BACKGROUND AND AIM Multiple studies have reported the impacts of the coronavirus-2019 pandemic on cardiovascular disease (CVD) and the concentration of air pollution, respectively. Although the association between air pollution and CVD outcomes has been widely identified, the changes in the association during the pandemic period have not been fully investigated. This study aimed to examine the nationwide changes in the short-term effect of fine particulate matter (PM2.5) on CVD deaths in South Korea. METHODS We performed an interrupted time-series analysis to estimate temporal changes in the association between PM2.5 and CVD-related deaths (total, ischemic health disease [IHD], cerebrovascular disease [CD], and hypertension) before (Jan 01, 2016 to Feb 17, 2020) and during the pandemic (Feb 18, 2020 to Dec 31, 2020), using daily data. Relative humidity, day-of-week, seasonality, and temporal trend were controlled. We conducted a two-stage analysis to estimate the risk of air pollution on CVD deaths for each of 16 regions and then generated an overall estimate. RESULTS The total number of CVD mortality was 53,552. The average annual concentration of PM2.5 changed before (23.8 µg/m3) and during the pandemic (17.1 µg/m3) in South Korea. For total CVD deaths, the changes in relative risks (RRs; for 10 µg/m3 increase in PM2.5) were not pronounced during the pandemic. Whereas, for ISH and CD, the RRs increased during the pandemic: (pre-pandemic to pandemic period) 1.00 (0.99, 1.01) to 1.02 (1.00, 1.04) for IHD and 1.00 (1.00, 1.01) to 1.02 (1.00, 1.04) for CD, although the changes were not statistically significant (p-values 0.08 and 0.24). CONCLUSIONS We found that the risks of short-term exposure to PM2.5 on mortality for IHD and CD increased in the first pandemic year in South Korea, compared to the pre-pandemic years. KEYWORDS COVID-19, Pandemic, PM2.5, Cardiovascular mortality.
BACKGROUND AND AIM: The association between desert dust and daily mortality has been investigated previously in East Asia, but with a different analytical approach and methods for quantifying dust exposure, rendering it difficult to compare results with other regions. We conducted a study to examine the association using the European Union (EU) Reference Method (Directive 2008/50/EC) to identify desert dust events and quantify exposure as a continuous measurement of particulate matter with diameters of 10 micrometers or less (PM₁₀). METHOD: We collected data on daily mortality (total respiratory and cardiovascular), PM₁₀, and average temperature from four cities – Beijing, Seoul, Fukuoka, and Taipei – with a period of 4-6 years between 2011-2017. Desert dust days were identified using aerosol maps (NAAPS-NRL), back trajectories of air masses (HYSPLIT) and reanalysis product (MERRA-2). We estimated the background level of PM₁₀ and quantified PM₁₀ concentrations by desert and non-desert sources. City-specific Poisson regression models with distributed lags were used to estimate the associations between mortality and source-specific PM₁₀ (by 3 sources: desert and non-desert PM₁₀ on days with or without dust events). RESULTS: Cities located closer to the desert areas had more dust events, ranging from 45% of the days in Beijing to 10% in Taipei. The exposure response curves tend to be more curvilinear for cities located closer to desert areas. We observed associations between mortality and PM₁₀ originating from desert dust notably in Beijing. The largest relative risks estimated for total, respiratory and cardiovascular mortality were 1.05 (95% confidence interval: 1.01, 1.10), 1.20 (1.06, 1.36), and 1.08 (1.02, 1.14), respectively, in comparison to the risk at the 1st percentile (3 microgram/m). Local PM₁₀ were also associated daily mortality but the association varied by cities. CONCLUSIONS: PM₁₀ from desert dusts is an independent risk factor for mortality in populations living near arid areas affected by desert dust.
BackgroundClimate 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.MethodsIn 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.FindingsThe MCC dataset included 126 809 537 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 126 766 164 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.InterpretationA 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.FundingThe Environment Research and Technology Development Fund of the Environmental Restoration and Conservation Agency, provided by the Ministry of the Environment of Japan.
Introduction Ambient temperature is associated with mortality/morbidity at local, national and regional levels. However, the burden of deaths attributed to cold and hot temperatures still remains to be determined at a global level. Methods We downloaded 140 country/region's annual mortality and population data from the World Health Organization Mortality Database and other sources. The pattern of cold and hot temperature-related mortality was assessed for developing and developed countries, separately, using a fixed effect model for meta-analysis. Results Overall, there were total 648,110,558 deaths in 140 countries and regions between 1985 and 2012. There were 1,263,782 deaths attributable to cold temperatures and 155,998 to hot temperatures annually among these countries and regions. During the study period, more deaths were attributable to cold temperatures (6.69%, 95% CI: 6.27–7·11%; and 3.49%, 95% CI: 2.92–4.05) than hot temperatures (0·46%, 95% CI: 0·32–0·59; 0.71%, 95% CI: 0.40–1.01) for developed and developing countries, respectively. Although this fraction varied substantially between countries/regions, it suggests that cold temperatures seemed to impact more on developed countries while hot temperatures appeared to affect developing countries more. Conclusions Globally, ambient temperature is responsible for a substantial fraction of deaths. Although, most of the temperature-related deaths were attributable to, at present, impacts of cold temperature, the mortality pattern will shift significantly as climate change proceeds. It is anticipated that the present cold-dominated mortality pattern will change to the hot-dominated mortality pattern in the near future. The findings may have important implications for the planning of public-health strategies to minimise the health consequences of temperature rise.
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 PM
BACKGROUND AND AIM: To assess and project the impact of urban heat island (UHI) on heat-related mortality in the Tokyo Metropolitan Area (TMA), Japan. METHOD: We collected daily time series data on mean ambient temperature and all-cause mortality from 2010 to 2019 for 242 municipalities in TMA. We quantified the UHI intensity using municipality-specific UHI anomaly (UHIa) and classified them into decile zones. We examined the heat-related mortality for each UHIa zone and then assessed its association with the UHIa. We estimated the heat-attributable excess deaths due to the UHI effect by comparing the observed UHI-related mortality with that under a counterfactual scenario in the past. Next, we projected the heat-attributable excess deaths under two climate change scenarios (RCP 2.6 and 8.5) for each UHIa zone, by allowing for two different assumptions on UHI and adaptation in the future. The difference under each climate change scenario was interpreted as the future impact of UHI on heat-related excess death. RESULTS: The mean UHIa ranged from -2.80°C to 1.29°C. A 1°C increase in mean UHIa was associated with an increase of 0.018 (95% CI: 0.002, 0.034) in heat-related log-relative risk after the full adjustment of all the other confounders. The heat-related excess death attributable to UHI was 0.42% (95% empirical CI [eCI]: 0.26,0.56) in TMA during 2010-2019. Under RCP 8.5, heat-related attributable fraction in TMA is projected to increase from 0.76% (95% eCI: 0.44,1.24) in the 2010s to 2.04% (95% eCI: 1.19,3.05) in the 2090s, and the corresponding attributable fraction due to UHI would increase from 0.52% (95% eCI: 0.33,0.77) to 1.02% (95% eCI: 0.67,1.40). CONCLUSIONS: Our findings suggest UHI contributes to heat-related mortality in TMA, and its impact is projected to increase under a warming climate. *This work was supported by the Japan Science and Technology Agency (JST) as part of SICORP. Grant Number JPMJSC20E4.
To evaluate the effects of particles and their components on lung function.A panel study was conducted on 107 primary schoolchildren. The peak expiratory flow rate (PEFR) for each subject was measured three times a day for 40 days continuously. Particulate air concentrations were measured every day. The concentrations of Pb, Ni, Fe, Mn, Cr, As, Cd, and Zn in particles were measured. Linear mixed-effect models were used to estimate the associations between particles, metal elements, and PEFR.We found that the increase in particles in air was associated with a significant reduction in PEFR. Its effects lasted 2 to 5 days. Pb, Ni, Fe, Mn, and Cr in particles also reduced PEFR. As and Cd increased PEFR. Zn showed inconstant effects on PEFR.This study suggested that most metal components in particles have negative effects on children's lung function.
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.
Background: We quantify the mortality burden and economic loss attributable to nonoptimal temperatures for cold and heat in the Central and South American countries in the Multi-City Multi-Country (MCC) Collaborative Research Network. Methods: We collected data for 66 locations from 13 countries in Central and South America to estimate location-specific temperature–mortality associations using time-series regression with distributed lag nonlinear models. We calculated the attributable deaths for cold and heat as the 2.5th and 97.5th temperature percentiles, above and below the minimum mortality temperature, and used the value of a life year to estimate the economic loss of delayed deaths. Results: The mortality impact of cold varied widely by country, from 9.64% in Uruguay to 0.22% in Costa Rica. The heat-attributable fraction for mortality ranged from 1.41% in Paraguay to 0.01% in Ecuador. Locations in arid and temperate climatic zones showed higher cold-related mortality (5.10% and 5.29%, respectively) than those in tropical climates (1.71%). Arid and temperate climatic zones saw lower heat-attributable fractions (0.69% and 0.58%) than arid climatic zones (0.92%). Exposure to cold led to an annual economic loss of $0.6 million in Costa Rica to $472.2 million in Argentina. In comparison, heat resulted in economic losses of $0.05 million in Ecuador to $90.6 million in Brazil. Conclusion: Most of the mortality burden for Central and South American countries is caused by cold compared to heat, generating annual economic losses of $2.1 billion and $290.7 million, respectively. Public health policies and adaptation measures in the region should account for the health effects associated with nonoptimal temperatures.
To the Editor, The seasonal cycle of respiratory viral diseases is widely recognized.1 A typical seasonal pattern of annual influenza epidemics is observed during the winter season in the northern hemisphere and during the summer season in the southern hemisphere.1,2 This knowledge has suggested that the transmission of SARS-CoV-2 could follow a similar seasonal pattern. Hence, many studies have been conducted to understand the seasonal pattern of COVID-19 since the beginning of the pandemic.3,4 However, a common limitation is the short timeframe since COVID-19 had only been prevalent for less than a year. Consequently, previously reported seasonal patterns could be incomplete and spurious due to the short study period.4 The first case of SARS-CoV-2 virus infection in humans was reported in December 2019 in Wuhan, China, and expanded worldwide. It has now been a year since the World Health Organisation declared the COVID-19 pandemic on March 9, 2020, and data corresponding to a complete seasonal cycle is already available. We aim to provide a descriptive view of the SARS-CoV-2 seasonality globally, comparing patterns between geographical regions (eFigure 1; https://links.lww.com/EE/A132). We collected data on the weekly incident cases of COVID-19 between March 2020 and February 2021 from the European Centre for Disease Control including data from 214 countries (eTable 1; https://links.lww.com/EE/A132).5 We studied the seasonality of COVID-19 in each geographical region using Poisson regression models by fitting periodic functions of time6 and calculating the predicted weekly incidence for each area. The first months of the pandemic were very haphazard in most countries, while some established immediate lockdowns, others took action too late or indecisively.7,8 This fact could make data less comparable at the early stages.9 Nevertheless, Figure 1 shows a consistent pattern in the European regions, reporting winter peaks between November and January. Similarly, some regions in the Northern hemisphere (Northern America, Northern Africa, Eastern, South-eastern, and Western Asia) also show a similar pattern. The seasonality in most regions in the Southern hemisphere and the Equator's intertropical convergence zone show a bimodal distribution with winter peaks between June and August and a second peak in January, which could be related to the appearance of new and more transmissible variants.10 Elsewhere, winter peaks appear heterogeneous with a gradual shift from Southern Asia to Oceania.Figure 1.: Estimated seasonality of COVID-19 incidence by geographical region between March 2020 and February 2021.In summary, although the seasonal pattern of COVID-19 appears to resemble other respiratory viruses, more time, and research is needed to establish its entirety. At this stage, the global changes in seasonality can be partially explained by the impact of public health interventions aiming to reduce the transmission of SARS-CoV-211 and potentially further complicated by the appearance of new variants.10 However, different seasonal patterns could also be found between countries in the same geographical region. We expect the seasonal cycle of SARS-CoV-2 might become more evident in subsequent years. However, it will be necessary to consider the impact that vaccination may have on the population protective immunity12 and any economic measures that could increase contact in the near future.
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