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Mortality risk and PM2.5 air pollution in the USA: An analysis of a national prospective cohort

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Epidemiologic evidence indicates that exposure to fine particulate matter air pollution (PM2.5) contributes to global burden of disease, primarily because of increased risk of cardiovascular morbidity and mortality. This study evaluates associations between long-term PM2.5 exposure and mortality risk in national, representative cohorts of the US adult population, constructed from public-use National Health Interview Survey (NHIS) data. Two cohorts consisting of 392,807 and 162,373 individuals (without and with individual smoking data) were compiled from public-use NHIS survey data (1986–2001) with mortality linkage through 2011. Cohorts included persons who lived in a metropolitan statistical area (MSA) were 18–84 years of age and had individual risk factor information. Modeled PM2.5 exposures were assigned as MSA-level mean ambient concentration for 1999 through 2008. Mortality hazard ratios (HRs) were estimated using Cox proportional hazard regression models, controlling for age, race, sex, income, marital status, education, body mass index, and smoking status. Estimated HRs for all-cause and cardiovascular mortality, associated with a 10-μg/m³ exposure increment of PM2.5 were 1.06 (1.01–1.11) and 1.34 (1.21–1.48), respectively, in models that controlled for various individual risk factors, including smoking. This study provides evidence that elevated risks of mortality, especially cardiovascular disease mortality, are associated with long-term exposure to PM2.5 air pollution in US nationwide adult cohorts constructed from public-use NHIS data.
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Mortality risk and PM
2.5
air pollution in the USA: an analysis of a national
prospective cohort
C. Arden Pope III
1
&Majid Ezzati
2
&John B. Cannon
1
&Ryan T. Allen
1
&Michael Jerrett
3
&Richard T. Burnett
4
Received: 14 March 2017 /Accepted: 30 November 2017 /Published online: 8 December 2017
#Springer Science+Business Media B.V., part of Springer Nature 2017
Abstract
Epidemiologic evidence indicates that exposure to fine particulate matter air pollution (PM
2.5
) contributes to global burden of
disease, primarily because of increased risk of cardiovascular morbidity and mortality. This study evaluates associations between
long-term PM
2.5
exposure and mortality risk in national, representative cohorts of the US adult population, constructed from
public-use National Health Interview Survey (NHIS) data. Two cohorts consisting of 392,807 and 162,373 individuals (without
and with individual smoking data) were compiled from public-use NHIS survey data (19862001) with mortality linkage through
2011. Cohorts included persons who lived in a metropolitan statistical area (MSA) were 1884 years of age and had individual
risk factor information. Modeled PM
2.5
exposures were assigned as MSA-level mean ambient concentration for 1999 through
2008. Mortality hazard ratios (HRs) were estimated using Cox proportional hazard regression models, controlling for age, race,
sex, income, marital status, education, body mass index, and smoking status. Estimated HRs for all-cause and cardiovascular
mortality, associated with a 10-μg/m
3
exposure increment of PM
2.5
were 1.06 (1.011.11) and 1.34 (1.211.48), respectively, in
models that controlled for various individual risk factors, including smoking. This study provides evidence that elevated risks of
mortality, especially cardiovascular disease mortality, are associated with long-term exposure to PM
2.5
air pollution in US
nationwide adult cohorts constructed from public-use NHIS data.
Keywords Air pollution .PM
2.5
.Mortality .Cohort study .Cardiovascular mortality
Introduction
There is growing evidence that long-term exposure to ambient
fine particulate matter air pollution (suspended particles
2.5 μm in aerodynamic diameter, PM
2.5
), even at concentrations
common to US urban areas, contributes to increased risk of
cardiovascular disease (Adar et al. 2013; Brook et al. 2010;
Franklin et al. 2015; Kaufman et al. 2016; Krishnan et al.
2012) and mortality (Hoek et al. 2013; Kioumourtzoglou et al.
2016;Dietal.2017). Recent assessments of health risk factors
that contribute to global burden of disease estimate that expo-
sure to ambient air pollution is the fourth largest contributor to
premature mortality worldwidelargely because of the estimat-
ed contribution of PM
2.5
on cardiovascular disease (GBD 2015
Risk factors collaborators 2016). Given the estimated impact of
PM
2.5
on human health, there is need for additional evidence
from nationally representative cohorts.
Survival analyses of the effects of long-term PM
2.5
air pollu-
tion exposure have provided primary evidence regarding the
impacts of long-term exposure. These studies have been con-
ducted using multiple cohorts from the USA (Dockery et al.
1993; Jerrett et al. 2017; Kioumourtzoglou et al. 2016;
Lepeule et al. 2012; Miller et al. 2007;Popeetal.2002;Puett
et al. 2009,2011;Thurstonetal.2016; Zeger et al. 2008;Di
et al. 2017), Europe (Beelen et al. 2014; Carey et al. 2013;
Cesaroni et al. 2013), and Canada (Crouse et al. 2012,2015).
Electronic supplementary material The online version of this article
(https://doi.org/10.1007/s11869-017-0535-3) contains supplementary
material, which is available to authorized users.
*C. Arden Pope, III
cap3@byu.edu
1
Department of Economics, Brigham Young University, Provo, UT,
USA
2
MRC-PHE Centre for Environment and Health, School of Public
Health, Imperial College London, London, UK
3
Environmental Health Sciences, UCLA Fielding School of Public
Health, University of California Los Angeles, Los Angeles, CA,
USA
4
Environmental Health Directorate, Health Canada, Ottawa, Canada
Air Quality, Atmosphere & Health (2018) 11:245252
https://doi.org/10.1007/s11869-017-0535-3
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
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We extracted relative risk and exposure estimates from 46749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017. Findings In 2017, 34·1 million (95% uncertainty interval [UI] 33·3–35·0) deaths and 1·21 billion (1·14–1·28) DALYs were attributable to GBD risk factors. Globally, 61·0% (59·6–62·4) of deaths and 48·3% (46·3–50·2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10·4 million (9·39–11·5) deaths and 218 million (198–237) DALYs, followed by smoking (7·10 million [6·83–7·37] deaths and 182 million [173–193] DALYs), high fasting plasma glucose (6·53 million [5·23–8·23] deaths and 171 million [144–201] DALYs), high body-mass index (BMI; 4·72 million [2·99–6·70] deaths and 148 million [98·6–202] DALYs), and short gestation for birthweight (1·43 million [1·36–1·51] deaths and 139 million [131–147] DALYs). In total, risk-attributable DALYs declined by 4·9% (3·3–6·5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23·5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18·6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. 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Background Studies have shown that long-term exposure to air pollution increases mortality. However, evidence is limited for air-pollution levels below the most recent National Ambient Air Quality Standards. Previous studies involved predominantly urban populations and did not have the statistical power to estimate the health effects in underrepresented groups. Methods We constructed an open cohort of all Medicare beneficiaries (60,925,443 persons) in the continental United States from the years 2000 through 2012, with 460,310,521 person-years of follow-up. Annual averages of fine particulate matter (particles with a mass median aerodynamic diameter of less than 2.5 μm [PM2.5]) and ozone were estimated according to the ZIP Code of residence for each enrollee with the use of previously validated prediction models. We estimated the risk of death associated with exposure to increases of 10 μg per cubic meter for PM2.5 and 10 parts per billion (ppb) for ozone using a two-pollutant Cox proportional-hazards model that controlled for demographic characteristics, Medicaid eligibility, and area-level covariates. Results Increases of 10 μg per cubic meter in PM2.5 and of 10 ppb in ozone were associated with increases in all-cause mortality of 7.3% (95% confidence interval [CI], 7.1 to 7.5) and 1.1% (95% CI, 1.0 to 1.2), respectively. When the analysis was restricted to person-years with exposure to PM2.5 of less than 12 μg per cubic meter and ozone of less than 50 ppb, the same increases in PM2.5 and ozone were associated with increases in the risk of death of 13.6% (95% CI, 13.1 to 14.1) and 1.0% (95% CI, 0.9 to 1.1), respectively. For PM2.5, the risk of death among men, blacks, and people with Medicaid eligibility was higher than that in the rest of the population. Conclusions In the entire Medicare population, there was significant evidence of adverse effects related to exposure to PM2.5 and ozone at concentrations below current national standards. This effect was most pronounced among self-identified racial minorities and people with low income. (Supported by the Health Effects Institute and others.)
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Background: Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures. Methods: We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography-year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings: Globally, life expectancy from birth increased from 61·7 years (95% uncertainty interval 61·4-61·9) in 1980 to 71·8 years (71·5-72·2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11·3 years (3·7-17·4), to 62·6 years (56·5-70·2). Total deaths increased by 4·1% (2·6-5·6) from 2005 to 2015, rising to 55·8 million (54·9 million to 56·6 million) in 2015, but age-standardised death rates fell by 17·0% (15·8-18·1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14·1% (12·6-16·0) to 39·8 million (39·2 million to 40·5 million) in 2015, whereas age-standardised rates decreased by 13·1% (11·9-14·3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. 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Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death. Interpretation: At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. 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Background: Remote sensing (RS) is increasingly used for exposure assessment in epidemiological and burden of disease studies, including those investigating whether chronic exposure to ambient fine particulate matter (PM2.5) is associated with mortality. Objectives: To compare relative risk estimates of mortality from diseases of the circulatory system for PM2.5 modeled from RS with that for PM2.5 modeled using ground-level information. Methods: We geocoded the baseline residence of 668,629 American Cancer Society Cancer Prevention Study II (CPS-II) cohort participants followed from 1982 to 2004 and assigned PM2.5 levels to all participants using seven different exposure models. Most of the exposure models were averaged for the years 2002-2004, while one RS estimate was for a longer, contemporaneous period. We used Cox proportional hazards regression to estimate relative risks (RR) for the association of PM2.5 with circulatory mortality and ischemic heart disease. Results: Estimates of mortality risk differed among exposure models. The smallest relative risk was observed for the RS estimates that excluded ground-based monitors for circulatory deaths (RR = 1.02 (95% confidence interval (CI): 1.00-1.04 per 10 µg/m(3) increment in PM2.5). The largest relative risk was observed for the land use regression model that included traffic information (RR = 1.14, 95% CI: 1.11-1.17 per 10 µg/m(3) increment in PM2.5). Conclusions: We found significant associations between PM2.5 and mortality in every model; however, relative risks estimated from exposure models using ground-based information were generally larger than those estimated with RS alone.
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Background: Long-term exposure to fine particulate matter less than 2.5 μm in diameter (PM2.5) and traffic-related air pollutant concentrations are associated with cardiovascular risk. The disease process underlying these associations remains uncertain. We aim to assess association between long-term exposure to ambient air pollution and progression of coronary artery calcium and common carotid artery intima-media thickness. Methods: In this prospective 10-year cohort study, we repeatedly measured coronary artery calcium by CT in 6795 participants aged 45-84 years enrolled in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) in six metropolitan areas in the USA. Repeated scans were done for nearly all participants between 2002 and 2005, for a subset of participants between 2005 and 2007, and for half of all participants between 2010 and 2012. Common carotid artery intima-media thickness was measured by ultrasound in all participants at baseline and in 2010-12 for 3459 participants. Residence-specific spatio-temporal pollution concentration models, incorporating community-specific measurements, agency monitoring data, and geographical predictors, estimated concentrations of PM2.5 and nitrogen oxides (NOX) between 1999 and 2012. The primary aim was to examine the association between both progression of coronary artery calcium and mean carotid artery intima-media thickness and long-term exposure to ambient air pollutant concentrations (PM2.5, NOX, and black carbon) between examinations and within the six metropolitan areas, adjusting for baseline age, sex, ethnicity, socioeconomic characteristics, cardiovascular risk factors, site, and CT scanner technology. Findings: In this population, coronary calcium increased on average by 24 Agatston units per year (SD 58), and intima-media thickness by 12 μm per year (10), before adjusting for risk factors or air pollutant exposures. Participant-specific pollutant concentrations averaged over the years 2000-10 ranged from 9.2-22.6 μg PM2.5/m(3) and 7.2-139.2 parts per billion (ppb) NOX. For each 5 μg PM2.5/m(3) increase, coronary calcium progressed by 4.1 Agatston units per year (95% CI 1.4-6.8) and for each 40 ppb NOX coronary calcium progressed by 4.8 Agatston units per year (0.9-8.7). Pollutant exposures were not associated with intima-media thickness change. The estimate for the effect of a 5 μg/m(3) higher long-term exposure to PM2.5 in intima-media thickness was -0.9 μm per year (95% CI -3.0 to 1.3). For 40 ppb higher NOX, the estimate was 0.2 μm per year (-1.9 to 2.4). Interpretation: Increased concentrations of PM2.5 and traffic-related air pollution within metropolitan areas, in ranges commonly encountered worldwide, are associated with progression in coronary calcification, consistent with acceleration of atherosclerosis. This study supports the case for global efforts of pollution reduction in prevention of cardiovascular diseases. Funding: US Environmental Protection Agency and US National Institutes of Health.
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The effectiveness of regulatory actions designed to improve air quality is often assessed by predicting changes in public health resulting from their implementation. Risk of premature mortality from long-term exposure to ambient air pollution is the single most important contributor to such assessments and is estimated from observational studies generally assuming a log-linear, no-threshold association between ambient concentrations and death. There has been only limited assessment of this assumption in part because of a lack of methods to estimate the shape of the exposure-response function in very large study populations. In this paper, we propose a new class of variable coefficient risk functions capable of capturing a variety of potentially non-linear associations which are suitable for health impact assessment. We construct the class by defining transformations of concentration as the product of either a linear or log-linear function of concentration multiplied by a logistic weighting function. These risk functions can be estimated using hazard regression survival models with currently available computer software and can accommodate large population-based cohorts which are increasingly being used for this purpose. We illustrate our modeling approach with two large cohort studies of long-term concentrations of ambient air pollution and mortality: the American Cancer Society Cancer Prevention Study II (CPS II) cohort and the Canadian Census Health and Environment Cohort (CanCHEC). We then estimate the number of deaths attributable to changes in fine particulate matter concentrations over the 2000 to 2010 time period in both Canada and the USA using both linear and non-linear hazard function models. Electronic supplementary material The online version of this article (doi:10.1007/s11869-016-0398-z) contains supplementary material, which is available to authorized users.