Projection of mortality attributed to heat and cold; the impact of climate change in a dry region of Iran, Kerman

Integrating Shared Socioeconomic Pathway-informed adaptation into temperature-related mortality projections under climate change

The extent to which populations will successfully adapt to continued warming temperatures will be a crucial factor in determining future health burdens. Previous health impact assessments of future temperature-related mortality burdens mostly disregard adaptation or make simplistic assumptions. We apply a novel evidence-based approach to model adaptation that takes into account the fact that adaptation potential is likely to vary at different temperatures. Temporal changes in age-specific mortality risk associated with low and high temperatures were characterised for Scotland between 1974 and 2018 using temperature-specific RR ratios to reflect past changes in adaptive capacity. Three scenarios of future adaption were constructed consistent with the SSPs. These adaptation projections were combined with climate and population projections to estimate the mortality burdens attributable to high (above the 90th percentile of the historical temperature distribution) and low (below the 10th percentile) temperatures up to 2080 under five RCP-SSP scenarios. A decomposition analysis was conducted to attribute the change in the mortality burden into adaptation, climate and population. In 1980-2000, the heat burden (21 deaths/year) was smaller than the colder burden (312 deaths/year). In the 2060-2080 period, the heat burden was projected to be the highest under RCP8.5-SSP5 (1285 deaths/year), and the cold burden was the highest under RCP4.5-SSP4 (320 deaths/year). The net burden was lowest under RCP2.6-SSP1 and highest under RCP8.5-SSP5. Improvements in adaptation was the largest factor reducing the cold burden under RCP2.6-SSP1 whilst temperature increase was the biggest factor contributing to the high heat burdens under RCP8.5-SSP5. Ambient heat will become a more important health determinant than cold in Scotland under all climate change and socio-economic scenarios. Adaptive capacity will not fully counter projected increases in heat deaths, underscoring the need for more ambitious climate mitigation measures for Scotland and elsewhere.

Projection of extreme heat- and cold-related mortality in Sweden based on the spatial synoptic classification

BACKGROUND

Climate change is projected to result in increased heat events and decreased cold events. This will substantially impact human health, particularly when compounded with demographic change. This study employed the Spatial Synoptic Classification (SSC) to categorize daily weather into one of seven types. Here we estimated future mortality due to extremely hot and cold weather types under different climate change scenarios for one southern (Stockholm) and one northern (Jämtland) Swedish region.

METHODS

Time-series Poisson regression with distributed lags was used to assess the relationship between extremely hot and cold weather events and daily deaths in the population above 65 years, with cumulative effects (6 days in summer, 28 days in winter), 1991 to 2014. A global climate model (MPI-M-MPI-ESM-LR) and two climate change scenarios (RCP 4.5 and 8.5) were used to project the occurrence of hot and cold days from 2031 to 2070. Place-specific projected mortality was calculated to derive attributable numbers and attributable fractions (AF) of heat- and cold-related deaths.

RESULTS

In Stockholm, for the RCP 4.5 scenario, the mean number of annual deaths attributed to heat increased from 48.7 (CI 32.2-64.2; AF = 0.68%) in 2031-2040 to 90.2 (56.7-120.5; AF = 0.97%) in 2061-2070, respectively. For RCP 8.5, heat-related deaths increased more drastically from 52.1 (33.6-69.7; AF = 0.72%) to 126.4 (68.7-175.8; AF = 1.36%) between the first and the last decade. Cold-related deaths slightly increased over the projected period in both scenarios. In Jämtland, projections showed a small decrease in cold-related deaths but no change in heat-related mortality.

CONCLUSIONS

In rural northern region of Sweden, a decrease of cold-related deaths represents the dominant trend. In urban southern locations, on the other hand, an increase of heat-related mortality is to be expected. With an increasing elderly population, heat-related mortality will outweigh cold-related mortality at least under the RCP 8.5 scenario, requiring societal adaptation measures.

Heat and cold-related morbidity risk in north-east of Iran: a time-stratified case crossover design

This study aimed to estimate morbidity risk/number attributed to air extreme temperatures using time-stratified case crossover study and distributed lag non-linear model in a region of Iran during 2015-2019. A time-stratified case crossover design based on aggregated exposure data was used in this study. In order to have no overlap bias in the estimations, a fixed and disjointed window by using 1-month strata was used in the design. A conditional Poisson regression model allowing for over dispersion (Quasi-Poisson) was applied into Distributed Lag Non-linear Model (DLNM). Different approaches were applied to estimate Optimum Temperature (OT). In the model, the interaction effect between temperature and humidity was assessed to see if the impact of heat or cold on Hospital Admissions (HAs) are different between different levels of humidity. The cumulative effect of heat during 21 days was not significant and it was the cold that had significant cumulative adverse effect on all groups. While the number of HAs attributed to any ranges of heat, including medium, high, extreme, and even all values were negligible, but a large number was attributable to cold values; about 10000 HAs were attributable to all values of cold temperature, of which about 9000 were attributed to medium range and about 1000 and less than 500 were attributed to high and extreme values of cold, respectively. This study highlights the need for interventions in cold seasons by policymakers. The results inform researchers as well as policy makers to address both men and women and elderly when any plan or preventive program is developed in the area under study.

Increased high-temperature extremes and associated population exposure in Africa by the mid-21st century

Previous studies warned that heat extremes are likely to intensify and frequently occur in the future due to climate change. Apart from changing climate, the population's size and distribution contribute to the total changes in the population exposed to heat extremes. The present study uses the ensemble mean of global climate models from the Coupled Model Inter-comparison Project Phase six (CMIP6) and population projection to assess the future changes in high-temperature extremes and exposure to the population by the middle of this century (2041-2060) in Africa compared to the recent climate taken from 1991 to 2010. Two Shared Socioeconomic Pathways (SSPs), namely SSP2-4.5 and SSP5-8.5, are used. Changes in population exposure and its contributors are quantified at continental and for various sub-regions. The intensity of high-temperature extremes is anticipated to escalate between 0.25 to 1.8 °C and 0.6 to 4 °C under SSP2-4.5 and SSP5-8.5, respectively, with Sahara and West Southern Africa projected to warm faster than the rest of the regions. On average, warm days' frequency is also expected to upsurge under SSP2-4.5 (26-59%) and SSP5-8.5 (30-69%) relative to the recent climate. By the mid-21st century, continental population exposure is expected to upsurge by ~25% (28%) of the reference period under SSP2-4.5|SSP2 (SSP5-8.5|SSP5). The highest increase in exposure is expected in most parts of West Africa (WAF), followed by East Africa. The projected changes in continental exposure (~353.6 million person-days under SSP2-4.5|SSP2 and ~401.4 million person-days under SSP5-8.5|SSP5) are mainly due to the interaction effect. However, the climate's influence is more than the population, especially for WAF, South-East Africa and East Southern Africa. The study findings are vital for climate change adaptation.

Ambient high temperature exposure and global disease burden during 1990-2019: An analysis of the Global Burden of Disease Study 2019

BACKGROUND

A warming climate throughout the 21st century makes ambient high temperature exposure a major threat to population health worldwide. Mitigating the health impact of high temperature requires a timely, comprehensive and reliable assessment of disease burden globally, regionally and temporally.

AIM

Based on Global Burden of Disease (GBD) Study 2019, this study aimed to evaluate the disease burden attributable to high temperature from various epidemiology perspectives.

METHODS

A three-stage analysis was undertaken to investigate the number and age-standardized rates of death and disability-adjusted life years (DALY) attributable to high temperature from GBD Study 2019. First, we reported the high temperature-related disease burden for the whole world and for different groups by gender, age, region, country and disease. Second, we examined the temporal trend of the disease burden attributable to high temperature from 1990 to 2019. Finally, we explored if and how the high temperature-related disease burden was modified by a number of country-level indicators.

RESULTS

Globally, high temperature accounted for 0.54% of death and 0.46% of DALY in 2019, equating to the age-standardized rates of death and DALY (per 100,000 population) of 3.99 (95% uncertainty interval (UI): 2.88, 5.93) and 156.81 (95% UI: 107.98, 261.98), respectively. In 2019, the high temperature-related DALY and death rates were the highest for lower respiratory infections, although they showed a downward trend. In contrast, during 1990-2019, high temperature-related non-communicable diseases burden exhibited an upward trend. Meanwhile, the disease burden attributable to high temperature varied spatially, with the heaviest burden in regions with low sociodemographic index (SDI) and the lightest burden in regions with high SDI. In addition, high temperature-related disease burden appeared to be higher in a country with a higher population density and PM_2.5 concentration background but lower in a country with a higher density of greenness.

CONCLUSION

This study for the first time provided a comprehensive understanding of the global disease burden attributable to high temperature, underscoring the policy priority to protect human health worldwide in the context of global warming with particular attention to vulnerable countries or regions as well as susceptible population and diseases.

Emergency hospital admissions for cardiovascular diseases attributed to air pollution in Tehran during 2016-2019

The burden of five main air pollutants, including CO, O3, NO2, SO2, and PM2.5, on the emergency department visits (EDVs) during January 2016-December 2019 due to all cardiovascular diseases was assessed in Tehran by using a time-series model. The pollutants data were collected from Iran Department of Environment including 10 air pollution monitoring stations for the period of our study. Cumulative relative risk and attributable number/fraction were calculated for each pollutants by a Quasi-Poisson time-series regression and distributed lag non-linear model (DLNM). The maximum lag was set to 14 days because harvesting effect is more likely happened during few days. We used percentile 25 as reference value in order to calculate cumulative relative risk and attributable fraction. About 69,000 patients with cardiovascular symptoms have been admitted into the hospital during 4 years. The cumulative relative risk during the 14 days was 1.13 (1.01, 1.26), 1.15 (1.02, 1.29), and 1.08 (1.01, 1.18) for CO, NO2, and PM2.5, respectively. The numbers attributed to all values of CO were more than others; about 3800 EDVs were significantly attributed to CO, of which over 3000 were significantly attributed to high values of the pollutant. Low values of all pollutants were, not surprisingly, responsible for low number of EDVs. PM2.5, CO, and NO2 were responsible to considerable attributable number of EDVs. Our study emphasizes the need for local authorities to establish a program to reduce the air pollution in Tehran.

Acute effects of ambient air pollution on clinic visits of college students for upper respiratory tract infection in Wuhan, China

Ambient air pollutants have been linked to adverse health outcomes, but evidence is still relatively rare in college students. Upper respiratory tract infection (URTI) is a common disease of respiratory system among college students. In this study, we assess the acute effect of air pollution on clinic visits of college students for URTI in Wuhan, China. Data on clinic visits due to URTI were collected from Wuhan University Hospital, meteorological factors (including daily temperature and relative humidity) provided by Wuhan Meteorological Bureau, and air pollutants by Wuhan Environmental Protection Bureau. In the present study, generalized additive model with a quasi-Poisson distribution link function was used to examine the association between ambient air pollutants (fine particulate matter (PM2.5), particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3)) and the daily number of clinic visits of college students for URTI at Wuhan University Hospital in Wuhan, China. In the meantime, the model was adjusted for the confounding effects of long-term trends, seasonality, day of the week, public holidays, vacation, and meteorological factors. The best degrees of free in model were selected based on AIC (Akaike Information Criteria). The effect modification by gender was also examined. A total of 44,499 cases with principal diagnosis of URTI were included from January 1, 2016, to December 31, 2018. In single-pollutant models, the largest increment of URTI visits were found at lag 0 day in single-day lags, and the effect values in cumulative lags were greater than those in single-day lags. PM2.5 (0.74% (95%CI: 0.05, 1.44)) at lag 0 day, PM10 (0.61% (95%CI: 0.12, 1.11)) and O3 (1.01% (95%CI: 0.24, 1.79)) at lag 0-1 days, and SO2 (9.18% (95%CI: 3.27, 15.42)) and NO2 (3.40% (95% CI:1.64, 5.19)) at lag 0-3 days were observed to be strongly and significantly associated with clinic visits for URTI. PM10 and NO2 were almost still significantly associated with URTI after controlling for the other pollutants in our two-pollutant models, where the effect value of SO2 after inclusion of O3 appeared to be the largest and the effects of NO2 were also obvious compared with the other pollutants. Subgroups analysis demonstrated that males were more vulnerable to PM10 and O3, while females seemed more vulnerable to exposure to SO2 and NO2. This study implied that short-term exposure to ambient air pollution was associated with increased risk of URTI among college students at Wuhan University Hospital in Wuhan, China. And gaseous pollutants had more negative health impact than solid pollutants. SO2 and NO2 were the major air pollutants affecting the daily number of clinic visits on URTI, to which females seemed more vulnerable than males.