Socio-environmental modifiers of heat-related mortality in eight Swiss cities: A case time series analysis

Abstract

In the light of growing urbanization and projected temperature increases due to climate change, heat-related mortality in urban areas is a pressing public health concern. Heat exposure and vulnerability to heat may vary within cities depending on structural features and socioeconomic factors. This study examined the effect modification of the temperature-mortality association of three socio-environmental factors in eight Swiss cities and population subgroups (<75 and ≥ 75 years, males, females): urban heat islands (UHI) based on within-city temperature contrasts, residential greenness measured as normalized difference vegetation index (NDVI) and neighborhood socioeconomic position (SEP). We used individual death records from the Swiss National Cohort occurring during the warm season (May to September) in the years 2003–2016. We performed a case time series analysis using conditional quasi-Poisson and distributed lag non-linear models with a lag of 0–3 days. As exposure variables, we used daily maximum temperatures (Tmax) and a binary indicator for warm nights (Tmin ≥20 °C).In total, 53,593 deaths occurred during the study period. Overall across the eight cities, the mortality risk increased by 31% (1.31 relative risk (95% confidence interval: 1.20–1.42)) between 22.5 °C (the minimum mortality temperature) and 35 °C (the 99th percentile) for warm-season Tmax. Stratified analysis suggested that the heat-related risk at 35 °C is 26% (95%CI: −4%, 67%) higher in UHI compared to non-UHI areas. Indications of smaller risk differences were observed between the low vs. high greenness strata (Relative risk difference = 13% (95%CI: −11%; 44%)). Living in low SEP neighborhoods was associated with an increased heat related risk in the non-elderly population (<75 years). Our results indicate that UHI are associated with increased heat-related mortality risk within Swiss cities, and that features beyond greenness are responsible for such spatial risk differences.