INTRO “Socioeconomic position” (SEP), a set of several social and economic conditions, influences health status among populations creating inequalities in health or in access to care There are two approaches of SEP measuring. Compositional (individual) approach examines the socioeconomic and behavioral characteristics of individuals and their associated health outcomes.The main individual level indicators are: occupation, education, income. Contextual (area) approach focuses on the social and economic conditions that affect all individuals who share a particular social environment. Examples include: neighborhoods, counties, region and states. They can be obtained by aggregating individual-level measures, or creating composite measures using aggregates of several individual-level indicators (“deprivation indices”). The reasons to measure SEP indicators in health research are: to describe the social distribution of diseases to monitor changes over time, regions and groups; to describe the causal mechanisms through which SEP generates health differences; to statistically adjust for socioeconomic circumstances (diseases socially patterned). Methods We analyze data from Atlas of mortality in Sicily, in the years 1997-2002. Cities and villages were classified according to the division into quintiles corresponding to as many levels of socioeconomic status, since the lowest level 1 to the highest level 5. The main causes of mortality were analyzed and it was calculated the relative risks (RR) and the corresponding 95% confidence interval, based on a comparison between each of the five levels with the highest level. Results The analysis of general mortality showed a statistically higher risk in men for the first two levels respect to the third considered the referenced level. The same situation was observed in women but we observed statistically significant risks only for the first and the second level. Cancers showed statistically significant excesses in men in second level of socio-economic position, whereas in women only for the second level. Circulatory system diseases showed statistically significant excesses in both of men and women for the first and the second level position. Infectious diseases statistically significant excesses were observed only in men and for all levels considered, except for the first socioeconomic level. Conclusions The results confirm that the socio-economic disadvantage is a mortality predictor factor also in Sicily. Data suggest that there is the same mortality risk for both of sexes except for infectious diseases and the influence of disadvantages is stronger in men than women.
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