Application of spatial synoptic classification in evaluating links between heat stress and cardiovascular mortality and morbidity in Prague, Czech Republic

Effect of Cold Adaptation on the State of Cardiovascular System and Cardiac Tolerance to Ischemia/Reperfusion Injury

Despite the unconditional success achieved in the treatment and prevention of AMI over the past 40 years, mortality in this disease remains high. Hence, it is necessary to develop novel drugs with mechanism of action different from those currently used in clinical practices. Studying the molecular mechanisms involved in the cardioprotective effect of adapting to cold could contribute to the development of drugs that increase cardiac tolerance to the impact of ischemia/reperfusion. An analysis of the published data shows that the long-term human stay in the Far North contributes to the occurrence of cardiovascular diseases. At the same time, chronic and continuous exposure to cold increases tolerance of the rat heart to ischemia/ reperfusion. It has been demonstrated that the cardioprotective effect of cold adaptation depends on the activation of ROS production, stimulation of the β2-adrenergic receptor and protein kinase C, MPT pore closing, and KATP channel.

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.

The joint and interaction effect of high temperature and humidity on mortality in China

BACKGROUND

Although many studies have reported the mortality effect of temperature, there were few studies on the mortality risk of humidity, let alone the joint effect of temperature and humidity. This study aimed to investigate the joint and interaction effect of high temperature and relative humidity on mortality in China, which will deepen understanding the health risk of mixture climate exposure.

METHODS

The mortality and meteorological data were collected from 353 locations in China (2013-2017 in Jilin, Hunan, Guangdong and Yunnan provinces, 2009-2017 in Zhejiang province, and 2006-2011 in other Provinces). We defined location-specific daily mean temperature ≥ 75th percentile of distribution as high temperature, while minimum mortality relative humidity as the threshold of high relative humidity. A time-series model with a distributed lag non-linear model was first employed to estimate the location-specific associations between humid-hot events and mortality, then we conducted meta-analysis to pool the mortality effect of humid-hot events. Finally, an additive interaction model was used to examine the interactive effect between high temperature and relative humidity.

RESULTS

The excess rate (ER) of non-accidental mortality attributed to dry-hot events was 10.18% (95% confidence interval (CI): 8.93%, 11.45%), which was higher than that of wet-hot events (ER = 3.21%, 95% CI: 0.59%, 5.89%). The attributable fraction (AF) of mortality attributed to dry-hot events was 10.00% (95% CI: 9.50%, 10.72%) with higher burden for females, older people, central China, cardiovascular diseases and urban city. While for wet-hot events, AF was much lower (3.31%, 95% CI: 2.60%, 4.30%). We also found that high temperature and low relative humidity had synergistic additive interaction on mortality risk.

CONCLUSION

Dry-hot events may have a higher risk of mortality than wet-hot events, and the joint effect of high temperature and low relative humidity may be greater than the sum of their individual effects.

Effect of extreme hot and cold weather on cause-specific hospitalizations in Sweden: A time series analysis

Considering that several meteorological variables can contribute to weather vulnerability, the estimation of their synergetic effects on health is particularly useful. The spatial synoptic classification (SSC) has been used in biometeorological applications to estimate the effect of the entire suite of weather conditions on human morbidity and mortality. In this study, we assessed the relationships between extremely hot and dry (dry tropical plus, DT+) and hot and moist (moist tropical plus, MT+) weather types in summer and extremely cold and dry (dry polar plus, DP+) and cold and moist (moist polar, MP+) weather types in winter and cardiovascular and respiratory hospitalizations by age and sex. Time-series quasi-Poisson regression with distributed lags was used to assess the relationship between oppressive weather types and daily hospitalizations over 14 subsequent days in the extended summer (May to August) and 28 subsequent days during the extended winter (November to March) over 24 years in 4 Swedish locations from 1991 to 2014. In summer, exposure to hot weather types appeared to reduce cardiovascular hospitalizations while increased the risk of hospitalizations for respiratory diseases, mainly related to MT+. In winter, the effect of cold weather on both cause-specific hospitalizations was small; however, MP+ was related to a delayed increase in cardiovascular hospitalizations, whilst MP+ and DP + increased the risk of hospitalizations due to respiratory diseases. This study provides useful information for the staff of hospitals and elderly care centers who can help to implement protective measures for patients and residents. Also, our results could be helpful for vulnerable people who can adopt protective measures to reduce health risks.

Hot and cold weather based on the spatial synoptic classification and cause-specific mortality in Sweden: a time-stratified case-crossover study

The spatial synoptic classification (SSC) is a holistic categorical assessment of the daily weather conditions at specific locations; it is a useful tool for assessing weather effects on health. In this study, we assessed (a) the effect of hot weather types and the duration of heat events on cardiovascular and respiratory mortality in summer and (b) the effect of cold weather types and the duration of cold events on cardiovascular and respiratory mortality in winter. A time-stratified case-crossover design combined with a distributed lag nonlinear model was carried out to investigate the association of weather types with cause-specific mortality in two southern (Skåne and Stockholm) and two northern (Jämtland and Västerbotten) locations in Sweden. During summer, in the southern locations, the Moist Tropical (MT) and Dry Tropical (DT) weather types increased cardiovascular and respiratory mortality at shorter lags; both hot weather types substantially increased respiratory mortality mainly in Skåne. The impact of heat events on mortality by cardiovascular and respiratory diseases was more important in the southern than in the northern locations at lag 0. The cumulative effect of MT, DT and heat events lagged over 14 days was particularly high for respiratory mortality in all locations except in Jämtland, though these did not show a clear effect on cardiovascular mortality. During winter, the dry polar and moist polar weather types and cold events showed a negligible effect on cardiovascular and respiratory mortality. This study provides valuable information about the relationship between hot oppressive weather types with cause-specific mortality; however, the cold weather types may not capture sufficiently effects on cause-specific mortality in this sub-Arctic region.

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.

Synoptic approach to evaluate the effect of temperature on pediatric respiratory disease-related hospitalization in Seoul, Korea

BACKGROUND

The spatial synoptic classification (SSC) scheme is a daily weather-type classification scheme that is widely used in climatological and epidemiological investigations. We investigated the modification effect of temperature on respiratory disease-related hospital admissions (RAs) in children based on the SSC type.

METHODS

Data on RAs among children aged ≤19 years were collected from the National Inpatient Sample (NIS) database between 2011 and 2015 in Seoul, Korea. In this time-series study, we used Poisson generalized linear models allowing for over-dispersion, with stratification by season and each of the seven distinctive SSC types (Dry moderate [DM], Dry polar [DP], Dry tropical [DT], Moist moderate [MM], Moist polar [MP], Moist tropical [MT], and Transition [T]). We investigated the modification effects of temperature by SSC type through seasonal stratification, adjusting for other meteorological conditions, air pollution, and time trends, and considered the delayed effect for up to four consecutive days. We reported the relative risk percentage change with 95% confidence intervals (CIs) of RAs for every 1 °C increase in ambient temperature, by season and SSC type.

RESULTS

Of the 8346 RAs overall investigated between 2011 and 2015, there were 5271 [63.2%] RAs in children aged 0-4 years. Overall, on majority of the days, the SSC types were DM (665 days [36.4%]), and DP (371 days [20.3%]). With regard to seasons, the different SSC types were distributed as follows: spring, DM (193 days [42.0%]); summer, MT (193 days [42.0%]); fall, DM (241 days [53.0%]); and winter, DP (228 days [50.6%]). A stronger association between RAs and temperature was observed overall (1.28% [95% CI; 0.04%, 2.53%]), and in spring (2.10% [0.62%, 3.60%]). According to SSC type, increased associations between RAs and temperature were detected with DM (2.20% [0.47%, 3.97%]) condition during spring and DT (2.41% [0.22%, 4.64%]) during fall. In addition, on re-categorizing the SSC types from a temperature or humidity standpoint, a modified association was observed especially in children aged ≤4 years and 5-9 years during spring.

CONCLUSIONS

Using temperature variability to distinguish seasonal characteristics, we found that the relationship between temperature and RAs in children varied by SSC type. Application of the SSC scheme as an integrative approach may assist in gaining an understanding of seasonal characteristics and health effects due to temperature change.

Particulate Matter Mortality Rates and Their Modification by Spatial Synoptic Classification

Air pollution levels are highly correlated with temperature or humidity, so we investigated the relationship between PM₁₀ and the spatial synoptic classification (SSC) scheme on daily mortality, according to age group and season. Daily death data for 2000-2014 from Seoul, Korea, were acquired, and time-series analysis was applied with respect to season and to each of seven distinct SSC types: dry moderate (DM); dry polar (DP); dry tropical (DT); moist moderate (MM); moist polar (MP); moist tropical (MT); and transition (T). Modification effects were estimated for daily, non-accidental, cardiovascular, and respiratory mortality between PM₁₀ and SSC types. The following SSC-type-specific increased mortalities were observed, by cause of death: non-accidental mortality: DT (1.86%) and MT (1.86%); cardiovascular mortality: DT (2.83%) and MM (3.00%); respiratory mortality: MT (3.78%). Based on simplified weather types, increased PM₁₀ effects in non-accidental mortality rates were observed in dry (1.54%) and moist (2.32%) conditions among those aged 40-59 years and were detected regardless of conditions in other age groups: 60-74 (1.11%), 75-84 (1.55%), and 85+ (1.75%). The effects of particulate air pollution, by SSC, suggest the applicability of SSC to the comparison and understanding of acute effects of daily mortality based on weather type.

Association between Weather Types based on the Spatial Synoptic Classification and All-Cause Mortality in Sweden, 1991⁻2014

Much is known about the adverse health impact of high and low temperatures. The Spatial Synoptic Classification is a useful tool for assessing weather effects on health because it considers the combined effect of meteorological factors rather than temperature only. The aim of this study was to assess the association between oppressive weather types and daily total mortality in Sweden. Time-series Poisson regression with distributed lags was used to assess the relationship between oppressive weather (Dry Polar, Dry Tropical, Moist Polar, and Moist Tropical) and daily deaths over 14 days in the extended summer (May to September), and 28 days during the extended winter (November to March), from 1991 to 2014. Days not classified as oppressive weather served as the reference category. We computed relative risks with 95% confidence intervals, adjusting for trends and seasonality. Results of the southern (Skåne and Stockholm) and northern (Jämtland and Västerbotten) locations were pooled using meta-analysis for regional-level estimates. Analyses were performed using the dlnm and mvmeta packages in R. During summer, in the South, the Moist Tropical and Dry Tropical weather types increased the mortality at lag 0 through lag 3 and lag 6, respectively. Moist Polar weather was associated with mortality at longer lags. In the North, Dry Tropical weather increased the mortality at shorter lags. During winter, in the South, Dry Polar and Moist Polar weather increased mortality from lag 6 to lag 10 and from lag 19 to lag 26, respectively. No effect of oppressive weather was found in the North. The effect of oppressive weather types in Sweden varies across seasons and regions. In the North, a small study sample reduces precision of estimates, while in the South, the effect of oppressive weather types is more evident in both seasons.

The predictability of heat-related mortality in Prague, Czech Republic, during summer 2015-a comparison of selected thermal indices

We compared selected thermal indices in their ability to predict heat-related mortality in Prague, Czech Republic, during the extraordinary summer 2015. Relatively, novel thermal indices-Universal Thermal Climate Index and Excess Heat Factor (EHF)-were compared with more traditional ones (apparent temperature, simplified wet-bulb globe temperature (WBGT), and physiologically equivalent temperature). The relationships between thermal indices and all-cause relative mortality deviations from the baseline (excess mortality) were estimated by generalized additive models for the extended summer season (May-September) during 1994-2014. The resulting models were applied to predict excess mortality in 2015 based on observed meteorology, and the mortality estimates by different indices were compared. Although all predictors showed a clear association between thermal conditions and excess mortality, we found important variability in their performance. The EHF formula performed best in estimating the intensity of heat waves and magnitude of heat-impacts on excess mortality on the most extreme days. Afternoon WBGT, on the other hand, was most precise in the selection of heat-alert days during the extended summer season, mainly due to a relatively small number of "false alerts" compared to other predictors. Since the main purpose of heat warning systems is identification of days with an increased risk of heat-related death rather than prediction of exact magnitude of the excess mortality, WBGT seemed to be a slightly favorable predictor for such a system.

Spatial Patterns of Heat-Related Cardiovascular Mortality in the Czech Republic

The study examines spatial patterns of effects of high temperature extremes on cardiovascular mortality in the Czech Republic at a district level during 1994–2009. Daily baseline mortality for each district was determined using a single location-stratified generalized additive model. Mean relative deviations of mortality from the baseline were calculated on days exceeding the 90th percentile of mean daily temperature in summer, and they were correlated with selected demographic, socioeconomic, and physical-environmental variables for the districts. Groups of districts with similar characteristics were identified according to socioeconomic status and urbanization level in order to provide a more general picture than possible on the district level. We evaluated lagged patterns of excess mortality after hot spell occurrences in: (i) urban areas vs. predominantly rural areas; and (ii) regions with different overall socioeconomic level. Our findings suggest that climatic conditions, altitude, and urbanization generally affect the spatial distribution of districts with the highest excess cardiovascular mortality, while socioeconomic status did not show a significant effect in the analysis across the Czech Republic as a whole. Only within deprived populations, socioeconomic status played a relevant role as well. After taking into account lagged effects of temperature on excess mortality, we found that the effect of hot spells was significant in highly urbanized regions, while most excess deaths in rural districts may be attributed to harvesting effects.