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BACKGROUND: Heat stroke is a significant cause of mortality in response to high summer temperatures. There is limited evidence on the pattern and magnitude of the association between temperature and heat stroke mortality. We examined this association in Spain, using data from a 27-year follow-up period. METHODS: We used a space-time-stratified case-crossover design. We analyzed data using conditional quasi-Poisson regression with distributed lag nonlinear models. RESULTS: Spain recorded a total of 285 heat stroke deaths between 1990 and 2016. Heat stroke deaths occurred in 6% of the days in the summer months. The mean temperature was, on average, 5 °C higher on days when a heat stroke was recorded than on days without heat stroke deaths. The overall relative risk was 1.74 (95% confidence interval = 1.54, 1.96) for a 1 °C rise in mean temperature above the threshold of 16 °C, at which a heat stroke death was first recorded. We observed lagged effects as long as 10 days. CONCLUSIONS: Although heat stroke represents a small fraction of total heat-attributable mortality during the summer, it is strongly associated with high temperatures, providing an immediately visible warning of heat-related risk.
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Golpe de Calor , Humanos , Temperatura , Espanha/epidemiologia , Temperatura Alta , Estações do AnoRESUMO
BACKGROUND AND AIM: Short-term associations between air pollution and mortality have been well reported in Japan, but the historical changes in mortality risk remain unknown. We examined temporal changes in the mortality risks associated with short-term exposure to four criteria air pollutants in selected Japanese cities. METHODS: We collected daily mortality data for non-accidental causes (n = 5,748,206), cardiovascular (n = 1,938,743) and respiratory diseases (n = 777,266), and air pollutants (sulfur dioxide [SO2], nitrogen dioxide [NO2], suspended particulate matter [SPM], and oxidants [Ox]) in 10 cities from 1977 to 2015. We performed two-stage analysis with 5-year stratification to estimate the relative risk (RR) of mortality per 10-unit increase in the 2-day moving average of air pollutant concentrations. In the first stage, city-specific associations were assessed using a quasi-Poisson generalized linear regression model. In the second stage, city-specific estimates were pooled using a random-effects meta-analysis. Linear trend and ratio of relative risks (RRR) were computed to examine temporal changes. RESULTS: When stratifying the analysis by every 5 years, average concentrations in each sub-period decreased for SO2, NO2, and SPM (14.2-2.3 ppb, 29.4-17.5 ppb, 52.1-20.6 µg/m3, respectively) but increased for Ox (29.1-39.1 ppb) over the study period. We found evidence of a negative linear trend in the risk of cardiovascular mortality associated with SPM across sub-periods. However, the risks of non-accidental and respiratory mortality per 10-unit increase in SPM concentration were significantly higher in the most recent period than in the earliest period. Other gaseous pollutants did not show such temporal risk change. The risks posed by these pollutants were slightly to moderately heterogeneous in the different cities. CONCLUSIONS: The mortality risks associated with short-term exposure to SPM changed, with different trends by cause of death, in 10 cities over 39 years whereas the risks for other gaseous pollutants were relatively stable.
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Poluição do Ar , Exposição Ambiental , Mortalidade , Humanos , Poluentes Atmosféricos/toxicidade , Poluentes Atmosféricos/análise , Poluição do Ar/efeitos adversos , Poluição do Ar/análise , Cidades/epidemiologia , Exposição Ambiental/efeitos adversos , Exposição Ambiental/análise , Poluentes Ambientais/análise , Poluentes Ambientais/toxicidade , Dióxido de Nitrogênio/toxicidade , Dióxido de Nitrogênio/análise , Material Particulado/toxicidade , Material Particulado/análise , Dióxido de Enxofre/toxicidade , Dióxido de Enxofre/análise , Japão/epidemiologia , Medição de Risco , Mortalidade/tendênciasRESUMO
BACKGROUND: During the COVID-19 pandemic, several illnesses were reduced. In Japan, heat-related illnesses were reduced by 22% compared to pre-pandemic period. However, it is uncertain as to what has led to this reduction. Here, we model the association of maximum temperature and heat-related illnesses in the 47 Japanese prefectures. We specifically examined how the exposure and lag associations varied before and during the pandemic. METHODS: We obtained the summer-specific, daily heat-related illness ambulance transport (HIAT), exposure variable (maximum temperature) and covariate data from relevant data sources. We utilized a stratified (pre-pandemic and pandemic), two-stage approach. In each stratified group, we estimated the 1) prefecture-level association using a quasi-Poisson regression coupled with a distributed lag non-linear model, which was 2) pooled using a random-effects meta-analysis. The difference between pooled pre-pandemic and pandemic associations was examined across the exposure and the lag dimensions. RESULTS: A total of 321,655 HIAT cases was recorded in Japan from 2016 to 2020. We found an overall reduction of heat-related risks for HIAT during the pandemic, with a wide range of reduction (10.85 to 57.47%) in the HIAT risk, across exposure levels ranging from 21.69 °C to 36.31 °C. On the contrary, we found an increment in the delayed heat-related risks during the pandemic at Lag 2 (16.33%; 95% CI: 1.00, 33.98%). CONCLUSION: This study provides evidence of the impact of COVID-19, particularly on the possible roles of physical interventions and behavioral changes, in modifying the temperature-health association. These findings would have implications on subsequent policies or heat-related warning strategies in light of ongoing or future pandemics.
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Ambulâncias , COVID-19 , Transtornos de Estresse por Calor , Pandemias , Ambulâncias/estatística & dados numéricos , COVID-19/epidemiologia , Transtornos de Estresse por Calor/epidemiologia , Humanos , Japão/epidemiologiaRESUMO
BACKGROUND: Ambient temperature may contribute to seasonality of mortality; in particular, a warming climate is likely to influence the seasonality of mortality. However, few studies have investigated seasonality of mortality under a warming climate. METHODS: Daily mean temperature, daily counts for all-cause, circulatory, and respiratory mortality, and annual data on prefecture-specific characteristics were collected for 47 prefectures in Japan between 1972 and 2015. A quasi-Poisson regression model was used to assess the seasonal variation of mortality with a focus on its amplitude, which was quantified as the ratio of mortality estimates between the peak and trough days (peak-to-trough ratio (PTR)). We quantified the contribution of temperature to seasonality by comparing PTR before and after temperature adjustment. Associations between annual mean temperature and annual estimates of the temperature-unadjusted PTR were examined using multilevel multivariate meta-regression models controlling for prefecture-specific characteristics. RESULTS: The temperature-unadjusted PTRs for all-cause, circulatory, and respiratory mortality were 1.28 (95% confidence interval (CI): 1.27-1.30), 1.53 (95% CI: 1.50-1.55), and 1.46 (95% CI: 1.44-1.48), respectively; adjusting for temperature reduced these PTRs to 1.08 (95% CI: 1.08-1.10), 1.10 (95% CI: 1.08-1.11), and 1.35 (95% CI: 1.32-1.39), respectively. During the period of rising temperature (1.3 °C on average), decreases in the temperature-unadjusted PTRs were observed for all mortality causes except circulatory mortality. For each 1 °C increase in annual mean temperature, the temperature-unadjusted PTR for all-cause, circulatory, and respiratory mortality decreased by 0.98% (95% CI: 0.54-1.42), 1.39% (95% CI: 0.82-1.97), and 0.13% (95% CI: - 1.24 to 1.48), respectively. CONCLUSION: Seasonality of mortality is driven partly by temperature, and its amplitude may be decreasing under a warming climate.
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Doenças Cardiovasculares/mortalidade , Mudança Climática/mortalidade , Mortalidade/tendências , Doenças Respiratórias/mortalidade , Causas de Morte , Temperatura Baixa/efeitos adversos , Temperatura Alta/efeitos adversos , Humanos , Japão/epidemiologia , Análise de Regressão , Estações do Ano , TempoRESUMO
An amendment to this paper has been published and can be accessed via the original article.
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BACKGROUND: Children are exposed to p,p'-dichlorodiphenyltrichloroethane (p,p'-DDT) and p,p'-dichlorodiphenyldichloroethylene (p,p'-DDE) through placental and lactational transfer. Some studies have suggested that early-life exposure to these compounds could lead to increased body mass index (BMI) during childhood. Our aim was to assess whether children's exposure during the first 2 years of life is associated with BMI z-score in Japanese children at 42 months of age. METHODS: We used data from a birth cohort (n = 290) of the Tohoku Study of Child Development. p,p'-DDT and p,p'-DDE levels were measured in breast milk samples collected 1 month after birth, and levels in children were estimated using a toxicokinetic model for three exposure periods (0-6 months, 6-12 months, 12-24 months). Associations between exposure estimates and BMI z-score at 42 months of age were assessed using multivariate linear regression models. RESULTS: We found no significant association between levels of p,p'-DDT measured in breast milk or estimated in children and BMI z-score. However, we observed associations between estimated p,p'-DDE levels in girls during all postnatal exposure periods and BMI z-score; for each log increase in the estimated p,p'-DDE levels, BMI z-score increased by 0.23 (C.I. 95%: 0.01, 0.45) for the 0-6 months exposure period, 0.26 (C.I. 95%: 0.06, 0.47) for the 6-12 months exposure period, and 0.24 (C.I. 95%: 0.05, 0.43) for the 12-24 months exposure period. CONCLUSION: In this study of Japanese children, estimated postnatal p,p'-DDE levels were associated with increased BMI z-score at 42 months of age, mostly in girls. These results are in line with previous studies supporting that early-life exposure to p,p'-DDE may be associated with higher BMI during childhood.
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Índice de Massa Corporal , DDT/metabolismo , Diclorodifenil Dicloroetileno/metabolismo , Exposição Ambiental , Poluentes Ambientais/metabolismo , Leite Humano/química , Desenvolvimento Infantil , Pré-Escolar , Feminino , Humanos , Inseticidas/metabolismo , Japão , Estudos Longitudinais , MasculinoRESUMO
Few studies have been conducted to investigate the underlying mechanisms of the effect of temperature on cardiovascular disease at population level, especially among Chinese population. A total of 56,039 participants were recruited from Kailuan cohort study, China. The lipoprotein profile indicators, including triglycerides (TG), low-density lipoprotein (LDL), and high-density lipoprotein, were collected. Non-linear associations between temperature and the lipoprotein profile indicators were examined using a nonlinear function for temperature. Stratified analyses were performed in groups by individual characteristics (age, gender, and body mass index) and individual behaviors (physical activities and smoking habits). Generally, a non-linear relationship was found between cholesterol levels and temperature. A 1 °C decrease in temperature below the threshold was related with 0.004 mmol/L (95% CI 0.0004, 0.008), 0.022 mmol/L (95% CI 0.020, 0.025), and 0.009 mmol/L (95% CI 0.008, 0.011) increase in TG, LDL, and HDL, respectively; a 1 °C increase in temperature above the threshold was associated with 0.005 mmol/L (95% CI 0.003, 0.007), 0.012 mmol/L (95% CI 0.009, 0.015), and 0.002 mmol/L (95% CI 0.001, 0.004) increase in TG, LDL, and HDL, respectively. Stratified analyses showed that effect estimates on TG and LDL were larger among females, subjects with higher BMI, and those with smoking habits, while effect estimates on HDL were smaller among these subjects (expect for female). Our results suggest both cold and hot effect of temperature on cholesterol. Furthermore, females, and people with higher BMI or smoking habit may be more susceptible to outdoor temperature.
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Colesterol , China , HDL-Colesterol , LDL-Colesterol , Estudos de Coortes , Feminino , Humanos , Temperatura , TriglicerídeosRESUMO
China is suffering from severe air pollution from fine particulate matter [≤ 2.5 µm in aerodynamic diameter (PM2.5)], especially East China. But its future trends and potential health impacts remain unclear. The study objectives were to project future trends of PM2.5 and its short-term effect on mortality in East China by 2030. First, daily changes in PM2.5 concentrations between 2005 and 2030 were projected under the "current legislation" scenario (CLE) and the "maximum technically feasible reduction" scenario (MFR). Then, they were linked to six population projections, two mortality rate projections, and PM2.5-mortality associations to estimate the changes in PM2.5-related mortality in East China between 2005 and 2030. Under the CLE scenario, the annual mean PM2.5 concentration was projected to decrease by 0.62 µg/m(3) in East China, which could cause up to 124,000 additional deaths, when considering the population growth. Under the MFR scenario, the annual mean PM2.5 concentration was projected to decrease by 20.41 µg/m(3) in East China. At least 230,000 deaths could be avoided by such a large reduction in PM2.5 concentration under MFR scenario, even after accounting for the population growth. Therefore, our results suggest that reducing PM2.5 concentration substantially in East China would benefit the public health. Otherwise, it may still remain as a great health risk in the future, especially when the population keeps growing.
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Mortalidade/tendências , Material Particulado/efeitos adversos , Poluentes Atmosféricos/análise , Poluição do Ar/análise , China/epidemiologia , Legislação como Assunto , Tamanho da Partícula , IncertezaRESUMO
The objective of this study is to examine the association between ambient temperature and children's lung function in Baotou, China. We recruited 315 children (8-12 years) from Baotou, China in the spring of 2004, 2005, and 2006. They performed three successive forced expiratory measurements three times daily (morning, noon, and evening) for about 5 weeks. The highest peak expiratory flow (PEF) was recorded for each session. Daily data on ambient temperature, relative humidity, and air pollution were monitored during the same period. Mixed models with a distributed lag structure were used to examine the effects of temperature on lung function while adjusting for individual characteristics and environmental factors. Low temperatures were significantly associated with decreases in PEF. The effects lasted for lag 0-2 days. For all participants, the cumulative effect estimates (lag 0-2 days) were -1.44 (-1.93, -0.94) L/min, -1.39 (-1.92, -0.86) L/min, -1.40 (-1.97, -0.82) L/min, and -1.28 (-1.69, -0.88) L/min for morning, noon, evening, and daily mean PEF, respectively, associated with 1 °C decrease in daily mean temperature. Generally, the effects of temperature were slightly stronger in boys than in girls for noon, evening, and daily mean PEF, while the effects were stronger in girls for morning PEF. PM2.5 had joint effects with temperature on children's PEF. Higher PM2.5 increased the impacts of low temperature. Low ambient temperatures are associated with lower lung function in children in Baotou, China. Preventive health policies will be required for protecting children from the cold weather.
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Poluentes Atmosféricos/análise , Pulmão/fisiopatologia , Material Particulado/análise , Temperatura , Poluição do Ar/análise , Criança , China/epidemiologia , Monitoramento Ambiental , Feminino , Humanos , Masculino , Dióxido de Nitrogênio/análise , Pico do Fluxo Expiratório , Dióxido de Enxofre/análiseRESUMO
The case-crossover design is widely used in environmental epidemiology as an effective alternative to the conventional time-series regression design to estimate short-term associations of environmental exposures with a range of acute events. This tutorial illustrates the implementation of the time-stratified case-crossover design to study aggregated health outcomes and environmental exposures, such as particulate matter air pollution, focusing on adjusting covariates and investigating effect modification using conditional Poisson regression. Time-varying confounders can be adjusted directly in the conditional regression model accounting for the adequate lagged exposure-response function. Time-invariant covariates at the subpopulation level require reshaping the typical time-series data set into a long format and conditioning out the covariate in the expanded stratum set. When environmental exposure data are available at geographical units, the stratum set should combine time and spatial dimensions. Moreover, it is possible to examine effect modification using interaction models. The time-stratified case-crossover design offers a flexible framework to properly account for a wide range of covariates in environmental epidemiology studies.
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Poluição do Ar , Humanos , Estudos Cross-Over , Poluição do Ar/efeitos adversos , Exposição Ambiental/efeitos adversos , Exposição Ambiental/análise , Material Particulado , Fatores de TempoRESUMO
In this article, we present a comprehensive compilation of open access daily time-series datasets tailored to assess the temperature-mortality association. The data consists of daily mortality counts and average ambient temperature at various levels of geographic aggregation, including data from four cities, ten regions, and two counties, which have been utilised in previously published studies. These datasets are applicable for time-series regression analysis to estimate location-specific temperature-mortality associations. Additionally, the availability of data from multiple geographical locations enabled the exploration of geographical differences by pooling associations using meta-analysis. This compilation aims to serve as a valuable resource for researchers, educators, and students, facilitating their application of time-series regression modelling for research endeavours and training activities.
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Background: Despite an unknown cause, Kawasaki disease (KD) is currently the primary leading cause of acquired heart disease in developed countries in children and has been increasing in recent years. Research efforts have explored environmental factors related to KD, but they are still unclear especially in the tropics. We aimed to describe the incidence of KD in children, assess its seasonality, and determine its association with ambient air temperature in the National Capital Region (NCR), Philippines from January 2009 to December 2019. Methods: Monthly number of KD cases from the Philippine Pediatric Society (PPS) disease registry was collected to determine the incidence of KD. A generalized linear model (GLM) with quasi-Poisson regression was utilized to assess the seasonality of KD and determine its association with ambient air temperature after adjusting for the relevant confounders. Results: The majority of KD cases (68.52%) occurred in children less than five years old, with incidence rates ranging from 14.98 to 23.20 cases per 100,000 population, and a male-to-female ratio of 1.43:1. Seasonal variation followed a unimodal shape with a rate ratio of 1.13 from the average, peaking in March and reaching the lowest in September. After adjusting for seasonality and long-term trend, every one-degree Celsius increase in the monthly mean temperature significantly increased the risk of developing KD by 8.28% (95% CI: 2.12%, 14.80%). Season-specific analysis revealed a positive association during the dry season (RR: 1.06, 95% CI: 1.01, 1.11), whereas no evidence of association was found during the wet season (RR: 1.10, 95% CI: 0.95, 1.27). Conclusion: We have presented the incidence of KD in the Philippines which is relatively varied from its neighboring countries. The unimodal seasonality of KD and its linear association with temperature, independent of season and secular trend, especially during dry season, may provide insights into its etiology and may support enhanced KD detection efforts in the country.
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Recent developments in linkage procedures and exposure modelling offer great prospects for cohort analyses on the health risks of environmental factors. However, assigning individual-level exposures to large population-based cohorts poses methodological and practical problems. In this contribution, we illustrate a linkage framework to reconstruct environmental exposures for individual-level epidemiological analyses, discussing methodological and practical issues such as residential mobility and privacy concerns. The framework outlined here requires the availability of individual residential histories with related time periods, as well as high-resolution spatio-temporal maps of environmental exposures. The linkage process is carried out in three steps: (1) spatial alignment of the exposure maps and residential locations to extract address-specific exposure series; (2) reconstruction of individual-level exposure histories accounting for residential changes during the follow-up; (3) flexible definition of exposure summaries consistent with alternative research questions and epidemiological designs. The procedure is exemplified by the linkage and processing of daily averages of air pollution for the UK Biobank cohort using gridded spatio-temporal maps across Great Britain. This results in the extraction of exposure summaries suitable for epidemiological analyses of both short and long-term risk associations and, in general, for the investigation of temporal dependencies. The linkage framework presented here is generally applicable to multiple environmental stressors and can be extended beyond the reconstruction of residential exposures. IMPACT: This contribution describes a linkage framework to assign individual-level environmental exposures to population-based cohorts using high-resolution spatio-temporal exposure. The framework can be used to address current limitations of exposure assessment for the analysis of health risks associated with environmental stressors. The linkage of detailed exposure information at the individual level offers the opportunity to define flexible exposure summaries tailored to specific study designs and research questions. The application of the framework is exemplified by the linkage of fine particulate matter (PM2.5) exposures to the UK Biobank cohort.
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Objectives: This study aims to estimate the short-term preventable mortality and associated economic costs of complying with the World Health Organization (WHO) air quality guidelines (AQGs) limit values for PM10 and PM2.5 in nine major Latin American cities. Methods: We estimated city-specific PM-mortality associations using time-series regression models and calculated the attributable mortality fraction. Next, we used the value of statistical life to calculate the economic benefits of complying with the WHO AQGs limit values. Results: In most cities, PM concentrations exceeded the WHO AQGs limit values more than 90% of the days. PM10 was found to be associated with an average excess mortality of 1.88% with concentrations above WHO AQGs limit values, while for PM2.5 it was 1.05%. The associated annual economic costs varied widely, between US$ 19.5 million to 3,386.9 million for PM10, and US$ 196.3 million to 2,209.6 million for PM2.5. Conclusion: Our findings suggest that there is an urgent need for policymakers to develop interventions to achieve sustainable air quality improvements in Latin America. Complying with the WHO AQGs limit values for PM10 and PM2.5 in Latin American cities would substantially benefits for urban populations.
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Poluição do Ar , Cidades , Material Particulado , Organização Mundial da Saúde , Material Particulado/análise , Material Particulado/economia , Humanos , América Latina , Poluição do Ar/economia , Poluição do Ar/prevenção & controle , Poluição do Ar/análise , Poluentes Atmosféricos/análise , Poluentes Atmosféricos/economia , Mortalidade , Exposição Ambiental/prevenção & controle , Exposição Ambiental/economiaRESUMO
BACKGROUND: Biomass burning (BB) is a major source of air pollution and particulate matter (PM) in Southeast Asia. However, the health effects of PM smaller than 10 µm (PM10) originating from BB may differ from those of other sources. This study aimed to estimate the short-term association of PM10 from BB with respiratory and cardiovascular hospital admissions in Peninsular Malaysia, a region often exposed to BB events. METHODS: We obtained and analyzed daily data on hospital admissions, PM10 levels and BB days from five districts from 2005 to 2015. We identified BB days by evaluating the BB hotspots and backward wind trajectories. We estimated PM10 attributable to BB from the excess of the moving average of PM10 during days without BB hotspots. We fitted time-series quasi-Poisson regression models for each district and pooled them using meta-analyses. We adjusted for potential confounders and examined the lagged effects up to 3 days, and potential effect modification by age and sex. RESULTS: We analyzed 210 960 respiratory and 178 952 cardiovascular admissions. Almost 50% of days were identified as BB days, with a mean PM10 level of 53.1 µg/m3 during BB days and 40.1 µg/m3 during normal days. A 10 µg/m3 increment in PM10 from BB was associated with a 0.44% (95% CI: 0.06, 0.82%) increase in respiratory admissions at lag 0-1, with a stronger association in adults aged 15-64 years and females. We did not see any significant associations for cardiovascular admissions. CONCLUSIONS: Our findings suggest that short-term exposure to PM10 from BB increased the risk of respiratory hospitalizations in Peninsular Malaysia.
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Poluentes Atmosféricos , Poluição do Ar , Biomassa , Doenças Cardiovasculares , Hospitalização , Material Particulado , Doenças Respiratórias , Humanos , Material Particulado/análise , Material Particulado/efeitos adversos , Malásia/epidemiologia , Feminino , Masculino , Adulto , Pessoa de Meia-Idade , Adolescente , Poluição do Ar/efeitos adversos , Poluição do Ar/análise , Adulto Jovem , Hospitalização/estatística & dados numéricos , Doenças Cardiovasculares/epidemiologia , Idoso , Poluentes Atmosféricos/análise , Poluentes Atmosféricos/efeitos adversos , Doenças Respiratórias/epidemiologia , Criança , Pré-Escolar , Lactente , Exposição Ambiental/efeitos adversos , Exposição Ambiental/estatística & dados numéricos , Recém-NascidoRESUMO
Background: Precipitation could affect the transmission of diarrheal diseases. The diverse precipitation patterns across different climates might influence the degree of diarrheal risk from precipitation. This study determined the associations between precipitation and diarrheal mortality in tropical, temperate, and arid climate regions. Methods: Daily counts of diarrheal mortality and 28-day cumulative precipitation from 1997 to 2019 were analyzed across 29 locations in eight middle-income countries (Argentina, Brazil, Costa Rica, India, Peru, the Philippines, South Africa, and Thailand). A two-stage approach was employed: the first stage is conditional Poisson regression models for each location, and the second stage is meta-analysis for pooling location-specific coefficients by climate zone. Results: In tropical climates, higher precipitation increases the risk of diarrheal mortality. Under extremely wet conditions (95th percentile of 28-day cumulative precipitation), diarrheal mortality increased by 17.8% (95% confidence interval [CI] = 10.4%, 25.7%) compared with minimum-risk precipitation. For temperate and arid climates, diarrheal mortality increases in both dry and wet conditions. In extremely dry conditions (fifth percentile of 28-day cumulative precipitation), diarrheal mortality risk increases by 3.8% (95% CI = 1.2%, 6.5%) for temperate and 5.5% (95% CI = 1.0%, 10.2%) for arid climates. Similarly, under extremely wet conditions, diarrheal mortality risk increases by 2.5% (95% CI = -0.1%, 5.1%) for temperate and 4.1% (95% CI = 1.1%, 7.3%) for arid climates. Conclusions: Associations between precipitation and diarrheal mortality exhibit variations across different climate zones. It is crucial to consider climate-specific variations when generating global projections of future precipitation-related diarrheal mortality.
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BACKGROUND: Climate change can directly impact temperature-related excess deaths and might subsequently change the seasonal variation in mortality. In this study, we aimed to provide a systematic and comprehensive assessment of potential future changes in the seasonal variation, or seasonality, of mortality across different climate zones. METHODS: In this modelling study, we collected daily time series of mean temperature and mortality (all causes or non-external causes only) via the Multi-Country Multi-City Collaborative (MCC) Research Network. These data were collected during overlapping periods, spanning from Jan 1, 1969 to Dec 31, 2020. We projected daily mortality from Jan 1, 2000 to Dec 31, 2099, under four climate change scenarios corresponding to increasing emissions (Shared Socioeconomic Pathways [SSP] scenarios SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). We compared the seasonality in projected mortality between decades by its shape, timings (the day-of-year) of minimum (trough) and maximum (peak) mortality, and sizes (peak-to-trough ratio and attributable fraction). Attributable fraction was used to measure the burden of seasonality of mortality. The results were summarised by climate zones. FINDINGS: The MCC dataset included 126â809â537 deaths from 707 locations within 43 countries or areas. After excluding the only two polar locations (both high-altitude locations in Peru) from climatic zone assessments, we analysed 126â766â164 deaths in 705 locations aggregated in four climate zones (tropical, arid, temperate, and continental). From the 2000s to the 2090s, our projections showed an increase in mortality during the warm seasons and a decrease in mortality during the cold seasons, albeit with mortality remaining high during the cold seasons, under all four SSP scenarios in the arid, temperate, and continental zones. The magnitude of this changing pattern was more pronounced under the high-emission scenarios (SSP3-7.0 and SSP5-8.5), substantially altering the shape of seasonality of mortality and, under the highest emission scenario (SSP5-8.5), shifting the mortality peak from cold seasons to warm seasons in arid, temperate, and continental zones, and increasing the size of seasonality in all zones except the arid zone by the end of the century. In the 2090s compared with the 2000s, the change in peak-to-trough ratio (relative scale) ranged from 0·96 to 1·11, and the change in attributable fraction ranged from 0·002% to 0·06% under the SSP5-8.5 (highest emission) scenario. INTERPRETATION: A warming climate can substantially change the seasonality of mortality in the future. Our projections suggest that health-care systems should consider preparing for a potentially increased demand during warm seasons and sustained high demand during cold seasons, particularly in regions characterised by arid, temperate, and continental climates. FUNDING: The Environment Research and Technology Development Fund of the Environmental Restoration and Conservation Agency, provided by the Ministry of the Environment of Japan.
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Mudança Climática , Temperatura Baixa , Temperatura , Estações do Ano , Estudos ProspectivosRESUMO
OBJECTIVE: To study source apportionment of atmospheric PM10 (particle matter ≤ 10 µm in aerodynamic diameter) and PM2.5 (particle matter ≤ 2.5 µm in aerodynamic diameter) in Beijing,Urumqi and Qingdao, China. METHODS: The atmospheric particle samples of PM10 and PM2.5 collected from Beijing between May 17th and June 18th, 2005, from Urumqi between April 20th and June 1st, 2006 and from Qingdao between April 4th and May 15th, 2005, were detected to trace the source apportionment by factor analysis and enrichment factor methods. RESULTS: In Beijing, the source apportionment results derived from factor analysis model for PM10 were construction dust and soil sand dust (contributing rate of variance at 45.35%), industry dust, coal-combusted smoke and vehicle emissions (contributing rate at 31.83%), and biomass burning dust (13.57%). The main pollution element was Pb, while the content (median (minimum value-maximum value)was 0.216 (0.040-0.795) µg/m(3)) . As for PM2.5, the sources were construction dust and soil sand dust (38.86%), industry dust, coal-combusted smoke and vehicle emissions (25.73%), biomass burning dust (13.10%) and burning oil dust (11.92%). The main pollution element was Zn (0.365(0.126-0.808) µg/m(3)).In Urumqi, source apportionment results for PM10 were soil sand dust and coal-combusted dust(49.75%), industry dust, vehicle emissions and secondary particles dust (30.65%). The main characteristic pollution element was Cd (0.463(0.033-1.351) ng/m(3)). As for PM2.5, the sources were soil sand dust and coal-combusted dust (43.26%), secondary particles dust (22.29%), industry dust and vehicle emissions (20.50%). The main characteristic pollution element was As (14.599 (1.696-36.741) µg/m(3)).In Qingdao, source apportionment results for PM10 were construction dust (30.91%), vehicle emissions and industry dust (29.65%) and secondary particles dust (28.99%). The main characteristic pollution element was Pb (64.071 (5.846-346.831) µg/m(3)). As for PM2.5, the sources were secondary particles dust, industry dust and vehicle emissions (49.82%) and construction dust (33.71%). The main characteristic pollution element was Pb(57.340 (5.004-241.559) µg/m(3)).Enrichment factors of Zn, Pb, As and Cd in PM2.5 were higher than those in PM10 both in Beijing and Urumqi. CONCLUSION: The major sources of the atmospheric particles PM10 and PM2.5 in Beijing were cement dust from construction sites and sand dust from soil; while the major sources of those in Urumqi were pollution by smoke and sand dust from burning coal. The major sources of the atmospheric particles PM10 in Qingdao were cement dust from construction sites; however, the major sources of PM2.5 there were secondary particles dust, industry dust and vehicle emissions. According to our study, the heavy metal elements were likely to gather in PM2.5.
Assuntos
Poluentes Atmosféricos/análise , Cidades , Estações do Ano , China , Poeira/análise , Monitoramento Ambiental/métodos , Tamanho da Partícula , Emissões de Veículos/análiseRESUMO
Ozone (O3)-induced health effects vary in terms of severity, from deterioration of lung function and hospitalization to death. Several studies have reported a linear increase in health risks after O3 exposure. However, current evidence suggests a non-linear U- and J-shaped concentration-response (C-R) function. The potential increasing risks with decreasing O3 concentrations may seem counterintuitive from the traditional standpoint that decreasing exposure should lead to decreasing health risks. Tus, the question of whether the increasing risks with decreasing concentrations are truly O3-induced or might be from other C-R mechanisms. If these potential risks were not accounted for, this may have contributed to the risks observed at the low ozone concentration range. In this study, we examined the short-term effects of photochemical oxidant (Ox, parts per billiion) on outpatient cardiorespiratory visits in 21 Japanese cities after adjusting for other air pollutant-specific C-R functions. Daily cardiorespiratory visits from January 1, 2014 to December 31, 2016 were obtained from the Japanese Medical Data Center Co. Ltd. Similar period of meteorological and air pollution variables were obtained from relevant data sources. We utilized a time-stratified case crossover design coupled with the generalized additive mixed model (TSCC-GAMM) to estimate the association between Ox and cardiorespiratory outpatient visits, after adjusting for several covariates. A total of 2,588,930 visits were recorded across the study period, with a mean of 111.87 and a standard deviation of 138.75. The results revealed that crude Ox-cardiorespiratory visits exhibited a U-shaped pattern. However, adjustment of the oxides of nitrogen, particularly nitrogen monoxide (NO), attenuated the lower risk curve and subsequently altered the shape of the C-R function, with a substantial reduction observed during winter. NO- and nitrogen dioxide (NO2)-adjusted Ox-cardiorespiratory associations increased nearly linearly, without an apparent threshold. Current evidence suggests the importance of adjusting the oxides of nitrogen in estimating the Ox C-R risk functions.