What individual and neighbourhood-level factors increase the risk of heat-related mortality? A case-crossover study of over 185,000 deaths in London using high-resolution climate datasets

Murage, Peninah; Kovats, Sari; Sarran, Christophe; Taylor, Jonathon; McInnes, Rachel N.; Hajat, Shakoor

doi:10.1016/j.envint.2019.105292

Cited by 58 publications

(23 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Although we assessed several potential factors driving changes in vulnerability over time (e.g., percent of population above 80 y of age and population density), none of them resulted in relevance in the statistical model. However, we acknowledge that other relevant timevarying factors were not assessed due to the lack of data, such as access to air conditioning (Nordio et al 2015;Sera et al 2020), socioeconomic status (Ng et al 2016;Sera et al 2019a), or changes in land use (Murage et al 2020;Sera et al 2019b). Similarly, regions currently having a large proportion of young population, such as in some low-and middle-income countries, will also likely experience population aging in the future, according to current population projections (United Nations 2019).…”

Section: Discussionmentioning

confidence: 99%

Nationwide Analysis of the Heat- and Cold-Related Mortality Trends in Switzerland between 1969 and 2017: The Role of Population Aging

Schrijver

Bundo

Ragettli

et al. 2022

Environ Health Perspect

View full text Add to dashboard Cite

Background: Because older adults are particularly vulnerable to nonoptimal temperatures, it is expected that the progressive population aging will amplify the health burden attributable to heat and cold due to climate change in future decades. However, limited evidence exists on the contribution of population aging on historical temperature–mortality trends. Objectives: We aimed to a ) assess trends in heat- and cold-related mortality in Switzerland between 1969 and 2017 and b ) to quantify the contribution of population aging to the observed patterns. Methods: We collected daily time series of all-cause mortality by age group ( , 65–79, and 80 y and older) and mean temperature for each Swiss municipality (1969–2017). We performed a two-stage time-series analysis with distributed lag nonlinear models and multivariate longitudinal meta-regression to obtain temperature–mortality associations by canton, decade, and age group. We then calculated the corresponding excess mortality attributable to nonoptimal temperatures and compared it to the estimates obtained in a hypothetical scenario of no population aging. Results: Between 1969 and 2017, heat- and cold-related mortality represented 0.28% [95% confidence interval (CI): 0.18, 0.37] and 8.91% (95% CI: 7.46, 10.21) of total mortality, which corresponded to 2.4 and 77 deaths per 100,000 people annually, respectively. Although mortality rates for heat slightly increased over time, annual number of deaths substantially raised up from 74 (12;125) to 181 (39;307) between 1969–78 and 2009–17, mostly driven by the age group. Cold-related mortality rates decreased across all ages, but annual cold-related deaths still increased among the , due to the increase in the population at risk. We estimated that heat- and cold-related deaths would have been 52.7% and 44.6% lower, respectively, in the most recent decade in the absence of population aging. Discussion: Our findings suggest that a substantial proportion of historical temperature-related impacts can be attributed to population aging. We found that population aging has attenuated the decrease in cold-related mortality and amplified heat-related mortality. https://doi.org/10.1289/EHP9835

show abstract

Section: Discussionmentioning

confidence: 99%

Nationwide Analysis of the Heat- and Cold-Related Mortality Trends in Switzerland between 1969 and 2017: The Role of Population Aging

Schrijver

Bundo

Ragettli

et al. 2022

Environ Health Perspect

View full text Add to dashboard Cite

show abstract

“…Most of the previous studies on temperature-mortality associations were based on time series analyses of largely aggregated data [10][11][12] or, alternatively, on small-area assessments that only included single cities. [13][14][15][16][17] Additionally, the use of advanced statistical models permitted the inspection of complex features of temperature-health dependencies and the definition of multiple effect summaries, avoiding the use of risk functions depicting approximate asso ciations previously used in large-scale analyses. [18][19][20] Importantly, geographical differences were modelled through the definition of composite vulnerability indicators, computed as a combination of multiple contextual characteristics, overcoming limitations and potential biases resulting from separate analyses of individual factors.…”

Section: Discussionmentioning

confidence: 99%

“…[10][11][12] Conversely, small-area analyses have mostly focused on selected urban areas, and often have low statistical power and representativeness. [13][14][15][16][17] Only a few studies have performed large-scale analyses using high-resolution data; however, they have relied on effect summaries that provide limited information on the complex risk associations with non-optimal temperature. [18][19][20] More importantly, these studies have not considered that variations in mortality risk are likely to be related to contributions of strongly correlated area-level factors that can lead to distinct geographical differences in risk.…”

Section: Introductionmentioning

confidence: 99%

Small-area assessment of temperature-related mortality risks in England and Wales: a case time series analysis

Gasparrini¹,

Masselot²,

Scortichini³

et al. 2022

The Lancet Planetary Health

View full text Add to dashboard Cite

“…However, there are other factors that operate at a subregional level that are probably important in explaining the different behavior of heat with respect to mortality; for example, the age of built structures [21], their quality and insulation [24] and even the access to air conditioning [14]. The existence of green roofs and walls [5] and the accessibility of green zones could also influence mortality due to heat [26] and, therefore, could change the relationship between temperature and mortality. Explanations of the differences in the evolution of MMT should also take place at the sub-provincial level considered here.…”

Section: Discussionmentioning

confidence: 99%

Evolution of the threshold temperature definition of a heat wave vs. evolution of the minimum mortality temperature: a case study in Spain during the 1983–2018 period

et al. 2021

View full text Add to dashboard Cite

Background An area of current study concerns analysis of the possible adaptation of the population to heat, based on the temporal evolution of the minimum mortality temperature (MMT). It is important to know how is the evolution of the threshold temperatures (Tthreshold) due to these temperatures provide the basis for the activation of public health prevention plans against high temperatures. The objective of this study was to analyze the temporal evolution of threshold temperatures (Tthreshold) produced in different Spanish regions during the 1983–2018 period and to compare this evolution with the evolution of MMT. The dependent variable used was the raw rate of daily mortality due to natural causes ICD X: (A00-R99) for the considered period. The independent variable was maximum daily temperature (Tmax) during the summer months registered in the reference observatory of each region. Threshold values were determined using dispersion diagrams (annual) of the prewhitened series of mortality temperatures and Tmax. Later, linear fit models were carried out between the different values of Tthreshold throughout the study period, which permitted detecting the annual rate of change in Tthreshold. Results The results obtained show that, on average, Tthreshold has increased at a rate of 0.57 ºC/decade in Spain, while Tmax temperatures in the summer have increased at a rate of 0.41 ºC/decade, suggesting adaptation to heat. This rate of evolution presents important geographic heterogeneity. Also, the rate of evolution of Tthreshold was similar to what was detected for MMT. Conclusions The temporal evolution of the series of both temperature measures can be used as indicators of population adaptation to heat. The temporal evolution of Tthreshold has important geographic variation, probably related to sociodemographic and economic factors, that should be studied at the local level.

show abstract

What individual and neighbourhood-level factors increase the risk of heat-related mortality? A case-crossover study of over 185,000 deaths in London using high-resolution climate datasets

Cited by 58 publications

References 28 publications

Nationwide Analysis of the Heat- and Cold-Related Mortality Trends in Switzerland between 1969 and 2017: The Role of Population Aging

Nationwide Analysis of the Heat- and Cold-Related Mortality Trends in Switzerland between 1969 and 2017: The Role of Population Aging

Small-area assessment of temperature-related mortality risks in England and Wales: a case time series analysis

Evolution of the threshold temperature definition of a heat wave vs. evolution of the minimum mortality temperature: a case study in Spain during the 1983–2018 period

Contact Info

Product

Resources

About