Long-term changes in the heat-mortality relationship according to heterogeneous regional climate: a time-series study in South Korea

The temporal variation in the effects of extreme temperature on respiratory mortality: Evidence from 136 cities in China, 2006-2019

BACKGROUND

In the context of climate change and urbanization, the temporal variation of the adverse health effect of extreme temperature has attracted increasing attention.

METHODS

The meteorological data and the daily death records of mortality from respiratory diseases of 136 Chinese cities were from 2006 to 2019. Heat wave and cold spell were selected as the indicator events of extreme high temperature and extreme low temperature, respectively. The generalized linear model and time-varying distributed lag model were used to perform a two-stage time-series analysis to evaluate the temporal variation of the mortality risk associated with extreme temperature in the total population, sub-populations (sex- and age- specific) and different regions (climatic zone and relative humidity level).

RESULTS

During the study period, relative risk (RR) of respiratory mortality associated with heat wave decreased from 1.22 (95 %CI: 1.07-1.39) to 1.13 (95 %CI: 1.01-1.26) in the total population, and RR of respiratory mortality associated with cold spell decreased from 1.30 (95 %CI: 1.14-1.49) to 1.17 (95 %CI: 1.08-1.26). The impact of heat wave reduced in the males (P = 0.044) and in the females as with cold spell (P < 0.001). The respiratory mortality risk of people over 65 associated with cold spell decreased (P = 0.040 for people aged 65-74 and P < 0.001 for people over 75). The effect of cold spell reduced in cities from tropical or arid zone (P = 0.035). The effects of both heat wave and cold spell decreased in cities with the relative humidity in the first quartile (P = 0.046 and 0.010, respectively).

CONCLUSION

The impact of heat wave on mortality of respiratory diseases decreased mainly in males and cities with the lowest relative humidity, while the impact of cold spell reduced in females, people over 65 and tropical and arid zone, suggesting adaptation to extreme temperature of Chinese residents to some extent.

Asthma incidence can be influenced by climate change in Italy: findings from the GEIRD study-a climatological and epidemiological assessment

An association between climatic conditions and asthma incidence has been widely assumed. However, it is unclear whether climatic variations have a fingerprint on asthma dynamics over long time intervals. The aim of this study is to detect a possible correlation of the Summer North Atlantic Oscillation (S-NAO) index and the self-calibrated palmer drought severity index (scPDSI) with asthma incidence over the period from 1957 to 2006 in Italy. To this aim, an analysis of non-stationary and non-linear signals was performed on the time series of the Italian databases on respiratory health (ISAYA and GEIRD) including 36,255 individuals overall, S-NAO, and scPDSI indices to search for characteristic periodicities. The ISAYA (Italian Study on Asthma in Young Adults) and GEIRD (Gene Environment Interactions in Respiratory Diseases) studies collected information on respiratory health in general population samples, born between 1925 and 1989 and aged 20-84 years at the time of the interview, from 13 Italian centres. We found that annual asthma total incidence shared the same periodicity throughout the 1957-2006 time interval. Asthma incidence turned out to be correlated with the dynamics of the scPDSI, modulated by the S-NAO, sharing the same averaged 6 year-periodicity. Since climate patterns appear to influence asthma incidence, future studies aimed at elucidating the complex relationships between climate and asthma incidence are warranted.

Unmasking the COVID-19 pandemic prevention gains: excess mortality reversal in 2022

OBJECTIVES

The purpose of this study was to assess the long-term effectiveness of COVID-19 pandemic prevention measures in saving lives after European governments began to lift restrictions.

STUDY DESIGN

Excess mortality interrupted time series.

METHODS

Country-level weekly data on deaths were fitted to the Poisson mixed linear model to estimate excess deaths. Based on this estimate, the percentage of excess deaths above the baseline during the pandemic (week 11 in 2020 to week 15 in 2022) (when public health interventions were in place) and during the post-pandemic period (week 16 in 2022 to week 52 in 2022) were calculated. These results were fitted to the linear regression model to determine any potential relationship between mortality during these two periods.

RESULTS

The model used in this study had high predictive value (adjusted R2 = 59.4%). Mortality during the endemic (post-pandemic) period alone increased by 7.2% (95% confidence interval [CI]: 5.7, 8.6) above baseline, while each percentage increase in mortality during the pandemic corresponded to a 0.357% reduction (95% CI: 0.243, 0.471) in mortality during the post-pandemic period.

CONCLUSIONS

The most successful countries in terms of protective measures also experienced the highest mortality rates after restrictions were lifted. The model used in this study clearly shows a measure of bidirectional mortality displacement that is sufficiently clear to mask any impact of long COVID on overall mortality. Results from this study also seriously impact previous cost-benefit analyses of pandemic prevention measures, since, according to the current model, 12.2% (95% CI: 8.3, 16.1) of the gains achieved in pandemic containment were lost after restrictions were lifted.

Nationwide projections of heat- and cold-related mortality impacts under various climate change and population development scenarios in Switzerland

Climate change and progressive population development (i.e., ageing and changes in population size) are altering the temporal patterns of temperature-related mortality in Switzerland. However, limited evidence exists on how current trends in heat- and cold-related mortality would evolve in future decades under composite scenarios of global warming and population development. Moreover, the contribution of these drivers to future mortality impacts is not well-understood. Therefore, we aimed to project heat- and cold-related mortality in Switzerland under various combinations of emission and population development scenarios and to disentangle the contribution of each of these two drivers using high-resolution mortality and temperature data. We combined age-specific (<75 and ⩾75 years) temperature-mortality associations in each district in Switzerland (1990-2010), estimated through a two-stage time series analysis, with 2 km downscaled CMIP5 temperature data and population and mortality rate projections under two scenarios: RCP4.5/SSP2 and RCP8.5/SSP5. We derived heat and cold-related mortality for different warming targets (1.5 °C, 2.0 °C and 3.0 °C) using different emission and population development scenarios and compared this to the baseline period (1990-2010). Heat-related mortality is projected to increase from 312 (116; 510) in the 1990-2010 period to 1274 (537; 2284) annual deaths under 2.0 °C of warming (RCP4.5/SSP2) and to 1871 (791; 3284) under 3.0 °C of warming (RCP8.5/SSP5). Cold-related mortality will substantially increase from 4069 (1898; 6016) to 6558 (3223; 9589) annual deaths under 2.0 °C (RCP4.5/SSP2) and to 5997 (2951; 8759) under 3.0 °C (RCP8.5/SSP5). Moreover, while the increase in cold-related mortality is solely driven by population development, for heat, both components (i.e., changes in climate and population) have a similar contribution of around 50% to the projected heat-related mortality trends. In conclusion, our findings suggest that both heat- and cold-related mortality will substantially increase under all scenarios of climate change and population development in Switzerland. Population development will lead to an increase in cold-related mortality despite the decrease in cold temperature under warmer scenarios. Whereas the combination of the progressive warming of the climate and population development will substantially increase and exacerbate the total temperature-related mortality burden in Switzerland.

Analysis of time-dependent effects of ambient temperatures on health by vulnerable groups in Korea in 1999-2018

This study compared the relative risks of heat days on mortalities by vulnerable groups (elderly, single-person households, less-educated) in the past decade (1999-2008) and the recent decade (2009-2018) in four cities, Seoul, Incheon, Daegu, and Gwangju, in Korea. It has been known that the health impacts of heatwaves have gradually decreased over time due to socio-economic development, climate adaptation, and acclimatization. Contrary to general perception, we found that the recent relative risk of mortality caused by heat days has increased among vulnerable groups. It may associate with recent increasing trends of severe heat days due to climate change. The increasing relative risk was more significant in single-person households and less-educated groups than in the elderly. It implies that the impacts of climate change-induced severe heat days have been and will be concentrated on vulnerable groups. It suggests that social polarization and social isolation should be addressed to reduce heatwave impacts. Furthermore, this study shows the necessity of customized heatwave policies, which consider the characteristics of vulnerable groups.

Trends in Temperature-associated Mortality in São Paulo (Brazil) between 2000 and 2018: an Example of Disparities in Adaptation to Cold and Heat

Exposure to non-optimal temperatures remains the single most deathful direct climate change impact to health. The risk varies based on the adaptation capacity of the exposed population which can be driven by climatic and/or non-climatic factors subject to fluctuations over time. We investigated temporal changes in the exposure-response relationship between daily mean temperature and mortality by cause of death, sex, age, and ethnicity in the megacity of São Paulo, Brazil (2000-2018). We fitted a quasi-Poisson regression model with time-varying distributed-lag non-linear model (tv-DLNM) to obtain annual estimates. We used two indicators of adaptation: trends in the annual minimum mortality temperature (MMT), i.e., temperature at which the mortality rate is the lowest, and in the cumulative relative risk (cRR) associated with extreme cold and heat. Finally, we evaluated their association with annual mean temperature and annual extreme cold and heat, respectively to assess the role of climatic and non-climatic drivers. In total, we investigated 4,471,000 deaths from non-external causes. We found significant temporal trends for both the MMT and cRR indicators. The former was decoupled from changes in AMT, whereas the latter showed some degree of alignment with extreme heat and cold, suggesting the role of both climatic and non-climatic adaptation drivers. Finally, changes in MMT and cRR varied substantially by sex, age, and ethnicity, exposing disparities in the adaptation capacity of these population groups. Our findings support the need for group-specific interventions and regular monitoring of the health risk to non-optimal temperatures to inform urban public health policies.

Temporal changes in associations between high temperature and hospitalizations by greenspace: Analysis in the Medicare population in 40 U.S. northeast counties

Although research indicates health and well-being benefits of greenspace, little is known regarding how greenspace may influence adaptation to health risks from heat, particularly how these risks change over time. Using daily hospitalization rates of Medicare beneficiaries ≥65 years for 2000-2016 in 40 U.S. Northeastern urban counties, we assessed how temperature-related hospitalizations from cardiovascular causes (CVD) and heat stroke (HS) changed over time. We analyzed effect modification of those temporal changes by Enhanced Vegetation Index (EVI), approximating greenspace. We used a two-stage analysis including a generalized additive model and meta-analysis. Results showed that relative risk (RR) (per 1 °C increase in lag0-3 temperature) for temperature-HS hospitalization was higher in counties with the lowest quartile EVI (RR = 2.7, 95% CI: 2.0, 3.4) compared to counties with the highest quartile EVI (RR = 0.40, 95% CI: 0.14, 1.13) in the early part of the study period (2000-2004). RR of HS decreased to 0.88 (95% CI: 0.31, 2.53) in 2013-2016 in counties with the lowest quartile EVI. RR for HS changed over time in counties in the highest quartile EVI, with RRs of 0.4 (95% CI: -0.7, 1.4) in 2000-2004 and 2.4 (95% CI: 1.6, 3.2) in 2013-2016. Findings suggest that adaptation to heat-health associations vary by greenness. Greenspace may help lower risks from heat but such health risks warrant continuous local efforts such as heat-health plans.

Temperature-mortality relationship in North Carolina, USA: Regional and urban-rural differences

BACKGROUND

Health disparities exist between urban and rural populations, yet research on rural-urban disparities in temperature-mortality relationships is limited. As inequality in the United States increases, understanding urban-rural and regional differences in the temperature-mortality association is crucial.

OBJECTIVE

We examined regional and urban-rural differences of the temperature-mortality association in North Carolina (NC), USA, and investigated potential effect modifiers.

METHODS

We applied time-series models allowing nonlinear temperature-mortality associations for 17 years (2000-2016) to generate heat and cold county-specific estimates. We used second-stage analysis to quantify the overall effects. We also explored potential effect modifiers (e.g. social associations, greenness) using stratified analysis. The analysis considered relative effects (comparing risks at 99th to 90th temperature percentiles based on county-specific temperature distributions for heat, and 1st to 10th percentiles for cold) and absolute effects (comparing risks at specific temperatures).

RESULTS

We found null effects for heat-related mortality (relative effect: 1.001 (95% CI: 0.995-1.007)). Overall cold-mortality risk for relative effects was 1.019 (1.015-1.023). All three regions had statistically significant cold-related mortality risks for relative and absolute effects (relative effect: 1.019 (1.010-1.027) for Coastal Plains, 1.021 (1.015-1.027) for Piedmont, 1.014 (1.006-1.023) for Mountains). The heat mortality risk was not statistically significant, whereas the cold mortality risk was statistically significant, showing higher cold-mortality risks in urban areas than rural areas (relative effect for heat: 1.006 (0.997-1.016) for urban, 1.002 (0.988-1.017) for rural areas; relative effect for cold: 1.023 (1.017-1.030) for urban, 1.012 (1.001-1.023) for rural areas). Findings are suggestive of higher relative cold risks in counties with the less social association, higher population density, less green-space, higher PM_2.5, lower education level, higher residential segregation, higher income inequality, and higher income (e.g., Ratio of Relative Risks 1.72 (0.68, 4.35) comparing low to high education).

CONCLUSION

Results indicate cold-mortality risks in NC, with potential differences by regional, urban-rural areas, and community characteristics.

Heatwave Damage Prediction Using Random Forest Model in Korea

Climate change increases the frequency and intensity of heatwaves, causing significant human and material losses every year. Big data, whose volumes are rapidly increasing, are expected to be used for preemptive responses. However, human cognitive abilities are limited, which can lead to ineffective decision making during disaster responses when artificial intelligence-based analysis models are not employed. Existing prediction models have limitations with regard to their validation, and most models focus only on heat-associated deaths. In this study, a random forest model was developed for the weekly prediction of heat-related damages on the basis of four years (2015–2018) of statistical, meteorological, and floating population data from South Korea. The model was evaluated through comparisons with other traditional regression models in terms of mean absolute error, root mean squared error, root mean squared logarithmic error, and coefficient of determination (R2). In a comparative analysis with observed values, the proposed model showed an R2 value of 0.804. The results show that the proposed model outperforms existing models. They also show that the floating population variable collected from mobile global positioning systems contributes more to predictions than the aggregate population variable.

Association between moderately cold temperature and mortality in China

Ambient air temperature is a key factor affecting human health. Adverse effects of extreme weather on mortality have been well explored and expounded in numerous epidemiological studies. The relationship between moderate temperature and mortality is, however, underexplored. This study quantitatively investigated the temperature-dependent mortality burden in China. Data on daily average temperature and mortality in 15 Chinese cities during 2010-2016 were collected for this study. The association between temperature and city-specific mortality was investigated with a quasi-Poisson regression combined with a distributed lag nonlinear model across lag 0-21 days. The results were then included in a multivariate meta-analysis to derive the pooled estimates of the effect of temperature on mortality at the multi-city level. Mortality fractions attributable to cold and heat (i.e., at temperatures below and above the minimum mortality temperature (MMT)) were calculated. Additionally, temperature ranges were further divided into 1 °C intervals of ambient temperature, and the attributable fractions were calculated for each range. The MMT varied from the 71th to 93th percentiles of temperature in the 15 Chinese cities, centering at the 78th percentile at the multi-city level. In total, 12.65% of non-accidental mortality was attributable to non-optimum temperature, of which cold and hot temperatures corresponded to attributable fractions of 11.38% and 1.27%, respectively. The results of temperature stratifications suggested that moderately cold temperatures provided the highest contribution to mortality caused by temperature. Specifically, the highest attributable fractions were at 7 °C, 7 °C, 8 °C, 8 °C, 4 °C, 4 °C, 5 °C, 7 °C, 7 °C, 4 °C, 5 °C, 5 °C, 6 °C, 11 °C, and 12 °C, for Harbin, Changchun, Shenyang, Urumqi, Beijing, Tianjin, Shijiazhuang, Xining, Lanzhou, Nanjing, Shanghai, Hefei, Chengdu, Kunming, and Guangzhou, respectively. Cold temperature was responsible for a higher proportion of deaths than heat. Moderate cold temperature contributed to most of the total health burden. Finally, the cumulative total counts of deaths caused by moderate cold were the largest. Although moderate cold conferred a slightly lower relative risk than extreme cold, it was more common than extreme cold. Taken together, our results show that the effects of moderate cold temperature on health should receive more attention. Furthermore, our findings could help improve the prediction of climate change effects on human health and support the development of response strategies for the changing climate.

Geospatial context of social and environmental factors associated with health risk during temperature extremes: Review and discussion

This study reviews forty-six publications between 2008 and 2017 dealing with socio-environmental impacts on adverse health effects of temperature extremes, in a geospatial context. The review showed that most studies focus on extremely hot weather but lack analysis of how spatial heterogeneity across a region can influence cold mortality/morbidity. There are limitations regarding the use of temperature datasets for spatial analyses. Only a few studies have applied air temperature datasets with high spatial resolution to health studies, but none of these studies have used anthropogenic heat as a factor for analysis of health risk. In addition, the elderly is generally recognized as a vulnerable group in most studies, but the interaction between old age and temperature risk varies by location. Other socio-demographic factors such as low income, low education and accessibility to community shelters may also need to be considered in the future. There are only a few studies which investigate the interaction between temperature and air pollution in a geospatial context, despite the fact that this is a known interaction that can influence health risk under extreme weather. In conclusions, although investigation of temperature effects on health risk is already at the "mature stage", studies of socio-environmental influences on human health under extreme weather in a geospatial context is still being investigated. A comprehensive assessment is required to analyse how the spatial aspects of the geophysical and social environments can influence human health under extreme weather, in order to develop a better community plan and health protocols for disaster preparedness.

Research Trends in Agenda-setting for Climate Change Adaptation Policy in the Public Health Sector in Korea

Many studies have been conducted to assess the health effects of climate change in Korea. However, there has been a lack of consideration regarding how the results of these studies can be applied to relevant policies. The current study aims to examine research trends at the agenda-setting stage and to review future ways in which health-related adaptation to climate change can be addressed within national public health policy. A systematic review of previous studies of the health effects of climate change in Korea was conducted. Many studies have evaluated the effect of ambient temperature on health. A large number of studies have examined the effects on deaths and cardio-cerebrovascular diseases, but a limitation of these studies is that it is difficult to apply their findings to climate change adaptation policy in the health sector. Many infectious disease studies were also identified, but these mainly focused on malaria. Regarding climate change-related factors other than ambient temperature, studies of the health effects of these factors (with the exception of air pollution) are limited. In Korea, it can be concluded that studies conducted as part of the agenda-setting stage are insufficient, both because studies on the health effects of climate change have not ventured beyond defining the problem and because health adaptation to climate change has not been set as an important agenda item. In the future, the sharing and development of relevant databases is necessary. In addition, the priority of agenda items should be determined as part of a government initiative.

Global drivers of minimum mortality temperatures in cities

Human mortality shows a pronounced temperature dependence. The minimum mortality temperature (MMT) as a characteristic point of the temperature-mortality relationship is influenced by many factors. As MMT estimates are based on case studies, they are sporadic, limited to data-rich regions, and their drivers have not yet been clearly identified across case studies. This impedes the elaboration of spatially comprehensive impact studies on heat-related mortality and hampers the temporal transfer required to assess climate change impacts. Using 400 MMTs from cities, we systematically establish a generalised model that is able to estimate MMTs (in daily apparent temperature) for cities, based on a set of climatic, topographic and socio-economic drivers. A sigmoid model prevailed against alternative model setups due to having the lowest Akaike Information Criterion (AICc) and the smallest RMSE. We find the long-term climate, the elevation, and the socio-economy to be relevant drivers of our MMT sample within the non-linear parametric regression model. A first model application estimated MMTs for 599 European cities (>100 000 inhabitants) and reveals a pronounced decrease in MMTs (27.8-16 °C) from southern to northern cities. Disruptions of this pattern across regions of similar mean temperatures can be explained by socio-economic standards as noted for central eastern Europe. Our alternative method allows to approximate MMTs independently from the availability of daily mortality records. For the first time, a quantification of climatic and non-climatic MMT drivers has been achieved, which allows to consider changes in socio-economic conditions and climate. This work contributes to the comparability among MMTs beyond location-specific and regional limits and, hence, towards a spatially comprehensive impact assessment for heat-related mortality.

Heat waves in South Korea: differences of heat wave characteristics by thermal indices

Heat wave warning systems and related research define heat waves using various indices and there exists no standard definition for a heat wave. Despite various weather forecast services for heat stress in South Korea, it is unclear how different thermal indices affect the designation of heat waves and health effect estimates. We aimed to analyze trends of heat wave characteristics and mortality associations using various criteria for the warm season (June-September) in 2011-5 for the most populated two cities in South Korea, Seoul and Busan. Hourly weather monitoring data and daily mortality data in each city were obtained. The following indices were estimated to define heat waves: air temperature, heat index (HI), humidex, apparent temperature (AT), effective temperature (ET), and wet-bulb globe temperature (WBGT). The thresholds of each index for heat wave definitions were obtained by statistical distribution (95th percentiles) and minimum mortality temperature (MMT). Thermal indices showed clustering of accumulation of excess heat above thresholds for northeast regions in the cities while air temperature showed it for central regions. Compared to 95th percentiles, the MMTs resulted 14 times longer heat wave days for thermal indices except for air temperature. When MMTs were used, nine times larger excess mortality from heat waves occurred for all indices compared to that from heat waves defined by the 95th percentiles. The thermal indices with the highest association between heat and mortality varied between the two cities: air temperature for Seoul and WBGT for Busan. Heat wave warnings should be based on a thorough comparison of how different heat wave criteria will affect the public health impact of heat wave warnings in terms of identifying a heat wave and degree of health impacts due to it.

Ambient temperature and mortality due to acute myocardial infarction in Brazil: an ecological study of time-series analyses

Ambient temperature may lead to decompensation of cardiovascular diseases and deaths by acute myocardial infarction (AMI). Little is known about this relationship in South American countries located in regions of a hot climate. This study aims to investigate the effects of ambient temperature on mortality due to AMI in six Brazilian micro-regions, which present different climates. We analyzed daily records of deaths by AMI between 1996 and 2013. We estimated the accumulate relative and attributable risks with lags of up to 14 days, using distributed non-linear lag model. Micro-regions that were closest to the equator did not show an association between temperature and mortality. The lowest risk temperatures varied between 22 °C and 28 °C, in the Southern region of Brazil and the Midwest region, respectively. Low temperatures associated with the highest mortality risk were observed in the same areas, varying between 5 °C and 15 °C. The number of deaths attributed to cold temperatures varied from 176/year in Brasilia to 661/year in São Paulo and those deaths attributed to hot temperatures in Rio de Janeiro amounted to 115/year. We showed the relative risk and the attributable risk of warmer and colder days in tropical regions. The estimate of the number of deaths due to climate, varying according to each area, is a way of bringing information to those responsible for health policies based on easily-understood measurements.

Evidence for a link between the Atlantic Multidecadal Oscillation and annual asthma mortality rates in the US

An association between climatic conditions and asthma mortality has been widely assumed. However, it is unclear whether climatic variations have a fingerprint on asthma dynamics over long time intervals. The aim of this study is to detect a possible correlation between climatic indices, namely the Atlantic Multidecadal Oscillation and Pacific Decadal Oscillation, and asthma mortality rates over the period from 1950 to 2015 in the contiguous US. To this aim, an analysis of non-stationary and non-linear signals was performed on time series of US annual asthma mortality rates, AMO and PDO indices to search for characteristic periodicities. Results revealed that asthma death rates evaluated for four different age groups (5-14 yr; 15-24 yr; 25-34 yr; 35-44 yr) share the same pattern of fluctuation throughout the 1950-2015 time interval, but different trends, i.e. a positive (negative) trend for the two youngest (oldest) categories. Annual asthma death rates turned out to be correlated with the dynamics of the AMO, and also modulated by the PDO, sharing the same averaged ∼44 year-periodicity. The results of the current study suggest that, since climate patterns have proved to influence asthma mortality rates, they could be advisable in future studies aimed at elucidating the complex relationships between climate and asthma mortality.

The Use of a Quasi-Experimental Study on the Mortality Effect of a Heat Wave Warning System in Korea

Many cities and countries have implemented heat wave warning systems to combat the health effects of extreme heat. Little is known about whether these systems actually reduce heat-related morbidity and mortality. We examined the effectiveness of heat wave alerts and health plans in reducing the mortality risk of heat waves in Korea by utilizing the discrepancy between the alerts and the monitored temperature. A difference-in-differences analysis combined with propensity score weighting was used. Mortality, weather monitoring, and heat wave alert announcement data were collected for 7 major cities during 2009–2014. Results showed evidence of risk reduction among people aged 19–64 without education (−0.144 deaths/1,000,000 people, 95% CI: −0.227, −0.061) and children aged 0–19 (−0.555 deaths/1,000,000 people, 95% CI: −0.993, −0.117). Decreased cardiovascular and respiratory mortality was found in several subgroups including single persons, widowed people, blue-collar workers, people with no education or the highest level of education (university or higher). No evidence was found for decreased all-cause mortality in the population (1.687 deaths/1,000,000 people per day; 95% CI: 1.118, 2.255). In conclusion, heat wave alerts may reduce mortality for several causes and subpopulations of age and socio-economic status. Further work needs to examine the pathways through which the alerts impact subpopulations differently.

Analysis of Mortality Change Rate from Temperature in Summer by Age, Occupation, Household Type, and Chronic Diseases in 229 Korean Municipalities from 2007⁻2016

This study analyzed mortality change rate (MCR: daily change rate of mortality at a given temperature per average summer mortality) for 229 municipalities in Korea considering age, occupation, household type, chronic diseases, and regional temperature distribution. We found that the MCR for heat wave differs depending on socioeconomic factors and the temperature distribution in the region. The MCRs for the elderly (≥65 years of age), outdoor workers, one-person households, and chronic disease patients start to increase at lower temperatures and react more sensitively to temperature than others. For the socioeconomic factors considered in this study, occupation was found to be the most significant factor for the MCR differences (outdoor workers 1.17 and others 1.10 above 35 °C, p < 0.01). The MCRs of elderly outdoor workers increased consistently with temperature, while the MCRs of younger outdoor workers decreased at 33 °C, the heat wave warning level in Korea. The MCRs in lower temperature regions start to increase at 28 °C, whereas the MCRs start to increase at 30 °C in higher temperature regions. The results of this study suggest that heat wave policies should be based on contextualized impacts considering age, occupation, household type, chronic disease, and regional temperature distribution.

Public perceptions of the health risks of extreme heat across US states, counties, and neighborhoods

Extreme heat is the leading weather-related cause of death in the United States. Many individuals, however, fail to perceive this risk, which will be exacerbated by global warming. Given that awareness of one's physical and social vulnerability is a critical precursor to preparedness for extreme weather events, understanding Americans' perceptions of heat risk and their geographic variability is essential for promoting adaptive behaviors during heat waves. Using a large original survey dataset of 9,217 respondents, we create and validate a model of Americans' perceived risk to their health from extreme heat in all 50 US states, 3,142 counties, and 72,429 populated census tracts. States in warm climates (e.g., Texas, Nevada, and Hawaii) have some of the highest heat-risk perceptions, yet states in cooler climates often face greater health risks from heat. Likewise, places with older populations who have increased vulnerability to health effects of heat tend to have lower risk perceptions, putting them at even greater risk since lack of awareness is a barrier to adaptive responses. Poorer neighborhoods and those with larger minority populations generally have higher risk perceptions than wealthier neighborhoods with more white residents, consistent with vulnerability differences across these populations. Comprehensive models of extreme weather risks, exposure, and effects should take individual perceptions, which motivate behavior, into account. Understanding risk perceptions at fine spatial scales can also support targeting of communication and education initiatives to where heat adaptation efforts are most needed.

Difference in temporal variation of temperature-related mortality risk in seven major South Korean cities spanning 1998-2013

Temporal variation of temperature-related mortality risk is an important issue in climate change era. However, difference in this temporal variation across cities in South Korea remains unclear. The aim of this study was to explore whether temporal variation might differ spatially across seven metropolitan cities of Korea during the period of 1998-2013. We estimated cumulative associations between temperature (up to previous 14 days of exposure) and all-cause mortality, and compared cumulative associations between the first eight years (1998-2005) and the last eight years (2006-2013). Multivariate meta-regression analysis was performed to investigate what factors might be associated with spatial and temporal variation in cumulative associations. We found that Busan, Daegu, and Gwangju experienced decrease in heat effect from 1998-2005 to 2006-2013, while Incheon experienced increase in heat effect. By comparing mortality risk at 99th percentile of temperature to mortality risk at minimum mortality temperature, percentage increase of mortality risk changed from 4.8% (95% CI: -1.3, 11.3) to 0.4% (95% CI: -6.0, 7.4) in Busan, from 17.2% (95% CI: 10.2, 24.7) to 4.0% (95% CI: -1.4, 9.8) in Daegu, from 20.3% (95% CI: 11.5, 29.7) to 2.2% (95% CI: -3.5, 8.3) in Gwangju, and from 3.5% (95% CI: 0.2, 6.8) to 7.9% (95% CI: 5.0, 10.9) in Incheon, respectively. Change in average temperature from 1998-2005 to 2006-2013 was negatively associated with change in heat effect even though average temperature in most of the cities fluctuated over time. We also found that all seven cities had decrease in effect of moderate cold temperature from 1998-2005 to 2006-2013. Such decrease was associated with improvement in medical resources. Results of this study suggest that plans for adaptation to temperature-related risks should differ across populations because adaptation to temperature varies across populations and within the same population over different time.

Comparison of health risks by heat wave definition: Applicability of wet-bulb globe temperature for heat wave criteria

Despite the active applications of thermal comfort indices for heat wave definitions, there is lack of evaluation for the impact of extended days of high temperature on health outcomes using many of the indices. This study compared the impact of heat waves on health outcomes among different heat wave definitions based on thermal comfort and air temperature. We compared heat waves in South Korea (cities and provinces) for the warm season for 2011-2014, using air temperature, heat index (HI), and web-bulb globe temperature (WBGT). Heat waves were defined as days with daily maximum values of each index at a specified threshold (literature-based, the 90th and 95th percentiles) or above. Distributed lag non-linear models and meta-analysis were used to estimate risk of mortality and hospitalization for all-causes, cardiovascular causes, respiratory causes and heat disorders during heat wave days compared to non-heat wave days. WBGT identified 1.15 times longer maximum heat wave duration for the study periods than air temperature when the thresholds were based on 90th and 95th percentiles. Over the study period, for heat waves defined by WBGT and HI, the Southwestern region showed the highest total number of heat wave days, whereas for air temperature the longest heat wave days were identified in the southeastern region. The highest and most significant impact of heat waves were found by WBGT for hospitalization from heat disorders (Relative risk = 2.959, 95% CI: 1.566-5.594). In sensitivity analyses using different structure of lags and temperature metrics (e.g., daily mean and minimum), the impacts of heat waves on most health outcomes substantially increased by using WBGT for heat wave definitions. As a result, WBGT and its thresholds can be used to relate heat waves and heat-related diseases to improve the prevention effectiveness of heat wave warnings and give informative health guidelines according to the range of WBGT thresholds.

A multi-country analysis on potential adaptive mechanisms to cold and heat in a changing climate

BACKGROUND

Temporal variation of temperature-health associations depends on the combination of two pathways: pure adaptation to increasingly warmer temperatures due to climate change, and other attenuation mechanisms due to non-climate factors such as infrastructural changes and improved health care. Disentangling these pathways is critical for assessing climate change impacts and for planning public health and climate policies. We present evidence on this topic by assessing temporal trends in cold- and heat-attributable mortality risks in a multi-country investigation.

METHODS

Trends in country-specific attributable mortality fractions (AFs) for cold and heat (defined as below/above minimum mortality temperature, respectively) in 305 locations within 10 countries (1985-2012) were estimated using a two-stage time-series design with time-varying distributed lag non-linear models. To separate the contribution of pure adaptation to increasing temperatures and active changes in susceptibility (non-climate driven mechanisms) to heat and cold, we compared observed yearly-AFs with those predicted in two counterfactual scenarios: trends driven by either (1) changes in exposure-response function (assuming a constant temperature distribution), (2) or changes in temperature distribution (assuming constant exposure-response relationships). This comparison provides insights about the potential mechanisms and pace of adaptation in each population.

RESULTS

Heat-related AFs decreased in all countries (ranging from 0.45-1.66% to 0.15-0.93%, in the first and last 5-year periods, respectively) except in Australia, Ireland and UK. Different patterns were found for cold (where AFs ranged from 5.57-15.43% to 2.16-8.91%), showing either decreasing (Brazil, Japan, Spain, Australia and Ireland), increasing (USA), or stable trends (Canada, South Korea and UK). Heat-AF trends were mostly driven by changes in exposure-response associations due to modified susceptibility to temperature, whereas no clear patterns were observed for cold.

CONCLUSIONS

Our findings suggest a decrease in heat-mortality impacts over the past decades, well beyond those expected from a pure adaptation to changes in temperature due to the observed warming. This indicates that there is scope for the development of public health strategies to mitigate heat-related climate change impacts. In contrast, no clear conclusions were found for cold. Further investigations should focus on identification of factors defining these changes in susceptibility.