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Estimated Changes in Life Expectancy and Adult Mortality Resulting from Declining PM2.5 Exposures in the Contiguous United States: 1980-2010.

ABSTRACT: BACKGROUND:PM2.5 precursor emissions have declined over the course of several decades, following the implementation of local, state, and federal air quality policies. Estimating the corresponding change in population exposure and PM2.5-attributable risk of death prior to the year 2000 is made difficult by the lack of PM2.5 monitoring data. OBJECTIVES:We used a new technique to estimate historical PM2.5 concentrations, and estimated the effects of changes in PM2.5 population exposures on mortality in adults (age ?30y), and on life expectancy at birth, in the contiguous United States during 1980-2010. METHODS:We estimated annual mean county-level PM2.5 concentrations in 1980, 1990, 2000, and 2010 using universal kriging incorporating geographic variables. County-level death rates and national life tables for each year were obtained from the U.S. Census and Centers for Disease Control and Prevention. We used log-linear and nonlinear concentration-response coefficients from previous studies to estimate changes in the numbers of deaths and in life years and life expectancy at birth, attributable to changes in PM2.5. RESULTS:Between 1980 and 2010, population-weighted PM2.5 exposures fell by about half, and the estimated number of excess deaths declined by about a third. The States of California, Virginia, New Jersey, and Georgia had some of the largest estimated reductions in PM2.5-attributable deaths. Relative to a counterfactual population with exposures held constant at 1980 levels, we estimated that people born in 2050 would experience an ?1-y increase in life expectancy at birth, and that there would be a cumulative gain of 4.4 million life years among adults ?30y of age. CONCLUSIONS:Our estimates suggest that declines in PM2.5 exposures between 1980 and 2010 have benefitted public health. https://doi.org/10.1289/EHP507.

SUBMITTER: Fann N

PROVIDER: S-EPMC5903877 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Estimated Changes in Life Expectancy and Adult Mortality Resulting from Declining PM2.5 Exposures in the Contiguous United States: 1980-2010.

Fann Neal N Kim Sun-Young SY Olives Casey C Sheppard Lianne L

Environmental health perspectives 20170906 9

<h4>Background</h4>PM2.5 precursor emissions have declined over the course of several decades, following the implementation of local, state, and federal air quality policies. Estimating the corresponding change in population exposure and PM2.5-attributable risk of death prior to the year 2000 is made difficult by the lack of PM2.5 monitoring data.<h4>Objectives</h4>We used a new technique to estimate historical PM2.5 concentrations, and estimated the effects of changes in PM2.5 population exposu ...[more]

PMID: 28934094

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Project description:Type 1 diabetes has historically been associated with a significant reduction in life expectancy. Major advances in treatment of type 1 diabetes have occurred in the past 3 decades. Contemporary estimates of the effect of type 1 diabetes on life expectancy are needed.To examine current life expectancy in people with and without type 1 diabetes in Scotland. We also examined whether any loss of life expectancy in patients with type 1 diabetes is confined to those who develop kidney disease.Prospective cohort of all individuals alive in Scotland with type 1 diabetes who were aged 20 years or older from 2008 through 2010 and were in a nationwide register (n=24,691 contributing 67,712 person-years and 1043 deaths).Differences in life expectancy between those with and those without type 1 diabetes and the percentage of the difference due to various causes.Life expectancy at an attained age of 20 years was an additional 46.2 years among men with type 1 diabetes and 57.3 years among men without it, an estimated loss in life expectancy with diabetes of 11.1 years (95% CI, 10.1-12.1). Life expectancy from age 20 years was an additional 48.1 years among women with type 1 diabetes and 61.0 years among women without it, an estimated loss with diabetes of 12.9 years (95% CI, 11.7-14.1). Even among those with type 1 diabetes with an estimated glomerular filtration rate of 90 mL/min/1.73 m2 or higher, life expectancy was reduced (49.0 years in men, 53.1 years in women) giving an estimated loss from age 20 years of 8.3 years (95% CI, 6.5-10.1) for men and 7.9 years (95% CI, 5.5-10.3) for women. Overall, the largest percentage of the estimated loss in life expectancy was related to ischemic heart disease (36% in men, 31% in women) but death from diabetic coma or ketoacidosis was associated with the largest percentage of the estimated loss occurring before age 50 years (29.4% in men, 21.7% in women).Estimated life expectancy for patients with type 1 diabetes in Scotland based on data from 2008 through 2010 indicated an estimated loss of life expectancy at age 20 years of approximately 11 years for men and 13 years for women compared with the general population without type 1 diabetes.

Project description:Various approaches have been proposed to model PM2.5 in the recent decade, with satellite-derived aerosol optical depth, land-use variables, chemical transport model predictions, and several meteorological variables as major predictor variables. Our study used an ensemble model that integrated multiple machine learning algorithms and predictor variables to estimate daily PM2.5 at a resolution of 1?km?×?1?km across the contiguous United States. We used a generalized additive model that accounted for geographic difference to combine PM2.5 estimates from neural network, random forest, and gradient boosting. The three machine learning algorithms were based on multiple predictor variables, including satellite data, meteorological variables, land-use variables, elevation, chemical transport model predictions, several reanalysis datasets, and others. The model training results from 2000 to 2015 indicated good model performance with a 10-fold cross-validated R2 of 0.86 for daily PM2.5 predictions. For annual PM2.5 estimates, the cross-validated R2 was 0.89. Our model demonstrated good performance up to 60??g/m3. Using trained PM2.5 model and predictor variables, we predicted daily PM2.5 from 2000 to 2015 at every 1?km?×?1?km grid cell in the contiguous United States. We also used localized land-use variables within 1?km?×?1?km grids to downscale PM2.5 predictions to 100?m?×?100?m grid cells. To characterize uncertainty, we used meteorological variables, land-use variables, and elevation to model the monthly standard deviation of the difference between daily monitored and predicted PM2.5 for every 1?km?×?1?km grid cell. This PM2.5 prediction dataset, including the downscaled and uncertainty predictions, allows epidemiologists to accurately estimate the adverse health effect of PM2.5. Compared with model performance of individual base learners, an ensemble model would achieve a better overall estimation. It is worth exploring other ensemble model formats to synthesize estimations from different models or from different groups to improve overall performance.

Project description:BackgroundThe impact of nitrogen dioxide (NO2) and particulate matter with an aerodynamic diameter of less than or equal to 2.5. microns (PM2.5) exposures on lung function has been investigated mainly in children and less in adults. Furthermore, it is unclear whether short-term deviations of air pollutant concentration need to be considered in long-term exposure models.ObjectivesThe aims of this study were to investigate the association between short-term air pollution exposure and lung function and to assess whether short-term deviations of air pollutant concentration should be integrated into long-term exposure models.MethodsShort-term (daily averages 0-7 d prior) and long-term (1- and 4-y means) NO2 and PM2.5 concentrations were modeled using satellite, land use, and meteorological data calibrated on ground measurements. Forced expiratory volume within the first second (FEV1) of forced exhalation and forced vital capacity (FVC) were measured during a LuftiBus assessment (2003-2012) and linked to exposure information from the Swiss National Cohort for 36,085 adults (ages 18-95 y). We used multiple linear regression to estimate adjusted associations, and additionally adjusted models of long-term exposures for short-term deviations in air pollutant concentrations.ResultsA 10μg/m3 increase in NO2 and PM2.5 on the day of the pulmonary function test was associated with lower FEV1 and FVC (NO2: FEV1 -8.0 ml [95% confidence interval: -13.4, -2.7], FVC -16.7 ml [-23.4, -10.0]; PM2.5: FEV1 -15.3 ml [-21.9, -8.7], FVC -18.5 ml [-26.5, -10.5]). A 10μg/m3 increase in 1-y mean NO2 was also associated with lower FEV1 (-7.7 ml; -15.9, 0.5) and FVC (-21.6 ml; -31.9, -11.4), as was a 10μg/m3 increase in 1-y mean PM2.5 (FEV1: -42.2 ml; -56.9, -27.5; FVC: -82.0 ml; -100.1, -63.9). These associations were robust to adjustment for short-term deviations in the concentration of each air pollutant.ConclusionsShort- and long-term air pollution exposures were negatively associated with lung function, in particular long-term PM2.5 exposure with FVC. Our findings contribute substantially to the evidence of adverse associations between air pollution and lung function in adults. https://doi.org/10.1289/EHP7529.

Project description:BackgroundExceptional aging, defined as reaching age 85 years, shows geographic inequalities that may depend on local environmental conditions. Links between particulate pollution-a well-recognized environmental risk factor-and exceptional aging have not been investigated.ObjectivesWe conducted a nationwide analysis of ~28 million adults in 3,034 United States counties to determine whether local PM2.5 levels (particulate matter < 2.5 μm in aerodynamic diameter) affected the probability of becoming 85- to 94-year-olds or centenarians (100- to 104-year-olds) in 2010 for individuals who were 55-64 or 70-74 years old, respectively, in 1980.MethodsWe used population-weighted regression models including county-level PM2.5 from hybrid land-use regression and geostatistical interpolation, smoking, obesity, sociodemographic, and age-specific migration variables.ResultsOn average, 2,295 and 71.4 per 10,000 of the 55- to 64- and 70- to 74-year-olds in 1980, respectively, remained in the 85- to 94- and 100- to 104-year-old population in 2010. An interquartile range (4.19 μg/m3) increase in PM2.5 was associated with 93.7 fewer 85- to 94-year-olds (p < 0.001) and 3.5 fewer centenarians (p < 0.05). These associations were nearly linear, were stable to model specification, and were detectable below the annual PM2.5 national standard. Exceptional aging was strongly associated with smoking, with an interquartile range (4.77%) increase in population who smoked associated with 181.9 fewer 85- to 94-year-olds (p < 0.001) and 6.4 fewer centenarians (p < 0.001). Exceptional aging was also associated with obesity rates and median income.ConclusionsCommunities with the most exceptional aging have low ambient air pollution and low rates of smoking, poverty, and obesity. Improvements in these determinants may contribute to increasing exceptional aging. Citation: Baccarelli AA, Hales N, Burnett RT, Jerrett M, Mix C, Dockery DW, Pope CA III. 2016. Particulate air pollution, exceptional aging, and rates of centenarians: a nationwide analysis of the United States, 1980-2010. Environ Health Perspect 124:1744-1750; http://dx.doi.org/10.1289/EHP197.

Dataset Information

Estimated Changes in Life Expectancy and Adult Mortality Resulting from Declining PM2.5 Exposures in the Contiguous United States: 1980-2010.

Publications

Estimated Changes in Life Expectancy and Adult Mortality Resulting from Declining PM2.5 Exposures in the Contiguous United States: 1980-2010.

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