Dose-response association of aerobic and muscle-strengthening physical activity with mortality: a national cohort study of 416 420 US adults.

OBJECTIVES: To investigate the dose-response association of aerobic physical activity (PA) and muscle-strengthening exercise (MSE) with all-cause mortality. METHODS: National Health Interview Survey data (1997-2014) were linked to the National Death Index through 2015, which produced a cohort of 416 420 US adults. Cox proportional-hazard models were used to estimate HRs and 95% CIs for the associations of moderate aerobic PA (MPA), vigorous aerobic PA (VPA) and MSE with mortality risk. Models controlled for age, sex, race-ethnicity, income, education, marital status, survey year, smoking status, body mass index and chronic conditions. RESULTS: Relative to those who engaged in no aerobic PA, substantial mortality risk reduction was associated with 1 hour/week of aerobic PA (HR: 0.85, 95% CI: 0.83 to 0.86) and levelled off at 3 hours/week of aerobic PA (0.73, 0.71 to 0.75). Similar results were observed for men and women and for individuals younger and older than 60 years. MSE conferred additional mortality risk reduction at 1 time/week (0.89, 0.81 to 0.97) and appeared no longer beneficial at 7 times/week (0.99, 0.94 to 1.04). CONCLUSION: The minimum effective dose of aerobic PA for significant mortality risk reduction was 1 hour/week of MPA or VPA, with additional mortality risk reduction observed up to 3 hours/week. For older adults, only small decreases in mortality risk were observed beyond this duration. Completing MSE in combination with aerobic PA conferred additional mortality risk reduction, with a minimum effective dose of 1-2 times/week.

Designing health impact functions to assess marginal changes in outdoor fine particulate matter.

Estimating health benefits from improvements in ambient air quality requires the characterization of the magnitude and shape of the association between marginal changes in exposure and marginal changes in risk, and its uncertainty. Several attempts have been made to do this, each requiring different assumptions. These include the Log-Linear(LL), IntegratedExposure-Response(IER), and GlobalExposureMortalityModel(GEMM). In this paper we develop an improved relative risk model suitable for use in health benefits analysis that incorporates features of existing models while addressing limitations in each model. We model the derivative of the relative risk function within a meta-analytic framework; a quantity directly applicable to benefits analysis, incorporating a Fusion of algebraic functions used in previous models. We assume a constant derivative in concentration over low exposures, like the LL model, a declining derivative over moderate exposures observed in cohort studies, and a derivative declining as the inverse of concentration over high global exposures in a similar manner to the GEMM. The model properties are illustrated with examples of fitting it to data for the six specific causes of death previously examined by the GlobalBurdenofDisease program with ambient fine particulate matter (PM2.5). In a test case analysis assuming a 1% (benefits analysis) or 100% (burden analysis), reduction in country-specific fine particulate matter concentrations, corresponding estimated global attributable deaths using the Fusion model were found to lie between those of the IER and LL models, with the GEMM estimates similar to those based on the LL model.

Cardiopulmonary Mortality and Fine Particulate Air Pollution by Species and Source in a National U.S. Cohort.

The purpose of this study was to estimate cardiopulmonary mortality associations for long-term exposure to PM2.5 species and sources (i.e., components) within the U.S. National Health Interview Survey cohort. Exposures were estimated through a chemical transport model for six species (i.e., elemental carbon (EC), primary organic aerosols (POA), secondary organic aerosols (SOA), sulfate (SO4), ammonium (NH4), nitrate (NO3)) and five sources of PM2.5 (i.e., vehicles, electricity-generating units (EGU), non-EGU industrial sources, biogenic sources (bio), "other" sources). In single-pollutant models, we found positive, significant (p < 0.05) mortality associations for all components, except POA. After adjusting for remaining PM2.5 (total PM2.5 minus component), we found significant mortality associations for EC (hazard ratio (HR) = 1.36; 95% CI [1.12, 1.64]), SOA (HR = 1.11; 95% CI [1.05, 1.17]), and vehicle sources (HR = 1.06; 95% CI [1.03, 1.10]). HRs for EC, SOA, and vehicle sources were significantly larger in comparison to those for remaining PM2.5 (per unit µg/m3). Our findings suggest that cardiopulmonary mortality associations vary by species and source, with evidence that EC, SOA, and vehicle sources are important contributors to the PM2.5 mortality relationship. With further validation, these findings could facilitate targeted pollution regulations that more efficiently reduce air pollution mortality.

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.

Outdoor air pollution and cancer: An overview of the current evidence and public health recommendations.

Outdoor air pollution is a major contributor to the burden of disease worldwide. Most of the global population resides in places where air pollution levels, because of emissions from industry, power generation, transportation, and domestic burning, considerably exceed the World Health Organization's health-based air-quality guidelines. Outdoor air pollution poses an urgent worldwide public health challenge because it is ubiquitous and has numerous serious adverse human health effects, including cancer. Currently, there is substantial evidence from studies of humans and experimental animals as well as mechanistic evidence to support a causal link between outdoor (ambient) air pollution, and especially particulate matter (PM) in outdoor air, with lung cancer incidence and mortality. It is estimated that hundreds of thousands of lung cancer deaths annually worldwide are attributable to PM air pollution. Epidemiological evidence on outdoor air pollution and the risk of other types of cancer, such as bladder cancer or breast cancer, is more limited. Outdoor air pollution may also be associated with poorer cancer survival, although further research is needed. This report presents an overview of outdoor air pollutants, sources, and global levels, as well as a description of epidemiological evidence linking outdoor air pollution with cancer incidence and mortality. Biological mechanisms of air pollution-derived carcinogenesis are also described. This report concludes by summarizing public health/policy recommendations, including multilevel interventions aimed at individual, community, and regional scales. Specific roles for medical and health care communities with regard to prevention and advocacy and recommendations for further research are also described.

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.

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.

Fine particulate air pollution and human mortality: 25+ years of cohort studies.

Much of the key epidemiological evidence that long-term exposure to fine particulate matter air pollution (PM2.5) contributes to increased risk of mortality comes from survival studies of cohorts of individuals. Although the first two of these studies, published in the mid-1990s, were highly controversial, much has changed in the last 25 + years. The objectives of this paper are to succinctly compile and summarize the findings of these cohort studies using meta-analytic tools and to address several of the key controversies. Independent reanalysis and substantial extended analysis of the original cohort studies have been conducted and many additional studies using a wide variety of cohorts, including cohorts constructed from public data and leveraging natural experiments have been published. Meta-analytic estimates of the mean of the distribution of effects from cohort studies that are currently available, provide substantial evidence of adverse air pollution associations with all-cause, cardiopulmonary, and lung cancer mortality.

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.

Particulate matter air pollution and national and county life expectancy loss in the USA: A spatiotemporal analysis.

BACKGROUND: Exposure to fine particulate matter pollution (PM2.5) is hazardous to health. Our aim was to directly estimate the health and longevity impacts of current PM2.5 concentrations and the benefits of reductions from 1999 to 2015, nationally and at county level, for the entire contemporary population of the contiguous United States. METHODS AND FINDINGS: We used vital registration and population data with information on sex, age, cause of death, and county of residence. We used four Bayesian spatiotemporal models, with different adjustments for other determinants of mortality, to directly estimate mortality and life expectancy loss due to current PM2.5 pollution and the benefits of reductions since 1999, nationally and by county. The covariates included in the adjusted models were per capita income; percentage of population whose family income is below the poverty threshold, who are of Black or African American race, who have graduated from high school, who live in urban areas, and who are unemployed; cumulative smoking; and mean temperature and relative humidity. In the main model, which adjusted for these covariates and for unobserved county characteristics through the use of county-specific random intercepts, PM2.5 pollution in excess of the lowest observed concentration (2.8 µg/m3) was responsible for an estimated 15,612 deaths (95% credible interval 13,248-17,945) in females and 14,757 deaths (12,617-16,919) in males. These deaths would lower national life expectancy by an estimated 0.15 years (0.13-0.17) for women and 0.13 years (0.11-0.15) for men. The life expectancy loss due to PM2.5 was largest around Los Angeles and in some southern states such as Arkansas, Oklahoma, and Alabama. At any PM2.5 concentration, life expectancy loss was, on average, larger in counties with lower income and higher poverty rate than in wealthier counties. Reductions in PM2.5 since 1999 have lowered mortality in all but 14 counties where PM2.5 increased slightly. The main limitation of our study, similar to other observational studies, is that it is not guaranteed for the observed associations to be causal. We did not have annual county-level data on other important determinants of mortality, such as healthcare access and quality and diet, but these factors were adjusted for with use of county-specific random intercepts. CONCLUSIONS: According to our estimates, recent reductions in particulate matter pollution in the USA have resulted in public health benefits. Nonetheless, we estimate that current concentrations are associated with mortality impacts and loss of life expectancy, with larger impacts in counties with lower income and higher poverty rate.

Fine Particulate Matter and Respiratory Healthcare Encounters among Survivors of Childhood Cancers.

Some chemotherapies that treat childhood cancers have pulmonary-toxic properties that increase risk for adverse respiratory-health outcomes. PM2.5 causes similar outcomes but its effect among pulmonary compromised cancer survivors is unknown. This case-crossover study identified the PM2.5-associated odds for primary-respiratory hospitalizations and emergency department visits among childhood cancer survivors in Utah. We compared risk among chemotherapy-treated survivors to a cancer-free sample. We calculated 3-day-average PM2.5 by ZIP code and county for event and control days. Conditional logistic regression estimated odds ratios. Models were stratified by cause of admission (infection, respiratory disease, asthma), previous chemotherapy, National Ambient Air Quality Standard (NAAQS), and other variables. Results are presented per 10 µg/m³ of PM2.5. 90% of events occurred at 3-day PM2.5 averages <35.4 µg/m³, the NAAQS 24-h standard. For survivors, PM2.5 was associated with respiratory hospitalizations (OR = 1.84, 95% CI = 1.13⁻3.00) and hospitalizations from respiratory infection (OR = 2.09, 95% CI = 1.06⁻4.14). Among chemotherapy-treated survivors, the PM2.5-associated odds of respiratory hospitalization (OR = 2.03, 95% CI = 1.14⁻3.61) were significantly higher than the cancer-free sample (OR = 0.84, 95% CI = 0.57⁻1.25). This is the first study to report significant associations between PM2.5 and respiratory healthcare encounters in childhood cancer survivors. Chemotherapy-treated survivors displayed the highest odds of hospitalization due to PM2.5 exposure and their risk is significantly higher than a cancer-free sample.

Acute exposure to air pollution is associated with novel changes in blood levels of endothelin-1 and circulating angiogenic cells in young, healthy adults.

Acute and chronic exposures to particulate matter (PM2.5) air pollution increase the risk for cardiovascular disease (CVD). A hypothesized mechanism linking PM2.5 exposure and CVD is the induction of endothelial dysfunction - a key step to increased CVD risk. Although PM2.5 exposure is associated with endothelial dysfunction and the vasoconstrictor peptide endothelin-1 (ET-1) is upregulated in endothelial dysfunction, the effects of PM2.5 on ET-1 and whether or not ET-1 mediates the downstream effects of PM2.5 are unclear. In addition to examining associations between acute changes in ambient PM2.5 and circulating levels of ET-1, we also looked at whether changes in ET-1 were associated with changes in markers of vascular health and systemic injury. For example, endothelial function is maintained in part by circulating angiogenic cell (CAC)-mediated repair, and our recent studies show that CACs in humans and mice are decreased by ambient PM2.5 exposure. In the current study, we recruited young, healthy adults who were exposed to natural variations in PM2.5, and we analyzed associations between PM2.5 and circulating levels of ET-1, between ET-1 and CACs, and between ET-1 and other biomarkers of injury using linear regression analyses. Surprisingly, ET-1 levels were negatively associated with PM2.5 levels (ß = -0.773, P = 0.0005), yet, in contrast, positively associated with two CACs: CAC-2 (CD31+/CD34+/CD45+) and CAC-4 (CD31+/CD34+/CD45+/CD133+). Interestingly, ET-1 levels were negatively associated with some biomarkers (platelet factor 4, ß = -0.148, P = 0.0003; triglycerides, ß = -0.095, P = 0.041) and positively with other biomarkers: albumin (ß = 0.035, P = 0.006) and IL-lß (ß = 0.082, P = 0.012). These findings further reveal the insidious nature of PI2.5's anti-angiogenic effect including a novel relationship between ET-1 and CACs in young adults exposed to acute elevations of air pollution.