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

Association between synoptic types in Beijing and acute myocardial infarction hospitalizations: A comprehensive analysis of environmental factors

BACKGROUND

Environmental factors like air pollution and temperature can trigger acute myocardial infarction (AMI). However, the link between large-scale weather patterns (synoptic types) and AMI admissions has not been extensively studied. This research aimed to identify the different synoptic air types in Beijing and investigate their association with AMI occurrences.

METHODS

We analyzed data from Beijing between 2013 and 2019, encompassing 2556 days and 149,632 AMI cases. Using principal component analysis and hierarchical clustering, classification into distinct synoptic types was conducted based on weather and pollution measurements. To assess the impact of each type on AMI risk over 14 days, we employed a distributed lag non-linear model (DLNM), with the reference being the lowest risk type (Type 2).

RESULTS

Four synoptic types were identified: Type 1 with warm, humid weather; Type 2 with warm temperatures, low humidity, and long sunshine duration; Type 3 with cold weather and heavy air pollution; and Type 4 with cold temperatures, dryness, and high wind speed. Type 4 exhibited the greatest cumulative relative risk (CRR) of 1.241 (95%CI: 1.150, 1.339) over 14 days. Significant effects of Types 1, 3, and 4 on AMI events were observed at varying lags: 4-12 days for Type 1, 1-6 days for Type 3, and 1-11 days for Type 4. Females were more susceptible to Types 1 and 3, while individuals younger than 65 years old showed increased vulnerability to Types 3 and 4.

CONCLUSION

Among the four synoptic types identified in Beijing from 2013 to 2019, Type 4 (cold, dry, and windy) presented the highest risk for AMI hospitalizations. This risk was particularly pronounced for males and people under 65. Our findings collectively highlight the need for improved methods to identify synoptic types. Additionally, developing a warning system based on these synoptic conditions could be crucial for prevention.

Short-term association between air temperature and mortality in seven cities in Norway: A time series analysis

BACKGROUND

The association between ambient air temperature and mortality has not been assessed in Norway. This study aimed to quantify for seven Norwegian cities (Oslo, Bergen, Stavanger, Drammen, Fredrikstad, Trondheim and Tromsø) the non-accidental, cardiovascular and respiratory diseases mortality burden due to non-optimal ambient temperatures.

METHODS

We used a historical daily dataset (1996-2018) to perform city-specific analyses with a distributed lag non-linear model with 14 days of lag, and pooled results in a multivariate meta-regression. We calculated attributable deaths for heat and cold, defined as days with temperatures above and below the city-specific optimum temperature. We further divided temperatures into moderate and extreme using cut-offs at the 1st and 99th percentiles.

RESULTS

We observed that 5.3% (95% confidence interval (CI) 2.0-8.3) of the non-accidental related deaths, 11.8% (95% CI 6.4-16.4) of the cardiovascular and 5.9% (95% CI -4.0 to 14.3) of the respiratory were attributable to non-optimal temperatures. Notable variations were found between cities and subgroups stratified by sex and age. The mortality burden related to cold dominated in all three health outcomes (5.1%, 2.0-8.1, 11.4%, 6.0-15.4, and 5.1%, -5.5 to 13.8 respectively). Heat had a more pronounced effect on the burden of respiratory deaths (0.9%, 0.2-1.0). Extreme cold accounted for 0.2% of non-accidental deaths and 0.3% of cardiovascular and respiratory deaths, while extreme heat contributed to 0.2% of non-accidental and to 0.3% of respiratory deaths.

CONCLUSIONS

Most of the burden could be attributed to the contribution of moderate cold. This evidence has significant implications for enhancing public-health policies to better address health consequences in the Norwegian setting.

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 influence of weather types over northern Greece on respiratory and cardio-vascular mortality

Extreme ambient temperatures are well-known for their adverse impact on public health, in the form of increased mortality and morbidity due to respiratory and cardio-vascular diseases. However, to capture the total impact of weather on cause-specific mortality/morbidity, the synoptic atmospheric conditions over the region under study need to be taken into account. The objective of this work is to identify weather types over Thessaloniki, Greece, statistically associated with mortality from circulatory and respiratory diseases, in an attempt to holistically determine the impact of weather on cause-specific mortality in the region. For this purpose, we employed datasets from the NCEP/NCAR Reanalysis comprising intrinsic daily data, gridded at a resolution of 2.5°×2.5° and covering a 41-year period (1980-2020). The first set used contains data of 500 hPa and 1,000 hPa geopotential heights for the main geographical domain of the Mediterranean region (30°N-45°N, 10°Ε-35°E). The second set comprises meteorological variables (2 m temperature, specific humidity, 2 m zonal and 2 m meridional wind and total cloud cover) for a geographical domain of north Greece (40.95°Ν, 22.50°Ε-26.25°E). We applied a combination of principal components analysis (PCA) as a dimensionality reduction tool and k-means cluster analysis (CA) in order to group days with homogeneous synoptic meteorological parameters. The derived weather types were statistically correlated with respiratory and mortality data for the time-period 1999-2018. It was concluded that the most fatal conditions for public health in Thessaloniki were associated with weather types bringing low/extremely low ambient temperature over north Greece.

Effects of circulation weather types on influenza hospital admissions in Spain

In this study, we use a statistical approach based on generalized additive models, linking atmospheric circulation and the number of influenza-related hospital admissions in the Spanish Iberian Peninsula during 2003-2013. The relative risks are estimated for administrative units in the Spanish territory, which is politically structured into 15 regions called autonomous communities. A catalog of atmospheric circulation types is defined for this purpose. The relationship between the exposure and response variables is modeled using a distributed lag nonlinear model (DLNM). Types from southwest and anticyclonic are significant in terms of the probability of having more influenza-related hospital admissions for all of Spain. The heterogeneity of the results is very high. The relative risk is also estimated for each autonomous community and weather type, with the maximum number of influenza-related hospital admissions associated with circulation types from the southwest and the south. We identify six specific situations where relative risk is considered extreme and twelve with a high risk of increasing influenza-related hospital admissions. The rest of the situations present a moderate risk. Atmospheric local conditions become a key factor for understanding influenza spread in each spatial unit of the Peninsula. Further research is needed to understand how different weather variables (temperature, humidity, and sun radiation) interact and promote the spread of influenza.

Evaluation of the ERA5 reanalysis-based Universal Thermal Climate Index on mortality data in Europe

Air temperature has been the most commonly used exposure metric in assessing relationships between thermal stress and mortality. Lack of the high-quality meteorological station data necessary to adequately characterize the thermal environment has been one of the main limitations for the use of more complex thermal indices. Global climate reanalyses may provide an ideal platform to overcome this limitation and define complex heat and cold stress conditions anywhere in the world. In this study, we explored the potential of the Universal Thermal Climate Index (UTCI) based on ERA5 - the latest global climate reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) - as a health-related tool. Employing a novel ERA5-based thermal comfort dataset ERA5-HEAT, we investigated the relationships between the UTCI and daily mortality data in 21 cities across 9 European countries. We used distributed lag nonlinear models to assess exposure-response relationships between mortality and thermal conditions in individual cities. We then employed meta-regression models to pool the results for each city into four groups according to climate zone. To evaluate the performance of ERA5-based UTCI, we compared its effects on mortality with those for the station-based UTCI data. In order to assess the additional effect of the UTCI, the performance of ERA5-and station-based air temperature (T) was evaluated. Whilst generally similar heat- and cold-effects were observed for the ERA5-and station-based data in most locations, the important role of wind in the UTCI appeared in the results. The largest difference between any two datasets was found in the Southern European group of cities, where the relative risk of mortality at the 1st percentile of daily mean temperature distribution (1.29 and 1.30 according to the ERA5 vs station data, respectively) considerably exceeded the one for the daily mean UTCI (1.19 vs 1.22). These differences were mainly due to the effect of wind in the cold tail of the UTCI distribution. The comparison of exposure-response relationships between ERA5-and station-based data shows that ERA5-based UTCI may be a useful tool for definition of life-threatening thermal conditions in locations where high-quality station data are not available.

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.

Higher Temperatures, Higher Solar Radiation, and Less Humidity Is Associated With Poor Clinical and Laboratory Outcomes in COVID-19 Patients

Background: The COVID-19 pandemic varies between countries, with suggestions that weather might contribute to the transmission mode, disease presentation, severity, and clinical outcomes. Yet the exact link between climate and COVID-19 is still not well-explored. Objectives: This study aimed to evaluate the effect of hot geographical region weather [like United Arab Emirates (UAE)] on COVID-19 clinical profile and outcomes. Temperature, wind speed, cloud cover, precipitation, and other weather-related variables were studied concerning COVID-19 patients outcomes and laboratory results. Methodology: A total of 434 COVID-19 positive patients admitted between January and June 2020, were recruited from Al Kuwait Hospital, Dubai, UAE. Temperature, wind speed, cloud cover, and precipitation rate were retrieved from history+ for the day when COVID-19 patients presented to the hospital. These weather parameters were correlated with COVID-19 clinical and laboratory parameters. Results: Our results showed that patients needed admission in days with higher temperatures, higher solar radiation, and less humidity were associated with higher deaths. This association can be linked to the association of these weather parameters with age at diagnosis; higher C-reactive protein (CRP), neutrophil count, white cell count (WCC), aspartate aminotransferase (AST), and alkaline phosphatase (ALP); and lower lymphocyte count, estimated glomerular filtration rate (eGFR), hemoglobin (Hb), Na, and albumin, all of which are considered poor prognostic factors for COVID-19. Conclusion: Our study highlighted the importance of weather-related variables on the dynamics of mortality and clinical outcomes of COVID-19. The hot weather might makes some people, especially those with comorbidities or older ages, develop aggressive inflammation that ends up with complications and mortality.

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.