Estimating Acute Cardiovascular Effects of Ambient PM2.5 Metals

BACKGROUND

Few epidemiologic studies have investigated health effects of water-soluble fractions of PM_2.5 metals, the more biologically accessible fractions of metals, in their attempt to identify health-relevant components of ambient PM_2.5.

OBJECTIVES

In this study, we estimated acute cardiovascular effects of PM_2.5 components in an urban population, including a suite of water-soluble metals that are not routinely measured at the ambient level.

METHODS

Ambient concentrations of criteria gases, PM_2.5, and PM_2.5 components were measured at a central monitor in Atlanta, Georgia, during 1998-2013, with some PM_2.5 components only measured during 2008-2013. In a time-series framework using Poisson regression, we estimated associations between these pollutants and daily counts of emergency department (ED) visits for cardiovascular diseases in the five-county Atlanta area.

RESULTS

Among the PM_2.5 components we examined during 1998-2013, water-soluble iron had the strongest estimated effect on cardiovascular outcomes [R͡R=1.012 (95% CI: 1.005, 1.019), per interquartile range increase (20.46ng/m³)]. The associations for PM_2.5 and other PM_2.5 components were consistent with the null when controlling for water-soluble iron. Among PM_2.5 components that were only measured during 2008-2013, water-soluble vanadium was associated with cardiovascular ED visits [R͡R=1.012 (95% CI: 1.000, 1.025), per interquartile range increase (0.19ng/m³)].

CONCLUSIONS

Our study suggests cardiovascular effects of certain water-soluble metals, particularly water-soluble iron. The observed associations with water-soluble iron may also point to certain aspects of traffic pollution, when processed by acidifying sulfate, as a mixture harmful for cardiovascular health. https://doi.org/10.1289/EHP2182.

Modeling the potential health benefits of lower household air pollution after a hypothetical liquified petroleum gas (LPG) cookstove intervention

INTRODUCTION

Improved biomass and advanced fuel cookstoves can lower household air pollution (HAP), but levels of fine particulate matter (PM_2.5) often remain above the World Health Organization (WHO) recommended interim target of 35μg/m³.

METHODS

Based on existing literature, we first estimate a range of likely levels of personal PM_2.5 before and after a liquefied petroleum gas (LPG) intervention. Using simulations reflecting uncertainty in both the exposure estimates and exposure-response coefficients, we estimate corresponding expected health benefits for systolic blood pressure (SBP) in adults, birthweight, and pneumonia incidence among children <2years old. We also estimate potential avoided premature mortality among those exposed.

RESULTS

Our best estimate is that an LPG stove intervention would decrease personal PM_2.5 exposure from approximately 270μg/m³ to approximately 70μg/m³, due to likely continued use of traditional open-fire stoves. We estimate that this decrease would lead to a 5.5mmHg lower SBP among women over age 50, a 338g higher birthweight, and a 37% lower incidence of severe childhood pneumonia. We estimate that decreased SBP, if sustained, would result in a 5%-10% decrease in mortality for women over age 50. We estimate that higher birthweight would reduce infant mortality by 4 to 11 deaths per 1000 births; for comparison, the current global infant mortality rate is 32/1000 live births. Reduced exposure is estimated to prevent approximately 29 cases of severe pneumonia per year per 1000 children under 2, avoiding approximately 2-3 deaths/1000 per year. However, there are large uncertainties around all these estimates due to uncertainty in both exposure estimates and in exposure-response coefficients; all health effect estimates include the null value of no benefit.

CONCLUSIONS

An LPG stove intervention, while not likely to lower exposure to the WHO interim target level, is still likely to offer important health benefits.

Erratum: Associations between Ambient Fine Particulate Oxidative Potential and Cardiorespiratory Emergency Department Visits

[This corrects the article DOI: 10.1289/EHP1545.].

The impact of climate change and emissions control on future ozone levels: Implications for human health

Overwhelming evidence has shown that, from the Industrial Revolution to the present, human activities influence ground-level ozone (O3) concentrations. Past studies demonstrate links between O3 exposure and health. However, knowledge gaps remain in our understanding concerning the impacts of climate change mitigation policies on O3 concentrations and health. Using a hybrid downscaling approach, we evaluated the separate impact of climate change and emission control policies on O3 levels and associated excess mortality in the US in the 2050s under two Representative Concentration Pathways (RCPs). We show that, by the 2050s, under RCP4.5, increased O3 levels due to combined climate change and emission control policies, could contribute to an increase of approximately 50 premature deaths annually nationwide in the US. The biggest impact, however, is seen under RCP8.5, where rises in O3 concentrations are expected to result in over 2,200 additional premature deaths annually. The largest increases in O3 are seen in RCP8.5 in the Northeast, the Southeast, the Central, and the West regions of the US. Additionally, when O3 increases are examined by climate change and emissions contributions separately, the benefits of emissions mitigation efforts may significantly outweigh the effects of climate change mitigation policies on O3-related mortality.

Associations between Ambient Fine Particulate Oxidative Potential and Cardiorespiratory Emergency Department Visits

BACKGROUND

Oxidative potential (OP) has been proposed as a measure of toxicity of ambient particulate matter (PM).

OBJECTIVES

Our goal was to address an important research gap by using daily OP measurements to conduct population-level analysis of the health effects of measured ambient OP.

METHODS

A semi-automated dithiothreitol (DTT) analytical system was used to measure daily average OP (OP^DTT) in water-soluble fine PM at a central monitor site in Atlanta, Georgia, over eight sampling periods (a total of 196 d) during June 2012-April 2013. Data on emergency department (ED) visits for selected cardiorespiratory outcomes were obtained for the five-county Atlanta metropolitan area. Poisson log-linear regression models controlling for temporal confounders were used to conduct time-series analyses of the relationship between daily counts of ED visits and either the 3-d moving average (lag 0-2) of OP^DTT or same-day OP^DTT. Bipollutant regression models were run to estimate the health associations of OP^DTT while controlling for other pollutants.

RESULTS

OP^DTT was measured for 196 d (mean=0.32 nmol/min/m³, interquartile range=0.21). Lag 0-2 OP^DTT was associated with ED visits for respiratory disease (RR=1.03, 95% confidence interval (CI): 1.00, 1.05 per interquartile range increase in OP^DTT), asthma (RR=1.12, 95% CI: 1.03, 1.22), and ischemic heart disease (RR=1.19, 95% CI: 1.03, 1.38). Same-day OP^DTT was not associated with ED visits for any outcome. Lag 0-2 OP^DTT remained a significant predictor of asthma and ischemic heart disease in most bipollutant models.

CONCLUSIONS

Lag 0-2 OP^DTT was associated with ED visits for multiple cardiorespiratory outcomes, providing support for the utility of OP^DTT as a measure of fine particle toxicity. https://doi.org/10.1289/EHP1545.

The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition

Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM2.5) concentrations in support of air pollution health effects research and air quality assessment at the urban to global scales. However, a large proportion, ~70%, of satellite observations of aerosols are missing as a result of cloud-cover, surface brightness, and snow-cover. The resulting PM2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM2.5 concentrations through complex chemical and physical processes. We developed a series of statistical models using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product at 1 km resolution with information from the MODIS cloud product and meteorological information to investigate the extent to which cloud parameters and associated meteorological conditions impact ground-level aerosols at two urban sites in the US: Atlanta and San Francisco. We find that changes in temperature, wind speed, relative humidity, planetary boundary layer height, convective available potential energy, precipitation, cloud effective radius, cloud optical depth, and cloud emissivity are associated with changes in PM2.5 concentration and composition, and the changes differ by overpass time and cloud phase as well as between the San Francisco and Atlanta sites. A case-study at the San Francisco site confirmed that accounting for cloud-cover and associated meteorological conditions could substantially alter the spatial distribution of monthly ground-level PM2.5 concentrations.

Bridging of double-stranded breaks by the nonhomologous end-joining ligation complex is modulated by DNA end chemistry

The nonhomologous end-joining (NHEJ) pathway is the primary repair pathway for DNA double strand breaks (DSBs) in humans. Repair is mediated by a core complex of NHEJ factors that includes a ligase (DNA Ligase IV; L4) that relies on juxtaposition of 3΄ hydroxyl and 5΄ phosphate termini of the strand breaks for catalysis. However, chromosome breaks arising from biological sources often have different end chemistries, and how these different end chemistries impact the way in which the core complex directs the necessary transitions from end pairing to ligation is not known. Here, using single-molecule FRET (smFRET), we show that prior to ligation, differences in end chemistry strongly modulate the bridging of broken ends by the NHEJ core complex. In particular, the 5΄ phosphate group is a recognition element for L4 and is critical for the ability of NHEJ factors to promote stable pairing of ends. Moreover, other chemical incompatibilities, including products of aborted ligation, are sufficient to disrupt end pairing. Based on these observations, we propose a mechanism for iterative repair of DSBs by NHEJ.

Stepped-wedge cluster-randomised controlled trial to assess the cardiovascular health effects of a managed aquifer recharge initiative to reduce drinking water salinity in southwest coastal Bangladesh: study design and rationale

INTRODUCTION

Saltwater intrusion and salinisation have contributed to drinking water scarcity in many coastal regions globally, leading to dependence on alternative sources for water supply. In southwest coastal Bangladesh, communities have few options but to drink brackish groundwater which has been associated with high blood pressure among the adult population, and pre-eclampsia and gestational hypertension among pregnant women. Managed aquifer recharge (MAR), the purposeful recharge of surface water or rainwater to aquifers to bring hydrological equilibrium, is a potential solution for salinity problem in southwest coastal Bangladesh by creating a freshwater lens within the brackish aquifer. Our study aims to evaluate whether consumption of MAR water improves human health, particularly by reducing blood pressure among communities in coastal Bangladesh.

METHODS AND ANALYSIS

The study employs a stepped-wedge cluster-randomised controlled community trial design in 16 communities over five monthly visits. During each visit, we will collect data on participants' source of drinking and cooking water and measure the salinity level and electrical conductivity of household stored water. At each visit, we will also measure the blood pressure of participants ≥20 years of age and pregnant women and collect urine samples for urinary sodium and protein measurements. We will use generalised linear mixed models to determine the association of access to MAR water on blood pressure of the participants.

ETHICS AND DISSEMINATION

The study protocol has been reviewed and approved by the Institutional Review Boards of the International Centre for Diarrheal Disease Research, Bangladesh (icddr,b). Informed written consent will be taken from all the participants. This study is funded by Wellcome Trust, UK. The study findings will be disseminated to the government partners, at research conferences and in peer-reviewed journals.

TRIAL REGISTRATION NUMBER

NCT02746003; Pre-results.

Chronic PM2.5 exposure and risk of infant bronchiolitis and otitis media clinical encounters

Chronic particulate matter less than 2.5μm in diameter (PM_2.5) exposure can leave infants more susceptible to illness. Our objective is to estimate associations of the chronic PM_2.5 exposure with infant bronchiolitis and otitis media (OM) clinical encounters. We obtained all first time bronchiolitis (n=18,029) and OM (n=40,042) clinical encounters among children less than 12 and 36 months of age, respectively, diagnosed from 2001 to 2009 and two controls per case matched on birthdate and gestational age from the Pregnancy to Early Life Longitudinal data linkage system in Massachusetts. We applied conditional logistic regression to estimate odds ratios (OR) and confidence intervals (CI) per 2-μg/m³ increase in lifetime average satellite based PM_2.5 exposure_. Effect modification was assessed by age, gestational age, frequency of clinical encounter, and income. We examined associations between residential distance to roadways, traffic density, and infant bronchiolitis and OM risk. PM_2.5 was not associated with infant bronchiolitis (OR=1.02, 95% CI=1.00, 1.04) and inversely associated with OM (OR=0.97, 95% CI=0.95, 0.99). There was no evidence of effect modification. Compared to infants living near low traffic density, infants residing in high traffic density had elevated risk of bronchiolitis (OR=1.23, 95% CI=1.14, 1.31) but not OM (OR=0.98, 95% CI=0.93, 1.02) clinical encounter. We did not find strong evidence to support an association between early-life long-term PM_2.5 exposure and infant bronchiolitis or OM. Bronchiolitis risk was increased among infants living near high traffic density.

Evaluation of individual and area-level factors as modifiers of the association between warm-season temperature and pediatric asthma morbidity in Atlanta, GA

INTRODUCTION

Previous studies have found associations between respiratory morbidity and high temperatures; however, few studies have explored associations in potentially sensitive sub-populations.

METHODS

We evaluated individual and area-level factors as modifiers of the association between warm-season (May-Sept.) temperature and pediatric respiratory morbidity in Atlanta. Emergency department (ED) visit data were obtained for children, 5-18 years old, with primary diagnoses of asthma or respiratory disease (diagnoses of upper respiratory infections, bronchiolitis, pneumonia, chronic obstructive pulmonary disease, asthma, or wheeze) in 20-county Atlanta during 1993-2012. Daily maximum temperature (Tmax) was acquired from the automated surface observing station at Atlanta Hartsfield International Airport. Poisson generalized linear models were used to estimate rate ratios (RR) between daily Tmax and asthma or respiratory disease ED visits, controlling for time and meteorology. Tmax effects were estimated for single-day lags of 0-6 days, for 3-, 5-, and 7-day moving averages and modeled with cubic terms to allow for non-linear relationships. Effect modification by individual factors (sex, race, insurance status) and area-level socioeconomic status (SES; ZIP code levels of poverty, education, and the neighborhood deprivation index) was examined via stratification.

RESULTS

Estimated RRs for Tmax and pediatric asthma ED visits were positive and significant for lag days 1-5, with the strongest single day association observed on lag day 2 (RR=1.06, 95% CI: 1.03, 1.09) for a change in Tmax from 27°C to 32°C (25th to 75th percentile). For the moving average exposure periods, associations increased as moving average periods increased. We observed stronger RRs between Tmax and asthma among males compared to females, non-white children compared to white children, children with private insurance compared to children with Medicaid, and among children living in high compared to low SES areas. Associations between Tmax and respiratory disease ED visits were weak and non-significant (p-value>0.05).

CONCLUSIONS

Results suggest socio-demographic factors (race/ethnicity, insurance status, and area-level SES) may confer vulnerability to temperature-related pediatric asthma morbidity. Our findings of weaker associations among children with Medicaid compared to other health insurance types and among children living in low compared to high SES areas run counter to our belief that children from disadvantaged households or ZIP codes would be more vulnerable to the respiratory effects of temperature. The potential reasons for these unexpected results are explored in the discussion.

Time-series Analysis of Heat Waves and Emergency Department Visits in Atlanta, 1993 to 2012

BACKGROUND

Heat waves are extreme weather events that have been associated with adverse health outcomes. However, there is limited knowledge of heat waves' impact on population morbidity, such as emergency department (ED) visits.

OBJECTIVES

We investigated associations between heat waves and ED visits for 17 outcomes in Atlanta over a 20-year period, 1993-2012.

METHODS

Associations were estimated using Poisson log-linear models controlling for continuous air temperature, dew-point temperature, day of week, holidays, and time trends. We defined heat waves as periods of consecutive days with temperatures beyond the 98th percentile of the temperature distribution over the period from 1945-2012. We considered six heat wave definitions using maximum, minimum, and average air temperatures and apparent temperatures. Associations by heat wave characteristics were examined.

RESULTS

Among all outcome-heat wave combinations, associations were strongest between ED visits for acute renal failure and heat waves defined by maximum apparent temperature at lag 0 [relative risk (RR) = 1.15; 95% confidence interval (CI): 1.03-1.29], ED visits for ischemic stroke and heat waves defined by minimum temperature at lag 0 (RR = 1.09; 95% CI: 1.02-1.17), and ED visits for intestinal infection and heat waves defined by average temperature at lag 1 (RR = 1.10; 95% CI: 1.00-1.21). ED visits for all internal causes were associated with heat waves defined by maximum temperature at lag 1 (RR = 1.02; 95% CI: 1.00, 1.04).

CONCLUSIONS

Heat waves can confer additional risks of ED visits beyond those of daily air temperature, even in a region with high air-conditioning prevalence. https://doi.org/10.1289/EHP44.

Ozone and childhood respiratory disease in three US cities: evaluation of effect measure modification by neighborhood socioeconomic status using a Bayesian hierarchical approach

BACKGROUND

Ground-level ozone is a potent airway irritant and a determinant of respiratory morbidity. Susceptibility to the health effects of ambient ozone may be influenced by both intrinsic and extrinsic factors, such as neighborhood socioeconomic status (SES). Questions remain regarding the manner and extent that factors such as SES influence ozone-related health effects, particularly across different study areas.

METHODS

Using a 2-stage modeling approach we evaluated neighborhood SES as a modifier of ozone-related pediatric respiratory morbidity in Atlanta, Dallas, & St. Louis. We acquired multi-year data on emergency department (ED) visits among 5-18 year olds with a primary diagnosis of respiratory disease in each city. Daily concentrations of 8-h maximum ambient ozone were estimated for all ZIP Code Tabulation Areas (ZCTA) in each city by fusing observed concentration data from available network monitors with simulations from an emissions-based chemical transport model. In the first stage, we used conditional logistic regression to estimate ZCTA-specific odds ratios (OR) between ozone and respiratory ED visits, controlling for temporal trends and meteorology. In the second stage, we combined ZCTA-level estimates in a Bayesian hierarchical model to assess overall associations and effect modification by neighborhood SES considering categorical and continuous SES indicators (e.g., ZCTA-specific levels of poverty). We estimated ORs and 95% posterior intervals (PI) for a 25 ppb increase in ozone.

RESULTS

The hierarchical model combined effect estimates from 179 ZCTAs in Atlanta, 205 ZCTAs in Dallas, and 151 ZCTAs in St. Louis. The strongest overall association of ozone and pediatric respiratory disease was in Atlanta (OR = 1.08, 95% PI: 1.06, 1.11), followed by Dallas (OR = 1.04, 95% PI: 1.01, 1.07) and St. Louis (OR = 1.03, 95% PI: 0.99, 1.07). Patterns of association across levels of neighborhood SES in each city suggested stronger ORs in low compared to high SES areas, with some evidence of non-linear effect modification.

CONCLUSIONS

Results suggest that ozone is associated with pediatric respiratory morbidity in multiple US cities; neighborhood SES may modify this association in a non-linear manner. In each city, children living in low SES environments appear to be especially vulnerable given positive ORs and high underlying rates of respiratory morbidity.

Design and rationale of a matched cohort study to assess the effectiveness of a combined household-level piped water and sanitation intervention in rural Odisha, India

INTRODUCTION

Government efforts to address massive shortfalls in rural water and sanitation in India have centred on construction of community water sources and toilets for selected households. However, deficiencies with water quality and quantity at the household level and community coverage and actual use of toilets have led Gram Vikas, a local non-governmental organization in Odisha, India, to develop an approach that provides household-level piped water connections contingent on full community-level toilet coverage.

METHODS

This matched cohort study was designed to assess the effectiveness of a combined piped water and sanitation intervention. Households with children <5 years in 45 randomly selected intervention villages and 45 matched control villages will be followed over 17 months. The primary outcome is prevalence of diarrhoeal diseases; secondary health outcomes include soil-transmitted helminth infection, nutritional status, seroconversion to enteric pathogens, urogenital infections and environmental enteric dysfunction. In addition, intervention effects on sanitation and water coverage, access and use, environmental fecal contamination, women's empowerment, as well as collective efficacy, and intervention cost and cost-effectiveness will be assessed.

ETHICS AND DISSEMINATION

The study protocol has been reviewed and approved by the ethics boards of the London School of Hygiene and Tropical Medicine, UK and KIIT University, Bhubaneswar, India. Findings will be disseminated via peer-reviewed literature and presentation to stakeholders, government officials, implementers and researchers.

TRIAL REGISTRATION NUMBER

NCT02441699.

Daily estimation of ground-level PM2.5 concentrations at 4km resolution over Beijing-Tianjin-Hebei by fusing MODIS AOD and ground observations

The satellite-borne Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) is widely used to estimate ground-level fine ambient particulate matter (PM_2.5) concentrations to evaluate their health effects. The associated estimation accuracy is often reduced by AOD missing values and by insufficiently accounting for the spatio-temporal PM_2.5 variations. In this study, we aim to estimate ground-level PM_2.5 concentrations at a fine resolution with improved accuracy by fusing fine-scale satellite and ground observations in the populated and polluted Beijing-Tianjin-Hebei (BTH) area of China in 2014. We employed a Bayesian-based statistical downscaler to model the spatio-temporal linear AOD-PM_2.5 relationships. We used a 3km MODIS AOD product, which was resampled to a 4km resolution in a Lambert conic conformal projection, to assist comparison and fusion with predictions by atmospheric chemistry models. A two-step method was used to fill the missing AOD values to obtain a full AOD dataset with complete spatial coverage. The downscaler has a good performance in the fitting procedure (R²=0.75) and in the cross validation procedure (R²=0.58 by random method and R²=0.47 by city-specific method). The number of missing AOD values was serious and related to elevated PM_2.5 concentrations. The gap-filled AOD values corresponded well with our understanding of PM_2.5 pollution conditions in BTH. The prediction accuracy of PM_2.5 concentrations were improved in terms of their annual and seasonal mean. As a result of its fine spatio-temporal resolution and complete spatial coverage, the daily PM_2.5 estimation dataset could provide extensive and insightful benefits to related studies in the BTH area. This may include understanding the formation processes of regional PM_2.5 pollution episodes, evaluating daily human exposure, and establishing pollution controlling measures.

A Bioequivalence Test by the Direct Comparison of Concentration-versus-Time Curves Using Local Polynomial Smoothers

In order to test if two chemically or pharmaceutically equivalent products have the same efficacy and/or toxicity, a bioequivalence (BE) study is conducted. The 80%/125% rule is the most commonly used criteria for BE and states that BE cannot be claimed unless the 90% CIs for the ratio of selected pharmacokinetics (PK) parameters of the tested to the reference drug are within 0.8 to 1.25. Considering that estimates of these PK parameters are derived from the concentration-versus-time curves, a direct comparison between these curves motivates an alternative and more flexible approach to test BE. Here, we propose to frame the BE test in terms of an equivalence of concentration-versus-time curves which are constructed using local polynomial smoother (LPS). A metric is presented to quantify the distance between the curves and its 90% CIs are calculated via bootstrapping. Then, we applied the proposed procedures to data from an animal study and found that BE between a generic drug and its brand name cannot be concluded, which was consistent with the results by applying the 80%/125% rule. However, the proposed procedure has the advantage of testing only on a single metric, instead of all PK parameters.

A simulation study to quantify the impacts of exposure measurement error on air pollution health risk estimates in copollutant time-series models

BACKGROUND

Exposure measurement error in copollutant epidemiologic models has the potential to introduce bias in relative risk (RR) estimates. A simulation study was conducted using empirical data to quantify the impact of correlated measurement errors in time-series analyses of air pollution and health.

METHODS

ZIP-code level estimates of exposure for six pollutants (CO, NO_x, EC, PM_2.5, SO₄, O₃) from 1999 to 2002 in the Atlanta metropolitan area were used to calculate spatial, population (i.e. ambient versus personal), and total exposure measurement error. Empirically determined covariance of pollutant concentration pairs and the associated measurement errors were used to simulate true exposure (exposure without error) from observed exposure. Daily emergency department visits for respiratory diseases were simulated using a Poisson time-series model with a main pollutant RR = 1.05 per interquartile range, and a null association for the copollutant (RR = 1). Monte Carlo experiments were used to evaluate the impacts of correlated exposure errors of different copollutant pairs.

RESULTS

Substantial attenuation of RRs due to exposure error was evident in nearly all copollutant pairs studied, ranging from 10 to 40% attenuation for spatial error, 3-85% for population error, and 31-85% for total error. When CO, NO_x or EC is the main pollutant, we demonstrated the possibility of false positives, specifically identifying significant, positive associations for copollutants based on the estimated type I error rate.

CONCLUSIONS

The impact of exposure error must be considered when interpreting results of copollutant epidemiologic models, due to the possibility of attenuation of main pollutant RRs and the increased probability of false positives when measurement error is present.

Assessing the Association between Thermotolerant Coliforms in Drinking Water and Diarrhea: An Analysis of Individual-Level Data from Multiple Studies

BACKGROUND

Fecally contaminated drinking water is believed to be a major contributor to the global burden of diarrheal disease and a leading cause of mortality among young children. However, recent systematic reviews and results from blinded studies of water quality interventions have raised questions about the risk associated with fecally contaminated water, particularly as measured by thermotolerant coliform (TTC) bacteria, a WHO-approved indicator of drinking water quality.

OBJECTIVES

We investigated the association between TTC in drinking water and diarrhea using data from seven previous studies.

METHODS

We obtained individual-level data from available field studies that measured TTC levels in household-drinking water and reported prevalence of diarrhea among household members during the days prior to the visit.

RESULTS

The combined data set included diarrhea prevalence for 26,518 individuals and 8,000 water samples from 4,017 households, yielding 45,052 observations. The odds of diarrhea increased for each log10 increase in TTC/100 mL by 18% (95% CI: 11, 26%) for children < 5 years old and 12% (95% CI: 8, 18%) for all ages. For all ages, the odds of diarrhea increased by 21%, 35% and 49% for those whose household water samples were from 11-100, 101-1,000, and > 1,000 TTC/100 mL, respectively compared to < 1 TTC/100 mL. We found no evidence of increased odds of diarrhea with contamination levels below 11 TTC/100 mL, either in adults or children.

CONCLUSIONS

Our analysis of individual-level data shows increased risk of diarrhea with increasing levels of TTC in drinking water. These results suggest an association between fecally contaminated water and diarrheal disease and provides support for health-based targets for levels of TTC in drinking water and for interventions to improve drinking water quality to prevent diarrhea.

CITATION

Hodge J, Chang HH, Boisson S, Collin SM, Peletz R, Clasen T. 2016. Assessing the association between thermotolerant coliforms in drinking water and diarrhea: an analysis of individual level data from multiple studies. Environ Health Perspect 124:1560-1567; http://dx.doi.org/10.1289/EHP156.

Spatiotemporal hurdle models for zero-inflated count data: Exploring trends in emergency department visits

Motivated by a study exploring spatiotemporal trends in emergency department use, we develop a class of two-part hurdle models for the analysis of zero-inflated areal count data. The models consist of two components—one for the probability of any emergency department use and one for the number of emergency department visits given use. Through a hierarchical structure, the models incorporate both patient- and region-level predictors, as well as spatially and temporally correlated random effects for each model component. The random effects are assigned multivariate conditionally autoregressive priors, which induce dependence between the components and provide spatial and temporal smoothing across adjacent spatial units and time periods, resulting in improved inferences. To accommodate potential overdispersion, we consider a range of parametric specifications for the positive counts, including truncated negative binomial and generalized Poisson distributions. We adopt a Bayesian inferential approach, and posterior computation is handled conveniently within standard Bayesian software. Our results indicate that the negative binomial and generalized Poisson hurdle models vastly outperform the Poisson hurdle model, demonstrating that overdispersed hurdle models provide a useful approach to analyzing zero-inflated spatiotemporal data.

Weighted-SAMGSR: combining significance analysis of microarray-gene set reduction algorithm with pathway topology-based weights to select relevant genes

BACKGROUND

It has been demonstrated that a pathway-based feature selection method that incorporates biological information within pathways during the process of feature selection usually outperforms a gene-based feature selection algorithm in terms of predictive accuracy and stability. Significance analysis of microarray-gene set reduction algorithm (SAMGSR), an extension to a gene set analysis method with further reduction of the selected pathways to their respective core subsets, can be regarded as a pathway-based feature selection method.

METHODS

In SAMGSR, whether a gene is selected is mainly determined by its expression difference between the phenotypes, and partially by the number of pathways to which this gene belongs. It ignores the topology information among pathways. In this study, we propose a weighted version of the SAMGSR algorithm by constructing weights based on the connectivity among genes and then combing these weights with the test statistics.

RESULTS

Using both simulated and real-world data, we evaluate the performance of the proposed SAMGSR extension and demonstrate that the weighted version outperforms its original version. CONCLUSIONS: To conclude, the additional gene connectivity information does faciliatate feature selection.

REVIEWERS

This article was reviewed by Drs. Limsoon Wong, Lev Klebanov, and, I. King Jordan.

Assessment of neighbourhood-level socioeconomic status as a modifier of air pollution-asthma associations among children in Atlanta

BACKGROUND

A broad literature base provides evidence of association between air pollution and paediatric asthma. Socioeconomic status (SES) may modify these associations; however, previous studies have found inconsistent evidence regarding the role of SES.

METHODS

Effect modification of air pollution-paediatric asthma morbidity by multiple indicators of neighbourhood SES was examined in Atlanta, Georgia. Emergency department (ED) visit data were obtained for 5-18 years old with a diagnosis of asthma in 20-county Atlanta during 2002-2008. Daily ZIP Code Tabulation Area (ZCTA)-level concentrations of ozone, nitrogen dioxide, fine particulate matter and elemental carbon were estimated using ambient monitoring data and emissions-based chemical transport model simulations. Pollutant-asthma associations were estimated using a case-crossover approach, controlling for temporal trends and meteorology. Effect modification by ZCTA-level (neighbourhood) SES was examined via stratification.

RESULTS

We observed stronger air pollution-paediatric asthma associations in 'deprivation areas' (eg, ≥20% of the ZCTA population living in poverty) compared with 'non-deprivation areas'. When stratifying analyses by quartiles of neighbourhood SES, ORs indicated stronger associations in the highest and lowest SES quartiles and weaker associations among the middle quartiles.

CONCLUSIONS

Our results suggest that neighbourhood-level SES is a factor contributing vulnerability to air pollution-related paediatric asthma morbidity in Atlanta. Children living in low SES environments appear to be especially vulnerable given positive ORs and high underlying asthma ED rates. Inconsistent findings of effect modification among previous studies may be partially explained by choice of SES stratification criteria, and the use of multiplicative models combined with differing baseline risk across SES populations.

Ambient air pollution epidemiology systematic review and meta-analysis: A review of reporting and methods practice

BACKGROUND

Systematic review and meta-analysis (SRMA) are increasingly employed in environmental health (EH) epidemiology and, provided methods and reporting are sound, contribute to translating science evidence to policy. Ambient air pollution (AAP) is both among the leading environmental causes of mortality and morbidity worldwide, and of growing policy relevance due to health co-benefits associated with greenhouse gas emissions reductions.

OBJECTIVES

We reviewed the published AAP SRMA literature (2009 to mid-2015), and evaluated the consistency of methods, reporting and evidence evaluation using a 22-point questionnaire developed from available best-practice consensus guidelines and emerging recommendations for EH. Our goal was to contribute to enhancing the utility of AAP SRMAs to EH policy.

RESULTS AND DISCUSSION

We identified 43 studies that used both SR and MA techniques to examine associations between the AAPs PM2.5, PM10, NO2, SO2, CO and O3, and various health outcomes. On average AAP SRMAs partially or thoroughly addressed 16 of 22 questions (range 10-21), and thoroughly addressed 13 of 22 (range 5-19). We found evidence of an improving trend over the period. However, we observed some weaknesses, particularly infrequent formal reviews of underlying study quality and risk-of-bias that correlated with lower frequency of thorough evaluation for key study quality parameters. Several other areas for enhanced reporting are highlighted.

CONCLUSIONS

The AAP SRMA literature, in particular more recent studies, indicate broad concordance with current and emerging best practice guidance. Development of an EH-specific SRMA consensus statement including a risk-of-bias evaluation tool, would be a contribution to enhanced reliability and robustness as well as policy utility.