Long-term air pollution exposure and diabetes risk in American older adults: A national secondary data-based cohort study.

Type 2 diabetes is a major public health concern. Several studies have found an increased diabetes risk associated with long-term air pollution exposure. However, most current studies are limited in their generalizability, exposure assessment, or the ability to differentiate incidence and prevalence cases. We assessed the association between air pollution and first documented diabetes occurrence in a national U.S. cohort of older adults to estimate diabetes risk. We included all Medicare enrollees 65 years and older in the fee-for-service program, part A and part B, in the contiguous United States (2000-2016). Participants were followed annually until the first recorded diabetes diagnosis, end of enrollment, or death (264, 869, 458 person-years). We obtained annual estimates of fine particulate matter (PM2.5), nitrogen dioxide (NO2), and warm-months ozone (O3) exposures from highly spatiotemporally resolved prediction models. We assessed the simultaneous effects of the pollutants on diabetes risk using survival analyses. We repeated the models in cohorts restricted to ZIP codes with air pollution levels not exceeding the national ambient air quality standards (NAAQS) during the study period. We identified 10, 024, 879 diabetes cases of 41, 780, 637 people (3.8% of person-years). The hazard ratio (HR) for first diabetes occurrence was 1.074 (95% CI 1.058; 1.089) for 5 µg/m3 increase in PM2.5, 1.055 (95% CI 1.050; 1.060) for 5 ppb increase in NO2, and 0.999 (95% CI 0.993; 1.004) for 5 ppb increase in O3. Both for NO2 and PM2.5 there was evidence of non-linear exposure-response curves with stronger associations at lower levels (NO2 ≤ 36 ppb, PM2.5 ≤ 8.2 µg/m3). Furthermore, associations remained in the restricted low-level cohorts. The O3-diabetes exposure-response relationship differed greatly between models and require further investigation. In conclusion, exposures to PM2.5 and NO2 are associated with increased diabetes risk, even when restricting the exposure to levels below the NAAQS set by the U.S. EPA.

Associations between long-term air pollution exposure and the incidence of cardiovascular diseases among American older adults.

BACKGROUND & AIM: Numerous studies have linked air pollution with cardiovascular diseases. Fewer studies examined the associations at low concentration levels or assessed potential modifiers. Some investigations only examined hospitalizations, which can miss incident cases. This study aims to address these gaps through a nationwide cohort study of Medicare enrollees. METHODS: Our study cohort comprise all Medicare enrollees (≥65 years old) continuously enrolled in the fee-for-service program and both Medicare part A and B across the contiguous U.S. from 2000 to 2016. We examined the associations of population-weighted ZIP code-level annual average PM2.5, NO2, and warm-season O3 (May-October), with the first diagnoses of atrial fibrillation (AF), congestive heart failure (CHF), and stroke. We fit multi-pollutant Cox proportional hazards models adjusted for individual demographic characteristics and area-level covariates. We further examined these associations at low pollutant concentration levels and the potential effect modifications by race/ethnicity and comorbidities (diabetes, hypertension, hyperlipidemia). RESULTS: Elevated PM2.5 and NO2 levels were associated with increased incidence of AF, CHF, and stroke. For each 1 µg/m3 increase in annual PM2.5, hazard ratios (HRs) were 1.0059 (95%CI: 1.0054-1.0064), 1.0260 (95%CI: 1.0256-1.0264), and 1.0279 (95%CI: 1.0274-1.0284), respectively. For each1 ppb increase in annual NO2, HRs are 1.0057 (95%CI: 1.0056-1.0059), 1.0112 (95%CI: 1.0110-1.0113), and 1.0095 (95%CI: 1.0093-1.0096), respectively. For warm-season O3, each 1 ppb increase was associated with increased incidence of CHF (HR=1.0035, 95%CI: 1.0033-1.0037) and stroke (HR=1.0026, 95%CI: 1.0023-1.0028). Larger magnitudes of HRs were observed when restricted to pollutants levels lower than NAAQS standards. Generally higher risks were observed for Black people and diabetics. CONCLUSIONS: Long-term exposure to PM2.5, NO2, and warm-season O3 were associated with increased incidence of cardiovascular diseases, even at low pollutant concentration levels. Black people and people with diabetes were found to be vulnerable populations.

The effect of long-term exposure to air pollution and seasonal temperature on hospital admissions with cardiovascular and respiratory disease in the United States: A difference-in-differences analysis.

BACKGROUND: Few studies have simultaneously examined the effect of long-term exposure to air pollution and ambient temperature on the rate of hospital admissions with cardiovascular and respiratory disease using causal inference methods. METHODS: We used a variation of a difference-in-difference (DID) approach to assess the effects of long-term exposure to warm-season temperature, cold-season temperature, NO2, O3, and PM2.5 on the rate of hospital admissions for cardiovascular disease (CVD), myocardial infarction (MI), ischemic stroke, and respiratory diseases from 2001 to 2016 among Medicare beneficiaries who use fee-for-service programs. We computed the rate of admissions by zip code and year. Covariates included demographic and socioeconomic variables which were obtained from the decennial Census, the American Community Survey, the Behavioral Risk Factor Surveillance System, and the Dartmouth Health Atlas. As a secondary analysis, we restricted the analysis to zip code-years that had exposure to low concentrations of our pollutants. RESULTS: PM2.5 was associated with a significant increase in the absolute rate of annual admissions with cardiovascular disease by 47.71 admissions (95 % CI: 41.25-56.05) per 100,000 person-years, myocardial infarction by 7.44 admissions (95 % CI: 5.53-9.63) per 100,000 person-years, and 18.58 respiratory admissions (95 % CI: 12.42-23.72) for each one µg/m3 increase in two-year average levels. O3 significantly increased the rates of all the studied outcomes. NO2 was associated with a decreased rate of admissions with MI by 0.83 admissions (95 % CI: 0.10-1.55) per 100,000 person-years but increased rate of admissions for respiratory disease by 3.16 admissions (95 % CI: 1.34-5.24) per 100,000 person-years. Warmer cold-season temperature was associated with a decreased admissions rate for all outcomes. CONCLUSION: Air pollutants, particularly PM2.5 and O3, increased the rate of hospital admissions with cardiovascular and respiratory disease among the elderly, while higher cold-season temperatures decreased the rate of admissions with these conditions.

Associations of short-term exposure to air pollution and increased ambient temperature with psychiatric hospital admissions in older adults in the USA: a case-crossover study.

BACKGROUND: Little is known about the associations between ambient environmental exposures and the risk of acute episodes of psychiatric disorders. We aimed to estimate the link between short-term exposure to atmospheric pollutants, temperature, and acute psychiatric hospital admissions in adults aged 65 years and older in the USA. METHODS: For this study, we included all people (aged ≥65 years) enrolled in the Medicare programme in the USA who had an emergency or urgent hospital admission for a psychiatric disorder recorded between Jan 31, 2000, and Dec 31, 2016. We applied a case-crossover design to study the associations between short-term exposure to air pollution (fine particulate matter [PM2·5], ozone, and nitrogen dioxide [NO2]), ambient temperature, and the risk of acute hospital admissions for depression, schizophrenia, and bipolar disorder in this population. The percentage change in the risk of hospital admission and annual absolute risk differences were estimated. FINDINGS: For each 5°C increase in short-term exposure to cold season temperature, the relative risk of acute hospital admission increased by 3·66% (95% CI 3·06-4·26) for depression, by 3·03% (2·04-4·02) for schizophrenia, and by 3·52% (2·38-4·68) for bipolar disorder in the US Medicare population. Increased short-term exposure to PM2·5 and NO2 was also associated with a significant increase in the risk of acute hospital admissions for psychiatric disorders. Each 5 µg/m3 increase in PM2·5 was associated with an increase in hospital admission rates of 0·62% (95% CI 0·23-1·02) for depression, 0·77% (0·11-1·44) for schizophrenia, and 1·19% (0·49-1·90) for bipolar disorder; each 5 parts per billion (ppb) increase in NO2, meanwhile, was linked to an increase in hospital admission rates of 0·35% (95% CI 0·03-0·66) for depression and 0·64% (0·20-1·08) for schizophrenia. No such associations were found with warm season temperature. INTERPRETATION: In the US Medicare population, short-term exposure to elevated concentrations of PM2·5 and NO2 and cold season ambient temperature were significantly associated with an increased risk of hospital admissions for psychiatric disorders. Considering the increasing burden of psychiatric disorders in the US population, these findings suggest that intervening on air pollution and ambient temperature levels through stricter environmental regulations or climate mitigation could help ease the psychiatric health-care burden. FUNDING: US National Institute of Environmental Health Sciences, US Environmental Protection Agency, and US National Institute on Aging.

Do temporal trends of associations between short-term exposure to fine particulate matter (PM2.5) and risk of hospitalizations differ by sub-populations and urbanicity-a study of 968 U.S. counties and the Medicare population.

While associations between short-term exposure to fine particulate matter (PM2.5) and risk of hospitalization are well documented and evidence suggests that such associations change over time, it is unclear whether these temporal changes exist in understudied less-urban areas or differ by sub-population. We analyzed daily time-series data of 968 continental U.S. counties for 2000-2016, with cause-specific hospitalization from Medicare claims and population-weighted PM2.5 concentrations originally estimated at 1km × 1 km from a hybrid model. Circulatory and respiratory hospitalizations were categorized based on primary diagnosis codes at discharge. Using modified Bayesian hierarchical modelling, we evaluated the temporal trend in association between PM2.5 and hospitalizations and whether disparities in this trend exist across individual-level characteristics (e.g., sex, age, race, and Medicaid eligibility as a proxy for socio-economic status) and urbanicity. Urbanicity was categorized into three levels by county-specific percentage of urban population based on urban rural delineation from the U.S. Census. In this cohort with understudied less-urban areas without regulatory monitors, we still found positive association between circulatory and respiratory hospitalization and short-term exposure to PM2.5, with higher effect estimates towards the end of study period. Consistent with current literature, we identified significant disparity in associations by race, socioeconomic status and urbanicity. We found that the percentage change in circulatory hospitalization rate per 10 µg/m3 increase in PM2.5 was higher in the 2008-2016 time period compared to the 2000-2007 period by 0.33% (95% posterior credible interval 0.22, 0.44%), 0.52% (0.33, 0.69%), and 0.67% (0.53, 0.83%) for low, medium and high tertiles of urban areas, respectively. We also observed significant differences in temporal trends of associations across socioeconomic status, sex, and age, indicating a possible widening in disparity of PM2.5-related health burden. This study raises the importance of considering environmental justice issues in PM2.5-related health impacts with respect to how associations may change over time.

Health benefits of decreases in on-road transportation emissions in the United States from 2008 to 2017.

Decades of air pollution regulation have yielded enormous benefits in the United States, but vehicle emissions remain a climate and public health issue. Studies have quantified the vehicle-related fine particulate matter (PM2.5)-attributable mortality but lack the combination of proper counterfactual scenarios, latest epidemiological evidence, and detailed spatial resolution; all needed to assess the benefits of recent emission reductions. We use this combination to assess PM2.5-attributable health benefits and also assess the climate benefits of on-road emission reductions between 2008 and 2017. We estimate total benefits of $270 (190 to 480) billion in 2017. Vehicle-related PM2.5-attributable deaths decreased from 27,700 in 2008 to 19,800 in 2017; however, had per-mile emission factors remained at 2008 levels, 48,200 deaths would have occurred in 2017. The 74% increase from 27,700 to 48,200 PM2.5-attributable deaths with the same emission factors is due to lower baseline PM2.5 concentrations (+26%), more vehicle miles and fleet composition changes (+22%), higher baseline mortality (+13%), and interactions among these (+12%). Climate benefits were small (3 to 19% of the total). The percent reductions in emissions and PM2.5-attributable deaths were similar despite an opportunity to achieve disproportionately large health benefits by reducing high-impact emissions of passenger light-duty vehicles in urban areas. Increasingly large vehicles and an aging population, increasing mortality, suggest large health benefits in urban areas require more stringent policies. Local policies can be effective because high-impact primary PM2.5 and NH3 emissions disperse little outside metropolitan areas. Complementary national-level policies for NOx are merited because of its substantial impacts-with little spatial variability-and dispersion across states and metropolitan areas.

Long-term effect of exposure to lower concentrations of air pollution on mortality among US Medicare participants and vulnerable subgroups: a doubly-robust approach.

BACKGROUND: Long-term exposure to air pollution has been linked with an increase in risk of mortality. Whether existing US Environmental Protection Agency standards are sufficient to protect health is unclear. Our study aimed to examine the relationship between exposure to lower concentrations of air pollution and the risk of mortality. METHODS: Our nationwide cohort study investigated the effect of annual average exposure to air pollutants on all-cause mortality among Medicare enrolees from the beginning of 2000 to the end of 2016. Patients entered the cohort in the month of January following enrolment and were followed up until the end of the study period in 2016 or death. We restricted our analyses to participants who had only been exposed to lower concentrations of pollutants over the study period, specifically particulate matter less than 2·5 µg/m3 in diameter (PM2·5) at a concentration of up to 12 µg/m3, nitrogen dioxide (NO2) at a concentration of up to 53 parts per billion (ppb), and summer ozone (O3) at concentrations of up to 50 ppb. We adjusted for two types of covariates, which were individual level and postal code-level variables. We used a doubly-robust additive model to estimate the change in risk. We further looked at effect-measure modification by stratification on the basis of demographic and socioeconomic characteristics. FINDINGS: We found an increased risk of mortality with all three pollutants. Each 1 µg/m3 increase in annual PM2·5 concentrations increased the absolute annual risk of death by 0·073% (95% CI 0·071-0·076). Each 1 ppb increase in annual NO2 concentrations increased the annual risk of death by 0·003% (0·003-0·004), and each 1 ppb increase in summer O3 concentrations increased the annual risk of death by 0·081% (0·080-0·083). This increase translated to approximately 11 540 attributable deaths (95% CI 11 087-11 992) for PM2·5, 1176 attributable deaths (998-1353) for NO2, and 15 115 attributable deaths (14 896-15 333) for O3 per year for each unit increase in pollution concentrations. The effects were higher in certain subgroups, including individuals living in areas of low socioeconomic status. Long-term exposure to permissible concentrations of air pollutants increases the risk of mortality. FUNDING: The US Environmental Protection Agency, National Institute of Environmental Health Services, and Health Effects Institute.

A self-controlled approach to survival analysis, with application to air pollution and mortality.

BACKGROUND: Many studies have reported that long-term air pollution exposure is associated with increased mortality rates. These investigations have been criticized for failure to control for omitted, generally personal, confounders. Study designs that are robust to such confounders can address this issue. METHODS: We used a self-controlled design for survival analysis. We stratified on each person in the Medicare cohort between 2000 and 2015 who died, and examined whether PM2.5, O3 and NO2 exposures predicted in which follow-up period the death occurred. We used conditional logistic regression stratified on person and controlled for nonlinear terms in calendar year and age. By design slowly varying covariates such as smoking history, BMI, diabetes and other pre-existing conditions, usual alcohol consumption, sex, race, socioeconomic status, and green space were controlled by matching each person to themselves. RESULTS: There were 6,452,618 deaths in the study population in the study period. We observed a 5.37% increase in the mortality rate (95% CI 4.67%, 6.08%) for every 5 µg/m3 increase in PM2.5, a 1.98% (95% CI 1.61%, 2.36%) increase for 5 ppb increment in O3, and a 2.10% decrease (95% CI 1.88%, 2.33%) for a 5 ppb increase in NO2. When restricted to persons whose PM2.5 exposure never exceeded 12 µg/m3 in any year between 2000 and 2015, the effect size increased for PM2.5 (12.71% (11.30, 14.15)), and the signs of O3 and NO2 reversed (-0.26% (-0.88, 0.35) for O3 and 1.77% increase (1.40, 2.13) for NO2). Effect sizes were larger for Blacks (e.g. 7.71% (5.46, 10.02) for PM2.5). CONCLUSION: There is strong evidence that the association between annual exposure to PM2.5 and mortality is not confounded by individual or neighborhood covariates, and continues below the standard. The effects of O3 and NO2 are difficult to disentangle.

Temporal changes in associations between high temperature and hospitalizations by greenspace: Analysis in the Medicare population in 40 U.S. northeast counties.

Although research indicates health and well-being benefits of greenspace, little is known regarding how greenspace may influence adaptation to health risks from heat, particularly how these risks change over time. Using daily hospitalization rates of Medicare beneficiaries ≥65 years for 2000-2016 in 40 U.S. Northeastern urban counties, we assessed how temperature-related hospitalizations from cardiovascular causes (CVD) and heat stroke (HS) changed over time. We analyzed effect modification of those temporal changes by Enhanced Vegetation Index (EVI), approximating greenspace. We used a two-stage analysis including a generalized additive model and meta-analysis. Results showed that relative risk (RR) (per 1 °C increase in lag0-3 temperature) for temperature-HS hospitalization was higher in counties with the lowest quartile EVI (RR = 2.7, 95% CI: 2.0, 3.4) compared to counties with the highest quartile EVI (RR = 0.40, 95% CI: 0.14, 1.13) in the early part of the study period (2000-2004). RR of HS decreased to 0.88 (95% CI: 0.31, 2.53) in 2013-2016 in counties with the lowest quartile EVI. RR for HS changed over time in counties in the highest quartile EVI, with RRs of 0.4 (95% CI: -0.7, 1.4) in 2000-2004 and 2.4 (95% CI: 1.6, 3.2) in 2013-2016. Findings suggest that adaptation to heat-health associations vary by greenness. Greenspace may help lower risks from heat but such health risks warrant continuous local efforts such as heat-health plans.

Emulating causal dose-response relations between air pollutants and mortality in the Medicare population.

BACKGROUND: Fine particulate matter (PM2.5), ozone (O3), and nitrogen dioxide (NO2) are major air pollutants that pose considerable threats to human health. However, what has been mostly missing in air pollution epidemiology is causal dose-response (D-R) relations between those exposures and mortality. Such causal D-R relations can provide profound implications in predicting health impact at a target level of air pollution concentration. METHODS: Using national Medicare cohort during 2000-2016, we simultaneously emulated causal D-R relations between chronic exposures to fine particulate matter (PM2.5), ozone (O3), and nitrogen dioxide (NO2) and all-cause mortality. To relax the contentious assumptions of inverse probability weighting for continuous exposures, including distributional form of the exposure and heteroscedasticity, we proposed a decile binning approach which divided each exposure into ten equal-sized groups by deciles, treated the lowest decile group as reference, and estimated the effects for the other groups. Binning continuous exposures also makes the inverse probability weights robust against outliers. RESULTS: Assuming the causal framework was valid, we found that higher levels of PM2.5, O3, and NO2 were causally associated with greater risk of mortality and that PM2.5 posed the greatest risk. For PM2.5, the relative risk (RR) of mortality monotonically increased from the 2nd (RR, 1.022; 95% confidence interval [CI], 1.018-1.025) to the 10th decile group (RR, 1.207; 95% CI, 1.203-1.210); for O3, the RR increased from the 2nd (RR, 1.050; 95% CI, 1.047-1.053) to the 9th decile group (RR, 1.107; 95% CI, 1.104-1.110); for NO2, the DR curve wiggled at low levels and started rising from the 6th (RR, 1.005; 95% CI, 1.002-1.018) till the highest decile group (RR, 1.024; 95% CI, 1.021-1.027). CONCLUSIONS: This study provided more robust evidence of the causal relations between air pollution exposures and mortality. The emulated causal D-R relations provided significant implications for reviewing the national air quality standards, as they inferred the number of potential early deaths prevented if air pollutants were reduced to specific levels; for example, lowering each air pollutant concentration from the 70th to 60th percentiles would prevent 65,935 early deaths per year.

A Direct Estimate of the Impact of PM2.5, NO2, and O3 Exposure on Life Expectancy Using Propensity Scores.

BACKGROUND: Many studies have reported associations of air pollutants and death, but fewer examined multiple pollutants, or used causal methods. We present a method for directly estimating changes in the distribution of age at death using propensity scores. METHODS: We included all participants in Medicare from 2000 to 2016 (637,207,589 person-years of follow-up). We fit separate logistic regressions modeling the probability of death at each year of age from 65 to 98 or older as a function of exposure to particulate matter less tha 2.5 µM in diameter (PM2.5), NO2, and O3, using separate propensity scores for each age. We estimated the propensity score using gradient boosting. We estimated the distribution of life expectancy at three counterfactual exposures for each pollutant. RESULTS: The estimated increase in mean life expectancy had the population been exposed to 7 versus 12 µg/m3 PM2.5 was 0.29 years (95% CI = 0.28, 0.30). The change in life expectancy had the population been exposed to 10 versus 20 ppb of NO2 was -0.01 years (95% CI = -0.015, -0.006). The increase in mean life expectancy had the population been exposed to 35 versus 45 ppb of O3 was 0.15 years (95% CI = 0.14, 0.16). Each of these effects was independent and additive. CONCLUSIONS: We estimated that reducing PM2.5 and O3 concentrations to levels below current standards would increase life expectancy by substantial amounts compared with the recent increase of life expectancy at age 65 of 0.7 years in a decade. Our results are not consistent with the hypothesis that exposure to NO2 decreases life expectancy.

Long-term Exposure to PM2.5 and Mortality for the Older Population: Effect Modification by Residential Greenness.

BACKGROUND: Although many studies demonstrated reduced mortality risk with higher greenness, few studies examined the modifying effect of greenness on air pollution-health associations. We evaluated residential greenness as an effect modifier of the association between long-term exposure to fine particles (PM2.5) and mortality. METHODS: We used data from all Medicare beneficiaries in North Carolina (NC) and Michigan (MI) (2001-2016). We estimated annual PM2.5 averages using ensemble prediction models. We estimated mortality risk per 1 µg/m3 increase using Cox proportional hazards modeling, controlling for demographics, Medicaid eligibility, and area-level covariates. We investigated health disparities by greenness using the Normalized Difference Vegetation Index with measures of urbanicity and socioeconomic status. RESULTS: PM2.5 was positively associated with mortality risk. Hazard ratios (HRs) were 1.12 (95% confidence interval (CI) = 1.12 to 1.13) for NC and 1.01 (95% CI = 1.00 to 1.01) for MI. HRs were higher for rural than urban areas. Within each category of urbanicity, HRs were generally higher in less green areas. For combined disparities, HRs were higher in low greenness or low SES areas, regardless of the other factor. HRs were lowest in high-greenness and high-SES areas for both states. CONCLUSIONS: In our study, those in low SES and high-greenness areas had lower associations between PM2.5 and mortality than those in low SES and low greenness areas. Multiple aspects of disparity factors and their interactions may affect health disparities from air pollution exposures. Findings should be considered in light of uncertainties, such as our use of modeled PM2.5 data, and warrant further investigation.

Long-Term Association of Air Pollution and Hospital Admissions Among Medicare Participants Using a Doubly Robust Additive Model.

BACKGROUND: Studies examining the nonfatal health outcomes of exposure to air pollution have been limited by the number of pollutants studied and focus on short-term exposures. METHODS: We examined the relationship between long-term exposure to fine particulate matter with an aerodynamic diameter <2.5 micrometers (PM2.5), NO2, and tropospheric ozone and hospital admissions for 4 cardiovascular and respiratory outcomes (myocardial infarction, ischemic stroke, atrial fibrillation and flutter, and pneumonia) among the Medicare population of the United States. We used a doubly robust method for our statistical analysis, which relies on both inverse probability weighting and adjustment in the outcome model to account for confounding. The results from this regression are on an additive scale. We further looked at this relationship at lower pollutant concentrations, which are consistent with typical exposure levels in the United States, and among potentially susceptible subgroups. RESULTS: Long-term exposure to fine PM2.5 was associated with an increased risk of all outcomes with the highest effect seen for stroke with a 0.0091% (95% CI, 0.0086-0.0097) increase in the risk of stroke for each 1-µg/m3 increase in annual levels. This translated to 2536 (95% CI, 2383-2691) cases of hospital admissions with ischemic stroke per year, which can be attributed to each 1-unit increase in fine particulate matter levels among the study population. NO2 was associated with an increase in the risk of admission with stroke by 0.00059% (95% CI, 0.00039-0.00075) and atrial fibrillation by 0.00129% (95% CI, 0.00114-0.00148) per ppb and tropospheric ozone was associated with an increase in the risk of admission with pneumonia by 0.00413% (95% CI, 0.00376-0.00447) per parts per billion. At lower concentrations, all pollutants were consistently associated with an increased risk for all our studied outcomes. CONCLUSIONS: Long-term exposure to air pollutants poses a significant risk to cardiovascular and respiratory health among the elderly population in the United States, with the greatest increase in the association per unit of exposure occurring at lower concentrations.

A fast divide-and-conquer sparse Cox regression.

We propose a computationally and statistically efficient divide-and-conquer (DAC) algorithm to fit sparse Cox regression to massive datasets where the sample size $n_0$ is exceedingly large and the covariate dimension $p$ is not small but $n_0\gg p$. The proposed algorithm achieves computational efficiency through a one-step linear approximation followed by a least square approximation to the partial likelihood (PL). These sequences of linearization enable us to maximize the PL with only a small subset and perform penalized estimation via a fast approximation to the PL. The algorithm is applicable for the analysis of both time-independent and time-dependent survival data. Simulations suggest that the proposed DAC algorithm substantially outperforms the full sample-based estimators and the existing DAC algorithm with respect to the computational speed, while it achieves similar statistical efficiency as the full sample-based estimators. The proposed algorithm was applied to extraordinarily large survival datasets for the prediction of heart failure-specific readmission within 30 days among Medicare heart failure patients.

PM2.5 and hospital admissions among Medicare enrollees with chronic debilitating brain disorders.

BACKGROUND: Although long-term exposure to particulate matter<2.5 µm (PM2.5) has been linked to chronic debilitating brain disorders (CDBD), the role of short-term exposure in health care demand, and increased susceptibility for PM2.5-related health conditions, among Medicare enrollees with CDBD has received little attention. We used a causal modeling approach to assess the effect of short-term high PM2.5 exposure on all-cause admissions, and prevalent cause-specific admissions among Medicare enrollees with CDBD (Parkinson's disease-PD, Alzheimer's disease-AD and other dementia). METHODS: We constructed daily zipcode counts of hospital admissions of Medicare beneficiaries older than 65 across the United-States (2000-2014). We obtained daily PM2.5 estimates from a satellite-based model. A propensity score matching approach was applied to match high-pollution (PM2.5 > 17.4 µg/m3) to low-pollution zip code-days with similar background characteristics. Then, we estimated the percent change in admissions attributable to high pollution. We repeated the models restricting the analysis to zipcode-days with PM2.5 below of 35 µg/m3. RESULTS: We observed significant increases in all-cause hospital admissions (2.53% in PD and 2.49% in AD/dementia) attributable to high PM2.5 exposure. The largest observed effect for common causes was for pneumonia and urinary tract infection. All the effects were larger in CDBD compared to the general Medicare population, and similarly strong at levels of exposure considered safe by the EPA. CONCLUSION: We found Medicare beneficiaries with CDBD to be at higher risk of being admitted to the hospital following acute exposure to PM2.5 levels well below the National Ambient Air Quality Standard defined as safe by the EPA.

Prenatal exposure to particulate air pollution and gestational age at delivery in Massachusetts neonates 2001-2015: A perspective of causal modeling and health disparities.

There is a lack of evidence on causal effects of air pollution on gestational age (GA) at delivery. METHODS: Inverse probability weighting (IPW) quantile regression was applied to derive causal marginal population-level GA reduction for GA percentiles associated with increased ambient particulate matter with diameter <2.5 µm (PM2.5) levels at maternal residential address for each trimester and the month preceding delivery using Massachusetts birth registry 2001 to 2015. Stratified analyses were conducted for neonatal sex, maternal age/race/education, and extreme ambient temperature conditions. RESULTS: For neonates at 2.5th, 10th, 25th, 50th, 75th, and 97.5th percentiles of GA at delivery, we estimated an adjusted GA reduction of 4.2 days (95% confidence interval [CI] = 3.4, 5.0), 1.9 days (1.6, 2.1), 1.2 days (1.0, 1.4), 0.82 days (0.72, 0.92), 0.74 days (0.54, 0.94), and 0.54 days (0.15, 0.93) for each 5 µg/m3 increment in third trimester average PM2.5 levels. Final gestational month average exposure yielded a similar effect with greater magnitude. Male neonates and neonates of younger (younger than 35 years) and African American mothers as well as with high/low extreme temperature exposure in third trimester were more affected. Estimates were consistently higher at lower GA percentiles, indicating preterm/early-term births being more affected. Low-exposure analyses yielded similar results, restricting to areas with PM2.5 levels under US ambient annual standard of 12 µg/m3. CONCLUSIONS: Prenatal exposure to PM2.5 in late pregnancy reduced GA at delivery among Massachusetts neonates, especially among preterm/early-term births, male neonates, and neonates of younger and African American mothers. Exposure to extremely high/low temperature amplifies the effect of PM2.5 on GA.

Long-term effects of PM2·5 on neurological disorders in the American Medicare population: a longitudinal cohort study.

BACKGROUND: Accumulating evidence links fine particulate matter (PM2·5) to premature mortality, cardiovascular disease, and respiratory disease. However, less is known about the influence of PM2·5 on neurological disorders. We aimed to investigate the effect of long-term PM2·5 exposure on development of Parkinson's disease or Alzheimer's disease and related dementias. METHODS: We did a longitudinal cohort study in which we constructed a population-based nationwide open cohort including all fee-for-service Medicare beneficiaries (aged ≥65 years) in the contiguous United States (2000-16) with no exclusions. We assigned PM2·5 postal code (ie, ZIP code) concentrations based on mean annual predictions from a high-resolution model. To accommodate our very large dataset, we applied Cox-equivalent Poisson models with parallel computing to estimate hazard ratios (HRs) for first hospital admission for Parkinson's disease or Alzheimer's disease and related dementias, adjusting for potential confounders in the health models. FINDINGS: Between Jan 1, 2000, and Dec 31, 2016, of 63 038 019 individuals who were aged 65 years or older during the study period, we identified 1·0 million cases of Parkinson's disease and 3·4 million cases of Alzheimer's disease and related dementias based on primary and secondary diagnosis billing codes. For each 5 µg/m3 increase in annual PM2·5 concentrations, the HR was 1·13 (95% CI 1·12-1·14) for first hospital admission for Parkinson's disease and 1·13 (1·12-1·14) for first hospital admission for Alzheimer's disease and related dementias. For both outcomes, there was strong evidence of linearity at PM2·5 concentrations less than 16 µg/m3 (95th percentile of the PM2·5 distribution), followed by a plateaued association with increasingly larger confidence bands. INTERPRETATION: We provide evidence that exposure to annual mean PM2·5 in the USA is significantly associated with an increased hazard of first hospital admission with Parkinson's disease and Alzheimer's disease and related dementias. For the ageing American population, improving air quality to reduce PM2·5 concentrations to less than current national standards could yield substantial health benefits by reducing the burden of neurological disorders. FUNDING: The Health Effects Institute, The National Institute of Environmental Health Sciences, The National Institute on Aging, and the HERCULES Center.

Risk of Acute Respiratory Distress Syndrome Among Older Adults Living Near Construction and Manufacturing Sites.

BACKGROUND: Construction and manufacturing sites produce airborne toxins that may affect nearby residents' respiratory health. Living in heavy industrial sites has been linked to respiratory conditions such as asthma and pneumonia. However, limited information is available for risk of acute respiratory distress syndrome (ARDS), a form of acute respiratory failure with high incidence among older adults. METHODS: We conducted a nationwide ecologic study to investigate associations between annual ZIP code-level changes in industrial activity and annual changes in ZIP code-level hospital admission rates for older community residents. Using adjusted generalized linear mixed models, we analyzed data from nearly 30 million yearly Medicare beneficiaries for the years 2006 through 2012. RESULTS: We found on average 92,363 hospital admissions for ARDS per year and 646,542 admissions over the course of 7 years. We found that an increase of 10 construction sites per year was associated with a 0.77% (95% confidence interval [CI] = 0.71, 0.84) increase in annual hospital admission rates for ARDS and an increase of 10 manufacturing industries per year was associated with a 1.21% (95% CI = 1.09, 1.33) increase in annual hospital admission rates for ARDS across all ZIP codes. The estimated effect of chemical product manufacturing industry on ARDS was higher than that of total manufacturing industries. Residing in ZIP codes with a high number of construction or manufacturing sites was associated with increased ARDS hospital admissions. CONCLUSIONS: This nationwide ecologic study of older adults suggests that residence in areas with more construction and manufacturing sites is associated with increased ARDS risk.

Causal Effects of Air Pollution on Mortality Rate in Massachusetts.

Air pollution epidemiology studies have primarily investigated long- and short-term exposures separately, have used multiplicative models, and have been associational studies. Implementing a generalized propensity score adjustment approach with 3.8 billion person-days of follow-up, we simultaneously assessed causal associations of long-term (1-year moving average) and short-term (2-day moving average) exposure to particulate matter with an aerodynamic diameter less than or equal to 2.5 µm (PM2.5), ozone, and nitrogen dioxide with all-cause mortality on an additive scale among Medicare beneficiaries in Massachusetts (2000-2012). We found that long- and short-term PM2.5, ozone, and nitrogen dioxide exposures were all associated with increased mortality risk. Specifically, per 10 million person-days, each 1-µg/m3 increase in long- and short-term PM2.5 exposure was associated with 35.4 (95% confidence interval (CI): 33.4, 37.6) and 3.04 (95% CI: 2.17, 3.94) excess deaths, respectively; each 1-part per billion (ppb) increase in long- and short-term ozone exposure was associated with 2.35 (95% CI: 1.08, 3.61) and 2.41 (95% CI: 1.81, 2.91) excess deaths, respectively; and each 1-ppb increase in long- and short-term nitrogen dioxide exposure was associated with 3.24 (95% CI: 2.75, 3.77) and 5.60 (95% CI: 5.24, 5.98) excess deaths, respectively. Mortality associated with long-term PM2.5 and ozone exposure increased substantially at low levels. The findings suggested that air pollution was causally associated with mortality, even at levels below national standards.

Inverse probability weighted distributed lag effects of short-term exposure to PM2.5 and ozone on CVD hospitalizations in New England Medicare participants - Exploring the causal effects.

BACKGROUND: Although many studies have established significant associations between short-term air pollution and the risk of getting cardiovascular diseases, there is a lack of evidence based on causal distributed lag modeling. METHODS: Inverse probability weighting (ipw) propensity score models along with conditional logistic outcome regression models based on a case-crossover study design were applied to get the causal unconstrained distributed (lag0-lag5) as well as cumulative lag effect of short-term exposure to PM2.5/Ozone on hospital admissions of acute myocardial infarction (AMI), congestive heart failure (CHF) and ischemic stroke (IS) among New England Medicare participants during 2000-2012. Effect modification by gender, race, secondary diagnosis of Chronic Obstructive Pulmonary Diseases (COPD) and Diabetes (DM) was explored. RESULTS: Each 10 µg/m3 increase in lag0-lag5 cumulative PM2.5 exposure was associated with an increase of 4.3% (95% confidence interval: 2.2%, 6.4%, percentage change) in AMI hospital admission rate, an increase of 3.9% (2.4%, 5.5%) in CHF rate and an increase of 2.6% (0.4%, 4.7%) in IS rate. A weakened lagging effect of PM2.5 from lag0 to lag5 could be observed. No cumulative short-term effect of ozone on CVD was found. People with secondary diagnosis of COPD, diabetes, female gender and black race are sensitive population. CONCLUSIONS: Based on our causal distributed lag modeling, we found that short-term exposure to an increased ambient PM2.5 level had the potential to induce higher risk of CVD hospitalization in a causal way. More attention should be paid to population of COPD, diabetes, female gender and black race.