Ambarish Vaidyanathan

Statistical air quality predictions for public health surveillance: evaluation and generation of county level metrics of PM2.5 for the environmental public health tracking network.

BackgroundThe Centers for Disease Control and Prevention (CDC) developed county level metrics for the Environmental Public Health Tracking Network (Tracking Network) to characterize potential population exposure to airborne particles with an aerodynamic diameter of 2.5 μm or less (PM2.5). These metrics are based on Federal Reference Method (FRM) air monitor data in the Environmental Protection Agency (EPA) Air Quality System (AQS); however, monitor data are limited in space and time. In order to understand air quality in all areas and on days without monitor data, the CDC collaborated with the EPA in the development of hierarchical Bayesian (HB) based predictions of PM2.5 concentrations. This paper describes the generation and evaluation of HB-based county level estimates of PM2.5.MethodsWe used three geo-imputation approaches to convert grid-level predictions to county level estimates. We used Pearson (r) and Kendall Tau-B (τ) correlation coefficients to assess the consistency of the relationship, and examined the direct differences (by county) between HB-based estimates and AQS-based concentrations at the daily level. We further compared the annual averages using Tukey mean-difference plots.ResultsDuring the year 2005, fewer than 20% of the counties in the conterminous United States (U.S.) had PM2.5 monitoring and 32% of the conterminous U.S. population resided in counties with no AQS monitors. County level estimates resulting from population-weighted centroid containment approach were correlated more strongly with monitor-based concentrations (r = 0.9; τ = 0.8) than were estimates from other geo-imputation approaches. The median daily difference was −0.2 μg/m3 with an interquartile range (IQR) of 1.9 μg/m3 and the median relative daily difference was −2.2% with an IQR of 17.2%. Under-prediction was more prevalent at higher concentrations and for counties in the western U.S.ConclusionsWhile the relationship between county level HB-based estimates and AQS-based concentrations is generally good, there are clear variations in the strength of this relationship for different regions of the U.S. and at various concentrations of PM2.5. This evaluation suggests that population-weighted county centroid containment method is an appropriate geo-imputation approach, and using the HB-based PM2.5 estimates to augment gaps in AQS data provides a more spatially and temporally consistent basis for calculating the metrics deployed on the Tracking Network.

Outdoor PM2.5, Ambient Air Temperature, and Asthma Symptoms in the Past 14 Days among Adults with Active Asthma.

Background: Relationships between air quality and health are well-described, but little information is available about the joint associations between particulate air pollution, ambient temperature, and respiratory morbidity. Objectives: We evaluated associations between concentrations of particulate matter ≤ 2.5 μm in diameter (PM2.5) and exacerbation of existing asthma and modification of the associations by ambient air temperature. Methods: Data from 50,356 adult respondents to the Asthma Call-back Survey from 2006–2010 were linked by interview date and county of residence to estimates of daily averages of PM2.5 and maximum air temperature. Associations between 14-day average PM2.5 and the presence of any asthma symptoms during the 14 days leading up to and including the interview date were evaluated using binomial regression. We explored variation by air temperature using similar models, stratified into quintiles of the 14-day average maximum temperature. Results: Among adults with active asthma, 57.1% reported asthma symptoms within the past 14 days, and 14-day average PM2.5 ≥ 7.07 μg/m3 was associated with an estimated 4–5% higher asthma symptom prevalence. In the range of 4.00–7.06 μg/m3 of PM2.5, each 1-μg/m3 increase was associated with a 3.4% [95% confidence interval (CI): 1.1, 5.7] increase in symptom prevalence; across categories of temperature from 1.1 to 80.5°F, each 1-μg/m3 increase was associated with increased symptom prevalence (1.1–44.4°F: 7.9%; 44.5–58.6°F: 6.9%; 58.7–70.1°F: 2.9%; 70.2–80.5°F: 7.3%). Conclusions: These results suggest that each unit increase in PM2.5 may be associated with an increase in the prevalence of asthma symptoms, even at levels as low as 4.00–7.06 μg/m3. Citation: Mirabelli MC, Vaidyanathan A, Flanders WD, Qin X, Garbe P. 2016. Outdoor PM2.5, ambient air temperature, and asthma symptoms in the past 14 days among adults with active asthma. Environ Health Perspect 124:1882–1890; http://dx.doi.org/10.1289/EHP92

Screening for Lead Poisoning: A Geospatial Approach to Determine Testing of Children in At-Risk Neighborhoods

OBJECTIVE To develop a spatial strategy to assess neighborhood risk for lead exposure and neighborhood-level blood lead testing of young children living in the city of Atlanta, Georgia. STUDY DESIGN This ecologic study used existing blood lead results of children aged <or=36 months tested and living in one of Atlantas 236 neighborhoods in 2005. Geographic information systems used Census, land parcel, and neighborhood spatial data to create a neighborhood priority testing index on the basis of proxies for poverty (Special Supplemental Nutrition Program for Women, Infants and Children [WIC] enrollment) and lead in house paint (year housing built). RESULTS In 2005, only 11.9% of Atlantas 18,627 children aged <or=36 months living in the city had blood lead tests, despite a high prevalence of risk factors: 75,286 (89.6%) residential properties were built before 1978, and 44% of children were enrolled in WIC. Linear regression analysis indicated testing was significantly associated with WIC status (P < .001) but not with old housing. CONCLUSIONS This neighborhood spatial approach provided smaller geographic areas to assign risk and assess testing in a city that has a high prevalence of risk factors for lead exposure. Testing may be improved by collaboration between pediatricians and public health practitioners.

Spatial variation in hyperthermia emergency department visits among those with employer-based insurance in the United States – a case-crossover analysis

BackgroundPredictions of intense heat waves across the United States will lead to localized health impacts, most of which are preventable. There is a need to better understand the spatial variation in the morbidity impacts associated with extreme heat across the country to prevent such adverse health outcomes.MethodsHyperthermia-related emergency department (ED) visits were obtained from the Truven Health MarketScan® Research dataset for 2000-2010. Three measures of daily ambient heat were constructed using meteorological observations from the National Climatic Data Center (maximum temperature, heat index) and the Spatial Synoptic Classification. Using a time-stratified case crossover approach, odds ratio of hyperthermia-related ED visit were estimated for the three different heat measures. Random effects meta-analysis was used to combine the odds ratios for 94 Metropolitan Statistical Areas (MSA) to examine the spatial variation by eight latitude categories and nine U.S. climate regions.ResultsExamination of lags for all three temperature measures showed that the odds ratio of ED visit was statistically significant and highest on the day of the ED visit. For heat waves lasting two or more days, additional statistically significant association was observed when heat index and synoptic classification was used as the temperature measure. These results were insensitive to the inclusion of air pollution measures. On average, the maximum temperature on the day of an ED visit was 93.4oF in ‘South’ and 81.9oF in the ‘Northwest’ climatic regions of United States. The meta-analysis showed higher odds ratios of hyperthermia ED visit in the central and the northern parts of the country compared to the south and southwest.ConclusionThe results showed spatial variation in average temperature on days of ED visit and odds ratio for hyperthermia ED visits associated with extreme heat across United States. This suggests that heat response plans need to be customized for different regions and the potential role of hyperthermia ED visits in syndromic surveillance for extreme heat.

Comparison of wildfire smoke estimation methods and associations with cardiopulmonary-related hospital admissions

Abstract Climate forecasts predict an increase in frequency and intensity of wildfires. Associations between health outcomes and population exposure to smoke from Washington 2012 wildfires were compared using surface monitors, chemical‐weather models, and a novel method blending three exposure information sources. The association between smoke particulate matter ≤2.5 μm in diameter (PM2.5) and cardiopulmonary hospital admissions occurring in Washington from 1 July to 31 October 2012 was evaluated using a time‐stratified case‐crossover design. Hospital admissions aggregated by ZIP code were linked with population‐weighted daily average concentrations of smoke PM2.5 estimated using three distinct methods: a simulation with the Weather Research and Forecasting with Chemistry (WRF‐Chem) model, a kriged interpolation of PM2.5 measurements from surface monitors, and a geographically weighted ridge regression (GWR) that blended inputs from WRF‐Chem, satellite observations of aerosol optical depth, and kriged PM2.5. A 10 μg/m3 increase in GWR smoke PM2.5 was associated with an 8% increased risk in asthma‐related hospital admissions (odds ratio (OR): 1.076, 95% confidence interval (CI): 1.019–1.136); other smoke estimation methods yielded similar results. However, point estimates for chronic obstructive pulmonary disease (COPD) differed by smoke PM2.5 exposure method: a 10 μg/m3 increase using GWR was significantly associated with increased risk of COPD (OR: 1.084, 95%CI: 1.026–1.145) and not significant using WRF‐Chem (OR: 0.986, 95%CI: 0.931–1.045). The magnitude (OR) and uncertainty (95%CI) of associations between smoke PM2.5 and hospital admissions were dependent on estimation method used and outcome evaluated. Choice of smoke exposure estimation method used can impact the overall conclusion of the study.

Short-term effects of ambient air pollutants on asthma-related emergency department visits in Indianapolis, Indiana, 2007-2011.

Abstract Objective: We estimate the short-term associations between daily changes in ambient air pollutants and daily asthma-related emergency department (ED) visits in Indianapolis, IN. Methods: We identified asthma-related ED visits among Indianapolis residents aged ≥5 years. We used Poisson regression in a time-series framework to estimate the increased risk for asthma-related ED visits from exposure to ambient SO2, PM2.5 and ozone during the warm season (April–September) and SO2 and PM2.5 during the cold (October–March) season, from 2007 to 2011. Our models controlled for measured confounders, including weather and respiratory infections, as well as unmeasured confounders using a natural cubic spline to account for long-term seasonal trends. Results: During 2007–2011 in Indianapolis, 165 056 asthma-related ED visits occurred. We found statistically significant positive associations (p < 0.05) between ambient air pollutants and ED visits during the warm season for persons aged 5–44 years. Interquartile range increases in daily ozone concentrations with same day, 2-day lagged, and 3-day moving average were associated with increased risks for ED visits of 3.2% (95% CI: 0.2%, 6.3%), 4.4% (0.1%, 8.9%) and 4.8% (0.2%, 9.6%), respectively. Interquartile range increases in 3-day moving averages for SO2 were associated with an increased risk of 3.3% (95% CI: 0.2%, 6.5%). We identified statistically significant associations (p < 0.05) between increased SO2 and PM2.5 levels and decreased ED visits among some age groups, primarily during the cold season, and no significant positive associations between changes in PM2.5 concentration and asthma-related ED visits. Conclusions: During the warm season, increases in ozone and SO2 concentrations were associated with increased asthma morbidity in children and young adults in Indianapolis. These results will enable reliable estimation of the health impacts of increases in these pollutants on asthma-related ED visits in Indianapolis and similar communities.

Particulate Matter Air Pollution Exposure and Heart Disease Mortality Risks by Race and Ethnicity in the United States: 1997 to 2009 National Health Interview Survey With Mortality Follow-Up Through 2011

Background: Most US studies of mortality and air pollution have been conducted on largely non-Hispanic white study populations. However, many health and mortality outcomes differ by race and ethnicity, and non-Hispanic white persons experience lower air pollution exposure than those who are non-Hispanic black or Hispanic. This study examines whether associations between air pollution and heart disease mortality differ by race/ethnicity. Methods: We used data from the 1997 to 2009 National Health Interview Survey linked to mortality records through December 2011 and annual estimates of fine particulate matter (PM2.5) by census tract. Proportional hazards models were used to estimate hazard ratios and 95% confidence intervals between PM2.5 (per 10 µg/m3) and heart disease mortality using the full sample and the sample adults, which have information on additional health variables. Interaction terms were used to examine differences in the PM2.5-mortality association by race/ethnicity. Results: Overall, 65 936 of the full sample died during follow-up, and 22 152 died from heart disease. After adjustment for several factors, we found a significant positive association between PM2.5 and heart disease mortality (hazard ratio, 1.16; 95% confidence interval, 1.08–1.25). This association was similar in sample adults with adjustment for smoking and body mass index (hazard ratio, 1.18; 95% confidence interval, 1.06–1.31). Interaction terms for non-Hispanic black and Hispanic groups compared with the non-Hispanic white group were not statistically significant. Conclusions: Using a nationally representative sample, the association between PM2.5 and heart disease mortality was elevated and similar to previous estimates. Associations for non-Hispanic black and Hispanic adults were not statistically significantly different from those for non-Hispanic white adults.

A Statistical Framework to Evaluate Extreme Weather Definitions from a Health Perspective: A Demonstration Based on Extreme Heat Events

A statistical framework for evaluating definitions of extreme weather phenomena can help weather agencies and health departments identify the definition(s) most applicable for alerts nd other preparedness operations related to extreme weather episodes.

Emergency Department Visits and Ambient Temperature: Evaluating the Connection and Projecting Future Outcomes

Abstract The U.S. Global Climate Change Research Program has identified climate change as a growing public health threat. We investigated the potential effects of changes in ambient daily maximum temperature on hyperthermia and cardiovascular emergency department (ED) visits using records for patients age 64 and younger from a private insurance database for the May–September period for 2005–2012. We found a strong positive relationship between daily maximum temperatures and ED visits for hyperthermia but not for cardiovascular conditions. Using the fitted relationship from 136 metropolitan areas, we calculated the number and rate of hyperthermia ED visits for climates representative of year 1995 (baseline period), as well as years 2050 and 2090 (future periods), for two climate change scenarios based on outcomes from five global climate models. Without considering potential adaptation or population growth and movement, we calculate that climate change alone will result in an additional 21,000–28,000 hyperthermia ED visits for May to September, with associated treatment costs between

Differences in Heat-Related Mortality by Citizenship Status: United States, 2005–2014

6 million and