The Impact of Long-Term Air Pollution Exposure on Type 1 Diabetes Mellitus-Related Mortality among U.S. Medicare Beneficiaries.

BACKGROUND: Little of the previous literature has investigated associations between air pollution exposure and type 1 diabetes mellitus (T1DM)-related mortality, despite a well-established link between air pollution exposure and other autoimmune diseases. METHODS: In a cohort of 53 million Medicare beneficiaries living across the conterminous United States, we used Cox proportional hazard models to assess the association of long-term PM2.5 and NO2 exposures on T1DM-related mortality from 2000 to 2008. Models included strata for age, sex, race, and ZIP code and controlled for neighborhood socioeconomic status (SES); we additionally investigated associations in two-pollutant models, and whether associations were modified by participant demographics. RESULTS: A 10 µg/m3 increase in 12-month average PM2.5 (HR: 1.183; 95% CI: 1.037-1.349) and a 10 ppb increase in NO2 (HR: 1.248; 95% CI: 1.089-1.431) was associated with an increased risk of T1DM-related mortality in age-, sex-, race-, ZIP code-, and SES-adjusted models. Associations for both pollutants were consistently stronger among Black (PM2.5: HR:1.877, 95% CI: 1.386-2.542; NO2: HR: 1.586, 95% CI: 1.258-2.001) and female (PM2.5: HR:1.297, 95% CI: 1.101-1.529; NO2: HR: 1.390, 95% CI: 1.187-1.627) beneficiaries. CONCLUSIONS: Long-term NO2 and, to a lesser extent, PM2.5 exposure is associated with statistically significant elevations in T1DM-related mortality risk.

Long-term PM2.5 exposure and sepsis mortality in a US medicare cohort.

BACKGROUND: Risk factors contributing to sepsis-related mortality include clinical conditions such as cardiovascular disease, chronic lung disease, and diabetes, all of which have also been shown to be associated with air pollution exposure. However, the impact of chronic exposure to air pollution on sepsis-related mortality has been little studied.  METHODS: In a cohort of 53 million Medicare beneficiaries (228,439 sepsis-related deaths) living across the conterminous United States between 2000 and 2008, we examined the association of long-term PM2.5 exposure and sepsis-related mortality. For each Medicare beneficiary (ages 65-120), we estimated the 12-month moving average PM2.5 concentration for the 12 month before death, for their ZIP code of residence using well validated GIS-based spatio-temporal models. Deaths were categorized as sepsis-related if they have ICD-10 codes for bacterial or other sepsis. We used Cox proportional hazard models to assess the association of long-term PM2.5 exposure on sepsis-related mortality. Models included strata for age, sex, race, and ZIP code and controlled for neighborhood socio-economic status (SES). We also evaluated confounding through adjustment of neighborhood behavioral covariates. RESULTS: A 10 µg/m3 increase in 12-month moving average PM2.5 was associated with a 9.1% increased risk of sepsis mortality (95% CI: 3.6-14.9) in models adjusted for age, sex, race, ZIP code, and SES. HRs for PM2.5 were higher and statistically significant for older (> 75), Black, and urban beneficiaries. In stratified analyses, null associations were found for younger beneficiaries (65-75), beneficiaries who lived in non-urban ZIP codes, and those residing in low-SES urban ZIP codes. CONCLUSIONS: Long-term PM2.5 exposure is associated with elevated risks of sepsis-related mortality.

Long-term nitrogen dioxide exposure and cause-specific mortality in the U.S. Medicare population.

BACKGROUND: Since 1971, the annual National Ambient Air Quality Standard (NAAQS) for nitrogen dioxide (NO2) has remained at 53 ppb, the impact of long-term NO2 exposure on mortality is poorly understood. OBJECTIVES: We examined associations between long-term NO2 exposure (12-month moving average of NO2) below the annual NAAQS and cause-specific mortality among the older adults in the U.S. METHODS: Cox proportional-hazard models were used to estimate Hazard Ratio (HR) for cause-specific mortality associated with long-term NO2 exposures among about 50 million Medicare beneficiaries living within the conterminous U.S. from 2001 to 2008. RESULTS: A 10 ppb increase in NO2 was associated with increased mortality from all-cause (HR: 1.06; 95% CI: 1.05-1.06), cardiovascular (HR: 1.10; 95% CI: 1.10-1.11), respiratory disease (HR: 1.09; 95% CI: 1.08-1.11), and cancer (HR: 1.01; 95% CI: 1.00-1.02) adjusting for age, sex, race, ZIP code as strata ZIP code- and state-level socio-economic status (SES) as covariates, and PM2.5 exposure using a 2-stage approach. NO2 was also associated with elevated mortality from ischemic heart disease, cerebrovascular disease, congestive heart failure, chronic obstructive pulmonary disease, pneumonia, and lung cancer. We found no evidence of a threshold, with positive and significant HRs across the range of NO2 exposures for all causes of death examined. Exposure-response curves were linear for all-cause, supra-linear for cardiovascular-, and sub-linear for respiratory-related mortality. HRs were highest consistently among Black beneficiaries. CONCLUSIONS: Long-term NO2 exposure is associated with elevated risks of death by multiple causes, without evidence of a threshold response. Our findings raise concerns about the sufficiency of the annual NAAQS for NO2.

The impact of Long-Term PM2.5 constituents and their sources on specific causes of death in a US Medicare cohort.

BACKGROUND: Our understanding of the impact of long-term exposures to PM2.5 constituents and sources on mortality is limited. OBJECTIVES: To examine associations between long-term exposures to PM2.5 constituents and sources and cause-specific mortality in US older adults. METHODS: We obtained demographic and mortality data for 15.4 million Medicare beneficiaries living within the conterminous United States (US) between 2000 and 2008. We assessed PM2.5 constituents exposures for each beneficiary and used factor analysis and residual-based methods to characterize PM2.5 sources and mixtures, respectively. In age-, sex-, race- and site- stratified Cox proportional hazard models adjusted for neighborhood socio-economic status (SES), we assessed associations of individual PM2.5 constituents, sources, and mixtures and cause-specific mortality and examined modification of these associations by participant demographics and location of residence. We assessed the robustness of our findings to additional adjustment for behavioral risk factors and to alternate exposure definitions and exposure windows. RESULTS: Hazard ratios (HR) were highest for all causes of death, except COPD, for PM2.5 constituents and the coal combustion-related PM2.5 components, with no evidence of confounding by behavioral covariates. We further found Pb and metal-related PM2.5 components to be significantly associated with increased HR of all causes of death, except COPD and lung cancer mortality, and nitrate (NO3-) and silicon (Si) and associated source-related PM2.5 components (traffic and soil, respectively) to be significantly associated with increased all-cause, CVD, respiratory and all cancer-related mortality HR. Associations for other examined constituents and mortality were inconsistent or largely null. Our analyses of mixtures were generally consistent with these findings. Mortality HRs were greatest for minority, especially Black, low-income urban, younger, and male beneficiaries. DISCUSSION: PM2.5 components related to coal combustion, traffic, and to a lesser extent, soil were strongly associated with mortality from CVD, respiratory disease, and cancer.

Comprehensive US database and model for ethanol blend effects on regulated tailpipe emissions.

Particulate matter (PM), oxides of nitrogen (NOx), carbon monoxide (CO), and total hydrocarbons (THC) in gasoline exhaust affect atmospheric quality, and hence human health. Ethanol produced from corn grain is a renewable resource with favorable anti-knock properties for gasoline blending. Refiners alter petroleum composition to produce a finished blend that meets specifications. Ethanol blending affects emissions from market fuels both directly and indirectly since aromatics are typically removed from the BOB as ethanol is added to reach a constant octane rating. Numerous studies have been conducted to assess the effect of ethanol blending on light duty vehicle emissions. However, few studies have examined market fuel blends directly and small studies yield insufficient information to be generally applicable. If blending of fuels for a study does not yield gasoline that adequately resembles the composition of a market blend, the generalizability of study results may be impacted by nonlinear blending effects. Most vehicle-based fuel effect studies employed fuel formulations that either facilitate examination of several fuel variables or blend ethanol into a baseline gasoline (splash blending). Such study results do not support direct quantification of emissions inventory effects. To examine real world blending implications on regulated emissions [PM, NOx, CO, THC], we compiled a comprehensive database of US emission studies, developed regression models based on fuel and vehicle properties, and used those models to estimate differences in emissions from expected market fuel compositions. We addressed nonlinear responses to ethanol composition by modeling both low (up to 10% ethanol by volume) and mid blends (split models). We used the Federal Test Procedure (FTP) and Unified Cycle (LA92) driving schedule data, with the cold-start eliciting the highest emissions. PM cold-start emissions were lower with higher ethanol content, and more so at higher blend levels but hot-running emissions showed no differences with respect to ethanol level. For all emissions, the effects differed between port fuel injection (PFI) and gasoline direct injection (GDI) powered vehicles and for NOx, CO and THC there were differences between comphrehensive and split models. NOx results varied over blend levels and THC results were scattered for the higher blends. CO emissions were lower with higher ethanol content in nearly all cases for PFI but only the hot-running GDI. Results did not differ between summer regular and premium fuels. To the extent that PFI and GDI models differ, an emissions inventory calculation should treat them separately. There is uncertainty directly associated with the regression process, and with model inputs since study methods vary and compositions are reported differently between laboratories and test methods. Small changes in modeled emissions should be considered in this light.

The impact of long-term PM2.5 exposure on specific causes of death: exposure-response curves and effect modification among 53 million U.S. Medicare beneficiaries.

BACKGROUND: The shape of the exposure-response curve for long-term ambient fine particulate (PM2.5) exposure and cause-specific mortality is poorly understood, especially for rural populations and underrepresented minorities. METHODS: We used hybrid machine learning and Cox proportional hazard models to assess the association of long-term PM2.5 exposures on specific causes of death for 53 million U.S. Medicare beneficiaries (aged ≥65) from 2000 to 2008. Models included strata for age, sex, race, and ZIP code and controlled for neighborhood socio-economic status (SES) in our main analyses, with approximately 4 billion person-months of follow-up, and additionally for warm season average of 1-h daily maximum ozone exposures in a sensitivity analysis. The impact of non-traffic PM2.5 on mortality was examined using two stage models of PM2.5 and nitrogen dioxide (NO2). RESULTS: A 10 µg /m3 increase in 12-month average PM2.5 prior to death was associated with a 5% increase in all-cause mortality, as well as an 8.8, 5.6, and 2.5% increase in all cardiovascular disease (CVD)-, all respiratory-, and all cancer deaths, respectively, in age, gender, race, ZIP code, and SES-adjusted models. PM2.5 exposures, however, were not associated with lung cancer mortality. Results were not sensitive to control for ozone exposures. PM2.5-mortality associations for CVD- and respiratory-related causes were positive and significant for beneficiaries irrespective of their sex, race, age, SES and urbanicity, with no evidence of a lower threshold for response or of lower Risk Ratios (RRs) at low PM2.5 levels. Associations between PM2.5 and CVD and respiratory mortality were linear and were higher for younger, Black and urban beneficiaries, but were largely similar by SES. Risks associated with non-traffic PM2.5 were lower than that for all PM2.5 and were null for respiratory and lung cancer-related deaths. CONCLUSIONS: PM2.5 was associated with mortality from CVD, respiratory, and all cancer, but not lung cancer. PM2.5-associated risks of CVD and respiratory mortality were similar across PM2.5 levels, with no evidence of a threshold. Blacks, urban, and younger beneficiaries were most vulnerable to the long-term impacts of PM2.5 on mortality.

Long-term ozone exposures and cause-specific mortality in a US Medicare cohort.

We examined the association of long-term, daily 1-h maximum O3 (ozone) exposures on cause-specific mortality for 22.2 million US Medicare beneficiaries between 2000-2008. We modeled the association between O3 and mortality using age-gender-race stratified log-linear regression models, adjusted for state of residence. We examined confounding by (1) adjusting for PM2.5 (particles with aerodynamic diameters <2.5 µm) and NO2 (nitrogen dioxide) exposures, temperature, and neighborhood-level characteristics and behaviors, and (2) decomposing O3 into its temporal and spatio-temporal components and comparing estimated risk ratios. We also examined sensitivity of our results to alternate exposure measures based on warm-season 8-h daily maximum and 24-h average exposures. We found increased risks from long-term O3 exposures to be strongest and most consistent for mortality from respiratory disease (1.030, 95% CI: 1.027, 1.034) (including COPD (chronic obstructive pulmonary disease)), CHF (congestive heart failure), and lung cancer (1.015, 95% CI: 1.010, 1.020), with no evidence of confounding by PM2.5, NO2, and temperature and with results similar across O3 exposure measures. While significant, associations between long-term O3 exposures and CVD (cardiovascular)-related mortality (1.005, 95% CI: 1.003, 1.007) were confounded by PM2.5 and varied with the exposure measure, with associations no longer significantly positive when warm-season 8-h maximum or 24-h average O3 was used to assess exposures. In this large study, we provide strong evidence that O3 exposure is associated with mortality from respiratory-related causes and for the first-time, lung cancer, but raise questions regarding O3-related impacts on CVD mortality. Our findings demonstrate the need to further identify potential confounders.

Long-term NO2 exposures and cause-specific mortality in American older adults.

BACKGROUND: The impact of long-term exposure to nitrogen dioxide (NO2) on cause-specific mortality is poorly understood. OBJECTIVE: To assess mortality risks associated with long-term NO2 exposure and evaluate confounding of this association. METHODS: We examined the association between 12-month moving average NO2 exposure and cause-specific mortality in 14.1 million US Medicare beneficiaries between 2000 and 2008. Associations were examined using age, gender, and race-stratified and state-adjusted Poisson regression models. We assessed the potential for confounding by PM2.5 and behavioral covariates and unmeasured confounding by decomposing NO2 into its spatial and spatio-temporal components. RESULTS: We found significant associations between 12-month NO2 exposure and increased mortality from all-causes [risk ratio (RR): 1.052; 95% CI: 1.051, 1.054; per 10 ppb], cardiovascular (CVD) (1.133; 95% CI: 1.130, 1.137) and respiratory disease (1.050; 95% CI: 1.044, 1.056), all cancers (1.021; 95% CI: 1.017, 1.025), ischemic heart disease (IHD) (1.221; 95% CI: 1.217, 1.226), cerebrovascular (CBV) disease (1.092; 95% CI: 1.085, 1.100), and for the first time pneumonia (1.275; 95% CI: 1.263, 1.287). Associations generally remained positive and statistically significant after adjustment for PM2.5 and behavioral factors. CONCLUSIONS: Our findings provide additional evidence of the increased risk posed by long-term NO2 exposures on increased mortality from all-causes, CVD, respiratory disease, IHD, CBV, and cancer and provide new evidence of their impact on mortality from pneumonia. Unmeasured confounding of these associations was present, however, demonstrating the need to understand sources of this confounding.

Long-Term PM2.5 Exposure and Respiratory, Cancer, and Cardiovascular Mortality in Older US Adults.

The impact of chronic exposure to fine particulate matter (particulate matter with an aerodynamic diameter less than or equal to 2.5 µm (PM2.5)) on respiratory disease and lung cancer mortality is poorly understood. In a cohort of 18.9 million Medicare beneficiaries (4.2 million deaths) living across the conterminous United States between 2000 and 2008, we examined the association between chronic PM2.5 exposure and cause-specific mortality. We evaluated confounding through adjustment for neighborhood behavioral covariates and decomposition of PM2.5 into 2 spatiotemporal scales. We found significantly positive associations of 12-month moving average PM2.5 exposures (per 10-µg/m3 increase) with respiratory, chronic obstructive pulmonary disease, and pneumonia mortality, with risk ratios ranging from 1.10 to 1.24. We also found significant PM2.5-associated elevated risks for cardiovascular and lung cancer mortality. Risk ratios generally increased with longer moving averages; for example, an elevation in 60-month moving average PM2.5 exposures was linked to 1.33 times the lung cancer mortality risk (95% confidence interval: 1.24, 1.40), as compared with 1.13 (95% confidence interval: 1.11, 1.15) for 12-month moving average exposures. Observed associations were robust in multivariable models, although evidence of unmeasured confounding remained. In this large cohort of US elderly, we provide important new evidence that long-term PM2.5 exposure is significantly related to increased mortality from respiratory disease, lung cancer, and cardiovascular disease.