Greenness, air pollution, and mortality risk: A U.S. cohort study of cancer patients and survivors.

BACKGROUND: Several studies suggest that living in areas of high surrounding greenness may be associated with a lower cardiopulmonary mortality risk. However, associations of greenness with specific causes of death in cancer patients and survivors has not been examined and it is unknown whether this relationship is affected by area levels of fine particulate matter air pollution (PM2.5). This study evaluated associations between greenness and PM2.5 on causes of death in a large, U.S.-based cohort of cancer patients and survivors. METHODS: Surveillance, Epidemiology and End Results (SEER) data were used to generate a cohort of 5,529,005 cancer patients and survivors from 2000 to 2016. Census-tract Normalized Difference Vegetation Index (NDVI) during May-October from 2003 to 2016 was population-weighted to act as a county-level greenness measure. County-level PM2.5 exposure was estimated from annual concentrations averaged from 1999 to 2015. Cox Proportional Hazards models were used to estimate the association between greenness, PM2.5, and cause-specific mortality while controlling for age, sex, race, and other individual and county level variables. FINDINGS: An IQR increase in greenness was associated with a decrease in cancer mortality for cancer patients (Hazard ratio of 0.94, 95% CI: 0.93-0.95), but not for cardiopulmonary mortality (0.98, 95% CI: 0.96-1.00). Inversely, an increase in 10 µg/m3 PM2.5 was associated with increased cardiopulmonary mortality (1.24, 95% CI: 1.19-1.29), but not cancer mortality (0.99, 95% CI: 0.97-1.00). Hazard ratios were robust to inclusion of PM2.5 in models with greenness and vice versa. Although exposure estimates were constant over most stratifications, greenness seemed to benefit individuals diagnosed with high survivability cancers (0.92, 95% CI: 0.90-0.95) more than those with low survivability cancers (0.98. 95% CI: 0.96-0.99). INTERPRETATION: Higher levels of greenness are associated with lower cancer mortality in cancer patients. The evidence suggests minimal confounding between greenness and PM2.5 exposures and risk of mortality.

Fine Particulate Matter Air Pollution and Mortality Risk Among US Cancer Patients and Survivors.

Background: Exposure to fine particulate matter (PM2.5) air pollution has been linked to increased risk of mortality, especially cardiopulmonary and lung cancer mortality. It is unknown if cancer patients and survivors are especially vulnerable to PM2.5 air pollution exposure. This study evaluates PM2.5 exposure and risk for cancer and cardiopulmonary mortality in cohorts of US cancer patients and survivors. Methods: A primary cohort of 5 591 168 of cancer patients and a 5-year survivor cohort of 2 318 068 was constructed using Surveillance, Epidemiology, and End Results Program data from 2000 to 2016, linked with county-level estimates of long-term average concentrations of PM2.5. Cox proportional hazards models were used to estimate PM2.5-mortality hazard ratios controlling for age-sex-race combinations and individual and county-level covariables. Results: Of those who died, 26% died of noncancer causes, mostly from cardiopulmonary disease. Minimal PM2.5-mortality associations were observed for all-cause mortality (hazard ratio [HR] = 1.01, 95% confidence interval [CI] = 1.00 to 1.03) per 10 µg/m3 increase in PM2.5. Substantial adverse PM2.5-mortality associations were observed for cardiovascular (HR = 1.32, 95% CI = 1.26 to 1.39), chronic obstructive pulmonary disease (HR = 1.10, 95% CI = 1.01 to 1.20), influenza and pneumonia (HR = 1.55, 95% CI = 1.33 to 1.80), and cardiopulmonary mortality combined (HR = 1.25, 95% CI = 1.21 to 1.30). PM2.5-cardiopulmonary mortality hazard ratio was higher for cancer patients who received chemotherapy or radiation treatments. Conclusions: Air pollution is adversely associated with cardiopulmonary mortality for cancer patients and survivors, especially those who received chemotherapy or radiation treatment. Given ubiquitous and involuntary air pollution exposures and large numbers of cancer patients and survivors, these results are of substantial clinical and public health importance.

Shape of BMI-Mortality Risk Associations: Reverse Causality and Heterogeneity in a Representative Cohort of US Adults.

OBJECTIVE: This study examines BMI-mortality associations and evaluates strategies intended to limit reverse causality. Heterogeneity in BMI-mortality risk associations across subgroups and causes of death is explored. METHODS: A cohort of 654,382 adults from the US National Health Interview Survey was constructed. Associations between unit BMI levels and mortality were estimated using Cox proportional hazards models, including and excluding the first 5 years of follow-up, with and without controls for smoking or preexisting conditions, and including and excluding ever-smokers and individuals with preexisting conditions. Stratified analyses by individual characteristics were performed. RESULTS: Addressing reverse causality led to reduced risk of mortality among those with low BMI levels (<18 kg/m2 ). Excluding ever-smokers and individuals with preexisting conditions further led to increased risk among those with high BMI levels (between 33 kg/m2 and >40 kg/m2 ) and lowered the estimated nadir risk from 27 kg/m2 to 23 kg/m2 . After excluding ever-smokers and individuals with preexisting conditions, limiting the analysis to >5 years of follow-up produced no substantive changes. Heterogeneous results were observed across individual characteristics, particularly age and causes of death. CONCLUSIONS: The exclusion of smokers and individuals with preexisting conditions alters the BMI-mortality risk association and results in a somewhat lower range of BMI with minimum mortality risk.

Fine Particulate Matter Exposure and Cancer Incidence: Analysis of SEER Cancer Registry Data from 1992-2016.

BACKGROUND: Previous research has identified an association between fine particulate matter (PM2.5) air pollution and lung cancer. Most of the evidence for this association, however, is based on research using lung cancer mortality, not incidence. Research that examines potential associations between PM2.5 and incidence of non-lung cancers is limited. OBJECTIVES: The primary purpose of this study was to evaluate the association between the incidence of cancer and exposure to PM2.5 using >8.5 million cases of cancer incidences from U.S. registries. Secondary objectives include evaluating the sensitivity of the associations to model selection, spatial control, and latency period as well as estimating the exposure-response relationship for several cancer types. METHODS: Surveillance, Epidemiology, and End Results (SEER) program data were used to calculate incidence rates for various cancer types in 607 U.S. counties. County-level PM2.5 concentrations were estimated using integrated empirical geographic regression models. Flexible semi-nonparametric regression models were used to estimate associations between PM2.5 and cancer incidence for selected cancers while controlling for important county-level covariates. Primary time-independent models using average incidence rates from 1992-2016 and average PM2.5 from 1988-2015 were estimated. In addition, time-varying models using annual incidence rates from 2002-2011 and lagged moving averages of annual estimates for PM2.5 were also estimated. RESULTS: The incidences of all cancer and lung cancer were consistently associated with PM2.5. The incident rate ratios (IRRs), per 10-µg/m3 increase in PM2.5, for all and lung cancer were 1.09 (95% CI: 1.03, 1.14) and 1.19 (95% CI: 1.09, 1.30), respectively. Less robust associations were observed with oral, rectal, liver, skin, breast, and kidney cancers. DISCUSSION: Exposure to PM2.5 air pollution contributes to lung cancer incidence and is potentially associated with non-lung cancer incidence. https://doi.org/10.1289/EHP7246.

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.