Figuring out health inequality (Bartley 2004)Studying health inequality demands comparisons between groupsStatistical explanationGoal is prediction of the observed outcome with a set of explanatory variablesWhen studying social inequalities in health, identifying groups that are more at riskWe can ‘build’ explanations by adding variables to identify pathways between inequality and healthBUT none of that tells us what underlying mechanismsput these groups at risk (why are they motivated to act in this way, how that exposure results in physiological changes in the body): need for fundamental biological and qualitative research. Spuriousness and ConfoundingWhen a third factor is the real cause of an association between two variablesEx: For school children, height is strongly correlated with reading skills.
StandardizationAge is a strong (and unavoidable!) determinant of health and mortality AND of social statusStandardization corrects for the possibility that a given group looks healthier/unealthier because of its age distribution: basic biological fact, not social causeExamples: How can age confound the relationship between socioeconomic status and health?Income groups above 40 years old: The lower income (poorer) groups are more likely on average to be retired, olderOccupational differences: unskilled services jobs tend to be occupied by younger individuals, while professional occupations tend to be occupied by older individuals – age differences may mask deleterious effects of unskilled service jobs
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