Is gastroschisis associated with county-level socio-environmental quality during pregnancy?

BACKGROUND: Gastroschisis prevalence more than doubled between 1995 and 2012. While there are individual-level risk factors (e.g., young maternal age, low body mass index), the impact of environmental exposures is not well understood. METHODS: We used the U.S. Environmental Protection Agency's Environmental Quality Index (EQI) as a county-level estimate of cumulative environmental exposures for five domains (air, water, land, sociodemographic, and built) and overall from 2006 to 2010. Adjusted odds ratios (aOR) and 95% confidence interval (CI) were estimated from logistic regression models between EQI tertiles (better environmental quality (reference); mid; poorer) and gastroschisis in the National Birth Defects Prevention Study from births delivered between 2006 and 2011. Our analysis included 594 cases with gastroschisis and 4105 infants without a birth defect (controls). RESULTS: Overall EQI was modestly associated with gastroschisis (aOR [95% CI]: 1.29 [0.98, 1.71]) for maternal residence in counties with poorer environmental quality, compared to the reference (better environmental quality). Within domain-specific indices, only the sociodemographic domain (aOR: 1.51 [0.99, 2.29]) was modestly associated with gastroschisis, when comparing poorer to better environmental quality. CONCLUSIONS: Future work could elucidate pathway(s) by which components of the sociodemographic domain or possibly related psychosocial factors like chronic stress potentially contribute to risk of gastroschisis.

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.

Diabetes control is associated with environmental quality in the USA.

Environmental parameters, including built and sociodemographic environments, can impact diabetes control (DC). Epidemiological studies have associated specific environmental factors with DC; however, the impact of multidimensional environmental status has not been assessed. The Environmental Quality Index (EQI), a comprehensive quantitative metric capturing five environmental domains, was considered as an exposure. Age-adjusted rates of DC prevalence for each county in the United States were used as an outcome. DC was defined as the proportion of adults aged 20+ years with a previous diabetes diagnosis who currently do not have high fasting blood glucose (≥126 mg/dL) or elevated HbA1c (≥6.5). We conducted county-level analyses of DC prevalence rates for the years 2004-2012 in association with EQI for 2006-2010 and domain-specific indices using random intercept multilevel linear regression models clustered by state and controlled for county-level rates of obesity and physical inactivity. Analyses were stratified by rural-urban strata, and results are reported as prevalence rate differences (PRD) with 95% CIs comparing highest quintile/worst environmental quality to lowest quintile/best environmental quality. The association of DC with cumulative environmental quality was negative after control for all counties (PRD -0.32, 95% CI: -0.38, -0.27); suggesting that rates of DC worsen as environmental quality declines. While overall environmental quality exerts effects on DC that vary across the rural-urban spectrum, poor sociodemographic, and built environmental factors are associated with decreased DC nationally. These data suggest improvements in environmental quality mediated by larger-scale policy and practice interventions may improve glycemic control and reduce the morbidity and mortality arising from hyperglycemia.

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.

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.

Acute effects of short-term exposure to air pollution while being physically active, the potential for modification: A review of the literature.

The science behind the combined effect of (and possible interaction between) physical activity and air pollution exposure on health endpoints is not well established, despite the fact that independent effects of physical activity and air pollution on health are well known. The objective of this review is to systematically assess the available literature pertaining to exposure to air pollution while being physically active, in order to assess statistical interaction. Articles published during 2000-2020 were identified by searching PubMed, Science Direct, and ProQuest Agricultural & Environmental Science Database for terms encompassing air pollution and exercise/physical activity. Articles were included if they examined the following four scenarios: at rest in clean air, physical activity in clean air, at rest in polluted air, and physical activity in polluted air. Risk of bias assessment was performed on all included articles. We identified 25 articles for inclusion and determined risk of bias was low to moderate. Nine articles identified evidence of statistical interaction between air pollution exposure and physical activity, while 16 identified no such interaction. However, pollutant levels, exercise intensity, and the population studied appeared to influence statistical interaction. Even in low levels of air pollution, low-intensity activities (i.e., walking), may intensify the negative impacts of air pollution, particularly among those with pre-existing conditions. However, among healthy adults, the review suggests that exercise is generally beneficial even in high air pollution environments. Particularly, the review indicates that moderate to high-intensity exercise may neutralize any short-term negative effects of air pollution.

Association between environmental quality and diabetes in the USA.

AIMS/INTRODUCTION: Caloric excess and physical inactivity fail to fully account for the rise of diabetes prevalence. Individual environmental pollutants can disrupt glucose homeostasis and promote metabolic dysfunction. However, the impact of cumulative exposures on diabetes risk is unknown. MATERIALS AND METHODS: The Environmental Quality Index, a county-level index composed of five domains, was developed to capture the multifactorial ambient environmental exposures. The Environmental Quality Index was linked to county-level annual age-adjusted population-based estimates of diabetes prevalence rates. Prevalence differences (PD, annual difference per 100,000 persons) and 95% confidence intervals (CI) were estimated using random intercept mixed effects linear regression models. Associations were assessed for overall environmental quality and domain-specific indices, and all analyses were stratified by four rural-urban strata. RESULTS: Comparing counties in the highest quintile/poorest environmental quality to those in the lowest quintile/best environmental quality, counties with poor environmental quality demonstrated lower total diabetes prevalence rates. Associations varied by rural-urban strata; overall better environmental quality was associated with lower total diabetes prevalence rates in the less urbanized and thinly populated strata. When considering all counties, good sociodemographic environments were associated with lower total diabetes prevalence rates (prevalence difference 2.77, 95% confidence interval 2.71-2.83), suggesting that counties with poor sociodemographic environments have an annual prevalence rate 2.77 per 100,000 persons higher than counties with good sociodemographic environments. CONCLUSIONS: Increasing attention has focused on environmental exposures as contributors to diabetes pathogenesis, and the present findings suggest that comprehensive approaches to diabetes prevention must include interventions to improve environmental quality.

Watershed integrity and associations with gastrointestinal illness in the United States.

Gastrointestinal (GI) illnesses are associated with various environmental factors, such as water quality, stormwater runoff, agricultural runoff, sewer overflows, and wastewater treatment plant effluents. However, rather than assessing an individual factor alone, two indices incorporating a combination of ecological and environmental stressors were created to represent (1) overall watershed integrity, Index of Watershed Integrity (IWI) and (2) catchment integrity, Index of Catchment Integrity (ICI). These indices could provide a more comprehensive understanding of how watershed/catchment integrity potentially impact the rates of GI illness, compared to assessing an individual stressor alone. We utilized the IWI and ICI, as well as agricultural and urban land uses, to assess associations at the county level with the rates of GI illness in a population of adults over 65 years of age. Our findings demonstrated that both watershed and catchment integrity are associated with reduced hospitalizations for any GI outcomes, though association varied by urbanicity. We believe that improved versions of the IWI and ICI may potentially be useful indicators for public health analyses in other circumstances, particularly when considering rural areas or to capture the complex stressors impacting the ecological health of a watershed.

Divergent trends in life expectancy across the rural-urban gradient and association with specific racial proportions in the contiguous USA 2000-2005.

OBJECTIVES: To estimate county-level adult life expectancy for Whites, Black/African Americans (Black), American Indian/Alaska Native (AIAN) and Asian/Pacific Islander (Asian) populations and assess the difference across racial groups in the relationship among life expectancy, rurality and specific race proportion. METHODS: We used individual-level death data to estimate county-level life expectancy at age 25 (e25) for Whites, Black, AIAN and Asian in the contiguous USA for 2000-2005. Race-sex-stratified models were used to examine the associations among e25, rurality and specific race proportion, adjusted for socioeconomic variables. RESULTS: Lower e25 was found in the central USA for AIANs and in the west coast for Asians. We found higher e25 in the most rural areas for Whites but in the most urban areas for AIAN and Asians. The associations between specific race proportion and e25 were positive or null for Whites but were negative for Blacks, AIAN, and Asians. The relationship between specific race proportion and e25 varied across rurality. CONCLUSIONS: Identifying differences in adult life expectancy, both across and within racial groups, provides new insights into the geographic determinants of life expectancy disparities.

Associations between access to healthcare, environmental quality, and end-stage renal disease survival time: Proportional-hazards models of over 1,000,000 people over 14 years.

Prevalence of end-stage renal disease (ESRD) in the US increased by 74% from 2000 to 2013. To investigate the role of the broader environment on ESRD survival time, we evaluated average distance to the nearest hospital by county (as a surrogate for access to healthcare) and the Environmental Quality Index (EQI), an aggregate measure of ambient environmental quality composed of five domains (air, water, land, built, and sociodemographic), at the county level across the US. Associations between average hospital distance, EQI, and survival time for 1,092,281 people diagnosed with ESRD between 2000 and 2013 (age 18+, without changes in county residence) from the US Renal Data System were evaluated using proportional-hazards models adjusting for gender, race, age at first ESRD service date, BMI, alcohol and tobacco use, and rurality. The models compared the average distance to the nearest hospital (<10, 10-20, >20 miles) and overall EQI percentiles [0-5), [5-20), [20-40), [40-60), [60-80), [80-95), and [95-100], where lower percentiles are interpreted as better EQI. In the full, non-stratified model with both distance and EQI, there was increased survival for patients over 20 miles from a hospital compared to those under 10 miles from a hospital (hazard ratio = 1.14, 95% confidence interval = 1.12-1.15) and no consistent direction of association across EQI strata. In the full model stratified by average hospital distance, under 10 miles from a hospital had increased survival in the worst EQI strata (median survival 3.0 vs. 3.5 years for best vs. worst EQI, respectively), however for people over 20 miles from a hospital, median survival was higher in the best (4.2 years) vs worst (3.4 years) EQI. This association held across different rural/urban categories and age groups. These results demonstrate the importance of considering multiple factors when studying ESRD survival and future efforts should consider additional components of the broader environment.

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.

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.

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.

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.

Validity of self-reported concentration and memory problems: Relationship with neuropsychological assessment and depression.

BACKGROUND: This study investigated the validity of self-reported concentration and memory problems (CMP) in residents environmentally exposed to manganese (Mn). METHOD: Self-report of CMP from a health questionnaire (HQ) and the Symptom Checklist-90-Revised (SCL-90-R) was compared to neuropsychological assessment (Trails A&B; Digit Span; Digit Symbol; Similarities; Auditory Consonant Trigrams, ACT; NAB Memory; Rey-Osterrieth, Rey-O, Delayed). Participants included 146 residents from Ohio exposed to air-Mn, with a modeled average concentration of 0.55 µg m-3 (range = 0.01-4.58). RESULTS: Residents were primarily White (94.5%), aged 30-64 years (M = 51.24), with a minimum of 10 years of residence (range = 10-64). Ninety-four (65.3%) participants reported concentration problems, and 107 residents (73.3%) reported memory problems. More participants endorsed CMP on the SCL-90-R than on the HQ. The prevalence of self-reported CMP was higher for women than for men (88.4% vs. 68.3%). Point-biserial and Pearson's correlations between self-reported CMP and neuropsychological test scores were nonsignificant and weak for both the HQ (rpb = -.20 to rpb = .04) and the SCL-90-R (r = -.12 to r = .007). Greater levels of depression, anxiety, and female sex predicted having more self-reported CMP on both the HQ and the SCL-90-R. Air-Mn and blood-Mn were not associated with self-reported CMP. Residential distance from the Mn source accounted for a small proportion of variance (sr2 = .04), although depression remained the largest predictor (sr2 = .21). CONCLUSION: These results indicate that self-report of CMP in Mn-exposed residents appear to be invalid when compared to neuropsychological test scores. The participants' misperception of having CMP is associated with less education and higher levels of depression. Neuropsychological assessment is recommended to attain valid results.

Is human fecundity changing? A discussion of research and data gaps precluding us from having an answer.

Fecundity, the biologic capacity to reproduce, is essential for the health of individuals and is, therefore, fundamental for understanding human health at the population level. Given the absence of a population (bio)marker, fecundity is assessed indirectly by various individual-based (e.g. semen quality, ovulation) or couple-based (e.g. time-to-pregnancy) endpoints. Population monitoring of fecundity is challenging, and often defaults to relying on rates of births (fertility) or adverse outcomes such as genitourinary malformations and reproductive site cancers. In light of reported declines in semen quality and fertility rates in some global regions among other changes, the question as to whether human fecundity is changing needs investigation. We review existing data and novel methodological approaches aimed at answering this question from a transdisciplinary perspective. The existing literature is insufficient for answering this question; we provide an overview of currently available resources and novel methods suitable for delineating temporal patterns in human fecundity in future research.

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 (PM2.5). 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 PM2.5 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.

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.

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.