Behavioral patterns that increase or decrease risk of abdominal adiposity in adults.

INTRODUCTION: The identification of risk or protective behavioral patterns associated with abdominal adiposity may aid in prevention and health promotion measures. OBJECTIVE: To identify and to associate behavioral patterns of risk and protection to abdominal adiposity in adults in a Brazilian city. MATERIAL AND METHODS: A population-based cross-sectional study was carried out in Viçosa, Brazil, with 1,226 adults of both sexes. Information on social-demographic characteristics, food intake, level of physical activity, alcohol consumption and smoking were collected by using a questionnaire. The anthropometric measurement of waist circumference and anthropometric indices waist/hip ratio and waist/height ratio were indicators of abdominal adiposity. To identify behavioral patterns, exploratory factor analysis was applied for the variables considered as risk or protective factors. The association of the identified patterns with abdominal adiposity was estimated by multiple linear regression, adjusted for gender, age and social economical class. RESULTS: Two patterns were obtained, "healthy" and "risk". The "healthy" pattern, comprised of the clustering of the variables food consumption, fruits, fresh fruit juices, raw and cooked vegetables and the appropriate level of physical activity, was negatively associated with abdominal adiposity identified by waist circumference (p = 0.048), waist/hip (p = 0.013) and waist/height (p = 0.018) indices. The "risk" pattern, composed of smoking, alcohol beverage abuse and habit of consuming visible fat in fat-rich red meat or poultry skin, was positively associated with abdominal adiposity identified by waist circumference (p = 0.002) and waist/hip (p = 0.007) and waist/height indices (p = 0.006). CONCLUSIONS: Two behavioral patterns were identified, a risk pattern and a protective pattern for abdominal adiposity in the assessed population. The study shows the importance of conducting clustering of multiple risk and protective factors to better explain the health conditions of a group.

Behavioral patterns that increase or decrease risk of abdominal adiposity in adults / Patrones de comportamiento que aumentan o disminuyen el riesgo de adiposidad abdominal en adultos

Introduction: The identification of risk or protective behavioral patterns associated with abdominal adiposity may aid in prevention and health promotion measures. Objective: To identify and to associate behavioral patterns of risk and protection to abdominal adiposity in adults in a Brazilian city. Material and methods: A population-based cross-sectional study was carried out in Viçosa, Brazil, with 1,226 adults of both sexes. Information on social-demographic characteristics, food intake, level of physical activity, alcohol consumption and smoking were collected by using a questionnaire. The anthropometric measurement of waist circumference and anthropometric indices waist/hip ratio and waist/height ratio were indicators of abdominal adiposity. To identify behavioral patterns, exploratory factor analysis was applied for the variables considered as risk or protective factors. The association of the identified patterns with abdominal adiposity was estimated by multiple linear regression, adjusted for gender, age and social economical class. Results: Two patterns were obtained, "healthy" and "risk". The "healthy" pattern, comprised of the clustering of the variables food consumption, fruits, fresh fruit juices, raw and cooked vegetables and the appropriate level of physical activity, was negatively associated with abdominal adiposity identified by waist circumference (p = 0.048), waist/hip (p = 0.013) and waist/height (p = 0.018) indices. The "risk" pattern, composed of smoking, alcohol beverage abuse and habit of consuming visible fat in fat-rich red meat or poultry skin, was positively associated with abdominal adiposity identified by waist circumference (p = 0.002) and waist/hip (p = 0.007) and waist/height indices (p = 0.006). Conclusions: Two behavioral patterns were identified, a risk pattern and a protective pattern for abdominal adiposity in the assessed population. The study shows the importance of conducting clustering of multiple risk and protective factors to better explain the health conditions of a group (AU)

Introducción: la identificación de los riesgos o los patrones de comportamiento de protección asociados con la adiposidad abdominal puede ayudar en las medidas de prevención y promoción de la salud. Objetivo: identificar y establecer la asociación entre los patrones de comportamiento de riesgo y de protección y la adiposidad abdominal en adultos en una ciudad brasileña. Material y métodos: se llevó a cabo un estudio transversal basado en la población en Viçosa, Brasil, con 1.226 adultos de ambos sexos. Se recogió información sobre las características sociodemográficas, la ingesta de alimentos, el nivel de actividad física, el consumo de bebidas alcohólicas y el hábito tabáquico mediante un cuestionario. La medición antropométrica de la circunferencia de la cintura y de los índices antropométricos cintura/cadera y cintura/altura fueron los indicadores de adiposidad abdominal. Para identificar los patrones de comportamiento, se aplicó un análisis factorial exploratorio de las variables de riesgo o factores de protección considerados. La asociación de los patrones identificados con la adiposidad abdominal se estimó por regresión lineal múltiple, ajustada por género, edad y nivel socioeconómico. Resultados: se establecieron dos patrones, "sano" y "riesgo". El patrón "sano", compuesto por la agrupación de las variables consumo de alimentos, frutas, zumos de fruta fresca, verdura cruda y cocida y el nivel apropiado de actividad física, se asoció negativamente con la adiposidad abdominal identificada por la circunferencia de la cintura (p = 0,048) y los índices cintura/cadera (p = 0,013) y cintura/altura (p = 0,018). El patrón de "riesgo", compuesto por hábito tabáquico, abuso de alcohol y consumo de grasa visible en carnes rojas ricas en grasa o piel de las aves, se asoció positivamente con la adiposidad abdominal identificada por la circunferencia de la cintura (p = 0,002) y las ratios cintura/cadera (p = 0,007) y cintura/altura (p = 0,006). Conclusiones: fueron identificados dos patrones de comportamiento, el patrón de riesgo y el patrón de protección, relacionados con la adiposidad abdominal en la población estudiada. El estudio muestra la importancia de agrupar múltiples factores de riesgo y de protección para explicar mejor las condiciones de salud de un grupo (AU)

Validity of body adiposity index in predicting body fat in Brazilians adults.

OBJECTIVES: The aim of this study was to compare various methods of assessing body compositions with body adiposity index (BAI) and to identify the validity of BAI as a predictor of body fat in Brazilian adults. METHODS: This study included 706 individuals (average age 37.3 years, SD = 12.1). Anthropometric data included percent body fat obtained by skinfold thicknesses, bioelectrical impedance analysis and DXA. Body mass index (BMI), waist/hip ratio, and BAI were calculated. The correlation between variables was assessed by Pearson's correlation coefficient, and the Bland-Altman and Kaplan Meier graphic approaches were used to verify the agreement between BAI and DXA. RESULTS: There was a strong correlation between BAI and BMI (r = 0.84 in men and r = 0.86 in women, P < .001), waist circumference (r = 0.77 in men and r = 0.75 in women, P < .001) percent fat by skinfold thicknesses (r = 0.71 in men and r = 0.71 in women, P < .001) and by DXA (r = 0.72 in men and r = 0.78 in women, P < .001). The Bland-Altman approach showed an overestimation of BAI in males and an underestimation in women using DXA as the reference method. The agreement between BAI and DXA through the Kaplan-Meier analysis was 41%. CONCLUSIONS: It was found that BAI does not replace other measurements of body fat, but compared with more complex methods can be an alternative for estimating the body fat in the absence of these methods.