Evaluating the association between extreme heat and mortality in urban Southwestern Ontario using different temperature data sources

Estimating the burden of disease attributable to high ambient temperature across climate zones: methodological framework with a case study

BACKGROUND

With high temperature becoming an increasing health risk due to a changing climate, it is important to quantify the scale of the problem. However, estimating the burden of disease (BoD) attributable to high temperature can be challenging due to differences in risk patterns across geographical regions and data accessibility issues.

METHODS

We present a methodological framework that uses Köppen-Geiger climate zones to refine exposure levels and quantifies the difference between the burden observed due to high temperatures and what would have been observed if the population had been exposed to the theoretical minimum risk exposure distribution (TMRED). Our proposed method aligned with the Australian Burden of Disease Study and included two parts: (i) estimation of the population attributable fractions (PAF); and then (ii) estimation of the BoD attributable to high temperature. We use suicide and self-inflicted injuries in Australia as an example, with most frequent temperatures (MFTs) as the minimum risk exposure threshold (TMRED).

RESULTS

Our proposed framework to estimate the attributable BoD accounts for the importance of geographical variations of risk estimates between climate zones, and can be modified and adapted to other diseases and contexts that may be affected by high temperatures.

CONCLUSIONS

As the heat-related BoD may continue to increase in the future, this method is useful in estimating burdens across climate zones. This work may have important implications for preventive health measures, by enhancing the reproducibility and transparency of BoD research.

Agreement in extreme precipitation exposure assessment is modified by race and social vulnerability

Epidemiologic investigations of extreme precipitation events (EPEs) often rely on observations from the nearest weather station to represent individuals' exposures, and due to structural factors that determine the siting of weather stations, levels of measurement error and misclassification bias may differ by race, class, and other measures of social vulnerability. Gridded climate datasets provide higher spatial resolution that may improve measurement error and misclassification bias. However, similarities in the ability to identify EPEs among these types of datasets have not been explored. In this study, we characterize the overall and temporal patterns of agreement among three commonly used meteorological data sources in their identification of EPEs in all census tracts and counties in the conterminous United States over the 1991-2020 U.S. Climate Normals period and evaluate the association between sociodemographic characteristics with agreement in EPE identification. Daily precipitation measurements from weather stations in the Global Historical Climatology Network (GHCN) and gridded precipitation estimates from the Parameter-elevation Relationships on Independent Slopes Model (PRISM) and the North American Land Data Assimilation System (NLDAS) were compared in their ability to identify EPEs defined as the top 1% of precipitation events or daily precipitation >1 inch. Agreement among these datasets is fair to moderate from 1991 to 2020. There are spatial and temporal differences in the levels of agreement between ground stations and gridded climate datasets in their detection of EPEs in the United States from 1991 to 2020. Spatial variation in agreement is most strongly related to a location's proximity to the nearest ground station, with areas furthest from a ground station demonstrating the lowest levels of agreement. These areas have lower socioeconomic status, a higher proportion of Native American population, and higher social vulnerability index scores. The addition of ground stations in these areas may increase agreement, and future studies intending to use these or similar data sources should be aware of the limitations, biases, and potential for differential misclassification of exposure to EPEs. Most importantly, vulnerable populations should be engaged to determine their priorities for enhanced surveillance of climate-based threats so that community-identified needs are met by any future improvements in data quality.

Territory Differences in Adaptation to Heat among Persons Aged 65 Years and Over in Spain (1983-2018)

Climate change is currently regarded as the greatest global threat to human health, and its health-related consequences take different forms according to age, sex, socioeconomic level, and type of territory. The aim of this study is to ascertain the differences in vulnerability and the heat-adaptation process through the minimum mortality temperature (MMT) among the Spanish population aged ≥65 years by territorial classification. A retrospective, longitudinal, ecological time-series study, using provincial data on daily mortality and maximum daily temperature across the period 1983-2018, was performed, differentiating between urban and nonurban populations. The MMTs in the study period were higher for the ≥65-year age group in urban provinces, with a mean value of 29.6 °C (95%CI 29.2-30.0) versus 28.1 °C (95%CI 27.7-28.5) in nonurban provinces. This difference was statistically significant (p < 0.05). In terms of adaptation levels, higher average values were obtained for nonurban areas, with values of 0.12 (95%CI -0.13-0.37), than for urban areas, with values of 0.09 (95%CI -0.27-0.45), though this difference was not statistically significant (p < 0.05). These findings may contribute to better planning by making it possible to implement more specific public health prevention plans. Lastly, they highlight the need to conduct studies on heat-adaptation processes, taking into account various differential factors, such as age and territory.

The trend and spatial spread of multisectoral climate extremes in CMIP6 models

Climate change could exacerbate extreme climate events. This study investigated the global and continental representations of fourteen multisectoral climate indices during the historical (1979-2014), near future (2025-2060) and far future (2065-2100) periods under two emission scenarios, in eleven Coupled Model Intercomparison Project (CMIP) General Circulation Models (GCM). We ranked the GCMs based on five metrics centred on their temporal and spatial performances. Most models followed the reference pattern during the historical period. MPI-ESM ranked best in replicating the daily precipitation intensity (DPI) in Africa, while CANESM5 GCM ranked first in heatwave index (HI), maximum consecutive dry days (MCCD). Across the different continents, MPI-LR GCM performed best in replicating the DPI, except in Africa. The model ranks could provide valuable information when selecting appropriate GCM ensembles when focusing on climate extremes. A global evaluation of the multi-index causal effects for the various indices shows that the dry spell total length (DSTL) was the most crucial index modulating the MCCD for all continents. Also, most indices exhibited a positive climate change signal from the historical to the future. Therefore, it is crucial to design appropriate strategies to strengthen resilience to extreme climatic events while mitigating greenhouse gas emissions.

Extreme Temperature and Mortality by Educational Attainment in Spain, 2012-2018

Extreme temperatures are a threat to public health, increasing mortality in the affected population. Moreover, there is substantial research showing how age and gender shape vulnerabilities to this environmental risk. However, there is only limited knowledge on how socioeconomic status (SES), operationalized using educational attainment, stratifies the effect of extreme temperatures on mortality. Here, we address this link using Poisson regression and administrative data from 2012 to 2018 for 50 Spanish Provinces on individuals aged above 65 matched with meteorological data provided by the E-OBS dataset. In line with previous studies, results show that hot and cold days increase mortality. Results on the interaction between SES and extreme temperatures show a positive and significant effect of exposure to heat and cold for individuals with medium and low SES level. Conversely, for high SES individuals we do not find evidence of a robust association with heat or cold. We further investigate how the local climate moderates these associations. A warmer climate increases risks with exposures to low temperatures and vice versa for hot temperatures in the pooled sample. Moreover, we observe that results are mostly driven by low SES individuals being particularly vulnerable to heat in colder climates and cold in warmer climates. In conclusion, results highlight how educational attainment stratifies the effect of extreme temperatures and the relevance of the local climate in shaping risks of low SES individuals aged above 65.

Associations between Perceptions and Measures of Weather and Walking, United States-2015

INTRODUCTION

Weather can be a barrier to walking. Understanding how perceptions of weather as a barrier and measured temperature are associated with walking can inform monitoring and promotion strategies. The objective of this study is to examine the association between perceptions of weather as a barrier to walking and measured weather with the volume of leisure and transportation walking.

METHODS

The 2015 National Health Interview Survey (NHIS) assessed participation in and volume of walking (transportation, leisure) in the past week and frequency of reporting weather as a barrier to walking. Data were collected over the entire year. In 2019, we merged month-specific temperature data from the PRISM climate group with individual NHIS records. We examined associations using logistic (participation) and linear regression models (volume).

RESULTS

Participation in walking increased as frequency of reporting weather as a barrier to walking decreased, from 'almost always' (transportation: 23%, leisure: 42%) to 'a little of the time' (transportation: 40%, leisure: 67%). Among adults reporting walking, walking volume increased as frequency of reporting weather as a barrier decreased from 'almost always' (transportation: 51 min/week, leisure: 64 min/week) to 'never' (transportation: 69 min/week, leisure: 98 min/week). Month-specific temperature was significantly associated with leisure walking with lower participation at the lowest and highest temperature quintiles, although the strength of the association differed by frequency of reporting weather as a barrier.

CONCLUSIONS

In general, prevalence and volume of leisure and transportation walking decreased as the perception of weather as a barrier increased. Low and high temperature conditions were also associated with leisure walking participation, particularly among adults with increased perceptions of weather as a barrier. Our findings highlight the importance of including strategies to help adults overcome perceived and actual weather-related barriers in walking promotion efforts.