BACKGROUND Many beliefs about obesity persist in the absence of supporting scientific evidence (presumptions); some persist despite contradicting evidence (myths). The promulgation of unsupported beliefs may yield poorly informed policy decisions, inaccurate clinical and public health recommendations, and an unproductive allocation of research resources and may divert attention away from useful, evidence-based information. METHODS Using Internet searches of popular media and scientific literature, we identified, reviewed, and classified obesity-related myths and presumptions. We also examined facts that are well supported by evidence, with an emphasis on those that have practical implications for public health, policy, or clinical recommendations. RESULTS We identified seven obesity-related myths concerning the effects of small sustained increases in energy intake or expenditure, establishment of realistic goals for weight loss, rapid weight loss, weight-loss readiness, physical-education classes, breast-feeding, and energy expended during sexual activity. We also identified six presumptions about the purported effects of regularly eating breakfast, early childhood experiences, eating fruits and vegetables, weight cycling, snacking, and the built (i.e., human-made) environment. Finally, we identified nine evidence-supported facts that are relevant for the formulation of sound public health, policy, or clinical recommendations. CONCLUSIONS False and scientifically unsupported beliefs about obesity are pervasive in both scientific literature and the popular press. (Funded by the National Institutes of Health.)

PurposeTo compare the effects of six weeks of high intensity interval training (HIIT) vs continuous moderate intensity training (MIT) for improving body composition, insulin sensitivity (SI), blood pressure, blood lipids, and cardiovascular fitness in a cohort of sedentary overweight or obese young men. We hypothesized that HIIT would result in similar improvements in body composition, cardiovascular fitness, blood lipids, and SI as compared to the MIT group, despite requiring only one hour of activity per week compared to five hours per week for the MIT group.Methods28 sedentary overweight or obese men (age, 20 ± 1.5 years, body mass index 29.5 ± 3.3 kg/m2) participated in a six week exercise treatment. Participants were randomly assigned to HIIT or MIT and evaluated at baseline and post-training. DXA was used to assess body composition, graded treadmill exercise test to measure cardiovascular fitness, oral glucose tolerance to measure SI, nuclear magnetic resonance spectroscopy to assess lipoprotein particles, and automatic auscultation to measure blood pressure.ResultsA greater improvement in VO2peak was observed in MIT compared to HIIT (11.1% vs 2.83%, P = 0.0185) in the complete-case analysis. No differences were seen in the intention to treat analysis, and no other group differences were observed. Both exercise conditions were associated with temporal improvements in % body fat, total cholesterol, medium VLDL, medium HDL, triglycerides, SI, and VO2peak (P < 0.05).ConclusionParticipation in HIIT or MIT exercise training displayed: 1) improved SI, 2) reduced blood lipids, 3) decreased % body fat, and 4) improved cardiovascular fitness. While both exercise groups led to similar improvements for most cardiometabolic risk factors assessed, MIT led to a greater improvement in overall cardiovascular fitness. Overall, these observations suggest that a relatively short duration of either HIIT or MIT training may improve cardiometabolic risk factors in previously sedentary overweight or obese young men, with no clear advantage between these two specific regimes (Clinical Trial Registry number NCT01935323).Trial RegistrationClinicalTrials.gov NCT01935323

The belief in the PEBO exceeds the strength of scientific evidence. The scientific record is distorted by RLPV and BRR. RLPV is a suboptimal use of collective scientific resources.

Background: A common dietary recommendation for weight loss, especially in lay public outlets, is to eat more fruit and vegetables (F/Vs). Without a compensatory reduction in total energy intake, significant weight loss would be unlikely. Objective: We aimed to synthesize the best available evidence on the effectiveness of the general recommendation to eat more F/Vs for weight loss or the prevention of weight gain. Design: We searched multiple databases for human randomized controlled trials that evaluated the effect of increased F/V intake on body weight. Inclusion criteria were as follows: $ 15 subjects/ treatment arm, $8-wk intervention, a stated primary or secondary outcome of body weight, the stated goal of the intervention was weight or fat loss or the prevention of weight or fat gain, and food intake provided or prescribed was of a variety of F/Vs that remained minimally processed. Results: Two studies met all criteria; 5 other studies met all criteria but one. The primary analysis indicated an effect size of weight change (outcome of interest) from baseline [standardized mean difference (SMD) for studies that met all criteria] of 20.16 (95% CI: 20.78, 0.46) (P = 0.60). The SMD for 7 studies that met all or most criteria was 0.04 (95% CI: 20.10, 0.17) (P = 0.62). Conclusions: Studies to date do not support the proposition that recommendations to increase F/V intake or the home delivery or provision of F/Vs will cause weight loss. On the basis of the current evidence, recommending increased F/V consumption to treat or prevent obesity without explicitly combining this approach with efforts to reduce intake of other energy sources is unwarranted. This systematic review and meta-analysis was registered at http://www.crd. york.ac.uk/PROSPERO/ as CRD42013004688 Am J Clin Nutr

Obesity is a topic on which many views are strongly held in the absence of scientific evidence to support those views, and some views are strongly held despite evidence to contradict those views. We refer to the former as “presumptions” and the latter as “myths”. Here we present nine myths and ten presumptions surrounding the effects of rapid weight loss; setting realistic goals in weight loss therapy; stage of change or readiness to lose weight; physical education classes; breast-feeding; daily self-weighing; genetic contribution to obesity; the “Freshman 15”; food deserts; regularly eating (versus skipping) breakfast; eating close to bedtime; eating more fruits and vegetables; weight cycling (i.e. yo-yo dieting); snacking; built environment; reducing screen time in childhood obesity; portion size; participation in family mealtime; and drinking water as a means of weight-loss. For each of these, we describe the belief and present evidence that the belief is widely held or stated, reasons to support the conjecture that the belief might be true, evidence to directly support or refute the belief, and findings from randomized controlled trials, if available. We conclude with a discussion of the implications of these determinations, conjecture on why so many myths and presumptions exist, and suggestions for limiting the spread of these and other unsubstantiated beliefs about obesity domain.

These data suggest that increased consumption of added sugars may be associated with adverse cardiovascular health factors in children, specifically elevated diastolic BP and triglycerides. Identification of dietary factors influencing cardiovascular health during childhood could serve as a tool to reduce cardiovascular disease risk. This trial was registered at clinicaltrials.gov as NCT00726778.

Cluster randomized controlled trials (cRCTs; also known as group randomized trials and community-randomized trials) are multilevel experiments in which units that are randomly assigned to experimental conditions are sets of grouped individuals, whereas outcomes are recorded at the individual level. In human cRCTs, clusters that are randomly assigned are typically families, classrooms, schools, worksites, or counties. With growing interest in community-based, public health, and policy interventions to reduce obesity or improve nutrition, the use of cRCTs has increased. Errors in the design, analysis, and interpretation of cRCTs are unfortunately all too common. This situation seems to stem in part from investigator confusion about how the unit of randomization affects causal inferences and the statistical procedures required for the valid estimation and testing of effects. In this article, we provide a brief introduction and overview of the importance of cRCTs and highlight and explain important considerations for the design, analysis, and reporting of cRCTs by using published examples.Am J Clin Nutr 2015;102:241-8.

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