, with 70% reaching ≥5% and 45% ≥10%, though central nervous system effects such as insomnia and paresthesia elevate dropout to around 25%.[151] Naltrexone-bupropion (up to 32 mg/360 mg daily), targeting reward pathways, yields 4-6% TBWL, with neuropsychiatric risks including mood disturbances.[151][149]
Overall, while newer incretin-based therapies substantiate clinically meaningful weight reduction—defined as ≥5% for metabolic benefits—their high cost, supply constraints, and requirement for subcutaneous administration limit accessibility, and real-world adherence remains suboptimal compared to trial settings.[149] No pharmacotherapy eradicates underlying drivers of overweight, underscoring the necessity of concurrent behavioral interventions for sustained outcomes.[149]
Surgical Options and Long-Term Outcomes
Bariatric surgery, also known as metabolic surgery, is generally reserved for patients with severe obesity, defined as BMI ≥40 kg/m² or BMI ≥35 kg/m² with obesity-related comorbidities such as type 2 diabetes or cardiovascular disease, rather than for overweight individuals (BMI 25-29.9 kg/m²) who typically do not meet eligibility criteria due to insufficient risk-benefit ratio.[155][156] Common procedures include Roux-en-Y gastric bypass (RYGB), which reroutes the small intestine to reduce nutrientabsorption and stomach size; sleeve gastrectomy (SG), involving removal of about 80% of the stomach to limit food intake; adjustable gastric banding (AGB), which places an inflatable band around the upper stomach; and biliopancreatic diversion with duodenal switch (BPD/DS), combining sleeve resection with intestinal bypass for malabsorption.[156][157] These interventions aim to achieve sustained weight loss and comorbidity remission through restrictive, malabsorptive, or combined mechanisms, with RYGB and SG being the most commonly performed worldwide as of 2023.[158]Long-term weight loss outcomes vary by procedure but demonstrate superiority over non-surgical interventions in meta-analyses of studies with ≥10-year follow-up. RYGB and SG typically yield 50-70% excess weight loss (%EWL) sustained at 10 years, with RYGB showing slightly better durability (mean %EWL 56%) compared to SG (mean %EWL 51%), though weight regain occurs in 20-30% of patients after 5 years due to behavioral or physiological factors.[159][160] AGB results in lower %EWL (40-50%) and higher revision rates (up to 30%), while BPD/DS achieves the highest %EWL (70-80%) but with greater nutritional risks.[159] Comorbidity remission is substantial: type 2 diabetes remits in 60-80% of cases post-RYGB (higher than SG's 50-70%), hypertension in 50-70%, and dyslipidemia in 60-80%, with benefits persisting 10+ years and reducing cardiovascular events.[160][161] These effects stem from caloric restriction, altered gut hormones (e.g., increased GLP-1), and weight-independent metabolic changes, though not all patients achieve full remission, particularly if diabetes duration exceeds 10 years pre-surgery.[162]Perioperative complications occur in 4-10% of cases, including leaks (1-2% for SG), bleeding, and infections, with 30-day mortality rates of 0.1-0.3% in high-volume centers.[163][164] Long-term risks include nutritional deficiencies (e.g., iron, B12 in 20-30% post-RYGB, requiring lifelong supplementation), gallstone formation (10-25%), and reoperations (10-20% for RYGB/SG, higher for AGB).[165] Despite these, overall mortality decreases by 30-50% compared to non-surgical obese controls over 10-20 years, with adjusted hazard ratios of 0.5-0.7 in large cohorts, attributed to reduced obesity-related diseases rather than procedure-specific effects alone.[164][166] Long-term survival benefits are most pronounced in patients with comorbidities, though smoking, older age, and male sex elevate risks.[167] Outcomes emphasize the need for multidisciplinary follow-up, as adherence to lifestyle changes post-surgery correlates with sustained efficacy.[161]
Controversies and Societal Debates
Body Positivity vs. Health Realism
The body positivity movement emerged in the late 20th century from fat acceptance advocacy, gaining prominence through social media in the 2010s, with the goal of fostering self-acceptance across body sizes and reducing weight-based discrimination, which proponents link to improved psychological well-being.[168] Advocates argue that emphasizing body diversity counters harmful stigma, potentially alleviating stress-related health burdens, though empirical support for broad physical health benefits remains limited and primarily short-term in nature.[169]In contrast, health realism prioritizes physiological evidence demonstrating that excess body fat, particularly visceral adiposity, causally contributes to metabolic dysfunction via mechanisms such as insulin resistance, chronic low-grade inflammation, and endothelial damage, elevating risks for type 2 diabetes, cardiovascular disease, hypertension, and certain malignancies like colorectal and endometrial cancers.[92][4] Meta-analyses of cohort studies confirm that obesity independently predicts higher all-cause mortality, with hazard ratios increasing dose-dependently; for instance, class II-III obesity associates with 1.5-2.5 times greater cardiovascular event risk compared to normal weight, even after adjusting for behaviors like smoking or exercise.[170][171] Proponents of health realism contend that acknowledging these links motivates targeted interventions, as sustained 5-10% weight reduction demonstrably lowers incidence of diabetes by 58% and cardiovascular events by 20-30% in randomized trials.[172]The core tension arises from body positivity's alignment with paradigms like Health at Every Size (HAES), which posits well-being achievable without weight focus through intuitive eating and joyful movement, yet systematic reviews reveal HAES yields modest psychological gains but no superior long-term cardiometabolic outcomes over weight-inclusive approaches, with obesity persistence correlating to persistent risks.[173][174] Studies indicate body-positive messaging inversely relates to weight management intentions; for example, higher body image satisfaction predicts lower dieting efforts among those with elevated BMI, potentially delaying interventions that evidence shows mitigate comorbidities.[175] Critics within health realism highlight that while stigma reduction aids access to care, normalizing obesity without addressing its modifiable causality—evident in dose-response relationships from Mendelian randomization studies—may inadvertently sustain elevated disease burdens, as global obesity prevalence rose to 16% in adults by 2022, paralleling surges in related non-communicable diseases.[134][176]This debate underscores trade-offs: body positivity's emphasis on mental health equity, often amplified in academic and media discourse despite potential underweighting of physiological data, versus health realism's insistence on causal evidence for policy and individual action, where interventions like pharmacotherapy achieve 10-15% weight loss and commensurate risk reductions in recent trials.[177] Empirical prioritization reveals that while no single factor like weight fully determines health, its role as a proximal cause warrants direct targeting to optimize outcomes, challenging narratives that equate acceptance with inaction on verifiable hazards.[172]
Policy Responses and Individual Responsibility
Governments worldwide have pursued various policy responses to address overweight and obesity, including fiscal measures such as taxes on sugar-sweetened beverages (SSBs). Implemented in over 50 countries and jurisdictions by 2025, these taxes have been associated with increased SSB prices by an average of 1.11 times the tax amount and reduced purchases of taxed items by about 10%, according to a 2022 meta-analysis of real-world implementations.[178] However, systematic reviews indicate that while such taxes may modestly lower calorie and sugar intake, their impact on overall obesity prevalence remains limited and not straightforward, with modeling studies projecting prevention of around 240,000 obesity cases over a decade in some contexts but lacking consistent evidence of shifts toward healthier alternatives.[179][180][181]Regulatory and educational interventions, such as mandatory nutrition labeling and school-based programs, form another pillar of policy efforts, as outlined in frameworks like the U.S. Healthy People 2030 objectives, which target reductions in adult obesity through culturally tailored nutrition promotion.[182] Yet, evaluations of these measures, including U.S. state-level legislation on food environments, show no strong association with decreased adolescent BMI or overweight rates, highlighting challenges in translating policy into sustained behavioral change amid environmental obesogenic factors.[183] Critics argue that such "nanny state" approaches risk overreach by prioritizing collective interventions over personal agency, often yielding marginal outcomes while potentially infringing on individual freedoms without addressing core caloric imbalances.[184][185]In contrast, empirical evidence underscores the primacy of individual responsibility in managing overweight, as sustained weight loss predominantly stems from personal adherence to energy-restricted diets and physical activity, independent of broader mandates.[186] A 2020 German survey of over 1,000 adults revealed that 70-80% attributed responsibility for healthy eating primarily to individuals rather than external entities like food industries or governments.[187] Longitudinal studies reinforce this, demonstrating that self-directed lifestyle modifications—such as caloric deficit maintenance—achieve greater long-term efficacy than policy-driven nudges alone, with twin research isolating behavioral choices as key mediators beyond genetic predispositions.[188] While acknowledging environmental influences, effective obesity strategies integrate personal accountability, as narratives emphasizing individual agency alongside social supports foster higher empathy and adherence without diluting causal focus on volitional intake and expenditure.[189]