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Trends in tropical nights and their effects on mortality in Switzerland across 50 years [1]

['Vanessa Rippstein', 'Institute Of Social', 'Preventive Medicine', 'Ispm', 'University Of Bern', 'Bern', 'Oeschger Centre For Climate Change Research', 'Occr', 'Evan De Schrijver', 'Graduate School Of Health Sciences']

Date: 2023-05

Our findings indicate that the frequency of TNs in Switzerland overall increased between 1970 and 2019, mainly in urban areas (Lausanne, Geneva, Basel, Lugano, and Zurich). The population exposed to TNs in Switzerland also increased, with the most substantial increases in the largest cities. However, the vulnerability to TNs in terms of associated mortality risk seems to be highly variable across cantons and cities. Our results suggest that TNs should be still considered a relevant health hazard in Switzerland. This has a sense of urgency since it has been suggested that due to climate change, the frequency of TNs will increase in the future in Switzerland [4,22].

Due to climate change, the average temperature has increased during the last decades and is projected to further increase in all regions of Switzerland in the future [ 22 ]. The CH2018 report [ 22 ] states that Switzerland represents a hotspot for changes in hot temperature extremes, such as heatwaves and TNs. Our results confirm these observations with an increasing trend in the frequency of TNs. In addition, these changes occur in low-lying areas with high population density, where the urban heat island effect may further amplify these extremes [ 22 , 39 ], as we observed in this study with larger increases in urban regions. Other studies from Georgian Territory, the Spanish Mediterranean coast, and Seoul, also showed a significant increase in TNs during the last decades [ 40 – 42 ].

The population exposed to TNs increased in Switzerland between 1970 and 2019, due to both the exponential increase in the frequency of TNs and in the population [ 43 ], which mainly occurred around the largest cities and urban agglomerations. Our findings are similar to a previous study by Tuholske et al. which explored whether population growth or increasing temperature is the main driver of the increasing exposure to extreme heat [ 44 ].

4.3 Vulnerability

We did not observe a clear spatial pattern in vulnerability to TNs across the cantons or the largest cities of Switzerland (Figs 4 and 5). For example, TN may represent a risk for the health of the population living in Vaud, Zurich, Lucerne, and Solothurn, with increased mortality between 20–40%. Whereas TNs may be associated with a protective effect in Ticino, Basel-Land, Geneva and Thurgau. Previous studies also found similar TN-mortality risks with highly heterogeneous patterns between populations [19,20]. This disparity across cantons can be attributed to differences in public health strategies, infrastructure (i.e. greenness), socioeconomic status, social equity, and cultural characteristics [45–49]. Heat action plans might explain in part the protective effect of TNs in Basel-Land, but not in Thurgau, Geneva and Ticino, as shown in the subperiod analysis (S3 Table). These would suggest that the implementation of more ambitious plans in the cantons of Geneva and Ticino may not explain the protective effect. Recent studies exploring the effectiveness of heat-health warning systems on preventing heat-related mortality also showed heterogenous results [28,50–53]. Additionally, a recent study concluded that vulnerability factors to heat differed between urban and rural populations in Switzerland [54]. Finally, we cannot disregard that different climatic characteristics of the TNs potentially more prevalent in some regions in Switzerland, such as a different intra-day temperature variability, may also explain differences in mortality risk associated with these events [55].

We also observed substantial heterogeneity in the TN-mortality risk between the cantons and their corresponding main cities. For example, while TNs may have a protective effect in the city, they may represent a risk at the cantonal level (i.e., Lausanne and Vaud). We hypothesize that there could be a gap between rural and urban residents’ sensitivity to heat. Urban residents may be more aware and potentially acclimatized to heat compared to the rural population and, therefore, better prepared in case of a heat wave and increased occurrence of TNs [56,57]. Although we did not observe substantial differences in the risk of TNs between decades due to large uncertainty, few studies have explored the temporal impact of heat on mortality. Possibly some of the variation over time could in part be explained by increased air conditioning uptake, increase in socio-economic status as well as changes in demographic structure [30,58].

We acknowledge several limitations of this study. We may consider our results as a conservative estimate because of the following reasons. First, although gridded temperature data has shown to be useful in epidemiological analysis [59], it is likely that in this study it might have partly removed the temporal and spatial variability in nighttime temperature. Second, we might have not fully captured the effect of urban heat island in the main cities due to the nature of the ERA5-Land reanalysis data. As an illustration, S3 Fig shows a higher frequency of TNs registered in areas with complex orography (i.e., Ticino) when met-station data is used compared to ERA5-Land, while a similar number is obtained in areas with more homogeneous characteristics (i.e., Zurich). Other similar studies on TNs and mortality alternatively used temperature data from meteorological stations [18–20]. However, we decided to not use temperature data from weather stations because it was very complex to derive district-specific temperature series given the heterogeneous orography and the limited number of stations, in particular before the 2000s. Additionally, we decided to use the definition of TNs established by MeteoSwiss, the climatological service in Switzerland. Other studies used percentile values (95th, 99th) to define a TN or hot nights because it would account for the characteristics of the local climate [18,20]. Future studies are warranted to explore how the choice of data set and the definition of TNs may influence the TN-mortality association.

We did not control for potential confounders such as air pollution and humidity since data on these variables were not available for the whole study period. However, we expect that the confounding effect, if any, would be small, as shown in recent studies [9,60]. In addition, we did not assess the role of contextual variables in explaining the differences across cantons and cities. And, finally, we cannot disregard the presence of exposure misclassification (i.e., Berkson error) typically found in this kind of ecological analysis which would lead to an increase in the imprecision of our estimates However, would also affect the precision of our estimates [61].

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[1] Url: https://journals.plos.org/climate/article?id=10.1371/journal.pclm.0000162

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