Mortality Risk and Fine Particulate Air Pollution in a Large, Representative Cohort of U.S. Adults

Abstract

Background: Evidence indicates that air pollution contributes to cardiopulmonary mortality. There is ongoing debate regarding the size and shape of the pollution–mortality exposure–response relationship. There are also growing appeals for estimates of pollution–mortality relationships that use public data and are based on large, representative study cohorts.

Objectives: Our goal was to evaluate fine particulate matter air pollution ([Formula: see text]) and mortality using a large cohort that is representative of the U.S. population and is based on public data. Additional objectives included exploring model sensitivity, evaluating relative effects across selected subgroups, and assessing the shape of the [Formula: see text]–mortality relationship.

Methods: National Health Interview Surveys (1986–2014), with mortality linkage through 2015, were used to create a cohort of 1,599,329 U.S. adults and a subcohort with information on smoking and body mass index (BMI) of 635,539 adults. Data were linked with modeled ambient [Formula: see text] at the census-tract level. Cox proportional hazards models were used to estimate [Formula: see text]–mortality hazard ratios for all-cause and specific causes of death while controlling for individual risk factors and regional and urban versus rural differences. Sensitivity and subgroup analyses were conducted and the shape of the [Formula: see text]–mortality relationship was explored.

Results: Estimated mortality hazard ratios, per [Formula: see text] long-term exposure to [Formula: see text], were 1.12 (95% CI: 1.08, 1.15) for all-cause mortality, 1.23 (95% CI: 1.17, 1.29) for cardiopulmonary mortality, and 1.12 (95% CI: 1.00, 1.26) for lung cancer mortality. In general, [Formula: see text]–mortality associations were consistently positive for all-cause and cardiopulmonary mortality across key modeling choices and across subgroups of sex, age, race-ethnicity, income, education levels, and geographic regions.

Discussion: This large, nationwide, representative cohort of U.S. adults provides robust evidence that long-term [Formula: see text] exposure contributes to cardiopulmonary mortality risk. The ubiquitous and involuntary nature of exposures and the broadly observed effects across subpopulations underscore the public health importance of breathing clean air. https://doi.org/10.1289/EHP4438.

Figure 1.

Average concentrations of ${\mathrm{PM}}_{2.5}$ pollution (${\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$) by 2010 U.S. Census tracts in the continental United States, 1999–2015. ${\mathrm{PM}}_{2.5}$, particulate matter $<2.5\mathrm{\mu }\mathrm{m}$ in aerodynamic diameter.

Figure 2.

Illustration of model sensitivity analysis. Hazard ratios (and 95% CIs) associated with $10{\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$ ${\mathrm{PM}}_{2.5}$ estimated from various models are presented. Gray and black symbols indicate models that use the full cohort and subcohort, respectively. Diamonds indicate complex CPH models that control for the complex survey design, whereas circles indicate models that use the basic CPH models. Cause-of-death groupings are based on ICD-10 codes. Cardiopulmonary disease includes cardiovascular disease (I00–I09, I11, I13, I20–I51), cerebrovascular disease (I60–I69), chronic lower respiratory disease (J40–J47), and influenza and pneumonia (J09–J18). Lung cancer includes C33–C34. CI, confidence interval; CPH, Cox proportional hazards (regression model); HR, hazard ratio; ${\mathrm{PM}}_{2.5}$, particulate matter $<2.5\mathrm{\mu }\mathrm{m}$ in aerodynamic diameter; ICD-10, International Statistical Classification of Diseases, Injuries, and Causes of Death, Tenth Revision.

Figure 3.

Illustration of stratified analysis for the subcohort. Hazard ratios (and 95% CIs) associated with $10{\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$ ${\mathrm{PM}}_{2.5}$ estimated from the basic CPH model are presented by sex, race-ethnicity, age, smoking status, BMI, income, education, marital status, rural/urban, census regions, and survey years. All stratified estimates are adjusted for remaining covariates. Cause-of-death groupings are based on ICD-10 codes. Cardiopulmonary disease includes cardiovascular disease (I00–I09, I11, I13, I20–I51), cerebrovascular disease (I60–I69), chronic lower respiratory disease (J40–J47), and influenza and pneumonia (J09–J18). Lung cancer includes C33–C34. BMI, body mass index; CI, confidence interval; CPH, Cox proportional hazards (regression model); HR, hazard ratio; ${\mathrm{PM}}_{2.5}$, particulate matter $<2.5\mathrm{\mu }\mathrm{m}$ in aerodynamic diameter; ICD-10, International Statistical Classification of Diseases, Injuries, and Causes of Death, Tenth Revision.

Figure 4.

Estimated concentration–response associations between ${\mathrm{PM}}_{2.5}$ and all-cause (A) and cardiopulmonary (B) mortality using the subcohort and basic CPH model with the flexible modeling approach, adjusting for age, sex, race-ethnicity, income, education, marital status, urban versus rural, census regions, survey year, smoking status, and BMI. The optimal nonlinear models are presented as solid lines with 95% uncertainty bounds (shaded area). Cause-of-death groupings are based on ICD-10 codes. Cardiopulmonary disease includes cardiovascular disease (I00–I09, I11, I13, I20–I51), cerebrovascular disease (I60–I69), chronic lower respiratory disease (J40–J47), and influenza and pneumonia (J09–J18). BMI, body mass index; CI, confidence interval; CPH, Cox proportional hazards (regression model); HR, hazard ratio; ICD-10, International Statistical Classification of Diseases, Injuries, and Causes of Death, Tenth Revision; ${\mathrm{PM}}_{2.5}$, particulate matter $<2.5\mathrm{\mu }\mathrm{m}$ in aerodynamic diameter.