A causal machine-learning framework for studying policy impact on air pollution: A case-study in COVID-19 lockdowns.

When studying the impact of policy interventions or natural experiments on air pollution, such as new environmental policies and opening or closing an industrial facility, careful statistical analysis is needed to separate causal changes from other confounding factors. Using COVID-19 lockdowns as a case-study, we present a comprehensive framework for estimating and validating causal changes from such perturbations. We propose using flexible machine learning-based comparative interrupted time series (CITS) models for estimating such a causal effect. We outline the assumptions required to identify causal effects, showing that many common methods rely on strong assumptions that are relaxed by machine learning models. For empirical validation, we also propose a simple diagnostic criterion, guarding against false effects in baseline years when there was no intervention. The framework is applied to study the impact of COVID-19 lockdowns on NO2 in the eastern US. The machine learning approaches guard against false effects better than common methods and suggest decreases in NO2 in Boston, New York City, Baltimore, and Washington D.C. The study showcases the importance of our validation framework in selecting a suitable method and the utility of a machine learning based CITS model for studying causal changes in air pollution time series.

Indoor Air Pollution and Impaired Cardiac Autonomic Function in Chronic Obstructive Pulmonary Disease.

Rationale: Indoor air pollution represents a modifiable risk factor for respiratory morbidity in chronic obstructive pulmonary disease (COPD). The effects of indoor air pollution, as well as the impact of interventions to improve indoor air quality, on cardiovascular morbidity in COPD remain unknown. Objectives: To determine the association between indoor particulate matter (PM) and heart rate variability (HRV), a measure of cardiac autonomic function tied to cardiovascular morbidity and mortality, as well as the impact of household air purifiers on HRV. Methods: Former smokers with moderate-severe COPD were recruited from a 6-month randomized controlled trial of a portable air cleaner intervention to undergo paired assessment of both in-home PM and HRV using 24-hour Holter monitoring at up to five time points. Primary outcomes were HRV measures tied to cardiovascular morbidity (standard deviation of normal-to-normal intervals [SDNN] and root mean square of successive differences between normal-to-normal intervals [RMSSD]). Measurements and Results: Eighty-five participants contributed 317 HRV measurements. A twofold increase in household PM ⩽2.5 µm in aerodynamic diameter was associated with decreases in SDNN (ß, -2.98% [95% confidence interval (CI), -5.12 to -0.78]) and RMSSD (ß, -4.57% [95% CI, -10.1 to -1.60]). The greatest effects were observed with ultrafine particles (<100 nm) (RMSSD; ß, -16.4% [95% CI, -22.3 to -10.1]) and among obese participants. Participants randomized to the active air cleaner saw improvements in RMSSD (ß, 25.2% [95% CI, 2.99 to 52.1]), but not SDNN (ß, 2.65% [95% CI, -10.8 to 18.1]), compared with the placebo group. Conclusions: This is the first U.S. study to describe the association between household PM and cardiac autonomic function among individuals with COPD, as well as the potential cardiovascular health benefits of household air cleaners.

Comprehensive home environmental intervention did not reduce allergen concentrations or controller medication requirements among children in Baltimore.

OBJECTIVE: To determine if the addition of home environmental control strategies (ECSs) to controller medication titration reduces asthma controller medication requirements and in-home allergen concentrations among children with persistent asthma in Baltimore City. METHODS: 155 children ages 5-17 with allergen-sensitized asthma were enrolled in a 6-month randomized clinical trial of multifaceted, individually-tailored ECS plus asthma controller medication titration compared to controller medication titration alone. Participants had to meet criteria for persistent asthma and have had an exacerbation in the previous 18 months. Allergen sensitization (mouse, cockroach, cat, dog, dust mite) was assessed at baseline and home dust allergen concentrations were measured at baseline, 3 and 6 months. ECS was delivered 3-4 times over the trial. Asthma controller medication was titrated using a guidelines-based algorithm at baseline, 2, 4, and 6 months. The primary outcome was controller medication treatment step at 6 months (0-6, as-needed albuterol to high-dose ICS + LABA). RESULTS: The population was predominately Black (90%), on public insurance (93%), and male (61%). The mean age was 10.1 years (SD 3.3). More than 70% were sensitized to a rodent, >50% to cockroach, and 70% were polysensitized. At 6 months, there were no differences in either treatment step (3.8 [SD 1.4] vs. 3.7 [SD 1.5]) or allergen concentrations between groups. CONCLUSION: Among this predominantly low-income, Black pediatric asthma population, the addition of ECS to controller medication titration reduced neither indoor allergen concentrations nor controller medication requirements compared to controller medication titration alone.

Association of a Housing Mobility Program With Childhood Asthma Symptoms and Exacerbations.

Importance: Structural racism has been implicated in the disproportionally high asthma morbidity experienced by children living in disadvantaged, urban neighborhoods. Current approaches designed to reduce asthma triggers have modest impact. Objective: To examine whether participation in a housing mobility program that provided housing vouchers and assistance moving to low-poverty neighborhoods was associated with reduced asthma morbidity among children and to explore potential mediating factors. Design, Setting, and Participants: Cohort study of 123 children aged 5 to 17 years with persistent asthma whose families participated in the Baltimore Regional Housing Partnership housing mobility program from 2016 to 2020. Children were matched to 115 children enrolled in the Urban Environment and Childhood Asthma (URECA) birth cohort using propensity scores. Exposure: Moving to a low-poverty neighborhood. Main Outcomes: Caregiver-reported asthma exacerbations and symptoms. Results: Among 123 children enrolled in the program, median age was 8.4 years, 58 (47.2%) were female, and 120 (97.6%) were Black. Prior to moving, 89 of 110 children (81%) lived in a high-poverty census tract (>20% of families below the poverty line); after moving, only 1 of 106 children with after-move data (0.9%) lived in a high-poverty tract. Among this cohort, 15.1% (SD, 35.8) had at least 1 exacerbation per 3-month period prior to moving vs 8.5% (SD, 28.0) after moving, an adjusted difference of -6.8 percentage points (95% CI, -11.9% to -1.7%; P = .009). Maximum symptom days in the past 2 weeks were 5.1 (SD, 5.0) before moving and 2.7 (SD, 3.8) after moving, an adjusted difference of -2.37 days (95% CI, -3.14 to -1.59; P < .001). Results remained significant in propensity score-matched analyses with URECA data. Measures of stress, including social cohesion, neighborhood safety, and urban stress, all improved with moving and were estimated to mediate between 29% and 35% of the association between moving and asthma exacerbations. Conclusions and Relevance: Children with asthma whose families participated in a program that helped them move into low-poverty neighborhoods experienced significant improvements in asthma symptom days and exacerbations. This study adds to the limited evidence suggesting that programs to counter housing discrimination can reduce childhood asthma morbidity.

Estimating the health effects of environmental mixtures using principal stratification.

The control of ambient air quality in the United States has been a major public health success since the passing of the Clean Air Act, with particulate matter (PM) reductions resulting in an estimated 160 000 premature deaths prevented in 2010 alone. Currently, public policy is oriented around lowering the levels of individual pollutants and this focus has driven the nature of much epidemiological research. Recently, attention has been given to viewing air pollution as a complex mixture and to developing a multi-pollutant approach to controlling ambient concentrations. We present a statistical approach for estimating the health impacts of complex environmental mixtures using a mixture-altering contrast, which is any comparison, intervention, policy, or natural experiment that changes a mixture's composition. We combine the notion of mixture-altering contrasts with sliced inverse regression, propensity score matching, and principal stratification to assess the health effects of different air pollution chemical mixtures. We demonstrate the application of this approach in an analysis of the health effects of wildfire PM air pollution in the Western US.

Phthalate biomarkers and associations with respiratory symptoms and healthcare utilization among low-income urban children with asthma.

BACKGROUND: Phthalates are synthetic chemicals present in building materials, personal care products and other consumer goods. Limited studies link phthalates to pediatric asthma incidence; however, their effects on respiratory-related outcomes among those with pre-existing asthma remains unclear. OBJECTIVE: We examined associations between phthalates and asthma symptoms, healthcare use, lung function, and lung inflammation among children with asthma. METHODS: We collected repeated measures of urinary biomarkers for select phthalates and phthalate replacements (MBzP, MCINP, MCIOP, MCPP, MECPTP, MEHHTP, molar sum of DEHP biomarkers [MECPP, MEHHP, MEHP, MEOHP], MEP, MiBP, MnBP) and asthma symptoms, healthcare utilization, lung function, and inflammation among 148 predominantly low-income Black children (5-17 years) with persistent asthma every 3 months for one year. We used generalized estimating equations to assess associations between biomarker concentrations and asthma-related measures adjusting for age, sex, race/ethnicity, caregiver's education level, presence of smokers in the home, and season. We also considered co-exposures to other contaminants previously associated with asthma morbidity. RESULTS: We observed consistent positive associations with individual DEHP biomarkers, the molar sum of DEHP, and BBzP with increased odds of asthma symptoms and with healthcare utilization (adjusted Odds Ratio for general asthma symptoms: ΣDEHP:1.49,95% Confidence Interval, CI:1.08-2.07; BBzP:1.34, CI:1.04-1.73). We observed similar associations between the DEHP phthalate replacement biomarker MEHHTP and most asthma symptoms evaluated; and with select low molecular weight phthalates (DiBP, DBP) and healthcare utilization. Results were similar when controlling for other environmental exposures (e.g., PM2.5, BPA). No associations were observed with lung function or inflammation, and overall, we did not observe consistent evidence of sexually dimorphic effects. CONCLUSION: In the present study, we found evidence to suggest that exposure to select phthalates may be associated with asthma symptoms and healthcare utilization. These findings warrant confirmation given the high asthma burden and widespread and disparate phthalate exposures reported among select populations of color.

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.

Assessing the health estimation capacity of air pollution exposure prediction models.

BACKGROUND: The era of big data has enabled sophisticated models to predict air pollution concentrations over space and time. Historically these models have been evaluated using overall metrics that measure how close predictions are to monitoring data. However, overall methods are not designed to distinguish error at timescales most relevant for epidemiologic studies, such as day-to-day errors that impact studies of short-term health associations. METHODS: We introduce frequency band model performance, which quantifies health estimation capacity of air quality prediction models for time series studies of air pollution and health. Frequency band model performance uses a discrete Fourier transform to evaluate prediction models at timescales of interest. We simulated fine particulate matter (PM2.5), with errors at timescales varying from acute to seasonal, and health time series data. To compare evaluation approaches, we use correlations and root mean squared error (RMSE). Additionally, we assess health estimation capacity through bias and RMSE in estimated health associations. We apply frequency band model performance to PM2.5 predictions at 17 monitors in 8 US cities. RESULTS: In simulations, frequency band model performance rates predictions better (lower RMSE, higher correlation) when there is no error at a particular timescale (e.g., acute) and worse when error is added to that timescale, compared to overall approaches. Further, frequency band model performance is more strongly associated (R2 = 0.95) with health association bias compared to overall approaches (R2 = 0.57). For PM2.5 predictions in Salt Lake City, UT, frequency band model performance better identifies acute error that may impact estimated short-term health associations. CONCLUSIONS: For epidemiologic studies, frequency band model performance provides an improvement over existing approaches because it evaluates models at the timescale of interest and is more strongly associated with bias in estimated health associations. Evaluating prediction models at timescales relevant for health studies is critical to determining whether model error will impact estimated health associations.

Exposure to bisphenols and asthma morbidity among low-income urban children with asthma.

BACKGROUND: Bisphenol A (BPA) has been linked with pediatric asthma development and allergic airway inflammation in animal models. Whether exposure to BPA or its structural analogs bisphenol S (BPS) and bisphenol F (BPF) is associated with asthma morbidity remains unknown. OBJECTIVE: We examined associations between bisphenols and morbidity due to pediatric asthma. METHODS: We quantified concentrations of BPA, BPS, and BPF in 660 urine samples from 148 predominantly low-income, African American children (aged 5-17 years) with established asthma. We used biobanked biospecimens and data on symptoms, health care utilization, and pulmonary function and inflammation that were collected every 3 months over the course of a year. We used generalized estimating equations to examine associations between concentrations or detection of urinary bisphenols and morbidity outcomes and assessed heterogeneity of associations by sex. RESULTS: We observed consistent positive associations between BPA exposure and measures of asthma morbidity. For example, we observed increased odds of general symptom days (adjusted odds ratio [aOR] = 1.40 [95% C = 1.02-1.92]), maximal symptom days (aOR = 1.36 [95% CI = 1.00-1.83]), and emergency department visits (aOR = 2.12 [95% CI =1.28-3.51]) per 10-fold increase in BPA concentration. We also observed evidence of sexually dimorphic effects; BPA concentrations were associated with increased odds of symptom days and health care utilization only among boys. Findings regarding BPS and BPF did not consistently point to associations with asthma symptoms or health care utilization. CONCLUSION: We found evidence to suggest that BPA exposure in a predominantly low-income, minority pediatric cohort is associated with asthma morbidity and that associations may differ by sex. Our findings support additional studies, given the high pediatric asthma burden and widespread exposure to BPA in the United States.

Reproducible Research: A Retrospective.

Advances in computing technology have spurred two extraordinary phenomena in science: large-scale and high-throughput data collection coupled with the creation and implementation of complex statistical algorithms for data analysis. These two phenomena have brought about tremendous advances in scientific discovery but have raised two serious concerns. The complexity of modern data analyses raises questions about the reproducibility of the analyses, meaning the ability of independent analysts to recreate the results claimed by the original authors using the original data and analysis techniques. Reproducibility is typically thwarted by a lack of availability of the original data and computer code. A more general concern is the replicability of scientific findings, which concerns the frequency with which scientific claims are confirmed by completely independent investigations. Although reproducibility and replicability are related, they focus on different aspects of scientific progress. In this review, we discuss the origins of reproducible research, characterize the current status of reproducibility in public health research, and connect reproducibility to current concerns about the replicability of scientific findings. Finally, we describe a path forward for improving both the reproducibility and replicability of public health research in the future.

Tropical Cyclone Exposures and Risks of Emergency Medicare Hospital Admission for Cardiorespiratory Diseases in 175 Urban United States Counties, 1999-2010.

BACKGROUND: Although injuries experienced during hurricanes and other tropical cyclones have been relatively well-characterized through traditional surveillance, less is known about tropical cyclones' impacts on noninjury morbidity, which can be triggered through pathways that include psychosocial stress or interruption in medical treatment. METHODS: We investigated daily emergency Medicare hospitalizations (1999-2010) in 180 US counties, drawing on an existing cohort of high-population counties. We classified counties as exposed to tropical cyclones when storm-associated peak sustained winds were ≥21 m/s at the county center; secondary analyses considered other wind thresholds and hazards. We matched storm-exposed days to unexposed days by county and seasonality. We estimated change in tropical cyclone-associated hospitalizations over a storm period from 2 days before to 7 days after the storm's closest approach, compared to unexposed days, using generalized linear mixed-effect models. RESULTS: For 1999-2010, 175 study counties had at least one tropical cyclone exposure. Cardiovascular hospitalizations decreased on the storm day, then increased following the storm, while respiratory hospitalizations were elevated throughout the storm period. Over the 10-day storm period, cardiovascular hospitalizations increased 3% (95% confidence interval = 2%, 5%) and respiratory hospitalizations increased 16% (95% confidence interval = 13%, 20%) compared to matched unexposed periods. Relative risks varied across tropical cyclone exposures, with strongest association for the most restrictive wind-based exposure metric. CONCLUSIONS: In this study, tropical cyclone exposures were associated with a short-term increase in cardiorespiratory hospitalization risk among the elderly, based on a multi-year/multi-site investigation of US Medicare beneficiaries ≥65 years.

Reduction in mouse allergen exposure is associated with greater lung function growth.

BACKGROUND: Current childhood asthma therapies have little effect on lung function trajectory. OBJECTIVE: We sought to determine whether mouse allergen exposure reduction is associated with lung function growth in mouse-sensitized/exposed asthmatic children. METHODS: Three hundred fifty mouse-sensitized/exposed asthmatic children (5-17 years old) were enrolled in a 1-year randomized trial of integrated pest management plus education versus education alone. Prebronchodilator/postbronchodilator spirometry was performed at baseline and 6 and 12 months, and bedroom floor mouse allergen levels were measured every 3 months. Mouse allergen reduction was defined as a 75% or greater decrease in mouse allergen levels from baseline. Treatment groups were combined for analyses because there were no differences in outcomes between groups. Changes in lung function over time were modeled, adjusting for age, sex, race, atopy, group, and bronchodilator reversibility and including an interaction term (allergen reduction*time). RESULTS: The study population was predominantly black (79.4%) and low income (66.3% [<$30,000]). At baseline, the median mouse allergen level was 5.7 µg/g (interquartile range, 1.5-22.8 µg/g), and the mean (SD) prebronchodilator FEV1/forced vital capacity ratio was 80.2% (9.0%). Ninety-two (26.3%) participants had 75% or greater reduction in mouse allergen levels. For a 10-year-old black boy, 75% or greater allergen reduction was associated with an increase in prebronchodilator FEV1 of 238 mL/y (95% CI, 177-299 mL/y), whereas less than 75% allergen reduction was associated with an increase in prebronchodilator FEV1 of 131 mL/y (95% CI, 97-166 mL/y). Estimated differences in prebronchodilator and postbronchodilator FEV1 growth were as follows: 107 mL/y (95% CI, 37-177 mL/y; Pint = .003) and 48 mL/y (95% CI, -17 to 113 mL/y; Pint = .15), respectively. Estimated differences in prebronchodilator and postbronchodilator forced expiratory flow at 25% to 75% of vital capacity growth were as follows: 182 mL/y (95% CI, 61-304 mL/y; Pint = .003) and 181 mL/y (95% CI, 48-314 mL/y; Pint = .008), respectively. CONCLUSION: Mouse allergen reduction is associated with greater increases in prebronchodilator FEV1 and prebronchodilator/postbronchodilator forced expiratory flow at 25% to 75% of vital capacity over 1 year among sensitized/exposed asthmatic children.

Rural Residence and Poverty Are Independent Risk Factors for Chronic Obstructive Pulmonary Disease in the United States.

RATIONALE: In developing countries, poor and rural areas have a high burden of chronic obstructive pulmonary disease (COPD), and environmental pollutants and indoor burning of biomass have been implicated as potential causal exposures. Less is known about the prevalence of COPD in the United States with respect to urban-rural distribution, poverty, and factors that uniquely contribute to COPD among never-smokers. OBJECTIVES: To understand the impact of urban-rural status, poverty, and other community factors on COPD prevalence nationwide and among never-smokers. METHODS: We studied a nationally representative sample of adults in the National Health Interview Survey 2012-2015, with data linkage between neighborhood data from the U.S. Census's American Community Survey and the National Center for Health Statistics Urban-Rural Classification Scheme. The main outcome was COPD prevalence. MEASUREMENTS AND MAIN RESULTS: The prevalence of COPD in poor, rural areas was almost twice that in the overall population (15.4% vs. 8.4%). In adjusted models, rural residence (odds ratio [OR], 1.23; P < 0.001) and census-level poverty (OR, 1.12; P = 0.012) were both associated with COPD prevalence, as were indicators of household wealth. Among never-smokers, rural residence was also associated with COPD (OR, 1.34; P < 0.001), as was neighborhood use of coal for heating (OR, 1.09; P < 0.001). CONCLUSIONS: In a nationally representative sample, rural residence and poverty were risk factors for COPD, even among never-smokers. The use of coal for heating was also a risk factor for COPD among never-smokers. Future disparities research to elucidate contributors to COPD development in poor and rural areas, including assessments of heating sources and environmental pollutants, is needed.

The impact of heat waves on mortality in Northwest India.

Heat waves are anticipated to worsen with climate change. India, an understudied area with >15% of the world's population, commonly experiences temperature extremes and already resembles potential future climates of more temperate regions. Registry data from local municipal corporations and government offices were collected and translated, yielding daily all-cause mortality for 4 communities in Northwest India for all or part of the period 2000-2012. Heat waves were defined as ≥2 days with local temperature ≥97th percentile for that community. An alternate definition matching that used by the Indian Meteorological Department was also developed, to enhance policy relevance. Community-specific average daily maximum temperature over the entire record ranged from 32.5 to 34.2 °C (90.5-93.6 °F). Across communities, total mortality increased 18.1% during heat wave days compared with non-heat-wave days [95% confidence interval (CI): -5.3%, 47.3%], with the highest risk in Jaipur (29.9% [95% CI: 24.6%, 34.9%]). Evidence of effect modification by heat wave characteristics (intensity, duration, and timing in season) was limited. Findings indicate health risks associated with heat waves in communities with high baseline temperatures. Results can inform heat wave-health assessments in temperate regions in future, and improve our understanding of temperature-health associations under climate change. Further investigation of potential effect modification by heat wave characteristics is needed.

Long-Term Coarse Particulate Matter Exposure Is Associated with Asthma among Children in Medicaid.

RATIONALE: Short- and long-term fine particulate matter (particulate matter ≤2.5 µm in aerodynamic diameter [PM2.5]) pollution is associated with asthma development and morbidity, but there are few data on the effects of long-term exposure to coarse PM (PM10-2.5) on respiratory health. OBJECTIVES: To understand the relationship between long-term fine and coarse PM exposure and asthma prevalence and morbidity among children. METHODS: A semiparametric regression model that incorporated PM2.5 and PM10 monitor data and geographic characteristics was developed to predict 2-year average PM2.5 and PM10-2.5 exposure during the period 2009 to 2010 at the zip-code tabulation area level. Data from 7,810,025 children aged 5 to 20 years enrolled in Medicaid from 2009 to 2010 were used in a log-linear regression model with predicted PM levels to estimate the association between PM exposure and asthma prevalence and morbidity, adjusting for race/ethnicity, sex, age, area-level urbanicity, poverty, education, and unmeasured spatial confounding. MEASUREMENTS AND MAIN RESULTS: Exposure to coarse PM was associated with increased asthma diagnosis prevalence (rate ratio [RR] for 1-µg/m3 increase in coarse PM level, 1.006; 95% confidence interval [CI], 1.001-1.011), hospitalizations (RR, 1.023; 95% CI, 1.003-1.042), and emergency department visits (RR, 1.017; 95% CI, 1.001-1.033) when adjusting for fine PM. Fine PM exposure was more strongly associated with increased asthma prevalence and morbidity than coarse PM. The estimates remained elevated across different levels of spatial confounding adjustment. CONCLUSIONS: Among children enrolled in Medicaid, exposure to higher average coarse PM levels is associated with increased asthma prevalence and morbidity. These results suggest the need for direct monitoring of coarse PM and reconsideration of limits on long-term average coarse PM pollution levels.

Urban residence, neighborhood poverty, race/ethnicity, and asthma morbidity among children on Medicaid.

BACKGROUND: Although poor-urban (inner-city) areas are thought to have high asthma prevalence and morbidity, we recently found that inner cities do not have higher prevalent pediatric asthma. Whether asthma morbidity is higher in inner-city areas across the United States is not known. OBJECTIVE: This study sought to examine relationships between residence in poor and urban areas, race/ethnicity, and asthma morbidity among children with asthma who are enrolled in Medicaid. METHODS: Children aged 5 to 19 enrolled in Medicaid in 2009 to 2010 were included. Asthma was defined by at least 1 outpatient or emergency department (ED) visit with a primary diagnosis code of asthma over the 2-year period. Urbanization status was defined at the county level and neighborhood poverty at the zip-code level. Among children with asthma, logistic models were created to examine the effects of urbanization, neighborhood poverty, and race/ethnicity on rates of asthma outpatient visits, ED visits, and hospitalizations. RESULTS: This study included 16,860,716 children (1,534,820 with asthma). Among children enrolled in Medicaid, residence in inner-city areas did not confer increased risk of prevalent asthma in either crude or adjusted analyses, but it was associated with significantly more asthma-related ED visits and hospitalizations among those with asthma in crude analyses (risk ratio, 1.48; 95% CI, 1.24-1.36; and 1.97; 95% CI, 1.50-1.72, respectively) and when adjusted for race/ethnicity, age, and sex (adjusted risk ratio, 1.23; 95% CI, 1.08-1.15; and 1.62; 95% CI, 1.26-1.43). Residence in urban or poor areas and non-Hispanic black race/ethnicity were all independently associated with increased risk of asthma-related ED visits and hospitalizations. CONCLUSIONS: Residence in poor and urban areas is an important risk factor for asthma morbidity, but not for prevalence, among low-income US children.

Who Among the Elderly Is Most Vulnerable to Exposure to and Health Risks of Fine Particulate Matter From Wildfire Smoke?

Wildfires burn more than 7 million acres in the United States annually, according to the US Forest Service. Little is known about which subpopulations are more vulnerable to health risks from wildfire smoke, including those associated with fine particulate matter. We estimated exposure to fine particles specifically from wildfires, as well as the associations between the presence of wildfire-specific fine particles and the amount of hospital admissions for respiratory causes among subpopulations older than 65 years of age in the western United States (2004-2009). Compared with other populations, higher fractions of persons who were black, lived in urban counties, and lived in California were exposed to more than 1 smoke wave (high-pollution episodes from wildfire smoke). The risks of respiratory admissions on smoke-wave days compared with non-smoke-wave days increased 10.4% (95% confidence interval: 1.9, 19.6) for women and 21.7% (95% confidence interval: 0.4, 47.3) for blacks. Our findings suggest that increased risks of respiratory admissions from wildfire smoke was significantly higher for women than for men (10.4% vs. 3.7%), blacks than whites (21.7% vs. 6.9%), and, although associations were not statistically different, people in lower-education counties than higher-educated counties (12.7% vs. 6.1%). Our study raised important environmental justice issues that can inform public health programs and wildfire management. As climate change increases the frequency and intensity of wildfires, evidence on vulnerable subpopulations can inform disaster preparedness and the understanding of climate change consequences.

Wildfire-specific Fine Particulate Matter and Risk of Hospital Admissions in Urban and Rural Counties.

BACKGROUND: The health impacts of wildfire smoke, including fine particles (PM2.5), are not well understood and may differ from those of PM2.5 from other sources due to differences in concentrations and chemical composition. METHODS: First, for the entire Western United States (561 counties) for 2004-2009, we estimated daily PM2.5 concentrations directly attributable to wildfires (wildfires-specific PM2.5), using a global chemical transport model. Second, we defined smoke wave as ≥2 consecutive days with daily wildfire-specific PM2.5 > 20 µg/m, with sensitivity analysis considering 23, 28, and 37 µg/m. Third, we estimated the risk of cardiovascular and respiratory hospital admissions associated with smoke waves for Medicare enrollees. We used a generalized linear mixed model to estimate the relative risk of hospital admissions on smoke wave days compared with matched comparison days without wildfire smoke. RESULTS: We estimated that about 46 million people of all ages were exposed to at least one smoke wave during 2004 to 2009 in the Western United States. Of these, 5 million are Medicare enrollees (≥65 years). We found a 7.2% (95% confidence interval: 0.25%, 15%) increase in risk of respiratory admissions during smoke wave days with high wildfire-specific PM2.5 (>37 µg/m) compared with matched non smoke wave days. We did not observe an association between smoke wave days with wildfire-specific PM2.5 ≤ 37 µg/mand respiratory or cardiovascular admissions. Respiratory effects of wildfire-specific PM2.5 may be stronger than that of PM2.5 from other sources. CONCLUSION: Short-term exposure to wildfire-specific PM2.5was associated with risk of respiratory diseases in the elderly population in the Western United States during severe smoke days. See video abstract at, http://links.lww.com/EDE/B137.