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Abstract 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.

Limited data exist on the reproducibility of food patterns measured by factor analysis as well as on the use of stability of patterns over time. Our primary objective was to explore the long-term stability of food patterns derived by confirmatory factor analysis among 33,840 women participating in the Swedish Mammography Cohort. Our secondary objective was to compare factor solutions from confirmatory factor analysis with those derived by use of exploratory factor analysis. Diet was assessed by a food frequency questionnaire in 1987 and 1997, and food patterns were derived by the use of exploratory and confirmatory factor analysis. We observed four major food patterns (Healthy, Western/Swedish, Alcohol, and Sweets) at both time points. Correlations between confirmed food patterns in 1987 and 1997 were 0.37 for the Healthy pattern, 0.27 for the Western/Swedish pattern, 0.54 for the Alcohol pattern, and 0.44 for the Sweets pattern (P < 0.0001 for all associations). Patterns derived by the use of exploratory factor analysis were strongly associated with those derived by the use of confirmatory factor analysis (r >/= 0.90, P < 0.0001, for all associations). The patterns derived in this study were similar to those derived in other studies, indicating reproducibility of food patterns across populations. Our study suggests that food patterns measured by the use of confirmatory factor analysis are reproducible over time, and weaker correlations observed may reflect natural changes in eating behavior, the food supply, and/or perceptions of what is considered healthy. Testing whether patterns measured over a long time period can be used in analytic studies is the next step in assessing the validity of this method.

The prevalence of obesity is increasing in most parts of the world. The objective of this study was to examine whether changes in food patterns were associated with changes in BMI among women over 9 y. Data were from 33,840 women participating in the Swedish Mammography Cohort in 1987 and 1997. Diet was assessed with a FFQ at both time points and 4 food patterns were derived using confirmatory factor analysis (Healthy, Western/Swedish, Alcohol, and Sweets). Our exposure variables were defined as change in factor score for each food pattern from 1987 to 1997. Our outcome variable was defined as change in BMI during the same period, and we also examined change in weight. Normal weight and overweight women had positive changes in weight and BMI during follow-up, whereas obese women had negative changes in BMI and weight; we observed a significant interaction between change in food patterns and baseline BMI. Obese subjects who increased their factor score for the Healthy pattern had larger decreases in BMI (beta = -0.18 kg/m(2) for a 1 unit increase in SD score, CI: -0.26 to -0.10; P < 0.0001), whereas normal weight and overweight women who increased their Healthy pattern score had smaller increases in BMI (-0.05 kg/m(2) and -0.11 kg/m(2), respectively; P < 0.05 for both). Obese women who increased their Healthy pattern score >3 SD had almost a 4 kg decrease in weight and a 1 unit decrease in BMI at follow-up. In conclusion, changes in eating patterns were significantly related to changes in BMI over 9 y and the effect was modified by baseline BMI. Pattern analysis is helpful in generating hypotheses regarding the role of diet in obesity, and additional research is needed to understand which elements of our patterns are protective or risk factors for weight gain.

BACKGROUND: Observational studies suggest that a plant-based diet is inversely related to body mass index (BMI), overweight, and obesity. OBJECTIVE: Our objective was to examine the BMI (kg/m(2)) and risk of overweight and obesity of self-defined semivegetarian, lactovegetarian, and vegan women. DESIGN: Data analyzed in this cross-sectional study were from 55459 healthy women participating in the Swedish Mammography Cohort. Women were asked whether they considered themselves to be omnivores (n = 54257), semivegetarians (n = 960), lactovegetarians (n = 159), or vegans (n = 83), and this question was the main exposure variable in this study. In secondary analyses, we reclassified women as lactovegetarians on the basis of food intakes reported on the food-frequency questionnaire. RESULTS: The prevalence of overweight or obesity (BMI >/= 25) was 40% among omnivores, 29% among both semivegetarians and vegans, and 25% among lactovegetarians. In multivariate, adjusted logistic regression analyses, self-identified vegans had a significantly lower risk of overweight or obesity [odds ratio (OR) = 0.35; 95% CI: 0.18, 0.69] than did omnivores, as did lactovegetarians (OR = 0.54; 95% CI: 0.35, 0.85) and semivegetarians (OR = 0.52; 95% CI: 0.43, 0.62). Risk of overweight or obesity remained significantly lower among lactovegetarians classified on the basis of the food-frequency questionnaire (OR = 0.48; 95% CI: 0.30, 0.78). CONCLUSIONS: Even if vegetarians consume some animal products, our results suggest that self-identified semivegetarian, lactovegetarian, and vegan women have a lower risk of overweight and obesity than do omnivorous women. The advice to consume more plant foods and less animal products may help individuals control their weight.