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The traditional lunch pattern is inversely correlated with body mass index in a population-based study in Brazil.

ABSTRACT: The association of obesity and dietary patterns has been well documented in scientific literature; however, information on the impact of meal patterns on obesity is scarce. The objective of this study was to investigate the association of adherence to lunch patterns and body mass index (BMI) in a representative sample of individuals aged 20 years or older in Sao Paulo.Data for 933 participants were retrieved from the Health Survey of São Paulo (ISA-Capital 2008), a cross-sectional population-based survey. The usual dietary intake of individuals with at least one 24-h recall was estimated by the Multiple Source Method. The definition of lunch was self-reported by the participant. Five lunch patterns were derived from twenty-two food groups by exploratory factor analysis: Traditional, Western, Sweetened juice, Salad, and Meats. To estimate the effect of lunch patterns on BMI, we used a generalized linear model with link identity and inverse Gaussian distribution. Analyses were adjusted by age, gender, household income per capita, physical activity levels, smoking status, alcohol consumption, total energy intake, and misreporting status.The greater adherence to the traditional pattern at the lunch meal was associated with lower BMI, only in insufficiently active individuals (ß = -0.78; 95% CI -1.57; -0.02).The traditional Brazilian lunch pattern might protect the insufficiently active individuals against obesity.

SUBMITTER: de Oliveira Santos R

PROVIDER: S-EPMC5518136 | biostudies-other | 2017 Jul

REPOSITORIES: biostudies-other

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Project description:BackgroundDuring pregnancy, healthy maternal body weight and a nutritionally complete diet provide a favorable environment for fetal development. Yet nearly two-thirds of women of reproductive age in the United States (US) are either overweight or obese. The objective of this research was to investigate the relationship between a measure of dietary diversity and body mass index (BMI) in a sample of women enrolled in a US pregnancy cohort.MethodsDietary data was obtained from one 24-hour dietary recall collected during the third trimester of pregnancy (n = 40). Pre-pregnancy BMI was calculated from pre-pregnancy weight and height self-reported by survey at the time of enrollment. Using the Minimum Dietary Diversity for Women (MDD-W) indicator developed by the Food and Agriculture Organization of the United Nations, dietary data was categorized and scored.ResultsOverall, 35% of participants did not achieve minimum dietary diversity (MDD-W ?5). In addition, 45% of participants were obese, 35% were normal weight and 20% were overweight. Women with higher BMI had lower MDD-W scores than women with lower BMI (p < 0.05). The median MDD-W for both normal and overweight women was ?5 indicating that normal and overweight pregnant women tended to consume a diet that was high in micronutrients. Conversely, the median MDD-W for obese women was below 5 meaning these women tended to consume a diet that was low in micronutrient density. The most commonly consumed food group was grain. In addition, 75% of all participants consumed sweetened drinks. Individuals with an MDD-W score ?5, were more likely to have consumed dark green leafy vegetables, vitamin A-rich fruits or vegetables, other vegetables and other fruits than those with MDD-W scores <5.DiscussionIn this study, we show that a food group diversity indicator that has been shown to reflect adequacy of micronutrient intake in populations from less economically developed countries may also be informative in US populations. Furthermore, these results reflect the importance of encouraging all pregnant women with less varied diets to consume more fruits and vegetables.

Project description:BackgroundNational data on body mass index (BMI), computed from self-reported height and weight, is readily available for many populations including the Canadian population. Because self-reported weight is found to be systematically under-reported, it has been proposed that the bias in self-reported BMI can be corrected using equations derived from data sets which include both self-reported and measured height and weight. Such correction equations have been developed and adopted. We aim to evaluate the usefulness (i.e., distributional similarity; sensitivity and specificity; and predictive utility vis-à-vis disease outcomes) of existing and new correction equations in population-based research.MethodsThe Canadian Community Health Surveys from 2005 and 2008 include both measured and self-reported values of height and weight, which allows for construction and evaluation of correction equations. We focused on adults age 18-65, and compared three correction equations (two correcting weight only, and one correcting BMI) against self-reported and measured BMI. We first compared population distributions of BMI. Second, we compared the sensitivity and specificity of self-reported BMI and corrected BMI against measured BMI. Third, we compared the self-reported and corrected BMI in terms of association with health outcomes using logistic regression.ResultsAll corrections outperformed self-report when estimating the full BMI distribution; the weight-only correction outperformed the BMI-only correction for females in the 23-28 kg/m2 BMI range. In terms of sensitivity/specificity, when estimating obesity prevalence, corrected values of BMI (from any equation) were superior to self-report. In terms of modelling BMI-disease outcome associations, findings were mixed, with no correction proving consistently superior to self-report.ConclusionsIf researchers are interested in modelling the full population distribution of BMI, or estimating the prevalence of obesity in a population, then a correction of any kind included in this study is recommended. If the researcher is interested in using BMI as a predictor variable for modelling disease, then both self-reported and corrected BMI result in biased estimates of association.

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The traditional lunch pattern is inversely correlated with body mass index in a population-based study in Brazil.

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