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.

尽管有大量关于热浪影响的科学证据，但很少有研究分析社会人口统计学因素对市政以下水平热浪影响的影响。这项研究的目的是分析收入水平，65岁以上马德里地区居民的空调设备的存在以及马德里各区绿色区域的公顷面积（Ha）在热量对一月之间每日死亡率的影响中的作用。分别于2010年1月1日和2013年12月31日进行了分析。使用广义线性（GLM）泊松回归模型来计算热浪对自然原因造成的死亡率影响的相对风险（RR）和归因风险（RA） （CIEX：A00-R99）。使用二项式家族的GLM单变量和多变量（链接logit）分析了获得的风险模式，介绍上述社会经济和人口变量。结果表明，热浪仅对三个地区产生了影响。在单变量模型中，所有变量在统计上都是显着的，但绿色区域的Ha在多变量模型中失去了显着性。该地区的收入水平，空调设备的存在以及该地区65岁以上人口的百分比仍然是变量，可以调节热浪对马德里市每日死亡率的影响。收入水平是解释此行为的关键变量。但是绿色区域的Ha在多变量模型中失去了意义。该地区的收入水平，空调设备的存在以及该地区65岁以上人口的百分比仍然是变量，可以调节热浪对马德里市每日死亡率的影响。收入水平是解释此行为的关键变量。但是绿色区域的Ha在多变量模型中失去了意义。该地区的收入水平，空调设备的存在以及该地区65岁以上人口的百分比仍然是变量，可以调节热浪对马德里市每日死亡率的影响。收入水平是解释此行为的关键变量。

这项研究获得的结果表明，在市级（区级）以下的因素应被视为卫生政策的重点领域，以减少热量的影响并促进环境中的热量适应过程。气候变化。