Evaluating the impact of long-term exposure to fine particulate matter on mortality among the elderly.
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ABSTRACT:
SUBMITTER: Wu X
PROVIDER: S-EPMC7439614 | biostudies-literature | 2020 Jul
REPOSITORIES: biostudies-literature
Publications
Evaluating the impact of long-term exposure to fine particulate matter on mortality among the elderly.
Wu X X Braun D D Schwartz J J Kioumourtzoglou M A MA Dominici F F
Science advances 20200717 29
Many studies link long-term fine particle (PM<sub>2.5</sub>) exposure to mortality, even at levels below current U.S. air quality standards (12 micrograms per cubic meter). These findings have been disputed with claims that the use of traditional statistical approaches does not guarantee causality. Leveraging 16 years of data-68.5 million Medicare enrollees-we provide strong evidence of the causal link between long-term PM<sub>2.5</sub> exposure and mortality under a set of causal inference assu ...[more]
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Project description:Background Environmental health risks for individuals with heart failure (HF) have been inadequately studied, as these individuals are not well represented in traditional cohort studies. To address this we studied associations between long-term air pollution exposure and mortality in HF patients. Methods and Results The study population was a hospital-based cohort of individuals diagnosed with HF between July 1, 2004 and December 31, 2016 compiled using electronic health records. Individuals were followed from 1 year after initial diagnosis until death or the end of the observation period (December 31, 2016). We used Cox proportional hazards models to evaluate the association of annual average fine particulate matter (PM2.5) exposure at the time of initial HF diagnosis with all-cause mortality, adjusted for age, race, sex, distance to the nearest air pollution monitor, and socioeconomic status indicators. Among 23 302 HF patients, a 1 μg/m3 increase in annual average PM2.5 was associated with an elevated risk of all-cause mortality (hazard ratio 1.13; 95% CI, 1.10-1.15). As compared with people with exposures below the current national PM2.5 exposure standard (12 μg/m3), those with elevated exposures experienced 0.84 (95% CI, 0.73-0.95) years of life lost over a 5-year period, an observation that persisted even for those residing in areas with PM2.5 concentrations below current standards. Conclusions Residential exposure to elevated concentrations of PM2.5 is a significant mortality risk factor for HF patients. Elevated PM2.5 exposures result in substantial years of life lost even at concentrations below current national standards.
| S-EPMC7335509 | biostudies-literature
Project description:Fasting blood glucose level is the primary indicator for the diagnosis of diabetes. We aim to conduct a longitudinal study on the association between long-term fine particulate matter (PM2.5) exposure and fasting blood glucose concentrations. We recruited and followed up 1449 participants older than 65 years of age in 2009, 2012, 2014, and 2017 in eight counties in China. Fasting blood glucose was repeatedly measured 3697 times in total among these participants. Data on annual ground-level PM2.5 concentrations with a 0.01° spatial resolution from 2005 to 2016 were used to assess exposures. An increase of 10 μg/m3 in 3-year average exposure to PM2.5 was associated with an increase of 0.146 mmol/L (95% confidence interval [CI]: 0.045, 0.248) in fasting blood glucose in all participants. The association was more pronounced among the subgroup with diabetes compared to the subgroup without diabetes (P < .05). In conclusion, Long-term PM2.5 exposure was associated with an increase in fasting blood glucose levels among elderly people. Elderly individuals with diabetes are particularly vulnerable to high level exposures of PM2.5. SUMMARY: Long-term PM2.5 exposure was associated with an increase in fasting blood glucose levels among elderly people. Elderly individuals with diabetes are particularly vulnerable to high level exposures of PM2.5.
| S-EPMC7183512 | biostudies-literature
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| S-EPMC6656583 | biostudies-literature
Project description:Few studies have examined the relationship between long-term exposure to ambient fine particulate matter (PM2.5) and nonaccidental mortality in rural populations.We examined the relationship between PM2.5 and nonaccidental and cardiovascular mortality in the U.S. Agricultural Health Study cohort.The cohort (n = 83,378) included farmers, their spouses, and commercial pesticide applicators residing primarily in Iowa and North Carolina. Deaths occurring between enrollment (1993-1997) and 30 December 2009 were identified by record linkage. Six-year average (2001-2006) remote-sensing derived estimates of PM2.5 were assigned to participants' residences at enrollment, and Cox proportional hazards models were used to estimate hazard ratios (HR) in relation to a 10-?g/m(3) increase in PM2.5 adjusted for individual-level covariates.In total, 5,931 nonaccidental and 1,967 cardiovascular deaths occurred over a median follow-up time of 13.9 years. PM2.5 was not associated with nonaccidental mortality in the cohort as a whole (HR = 0.95; 95% CI: 0.76, 1.20), but consistent inverse relationships were observed among women. Positive associations were observed between ambient PM2.5 and cardiovascular mortality among men, and these associations were strongest among men who did not move from their enrollment address (HR = 1.63; 95% 0.94, 2.84). In particular, cardiovascular mortality risk in men was significantly increased when analyses were limited to nonmoving participants with the most precise exposure geocoding (HR = 1.87; 95% CI: 1.04, 3.36).Rural PM2.5 may be associated with cardiovascular mortality in men; however, similar associations were not observed among women. Further evaluation is required to explore these sex differences.
| S-EPMC4050514 | biostudies-other
Project description:BackgroundEcological evidence suggests that exposure to air pollution affects coronavirus disease 2019 (COVID-19) outcomes. However, no individual-level study has confirmed the association to date.MethodsWe identified COVID-19 patients diagnosed at the University of Cincinnati hospitals and clinics and estimated particulate matter ≤2.5 μm (PM2.5) exposure over a 10-year period (2008-2017) at their residential zip codes. We used logistic regression to evaluate the association between PM2.5 exposure and hospitalizations for COVID-19, adjusting for socioeconomic characteristics and comorbidities.ResultsAmong the 1128 patients included in our study, the mean (standard deviation) PM2.5 was 11.34 (0.70) μg/m3 for the 10-year average exposure and 13.83 (1.03) μg/m3 for the 10-year maximal exposures. The association between long-term PM2.5 exposure and hospitalization for COVID-19 was contingent upon having pre-existing asthma or chronic obstructive pulmonary (COPD) (Pinteraction = 0.030 for average PM2.5 and Pinteraction = 0.001 for maximal PM2.5). In COVID-19 patients with asthma or COPD, the odds of hospitalization were 62% higher with 1 μg/m3 increment in 10-year average PM2.5 (odds ratio [OR]: 1.62, 95% confidence interval [CI]: 1.00-2.64) and 65% higher with 1 μg/m3 increase in 10-year maximal PM2.5 levels (OR: 1.65, 95% CI: 1.16-2.35). However, among COVID-19 patients without asthma or COPD, PM2.5 exposure was not associated with higher hospitalizations (OR: 0.84, 95% CI: 0.65-1.09 for average PM2.5 and OR: 0.78, 95% CI: 0.65-0.95 for maximal PM2.5).ConclusionsLong-term exposure to PM2.5 is associated with higher odds of hospitalization in COVID-19 patients with pre-existing asthma or COPD.
| S-EPMC7835077 | biostudies-literature
Project description:BackgroundEvidences have shown that the stroke risk associated with long-term exposure to particulate matter with an aerodynamic diameter of ≤2.5 μm (PM2.5) varies among people in North America, Europe and Asia, but studies in Asia rarely evaluated the association by stroke type. We examined whether long-term exposure to PM2.5 is associated with developing all strokes, ischemic stroke and hemorrhagic stroke.MethodsThe retrospective cohort study consisted of 1,362,284 adults identified from beneficiaries of a universal health insurance program in 2011. We obtained data on air pollutants and meteorological measurements from air quality monitoring stations across Taiwan in 2010-2015. Annual mean levels of all environmental measurements in residing areas were calculated and assigned to cohort members. We used Cox proportional hazards models to estimate hazard ratio (HR) and 95% confidence interval (CI) of developing stroke associated with 1-year mean levels of PM2.5 at baseline in 2010, and yearly mean levels from 2010 to 2015 as the time-varying exposure, adjusting for age, sex, income and urbanization level.ResultsDuring a median follow-up time of 6.0 years, 12,942 persons developed strokes, 9919 (76.6%) were ischemic. The adjusted HRs (95% CIs) per interquartile range increase in baseline 1-year mean PM2.5 were 1.03 (1.00-1.06) for all stroke, 1.06 (1.02-1.09) for ischemic stroke, and 0.95 (0.89-1.10) for hemorrhagic stroke. The concentration-response curves estimated in the models with and without additional adjustments for other environmental measurements showed a positively linear association between baseline 1-year mean PM2.5 and ischemic stroke at concentrations greater than 30 μg/m3, under which no evidence of association was observed. There was an indication of an inverse association between PM2.5 and hemorrhagic stroke, but the association no longer existed after controlling for nitrogen dioxide or ozone. We found similar shape of the concentration-response association in the Cox regression models with time-varying PM2.5 exposures.ConclusionLong-term exposure to PM2.5 might be associated with increased risk of developing ischemic stroke. The association with high PM2.5 concentrations remained significant after adjustment for other environmental factors.
| S-EPMC9017007 | biostudies-literature
Project description:Adverse cardiovascular events have been linked with PM2.5 exposure obtained primarily from air quality monitors, which rarely co-locate with participant residences. Modeled PM2.5 predictions at finer resolution may more accurately predict residential exposure; however few studies have compared results across different exposure assessment methods.We utilized a cohort of 5679 patients who had undergone a cardiac catheterization between 2002-2009 and resided in NC. Exposure to PM2.5 for the year prior to catheterization was estimated using data from air quality monitors (AQS), Community Multiscale Air Quality (CMAQ) fused models at the census tract and 12km spatial resolutions, and satellite-based models at 10km and 1km resolutions. Case status was either a coronary artery disease (CAD) index >23 or a recent myocardial infarction (MI). Logistic regression was used to model odds of having CAD or an MI with each 1-unit (?g/m3) increase in PM2.5, adjusting for sex, race, smoking status, socioeconomic status, and urban/rural status.We found that the elevated odds for CAD>23 and MI were nearly equivalent for all exposure assessment methods. One difference was that data from AQS and the census tract CMAQ showed a rural/urban difference in relative risk, which was not apparent with the satellite or 12km-CMAQ models.Long-term air pollution exposure was associated with coronary artery disease for both modeled and monitored data.
| S-EPMC6100751 | biostudies-literature
Project description:BackgroundPrior studies have investigated the association of PM2.5 exposure with arterial stiffness measured by ankle-brachial index (ABI) and brachial-ankle pulse wave velocity (baPWV), of which conclusions are inconsistent. Moreover, limited evidence is available on the contributory role of PM2.5 exposure on the arterial stiffness index.MethodsWe used the population data from the Beijing Health Management Cohort and conducted a longitudinal analysis. The annual average concentration of PM2.5 for 35 air pollutant monitoring sites in Beijing from 2014 to 2018 was used to estimate individual exposure by different interpolation methods. Multivariate logistic regression and linear regression were conducted to assess the association of annual average PM2.5 concentration with the incidence of higher baPWV, the progression of ABI, and baPWV, respectively.ResultsThe association between PM2.5 exposure and incidence of higher baPWV was not significant (OR = 1.11, 95% CI: 0.82-1.50, P = 0.497). There was - 0.16% (95% CI: - 0.43-0.11%) decrease in ABI annually and 1.04% (95% CI: 0.72-1.37%) increase in baPWV annually with each increment of 10 μg/m3 average PM2.5 concentration.ConclusionsLong-term exposure to PM2.5 was associated with the progression of arterial stiffness in Beijing. This study suggests that improvement of air quality may help to prevent arterial stiffness.
| S-EPMC7789369 | biostudies-literature
Project description:ImportanceThe association between short-term exposure to air pollution and mortality has been widely documented worldwide; however, few studies have applied causal modeling approaches to account for unmeasured confounders that vary across time and space.ObjectiveTo estimate the association between short-term changes in fine particulate matter (PM2.5) and nitrogen dioxide (NO2) concentrations and changes in daily all-cause mortality rates using a causal modeling approach.Design, setting, and participantsThis cross-sectional study used air pollution and mortality data from Jiangsu, China; California; central-southern Italy; and Germany with interactive fixed-effects models to control for both measured and unmeasured spatiotemporal confounders. A total of 8 963 352 deaths in these 4 regions from January 1, 2015, to December 31, 2019, were included in the study. Data were analyzed from June 1, 2021, to October 30, 2023.ExposureDay-to-day changes in county- or municipality-level mean PM2.5 and NO2 concentrations.Main outcomes and measuresDay-to-day changes in county- or municipality-level all-cause mortality rates.ResultsAmong the 8 963 352 deaths in the 4 study regions, a 10-μg/m3 increase in daily PM2.5 concentration was associated with an increase in daily all-cause deaths per 100 000 people of 0.01 (95% CI, 0.001-0.01) in Jiangsu, 0.03 (95% CI, 0.004-0.05) in California, 0.10 (95% CI, 0.07-0.14) in central-southern Italy, and 0.04 (95% CI, 0.02- 0.05) in Germany. The corresponding increases in mortality rates for a 10-μg/m3 increase in NO2 concentration were 0.04 (95% CI, 0.03-0.05) in Jiangsu, 0.03 (95% CI, 0.01-0.04) in California, 0.10 (95% CI, 0.05-0.15) in central-southern Italy, and 0.05 (95% CI, 0.04-0.06) in Germany. Significant effect modifications by age were observed in all regions, by sex in Germany (eg, 0.05 [95% CI, 0.03-0.06] for females in the single-pollutant model of PM2.5), and by urbanicity in Jiangsu (0.07 [95% CI, 0.04-0.10] for rural counties in the 2-pollutant model of NO2).Conclusions and relevanceThe findings of this cross-sectional study contribute to the growing body of evidence that increases in short-term exposures to PM2.5 and NO2 may be associated with increases in all-cause mortality rates. The interactive fixed-effects model, which controls for unmeasured spatial and temporal confounders, including unmeasured time-varying confounders in different spatial units, can be used to estimate associations between changes in short-term exposure to air pollution and changes in health outcomes.
| S-EPMC10907920 | biostudies-literature