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. 2015 Apr 29:2:337-41.
doi: 10.1016/j.pmedr.2015.04.019. eCollection 2015.

Neighbourhood environments and obesity among adults: A multilevel analysis of an urban Brazilian context

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Neighbourhood environments and obesity among adults: A multilevel analysis of an urban Brazilian context

Fernanda Penido Matozinhos et al. Prev Med Rep. .

Abstract

Objective. This study identified environmental variables associated with obesity in the adult population of a city in Brazil. Methods. It was conducted using the Surveillance System for Risk and Protective Factors for Chronic Diseases by Telephone Survey from 2008 to 2010. The body mass index (BMI) was calculated from the participants' self-reported weight and height. Obesity was defined as a BMI ≥ 30 kg/m2. The food establishments, georeferenced areas conducive to physical activity, total income of the neighbourhood, homicide rate and population density were used to characterise the environment. In addition, individual variables were considered. A multilevel logistic regression was performed. Results. A total of 5273 individuals were evaluated. The odds of obesity was found to be significantly decreased with increases in the number of establishments that sell healthy food, number of restaurants, number of places for physical activity and total income - in different models. In addition, these associations remained significant after adjustment for age, gender, education and consumption of meat with visible fat. Conclusions. This study contributes to a better understanding of the complex interaction between environmental and individual determinants of obesity and may aid in the development of effective interventions, such as the expansion of obesity control programmes.

Keywords: Multilevel analysis; Obesity; Public health; Telephone survey.

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Figures

Fig. 1
Fig. 1
Prevalence of obesity (%) among neighbourhoods. There was variation in obesity prevalence from 0 to 41.94% among coverage areas (likelihood ratio (LR) test, p = 0.002), defining the hierarchical structure of the data.

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