The effect of cold waves on daily mortality in districts in Madrid considering sociodemographic variables.

While there is much research that focuses on the association between cold waves and their impacts on daily mortality at the city level, few analyze the impact related to social context and demographic variables at levels lower than the municipal. The objective of this study was to determine the role of the percentage of people over age 65, income level and percentage of homes without heating in the analysis of the impact of cold waves on daily mortality between January 1, 2010 and December 31, 2013 in different districts of the municipality of Madrid. We calculated Relative Risks (RR) and Attributable Risks (RA) for each of 17 districts to determine correlations between the effect of cold waves and daily mortality due to natural causes (CIEX: A00-R99) using Generalized Linear Models (GLM) of the Poisson family (link log). The pattern of risks obtained by district was analyzed using binomial family models (link logit), considering socioeconomic and demographic variables. In terms of results, an impact of cold on mortality was detected in 9 of the 17 districts analyzed. The analysis of risk patterns revealed that the probability of detecting an impact in a district increases in a statistically significant way (p-value <0.05) with a higher percentage of homes without heating systems and a higher percentage of population over age 65. The results obtained identify the factors that should be considered in public health policies that target the district level to reduce the impact of cold waves.

The impact of heat waves on daily mortality in districts in Madrid: The effect of sociodemographic factors.

Although there is significant scientific evidence on the impact of heat waves, there are few studies that analyze the effects of sociodemographic factors on the impact of heat waves below the municipal level. The objective of this study was to analyze the role of income level, percent of the population over age 65, existence of air conditioning units and hectares (Ha) of green zones in districts in Madrid, in the impact of heat on daily mortality between January 1, 2010 and December 31, 2013. Seventeen districts were analyzed, and Generalized Linear (GLM) Poisson Regression Models were used to calculate relative risks (RR) and attributable risks (RA) for the impact of heat waves on mortality due to natural causes (CIEX:A00-R99). The pattern of risks obtained was analyzed using GLM univariates and multivariates of the binomial family (link logit), introducing the socioeconomic and demographic variables mentioned above. The results indicate that heat wave had an impact in only three of the districts analyzed. In the univariate models, all of the variables were statistically significant, but Ha of green zones lost significance in the multivariate model. Income level, existence of air conditioning units, and percent of the population over age 65 in the district remained as variables that modulate the impact of heat wave on daily mortality in the municipality of Madrid. Income level was the key variable that explained this behavior. The results obtained in this study show that there are factors at levels below the municipal level (district level) that should be considered as focus areas for health policy in order to decrease the impact of heat and promote the process of adaptation to heat in the context of climate change.