Jenna R. Krall

Recent Approaches to Estimate Associations Between Source-Specific Air Pollution and Health

Purpose of ReviewEstimating health effects associated with source-specific exposure is important for better understanding how pollution impacts health and for developing policies to better protect public health. Although epidemiologic studies of sources can be informative, these studies are challenging to conduct because source-specific exposures (e.g., particulate matter from vehicles) often are not directly observed and must be estimated. We reviewed recent studies that estimated associations between pollution sources and health to identify methodological developments designed to address important challenges.Recent FindingsNotable advances in epidemiologic studies of sources include approaches for (1) propagating uncertainty in source estimation into health effect estimates, (2) assessing regional and seasonal variability in emissions sources and source-specific health effects, and (3) addressing potential confounding in estimated health effects.SummaryNovel methodological approaches to address challenges in studies of pollution sources, particularly evaluation of source-specific health effects, are important for determining how source-specific exposure impacts health.

Source-specific pollution exposure and associations with pulmonary response in the Atlanta Commuters Exposure Studies

Concentrations of traffic-related air pollutants are frequently higher within commuting vehicles than in ambient air. Pollutants found within vehicles may include those generated by tailpipe exhaust, brake wear, and road dust sources, as well as pollutants from in-cabin sources. Source-specific pollution, compared to total pollution, may represent regulation targets that can better protect human health. We estimated source-specific pollution exposures and corresponding pulmonary response in a panel study of commuters. We used constrained positive matrix factorization to estimate source-specific pollution factors and, subsequently, mixed effects models to estimate associations between source-specific pollution and pulmonary response. We identified four pollution factors that we named: crustal, primary tailpipe traffic, non-tailpipe traffic, and secondary. Among asthmatic subjects (N = 48), interquartile range increases in crustal and secondary pollution were associated with changes in lung function of −1.33% (95% confidence interval (CI): −2.45, −0.22) and −2.19% (95% CI: −3.46, −0.92) relative to baseline, respectively. Among non-asthmatic subjects (N = 51), non-tailpipe pollution was associated with pulmonary response only at 2.5 h post-commute. We found no significant associations between pulmonary response and primary tailpipe pollution. Health effects associated with traffic-related pollution may vary by source, and therefore some traffic pollution sources may require targeted interventions to protect health.

State helmet laws and helmet use among fatally injured moped riders in the United States, 2011–2015

ABSTRACT Objective: Research has found that mandatory motorcycle helmet laws increase helmet use and reduce motorcycle-related fatalities. However, the association between state moped helmet laws and helmet use in the United States has not been examined. This study investigated this association among a census of fatally injured moped riders in the United States. Methods: A logistic regression model was constructed to analyze data extracted from the Fatality Analysis Reporting System (FARS) to examine risk factors for helmet nonuse among 572 moped riders fatally injured between 2011 and 2015. Results: Fatally injured moped riders in states with universal helmet laws had 69 times the odds of wearing a helmet (P < .001). Conclusions: Findings suggest that universal moped helmet laws increase helmet use. However, additional research is needed to examine helmet laws and use among nonfatally injured moped riders.

A multicity study of air pollution and cardiorespiratory emergency department visits: Comparing approaches for combining estimates across cities

Determining how associations between ambient air pollution and health vary by specific outcome is important for developing public health interventions. We estimated associations between twelve ambient air pollutants of both primary (e.g. nitrogen oxides) and secondary (e.g. ozone and sulfate) origin and cardiorespiratory emergency department (ED) visits for 8 specific outcomes in five U.S. cities including Atlanta, GA; Birmingham, AL; Dallas, TX; Pittsburgh, PA; St. Louis, MO. For each city, we fitted overdispersed Poisson time-series models to estimate associations between each pollutant and specific outcome. To estimate multicity and posterior city-specific associations, we developed a Bayesian multicity multi-outcome (MCM) model that pools information across cities using data from all specific outcomes. We fitted single pollutant models as well as models with multipollutant components using a two-stage chemical mixtures approach. Posterior city-specific associations from the MCM models were somewhat attenuated, with smaller standard errors, compared to associations from time-series regression models. We found positive associations of both primary and secondary pollutants with respiratory disease ED visits. There was some indication that primary pollutants, particularly nitrogen oxides, were also associated with cardiovascular disease ED visits. Bayesian models can help to synthesize findings across multiple outcomes and cities by providing posterior city-specific associations building on variation and similarities across the multiple sources of available information.

Exposure to bisphenol A, chlorophenols, benzophenones, and parabens in relation to reproductive hormones in healthy women: A chemical mixture approach

BACKGROUND Little is known about the associations of bisphenol A, chlorophenols, benzophenones, and parabens with reproductive hormone levels in women. Our goal was to evaluate the associations between repeated measures of these chemicals and their mixtures with reproductive hormones in women. METHODS Longitudinal urine samples from healthy, premenopausal women (n = 143 with 3-5 urine samples each) were measured for bisphenol A, five chlorophenols (2,4-dichlorophenol (2,4-DCP), 2,5-dichlorophenol, 2,4,5-trichlorophenol, 2,4,6-trichlorophenol, triclosan), two ultraviolet (UV) filters (benzophenone-1, benzophenone-3), and eight parabens and their metabolites (benzyl, butyl, ethyl, heptyl, methyl, propyl, 4-hydroxybenzoic acid (4-HB), 3,4-dihydroxybenzoic acid (3,4-DHB)) over two menstrual cycles. Estradiol, progesterone, luteinizing hormone (LH), and follicle stimulating hormone (FSH) were measured in blood up to 8 times each menstrual cycle. Linear mixed models were used for both single and multi-chemical exposures estimated using principal component analysis. Four factors were identified including: paraben; paraben metabolites and BPA, phenols, and UV filters. Models were adjusted for creatinine, age, race, and body mass index and weighted with inverse probability of exposure weights to account for time varying confounding. RESULTS In single-chemical models, 3,4-DHB was associated with estradiol (0.06 (95% confidence interval (CI): 0.001, 0.12)), 2-4-DCP with increased progesterone 0.14 (0.06, 0.21) and decreased FSH -0.08 (-0.11, -0.04), and 4-HB was associated with increased FSH 0.07 (0.01, 0.13). In multi-chemical models, all factors were associated with increased progesterone (beta coefficient range: 0.15 for UV filter factor to 0.32 for paraben factor). The paraben factor and the paraben metabolite and BPA factor were associated with increased estradiol [0.21 (0.15, 0.28); 0.12 (0.07, 0.18)]. The phenol and UV filter factors were associated with decreased estradiol, FSH, and LH. The UV filter factor showed the strongest inverse association with estradiol -0.16 (-0.22, -0.10), FSH -0.12 (-0.17, -0.07), and LH -0.17 (-0.23, -0.10). CONCLUSION Mixtures of phenols were associated with changes in reproductive hormones. Such changes could contribute to adverse health in women but additional research is necessary.

Alcohol retail sales licenses and sexually transmitted infections in Texas counties, 2008-2015

ABSTRACT Background: Research suggests that reduced retail alcohol outlet density may be associated with lower prevalence of HIV and other sexually transmitted infections (STIs). On-premise sale of alcohol for immediate consumption is theorized as increasing social interactions that can lead to sexual encounters. Objective: We examined associations between on- and off-premise retail alcohol sales licenses and number of newly diagnosed HIV and STI cases in Texas counties. Methods: Retail alcohol sales license data were obtained from the Texas Alcoholic Beverage Commission. HIV and bacterial STI data were obtained from the Texas Department of State Health Services. Associations between retail alcohol sales licenses and STIs were estimated using spatial linear models and Poisson mixed effects models for over-dispersed count data. Results: Adjusting for county-specific confounders, there was no evidence of residual spatial correlation. In Poisson models, each additional on-premise (e.g., bar and restaurant) alcohol license per 10,000 population in a county was associated with a 1.5% increase (95% CI: 0.4%, 2.6%) in the rate of HIV and a 2.4% increase (95% CI: 1.9%, 3.0%) in the rate of bacterial STIs, adjusting for potential confounders. In contrast, number of off-premise licenses (e.g., take-out stores) was inversely associated with the incidence of STI and HIV, although the association with HIV was not statistically significant. Conclusions: This study adds to the limited literature on the association between retail alcohol availability and STIs. Additional research is needed on the role of alcohol availability (and policies affecting availability) in the spread of HIV and other STIs.