Association between area-level education and the co-occurrence of behavior-related risk factors: a multilevel analysis

Abstract

Introduction: This study aimed to investigate the association of four different risk factors for chronic diseases and accumulation of these health behaviors with area-level education, regardless of individual-level characteristics in Brazil. Methods: A population-based cross-sectional study was carried out in Southern Brazil including 1,720 adults in 2009/2010. The simultaneous occurrence of tobacco smoking, abusive drinking, unhealthy eating habits, and physical inactivity was investigated. Using multilevel models, we tested whether area-level education was associated with each risk factor and with the co-occurrence of them after controlling sociodemographic individual-level variables. Results: We observed a between-group variance of 7.79, 7.11, 6.84 and 1.08% for physical inactivity, problematic use of alcohol, unhealthy eating habits, and smoking, respectively. The between-group variance for the combination of four behaviors was 14.2%. Area-level education explained a significant proportion of the variance observed in physical inactivity and unhealthy eating habits. Residents of low educational level neighborhoods showed a 2.40 (95%CI 1.58 - 3.66) times higher chance of unhealthy eating and 1.78 (95%CI 1.19 - 2.67) times higher chance of physical inactivity. The likelihood of individuals with two or three/four risk factors was simultaneously higher among residents of low educational level neighborhoods. Conclusion: Public policies should consider the area-level characteristics, including education to control risk factors for chronic diseases.

Small area influences on the individual unhealthy lifestyle behaviors: A multilevel analysis of discriminatory accuracy

“…Finally, Boing et al, analyzed the same four risk factors on a Brazilian sample and, similar to our study, they failed to observe an environmental influence (based on census tracts) on tobacco consumption. However, they reported an intra-class correlation coefficient (ICC), which interpretation mirrors that of the VPC, of 0.8% for unbalanced diet, 5.2% for physical activity, and 3.8% for problem drinking (Boing et al, 2019).…”

“…Most research using multilevel regression analysis observed an inverse association with smoking, i.e., the lower the status, the higher the risk of tobacco consumption (Adams et al, 2009;Caraballo et al, 2019;Diez Roux, 2003;Ecob and Macintyre, 2000;van Lenthe, 2006). However, a French study showed the opposite effect, higher probability of smoking in better off areas (Chaix et al, 2004), and another study reported no association (Boing et al, 2019).…”

“…As far as we are aware of, few studies to date have quantified, simultaneously, the influence of the area of residence on the main risk factors for chronic diseases at the individual level (Adams et al, 2009;Boing et al, 2019;Ecob and Macintyre, 2000). It is also still uncommon for studies to differentiate between general and specific contextual effects.…”

Socioeconomic determinants of eating behavior

“…Имеются данные о влиянии данной детерминанты на пищевое поведение. Согласно результатам, полученным в ходе исследования распространенности пищевых и сердечно-сосудистых рисков (ССР), проведенным в Гонконге, высокий уровень образования был связан с более высоким процентным содержанием белка в рационе мужчин, жира, некоторых макро-, микроэлементов и витаминовв рационе женщин [40].…”

“…Распространенность нездорового питания и отсутствия физической активности была выше среди районов с низким уровнем образования. Люди с более высоким образованием с большей вероятностью будут правильно применять полезные рекомендации по вопросам здорового питания [40].…”