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To investigate the relationship between social deprivation and the food environment. Furthermore, to evaluate if the food environment is associated with the prevalence of obesity among students in Brazilian public schools.
Cross-sectional. For the classification of obesity, weight and height were measured, and the cut-off point of BMI-for-age Z-score >+2 was adopted. Social deprivation level was determined from the Health Vulnerability Index (HVI). To assess the food environment, the density of food establishments in urban residential areas was calculated. Associations between the food environment and the presence of obesity were estimated by binary logistic regression through a generalized estimating equations model.
Juiz de Fora, Minas Gerais, Brazil.
Children and adolescents (n 661) aged 7–14 years.
The lowest social deprivation level showed a higher density of all types of establishments that sold predominantly unhealthy foods. An inverse association was found between the density of supermarkets and hypermarkets and the presence of obesity (OR=0·58; 95 % CI 0·36, 0·93). For the other categories of food retailers, no significant differences were found.
The findings reinforce the need for public policies that promote equality in the food environments of the city. Also, further investigations into the influence of the presence of supermarkets on the nutritional status of children and adolescents are required.
Obesity is defined as an excess of total body fat and may be assessed by different methods. The objective of the present study was to establish the discriminatory power of anthropometric data in determining obesity.
The subjects comprised 685 individuals, aged 20–79 years, sampled from a population-based survey. The following indicators were used: body mass index (BMI), waist circumference (WC) and total body fat percentage estimated with both Siri's equation (%BF Siri) and foot-to-foot bioelectrical impedance analysis (%BF BIA). Sensitivity and specificity of different cut-off points for each method were determined using %BF BIA as reference.
Of 685 participants, 57.6% were aged ≥ 40 years, 69.9% were women and 72.6% self-referred themselves as non-white. To classify obesity based on sex and age among women aged < 40 years, the cut-off points were BMI of 26.0 kg m− 2, WC of 84.0 cm and %BF Siri of 34.0%; in those aged ≥ 40 years, the cut-off points were 28.0 kg m− 2, 90.0 cm and 37.4%, respectively. The cut-off points among men aged < 40 years were BMI of 26.3 kg m− 2, WC of 86.0 cm and %BF Siri of 22.5%, and in those aged ≥ 40 years, 26.3 kg m− 2, 89.0 cm and 24.5%, respectively. BMI was the method with the largest area under the curve (AUC) independent of sex and sex/age, yet no differences were observed in AUC between BMI and WC (P>0.05). Classifying according to skin colour did not change cut-off points in any indicator.
BMI and WC better discriminate obesity among women and men aged ≥ 40 years from a mixed-race population.
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