• Nancy L Fleischer, Ana V Diez Roux, Marcio Alazraqui, and Hugo Spinelli.
• Center for Social Epidemiology and Population Health, Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA. nancyfl@umich.edu
• J Urban Health. 2008 Nov 1; 85 (6): 923937923-37.

AbstractMost studies of socioeconomic status (SES) and chronic disease risk factors have been conducted in high-income countries, and most show inverse social gradients. Few studies examine these patterns in lower- or middle-income countries. Using cross-sectional data from a 2005 national risk factor survey in Argentina (a middle-income country), we investigated the associations of individual- and area-level SES with chronic disease risk factors (body mass index [BMI], hypertension, and diabetes) among residents of Buenos Aires. Associations of risk factors with income and education were estimated after adjusting for age, sex (except in sex-stratified models), and the other socioeconomic indicators. BMI and obesity were inversely associated with education and income for women, but not for men (e.g., mean differences in BMI for lowest versus highest education level were 1.55 kg/m2, 95%CI = 0.72-2.37 in women and 0.17 kg/m2, 95%CI = -0.72-1.06 in men). Low education and income were also associated with increased odds of hypertension diagnosis in all adults (adjusted odds ratio [AOR] = 1.48, 95%CI = 0.99-2.20 and AOR = 1.50, 95%CI = 0.99-2.26 for the lowest compared to the highest education and income categories, respectively). Lower education was strongly associated with increased odds of diabetes diagnosis (AOR = 4.12, 95%CI = 1.85-9.18 and AOR = 2.43, 95%CI = 1.14-5.20 for the lowest and middle education categories compared to highest, respectively). Area-level education also showed an inverse relationship with BMI and obesity; these results did not vary by sex as they did at the individual level. This cross-sectional study of a major urban area provides some insight into the global transition with a trend toward concentrations of risk factors in poorer populations.

32 keywords...

hide…