Short-term exposure to air pollution and infant mortality: A systematic review and meta-analysis

BACKGROUND AND AIM

Infant mortality is a widely reported indicator of population health and a leading public health concern. In this systematic review and meta-analysis, we review the available literature for epidemiologic evidence of the association between short-term air pollution exposure and infant mortality.

METHODS

Relevant publications were identified through PubMed and Web of Science databases using comprehensive search terms and screened using predefined inclusion/exclusion criteria. We extracted data from included studies and applied a systematic rubric for evaluating study quality across domains including participant selection, outcome, exposure, confounding, analysis, selective reporting, sensitivity, and overall quality. We performed meta-analyses, using both fixed and random-effect methods, and estimated pooled odds ratios (ORs) and 95 % confidence intervals (95%CI) for pollutants (nitrogen dioxide (NO2), sulfur dioxide (SO2), coarse particulate matter (PM10), fine particulate matter (PM2.5), ozone (O3), carbon monoxide (CO)) and infant mortality, neonatal mortality, or postneonatal mortality.

RESULTS

Our search returned 549 studies. We excluded 490 studies in the abstract screening phase and an additional 37 studies in the full text screening phase, leaving 22 studies for inclusion. Among these 22 studies, 14 included effect estimates for PM10, 13 for O3, 11 for both NO2 and CO, 8 for SO2, and 3 for PM2.5. We did not calculate a pooled OR for PM2.5 due to the limited number of studies available and demonstrated heterogeneity in the effect estimates. The pooled ORs (95%CI) with the greatest magnitudes were for a 10-ppb increase in SO2 or NO2 concentration in the days before death (1.07 [95%CI: 1.02, 1.12], 1.04 [95%CI: 1.01, 1.08], respectively). The pooled OR for PM10 was 1.02 (95%CI: 1.00, 1.03), and the pooled ORs for CO and O3 were 1.01 (95%CI: 1.00, 1.02) and 0.99 (95%CI: 0.97, 1.01).

CONCLUSIONS

Increased exposure to SO2, NO2, PM10, or CO is associated with infant mortality across studies.

Identifying groups of children's social mobility opportunity for public health applications using k-means clustering

Background

The Opportunity Atlas project is a pioneering effort to trace social mobility and adulthood socioeconomic outcomes back to childhood residence. Half of the variation in adulthood socioeconomic outcomes was explainable by neighborhood-level socioeconomic characteristics during childhood. Clustering census tracts by Opportunity Atlas characteristics would allow for further exploration of variance in social mobility. Our objectives here are to identify and describe spatial clustering trends within Opportunity Atlas outcomes.

Methods

We utilized a k-means clustering machine learning approach with four outcome variables (individual income, incarceration rate, employment, and percent of residents living in a neighborhood with low levels of poverty) each given at five parental income levels (1st, 25th, 50th, 75th, and 100th percentiles of the national distribution) to create clusters of census tracts across the contiguous United States (US) and within each Environmental Protection Agency region.

Results

At the national level, the algorithm identified seven distinct clusters; the highest opportunity clusters occurred in the Northern Midwest and Northeast, and the lowest opportunity clusters occurred in rural areas of the Southwest and Southeast. For regional analyses, we identified between five to nine clusters within each region. PCA loadings fluctuate across parental income levels; income and low poverty neighborhood residence explain a substantial amount of variance across all variables, but there are differences in contributions across parental income levels for many components.

Conclusions

Using data from the Opportunity Atlas, we have taken four social mobility opportunity outcome variables each stratified at five parental income levels and created nationwide and EPA region-specific clusters that group together census tracts with similar opportunity profiles. The development of clusters that can serve as a combined index of social mobility opportunity is an important contribution of this work, and this in turn can be employed in future investigations of factors associated with children's social mobility.

Effect measure modification of the association between short-term exposures to PM2.5 and hospitalizations by longs-term PM2.5 exposure among a cohort of people with Chronic Obstructive Pulmonary Disease (COPD) in North Carolina, 2002-2015

BACKGROUND

Approximately nine million adults in the United States are living with chronic obstructive pulmonary disease (COPD), and positive associations between short-term air pollution exposure and increased risk of COPD hospitalizations in older adults are consistently reported. We examined the association between short-term PM2.5 exposure and hospitalizations and assessed if there is modification by long-term exposure in a cohort of individuals with COPD.

METHODS

In a time-referent case-crossover design, we used a cohort of randomly selected individuals with electronic health records from the University of North Carolina Healthcare System, restricted to patients with a medical encounter coded with a COPD diagnosis from 2004-2016 (n = 520), and estimated ambient PM2.5 concentrations from an ensemble model. Odds ratios and 95% confidence intervals (OR (95%CI)) were estimated with conditional logistic regression for respiratory-related, cardiovascular (CVD), and all-cause hospitalizations. Exposures examined were 0-2 and 0-3 day lags of PM2.5 concentration, adjusting for daily census-tract temperature and humidity, and models were stratified by long-term (annual average) PM2.5 concentration at the median value.

RESULTS

We observed generally null or low-magnitude negative associations with short-term PM2.5 exposure and respiratory-related (OR per 5 µg/m3 increase in 3-day lag PM2.5: 0.971 (0.885, 1.066)), CVD (2-day lag: 0.976 (0.900, 1.058) and all-cause (3 day lag: 1.003 (0.927, 1.086)) hospitalizations. Associations between short-term PM2.5 exposure and hospitalizations were higher among patients residing in areas with higher levels of annual PM2.5 concentrations (OR per 5 µg/m3 in 3-day lag PM2.5 for all-cause hospitalizations: 1.066 (0.958, 1.185)) than those in areas with lower annual PM2.5 concentrations (OR per 5 µg/m3 in 3-day lag PM2.5 for all-cause hospitalizations: 0.914 (0.804, 1.039)).

CONCLUISONS

Differences in associations demonstrate that people in areas with higher annual PM2.5 exposure may be associated with higher risk of hospitalization during short-term increases in PM2.5 exposure.

Interplay of gestational parent exposure to ambient air pollution and diet characteristics on preterm birth

BACKGROUND

Despite many efforts, preterm birth (PTB) is poorly understood and remains a major public health problem in the United States. Toxicological work suggests gestational parent (GP) diet may modify the effect of ambient pollutants on birth outcomes. We assessed risk of PTB in humans in relation to fine particulate matter (PM2.5), ozone (O3), and nitrogen dioxide (NO2) and variation by diet.

METHODS

684 GP-singleton infant pairs in the Newborn Epigenetics Study prospective birth cohort were attributed ambient air pollutant exposures for each trimester based on residence. Total energy intake, percent of energy intake from saturated fat, and percent of energy intake from total fat were dichotomized at the 75th percentile. >We used log binomial regressions to estimate risk ratios (RR (95%CI)) for PTB by pollutant interquartile ranges, adjusting for GP age, pre-pregnancy body mass index, GP race/ethnicity, GP education, season of conception, household income, and each diet factor. We assessed departure from additivity using interaction contrast ratios (ICRs). We addressed missing covariate data with multiple imputation.

RESULTS

Point estimates suggest that O3 may be inversely associated with PTB when exposure occurs in trimester 2 (min RR: 0.77, 95% CI: 0.39, 1.49), but may be harmful when exposure occurs in trimester 3 (max RR: 1.51, 95% CI: 0.62, 3.64). Additionally, PM2.5 may be inversely associated with PTB when considered with total fat and saturated fat in trimester 2. Imprecise ICRs suggest departure from additivity (evidence of modification) with some pollutant-diet combinations.

CONCLUSIONS

While confidence intervals are wide, we observed potential modification of pollutant associations by dietary factors. It is imperative that large cohorts collect the required data to examine this topic, as more power is necessary to investigate the nuances suggested by this work.

Systematic review and meta-analysis of birth weight and PFNA exposures

We used a systematic review that included risk of bias and study sensitivity analysis to identify 34 studies examining changes in birth weight (BWT) in relation to PFNA biomarker measures (e.g., maternal serum/plasma or umbilical cord samples). We fit a random effects model of the overall pooled estimate and stratified estimates based on sample timing and overall study confidence. We conducted a meta-regression to further examine the impact of gestational age at biomarker sample timing. We detected a -32.9 g (95%CI: -47.0, -18.7) mean BWT deficit per each ln PFNA increase from 27 included studies. We did not detect evidence of publication bias (p_E = 0.30) or between-study heterogeneity in the summary estimate (p_Q = 0.05; I² = 36%). The twelve high confidence studies yielded a smaller pooled effect estimate (β = -28.0 g; 95%CI: -49.0, -6.9) than the ten medium (β = -39.0 g; 95%CI: -61.8, -16.3) or four low (β = -36.9 g; 95%CI: -82.9, 9.1) confidence studies. The stratum-specific results based on earlier pregnancy sampling periods in 11 studies showed smaller deficits (β = -22.0 g; 95%CI: -40.1, -4.0) compared to 10 mid- and late-pregnancy (β = -44.2 g; 95%CI: -64.8, -23.5) studies and six post-partum studies (β = -42.9 g; 95%CI: -88.0, 2.2). Using estimates of the specific gestational week of sampling, the meta-regression showed results consistent with the categorical sample analysis, in that as gestational age at sampling time increases across these studies, the summary effect estimate of a mean BWT deficit got larger. Overall, we detected mean BWT deficits for PFNA that were larger and more consistent across studies than previous PFAS meta-analyses. Compared to studies with later sampling, BWT deficits were smaller but remained sizeable for even the earliest sampling periods. Contrary to earlier meta-analyses for PFOA and PFOS, BWT deficits that were detected across all strata did not appear to be fully explained by potential bias due to pregnancy hemodynamics from sampling timing differences.

Are the adverse health effects of air pollution modified among active children and adolescents? A review of the literature

Air pollution exposure is associated with negative health consequences among children and adolescents. Physical activity is recommended for all children/adolescents due to benefits to health and development. However, it is unclear if physically active children have additional protective benefits when exposed to higher levels of air pollution, compared to less active children. This systematic review evaluates all available literature since 2000 and examines if effect measure modification (EMM) exists between air pollution exposure and health outcomes among children/adolescents partaking in regular physical activity. PubMed, Science Direct, Scopus, Web of Science, and ProQuest Agricultural & Environmental Science databases were queried, identifying 2686 articles. Title/abstract screening and full-text review eliminated 2620 articles, and 56 articles were removed for evaluating individuals >21, leaving 10 articles for review. Of the included articles, half were conducted in China, three in the United States, and one each in Indonesia and Germany. Seven articles identified EMM between active children and air-pollution related health outcomes. Five of these indicated that children/adolescents do not experience any additional benefits from being physically active in higher levels of air pollution, with some studies implying active children may experience additional detriments, compared to less active children. However, the remaining two EMM studies highlighted modest benefits of having a higher activity level, even in polluted air. Overall, active children/adolescents may be at greater risk from air pollution exposure, but results were not consistent across all studies. Future studies assessing the intersection between air pollution and regular physical activity among children would be useful.

Beneficial Use Impairments, Degradation of Aesthetics, and Human Health: A Review

In environmental programs and blue/green space development, improving aesthetics is a common goal. There is broad interest in understanding the relationship between ecologically sound environments that people find aesthetically pleasing and human health. However, to date, few studies have adequately assessed this relationship, and no summaries or reviews of this line of research exist. Therefore, we undertook a systematic literature review to determine the state of science and identify critical needs to advance the field. Keywords identified from both aesthetics and loss of habitat literature were searched in PubMed and Web of Science databases. After full text screening, 19 studies were included in the review. Most of these studies examined some measure of greenspace/bluespace, primarily proximity. Only one study investigated the impacts of making space quality changes on a health metric. The studies identified for this review continue to support links between green space and various metrics of health, with additional evidence for blue space benefits on health. No studies to date adequately address questions surrounding the beneficial use impairment degradation of aesthetics and how improving either environmental quality (remediation) or ecological health (restoration) efforts have impacted the health of those communities.

A cross-sectional study of brownfields and birth defects

BACKGROUND

Brownfields are a multitude of abandoned and disused sites, spanning many former purposes. Brownfields represent a heterogenous yet ubiquitous exposure for many Americans, which may contain hazardous wastes and represent urban blight. Neonates and pregnant individuals are often sensitive to subtle environmental exposures. We evaluate whether residential brownfield exposure is associated with birth defects.

METHODS

Using North Carolina birth records from 2003 to 2015, we sampled 753,195 births with 39,495 defects identified. We examined defect groups and 30 distinct phenotypes. Number of brownfields within 2,000 m of the residential address at birth was summed. We utilized mixed effects multivariable logistic regression models adjusted for demographic and environmental covariates available from birth records, 2010 Census, and EPA's Environmental Quality Index to estimate odds ratios (OR) and 95% confidence intervals (CI).

RESULTS

We observed positive associations between cardiovascular and external defect groups (OR [95% CI]: 1.07 [1.02-1.13] and 1.17 [1.01-1.35], respectively) and any brownfield exposure. We also observed positive associations with atrial septal and ventricular septal defects (1.08 [1.01-1.16] and 1.15 [1.03-1.28], respectively), congenital cataracts (1.38 [0.98-1.96]), and an inverse association with gastroschisis (0.74 [0.58-0.94]). Effect estimates for several additional defects were positive, though we observed null associations for most group and individual defects. Additional analyses indicated an exposure-response relationship for several defects across levels of brownfield exposure.

CONCLUSIONS

Our results indicate that residential proximity to brownfields is associated with birth defects, especially cardiovascular and external defects. In-depth analyses of individual defects and specific contaminants or brownfield sites may reveal additional novel associations.

Increased risk of eosinophilic esophagitis with poor environmental quality as measured by the Environmental Quality Index

Geographic differences in eosinophilic esophagitis (EoE) prevalence suggest the possibility that environmental exposures contribute to EoE pathogenesis. We aimed to examine the association between environmental quality and risk of EoE, using the Environmental Quality Index (EQI), which provides quantification of environmental quality in five domains: air, land, water, built, and sociodemographic for all counties in the United States. To do this, we performed a case-control study in a large pathology database. EoE cases were defined by ≥15 eosinophils per high-power field with other pathologic diagnoses excluded; controls did not have EoE. The pathology data were geocoded and linked with the EQI by county of residence. Logistic regression was used to estimate odds ratio (OR and 95% confidence interval [CI]) of EoE with overall EQI and for each domain, after adjusting for sex, age, and proportion minority race or ethnicity at the county level (higher EQI score indicates worse environmental quality). Of 29,802 EoE cases and 593,329 controls analyzed, odds of EoE were highest in the worst quintile of EQI (OR 1.25; 95% CI: 1.04-1.50), which was largely explained by poor scores in the water domain (OR: 1.33; 1.17-1.50). Conversely, odds of EoE were reduced with higher scores in the air domain (OR: 0.87, 0.74-1.03) and land domain (OR 0.87; 0.76-0.99). Poor EQI, mostly reflected by poor water quality, was associated with increased odds of EoE, while poor air and land quality were inversely associated with EoE. Additional work to identify specific water pollutants that may have an etiologic role in EoE may be warranted.

Aggregated cumulative county arsenic in drinking water and associations with bladder, colorectal, and kidney cancers, accounting for population served

BACKGROUND

Many studies neglect to account for variation in population served by community water systems (CWSs) when aggregating CWS-level contaminant concentrations to county level.

OBJECTIVE

In an ecological epidemiologic analysis, we explored two methods-unweighted and weighted (proportion of CWS population served by county population)-to account for population served by CWS in association between arsenic and three cancers to determine the impact of population served on aggregated measures of exposure.

METHODS

CWS arsenic concentration data for 19 states were obtained from Centers for Disease Control and Prevention (CDC) National Environmental Public Health Tracking Network for 2000-10, aggregated to county level, and linked to county-level cancer data for 2011-5 from National Cancer Institute and CDC State Cancer Profiles. Negative binomial regression models estimated adjusted risk ratios (aRR) and 95% confidence intervals (CI) between county-level bladder, colorectal, and kidney cancers and quartiles of aggregated cumulative county-level arsenic concentration (ppb-years).

RESULTS

We observed positive associations between the highest quartile of exposure, compared to the lowest, of aggregated cumulative county-level arsenic concentration (ppb-year) for bladder [weighted aRR: 1.89(1.53, 2.35)], colorectal [1.64(1.33, 2.01)], and kidney [1.69(1.37, 2.09)] cancers. We observed stronger associations utilizing the weighted exposure assessment method. However, inferences from this study are limited due to the ecologic nature of the analyses and different analytic study designs are needed to assess the utility that the weighted by CWS population served metric has for exposure assessment.

SIGNIFICANCE

Weighting by CWS population served accounts for some potential exposure assignment error in epidemiologic analysis.

Exploration of PM mass, source, and component-related factors that might explain heterogeneity in daily PM2.5-mortality associations across the United States

Multi-city epidemiologic studies examining short-term (daily) differences in fine particulate matter (PM_2.5) provide evidence of substantial spatial heterogeneity in city-specific mortality risk estimates across the United States. Because PM_2.5 is a mixture of particles, both directly emitted from sources or formed through atmospheric reactions, some of this heterogeneity may be due to regional variations in PM_2.5 toxicity. Using inverse variance weighted linear regression, we examined change in percent change in mortality in association with 24 "exposure" determinants representing three basic groupings based on potential explanations for differences in PM toxicity - size, source, and composition. Percent changes in mortality for the PM_2.5-mortality association for 313 core-based statistical areas and their metropolitan divisions over 1999-2005 were used as the outcome. Several determinants were identified as potential contributors to heterogeneity: all mass fraction determinants, vehicle miles traveled (VMT) for diesel total, VMT gas per capita, PM_2.5 ammonium, PM_2.5 nitrate, and PM_2.5 sulfate. In multivariable models, only daily correlation of PM_2.5 with PM₁₀ and long-term average PM_2.5 mass concentration were retained, explaining approximately 10% of total variability. The results of this analysis contribute to the growing body of literature specifically focusing on assessing the underlying basis of the observed spatial heterogeneity in PM_2.5-mortality effect estimates, continuing to demonstrate that this heterogeneity is multifactorial and not attributable to a single aspect of PM.

Ozone exposure during early pregnancy and preterm birth: A systematic review and meta-analysis

Exposure to ozone has been linked to reproductive outcomes, including preterm birth. In this systematic review, we summarize published epidemiologic cohort and case-control studies examining ozone exposures (estimated on a continuous scale) in early pregnancy (1st and 2nd trimesters (T1, T2)) and preterm birth using ratio measures, and perform a meta-analysis to evaluate the potential relationship between them. Studies were identified by searching PubMed and Web of Science, screened according to predefined inclusion/exclusion criteria, and evaluated for study quality. We extracted study data including effect estimates, confidence limits, study location, study years, ozone exposure assessment method, and mean or median ozone concentrations. Nineteen studies were identified and included, of which 18 examined T1 exposure (17 reported effect estimates), and 15 examined T2 exposure. Random effects meta-analysis was performed in the metafor package, R 3.5.3. The pooled OR (95% CI) for a 10 ppb increase in ozone exposure in T1 was 1.06 (1.03, 1.10) with a 95% prediction interval of 0.95, 1.19; for T2 it was 1.05 (1.02, 1.08) with a 95% prediction interval of 0.95, 1.16. Effect estimates for both exposure periods showed high heterogeneity. In meta-regression analyses of study characteristics, study location (continent) explained some (~20%) heterogeneity for T1 exposure studies, but no characteristic explained a substantial amount of heterogeneity for T2 exposure studies. Increased ozone exposure during early pregnancy is associated with preterm birth across studies.

Estimating exposure to neighborhood crime by race and ethnicity for public health research

BACKGROUND

Police-reported crime data (hereafter "crime") is routinely used as a psychosocial stressor in public health research, yet few studies have jointly examined (a) differences in crime exposure based on participant race and ethnicity, (b) differences in measures of crime exposure, and (c) considerations for how exposure to police is captured in police-recorded crime data. We estimate neighborhood exposure to crime and discuss the implications of structural differences in exposure to crime and police based on race and ethnicity.

METHODS

Using GPS coordinates from 1188 participants in the Newborn Epigenetics Study, we estimated gestational exposure to crime provided by the Durham, North Carolina, Police Department within (a) 800 m and (b) the Census block group of residence. We controlled for non-overlapping spatial boundaries in crime, Census, residential, and police data to report crime spatial (crime per km2) and population (crime per 1000 people per km2) density.

RESULTS

We demonstrate dramatic disparities in exposure to crime based on participant race and ethnicity and highlight variability in these disparities based on the type of crime and crime measurement method chosen.

CONCLUSIONS

Public health researchers should give thoughtful consideration when using police-reported crime data to measure and model exposure to crime in the United States, as police-reported data encompasses joint exposure to police and crime in the neighborhood setting.

Associations between cumulative environmental quality and ten selected birth defects in Texas

BACKGROUND

Causes of most birth defects are largely unknown. Genetics, maternal factors (e.g., age, smoking) and environmental exposures have all been linked to some birth defects, including neural tube, oral cleft, limb reduction, and gastroschisis; however, the contribution of cumulative exposures across several environmental domains in association with these defects is not well understood.

METHODS

The Environmental Quality Index (EQI) and its domains (air, water, land, sociodemographic, built) were used to estimate county-level cumulative environmental exposures from 2006-2010 and matched to birth defects identified from Texas Birth Defects Registry and live birth records from births in years 2007-2010 (N = 1,610,709). Poisson regression models estimated prevalence ratios (PR) and 95% confidence intervals (CI) for associations between 10 birth defects and the EQI.

RESULTS

We observed some positive associations between worst environmental quality and neural tube, anencephaly, spina bifida, oral cleft, cleft palate, cleft lip with and without cleft palate, and gastroschisis [PR range: 1.12-1.55], but near null associations with limb reduction defects. Among domain specific results, we observed the strongest positive associations with the sociodemographic domain across birth defects but varied positive associations among the air and water domains, and negative or null associations with the land and built domains. Overall, few exposure-response patterns were evident.

CONCLUSIONS

Our results highlight the complexities of cumulative, simultaneous environmental exposures in the prevalence rates of 10 selected birth defects. We were able to explore the impact of overall and domain specific environmental quality on birth defects and identify potential domain specific drivers of these associations.

A case-crossover analysis of the relationship of air pollution with out-of-hospital sudden unexpected death in Wake County, North Carolina (2013-2015)

Out-of-hospital sudden unexpected deaths are non-accidental deaths that occur without obvious underlying causes and may account for 10% of natural deaths before age 65. Short-term exposure to ambient air pollution is associated with all-cause (non-accidental) and cause-specific (e.g., cardiovascular) mortality, and with immediate exposures often yielding the highest magnitude risk estimates. Few studies have focused on short-term exposure to air pollution and sudden unexpected deaths. Using the University of North Carolina Sudden Unexpected Death in North Carolina population, we examine associations between short-term criteria air pollutant exposures with sudden unexpected deaths using a time-stratified case-crossover design, with data on criteria air pollutants from the Environmental Protection Agency's Air Quality System. Odds ratios (OR) and 95% confidence intervals (CI) were estimated using conditional logistic regression with air pollutant exposures scaled to roughly inter-quartile ranges; models were adjusted for average temperature and relative humidity on event day and preceding 3 days. Potential for confounding by co-pollutants were examined in two pollutant models. ORs for PM_2.5 at lag day 1 were elevated (adjusted OR for 5 μg/m³ increase: 1.17 (0.98, 1.40)), and were robust to co-pollutant adjustment. Elevated odds were observed for SO₂ at lag day 0, and reduced odds for O₃ at lag day 0; however, these associations were somewhat attenuated toward the null (SO₂) or were not robust (O₃) to co-pollutant adjustment. This analysis in a racially and socioeconomically diverse cohort, with a more inclusive definition of sudden unexpected death than is typically employed offers evidence that PM_2.5 may be a clinically relevant trigger of sudden unexpected deaths in susceptible individuals.

Maternal residential exposure to specific agricultural pesticide active ingredients and birth defects in a 2003-2005 North Carolina birth cohort

BACKGROUND

Previously we observed elevated odds ratios (ORs) for total pesticide exposure and 10 birth defects: three congenital heart defects and structural defects affecting the gastrointestinal, genitourinary and musculoskeletal systems. This analysis examines association of those defects with exposure to seven commonly applied pesticide active ingredients.

METHODS

Cases were live-born singleton infants from the North Carolina Birth Defects Monitoring Program linked to birth records for 2003-2005; noncases served as controls (total n = 304,906). Pesticide active ingredient exposure was assigned using a previously constructed metric based on crops within 500 m of residence, dates of pregnancy, and likely chemical application dates for each pesticide-crop combination. ORs (95% CI) were estimated with logistic regression for categories of exposure compared to unexposed. Models were adjusted for maternal race/ethnicity, age at delivery, education, marital status, and smoking status.

RESULTS

Associations varied by birth defect and pesticide combinations. For example, hypospadias was positively associated with exposures to 2,4-D (OR_{50th to <90th percentile} : 1.39 [1.18, 1.64]), mepiquat (OR_{50th to <90th percentile} : 1.10 [0.90, 1.34]), paraquat (OR_{50th to <90th} : 1.14 [0.93, 1.39]), and pendimethalin (OR_{50th to <90th} : 1.21 [1.01, 1.44]), but not S-metolachlor (OR_{50th to <90th} : 1.00 [0.81, 1.22]). Whereas atrial septal defects were positively associated with higher levels of exposure to glyphosate, cyhalothrin, S-metolachlor, mepiquat, and pendimethalin (ORs ranged from 1.22 to 1.35 for 50th to <90th exposures, and 1.72 to 2.09 for >90th exposures); associations with paraquat were null or inconsistent (OR 50th to <90th: 1.05 (0.87, 1.27).

CONCLUSION

Our results suggest differing patterns of association for birth defects with residential exposure to seven pesticide active ingredients in North Carolina.

Associations between environmental quality and infant mortality in the United States, 2000-2005

Background

The United States (U.S.) suffers from high infant mortality (IM) rates and there are significant racial/ethnic differences in these rates. Prior studies on the environment and infant mortality are generally limited to singular exposures. We utilize the Environmental Quality Index (EQI), a measure of cumulative environmental exposure (across air, water, land, sociodemographic, and land domains) for U.S. counties from 2000 to 2005, to investigate associations between ambient environment and IM across maternal race/ethnicity.

Methods

We linked 2000–2005 infant data from the U.S. Centers for Disease Control and Prevention to the EQI (n = 22,702,529; 144,741 deaths). We utilized multi-level regression to estimate associations between quartiles of county-level EQI and IM. We also considered associations between quartiles of county level domain specific indices with IM. We controlled for rural-urban status (RUCC1: urban, metropolitan; RUCC2: urban, non-metropolitan; RUCC3: less urbanized; RUCC4: thinly populated), maternal age, maternal education, marital status, infant sex, and stratified on race/ethnicity. Additionally, we estimated associations for linear combinations of environmental quality and rural-urban status.

Results

We found a mix of positive, negative, and null associations and our findings varied across domain and race/ethnicity. Poorer overall environmental quality was associated with decreased odds among Non-Hispanic whites (OR and 95% CI: EQIQ4 (ref. EQIQ1): 0.84[0.80,0.89]). For Non-Hispanic blacks and Hispanics, some increased odds were observed. Poorer air quality was monotonically associated with increased odds among Non-Hispanic whites (airQ4 (ref. airQ1): 1.05[0.99,1.11]) and blacks (airQ4 (ref. airQ1): 1.09 [0.9,1.31]). Rural status was associated with increased IM odds among Hispanics (RUCC4-Q4:1.36[1.04,1.78]; RUCC1-Q4: 1.04[0.92,1.16], ref. for both RUCC1-Q1).

Conclusions

This study is the first to report on associations between ambient environmental quality and IM across the United States. It corroborates prior research suggesting an association between air pollution and IM and identifies residence in thinly populated (rural) areas as a potential risk factor towards IM amongst Hispanics. Some of the counterintuitive findings highlight the need for additional research into potentially differential drivers of environmental quality across the rural-urban continuum, especially with regards to the sociodemographic environment.

Electronic supplementary material

The online version of this article (10.1186/s13690-018-0306-0) contains supplementary material, which is available to authorized users.

Associations between environmental quality and adult asthma prevalence in medical claims data

As of 2014, approximately 7.4% of U.S. adults had current asthma. The etiology of asthma is complex, involving genetics, behavior, and environmental factors. To explore the association between cumulative environmental quality and asthma prevalence in U.S. adults, we linked the U.S. Environmental Protection Agency's Environmental Quality Index (EQI) to the MarketScan® Commercial Claims and Encounters Database. The EQI is a summary measure of five environmental domains (air, water, land, built, sociodemographic). We defined asthma as having at least 2 claims during the study period, 2003-2013. We used a Bayesian approach with non-informative priors, implementing mixed-effects regression modeling with a Poisson link function. Fixed effects variables were EQI, sex, race, and age. Random effects were counties. We modeled quintiles of the EQI comparing higher quintiles (worse quality) to lowest quintile (best quality) to estimate prevalence ratios (PR) and credible intervals (CIs). We estimated associations using the cumulative EQI and domain-specific EQIs; we assessed U.S. overall (non-stratified) as well as stratified by rural-urban continuum codes (RUCC) to assess rural/urban heterogeneity. Among the 71,577,118 U.S. adults with medical claims who could be geocoded to county of residence, 1,147,564 (1.6%) met the asthma definition. Worse environmental quality was associated with increased asthma prevalence using the non-RUCC-stratified cumulative EQI, comparing the worst to best EQI quintile (PR:1.27; 95% CI: 1.21, 1.34). Patterns varied among different EQI domains, as well as by rural/urban status. Poor environmental quality may increase asthma prevalence, but domain-specific drivers may operate differently depending on rural/urban status.

The association between physical inactivity and obesity is modified by five domains of environmental quality in U.S. adults: A cross-sectional study

Physical inactivity is a primary contributor to the obesity epidemic, but may be promoted or hindered by environmental factors. To examine how cumulative environmental quality may modify the inactivity-obesity relationship, we conducted a cross-sectional study by linking county-level Behavioral Risk Factor Surveillance System data with the Environmental Quality Index (EQI), a composite measure of five environmental domains (air, water, land, built, sociodemographic) across all U.S. counties. We estimated the county-level association (N = 3,137 counties) between 2009 age-adjusted leisure-time physical inactivity (LTPIA) and 2010 age-adjusted obesity from BRFSS across EQI tertiles using multi-level linear regression, with a random intercept for state, adjusted for percent minority and rural-urban status. We modelled overall and sex-specific estimates, reporting prevalence differences (PD) and 95% confidence intervals (CI). In the overall population, the PD increased from best (PD = 0.341 (95% CI: 0.287, 0.396)) to worst (PD = 0.645 (95% CI: 0.599, 0.690)) EQI tertile. We observed similar trends in males from best (PD = 0.244 (95% CI: 0.194, 0.294)) to worst (PD = 0.601 (95% CI: 0.556, 0.647)) quality environments, and in females from best (PD = 0.446 (95% CI: 0.385, 0.507)) to worst (PD = 0.655 (95% CI: 0.607, 0.703)). We found that poor environmental quality exacerbates the LTPIA-obesity relationship. Efforts to improve obesity through LTPIA may benefit from considering this relationship.

Exploring links between greenspace and sudden unexpected death: A spatial analysis

Greenspace has been increasingly recognized as having numerous health benefits. However, its effects are unknown concerning sudden unexpected death (SUD), commonly referred to as sudden cardiac death, which constitutes a large proportion of mortality in the United States. Because greenspace can promote physical activity, reduce stress and buffer air pollutants, it may have beneficial effects for people at risk of SUD, such as those with heart disease, hypertension, and diabetes mellitus. Using several spatial techniques, this study explored the relationship between SUD and greenspace. We adjudicated 396 SUD cases that occurred from March 2013 to February 2015 among reports from emergency medical services (EMS) that attended out-of-hospital deaths in Wake County (central North Carolina, USA). We measured multiple greenspace metrics in each census tract, including the percentages of forest, grassland, average tree canopy, tree canopy diversity, near-road tree canopy and greenway density. The associations between SUD incidence and these greenspace metrics were examined using Poisson regression (non-spatial) and Bayesian spatial models. The results from both models indicated that SUD incidence was inversely associated with both greenway density (adjusted risk ratio [RR] = 0.82, 95% credible/ confidence interval [CI]: 0.69-0.97) and the percentage of forest (adjusted RR = 0.90, 95% CI: 0.81-0.99). These results suggest that increases in greenway density by 1 km/km2 and in forest by 10% were associated with a decrease in SUD risk of 18% and 10%, respectively. The inverse relationship was not observed between SUD incidence and other metrics, including grassland, average tree canopy, near-road tree canopy and tree canopy diversity. This study implies that greenspace, specifically greenways and forest, may have beneficial effects for people at risk of SUD. Further studies are needed to investigate potential causal relationships between greenspace and SUD, and potential mechanisms such as promoting physical activity and reducing stress.

A cross-disciplinary evaluation of evidence for multipollutant effects on cardiovascular disease

BACKGROUND

The current single-pollutant approach to regulating ambient air pollutants is effective at protecting public health, but efficiencies may be gained by addressing issues in a multipollutant context since multiple pollutants often have common sources and individuals are exposed to more than one pollutant at a time.

OBJECTIVE

We performed a cross-disciplinary review of the effects of multipollutant exposures on cardiovascular effects.

METHODS

A broad literature search for references including at least two criteria air pollutants (particulate matter [PM], ozone [O₃], oxides of nitrogen, sulfur oxides, carbon monoxide) was conducted. References were culled based on scientific discipline then searched for terms related to cardiovascular disease. Most multipollutant epidemiologic and experimental (i.e., controlled human exposure, animal toxicology) studies examined PM and O₃ together.

DISCUSSION

Epidemiologic and experimental studies provide some evidence for O₃ concentration modifying the effect of PM, although PM did not modify O₃ risk estimates. Experimental studies of combined exposure to PM and O₃ provided evidence for additivity, synergism, and/or antagonism depending on the specific health endpoint. Evidence for other pollutant pairs was more limited.

CONCLUSIONS

Overall, the evidence for multipollutant effects was often heterogeneous, and the limited number of studies inhibited making a conclusion about the nature of the relationship between pollutant combinations and cardiovascular disease.

County-level cumulative environmental quality associated with cancer incidence

BACKGROUND

Individual environmental exposures are associated with cancer development; however, environmental exposures occur simultaneously. The Environmental Quality Index (EQI) is a county-level measure of cumulative environmental exposures that occur in 5 domains.

METHODS

The EQI was linked to county-level annual age-adjusted cancer incidence rates from the Surveillance, Epidemiology, and End Results (SEER) Program state cancer profiles. All-site cancer and the top 3 site-specific cancers for male and female subjects were considered. Incident rate differences (IRDs; annual rate difference per 100,000 persons) and 95% confidence intervals (CIs) were estimated using fixed-slope, random intercept multilevel linear regression models. Associations were assessed with domain-specific indices and analyses were stratified by rural/urban status.

RESULTS

Comparing the highest quintile/poorest environmental quality with the lowest quintile/best environmental quality for overall EQI, all-site county-level cancer incidence rate was positively associated with poor environmental quality overall (IRD, 38.55; 95% CI, 29.57-47.53) and for male (IRD, 32.60; 95% CI, 16.28-48.91) and female (IRD, 30.34; 95% CI, 20.47-40.21) subjects, indicating a potential increase in cancer incidence with decreasing environmental quality. Rural/urban stratified models demonstrated positive associations comparing the highest with the lowest quintiles for all strata, except the thinly populated/rural stratum and in the metropolitan/urbanized stratum. Prostate and breast cancer demonstrated the strongest positive associations with poor environmental quality.

CONCLUSION

We observed strong positive associations between the EQI and all-site cancer incidence rates, and associations differed by rural/urban status and environmental domain. Research focusing on single environmental exposures in cancer development may not address the broader environmental context in which cancers develop, and future research should address cumulative environmental exposures. Cancer 2017;123:2901-8. © 2017 American Cancer Society.

Exposure to Perfluorinated Alkyl Substances and Health Outcomes in Children: A Systematic Review of the Epidemiologic Literature

Perfluoroalkyl substances (PFAS), chemicals used to make products stain and stick resistant, have been linked to health effects in adults and adverse birth outcomes. A growing body of literature also addresses health effects in children exposed to PFAS. This review summarizes the epidemiologic evidence for relationships between prenatal and/or childhood exposure to PFAS and health outcomes in children as well as to provide a risk of bias analysis of the literature. A systematic review was performed by searching PubMed for studies on PFAS and child health outcomes. We identified 64 studies for inclusion and performed risk of bias analysis on those studies. We determined that risk of bias across studies was low to moderate. Six categories of health outcomes emerged. These were: immunity/infection/asthma, cardio-metabolic, neurodevelopmental/attention, thyroid, renal, and puberty onset. While there are a limited number of studies for any one particular health outcome, there is evidence for positive associations between PFAS and dyslipidemia, immunity (including vaccine response and asthma), renal function, and age at menarche. One finding of note is that while PFASs are mixtures of multiple compounds few studies examine them as such, therefore the role of these compounds as complex mixtures remains largely unknown.

County-level cumulative environmental quality associated with cancer incidence

BACKGROUND

Individual environmental exposures are associated with cancer development; however, environmental exposures occur simultaneously. The Environmental Quality Index (EQI) is a county-level measure of cumulative environmental exposures that occur in 5 domains.

METHODS

The EQI was linked to county-level annual age-adjusted cancer incidence rates from the Surveillance, Epidemiology, and End Results (SEER) Program state cancer profiles. All-site cancer and the top 3 site-specific cancers for male and female subjects were considered. Incident rate differences (IRDs; annual rate difference per 100,000 persons) and 95% confidence intervals (CIs) were estimated using fixed-slope, random intercept multilevel linear regression models. Associations were assessed with domain-specific indices and analyses were stratified by rural/urban status.

RESULTS

Comparing the highest quintile/poorest environmental quality with the lowest quintile/best environmental quality for overall EQI, all-site county-level cancer incidence rate was positively associated with poor environmental quality overall (IRD, 38.55; 95% CI, 29.57-47.53) and for male (IRD, 32.60; 95% CI, 16.28-48.91) and female (IRD, 30.34; 95% CI, 20.47-40.21) subjects, indicating a potential increase in cancer incidence with decreasing environmental quality. Rural/urban stratified models demonstrated positive associations comparing the highest with the lowest quintiles for all strata, except the thinly populated/rural stratum and in the metropolitan/urbanized stratum. Prostate and breast cancer demonstrated the strongest positive associations with poor environmental quality.

CONCLUSION

We observed strong positive associations between the EQI and all-site cancer incidence rates, and associations differed by rural/urban status and environmental domain. Research focusing on single environmental exposures in cancer development may not address the broader environmental context in which cancers develop, and future research should address cumulative environmental exposures. Cancer 2017;123:2901-8. © 2017 American Cancer Society.

Associations between Environmental Quality and Mortality in the Contiguous United States, 2000-2005

BACKGROUND

Assessing cumulative effects of the multiple environmental factors influencing mortality remains a challenging task.

OBJECTIVES

This study aimed to examine the associations between cumulative environmental quality and all-cause and leading cause-specific (heart disease, cancer, and stroke) mortality rates.

METHODS

We used the overall Environmental Quality Index (EQI) and its five domain indices (air, water, land, built, and sociodemographic) to represent environmental exposure. Associations between the EQI and mortality rates (CDC WONDER) for counties in the contiguous United States (n = 3,109) were investigated using multiple linear regression models and random intercept and random slope hierarchical models. Urbanicity, climate, and a combination of the two were used to explore the spatial patterns in the associations.

RESULTS

We found 1 standard deviation increase in the overall EQI (worse environment) was associated with a mean 3.22% (95% CI: 2.80%, 3.64%) increase in all-cause mortality, a 0.54% (95% CI: -0.17%, 1.25%) increase in heart disease mortality, a 2.71% (95% CI: 2.21%, 3.22%) increase in cancer mortality, and a 2.25% (95% CI: 1.11%, 3.39%) increase in stroke mortality. Among the environmental domains, the associations ranged from -1.27% (95% CI: -1.70%, -0.84%) to 3.37% (95% CI: 2.90%, 3.84%) for all-cause mortality, -2.62% (95% CI: -3.52%, -1.73%) to 4.50% (95% CI: 3.73%, 5.27%) for heart disease mortality, -0.88% (95% CI: -2.12%, 0.36%) to 3.72% (95% CI: 2.38%, 5.06%) for stroke mortality, and -0.68% (95% CI: -1.19%, -0.18%) to 3.01% (95% CI: 2.46%, 3.56%) for cancer mortality. Air had the largest associations with all-cause, heart disease, and cancer mortality, whereas the sociodemographic index had the largest association with stroke mortality. Across the urbanicity gradient, no consistent trend was found. Across climate regions, the associations ranged from 2.29% (95% CI: 1.87%, 2.72%) to 5.30% (95% CI: 4.30%, 6.30%) for overall EQI, and larger associations were generally found in dry areas for both overall EQI and domain indices.

CONCLUSIONS

These results suggest that poor environmental quality, particularly poor air quality, was associated with increased mortality and that associations vary by urbanicity and climate region. Citation: Jian Y, Messer LC, Jagai JS, Rappazzo KM, Gray CL, Grabich SC, Lobdell DT. 2017. Associations between environmental quality and mortality in the contiguous United States, 2000-2005. Environ Health Perspect 125:355-362; http://dx.doi.org/10.1289/EHP119.

Comparison of gestational dating methods and implications for exposure-outcome associations: an example with PM2.5 and preterm birth

OBJECTIVES

Estimating gestational age is usually based on date of last menstrual period (LMP) or clinical estimation (CE); both approaches introduce potential bias. Differences in methods of estimation may lead to misclassification and inconsistencies in risk estimates, particularly if exposure assignment is also gestation-dependent. This paper examines a 'what-if' scenario in which alternative methods are used and attempts to elucidate how method choice affects observed results.

METHODS

We constructed two 20-week gestational age cohorts of pregnancies between 2000 and 2005 (New Jersey, Pennsylvania, Ohio, USA) using live birth certificates: one defined preterm birth (PTB) status using CE and one using LMP. Within these, we estimated risk for 4 categories of preterm birth (PTBs per 10⁶ pregnancies) and risk differences (RD (95% CIs)) associated with exposure to particulate matter (PM_2.5).

RESULTS

More births were classified preterm using LMP (16%) compared with CE (8%). RD divergences increased between cohorts as exposure period approached delivery. Among births between 28 and 31 weeks, week 7 PM_2.5 exposure conveyed RDs of 44 (21 to 67) for CE and 50 (18 to 82) for LMP populations, while week 24 exposure conveyed RDs of 33 (11 to 56) and -20 (-50 to 10), respectively.

CONCLUSIONS

Different results from analyses restricted to births with both CE and LMP are most likely due to differences in dating methods rather than selection issues. Results are sensitive to choice of gestational age estimation, though degree of sensitivity can vary by exposure timing. When both outcome and exposure depend on estimate of gestational age, awareness of nuances in the method used for estimation is critical.

Additive Interaction between Heterogeneous Environmental Quality Domains (Air, Water, Land, Sociodemographic, and Built Environment) on Preterm Birth

BACKGROUND

Environmental exposures often occur in tandem; however, epidemiological research often focuses on singular exposures. Statistical interactions among broad, well-characterized environmental domains have not yet been evaluated in association with health. We address this gap by conducting a county-level cross-sectional analysis of interactions between Environmental Quality Index (EQI) domain indices on preterm birth in the Unites States from 2000 to 2005.

METHODS

The EQI, a county-level index constructed for the 2000-2005 time period, was constructed from five domain-specific indices (air, water, land, built, and sociodemographic) using principal component analyses. County-level preterm birth rates (n = 3141) were estimated using live births from the National Center for Health Statistics. Linear regression was used to estimate prevalence differences (PDs) and 95% confidence intervals (CIs) comparing worse environmental quality to the better quality for each model for (a) each individual domain main effect, (b) the interaction contrast, and (c) the two main effects plus interaction effect (i.e., the "net effect") to show departure from additivity for the all U.S. counties. Analyses were also performed for subgroupings by four urban/rural strata.

RESULTS

We found the suggestion of antagonistic interactions but no synergism, along with several purely additive (i.e., no interaction) associations. In the non-stratified model, we observed antagonistic interactions, between the sociodemographic/air domains [net effect (i.e., the association, including main effects and interaction effects) PD: -0.004 (95% CI: -0.007, 0.000), interaction contrast: -0.013 (95% CI: -0.020, -0.007)] and built/air domains [net effect PD: 0.008 (95% CI 0.004, 0.011), interaction contrast: -0.008 (95% CI: -0.015, -0.002)]. Most interactions were between the air domain and other respective domains. Interactions differed by urbanicity, with more interactions observed in non-metropolitan regions.

CONCLUSION

Observed antagonistic associations may indicate that those living in areas with multiple detrimental domains may have other interfering factors reducing the burden of environmental exposure. This study is the first to explore interactions across different environmental domains and demonstrates the utility of the EQI to examine the relationship between environmental domain interactions and human health. While we did observe some departures from additivity, many observed effects were additive. This study demonstrated that interactions between environmental domains should be considered in future analyses.

Maternal residential exposure to agricultural pesticides and birth defects in a 2003 to 2005 North Carolina birth cohort

BACKGROUND

Birth defects are responsible for a large proportion of disability and infant mortality. Exposure to a variety of pesticides have been linked to increased risk of birth defects.

METHODS

We conducted a case-control study to estimate the associations between a residence-based metric of agricultural pesticide exposure and birth defects. We linked singleton live birth records for 2003 to 2005 from the North Carolina (NC) State Center for Health Statistics to data from the NC Birth Defects Monitoring Program. Included women had residence at delivery inside NC and infants with gestational ages from 20 to 44 weeks (n = 304,906). Pesticide exposure was assigned using a previously constructed metric, estimating total chemical exposure (pounds of active ingredient) based on crops within 500 meters of maternal residence, specific dates of pregnancy, and chemical application dates based on the planting/harvesting dates of each crop. Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals for four categories of exposure (<10(th) , 10-50(th) , 50-90(th) , and >90(th) percentiles) compared with unexposed. Models were adjusted for maternal race, age at delivery, education, marital status, and smoking status.

RESULTS

We observed elevated ORs for congenital heart defects and certain structural defects affecting the gastrointestinal, genitourinary and musculoskeletal systems (e.g., OR [95% confidence interval] [highest exposure vs. unexposed] for tracheal esophageal fistula/esophageal atresia = 1.98 [0.69, 5.66], and OR for atrial septal defects: 1.70 [1.34, 2.14]).

CONCLUSION

Our results provide some evidence of associations between residential exposure to agricultural pesticides and several birth defects phenotypes. Birth Defects Research (Part A) 106:240-249, 2016. © 2016 Wiley Periodicals, Inc.

Exposure to Elemental Carbon, Organic Carbon, Nitrate, and Sulfate Fractions of Fine Particulate Matter and Risk of Preterm Birth in New Jersey, Ohio, and Pennsylvania (2000-2005)

BACKGROUND

Particulate matter ≤ 2.5 μm in aerodynamic diameter (PM2.5) has been consistently associated with preterm birth (PTB) to varying degrees, but roles of PM2.5 species have been less studied.

OBJECTIVE

We estimated risk differences (RD) of PTB (reported per 106 pregnancies) associated with change in ambient concentrations of elemental carbon (EC), organic carbon (OC), nitrates (NO3), and sulfates (SO4).

METHODS

From live birth certificates from three states, we constructed a cohort of singleton pregnancies at or beyond 20 weeks of gestation from 2000 through 2005 (n = 1,771,225; 8% PTB). We estimated mean species exposures for each week of gestation from monitor-corrected Community Multi-Scale Air Quality modeling data. RDs and 95% confidence intervals (CIs) for four PTB categories were estimated for each exposure using linear regression, adjusted for maternal race/ethnicity, marital status, education, age, smoking, maximum temperature, ozone, and season of conception. We also adjusted for other species in multi-species models.

RESULTS

RDs varied by exposure window and outcome period. EC was positively associated with PTB after 27 and before 35 weeks of gestation. For example, for a 0.25-μg/m(3) increase in EC exposure during gestational week 9, RD = 96 (95% CI: -20, 213) and RD = 145 (95% CI: -50, 341) for PTB during weeks 28-31 and 32-34, respectively. Associations with OCs were null or negative. RDs for NO3 were elevated with exposure in early weeks of gestation, and null in later weeks. RDs for SO4 exposure were positively associated with PTB, though magnitude varied across gestational weeks. We observed effect measure modification for associations between EC and PTB by race/ethnicity and smoking status.

CONCLUSION

EC and SO4 may contribute to associations between PM2.5 and PTB. Associations varied according to the timing of exposure and the timing of PTB.

The associations between environmental quality and preterm birth in the United States, 2000-2005: a cross-sectional analysis

BACKGROUND

Many environmental factors have been independently associated with preterm birth (PTB). However, exposure is not isolated to a single environmental factor, but rather to many positive and negative factors that co-occur. The environmental quality index (EQI), a measure of cumulative environmental exposure across all US counties from 2000-2005, was used to investigate associations between ambient environment and PTB.

METHODS

With 2000-2005 birth data from the National Center for Health Statistics for the United States (n = 24,483,348), we estimated the association between increasing quintiles of the EQI and county-level and individual-level PTB; we also considered environmental domain-specific (air, water, land, sociodemographic and built environment) and urban-rural stratifications.

RESULTS

Effect estimates for the relationship between environmental quality and PTB varied by domain and by urban-rural strata but were consistent across county- and individual-level analyses. The county-level prevalence difference (PD (95% confidence interval) for the non-stratified EQI comparing the highest quintile (poorest environmental quality) to the lowest quintile (best environmental quality) was -0.0166 (-0.0198, -0.0134). The air and sociodemographic domains had the strongest associations with PTB; PDs were 0.0196 (0.0162, 0.0229) and -0.0262 (-0.0300, -0.0224) for the air and sociodemographic domain indices, respectively. Within the most urban strata, the PD for the sociodemographic domain index was 0.0256 (0.0205, 0.0307). Odds ratios (OR) for the individual-level analysis were congruent with PDs.

CONCLUSION

We observed both strong positive and negative associations between measures of broad environmental quality and preterm birth. Associations differed by rural-urban stratum and by the five environmental domains. Our study demonstrates the use of a large scale composite environment exposure metric with preterm birth, an important indicator of population health and shows potential for future research.

Exposure to fine particulate matter during pregnancy and risk of preterm birth among women in New Jersey, Ohio, and Pennsylvania, 2000-2005

BACKGROUND

Particulate matter ≤ 2.5 μm in aerodynamic diameter (PM2.5) has been variably associated with preterm birth (PTB).

OBJECTIVE

We classified PTB into four categories (20-27, 28-31, 32-34, and 35-36 weeks completed gestation) and estimated risk differences (RDs) for each category in association with a 1-μg/m3 increase in PM2.5 exposure during each week of gestation.

METHODS

We assembled a cohort of singleton pregnancies that completed ≥ 20 weeks of gestation during 2000-2005 using live birth certificate data from three states (Pennsylvania, Ohio, and New Jersey) (n = 1,940,213; 8% PTB). We estimated mean PM2.5 exposures for each week of gestation from monitor-corrected Community Multi-Scale Air Quality modeling data. RDs were estimated using modified Poisson linear regression and adjusted for maternal race/ethnicity, marital status, education, age, and ozone.

RESULTS

RD estimates varied by exposure window and outcome period. Average PM2.5 exposure during the fourth week of gestation was positively associated with all PTB outcomes, although magnitude varied by PTB category [e.g., for a 1-μg/m3 increase, RD = 11.8 (95% CI: -6, 29.2); RD = 46 (95% CI: 23.2, 68.9); RD = 61.1 (95% CI: 22.6, 99.7); and RD = 28.5 (95% CI: -39, 95.7) for preterm births during 20-27, 28-31, 32-34, and 35-36 weeks, respectively]. Exposures during the week of birth and the 2 weeks before birth also were positively associated with all PTB categories.

CONCLUSIONS

Exposures beginning around the time of implantation and near birth appeared to be more strongly associated with PTB than exposures during other time periods. Because particulate matter exposure is ubiquitous, evidence of effects of PM2.5 exposure on PTB, even if small in magnitude, is cause for concern.

Construction of an environmental quality index for public health research

BACKGROUND

A more comprehensive estimate of environmental quality would improve our understanding of the relationship between environmental conditions and human health. An environmental quality index (EQI) for all counties in the U.S. was developed.

METHODS

The EQI was developed in four parts: domain identification; data source acquisition; variable construction; and data reduction. Five environmental domains (air, water, land, built and sociodemographic) were recognized. Within each domain, data sources were identified; each was temporally (years 2000-2005) and geographically (county) restricted. Variables were constructed for each domain and assessed for missingness, collinearity, and normality. Domain-specific data reduction was accomplished using principal components analysis (PCA), resulting in domain-specific indices. Domain-specific indices were then combined into an overall EQI using PCA. In each PCA procedure, the first principal component was retained. Both domain-specific indices and overall EQI were stratified by four rural-urban continuum codes (RUCC). Higher values for each index were set to correspond to areas with poorer environmental quality.

RESULTS

Concentrations of included variables differed across rural-urban strata, as did within-domain variable loadings, and domain index loadings for the EQI. In general, higher values of the air and sociodemographic indices were found in the more metropolitan areas and the most thinly populated areas have the lowest values of each of the domain indices. The less-urbanized counties (RUCC 3) demonstrated the greatest heterogeneity and range of EQI scores (-4.76, 3.57) while the thinly populated strata (RUCC 4) contained counties with the most positive scores (EQI score ranges from -5.86, 2.52).

CONCLUSION

The EQI holds promise for improving our characterization of the overall environment for public health. The EQI describes the non-residential ambient county-level conditions to which residents are exposed and domain-specific EQI loadings indicate which of the environmental domains account for the largest portion of the variability in the EQI environment. The EQI was constructed for all counties in the United States, incorporating a variety of data to provide a broad picture of environmental conditions. We undertook a reproducible approach that primarily utilized publically-available data sources.

Construction of an environmental quality index for public health research

BACKGROUND

A more comprehensive estimate of environmental quality would improve our understanding of the relationship between environmental conditions and human health. An environmental quality index (EQI) for all counties in the U.S. was developed.

METHODS

The EQI was developed in four parts: domain identification; data source acquisition; variable construction; and data reduction. Five environmental domains (air, water, land, built and sociodemographic) were recognized. Within each domain, data sources were identified; each was temporally (years 2000-2005) and geographically (county) restricted. Variables were constructed for each domain and assessed for missingness, collinearity, and normality. Domain-specific data reduction was accomplished using principal components analysis (PCA), resulting in domain-specific indices. Domain-specific indices were then combined into an overall EQI using PCA. In each PCA procedure, the first principal component was retained. Both domain-specific indices and overall EQI were stratified by four rural-urban continuum codes (RUCC). Higher values for each index were set to correspond to areas with poorer environmental quality.

RESULTS

Concentrations of included variables differed across rural-urban strata, as did within-domain variable loadings, and domain index loadings for the EQI. In general, higher values of the air and sociodemographic indices were found in the more metropolitan areas and the most thinly populated areas have the lowest values of each of the domain indices. The less-urbanized counties (RUCC 3) demonstrated the greatest heterogeneity and range of EQI scores (-4.76, 3.57) while the thinly populated strata (RUCC 4) contained counties with the most positive scores (EQI score ranges from -5.86, 2.52).

CONCLUSION

The EQI holds promise for improving our characterization of the overall environment for public health. The EQI describes the non-residential ambient county-level conditions to which residents are exposed and domain-specific EQI loadings indicate which of the environmental domains account for the largest portion of the variability in the EQI environment. The EQI was constructed for all counties in the United States, incorporating a variety of data to provide a broad picture of environmental conditions. We undertook a reproducible approach that primarily utilized publically-available data sources.