Cancer mortality risk, fine particulate air pollution, and smoking in a large, representative cohort of US adults.

PURPOSE: Air pollution and smoking are associated with various types of mortality, including cancer. The current study utilizes a publicly accessible, nationally representative cohort to explore relationships between fine particulate matter (PM2.5) exposure, smoking, and cancer mortality. METHODS: National Health Interview Survey and mortality follow-up data were combined to create a study population of 635,539 individuals surveyed from 1987 to 2014. A sub-cohort of 341,665 never-smokers from the full cohort was also created. Individuals were assigned modeled PM2.5 exposure based on average exposure from 1999 to 2015 at residential census tract. Cox Proportional Hazard models were utilized to estimate hazard ratios for cancer-specific mortality controlling for age, sex, race, smoking status, body mass, income, education, marital status, rural versus urban, region, and survey year. RESULTS: The risk of all cancer mortality was adversely associated with PM2.5 (per 10 µg/m3 increase) in the full cohort (hazard ratio [HR] 1.15, 95% confidence interval [CI] 1.08-1.22) and the never-smokers' cohort (HR 1.19, 95% CI 1.06-1.33). PM2.5-morality associations were observed specifically for lung, stomach, colorectal, liver, breast, cervix, and bladder, as well as Hodgkin lymphoma, non-Hodgkin lymphoma, and leukemia. The PM2.5-morality association with lung cancer in never-smokers was statistically significant adjusting for multiple comparisons. Cigarette smoking was statistically associated with mortality for many cancer types. CONCLUSIONS: Exposure to PM2.5 air pollution contributes to lung cancer mortality and may be a risk factor for other cancer types. Cigarette smoking has a larger impact on cancer mortality than PM2.5 , but is associated with similar cancer types.

Air pollution and mortality in a large, representative U.S. cohort: multiple-pollutant analyses, and spatial and temporal decompositions.

BACKGROUND: Cohort studies have documented associations between fine particulate matter air pollution (PM2.5) and mortality risk. However, there remains uncertainty regarding the contribution of co-pollutants and the stability of pollution-mortality associations in models that include multiple air pollutants. Furthermore, it is unclear whether the PM2.5-mortality relationship varies spatially, when exposures are decomposed according to scale of spatial variability, or temporally, when effect estimates are allowed to change between years. METHODS: A cohort of 635,539 individuals was compiled using public National Health Interview Survey (NHIS) data from 1987 to 2014 and linked with mortality follow-up through 2015. Modelled air pollution exposure estimates for PM2.5, other criteria air pollutants, and spatial decompositions (< 1 km, 1-10 km, 10-100 km, > 100 km) of PM2.5 were assigned at the census-tract level. The NHIS samples were also divided into yearly cohorts for temporally-decomposed analyses. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) in regression models that included up to six criteria pollutants; four spatial decompositions of PM2.5; and two- and five-year lagged mean PM2.5 exposures in the temporally-decomposed cohorts. Meta-analytic fixed-effect estimates were calculated using results from temporally-decomposed analyses and compared with time-independent results using 17- and 28-year exposure windows. RESULTS: In multiple-pollutant analyses, PM2.5 demonstrated the most robust pollutant-mortality association. Coarse fraction particulate matter (PM2.5-10) and sulfur dioxide (SO2) were also associated with excess mortality risk. The PM2.5-mortality association was observed across all four spatial scales of PM2.5, with higher but less precisely estimated HRs observed for local (< 1 km) and neighborhood (1-10 km) variations. In temporally-decomposed analyses, the PM2.5-mortality HRs were stable across yearly cohorts. The meta-analytic HR using two-year lagged PM2.5 equaled 1.10 (95% CI 1.07, 1.13) per 10 µg/m3. Comparable results were observed in time-independent analyses using a 17-year (HR 1.13, CI 1.09, 1.16) or 28-year (HR 1.09, CI 1.07, 1.12) exposure window. CONCLUSIONS: Long-term exposures to PM2.5, PM2.5-10, and SO2 were associated with increased risk of all-cause and cardiopulmonary mortality. Each spatial decomposition of PM2.5 was associated with mortality risk, and PM2.5-mortality associations were consistent over time.

Estimating long-term pollution exposure effects through inverse probability weighting methods with Cox proportional hazards models.

BACKGROUND: Fine particulate matter (PM2.5) is associated with negative health outcomes in both the short and long term. However, the cohort studies that have produced many of the estimates of long-term exposure associations may fail to account for selection bias in pollution exposure as well as covariate imbalance in the study population; therefore, causal modeling techniques may be beneficial. METHODS: Twenty-nine years of data from the National Health Interview Survey (NHIS) was compiled and linked to modeled annual average outdoor PM2.5 concentration and restricted-use mortality data. A series of Cox proportional hazards models, adjusted using inverse probability weights, yielded causal risk estimates of long-term exposure to ambient PM2.5 on all-cause and cardiopulmonary mortality. RESULTS: Covariate-adjusted estimated relative risks per 10 µg/m3 increase in PM2.5 exposure were estimated to be 1.117 (1.083, 1.152) for all-cause mortality and 1.232 (1.174, 1.292) for cardiopulmonary mortality. Inverse probability weighted Cox models provide relatively consistent and robust estimates similar to those in the unweighted baseline multivariate Cox model, though they have marginally lower point estimates and higher standard errors. CONCLUSIONS: These results provide evidence that long-term exposure to PM2.5 contributes to increased mortality risk in US adults and that the estimated effects are generally robust to modeling choices. The size and robustness of estimated associations highlight the importance of clean air as a matter of public health. Estimated confounding due to measured covariates appears minimal in the NHIS cohort, and various distributional assumptions have little bearing on the magnitude or standard errors of estimated causal associations.

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

BACKGROUND: Evidence indicates that air pollution contributes to cardiopulmonary mortality. There is ongoing debate regarding the size and shape of the pollution­mortality exposure­response relationship. There are also growing appeals for estimates of pollution­mortality 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 (1986­2014), 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.