The obesity epidemic is a global issue and shows no signs of abating, while the cause of this epidemic remains unclear. Marketing practices of energy-dense foods and institutionally-driven declines in physical activity are the alleged perpetrators for the epidemic, despite a lack of solid evidence to demonstrate their causal role. While both may contribute to obesity, we call attention to their unquestioned dominance in program funding and public efforts to reduce obesity, and propose several alternative putative contributors that would benefit from equal consideration and attention. Evidence for microorganisms, epigenetics, increasing maternal age, greater fecundity among people with higher adiposity, assortative mating, sleep debt, endocrine disruptors, pharmaceutical iatrogenesis, reduction in variability of ambient temperatures, and intrauterine and intergenerational effects, as contributing factors to the obesity epidemic are reviewed herein. While the evidence is strong for some contributors such as pharmaceutical-induced weight gain, it is still emerging for other reviewed

Objective: To investigate plausible contributors to the obesity epidemic beyond the two most commonly suggested factors, reduced physical activity and food marketing practices. Design: A narrative review of data and published materials that provide evidence of the role of additional putative factors in contributing to the increasing prevalence of obesity. Data: Information was drawn from ecological and epidemiological studies of humans, animal studies and studies addressing physiological mechanisms, when available. Results: For at least 10 putative additional explanations for the increased prevalence of obesity over the recent decades, we found supportive (although not conclusive) evidence that in many cases is as compelling as the evidence for more commonly discussed putative explanations. Conclusion: Undue attention has been devoted to reduced physical activity and food marketing practices as postulated causes for increases in the prevalence of obesity, leading to neglect of other plausible mechanisms and well-intentioned, but potentially ill-founded proposals for reducing obesity rates.

SummaryCaloric restriction (CR) can delay many age-related diseases and extend lifespan, while an increase in adiposity is associated with enhanced disease risk and accelerated aging. Among the various fat depots, the accrual of visceral fat (VF) is a common feature of aging, and has been shown to be the most detrimental on metabolic syndrome of aging in humans. We have previously demonstrated that surgical removal of VF in rats improves insulin action; thus, we set out to determine if VF removal affects longevity. We prospectively studied lifespan in three groups of rats: ad libitum -fed (AL-fed), CR (Fed 60% of AL) and a group of AL-fed rats with selective removal of VF at 5 months of age (VF-removed rats). We demonstrate that compared to AL-fed rats, VF-removed rats had a significant increase in mean ( p < < < < 0.001) and maximum lifespan ( p < < < < 0.04) and significant reduction in the incidence of severe renal disease ( p < < < < 0.01). CR rats demonstrated the greatest mean and maximum lifespan ( p < < < < 0.001) and the lowest rate of death as compared to AL-fed rats (0.13). Taken together, these observations provide the most direct evidence to date that a reduction in fat mass, specifically VF, may be one of the possible underlying mechanisms of the antiaging effect of CR. Key words: aging; lifespan; obesity; caloric restriction; visceral fat removal.Caloric restriction (CR) extends lifespan in a variety of species (Weindruch, 1996). In contrast, obesity is a major risk factor for several age-related diseases and has been estimated to markedly lessen life expectancy (Fontaine et al ., 2003). Visceral fat (VF) accretion occurs in obesity and with aging, and a reduction in VF is a common phenotypic change in calorie-restricted mammals (Barzilai & Gupta, 1999). VF has been shown to be the single most important determinant of metabolic syndrome (Carr et al ., 2004), and its removal in rats results in improved insulin action and delays the onset of diabetes Gabriely et al ., 2002). Given the hazards associated with abdominal obesity, it seems plausible that the beneficial effects of CR on longevity may be due at least in part to an attenuation of VF (Barzilai & Gupta, 1999). Here we study the effects of VF removal on the lifespan of rats.We prospectively studied lifespan in three groups of rats: ad libitum -fed (AL-fed), CR (Fed 60% of AL) and a group of AL-fed rats with selective removal of VF at 5 months of age (VF-removed rats). At 20 months of age, a subgroup of animals ( n = 8 per group) were killed to assess body fat distribution. There was no significant difference in body weights among all three groups at the beginning of the study (8 weeks of age) nor were body weights significantly different between AL-fed and VF-removed rats throughout their lifespan (Fig. 1A). However, maximal body weight was achieved at an earlier age in AL-fed rats (69 ± 3 weeks; mean ± SD) than in VF-removed rats (79 ± 3 weeks; p < 0.001), indicating a delay in the age-related weight decline in VF-removed animals. Although V...

We identify 10 common errors and problems in the statistical analysis, design, interpretation, and reporting of obesity research and discuss how they can be avoided. The 10 topics are: 1) misinterpretation of statistical significance, 2) inappropriate testing against baseline values, 3) excessive and undisclosed multiple testing and “p-value hacking,” 4) mishandling of clustering in cluster randomized trials, 5) misconceptions about nonparametric tests, 6) mishandling of missing data, 7) miscalculation of effect sizes, 8) ignoring regression to the mean, 9) ignoring confirmation bias, and 10) insufficient statistical reporting. We hope that discussion of these errors can improve the quality of obesity research by helping researchers to implement proper statistical practice and to know when to seek the help of a statistician.

Background Many large-scale epidemiologic data sources used to evaluate the body mass index (BMI: kg/m2) mortality association have relied on BMI derived from self-reported height and weight. Although measured BMI (BMIM) and self-reported BMI (BMISR) correlate highly, self-reports are systematically biased. Objective To rigorously examine how self-reporting bias influences the association between BMI and mortality rate. Subjects Samples representing the US non-institutionalized civilian population. Design and Methods National Health and Nutrition Examination Survey data (NHANES II: 1976-80; NHANES III: 1988-94) contain BMIM and BMISR. We applied Cox regression to estimate mortality hazard ratios (HRs) for BMIM and BMISR categories, respectively, and compared results. We similarly analyzed subgroups of ostensibly healthy never-smokers. Results Misclassification by BMISR among the underweight and obesity ranged from 30–40% despite high correlations between BMIM and BMISR (r>0.9). The reporting bias was moderately correlated with BMIM (r>0.35), but not BMISR (r<0.15). Analyses using BMISR failed to detect six of eight significant mortality HRs detected by BMIM. Significantly biased HRs were detected in the NHANES II full dataset (χ2 = 12.49; p = 0.01) and healthy subgroup (χ2 = 9.93; p = 0.04), but not in the NHANES III full dataset (χ2 = 5.63; p = 0.23) or healthy subgroup (χ2 = 1.52; p = 0.82). Conclusions BMISR should not be treated as interchangeable with BMIM in BMI-mortality analyses. Bias and inconsistency introduced by using BMISR in place of BMIM in BMI-mortality estimation and hypothesis tests may account for important discrepancies in published findings.