Social inequalities differences in the association between summer temperatures and mortality in the city of Turin, northwest of Italy. A distributed lag non-linear time series analysis from 1982 to 2018

Abstract

Social inequalities differences in the association between summer temperatures and mortality in the city of Turin, northwest of Italy: a distributed lag non-linear time series analysis from 1982 to 2018AimTo investigate social inequalities in the association between summer temperatures and mortality in the city of Turin for the period 1982-2018. As a measure of and socioeconomic position, we used the educational level, the marital status, the employment status and the number of dwelling’s occupants of the deceased, diversifying the analysis by gender and sub-categories.MethodsMortality data are represented by individual all-causes mortality counts for the summer periods from 1982 to 2018. Socioeconomic position and daily mean temperature were assigned to each deceased. A time series Poisson regression with distributed lag non-linear models was fitted to capture the complex nonlinear dependency between mortality and summer temperatures.Results The mortality risk grows with age in both genders, and we found a statistically significant association for all the age-groups. With regards to education, the higher risk corresponded to the highest educational levels. Temperature-mortality association was more evident for non-mate people than for married people, with higher risks for women. Results on the employment status highlighted a strong association over people retired from work and in people in other conditions. For the number of dwelling occupants, we found a strong association for those who lived in a crowded environment, followed by people who lived in an isolated context.ConclusionsAssociations between heat and mortality are unequal across different aspects of social vulnerability, and, inter alia, factors influencing the population vulnerability to temperatures can be related to demographic, social, and economic aspects. A better knowledge of these effect modifiers is needed to identify the axes of inequality across the most vulnerable population groups.