Dataset Information

Engagement in outdoor physical activity under ambient fine particulate matter pollution: A risk-benefit analysis.

ABSTRACT: OBJECTIVE:Outdoor physical activity (PA) brings important health benefits, but exposure to polluted air increases health risks. This study aimed to quantify the tradeoff of PA under fine particulate matter (PM_2.5) air pollution by estimating the optimal PA duration under various pollution levels. METHODS:A risk-benefit analysis was performed to estimate the optimal outdoor moderate-intensity PA (MPA) duration under varying PM_2.5 concentrations. RESULTS:An inverse nonlinear relationship was identified between optimal MPA duration and background PM_2.5 concentration levels. When background PM_2.5 concentration increased to 186 µg/m³, the optimal outdoor MPA duration decreased to 2.5 h/week, the minimum level recommended by current PA guidelines. When background PM_2.5 concentration further increased to 235 µg/m³, the optimal outdoor MPA duration decreased to 1 h/week. The relationship between optimal MPA duration and background PM_2.5 concentration levels was stronger when exercising at a location closer to a source of air pollution. Compared to the general adult population, adults aged 60 years and older had substantially steeper curves-the optimal outdoor MPA duration decreased to 2.5 h/week when background PM_2.5 concentration reached 45 µg/m³. CONCLUSION:The health benefit of outdoor MPA by far outweighs the health risk of PM_2.5 pollution for the global average urban background concentration (22 ?g/m³). This modeling study examined a single type of air pollutant and suffered from measurement errors and estimation uncertainties. Future research should examine other air pollutants and indoor PA, incorporate short- and mid-term health effects of MPA and air pollution into the risk-benefit analysis, and provide estimates specific for high-risk subgroups.

SUBMITTER: An R

PROVIDER: S-EPMC7537654 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Engagement in outdoor physical activity under ambient fine particulate matter pollution: A risk-benefit analysis.

An Ruopeng R Kang Hyojung H Cao Lianzhong L Xiang Xiaoling X

Journal of sport and health science 20201006 4

<h4>Background</h4>Outdoor physical activity (PA) brings important health benefits, but exposure to polluted air increases health risks. This study aimed to quantify the tradeoff of PA under fine particulate matter (PM<sub>2.5</sub>) air pollution by estimating the optimal PA duration under various pollution levels.<h4>Methods</h4>A risk-benefit analysis was performed to estimate the optimal outdoor moderate-intensity PA (MPA) duration under varying PM<sub>2.5</sub> concentrations.<h4>Results</h ...[more]

PMID: 33035708

Similar Datasets

Project description:ImportanceOutdoor particulate matter 2.5 μm or less in diameter (PM2.5) is a ubiquitous environmental neurotoxicant that may affect the developing brain. Little is known about associations between PM2.5 and white matter connectivity.ObjectivesTo assess associations between annual residential PM2.5 exposure and white matter microstructure health in a US sample of children 9 to 10 years of age and to examine whether associations are specific to certain white matter pathways or vary across neuroimaging diffusion markers reflective of intracellular and extracellular microstructural processes.Design, setting, and participantsThis cross-sectional study, the Adolescent Brain and Cognitive Development (ABCD) Study, was composed of 21 study sites across the US and used baseline data collected from children 9 to 10 years of age from September 1, 2016, to October 15, 2018. Data analysis was performed from September 15, 2020, to June 30, 2021.ExposuresAnnual mean PM2.5 exposure estimated by ensemble-based models and assigned to the primary residential addresses at baseline.Main outcomes and measuresDiffusion-weighted imaging (DWI) and tractography were used to delineate white matter tracts. The biophysical modeling technique of restriction spectrum imaging (RSI) was implemented to examine total hindered diffusion and restricted isotropic and anisotropic intracellular diffusion in each tract. Hierarchical mixed-effects models with natural splines were used to analyze the associations between PM2.5 exposure and DWI.ResultsIn a study population of 7602 children (mean [SD] age, 119.1 [7.42] months; 3955 [52.0%] female; 160 [ 21.%] Asian, 1025 [13.5%] Black, 1616 [21.3%] Hispanic, 4025 [52.9%] White, and 774 [10.2%] other [identified by parents as American Indian/Native American or Alaska Native; Native Hawaiian, Guamanian, Samoan, other Pacific Islander; Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese, or other Asian; or other race]), associations were seen between annual ambient PM2.5 and hemispheric differences in white matter microstructure. Hemisphere-stratified models revealed significant associations between PM2.5 exposure and restricted isotropic intracellular diffusion in the left cingulum, in the left superior longitudinal fasciculus, and bilaterally in the fornix and uncinate fasciculus. In tracts with strong positive associations, a PM2.5 increase from 8 to 12 μg/m3 was associated with increases of 2.16% (95% CI, 0.49%-3.84%) in the left cingulum, 1.95% (95% CI, 0.43%-3.47%) in the left uncinate, and 1.68% (95% CI, 0.01%-3.34%) in the right uncinate. Widespread negative associations were observed between PM2.5 and mean diffusivity.Conclusions and relevanceThe findings of this cross-sectional study suggest that annual mean PM2.5 exposure during childhood is associated with increased restricted isotropic diffusion and decreased mean diffusivity of specific white matter tracts, potentially reflecting differences in the composition of white matter microarchitecture.

Project description:ObjectiveTo quantitate the 2016 global and national burden of chronic kidney disease (CKD) attributable to ambient fine particulate matter air pollution ≤ 2.5 μm in aerodynamic diameter (PM2.5).DesignWe used the Global Burden of Disease (GBD) study data and methodologies to estimate the 2016 burden of CKD attributable to PM2.5 in 194 countries and territories. Population-weighted PM2.5 levels and incident rates of CKD for each country were curated from the GBD study publicly available data sources.SettingGBD global and national data on PM2.5 and CKD.Participants194 countries and territories.Main outcome measuresWe estimated the attributable burden of disease (ABD), years living with disability (YLD), years of life lost (YLL) and disability-adjusted life-years (DALYs).ResultsThe 2016 global burden of incident CKD attributable to PM2.5 was 6 950 514 (95% uncertainty interval: 5 061 533-8 914 745). Global YLD, YLL and DALYs of CKD attributable to PM2.5 were 2 849 311 (1 875 219-3 983 941), 8 587 735 (6 355 784-10 772 239) and 11 445 397 (8 380 246-14 554 091), respectively. Age-standardised ABD, YLL, YLD and DALY rates varied substantially among geographies. Populations in Mesoamerica, Northern Africa, several countries in the Eastern Mediterranean region, Afghanistan, Pakistan, India and several countries in Southeast Asia were among those with highest age-standardised DALY rates. For example, age-standardised DALYs per 100 000 were 543.35 (391.16-707.96) in El Salvador, 455.29 (332.51-577.97) in Mexico, 408.41 (283.82-551.84) in Guatemala, 238.25 (173.90-303.98) in India and 178.26 (125.31-238.47) in Sri Lanka, compared with 5.52 (0.82-11.48) in Sweden, 6.46 (0.00-14.49) in Australia and 12.13 (4.95-21.82) in Canada. Frontier analyses showed that Mesoamerican countries had significantly higher CKD DALY rates relative to other countries with comparable sociodemographic development.ConclusionsOur results demonstrate that the global toll of CKD attributable to ambient air pollution is significant and identify several endemic geographies where air pollution may be a significant driver of CKD burden. Air pollution may need to be considered in the discussion of the global epidemiology of CKD.

Project description:BackgroundEcologic analyses suggest that living in areas with higher levels of ambient fine particulate matter air pollution (PM2.5) is associated with higher risk of adverse COVID-19 outcomes. Studies accounting for individual-level health characteristics are lacking.MethodsWe leveraged the breadth and depth of the US Department of Veterans Affairs national healthcare databases and built a national cohort of 169,102 COVID-19 positive United States Veterans, enrolled between March 2, 2020 and January 31, 2021, and followed them through February 15, 2021. Annual average 2018 PM2.5 exposure, at an approximately 1 km2 resolution, was linked with residential street address at the year prior to COVID-19 positive test. COVID-19 hospitalization was defined as first hospital admission between 7 days prior to, and 15 days after, the first COVID-19 positive date. Adjusted Poisson regression assessed the association of PM2.5 with risk of hospitalization.ResultsThere were 25,422 (15.0%) hospitalizations; 5,448 (11.9%), 5,056 (13.0%), 7,159 (16.1%), and 7,759 (19.4%) were in the lowest to highest PM2.5 quartile, respectively. In models adjusted for State, demographic and behavioral factors, contextual characteristics, and characteristics of the pandemic a one interquartile range increase in PM2.5 (1.9 µg/m3) was associated with a 10% (95% CI: 8%-12%) increase in risk of hospitalization. The association of PM2.5 and risk of hospitalization among COVID-19 individuals was present in each wave of the pandemic. Models of non-linear exposure-response suggested increased risk at PM2.5 concentrations below the national standard 12 µg/m3. Formal effect modification analyses suggested higher risk of hospitalization associated with PM2.5 in Black people compared to White people (p = 0.045), and in those living in socioeconomically disadvantaged neighborhoods (p < 0.001).ConclusionsExposure to higher levels of PM2.5 was associated with increased risk of hospitalization among COVID-19 infected individuals. The risk was evident at PM2.5 levels below the regulatory standards. The analysis identified those of Black race and those living in disadvantaged neighborhoods as population groups that may be more susceptible to the untoward effect of PM2.5 on risk of hospitalization in the setting of COVID-19.

Project description:Using daily fine particulate matter (PM2.5) composition data from the 2000-2005 U.S. EPA Chemical Speciation Network (CSN) for over 200 sites, we applied multivariate methods to identify and quantify the major fine particulate matter (PM2.5) source components in the U.S. Novel aspects of this work were: (1) the application of factor analysis (FA) to multi-city daily data, drawing upon both spatial and temporal variations of chemical species; and, (2) the exclusion of secondary components (sulfates, nitrates and organic carbon) from the source identification FA to more clearly discern and apportion the PM2.5 mass to primary emission source categories. For the quantification of source-related mass, we considered two approaches based upon the FA results: 1) using single key tracers for sources identified by FA in a mass regression; and, 2) applying Absolute Principal Component Analysis (APCA). In each case, we followed a two-stage mass regression approach, in which secondary components were first apportioned among the identified sources, and then mass was apportioned to the sources and to other secondary mass not explained by the individual sources. The major U.S. PM2.5 source categories identified via FA (and their key elements) were: Metals Industry (Pb, Zn); Crustal/Soil Particles (Ca, Si); Motor Vehicle Traffic (EC, NO2); Steel Industry (Fe, Mn); Coal Combustion (As, Se); Oil Combustion (V, Ni); Salt Particles (Na, Cl) and Biomass Burning (K). Nationwide spatial plots of the source-related PM2.5 impacts were confirmatory of the factor interpretations: ubiquitous sources, such as Traffic and Soil, were found to be spread across the nation, more unique sources (such as Steel and Metals Processing) being highest in select industrialized cities, Biomass Burning was highest in the U.S. Northwest, while Residual Oil combustion was highest in cities in the Northeastern U.S. and in cities with major seaports. The sum of these source contributions and the secondary PM2.5 components agreed well with the U.S. PM2.5 observed during the study period (mean=14.3 ug/m3; R2= 0.91). Apportionment regression analyses using single-element tracers for each source category gave results consistent with the APCA estimates. Comparisons of nearby sites indicated that the PM2.5 mass and the secondary aerosols were most homogenous spatially, while traffic PM2.5 and its tracer, EC, were among the most spatially representative of the source-related components. Comparison of apportionment results to a previous analysis of the 1979-1982 IP Network revealed similar and correlated major U.S. source category factors, albeit at lower levels than in the earlier period, suggesting a consistency in the U.S. spatial patterns of these source-related exposures over time, as well. These results indicate that applying source apportionment methods to the nationwide CSN can be an informative avenue for identifying and quantifying source components for the subsequent estimation of source-specific health effects, potentially contributing to more efficient regulation of PM2.5.

Dataset Information

Engagement in outdoor physical activity under ambient fine particulate matter pollution: A risk-benefit analysis.

Publications

Engagement in outdoor physical activity under ambient fine particulate matter pollution: A risk-benefit analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets