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This study compared the audit method and secondary data sources for assessing health-related characteristics of the built environment in a Brazilian city. Study sample included 45 census tracts chosen by systematic random sampling, and 36 homes selected from each, from a population-based study. Each neighborhood was delimited by a 400m buffer around the midpoint of the homes. The built environment was assessed for dietary intake and physical activity categorized, respectively, into commercial establishments and services, food retail establishments for home consumption, food retail establishments for immediate consumption, physical activity establishments and public leisure spaces. An audit was conducted in 45 neighborhoods. Secondary data were obtained from lists of commercial establishments and services provided by the city council. Data were analyzed using ArcGIS. Agreement between the audit and secondary data was tested by the intraclass correlation coefficient. Analysis was performed for all neighborhoods and according to neighborhood income tertiles. Results show that agreement between the audit and secondary data was good or excellent for most of the dietary intake and physical activity categories. However, agreement differed according to neighborhood income level across three of the five categories, with lower income neighborhoods presenting the worse agreements. Hence, secondary data should be used with caution to assess health-related characteristics of the built environment in the poorest areas of Brazilian cities.

This cross-sectional school-based study in São Leopoldo, Rio Grande do Sul State, Brazil, evaluated the association between food insecurity and overweight in first grade students in the municipal elementary school system. A total of 2,369 students were invited to participate, of whom 847 were examined, and of these, 782 had data available on weight and height. Dietary data were obtained from a parent or guardian. Food insecurity was measured by the Brazilian Food Insecurity Scale (EBIA). Data on weight and height were provided by the Nutrition Service of the Municipal Department of Education. Prevalence rates for overweight and food insecurity were 38.1% and 45.1%, respectively. After controlling for potential confounders, children with food insecurity had 22% lower odds of overweight. Notwithstanding the inverse association between the exposure and outcome, this sample showed high rates of food insecurity and overweight, revealing a complex relationship and indicating that further research is needed to understand it. Robust public policies are critical for addressing these conditions.

This study tested the relative validity and estimated calibration factors of a food-frequency questionnaire (FFQ) with 120 food items in 128 adults. We applied one FFQ and three 24h recalls. Validity was tested by the Bland-Altman method, intraclass correlation coefficient (ICC), classification in quartile categorization, and weighted kappa. Calibration factors were estimated by linear regression, with 24h recall of food intake as the dependent variable and the FFQ values as the independent variable. FFQ underestimated the nutrient intake when compared to 24h recall. The energy-adjusted and de-attenuated ICC ranged from 0.19 (zinc) to 0.82 (calcium). 37% of subjects were classified in the same quartile, with mean kappa of 0.28 (zinc: 0.08; calcium: 0.49). The highest calibration factors were 0.48 (calcium), 0.47 (potassium), and 0.44 (carbohydrates), and the lowest was 0.10 (retinol). FFQ showed satisfactory relative validity and calibrated energy and nutrient intake values similar to 24h recall.

The objective of this study was to investigate the association between psychosocial factors and self-reported overweight. A cross-sectional study was carried out with 1,100 adults in a Brazilian city. Structured interviews were conducted using a standard pre-tested questionnaire. Overweight was self-reported by participants and defined as body mass index (BMI) > 25kg/m². Psychosocial factors were quality of life (WHO-8: EUROHIS) and social support (Medical Outcomes Study). Crude and adjusted prevalence ratios (PR) were obtained by modified Poisson regression. After controlling for socio-demographic and behavioral variables, prevalence of overweight among individuals reporting low quality of life and low social support was 19% (PR = 1.19; 95%CI: 1.03-1.38) and 12% (PR = 1.12; 95%CI: 0.96-1.31), respectively, and was higher in those reporting high/moderate quality of life and high/moderate social support, respectively. The findings suggest that psychosocial factors can play a role in self-assessment of overweight.

The reproducibility and validity of a Food Frequency Questionnaire (FFQ) was evaluated in 83 adults living in a State capital in southern Brazil. The reproducibility and validity were tested with intra-class correlation coefficients (ICC). Mean nutrient intakes from three 24-hour dietary recalls (24hDR) were compared to mean intakes from each FFQ (FFQ1 and FFQ2), adjusted for energy intake and within-person variation. Nutrients were categorized into quartiles and assessed using weighted kappa statistics. Mean ICC for the test-retest FFQ ranged from 0.44 (95%CI: -0.19-0.76) to 0.83 (95%CI: 0.72-0.90) for energy-adjusted carbohydrate and vitamin C intakes, respectively. Mean ICC, energy-adjusted and corrected for within-person variability, ranged from 0.23 (95%CI: -0.22-0.61) to 0.86 (95%CI: 0.21-1.16) for vitamin A and lipids for the FFQ1, and 0.50 (95%CI: -0.16-0.91) to 0.95 (95%CI: 0.79-1.05) for vitamin A and energy for the FFQ2. For the FFQ1, calcium showed the lowest weighted kappa value (0.10; 95%CI: 0.00-0.26), while vitamin C (0.38; 95%CI: 0.23-0.53) and total energy (0.38; 95%CI: 0.24-0.52) had the highest weighted kappa for the FFQ2. The FFQ showed good reproducibility and reasonable relative validity.

This study focused on the association between dietary patterns and obesity. A cross-sectional population-based study was performed in 1,026 adult women from Southern Brazil. Waist circumference (WC), height, and weight were measured according to a standardized protocol, and body mass index (BMI) was calculated. Obesity was defined as BMI > 30kg/m(2) and WC > 88cm. Principal components analysis was used to identify dietary patterns. Multivariate analysis used a Poisson regression model to estimate prevalence ratios and respective confidence intervals. After controlling for possible confounders, low consumption of "vegetables" protected against increased BMI (PR = 0.64; 95%CI: 0.47-0.86; p = 0.004), while low consumption of "nuts/oilseeds" protected against increased WC (PR = 0.93; 95%CI: 0.89-0.98; p = 0.008). Low consumption of "fruits" was a risk factor for high BMI (PR = 2.18; 95%CI: 1.35-3.53; p = 0.001). The study indicates the complexity of the association between dietary patterns and obesity. New studies are needed to further clarify the subject.