The effect of cold waves on mortality in urban and rural areas of Madrid

Abstract

Background While many studies analyze the effect of extreme thermal events on health, little has been written about the effects of extreme cold on mortality. This scarcity of papers is particularly relevant when we search studies about extreme cold on the health of rural population. Therefore, we tried to analyze the effect of cold waves on urban areas and rural areas from Madrid and to test whether differentiated effects exist between both population classes. For this purpose, we analyzed data from the municipalities with over 10,000 inhabitants for the period from January 1, 2000 through December 31, 2013. Municipalities were classified as urban or rural (Eurostat), and they were grouped into similar climatological zones: Urban Metropolitan Centre (UMC), Rural Northern Mountains (RNM), Rural Centre (RC) and Southern Rural (SR). The dependent variable was the daily mortality rate due to natural causes per million inhabitants (CIE-X: A00-R99) that occurred between the months of November and March for the period. The independent variable was minimum daily temperature (ºC) (Tmin). Social and demographic contextual variables were used, including: population > age 64 (%), deprivation index and housing indicators. The analysis was carried out in three phases: (1) determination of the threshold temperature (Tthreshold) which defines the cold waves; (2) determination of the relative risk (RR) for cold waves using Poisson linear regression (GLM); and (3) using GLM of the binomial family, Odds Ratios (OR) were calculated to analyze the relationship between the frequency of the appearance of cold waves and the socioeconomic variables. Results The UMC zone experienced 585 extreme cold events related to attributable increases in the mortality rate. The average number of cold waves in the rural zones was 319. The primary risk factor was the percentage of population over age 64, and the primary protective factor was housing rehabilitation. As a whole, the period experienced more cold waves (1542) than heat waves (1130). Conclusion The UMC was more vulnerable than the rural areas. Furthermore, the results support the development of prevention policies, especially considering the fact that cold wave events were more frequent than heat waves.

Rural-urban gradients and all-cause, cardiovascular and cancer mortality in Spain using individual data

“…For instance, air pollution, with its highest concentrations found in large cities and with consistent evidence of its impact on mortality ( Khomenko et al, 2021 ; Liu et al, 2019 ). Also, extremes temperatures, in the form of heat and cold waves, are known to affect Spanish metropolitan areas more than rural municipalities, as illustrated in recent research in the Madrid region ( López-Bueno, Navas-Martín, Díaz, et al, 2021 ; 2021b ). The traffic-related noise pollution has also been linked to premature mortality in large cities ( Cai et al, 2021 ).…”

Analysis of vulnerability to heat in rural and urban areas in Spain: What factors explain Heat's geographic behavior?

“…To establish Tmax percentiles, we followed the recommended methodology described in the literature (Carmona et al, 2016(Carmona et al, , 2017Díaz et al, 2018;Linares et al, 2016;López-Bueno et al, 2021a, 2021bMirón et al, 2015). First ARIMA models were fitted to the full mortality rate time series, so that 5114 days were include in each model, and an ARIMA model was calculated to each province.…”

“…The use of percentiles as a measure of impact of heat has been previously reported (López-Bueno et al, 2019;López-Bueno et al, 2021a, 2021b. This definition has the advantage of being a direct result of the Fig.…”

Impact of the Eurasian Zonal Circulation on the Interannual Variability of Winter Surface Air Temperature and Subseasonal Temperature Reversal in North China

“…These reversals were linked to extreme cold events occurring either early or late in the winter season, resulting in SAT differences between early and late winters of 6.5°C or more (Geng et al., 2017; Yang & Fan, 2022). Such extreme weather events, including cold waves, heavy rain, snow, and ice, during the subseasonal SAT reversals, can have severe impacts on human health, and national economies, and may also end crop dormancy early or freeze crops thereby causing significant losses to agriculture (Añel et al., 2017; Hochman et al., 2022; López‐Bueno et al., 2021). Despite the importance of accurate predictions of winter mean SAT and subseasonal SAT reversals, achieving precise forecasts remains a significant challenge (Cui et al., 2021; Li et al., 2021).…”