Culture, socioeconomic status, and physical and mental health in Brazil
The association of socioeconomic variables with poor health status has been widely observed, if not well understood, and cultural dimensions of socioeconomic differences have rarely been incorporated into research models. In this article, a cultural dimension of socioeconomic status is examined in a Brazilian city through the use of ethnographic and social survey techniques. It suggests that lifestyle, defined in terms of the relative ability to accumulate consumer goods and the adoption of associated behaviors, is an important component of socioeconomic differences. Further research using cultural consensus analysis, a structured ethnographic technique that may be used to study shared cultural knowledge, demonstrates significant consensus regarding the definition of the successful lifestyle. Then, using that culturally defined model of the successful lifestyle as the central tendency, an individual-level measure of approximation to that lifestyle was developed for a representative sample of 250 persons. This culturally defined measure of lifestyle was inversely associated with arterial blood pressure (beta = -.216, p < .01), depressive symptoms (beta = -.236, p < .01), and globally perceived stress (beta = -.358, p < .01); furthermore, it absorbed the explained variability in these outcomes that is associated with conventional socioeconomic variables (occupation, education, income). For arterial pressure, cultural consonance explained almost 10 percent of the differences in blood pressure between individuals; for the psychological outcome variables, cultural consonance explained between 10 percent and 20 percent of the differences between individuals. Finally, its statistical effects were independent of other socioeconomic, dietary, anthropometric, and psychosocial variables. These results suggest that an individual's approximation to the cultural ideal of lifestyle, his or her "cultural consonance," mediates the observed effects of socioeconomic variables on health status.