Methods to Estimate Acclimatization to Urban Heat Island Effects on Heat- and Cold-Related Mortality

Spatial Bayesian distributed lag non-linear models (SB-DLNM) for small-area exposure-lag-response epidemiological modelling

BACKGROUND

Distributed lag non-linear models (DLNMs) are the reference framework for modelling lagged non-linear associations. They are usually used in large-scale multi-location studies. Attempts to study these associations in small areas either did not include the lagged non-linear effects, did not allow for geographically-varying risks or downscaled risks from larger spatial units through socioeconomic and physical meta-predictors when the estimation of the risks was not feasible due to low statistical power.

METHODS

Here we proposed spatial Bayesian DLNMs (SB-DLNMs) as a new framework for the estimation of reliable small-area lagged non-linear associations, and demonstrated the methodology for the case study of the temperature-mortality relationship in the 73 neighbourhoods of the city of Barcelona. We generalized location-independent DLNMs to the Bayesian framework (B-DLNMs), and extended them to SB-DLNMs by incorporating spatial models in a single-stage approach that accounts for the spatial dependence between risks.

RESULTS

The results of the case study highlighted the benefits of incorporating the spatial component for small-area analysis. Estimates obtained from independent B-DLNMs were unstable and unreliable, particularly in neighbourhoods with very low numbers of deaths. SB-DLNMs addressed these instabilities by incorporating spatial dependencies, resulting in more plausible and coherent estimates and revealing hidden spatial patterns. In addition, the Bayesian framework enriches the range of estimates and tests that can be used in both large- and small-area studies.

CONCLUSIONS

SB-DLNMs account for spatial structures in the risk associations across small areas. By modelling spatial differences, SB-DLNMs facilitate the direct estimation of non-linear exposure-response lagged associations at the small-area level, even in areas with as few as 19 deaths. The manuscript includes an illustrative code to reproduce the results, and to facilitate the implementation of other case studies by other researchers.

Mapping disability and climate change knowledge base in Scopus using bibliometric analysis

Background

Climate change and disability are rarely addressed by academic scholars within the spectrum of disabilities and as a single field of study. However, the intersectionality of disability exacerbates the vulnerability of people with disabilities to climate change as climate change frameworks in the Global North and South continue excluding them.

Objectives

This study aims to map the research-based knowledge housed in Scopus on disability and climate change. At the same time, it provides insights into innovative (novelty) ways of thinking and proposes a futuristic research agenda.

Method

A bibliometric analysis was conducted on Scopus-indexed articles using VOSviewer to map co-occurrences of keywords and co-authorship, and a manual thematic-scoping review augmented the data analysis.

Results

The disability and climate change debate as a joint study evolved from concern among health practitioners to human rights and social inclusion.

Conclusion

In conclusion, there is a skewness towards mental health and medical sociology lens, while other sub-groups of persons with disabilities are yet to be engaged in co-creating disability-inclusive climate change knowledge.

Contribution

Thematic areas emerged as gaps that future studies embed principles enshrined in the United Nations Convention for the Rights of Persons with Disabilities and the Sustainable Development Goals.

Premature Deaths Due To Heat Exposure: The Potential Effects of Neighborhood-Level Versus City-Level Acclimatization Within US Cities

For the population of a given US city, the risk of premature death associated with heat exposure increases as temperatures rise, but risks in hotter cities are generally lower than in cooler cities at equivalent temperatures due to factors such as acclimatization. Those living in especially hot neighborhoods within cities might therefore suffer much more than average if such adaptation is only at the city-wide level, whereas they might not experience greatly increased risk if adjustment is at the neighborhood level. To compare these possibilities, we use high spatial resolution temperature data to evaluated heat-related deaths assuming either adjustment at the city-wide or at the neighborhood scale in 10 large US cities. On average, we find that if inhabitants are adjusted to their local conditions, a neighborhood that was 10°C hotter than a cooler one would experience only about 1.0-1.5 excess heat deaths per year per 100,000 persons. By contrast, if inhabitants are acclimatized to city-wide temperatures, the hotter neighborhood would experience about 15 excess deaths per year per 100,000 persons. Using idealized analyses, we demonstrate that current city-wide epidemiological data do not differentiate between these differing adjustments. Given the very large effects of assumptions about neighborhood-level acclimatization found here, as well as the fact that current literature is conflicting on the spatial scale of acclimatization, more neighborhood-level epidemiological data are urgently needed to determine the health impacts of variations in heat exposure within urban areas, better constrain projected changes, and inform mitigation efforts.

Urban heat island impacts on heat-related cardiovascular morbidity: A time series analysis of older adults in US metropolitan areas

Many United States (US) cities are experiencing urban heat islands (UHIs) and climate change-driven temperature increases. Extreme heat increases cardiovascular disease (CVD) risk, yet little is known about how this association varies with UHI intensity (UHII) within and between cities. We aimed to identify the urban populations most at-risk of and burdened by heat-related CVD morbidity in UHI-affected areas compared to unaffected areas. ZIP code-level daily counts of CVD hospitalizations among Medicare enrollees, aged 65-114, were obtained for 120 US metropolitan statistical areas (MSAs) between 2000 and 2017. Mean ambient temperature exposure was estimated by interpolating daily weather station observations. ZIP codes were classified as low and high UHII using the first and fourth quartiles of an existing surface UHII metric, weighted to each have 25% of all CVD hospitalizations. MSA-specific associations between ambient temperature and CVD hospitalization were estimated using quasi-Poisson regression with distributed lag non-linear models and pooled via multivariate meta-analyses. Across the US, extreme heat (MSA-specific 99th percentile, on average 28.6 °C) increased the risk of CVD hospitalization by 1.5% (95% CI: 0.4%, 2.6%), with considerable variation among MSAs. Extreme heat-related CVD hospitalization risk in high UHII areas (2.4% [95% CI: 0.4%, 4.3%]) exceeded that in low UHII areas (1.0% [95% CI: -0.8%, 2.8%]), with upwards of a 10% difference in some MSAs. During the 18-year study period, there were an estimated 37,028 (95% CI: 35,741, 37,988) heat-attributable CVD admissions. High UHII areas accounted for 35% of the total heat-related CVD burden, while low UHII areas accounted for 4%. High UHII disproportionately impacted already heat-vulnerable populations; females, individuals aged 75-114, and those with chronic conditions living in high UHII areas experienced the largest heat-related CVD impacts. Overall, extreme heat increased cardiovascular morbidity risk and burden in older urban populations, with UHIs exacerbating these impacts among those with existing vulnerabilities.

Identifying and characterizing frequency and maximum durations of surface urban heat and cool island across global cities

Surface urban heat island (SUHI) has been widely reported from a local to global scale. However, variations and controls of temporal indicators for SUHI and SUCI (surface urban cool island) remain unclear. This paper firstly reconstructed the seamless daily LST (land surface temperature) based on ATC-SKT (annual temperature cycle-skin temperature) and comprehensively validated for SUHI applications across 1112 global cities. Based on the seamless daily LST, this paper further characterized the spatiotemporal variations of the frequency (SUHIF and SUCIF) and maximum duration (SUHID and SUCID) and investigated the impacts from related factors, inconsideration of the different characteristics of SUHI and SUCI. There are five major findings. (1) The seamless daily LST reconstructed based on ATC-SKT is validated through pixel-based temperature and city-based SUHII accuracy assessments. (2) The selection of the frequency threshold is based on robustness for LST accuracy, approximation to SUHII global average, and mitigation of frequency saturation. (3) The average daytime SUHIF is 214 days/year, with 44 % of cities exhibiting SUHI occurrences for almost every day in summer. The nighttime SUHIF is 175 days/year, with increasing latitudinal variations from equatorial to polar regions. The daytime SUCIF is 41 days/year, with the greatest average frequency of 172 days/year exhibited in arid regions. (4) The average SUHID is 147 days at daytime and 58 days at nighttime, with relatively opposite geographical distributions between day and night. (5) Greater vegetation difference at daytime and greater albedo difference at nighttime result in more occurrences and longer consecutive durations of SUHI, with opposite effects on the temporal indicators of SUCI. Furthermore, the improvements in daily SUHII and impacts from the maximum duration were discussed. This paper aims to identify and highlight the period with significant SUHI and SUCI effects across global cities for further mitigation.

Urban heat island effect-related mortality under extreme heat and non-extreme heat scenarios: A 2010-2019 case study in Hong Kong

The urban heat island (UHI) effect exacerbates the adverse impact of heat on human health. However, while the UHI effect is further intensified during extreme heat events, prior studies have rarely mapped the UHI effect during extreme heat events to assess its direct temperature impact on mortality. This study examined the UHI effect during extreme heat and non-extreme heat scenarios and compared their temperature-mortality associations in Hong Kong from 2010 to 2019. Four urban heat island degree hour (UHIdh) scenarios were mapped onto Hong Kong's tertiary planning units and classified into three levels (Low, Moderate, and High). We assessed the association between temperature and non-external mortality of populations living in each UHIdh level for the extreme heat/non-extreme heat scenarios during the 2010-2019 hot seasons. Our results showed substantial differences between the temperature-mortality associations in the three levels under the UHIdh extreme heat scenario (UHIdh_EH). While there was no evidence of increased mortality in Low UHIdh_EH areas, the mortality risk in Moderate and High UHIdh_EH areas were significantly increased during periods of hot temperature, with the High UHIdh_EH areas displaying almost double the risk (RR: 1.08, 95%CI: 1.03, 1.14 vs. RR: 1.05, 95 % CI: 1.01, 1.09). However, other non-extreme heat UHI scenarios did not demonstrate as prominent of a difference. When stratified by age, the heat effects were found in Moderate and High UHIdh_EH among the elderly aged 75 and above. Our study found a difference in the temperature-mortality associations based on UHI intensity and potential heat vulnerability of populations during extreme heat events. Preventive measures should be taken to mitigate heat especially in urban areas with high UHI intensity during extreme heat events, with particular attention and support for those prone to heat vulnerability, such as the elderly and poorer populations.

Ambient temperature and stillbirth risks in northern Sweden, 1880-1950

Background

Climate vulnerability of the unborn can contribute to adverse birth outcomes, in particular, but it is still not well understood. We investigated the association between ambient temperature and stillbirth risk among a historical population in northern Sweden (1880-1950).

Methods

We used digitized parish records and daily temperature data from the study region covering coastal and inland communities some 600 km north of Stockholm, Sweden. The data included 141,880 births, and 3,217 stillbirths, corresponding to a stillbirth rate of 22.7 (1880-1950). The association between lagged temperature (0-7 days before birth) and stillbirths was estimated using a time-stratified case-crossover design. Incidence risk ratios (IRR) with 95% confidence intervals were computed, and stratified by season and sex.

Results

We observed that the stillbirth risk increased both at low and high temperatures during the extended summer season (April to September), at -10°C, and the IRR was 2.3 (CI 1.28, 4.00) compared to the minimum mortality temperature of +15°C. No clear effect of temperature during the extended winter season (October to March) was found. Climate vulnerability was greater among the male fetus compared to the female counterparts.

Conclusion

In this subarctic setting before and during industrialization, both heat and cold during the warmer season increased the stillbirth risk. Urbanization and socio-economic development might have contributed to an uneven decline in climate vulnerability of the unborn.

Projecting the impacts of housing on temperature-related mortality in London during typical future years

Climate change means the UK will experience warmer winters and hotter summers in the future. Concurrent energy efficiency improvements to housing may modify indoor exposures to heat or cold, while population aging may increase susceptibility to temperature-related mortality. We estimate heat and cold mortality and energy consumption in London for typical (non-extreme) future climates, given projected changes in population and housing. Building physics models are used to simulate summertime and wintertime indoor temperatures and space heating energy consumption of London dwellings for 'baseline' (2005-2014) and future (2030s, 2050s) periods using data from the English Housing Survey, historical weather data, and projected future weather data with temperatures representative of 'typical' years. Linking to population projections, we calculate future heat and cold attributable mortality and energy consumption with demolition, construction, and alternative scenarios of energy efficiency retrofit. At current retrofit rates, around 168-174 annual cold-related deaths per million population would typically be avoided by the 2050s, or 261-269 deaths per million under ambitious retrofit rates. Annual heat deaths would typically increase by 1 per million per year under the current retrofit rate, and 12-13 per million under ambitious rates without population adaptation to heat. During typical future summers, an estimated 38-73% of heat-related deaths can be avoided using external shutters on windows, with their effectiveness lower during hotter weather. Despite warmer winters, ambitious retrofit rates are necessary to reduce typical annual energy consumption for heating below baseline levels, assuming no improvement in heating system efficiencies. Concerns over future overheating in energy efficient housing are valid but increases in heat attributable mortality during typical and hot (but not extreme) summers are more than offset by significant reductions in cold mortality and easily mitigated using passive measures. More ambitious retrofit rates are critical to reduce energy consumption and offer co-benefits for reducing cold-related mortality.

Comparing temperature-related mortality impacts of cool roofs in winter and summer in a highly urbanized European region for present and future climate

Human health can be negatively impacted by hot or cold weather, which often exacerbates respiratory or cardiovascular conditions and increases the risk of mortality. Urban populations are at particular increased risk of effects from heat due to the Urban Heat Island (UHI) effect (higher urban temperatures compared with rural ones). This has led to extensive investigation of the summertime UHI, its impacts on health, and also the consideration of interventions such as reflective 'cool' roofs to help reduce summertime overheating effects. However, interventions aimed at limiting summer heat are rarely evaluated for their effects in wintertime, and thus their overall annual net impact on temperature-related health effects are poorly understood. In this study we use a regional weather model to simulate the winter 2009/10 period for an urbanized region of the UK (Birmingham and the West Midlands), and use a health impact assessment to estimate the impact of reflective 'cool' roofs (an intervention usually aimed at reducing the UHI in summer) on cold-related mortality in winter. Cool roofs have been shown to be effective at reducing maximum temperatures during summertime. In contrast to the summer, we find that cool roofs have a minimal effect on ambient air temperatures in winter. Although the UHI in summertime can increase heat-related mortality, the wintertime UHI can have benefits to health, through avoided cold-related mortality. Our results highlight the potential annual net health benefits of implementing cool roofs to reduce temperature-related mortality in summer, without reducing the protective UHI effect in winter. Further, we suggest that benefits of cool roofs may increase in future, with a doubling of the number of heat-related deaths avoided by the 2080s (RCP8.5) compared to summer 2006, and with insignificant changes in the impact of cool-roofs on cold-related mortality. These results further support reflective 'cool' roof implementation strategies as effective interventions to protect health, both today and in future.

Science Policy to Advance a Climate Change and Health Research Agenda in the United States

Climate change is thought to be one of the greatest public health threats of the 21st century and there has been a tremendous growth in the published literature describing the health implications of climate change over the last decade. Yet, there remain several critical knowledge gaps in this field. Closing these gaps is crucial to developing effective interventions to minimize the health risks from climate change. In this commentary, we discuss policy trends that have influenced the advancement of climate change and health research in the United States context. We then enumerate specific knowledge gaps that could be addressed by policies to advance scientific research. Finally, we describe tools and methods that have not yet been fully integrated into the field, but hold promise for advancing the science. Prioritizing this advancement offers the potential to improve public health-related policies on climate change.

Heat-mortality risk and the population concentration of metropolitan areas in Japan: a nationwide time-series study

BACKGROUND

The complex role of urbanisation in heat-mortality risk has not been fully studied. Japan has experienced a rapid population increase and densification in metropolitan areas since the 2000s; we investigated the effects of population concentration in metropolitan areas on heat-mortality risk using nationwide data.

METHODS

We collected time-series data for mortality and weather variables for all 47 prefectures in Japan (1980-2015). The prefectures were classified into three sub-areas based on population size: lowest (<1 500 000), intermediate (1 500 000 to 3 000 000), and highest (>3 000 000; i.e. metropolitan areas). Regional indicators associated with the population concentration of metropolitan areas were obtained.

RESULTS

Since the 2000s, the population concentration intensified in the metropolitan areas, with the highest heat-mortality risk in prefectures with the highest population. Higher population density and apartment % as well as lower forest area and medical services were associated with higher heat-mortality risk; these associations have generally become stronger since the 2000s.

CONCLUSIONS

Population concentration in metropolitan areas intensified interregional disparities in demography, living environments, and medical services in Japan; these disparities were associated with higher heat-mortality risk. Our results can contribute to policies to reduce vulnerability to high temperatures.

Analysis of the impact of heat waves on daily mortality in urban and rural areas in Madrid

The objective of this study was to analyze and compare the effect of high temperatures on daily mortality in the urban and rural populations in Madrid. Data were analyzed from municipalities in Madrid with a population of over 10,000 inhabitants during the period from January 1, 2000 to December 31, 2020. Four groups were generated: Urban Metropolitan Center, Rural Northern Mountains, Rural Center, and Southern Rural. The dependent variable used was the rate of daily mortality due to natural causes per million inhabitants (CIE-X: A00-R99) between the months of June and September for the period. The primary independent variable was maximum daily temperature. Social and demographic "context variables" were included: population >64 years of age (%), deprivation index and housing indicators. The analysis was carried out in three phases: 1) determination of the threshold definition temperature of a heat wave (Tumbral) for each study group; 2) determination of relative risks (RR) attributable to heat for each group using Poisson linear regression (GLM), and 3) calculation of odds ratios (OR) using binomial family GLM for the frequency of the appearance of heat waves associated with context variables. The resulting percentiles (for the series of maximum daily temperatures for the summer months) corresponding to Tthreshold were: 74th percentile for Urban Metropolitan Center, 76th percentile for Southern Rural, 83rd for Rural Northern Mountains and 98th percentile for Center Rural (98). Greater vulnerability was found for the first two. In terms of context variables that explained the appearance of heat waves, deprivation index level, population >64 years of age and living in the metropolitan area were found to be risk factors. Rural and urban areas behaved differently, and socioeconomic inequality and the composition of the population over age 64 were found to best explain the vulnerability of the Rural Center and Southern Rural zones.

Does climatic zone of birth modify the temperature-mortality association of London inhabitants during the warm season? A time-series analysis for 2004-2013

BACKGROUND

It is known that on days with high temperatures higher mortality is observed and there is a minimum mortality temperature (MMT) point which is higher in places with warmer climate. This indicates some population adaptation to local climate but information on how quickly this adaptation will occur under climate change is lacking.

METHODS

To investigate this, we associated daily mortality data with temperature during the warm period in 2004-2013 for London inhabitants born in five climatic zones (UK, Tropical, Sub-tropical, Boreal and Mixed). We fitted Poisson regression with distributed-lag non-linear models for each climatic zone group separately to estimate group-specific exposure-response associations and MMTs. We report relative risks of death comparing the 95th percentile (21 °C) and maximum (25 °C) of the temperature distribution in London with the zone-specific minimum mortality temperature.

RESULTS

No heat-related mortality was observed for people born in countries with Sub-tropical and Mixed climates. We observed an increase of 26%, 35% and 39% in the risk of death at 25 °C compared to the MMT in people born in the UK (marine climate), Tropical and Boreal climate respectively. The temperatures with the lowest mortality in these groups ranged from 15.9 to 17.7 °C.

DISCUSSION

Our findings imply that people born in different climatic zones do not adapt fully to their new environment within their lifetime. This implies that populations may not adapt readily to climate change and will suffer increased effects from heat. In the presence of climate change, policy makers should be aware of a delayed process of adaptation.

Temperature-Related Mortality in Helsinki Compared to Its Surrounding Region Over Two Decades, with Special Emphasis on Intensive Heatwaves

Urbanization and ongoing climate change increase the exposure of the populations to heat stress, and the urban heat island (UHI) effect may magnify heat-related mortality, especially during heatwaves. We studied temperature-related mortality in the city of Helsinki—with urban and suburban land uses—and in the surrounding Helsinki-Uusimaa hospital district (HUS-H, excluding Helsinki)—with more rural types of land uses—in southern Finland for two decades, 2000–2018. Dependence of the risk of daily all-cause deaths (all-age and 75+ years) on daily mean temperature was modelled using the distributed lag nonlinear model (DLNM). The modelled relationships were applied in assessing deaths attributable to four intensive heatwaves during the study period. The results showed that the heat-related mortality risk was substantially higher in Helsinki than in HUS-H, and the mortality rates attributable to four intensive heatwaves (2003, 2010, 2014 and 2018) were about 2.5 times higher in Helsinki than in HUS-H. Among the elderly, heat-related risks were also higher in Helsinki, while cold-related risks were higher in the surrounding region. The temperature ranges recorded in the fairly coarse resolution gridded datasets were not distinctly different in the two considered regions. It is therefore probable that the modelling underestimated the actual exposure to the heat stress in Helsinki. We also studied the modifying, short-term impact of air quality on the modelled temperature-mortality association in Helsinki; this effect was found to be small. We discuss a need for higher resolution data and modelling the UHI effect, and regional differences in vulnerability to thermal stress.

Roles of urban heat anomaly and land-use/land-cover on the heat-related mortality in the national capital region of South Korea: A multi-districts time-series study

The urban heat anomaly has been suggested as a representative risk factor for human health in metropolitan areas, but few studies have measured a quantitative increase in risk due to the urban heat anomaly on heat-related mortality in the summer season or assessed the role of various types of land-use/land-cover (LULC), which may contribute to the urban heat anomaly. In this study, we evaluated the association between the urban heat anomaly and heat-related mortality risk in the summer and the potential roles of multiple types of LULC indicators. We used district-level time-series and cadastral data from 51 urban districts in the national capital region of South Korea. We applied a two-stage analysis. In the first stage, we estimated the district-specific heat-related mortality risk by using a distributed lag non-linear model. In the second stage, we used a meta-analysis to pool the estimates across all districts and calculate the association between the urban heat anomaly/LULC indicators and heat-related mortality risk. We found that the higher urban heat anomaly was related to lower vegetation and higher urban surface indicators, and the urban heat anomaly was positively associated with the heat-related mortality risk. The association between the urban heat anomaly and the heat-related mortality risk was more pronounced in the elderly (age ≥ 65 years) and female population than in the non-elderly and male population. We also found that the LULC indicators affected the heat-related mortality only through the urban heat anomaly. Our findings indicate that urban areas may be more vulnerable to heat-related mortality risk as determined by the urban heat anomaly. These results suggest a need for urban heat mitigation strategies such as increased vegetation or surface albedo to help reduce heat-related mortality risk.

Cumulative effect of indoor temperature on cardiovascular disease-related emergency department visits among older adults in Taiwan

Studies have demonstrated that exposure to extreme outdoor temperatures increases cardiovascular disease mortality and morbidity. However, people spend 80%-90% of their time indoors, and the cumulative effects of exposure to high or low temperature on the risk of cardiovascular diseases had not been considered. This study investigated the cumulative effects of high or low indoor temperature exposure on the risk of cardiovascular diseases. We estimated indoor temperatures by using a prediction model of indoor temperature from a previous study and further calculated the cumulative degree hours at different indoor temperature ranges. Samples of emergency department visits due to cardiovascular diseases were collected from the Longitudinal Health Insurance Database (LHID) from 2000 to 2014 in Taiwan. We used a distributed lag nonlinear model to analyze the data. Our data demonstrated a significant risk of emergency department visits due to cardiovascular diseases at 27, 28, 29, 30, and 31 °C when cooling cumulative degree hours exceeded 62, 43, 16, 1, and 1 during the hot season (May to October), respectively, and at 19, 20, 21, 22, and 23 °C when heating cumulative degree hours exceeded 1, 1, 1, 11, and 33 during the cold season (November to April), respectively. Cumulative degree hours were different according to gender and age groups. Policymakers should further consider the cumulative effects to prevent hot- or cold-related cardiovascular diseases for populations.

A multi-resolution air temperature model for France from MODIS and Landsat thermal data

Understanding and managing the health effects of ambient temperature (Ta) in a warming, urbanizing world requires spatially- and temporally-resolved Ta at high resolutions. This is challenging in a large area like France which includes highly variable topography, rural areas with few weather stations, and heterogeneous urban areas where Ta can vary at fine spatial scales. We have modeled daily Ta from 2000 to 2016 at a base resolution of 1 km2 across continental France and at a 200 × 200 m2 resolution over large urban areas. For each day we predict three Ta measures: minimum (Tmin), mean (Tmean), and maximum (Tmax). We start by using linear mixed models to calibrate daily Ta observations from weather stations with remotely sensed MODIS land surface temperature (LST) and other spatial predictors (e.g. NDVI, elevation) on a 1 km2 grid. We fill gaps where LST is missing (e.g. due to cloud cover) with additional mixed models that capture the relationship between predicted Ta at each location and observed Ta at nearby weather stations. The resulting 1 km Ta models perform very well, with ten-fold cross-validated R2 of 0.92, 0.97, and 0.95, mean absolute error (MAE) of 1.4 °C, 0.9 °C, and 1.4 °C, and root mean square error (RMSE) of 1.9 °C, 1.3 °C, and 1.8 °C (Tmin, Tmean, and Tmax, respectively) for the initial calibration stage. To increase the spatial resolution over large urban areas, we train random forest and extreme gradient boosting models to predict the residuals (R) of the 1 km Ta predictions on a 200 × 200 m2 grid. In this stage we replace MODIS LST and NDVI with composited top-of-atmosphere brightness temperature and NDVI from the Landsat 5, 7, and 8 satellites. We use a generalized additive model to ensemble the random forest and extreme gradient boosting predictions with weights that vary spatially and by the magnitude of the predicted residual. The 200 m models also perform well, with ten-fold cross-validated R2 of 0.79, 0.79, and 0.85, MAE of 0.4, 0.3, and 0.3, and RMSE of 0.6, 0.4, and 0.5 (Rmin, Rmean, and Rmax, respectively). Our model will reduce bias in epidemiological studies in France by improving Ta exposure assessment in both urban and rural areas, and our methodology demonstrates that MODIS and Landsat thermal data can be used to generate gap-free timeseries of daily minimum, maximum, and mean Ta at a 200 × 200 m2 spatial resolution.

Probability Risk of Heat- and Cold-Related Mortality to Temperature, Gender, and Age Using GAM Regression Analysis

We have examined the heat and cold-related mortality risk subject to cold and heat extremes by using a generalized additive model (GAM) regression technique to quantify the effect of the stimulus of mortality in the presence of covariate data for 2007–2014 in Nicosia, Cyprus. The use of the GAM technique with multiple linear regression allowed for the continuous covariates of temperature and diurnal temperature range (DTR) to be modeled as smooth functions and the lag period was considered to relate mortality to lagged values of temperature. Our findings indicate that the previous three days’ temperatures were strongly predictive of mortality. The mortality risk decreased as the minimum temperature (Tmin) increased from the coldest days to a certain threshold temperature about 20–21°C (different for each age group and gender), above which the mortality risk increased as Tmin increased. The investigated fixed factors analysis showed an insignificant association of gender-mortality, whereas the age-mortality association showed that the population over 80 was more vulnerable to temperature variations. It was recommended that the minimum mortality temperature is calculated using the minimum daily temperatures because it has a stronger correlation to the probability for risk of mortality. It is still undetermined as to what degree a change in existing climatic conditions will increase the environmental stress to humans as the population is acclimatized to different climates with different threshold temperatures and minimum mortality temperatures.

Impacts of climate change on the public health of the Mediterranean Basin population - Current situation, projections, preparedness and adaptation

The Mediterranean Basin is undergoing a warming trend with longer and warmer summers, an increase in the frequency and the severity of heat waves, changes in precipitation patterns and a reduction in rainfall amounts. In this unique populated region, which is characterized by significant gaps in the socio-economic levels particularly between the North (Europe) and South (Africa), parallel with population growth and migration, increased water demand and forest fires risk - the vulnerability of the Mediterranean population to human health risks increases significantly. Indeed, climatic changes impact the health of the Mediterranean population directly through extreme heat, drought or storms, or indirectly by changes in water availability, food provision and quality, air pollution and other stressors. The main health effects are related to extreme weather events (including extreme temperatures and floods), changes in the distribution of climate-sensitive diseases and changes in environmental and social conditions. The poorer countries, particularly in North Africa and the Levant, are at highest risk. Climate change affects the vulnerable sectors of the region, including an increasingly older population, with a larger percentage of those with chronic diseases, as well as poor people, which are therefore more susceptible to the effects of extreme temperatures. For those populations, a better surveillance and control systems are especially needed. In view of the climatic projections and the vulnerability of Mediterranean countries, climate change mitigation and adaptation become ever more imperative. It is important that prevention Health Action Plans will be implemented, particularly in those countries that currently have no prevention plans. Most adaptation measures are "win-win situation" from a health perspective, including reducing air pollution or providing shading solutions. Additionally, Mediterranean countries need to enhance cross-border collaboration, as adaptation to many of the health risks requires collaboration across borders and also across the different parts of the basin.

Spatial Variability in the Effect of High Ambient Temperature on Mortality: An Analysis at Municipality Level within the Greater Athens Area

Spatial variability in temperature exists within metropolitan areas but very few studies have investigated intra-urban differentiation in the temperature-mortality effects. We investigated whether local characteristics of 42 Municipalities within the Greater Athens Area lead to modified temperature effects on mortality and if effect modifiers can be identified. Generalized Estimating Equations models were used to assess the effect of high ambient temperature on the total and cause-specific daily number of deaths and meta-regression to investigate effect modification. We found significant effects of daily temperature increases on all-cause, cardiovascular, and respiratory mortality (e.g., for all ages 4.16% (95% CI: 3.73,4.60%) per 1 °C increase in daily temperature (lags 0–3). Heterogeneity in the effect estimates between Municipalities was observed in several outcomes and environmental and socio-economic effect modifying variables were identified, such as % area coverage of buildings, length of roads/km², population density, % unemployed, % born outside the EU countries and mean daily temperature. To further examine the role of temperature, we alternatively used modelled temperature per Municipality and calculated the effects. We found that heterogeneity was reduced but not eliminated. It appears that there are socioeconomic status and environmental determinants of the magnitude of heat-related effects on mortality, which are detected with some consistency and should be further investigated.

Will there be cold-related mortality in Spain over the 2021-2050 and 2051-2100 time horizons despite the increase in temperatures as a consequence of climate change?

INTRODUCTION

Global warming is resulting in an increase in temperatures which is set to become more marked by the end of the century and depends on the accelerating pace of greenhouse gas emissions into the atmosphere. Yet even in this scenario, so-called "cold waves" will continue to be generated and have an impact on health.

OBJECTIVES

This study sought to analyse the impact of cold waves on daily mortality at a provincial level in Spain over the 2021-2050 and 2051-2100 time horizons under RCP4.5 and RCP 8.5 emission scenarios, on the basis of two hypotheses: (1) that the cold-wave definition temperature (T _threshold) would not vary over time; and, (2) that there would be a variation in T _threshold.

MATERIAL AND METHODS

The results of a retrospective study undertaken for Spain as a whole across the period 2000-2009 enabled us to ascertain the cold-wave definition temperature at a provincial level and its impact on health, measured by reference to population attributable risk (PAR). The minimum daily temperatures projected for each provincial capital considering the above time horizons and emission scenarios were provided by the State Meteorological Agency. On the basis of the T _threshold definition values and minimum daily temperatures projected for each province, we calculated the expected impact of low temperatures on mortality under the above two hypotheses. Keeping the PAR values constant, it was assumed that the mortality rate would vary in accordance with the available data.

RESULTS

If T _threshold remained constant over the above time horizons under both emission scenarios, there would be no cold-related mortality. If T _threshold were assumed to vary over time, however, then cold-related mortality would not disappear: it would instead remain practically constant over time and give rise to an estimated overall figure of around 250 deaths per year, equivalent to close on a quarter of Spain's current annual cold-related mortality and entailing a cost of approximately €1000 million per year.

CONCLUSION

Given that cold waves are not going to disappear and that their impact on mortality is far from negligible and is likely to remain so, public health prevention measures must be implemented to minimise these effects as far as possible.

Association of Extreme Heat Events With Hospital Admission or Mortality Among Patients With End-Stage Renal Disease

Importance

Extreme heat events (EHEs) are increasing in frequency, duration, and intensity, and this trend is projected to continue as part of ongoing climate change. There is a paucity of data regarding how EHEs may affect highly vulnerable populations, such as patients with end-stage renal disease (ESRD). Such data are needed to inform ESRD patient management guidelines in a changing climate.

Objectives

To investigate the association between EHEs and the risk of hospital admission or mortality among patients with ESRD and further characterize how this risk may vary among races/ethnicities or patients with preexisting comorbidities.

Design, Setting, and Participants

This study used hospital admission and mortality records of patients with ESRD who underwent hemodialysis treatment at Fresenius Kidney Care clinics in Boston, Massachusetts; Philadelphia, Pennsylvania; or New York, New York, from January 1, 2001, to December 31, 2012. Data were analyzed using a time-stratified case-crossover design with conditional Poisson regression to investigate associations between EHEs and risk of hospital admission or mortality among patients with ESRD. Data were analyzed from July 1, 2017, to March 31, 2019.

Exposures

Calendar day- and location-specific 95th-percentile maximum temperature thresholds were calculated using daily meteorological data from 1960 to 1989. These thresholds were used to identify EHEs in each of the 3 cities during the study.

Main Outcomes and Measures

Daily all-cause hospital admission and all-cause mortality among patients with ESRD.

Results

The study included 7445 patients with ESRD (mean [SD] age, 61.1 [14.1] years; 4283 [57.5%] men), among whom 2953 deaths (39.7%) and 44 941 hospital admissions (mean [SD], 6.0 [7.5] per patient) were recorded. Extreme heat events were associated with increased risk of same-day hospital admission (rate ratio [RR], 1.27; 95% CI, 1.13-1.43) and same-day mortality (RR, 1.31; 95% CI, 1.01-1.70) among patients with ESRD. There was some heterogeneity in risk, with patients in Boston showing statistically significant increased risk for hospital admission (RR, 1.15; 95% CI, 1.00-1.31) and mortality (RR, 1.45; 95% CI, 1.04-2.02) associated with cumulative exposure to EHEs, while such risk was absent among patients with ESRD in Philadelphia. While increases in risks were similar among non-Hispanic black and non-Hispanic white patients, findings among Hispanic and Asian patients were less clear. After stratifying by preexisting comorbidities, cumulative lag exposure to EHEs was associated with increased risk of mortality among patients with ESRD living with congestive heart failure (RR, 1.55; 95% CI, 1.27-1.89), chronic obstructive pulmonary disease (RR, 1.60; 95% CI, 1.24-2.06), or diabetes (RR, 1.83; 95% CI, 1.51-2.21).

Conclusions and Relevance

In this study, extreme heat events were associated with increased risk of hospital admission or mortality among patients with ESRD, and the association was potentially affected by geographic region and race/ethnicity. Future studies with larger populations and broader geographic coverage are needed to better characterize this variability in risk and inform ESRD management guidelines and differential risk variables, given the projected increases in the frequency, duration, and intensity of EHEs.

The Challenge of Urban Heat Exposure under Climate Change: An Analysis of Cities in the Sustainable Healthy Urban Environments (SHUE) Database

The so far largely unabated emissions of greenhouse gases (GHGs) are expected to increase global temperatures substantially over this century. We quantify the patterns of increases for 246 globally-representative cities in the Sustainable Healthy Urban Environments (SHUE) database. We used an ensemble of 18 global climate models (GCMs) run under a low (RCP2.6) and high (RCP8.5) emissions scenario to estimate the increase in monthly mean temperatures by 2050 and 2100 based on 30-year averages. Model simulations were from the Coupled Model Inter-comparison Project Phase 5 (CMIP5). Annual mean temperature increases were 0.93 degrees Celsius by 2050 and 1.10 degrees Celsius by 2100 under RCP2.6, and 1.27 and 4.15 degrees Celsius under RCP8.5, but with substantial city-to-city variation. By 2100, under RCP2.6 no city exceeds an increase in T_mean > 2 degrees Celsius (relative to a 2017 baseline), while all do under RCP8.5, some with increases in T_mean close to, or even greater than, 7 degrees Celsius. The increases were greatest in cities of mid to high latitude, in humid temperate and dry climate regions, and with large seasonal variation in temperature. Cities are likely to experience large increases in hottest month mean temperatures under high GHG emissions trajectories, which will often present substantial challenges to adaptation and health protection.

Potential benefits of cool roofs in reducing heat-related mortality during heatwaves in a European city

Hot weather can exacerbate health conditions such as cardiovascular and respiratory diseases, and lead to heat stroke and death. In built up areas, temperatures are commonly observed to be higher than those in surrounding rural areas, due to the Urban Heat Island (UHI) effect. Climate change and increasing urbanisation mean that future populations are likely to be at increased risk of overheating in cities, although building and city scale interventions have the potential to reduce this risk. We use a regional weather model to assess the potential effect of one type of urban intervention - reflective 'cool' roofs - to reduce local ambient temperatures, and the subsequent impact on heat-related mortality in the West Midlands, UK, with analysis undertaken for the summer of 2006, as well as two shorter heatwave periods in 2006 and 2003. We show that over a summer season, the population-weighted UHI intensity (the difference between simulated urban and rural temperature) was 1.1 °C on average, but 1.8 °C when including only night times, and reached a maximum of 9 °C in the West Midlands. Our results suggest that the UHI contributes up to 40% of heat related mortality over the summer period and that cool roofs implemented across the whole city could potentially offset 18% of seasonal heat-related mortality associated with the UHI (corresponding to 7% of total heat-related mortality). For heatwave periods, our modelling suggests that cool roofs could reduce city centre daytime 2 m air temperature by 0.5 °C on average, and up to a maximum of ~3 °C. Cool roofs reduced average UHI intensity by ~23%, and reduced heat related mortality associated with the UHI by ~25% during a heatwave. Cool roofs were most effective at reducing peak temperatures during the daytime, and therefore have the potential to limit dangerous extreme temperatures during heatwaves. Temperature reductions were dependent on the category of buildings where cool roofs were applied; targeting only commercial and industrial type buildings contributed more than half of the reduction for heatwave periods. Our modelling suggested that modifying half of all industrial/commercial urban buildings could have the same impact as modifying all high-intensity residential buildings in the West Midlands.

Differences in the impact of heat waves according to urban and peri-urban factors in Madrid

Aside from climatic factors, the impact of heat waves on mortality depends on the demographic and socio-economic structure of the population as well as variables relating to local housing. Hence, this study's main aim was to ascertain whether there might be a differential impact of heat waves on daily mortality by area of residence. The study is a time-series analysis (2000-2009) of daily mortality and minimum and maximum daily temperatures (°C) in five geographical areas of the Madrid region. The impact of such waves on heat-related mortality due to natural causes (ICD-10: A00- R99), circulatory causes (ICD-10: I00-I99) and respiratory causes (ICD-10: J00-J99) was obtained by calculating the relative risk (RR) and attributable risk (AR), using GLM models with the Poisson link and controlling for trend, seasonalities and the autoregressive nature of the series. Furthermore, we also evaluated other external variables, such as the percentage of the population aged over 65 years and the percentage of old housing. No heat-related mortality threshold temperature with statistical significance was detected in the northern and eastern areas. While the threshold temperatures in the central and southern areas were very similar and close to the 90th percentile, the threshold in the western area corresponded to the 97th percentile. Attributable mortality proved to be highest in the central area with 85 heat wave-related deaths per annum. External factors found to influence the impact of heat on mortality in Madrid were the size of the population aged over 65 years and the age of residential housing. Demographic structure and the percentage of old housing play a key role in modulating the impact of heat waves. This study concludes that the areas in which heat acts earliest are those having a higher degree of population ageing.

Quantification and evaluation of intra-urban heat-stress variability in Seoul, Korea

This study quantifies heat-stress hazard (air temperature), vulnerability (heat vulnerability index and age score), and risk (heat-related mortality) on the district scale in Seoul, Korea, for a comprehensive heat-stress impact assessment. Moreover, the heat-stress impact assessment is evaluated by checking the spatial consistency between heat-stress hazard, vulnerability, and risk, which was rarely done before. We applied numerical and geo-empirical models to simulate the spatial pattern of heat-stress hazard. For heat-stress vulnerability, we used demographic and socioeconomic factors. Heat-related mortality was estimated based on an event-based heat-stress risk analysis. Results are that heat-stress hazard, vulnerability, and risk are spatially variable in Seoul. The highest heat-stress hazard was detected in the districts Mapo, Yeongdeungpo, and Yangcheon, the highest vulnerability in Jongno and the highest risk in Jongno and Yangcheon. The different components (heat-stress hazard, vulnerability, and risk) and variables (heat vulnerability index and percentage of seniors) showed different spatial patterns. Knowledge about the causes of higher heat-stress risk, either the hazard or vulnerability, is helpful to design tailored adaptation measures that focus on the reduction of thermal loads or on the preparation of the vulnerable population. The evaluation showed that heat-stress vulnerability and hazard explain the spatial pattern of risk only partly. This highlights the need to evaluate heat-stress impact assessment systems to produce reliable urban heat-stress maps.

The impact of home energy efficiency interventions and winter fuel payments on winter- and cold-related mortality and morbidity in England: a natural equipment mixed-methods study

Background

England, and the UK more generally, has a large burden of winter- and cold-related mortality/morbidity in comparison with nearby countries in continental Europe. Improving the energy efficiency of the housing stock may help to reduce this, as well as being important for climate change and energy security objectives.

Objectives

To evaluate the impact of home energy efficiency (HEE) interventions on winter- and cold-related mortality/morbidity, including assessing the impact of winter fuel payments (WFPs) and fuel costs.

Design

A mixed-methods study – an epidemiological time-series analysis, an analysis of data on HEE interventions, the development and application of modelling methods including a multicriteria decision analysis and an in-depth interview study of householders.

Setting

England, UK.

Participants

The population of England. In-depth interviews were conducted with 12 households (2–4 participants each) and 41 individuals in three geographical regions.

Interventions

HEE interventions.

Main outcome measures

Mortality, morbidity and intervention-related changes to the home indoor environment.

Data sources

The Homes Energy Efficiency Database, mortality and hospital admissions data and weather (temperature) data.

Results

There has been a progressive decline in cold-related deaths since the mid-1970s. Since the introduction of WFPs, the gradient of association between winter cold and mortality [2.00%, 95% confidence interval (CI) 1.74% to 2.28%] per degree Celsius fall in temperature is somewhat weaker (i.e. that the population is less vulnerable to cold) than in earlier years (2.37%, 95% CI 0.22% to 2.53%). There is also evidence that years with above-average fuel costs were associated with higher vulnerability to outdoor cold. HEE measures installed in England in 2002–10 have had a relatively modest impact in improving the indoor environment. The gains in winter temperatures (around +0.09 °C on a day with maximum outdoor temperature of 5 °C) are associated with an estimated annual reduction of ≈280 cold-related deaths in England (an eventual maximum annual impact of 4000 life-years gained), but these impacts may be appreciably smaller than those of changes in indoor air quality. Modelling studies indicate the potential importance of the medium- and longer-term impacts that HEE measures have on health, which are not observable in short-term studies. They also suggest that HEE improvements of similar annualised cost to current WFPs would achieve greater improvements in health while reducing (rather than increasing) carbon dioxide emissions. In-depth interviews suggest four distinct householder framings of HEE measures (as home improvement, home maintenance, subsidised public goods and contributions to sustainability), which do not dovetail with current ‘consumerist’ national policy and may have implications for the uptake of HEE measures.

Limitations

The quantification of intervention impacts in this national study is reliant on various indirect/model-based assessments.

Conclusions

Larger-scale changes are required to the housing stock in England if the full potential benefits for improving health and for reaching increasingly important climate change mitigation targets are to be realised.

Future work

Studies based on data linkage at individual dwelling level to examine health impacts. There is a need for empirical assessment of HEE interventions on indoor air quality.

Funding

This project was funded by the National Institute for Health Research (NIHR) Public Health Research programme and will be published in full in Public Health Research; Vol. 6, No. 11. See the NIHR Journals Library website for further project information.

The Urban Heat Island: Implications for Health in a Changing Environment

PURPOSE OF REVIEW

The Urban Heat Island (UHI) is a well-studied phenomenon, whereby urban areas are generally warmer than surrounding suburban and rural areas. The most direct effect on health from the UHI is due to heat risk, which is exacerbated in urban areas, particularly during heat waves. However, there may be health benefits from warming during colder months. This review highlights recent attempts to quantitatively estimate the health impacts of the UHI and estimations of the health benefits of UHI mitigation measures.

RECENT FINDINGS

Climate change, increasing urbanisation and an ageing population in much of the world, is likely to increase the risks to health from the UHI, particularly from heat exposure. Studies have shown increased health risks in urban populations compared with rural or suburban populations in hot weather and a disproportionate impact on more vulnerable social groups. Estimations of the impacts of various mitigation techniques suggest that a range of measures could reduce health impacts from heat and bring other benefits to health and wellbeing. The impact of the UHI on heat-related health is significant, although often overlooked, particularly when considering future impacts associated with climate change. Multiple factors should be considered when designing mitigation measures in urban environments in order to maximise health benefits and avoid unintended negative effects.

Modification of the association between high ambient temperature and health by urban microclimate indicators: A systematic review and meta-analysis

BACKGROUND

Landscape characteristics, including vegetation and impervious surfaces, influence urban microclimates and may lead to within-city differences in the adverse health effects of high ambient temperatures.

OBJECTIVE

Our objective was to quantitatively summarize the epidemiologic literature that assessed microclimate indicators as effect measure modifiers (EMM) of the association between ambient temperature and mortality or morbidity.

METHODS

We systematically identified papers and abstracted relative risk estimates for hot and cool microclimate indicator strata. We calculated the ratio of the relative risks (RRR) and 95% confidence intervals (95% CI) to assess differences in health effects across strata, and pooled the RRR estimates using random effects meta-analyses.

RESULTS

Eleven papers were retained. In the pooled analyses, people living in hotter areas within cities (based on land surface temperature or modeled estimates of air temperature) had 6% higher risk of mortality/morbidity compared to those in cooler areas (95% CI: 1.03-1.09). Those living in less vegetated areas had 5% higher risk compared to those living in more vegetated areas (95% CI: 1.00-1.11).

DISCUSSION

There is epidemiologic evidence that those living in hotter, and less vegetated areas of cities have higher risk of morbidity or mortality from higher ambient temperature. Further research with improved assessment of landscape characteristics and investigation of the joint effects of physiologic adaptation and landscape will advance the current understanding.

CONCLUSION

This review provides quantitative evidence that intra-urban differences in landscape characteristics and micro-urban heat islands contribute to within-city variability in the health effects of high ambient temperatures.

Projected trends in high-mortality heatwaves under different scenarios of climate, population, and adaptation in 82 US communities

Some rare heatwaves have extreme daily mortality impacts; moderate heatwaves have lower daily impacts but occur much more frequently at present and so account for large aggregated impacts. We applied health-based models to project trends in high-mortality heatwaves, including proportion of all heatwaves expected to be high-mortality, using the definition that a high-mortality heatwave increases mortality risk by ≥20 %. We projected these trends in 82 US communities in 2061-2080 under two scenarios of climate change (RCP4.5, RCP8.5), two scenarios of population change (SSP3, SSP5), and three scenarios of community adaptation to heat (none, lagged, on-pace) for large- and medium-ensemble versions of the National Center for Atmospheric Research's Community Earth System Model. More high-mortality heatwaves were expected compared to present under all scenarios except on-pace adaptation, and population exposure was expected to increase under all scenarios. At least seven more high-mortality heatwaves were expected in a twenty-year period in the 82 study communities under RCP8.5 than RCP4.5 when assuming no adaptation. However, high-mortality heatwaves were expected to remain <1 % of all heatwaves and heatwave exposure under all scenarios. Projections were most strongly influenced by the adaptation scenario- going from a scenario of on-pace to lagged adaptation or from lagged to no adaptation more than doubled the projected number of and exposure to high-mortality heatwaves. Based on our results, fewer high-mortality heatwaves are expected when following RCP4.5 versus RCP8.5 and under higher levels of adaptation, but high-mortality heatwaves are expected to remain a very small proportion of total heatwave exposure.

Green Space and Deaths Attributable to the Urban Heat Island Effect in Ho Chi Minh City

OBJECTIVES

To quantify heat-related deaths in Ho Chi Minh City, Vietnam, caused by the urban heat island (UHI) and explore factors that may alleviate the impact of UHIs.

METHODS

We estimated district-specific meteorological conditions from 2010 to 2013 using the dynamic downscaling model and calculated the attributable fraction and number of mortalities resulting from the total, extreme, and mild heat in each district. The difference in attributable fraction of total heat between the central and outer districts was classified as the attributable fraction resulting from the UHI. The association among attributable fraction, attributable number with a green space, population density, and budget revenue of each district was then explored.

RESULTS

The temperature-mortality relationship between the central and outer areas was almost identical. The attributable fraction resulting from the UHI was 0.42%, which was contributed by the difference in temperature distribution between the 2 areas. Every 1-square-kilometer increase in green space per 1000 people can prevent 7.4 deaths caused by heat.

CONCLUSIONS

Green space can alleviate the impacts of UHIs, although future studies conducting a heath economic evaluation of tree planting are warranted.

Socioeconomic and urban-rural differentials in exposure to air pollution and mortality burden in England

BACKGROUND

Socioeconomically disadvantaged populations often have higher exposures to particulate air pollution, which can be expected to contribute to differentials in life expectancy. We examined socioeconomic differentials in exposure and air pollution-related mortality relating to larger scale (5 km resolution) variations in background concentrations of selected pollutants across England.

METHODS

Ozone and particulate matter (sub-divided into PM₁₀, PM_2.5, PM_2.5-10, primary, nitrate and sulphate PM_2.5) were simulated at 5 km horizontal resolution using an atmospheric chemistry transport model (EMEP4UK). Annual mean concentrations of these pollutants were assigned to all 1,202,578 residential postcodes in England, which were classified by urban-rural status and socioeconomic deprivation based on the income and employment domains of the 2010 English Index of Multiple Deprivation for the Lower-level Super Output Area of residence. We used life table methods to estimate PM_2.5-attributable life years (LYs) lost in both relative and absolute terms.

RESULTS

Concentrations of the most particulate fractions, but not of nitrate PM_2.5 or ozone, were modestly higher in areas of greater socioeconomic deprivation. Relationships between pollution level and socioeconomic deprivation were non-linear and varied by urban-rural status. The pattern of PM_2.5 concentrations made only a small contribution to the steep socioeconomic gradient in LYs lost due to PM_2.5 per 10³ population, which primarily was driven by the steep socioeconomic gradient in underlying mortality rates. In rural areas, the absolute burden of air pollution-related LYs lost was lowest in the most deprived deciles.

CONCLUSIONS

Air pollution shows modest socioeconomic patterning at 5 km resolution in England, but absolute attributable mortality burdens are strongly related to area-level deprivation because of underlying mortality rates. Measures that cause a general reduction in background concentrations of air pollution may modestly help narrow socioeconomic differences in health.

Small-area spatiotemporal analysis of heatwave impacts on elderly mortality in Paris: A cluster analysis approach

BACKGROUND

Heat-waves have a substantial public health burden. Understanding spatial heterogeneity at a fine spatial scale in relation to heat and related mortality is central to target interventions towards vulnerable communities.

OBJECTIVES

To determine the spatial variability of heat-wave-related mortality risk among elderly in Paris, France at the census block level. We also aimed to assess area-level social and environmental determinants of high mortality risk within Paris.

METHODS

We used daily mortality data from 2004 to 2009 among people aged >65 at the French census block level within Paris. We used two heat wave days' definitions that were compared to non-heat wave days. A Bernoulli cluster analysis method was applied to identify high risk clusters of mortality during heat waves. We performed random effects meta-regression analyses to investigate factors associated with the magnitude of the mortality risk.

RESULTS

The spatial approach revealed a spatial aggregation of death cases during heat wave days. We found that small scale chronic PM₁₀ exposure was associated with a 0.02 (95% CI: 0.001; 0.045) increase of the risk of dying during a heat wave episode. We also found a positive association with the percentage of foreigners and the percentage of labor force, while the proportion of elderly people living in the neighborhood was negatively associated. We also found that green space density had a protective effect and inversely that the density of constructed feature increased the risk of dying during a heat wave episode.

CONCLUSION

We showed that a spatial variation in terms of heat-related vulnerability exists within Paris and that it can be explained by some contextual factors. This study can be useful for designing interventions targeting more vulnerable areas and reduce the burden of heat waves.