Author Correction: Increasing CO2 threatens human nutrition.

An Amendment to this paper has been published and can be accessed via a link at the top of the paper.

The Legacy of Redlining: Increasing Childhood Asthma Disparities Through Neighborhood Poverty.

RATIONALE: Identifying the root causes of racial disparities in childhood asthma is critical for health equity. OBJECTIVES: To determine if the 1930's racist policy of redlining led to present-day disparities in childhood asthma by increasing community-level poverty and decreasing neighborhood socioeconomic position (SEP). METHODS: We categorized census tracts at birth of participants from the Children's Respiratory and Environmental Workgroup birth cohort consortium into A, B, C, or D categories as defined by the Home Owners Loan Corporation (HOLC), with D being the highest perceived risk. Surrogates of present-day neighborhood-level SEP were determined for each tract including the percentage of low-income households, the CDC's social vulnerability index (SVI), and other tract-level variables. We performed causal mediation analysis, which, under the assumption of no unmeasured confounding, estimates the direct and mediated pathways by which redlining may cause asthma disparities through census tract-level mediators adjusting for individual-level covariates. MEASUREMENTS AND MAIN RESULTS: Of 4,849 children, the cumulative incidence of asthma through age 11 was 26.6% and 13.2% resided in census tracts with a HOLC grade of D. In mediation analyses, residing in grade D tracts (aOR = 1.03 [95%CI 1.01,1.05]) was significantly associated with childhood asthma, with 79% of this increased risk mediated by percentage of low-income households; results were similar for SVI and other tract-level variables. CONCLUSIONS: The historical structural racist policy of redlining led to present-day asthma disparities in part through decreased neighborhood SEP. Policies aimed at reversing the effects of structural racism should be considered to create more just, equitable, and healthy communities.

Associations Between Extreme Temperatures and Cardiovascular Cause-Specific Mortality: Results From 27 Countries.

BACKGROUND: Cardiovascular disease is the leading cause of death worldwide. Existing studies on the association between temperatures and cardiovascular deaths have been limited in geographic zones and have generally considered associations with total cardiovascular deaths rather than cause-specific cardiovascular deaths. METHODS: We used unified data collection protocols within the Multi-Country Multi-City Collaborative Network to assemble a database of daily counts of specific cardiovascular causes of death from 567 cities in 27 countries across 5 continents in overlapping periods ranging from 1979 to 2019. City-specific daily ambient temperatures were obtained from weather stations and climate reanalysis models. To investigate cardiovascular mortality associations with extreme hot and cold temperatures, we fit case-crossover models in each city and then used a mixed-effects meta-analytic framework to pool individual city estimates. Extreme temperature percentiles were compared with the minimum mortality temperature in each location. Excess deaths were calculated for a range of extreme temperature days. RESULTS: The analyses included deaths from any cardiovascular cause (32 154 935), ischemic heart disease (11 745 880), stroke (9 351 312), heart failure (3 673 723), and arrhythmia (670 859). At extreme temperature percentiles, heat (99th percentile) and cold (1st percentile) were associated with higher risk of dying from any cardiovascular cause, ischemic heart disease, stroke, and heart failure as compared to the minimum mortality temperature, which is the temperature associated with least mortality. Across a range of extreme temperatures, hot days (above 97.5th percentile) and cold days (below 2.5th percentile) accounted for 2.2 (95% empirical CI [eCI], 2.1-2.3) and 9.1 (95% eCI, 8.9-9.2) excess deaths for every 1000 cardiovascular deaths, respectively. Heart failure was associated with the highest excess deaths proportion from extreme hot and cold days with 2.6 (95% eCI, 2.4-2.8) and 12.8 (95% eCI, 12.2-13.1) for every 1000 heart failure deaths, respectively. CONCLUSIONS: Across a large, multinational sample, exposure to extreme hot and cold temperatures was associated with a greater risk of mortality from multiple common cardiovascular conditions. The intersections between extreme temperatures and cardiovascular health need to be thoroughly characterized in the present day-and especially under a changing climate.

Extreme Temperatures and Stroke Mortality: Evidence From a Multi-Country Analysis.

BACKGROUND: Extreme temperatures contribute significantly to global mortality. While previous studies on temperature and stroke-specific outcomes presented conflicting results, these studies were predominantly limited to single-city or single-country analyses. Their findings are difficult to synthesize due to variations in methodologies and exposure definitions. METHODS: Within the Multi-Country Multi-City Network, we built a new mortality database for ischemic and hemorrhagic stroke. Applying a unified analysis protocol, we conducted a multinational case-crossover study on the relationship between extreme temperatures and stroke. In the first stage, we fitted a conditional quasi-Poisson regression for daily mortality counts with distributed lag nonlinear models for temperature exposure separately for each city. In the second stage, the cumulative risk from each city was pooled using mixed-effect meta-analyses, accounting for clustering of cities with similar features. We compared temperature-stroke associations across country-level gross domestic product per capita. We computed excess deaths in each city that are attributable to the 2.5% hottest and coldest of days based on each city's temperature distribution. RESULTS: We collected data for a total of 3 443 969 ischemic strokes and 2 454 267 hemorrhagic stroke deaths from 522 cities in 25 countries. For every 1000 ischemic stroke deaths, we found that extreme cold and hot days contributed 9.1 (95% empirical CI, 8.6-9.4) and 2.2 (95% empirical CI, 1.9-2.4) excess deaths, respectively. For every 1000 hemorrhagic stroke deaths, extreme cold and hot days contributed 11.2 (95% empirical CI, 10.9-11.4) and 0.7 (95% empirical CI, 0.5-0.8) excess deaths, respectively. We found that countries with low gross domestic product per capita were at higher risk of heat-related hemorrhagic stroke mortality than countries with high gross domestic product per capita (P=0.02). CONCLUSIONS: Both extreme cold and hot temperatures are associated with an increased risk of dying from ischemic and hemorrhagic strokes. As climate change continues to exacerbate these extreme temperatures, interventional strategies are needed to mitigate impacts on stroke mortality, particularly in low-income countries.

Comparing traditional and causal inference methodologies for evaluating impacts of long-term air pollution exposure on hospitalization with Alzheimer's disease and related dementias.

Alzheimer's disease and related dementias (ADRD) present a growing public health burden in the United States. One actionable risk factor for ADRD is air pollution: multiple studies have found associations between air pollution and exacerbation of ADRD. Our study builds on previous studies by applying modern statistical causal inference methodologies-generalized propensity score (GPS) weighting and matching-on a large, longitudinal dataset. We follow 50 million Medicare enrollees to investigate impacts of three air pollutants-fine particular matter (PM${}_{2.5}$), nitrogen dioxide (NO${}_2$), and summer ozone (O${}_3$)-on elderly patients' rate of first hospitalization with ADRD diagnosis. Similar to previous studies using traditional statistical models, our results found increased hospitalization risks due to increased PM${}_{2.5}$ and NO${}_2$ exposure, with less conclusive results for O${}_3$. In particular, our GPS weighting analysis finds IQR increases in PM${}_{2.5}$, NO${}_2$, or O${}_3$ exposure results in hazard ratios of 1.108 (95% CI: 1.097-1.119), 1.058 (1.049-1.067), or 1.045 (1.036-1.054), respectively. GPS matching results are similar for PM${}_{2.5}$ and NO${}_2$ with attenuated effects for O${}_3$. Our results strengthen arguments that long-term PM${}_{2.5}$ and NO${}_2$ exposure increases risk of hospitalization with ADRD diagnosis. Additionally, we highlight strengths and limitations of causal inference methodologies in observational studies with continuous treatments. Keywords: Alzheimer's disease and related dementias, air pollution, Medicare, causal inference, generalized propensity score.

Relative humidity, temperature, and hypertensive disorders of pregnancy: Findings from the Project Viva cohort.

BACKGROUND: Preeclampsia is a multi-system hypertensive disorder of pregnancy that is a leading cause of maternal and fetal morbidity and mortality. Prior studies disagree on the cause and even the presence of seasonal patterns in its incidence. Using unsuitable time windows for seasonal exposures can bias model results, potentially explaining these inconsistencies. OBJECTIVES: We aimed to investigate humidity and temperature as possible causes for seasonal trends in preeclampsia in Project Viva, a prebirth cohort in Boston, Massachusetts, considering only exposure windows that precede disease onset. METHODS: Using the Parameter-elevation Relationships on Independent Slopes Model (PRISM) Climate Dataset, we estimated daily residential temperature and relative humidity (RH) exposures during pregnancy. Our primary multinomial regression adjusted for person-level covariates and season. Secondary analyses included distributed lag models (DLMs) and adjusted for ambient air pollutants including fine particulates (PM2.5). We used Generalized Additive Mixed Models (GAMMs) for systolic blood pressure (SBP) trajectories across hypertensive disorder statuses to confirm exposure timing. RESULTS: While preeclampsia is typically diagnosed late in pregnancy, GAMM-fitted SBP trajectories for preeclamptic and non-preeclamptic women began to diverge at around 20 weeks' gestation, confirming the need to only consider early exposures. In the primary analysis with 1776 women, RH in the early second trimester, weeks 14-20, was associated with significantly higher odds of preeclampsia (OR per IQR increase: 1.81, 95% CI: 1.10, 2.97). The DLM corroborated this window, finding a positive association from weeks 12-20. There were no other significant associations between RH or temperature and preeclampsia or gestational hypertension in any other time period. DISCUSSION: The association between preeclampsia and RH in the early second trimester was robust to model choice, suggesting that RH may contribute to seasonal trends in preeclampsia incidence. Differences between these results and those of prior studies could be attributable to exposure timing differences.

Incidence rates of childhood asthma with recurrent exacerbations in the US Environmental influences on Child Health Outcomes (ECHO) program.

BACKGROUND: Descriptive epidemiological data on incidence rates (IRs) of asthma with recurrent exacerbations (ARE) are sparse. OBJECTIVES: This study hypothesized that IRs for ARE would vary by time, geography, age, and race and ethnicity, irrespective of parental asthma history. METHODS: The investigators leveraged data from 17,246 children born after 1990 enrolled in 59 US with 1 Puerto Rican cohort in the Environmental Influences on Child Health Outcomes (ECHO) consortium to estimate IRs for ARE. RESULTS: The overall crude IR for ARE was 6.07 per 1000 person-years (95% CI: 5.63-6.51) and was highest for children aged 2-4 years, for Hispanic Black and non-Hispanic Black children, and for those with a parental history of asthma. ARE IRs were higher for 2- to 4-year-olds in each race and ethnicity category and for both sexes. Multivariable analysis confirmed higher adjusted ARE IRs (aIRRs) for children born 2000-2009 compared with those born 1990-1999 and 2010-2017, 2-4 versus 10-19 years old (aIRR = 15.36; 95% CI: 12.09-19.52), and for males versus females (aIRR = 1.34; 95% CI 1.16-1.55). Black children (non-Hispanic and Hispanic) had higher rates than non-Hispanic White children (aIRR = 2.51; 95% CI 2.10-2.99; and aIRR = 2.04; 95% CI: 1.22-3.39, respectively). Children born in the Midwest, Northeast and South had higher rates than those born in the West (P < .01 for each comparison). Children with a parental history of asthma had rates nearly 3 times higher than those without such history (aIRR = 2.90; 95% CI: 2.43-3.46). CONCLUSIONS: Factors associated with time, geography, age, race and ethnicity, sex, and parental history appear to influence the inception of ARE among children and adolescents.

Home indoor air quality and cognitive function over one year for people working remotely during COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic triggered an increase in remote work-from-home for office workers. Given that many homes now function as offices despite not being designed to support office work, it is critical to research the impact of indoor air quality (IAQ) in homes on the cognitive performance of people working from home. In this study, we followed 206 office workers across the U.S. over one year under remote or hybrid-remote settings during 2021-2022. Participants placed two real-time, consumer-grade indoor environmental monitors in their home workstation area and bedroom. Using a custom smartphone application geofenced to their residential address, participants responded to surveys and periodic cognitive function tests, including the Stroop color-word interference test, Arithmetic two-digit addition/subtraction test, and Compound Remote Associates Task (cRAT). Exposures assessed included carbon dioxide (CO2) and thermal conditions (indoor heat index: a combination of temperature and relative humidity) averaged over 30 minutes prior to each cognitive test. In fully adjusted longitudinal mixed models (n≤121), we found that indoor thermal conditions at home were associated with cognitive function outcomes non-linearly (p<0.05), with poorer cognitive performance on the Stroop test and poorer creative problem-solving on the cRAT when conditions were either too warm or too cool. Most indoor CO2 levels were <640 ppm, but there was still a slight association between higher CO2 and poorer cognitive performance on Stroop (p=0.09). Our findings highlight the need to enhance home indoor environmental quality for optimal cognitive function during remote work, with benefits for both employees and employers.

Effects of long-term average temperature on cardiovascular disease hospitalizations in an American elderly population.

BACKGROUND: Short-term exposure to high or low temperatures is associated with increased mortality and morbidity. Less is known about effects of long-term exposure to high or low temperatures. Prolonged exposure to high or low temperatures might contribute to pathophysiological mechanisms, thereby influencing the development of diseases. Our aim was to evaluate associations of long-term temperature exposure with cardiovascular disease (CVD) hospitalizations. METHODS: We constructed an open cohort consisting of all fee-for-service Medicare beneficiaries, aged ≥65, living in the contiguous US from 2000 through 2016 (∼61.6 million individuals). We used data from the 4 km Gridded Surface Meteorological dataset to assess the summer (June-August) and winter (December-February) average daily maximum temperature for each year for each zip code. Cox-equivalent Poisson models were used to estimate associations with first CVD hospitalization, after adjustment for potential confounders. We performed stratified analyses to assess potential effect modification by sex, age, race, Medicaid eligibility and relative humidity. RESULTS: Higher summer average and lower winter average temperatures were associated with an increased risk of CVD hospitalization. We found a HR of 1.068 (95% CI: 1.063, 1.074) per IQR increase (5.2 °C) for summer average temperature and a HR of 1.022 (95% CI: 1.017, 1.028) per IQR decrease (11.7 °C) for winter average temperature. Positive associations of higher summer average temperatures were strongest for individuals aged <75 years, Medicaid eligible, and White individuals. Positive associations of lower winter average temperatures were strongest for individuals aged <75 years and Black individuals, and individuals living in low relative humidity areas. CONCLUSIONS: Living in areas with high summer average temperatures or low winter average temperatures could increase the risk of CVD hospitalizations. The magnitude of the associations of summer and winter average temperatures differs by demographics and relative humidity levels.

Critical windows of susceptibility for the effects of prenatal exposure to heat and heat variability on gestational growth.

BACKGROUND: Studies have shown that prenatal heat exposure may impact fetal growth, but few studies have examined the critical windows of susceptibility. As extreme heat events and within season temperature variability is expected to increase in frequency, it is important to understand how this may impact gestational growth. OBJECTIVES: We investigated associations between various measures of weekly prenatal heat exposure (mean and standard deviation (SD) of temperature and heat index (HI), derived using temperature in °C and dew point) and term birthweight or odds of being born small for gestational age (SGA) to identify critical windows of susceptibility. METHODS: We analyzed data from mother-child dyads (n = 4442) in the Boston-based Children's HealthWatch cohort. Birthweights were collected from survey data and electronic health records. Daily temperature and HI values were obtained from 800 m gridded spatial climate datasets aggregated by the PRISM Climate Group. Distributed lag-nonlinear models were used to assess the effect of the four weekly heat metrics on measures of gestational growth (birthweight, SGA, and birthweight z-scores). Analyses were stratified by child sex and maternal homelessness status during pregnancy. RESULTS: HI variability was significantly associated with decreased term birthweight during gestational weeks 10-29 and with SGA for weeks 9-26. Cumulative effects for these time periods were -287.4 g (95% CI: -474.1 g, -100.8 g for birthweight and 4.7 (95% CI: 1.6, 14.1) for SGA. Temperature variability was also significantly associated with decreased birthweight between weeks 15 and 26. The effects for mean heat measures on term birthweight and SGA were not significant for any gestational week. Stratification by sex revealed a significant effect on term birthweight in females between weeks 23-28 and in males between weeks 9-26. Strongest effects of HI variability on term birthweight were found in children of mothers who experienced homelessness during pregnancy. Weekly HI variability was the heat metric most strongly associated with measures of gestational growth. The effects observed were largest in males and those who experienced homelessness during pregnancy. DISCUSSION: Given the impact of heat variability on birthweight and risk of SGA, it is important for future heat warnings to incorporate measure of heat index and temperature variability.

Air Pollutants and Asthma Hospitalization in the Medicaid Population.

Rationale: Risk of asthma hospitalization and its disparities associated with air pollutant exposures are less clear within socioeconomically disadvantaged populations, particularly at low degrees of exposure. Objectives: To assess effects of short-term exposures to fine particulate matter (particulate matter with an aerodynamic diameter of ⩽2.5 µm [PM2.5]), warm-season ozone (O3), and nitrogen dioxide (NO2) on risk of asthma hospitalization among national Medicaid beneficiaries, the most disadvantaged population in the United States, and to test whether any subpopulations were at higher risk. Methods: We constructed a time-stratified case-crossover dataset among 1,627,002 hospitalizations during 2000-2012 and estimated risk of asthma hospitalization associated with short-term PM2.5, O3, and NO2 exposures. We then restricted the analysis to hospitalizations with degrees of exposure below increasingly stringent thresholds. Furthermore, we tested effect modifications by individual- and community-level characteristics. Measurements and Main Results: Each 1-µg/m3 increase in PM2.5, 1-ppb increase in O3, and 1-ppb increase in NO2 was associated with 0.31% (95% confidence interval [CI], 0.24-0.37%), 0.10% (95% CI, 0.05 - 0.15%), and 0.28% (95% CI, 0.24 - 0.32%) increase in risk of asthma hospitalization, respectively. Low-level PM2.5 and NO2 exposures were associated with higher risk. Furthermore, beneficiaries with only one asthma hospitalization during the study period or in communities with lower population density, higher average body mass index, longer distance to the nearest hospital, or greater neighborhood deprivation experienced higher risk. Conclusions: Short-term air pollutant exposures increased risk of asthma hospitalization among Medicaid beneficiaries, even at concentrations well below national standards. The subgroup differences suggested individual and contextual factors contributed to asthma disparities under effects of air pollutant exposures.

Coarse Particulate Air Pollution and Daily Mortality: A Global Study in 205 Cities.

Rationale: The associations between ambient coarse particulate matter (PM2.5-10) and daily mortality are not fully understood on a global scale. Objectives: To evaluate the short-term associations between PM2.5-10 and total, cardiovascular, and respiratory mortality across multiple countries/regions worldwide. Methods: We collected daily mortality (total, cardiovascular, and respiratory) and air pollution data from 205 cities in 20 countries/regions. Concentrations of PM2.5-10 were computed as the difference between inhalable and fine PM. A two-stage time-series analytic approach was applied, with overdispersed generalized linear models and multilevel meta-analysis. We fitted two-pollutant models to test the independent effect of PM2.5-10 from copollutants (fine PM, nitrogen dioxide, sulfur dioxide, ozone, and carbon monoxide). Exposure-response relationship curves were pooled, and regional analyses were conducted. Measurements and Main Results: A 10 µg/m3 increase in PM2.5-10 concentration on lag 0-1 day was associated with increments of 0.51% (95% confidence interval [CI], 0.18%-0.84%), 0.43% (95% CI, 0.15%-0.71%), and 0.41% (95% CI, 0.06%-0.77%) in total, cardiovascular, and respiratory mortality, respectively. The associations varied by country and region. These associations were robust to adjustment by all copollutants in two-pollutant models, especially for PM2.5. The exposure-response curves for total, cardiovascular, and respiratory mortality were positive, with steeper slopes at lower exposure ranges and without discernible thresholds. Conclusions: This study provides novel global evidence on the robust and independent associations between short-term exposure to ambient PM2.5-10 and total, cardiovascular, and respiratory mortality, suggesting the need to establish a unique guideline or regulatory limit for daily concentrations of PM2.5-10.

Ambient Particulate Air Pollution and Daily Mortality in 652 Cities.

BACKGROUND: The systematic evaluation of the results of time-series studies of air pollution is challenged by differences in model specification and publication bias. METHODS: We evaluated the associations of inhalable particulate matter (PM) with an aerodynamic diameter of 10 µm or less (PM10) and fine PM with an aerodynamic diameter of 2.5 µm or less (PM2.5) with daily all-cause, cardiovascular, and respiratory mortality across multiple countries or regions. Daily data on mortality and air pollution were collected from 652 cities in 24 countries or regions. We used overdispersed generalized additive models with random-effects meta-analysis to investigate the associations. Two-pollutant models were fitted to test the robustness of the associations. Concentration-response curves from each city were pooled to allow global estimates to be derived. RESULTS: On average, an increase of 10 µg per cubic meter in the 2-day moving average of PM10 concentration, which represents the average over the current and previous day, was associated with increases of 0.44% (95% confidence interval [CI], 0.39 to 0.50) in daily all-cause mortality, 0.36% (95% CI, 0.30 to 0.43) in daily cardiovascular mortality, and 0.47% (95% CI, 0.35 to 0.58) in daily respiratory mortality. The corresponding increases in daily mortality for the same change in PM2.5 concentration were 0.68% (95% CI, 0.59 to 0.77), 0.55% (95% CI, 0.45 to 0.66), and 0.74% (95% CI, 0.53 to 0.95). These associations remained significant after adjustment for gaseous pollutants. Associations were stronger in locations with lower annual mean PM concentrations and higher annual mean temperatures. The pooled concentration-response curves showed a consistent increase in daily mortality with increasing PM concentration, with steeper slopes at lower PM concentrations. CONCLUSIONS: Our data show independent associations between short-term exposure to PM10 and PM2.5 and daily all-cause, cardiovascular, and respiratory mortality in more than 600 cities across the globe. These data reinforce the evidence of a link between mortality and PM concentration established in regional and local studies. (Funded by the National Natural Science Foundation of China and others.).

Differential Mortality Risks Associated With PM2.5 Components: A Multi-Country, Multi-City Study.

BACKGROUND: The association between fine particulate matter (PM2.5) and mortality widely differs between as well as within countries. Differences in PM2.5 composition can play a role in modifying the effect estimates, but there is little evidence about which components have higher impacts on mortality. METHODS: We applied a 2-stage analysis on data collected from 210 locations in 16 countries. In the first stage, we estimated location-specific relative risks (RR) for mortality associated with daily total PM2.5 through time series regression analysis. We then pooled these estimates in a meta-regression model that included city-specific logratio-transformed proportions of seven PM2.5 components as well as meta-predictors derived from city-specific socio-economic and environmental indicators. RESULTS: We found associations between RR and several PM2.5 components. Increasing the ammonium (NH4+) proportion from 1% to 22%, while keeping a relative average proportion of other components, increased the RR from 1.0063 (95% confidence interval [95% CI] = 1.0030, 1.0097) to 1.0102 (95% CI = 1.0070, 1.0135). Conversely, an increase in nitrate (NO3-) from 1% to 71% resulted in a reduced RR, from 1.0100 (95% CI = 1.0067, 1.0133) to 1.0037 (95% CI = 0.9998, 1.0077). Differences in composition explained a substantial part of the heterogeneity in PM2.5 risk. CONCLUSIONS: These findings contribute to the identification of more hazardous emission sources. Further work is needed to understand the health impacts of PM2.5 components and sources given the overlapping sources and correlations among many components.

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.

A national difference in differences analysis of the effect of PM2.5 on annual death rates.

Many studies have reported that PM2.5 was associated with mortality, but these were criticized for unmeasured confounding, not using causal modeling, and not focusing on changes in exposure and mortality rates. Recent studies have used propensity scores, a causal modeling approach that requires the assumption of no unmeasured confounders. We used differences in differences, a causal modeling approach that focuses on exposure changes, and controls for unmeasured confounders by design to analyze PM2.5 and mortality in the U.S. Medicare population, with 623, 036, 820 person-years of follow-up, and 29, 481, 444 deaths. We expanded the approach by clustering ZIP codes into 32 groups based on racial, behavioral and socioeconomic characteristics, and analyzing each cluster separately. We controlled for multiple time varying confounders within each cluster. A separate analysis examined participants whose exposure was always below 12 µg/m3. We found an increase of 1 µg/m3 in PM2.5 produced an increased risk of dying in that year of 3.85 × 10-4 (95% CI 1.95 × 10-4, 5.76 × 10-4). This corresponds to 14,000 early deaths per year per 1 µg/m3. When restricted to exposures below 12 µg/m3, the increased mortality risk was 4.26 × 10-4 (95% CI 1.43 × 10-4, 7.09 × 10-4). Using a causal modeling approach robust to omitted confounders, we found associations of PM2.5 with increased death rates, including below U.S. and E.U. standards.

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.

Assessing additive effects of air pollutants on mortality rate in Massachusetts.

BACKGROUND: We previously found additive effects of long- and short-term exposures to fine particulate matter (PM2.5), ozone (O3), and nitrogen dioxide (NO2) on all-cause mortality rate using a generalized propensity score (GPS) adjustment approach. The study addressed an important question of how many early deaths were caused by each exposure. However, the study was computationally expensive, did not capture possible interactions and high-order nonlinearities, and omitted potential confounders. METHODS: We proposed two new methods and reconducted the analysis using the same cohort of Medicare beneficiaries in Massachusetts during 2000-2012, which consisted of 1.5 million individuals with 3.8 billion person-days of follow-up. The first method, weighted least squares (WLS), leveraged large volume of data by aggregating person-days, which gave equivalent results to the linear probability model (LPM) method in the previous analysis but significantly reduced computational burden. The second method, m-out-of-n random forests (moonRF), implemented scaling random forests that captured all possible interactions and nonlinearities in the GPS model. To minimize confounding bias, we additionally controlled relative humidity and health care utilizations that were not included previously. Further, we performed low-level analysis by restricting to person-days with exposure levels below increasingly stringent thresholds. RESULTS: We found consistent results between LPM/WLS and moonRF: all exposures were positively associated with mortality rate, even at low levels. For long-term PM2.5 and O3, the effect estimates became larger at lower levels. Long-term exposure to PM2.5 posed the highest risk: 1 µg/m3 increase in long-term PM2.5 was associated with 1053 (95% confidence interval [CI]: 984, 1122; based on LPM/WLS methods) or 1058 (95% CI: 988, 1127; based on moonRF method) early deaths each year among the Medicare population in Massachusetts. CONCLUSIONS: This study provides more rigorous causal evidence between PM2.5, O3, and NO2 exposures and mortality, even at low levels. The largest effect estimate for long-term PM2.5 suggests that reducing PM2.5 could gain the most substantial benefits. The consistency between LPM/WLS and moonRF suggests that there were not many interactions and high-order nonlinearities. In the big data context, the proposed methods will be useful for future scientific work in estimating causality on an additive scale.

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.

Air Pollution and Mortality in the Medicare Population.

BACKGROUND: Studies have shown that long-term exposure to air pollution increases mortality. However, evidence is limited for air-pollution levels below the most recent National Ambient Air Quality Standards. Previous studies involved predominantly urban populations and did not have the statistical power to estimate the health effects in underrepresented groups. METHODS: We constructed an open cohort of all Medicare beneficiaries (60,925,443 persons) in the continental United States from the years 2000 through 2012, with 460,310,521 person-years of follow-up. Annual averages of fine particulate matter (particles with a mass median aerodynamic diameter of less than 2.5 µm [PM2.5]) and ozone were estimated according to the ZIP Code of residence for each enrollee with the use of previously validated prediction models. We estimated the risk of death associated with exposure to increases of 10 µg per cubic meter for PM2.5 and 10 parts per billion (ppb) for ozone using a two-pollutant Cox proportional-hazards model that controlled for demographic characteristics, Medicaid eligibility, and area-level covariates. RESULTS: Increases of 10 µg per cubic meter in PM2.5 and of 10 ppb in ozone were associated with increases in all-cause mortality of 7.3% (95% confidence interval [CI], 7.1 to 7.5) and 1.1% (95% CI, 1.0 to 1.2), respectively. When the analysis was restricted to person-years with exposure to PM2.5 of less than 12 µg per cubic meter and ozone of less than 50 ppb, the same increases in PM2.5 and ozone were associated with increases in the risk of death of 13.6% (95% CI, 13.1 to 14.1) and 1.0% (95% CI, 0.9 to 1.1), respectively. For PM2.5, the risk of death among men, blacks, and people with Medicaid eligibility was higher than that in the rest of the population. CONCLUSIONS: In the entire Medicare population, there was significant evidence of adverse effects related to exposure to PM2.5 and ozone at concentrations below current national standards. This effect was most pronounced among self-identified racial minorities and people with low income. (Supported by the Health Effects Institute and others.).