Costs and Projected Effect of a Federally Qualified Health Center-Based Mailed Colorectal Cancer Screening Program in Texas.

Introduction: Mailed stool testing for colorectal cancer (CRC) may improve screening uptake and reduce the incidence and mortality of CRC, especially among patients at federally qualified health centers (FQHCs). To expand screening programs it is important to identify cost-effective approaches. Methods: We developed a decision-analytic model to estimate the cost, effects on screening and patient outcomes (CRCs detected, CRCs prevented, CRC deaths prevented), and cost-effectiveness of implementing a state-wide mailed stool testing program over 5 years among unscreened, age-eligible (aged 50-75 y) patients at FQHCs in Texas. We compared various outreach strategies and organizational structures (centralized, regional, or a hybrid). We used data from our existing regional mailed stool testing program and recent systematic reviews to set parameters for the model. Costs included start-up and ongoing activities and were estimated in 2022 US dollars from the perspective of a hypothetical third-party payer. Cost-effectiveness was assessed by using both incremental and average cost-effectiveness ratios. Results: Using either a statewide centralized or hybrid organizational configuration to mail stool tests to newly eligible FQHC patients and patients who have responded at least once since program inception is likely to result in the best use of resources over 5 years, enabling more than 110,000 additional screens, detecting an incremental 181 to 194 CRCs, preventing 91 to 98 CRCs, and averting 46 to 50 CRC deaths, at a cost of $10 million to $11 million compared with no program. Conclusions: A statewide mailed stool testing program for FQHC patients can be implemented at reasonable cost with considerable effects on CRC screening outcomes, especially when its structure maximizes program efficiency while maintaining effectiveness.

Industrial air pollution and low birth weight in New Mexico, USA.

In recent decades, the low birth weight (LBW) rate in New Mexico has consistently exceeded the Unites States average. Maternal exposure to air pollution during pregnancy may be a significant contributor to LBW in offspring. This study investigated the links between maternal residential exposure to air pollution from industrial sources and the risk of LBW in offspring. The analysis included 22,375 LBW cases and 233,340 controls. It focused on 14 common chemicals listed in the Toxic Release Inventory (TRI) and monitoring datasets, which have abundant monitoring samples. The Emission Weighted Proximity Model (EWPM) was used to calculate maternal air pollution exposure intensity. Adjusted odds ratios (adjORs) were calculated using binary logistic regressions to examine the association between maternal residential air pollution exposure and LBW, while controlling for potential confounders, such as the maternal age, race/ethnicity, gestational age, prenatal care, education level, consumption of alcohol during pregnancy, public health regions, child's sex, and the year of birth. Multiple comparison correction was applied using the False Discovery Rate approach. The results showed that maternal residential exposure to 1,2,4-trimethylbenzene, benzene, chlorine, ethylbenzene, and styrene had significant positive associations with LBW in offspring, with adjusted odds ratios ranging from 1.10 to 1.13. These five chemicals remained as significant risk factors after dividing the estimated exposure intensities into four categories. In addition, significant linear trends were found between LBW and maternal exposure to each of the five identified chemicals. Furthermore, 1,2,4-trimethylbenzene was identified as a risk factor to LBW for the first time. The findings of this study should be confirmed through additional epidemiological, biological, and toxicological studies.

Spatial Insights for Understanding Colorectal Cancer Screening in Disproportionately Affected Populations, Central Texas, 2019.

INTRODUCTION: Colorectal cancer (CRC) screening can reduce morbidity and mortality; however, important disparities exist in CRC uptake. Our study examines the associations of distance to care and frequency of using primary care and screening. METHODS: To examine the distribution of screening geographically and according to several demographic features, we used individual patient-level data, dated September 30, 2018, from a large urban safety-net health system in Central Texas. We used spatial cluster analysis and logistic regression adjusted for age, race, sex, socioeconomic status, and health insurance status. RESULTS: We obtained screening status data for 13,079 age-eligible patients from the health system's electronic medical records. Of those eligible, 55.1% were female, and 55.9% identified as Hispanic. Mean age was 58.1 years. Patients residing more than 20 miles from one of the system's primary care clinics was associated with lower screening rates (odds ratio [OR], 0.63; 95% CI, 0.43-0.93). Patients with higher screening rates included those who had a greater number of primary care-related (nonspecialty) visits within 1 year (OR, 6.90; 95% CI, 6.04-7.88) and those who were part of the county-level medical assistance program (OR, 1.61; 95% CI, 1.40-1.84). Spatial analysis identified an area where the level of CRC screening was particularly low. CONCLUSION: Distance to primary care and use of primary care were associated with screening. Priorities in targeted interventions should include identifying and inviting patients with limited care engagements.

Geographic Variations of Racial/Ethnic Disparities in Late-Stage Diagnosis of Childhood Cancer in Texas.

OBJECTIVES: This study aimed to identify small geographic areas where the childhood cancer yearly incidence and late-stage diagnosis rates were disproportionately higher among racial/ethnic minorities (Hispanics and non-Hispanic African Americans) in Texas. METHODS: The study examined childhood cancer disparities in Texas from 2005 to 2014, based on geographic location and race/ethnicity. Relative (risk ratio) and absolute (risk difference) measures were used to investigate racial disparities of childhood cancer late-stage diagnosis in small geographic areas (census tracts). The study investigated childhood cancer yearly incidence- and late-stage diagnosis rates for three racial groups combined. The study also analyzed the temporal change of childhood cancer late-stage diagnosis rates based on the data from census tracts where disparities existed for Hispanics and non-Hispanic African Americans compared with a non-Hispanic white reference group. RESULTS: A total of 54% of the cases in the study cohort were diagnosed in the late stage. Although there were fewer non-Hispanic African Americans cases compared with non-Hispanic white and Hispanic cases, they showed significant geographic variation in racial/ethnic disparities compared with the non-Hispanic white reference group. The study also revealed that 58 census tracts for non-Hispanic African Americans and 47 census tracts for Hispanics (of 5265) had significantly higher late-stage diagnosis rates compared with non-Hispanic whites. The findings also demonstrated consistent increases in incidence and late-stage diagnosis from 2005 to 2014 for all cases combined. CONCLUSIONS: Most of the significant census tracts with a higher late-stage diagnosis rate for Hispanics were located on the outskirts of the Dallas-Fort Worth, Houston, and San Antonio areas. In contrast, geographic disparities of childhood cancer late-stage diagnosis for non-Hispanic African Americans were found inside the large metropolitan areas of Houston and Dallas-Fort Worth. The findings of this study will help prioritize the geographical allocation of resources, which, in turn, will help to facilitate preventive healthcare services and alleviate the disease burden in children.

Influencing factor analysis of phosphorus loads from non-point source: a case study in central China.

The influence factor analysis for non-point source (NPS) pollution is very important to taking effective water pollution control measures. In this study, the self-organizing map (SOM) and linear model analysis were used to analyze the relationships between total phosphorus (TP) loads and influencing factors, both qualitatively and quantitatively. The land-use type, topography, and vegetation coverage were the main factors influencing the export of TP loads in Tangxun watershed. Slope and normalized difference vegetation index (NDVI) were chosen as characteristic indices of topography and vegetation coverage, respectively. For the whole watershed, the high TP loads were mainly distributed in areas with high slope and low vegetation coverage for a specific land-use type. For different land types, the slope significantly influenced the export of TP loads in waste/bare land and forest/green land while NDVI influenced the export of TP loads in forest/green land and farmland. In terms of multi-factor analysis, the comprehensive influence of slope and NDVI on TP loads showed as waste/bare land>forest/green land>farmland>rural/urban construction land.

Maternal residential proximity to chlorinated solvent emissions and birth defects in offspring: a case-control study.

BACKGROUND: Some studies have noted an association between maternal occupational exposures to chlorinated solvents and birth defects in offspring, but data are lacking on the potential impact of industrial air emissions of these solvents on birth defects. METHODS: With data from the Texas Birth Defects Registry for births occurring in 1996-2008, we examined the relation between maternal residential proximity to industrial air releases of chlorinated solvents and birth defects in offspring of 60,613 case-mothers and 244,927 control-mothers. Maternal residential exposures to solvent emissions were estimated with metrics that took into account residential distances to industrial sources and annual amounts of chemicals released. Logistic regression was used to generate odds ratios and 95% confidence intervals for the associations between residential proximity to emissions of 14 chlorinated solvents and selected birth defects, including neural tube, oral cleft, limb deficiency, and congenital heart defects. All risk estimates were adjusted for year of delivery and maternal age, education, race/ethnicity, and public health region of residence. RESULTS: Relative to exposure risk values of 0, neural tube defects were associated with maternal residential exposures (exposure risk values >0) to several types of chlorinated solvents, most notably carbon tetrachloride (adjusted odds ratio [aOR] 1.42, 95% confidence interval [CI] 1.09, 1.86); chloroform (aOR 1.40, 95% CI 1.04, 1.87); ethyl chloride (aOR 1.39, 95% CI 1.08, 1.79); 1,1,2-trichloroethane (aOR 1.56, 95% CI 1.11, 2.18); and 1,2,3-trichloropropane (aOR 1.49, 95% CI 1.08, 2.06). Significant associations were also noted between a few chlorinated solvents and oral cleft, limb deficiency, and congenital heart defects. We observed stronger associations between some emissions and neural tube, oral cleft, and heart defects in offspring of mothers 35 years or older, such as spina bifida with carbon tetrachloride (aOR 2.49, 95% CI 1.09, 5.72), cleft palate with 1,2-dichloroethane (aOR 1.93, 95% 1.05, 3.54), cleft lip with or without cleft palate with ethyl chloride (aOR 1.81, 95% CI 1.06, 3.07), and obstructive heart defects with trichloroethylene (aOR 1.43, 95% CI 1.08, 1.88). CONCLUSIONS: These findings suggest that maternal residential proximity to industrial emissions of chlorinated solvents might be associated with selected birth defects in offspring, especially among older mothers.

Geographic variations of racial/ethnic disparities in cervical cancer mortality in Texas.

OBJECTIVES: To examine how racial/ethnic disparities of cervical cancer mortality vary geographically and to identify factors contributing to the variation. METHODS: Using the population-weighted risk difference, the authors investigated geographic patterns of racial/ethnic disparities in cervical cancer mortality in Texas based on data from 1995 to 2008 georeferenced at the census tract level. In addition, we considered the impact of seven factors--stage at diagnosis, spatial access to health care, and five factors that were created from available demographic data: socioeconomic status (SES), the sociodemographic factor, the percentage of African Americans, the health insurance factor, and the behavioral factor--on racial/ethnic disparities in the analysis using multivariate logistic regression. RESULTS: SES, the sociodemographic factor, the percentage of African Americans, and racial/ethnic disparities in late-stage diagnosis in a census tract were independent predictors of a census tract's displaying significant racial/ethnic disparities in cervical cancer mortality. Compared with a census tract with the highest SES, a census tract with the lowest SES was more likely to have higher mortality rates in African Americans (odds ratio 4.19, confidence interval 2.18-8.07) or Hispanics (odds ratio 8.15, confidence interval 5.27-12.61) than non-Hispanic whites after adjusting for covariates. Health insurance expenditures also influenced racial/ethnic disparities in mortality, although this effect was attenuated after adjusting for covariates. Neither our calculated behavioral factor nor spatial analysis of access to health care explained racial/ethnic gaps in mortality. CONCLUSIONS: Findings from this study could allow cervical cancer intervention programs to more clearly identify areas that would reduce disparities in cervical cancer outcomes.

High polygenic risk score is a risk factor associated with colorectal cancer based on data from the UK Biobank.

Colorectal cancer (CRC) is a common cancer among both men and women and is one of the leading causes of cancer death worldwide. It is important to identify risk factors that may be used to help reduce morbidity and mortality of the disease. We used a case-control study design to explore the association between CRC, polygenic risk scores (PRS), and other factors. We extracted data about 2,585 CRC cases and 9,362 controls from the UK Biobank, calculated the PRS for these cases and controls based on 140 single nucleotide polymorphisms, and performed logistic regression analyses for the 11,947 cases and controls, for an older group (ages 50+), and for a younger group (younger than 50). Five significant risk factors were identified when all 11,947 cases and controls were considered. These factors were, in descending order of the values of the adjusted odds ratios (aOR), high PRS (aOR: 2.70, CI: 2.27-3.19), male sex (aOR: 1.52, CI: 1.39-1.66), unemployment (aOR: 1.47, CI: 1.17-1.85), family history of CRC (aOR: 1.44, CI: 1.28-1.62), and age (aOR: 1.01, CI: 1.01-1.02). These five risk factors also remained significant in the older group. For the younger group, only high PRS (aOR: 2.87, CI: 1.65-5.00) and family history of CRC (aOR: 1.73, CI: 1.12-2.67) were significant risk factors. These findings indicate that genetic risk for the disease is a significant risk factor for CRC even after adjusting for family history. Additional studies are needed to examine this association using larger samples and different population groups.

Determining Association between Lung Cancer Mortality Worldwide and Risk Factors Using Fuzzy Inference Modeling and Random Forest Modeling.

Lung cancer remains the leading cause for cancer mortality worldwide. While it is well-known that smoking is an avoidable high-risk factor for lung cancer, it is necessary to identify the extent to which other modified risk factors might further affect the cell's genetic predisposition for lung cancer susceptibility, and the spreading of carcinogens in various geographical zones. This study aims to examine the association between lung cancer mortality (LCM) and major risk factors. We used Fuzzy Inference Modeling (FIM) and Random Forest Modeling (RFM) approaches to analyze LCM and its possible links to 30 risk factors in 100 countries over the period from 2006 to 2016. Analysis results suggest that in addition to smoking, low physical activity, child wasting, low birth weight due to short gestation, iron deficiency, diet low in nuts and seeds, vitamin A deficiency, low bone mineral density, air pollution, and a diet high in sodium are potential risk factors associated with LCM. This study demonstrates the usefulness of two approaches for multi-factor analysis of determining risk factors associated with cancer mortality.

Detection of arbitrarily-shaped clusters using a neighbor-expanding approach: a case study on murine typhus in south Texas.

BACKGROUND: Kulldorff's spatial scan statistic has been one of the most widely used statistical methods for automatic detection of clusters in spatial data. One limitation of this method lies in the fact that it has to rely on scan windows with predefined shapes in the search process, and therefore it cannot detect cluster with arbitrary shapes. We employ a new neighbor-expanding approach and introduce two new algorithms to detect cluster with arbitrary shapes in spatial data. These two algorithms are called the maximum-likelihood-first (MLF) algorithm and non-greedy growth (NGG) algorithm. We then compare the performance of these two new algorithms with the spatial scan statistic (SaTScan), Tango's flexibly shaped spatial scan statistic (FlexScan), and Duczmal's simulated annealing (SA) method using two datasets. Furthermore, we utilize the methods to examine clusters of murine typhus cases in South Texas from 1996 to 2006. RESULT: When compared with the SaTScan and FlexScan method, the two new algorithms were more flexible and sensitive in detecting the clusters with arbitrary shapes in the test datasets. Clusters detected by the MLF algorithm are statistically more significant than those detected by the NGG algorithm. However, the NGG algorithm appears to be more stable when there are no extreme cluster patterns in the data. For the murine typhus data in South Texas, a large portion of the detected clusters were located in coastal counties where environmental conditions and socioeconomic status of some population groups were at a disadvantage when compared with those in other counties with no clusters of murine typhus cases. CONCLUSION: The two new algorithms are effective in detecting the location and boundary of spatial clusters with arbitrary shapes. Additional research is needed to better understand the etiology of the concentration of murine typhus cases in some counties in south Texas.

Spatial association of racial/ethnic disparities between late-stage diagnosis and mortality for female breast cancer: where to intervene?

BACKGROUND: Over the past twenty years, racial/ethnic disparities between late-stage diagnoses and mortality outcomes have widened due to disproportionate medical benefits that different racial/ethnic groups have received. Few studies to date have examined the spatial relationships of racial/ethnic disparities between breast cancer late-stage diagnosis and mortality as well as the impact of socioeconomic status (SES) on these two disparities at finer geographic scales. METHODS: Three methods were implemented to assess the spatial relationship between racial/ethnic disparities of breast cancer late-stage diagnosis and morality. First, this study used rate difference measure to test for racial/ethnic disparities in both late-stage diagnosis and mortality of female breast cancer in Texas during 1995-2005. Second, we used linear and logistic regression models to determine if there was a correlation between these two racial/ethnic disparities at the census tract level. Third, a geographically-weighted regression analysis was performed to evaluate if this correlation occurred after weighting for local neighbors. RESULTS: The spatial association of racial disparities was found to be significant between late-stage diagnosis and breast cancer mortality with odds ratios of 33.76 (CI: 23.96-47.57) for African Americans and 30.39 (CI: 22.09-41.82) for Hispanics. After adjusting for a SES cofounder, logistic regression models revealed a reduced, although still highly significant, odds ratio of 18.39 (CI: 12.79-26.44) for African-American women and 11.64 (CI: 8.29-16.34) for Hispanic women. Results of the logistic regression analysis indicated that census tracts with low and middle SES were more likely to show significant racial disparities of breast cancer late-stage diagnosis and mortality rates. However, values of local correlation coefficients suggested that the association of these two types of racial/ethnic disparities varied across geographic regions. CONCLUSIONS: This study may have health-policy implications that can help early detection of breast cancer among disadvantaged minority groups through implementing effective intervention programs in targeted regions.

Socioeconomic disparities in prostate cancer mortality and the impact of geographic scale.

OBJECTIVE: To examine socioeconomic disparities in prostate cancer mortality and to assess the scale effect on the results of the disparity analysis. METHODS: Using prostate cancer mortality data (N = 14,036) of Texas from 1996 to 2004, this study examines the variations of socioeconomic disparities in prostate cancer mortality across different geographic scales. Age-adjusted odds ratios are employed to reveal the disparities by single and composite socioeconomic indicators at county, census tract, and block group levels. RESULTS: The analysis shows that (1) disparities in prostate cancer mortality are significant for most socioeconomic indicators, (2) area-level socioeconomic indicators tend to reveal a less extent of disparity than individual-level indicators do, and (3) socioeconomic disparities in prostate cancer mortality at the census tract and block group levels are similar to each other but are completely different from those at the county level. CONCLUSION: The selection of geographic scale and socioeconomic indicators affects the results of socioeconomic disparity analysis in prostate cancer mortality. Most census tract and block group level socioeconomic indicators are appropriate for analyzing disparities in prostate cancer mortality. County level socioeconomic indicators should be avoided if possible.

[Maternal sulfur dioxide exposure and the risk of low birth-weight babies].

The relationship between maternal exposure to sulfur dioxide (SO2) and the risk of low birth-weight (LBW) babies which has been reported in literatures remained inconclusive. In this study, the data on SO2 emission, meteorology, topography as well as LBW and control babies in the Dallas-Fort Worth area of the United States in 1997 were collected to re-examine the associations between maternal SO2 exposure and the risk of LBW in babies. A combination of air dispersion modeling, Geographic Information System (GIS) spatial interpolation and geo-statistical analysis, as well as logistic regression was used for analyses. Results showed that the risk of LBW was not significantly increased with the exposure of pregnant mothers to higher level of SO2 when all data were considered together as one group. However, for mothers at the age 35 or older, the risk of LBW babies was higher in exposure to SO2 (OR = 2.31, 95% CI 1.01 - 5.30). Therefore, the potential risk of LBW baby might be higher in elder women in exposure to SO2 during pregnancy.

Identification of racial disparities in breast cancer mortality: does scale matter?

BACKGROUND: This paper investigates the impact of geographic scale (census tract, zip code, and county) on the detection of disparities in breast cancer mortality among three ethnic groups in Texas (period 1995-2005). Racial disparities were quantified using both relative (RR) and absolute (RD) statistics that account for the population size and correct for unreliable rates typically observed for minority groups and smaller geographic units. Results were then correlated with socio-economic status measured by the percentage of habitants living below the poverty level. RESULTS: African-American and Hispanic women generally experience higher mortality than White non-Hispanics, and these differences are especially significant in the southeast metropolitan areas and southwest border of Texas. The proportion and location of significant racial disparities however changed depending on the type of statistic (RR versus RD) and the geographic level. The largest proportion of significant results was observed for the RD statistic and census tract data. Geographic regions with significant racial disparities for African-Americans and Hispanics frequently had a poverty rate above 10.00%. CONCLUSIONS: This study investigates both relative and absolute racial disparities in breast cancer mortality between White non-Hispanic and African-American/Hispanic women at the census tract, zip code and county levels. Analysis at the census tract level generally led to a larger proportion of geographical units experiencing significantly higher mortality rates for minority groups, although results varied depending on the use of the relative versus absolute statistics. Additional research is needed before general conclusions can be formulated regarding the choice of optimal geographic regions for the detection of racial disparities.

Maternal residential proximity to waste sites and industrial facilities and conotruncal heart defects in offspring.

Most studies of the relationship between maternal residential proximity to sources of environmental pollution and congenital cardiovascular malformations have combined heart defects into one group or broad subgroups. The current case-control study examined whether risk of conotruncal heart defects, including subsets of specific defects, was associated with maternal residential proximity to hazardous waste sites and industrial facilities with recorded air emissions. Texas Birth Defects Registry cases were linked to their birth or fetal death certificate. Controls without birth defects were randomly selected from birth certificates. Distances from maternal addresses at delivery to National Priority List (NPL) waste sites, state superfund waste sites, and Toxic Release Inventory (TRI) facilities were determined for 1244 cases (89.5% of those eligible) and 4368 controls (88.0%). Living within 1 mile of a hazardous waste site was not associated with risk of conotruncal heart defects [adjusted odds ratio (aOR) = 0.83, 95% confidence interval (CI) = 0.54, 1.27]. This was true whether looking at most types of defects or waste sites. Only truncus arteriosus showed statistically elevated ORs with any waste site (crude OR: 2.80, 95% CI 1.19, 6.54) and with NPL sites (crude OR: 4.63, 95% CI 1.18, 13.15; aOR 4.99, 95% CI 1.26, 14.51), but the latter was based on only four exposed cases. There was minimal association between conotruncal heart defects and proximity to TRI facilities (aOR = 1.10, 95% CI = 0.91, 1.33). Stratification by maternal age or race/ethnic group made little difference in effect estimates for waste sites or industrial facilities. In this study population, maternal residential proximity to waste sites or industries with reported air emissions was not associated with conotruncal heart defects or its subtypes in offspring, with the exception of truncus arteriosus.

Air pollution exposure assessment methods utilized in epidemiological studies.

The assessment of personal exposure to air pollution is a critical component of epidemiological studies associating air pollution and health effects. This paper critically reviewed 157 studies over 29 years that utilized one of five categories of exposure methods (proximity, air dispersion, hybrid, human inhalation, and biomarkers). Proximity models were found to be a questionable technique as they assume that closer proximity equates to greater exposure. Inhalation models and biomarker estimates were the most effective in assessing personal exposure, but are often cost prohibitive for large study populations. This review suggests that: (i) factors such as uncertainty, validity, data availability, and transferability related to exposure assessment methods should be considered when selecting a model; and (ii) although an entirely discreet new class of approach is not necessary, significant progress could be made through the development of a 'hybrid' model utilizing the strengths of several existing methods. Future work should systematically evaluate the performance of hybrid models compared to other individual exposure assessment methods utilizing geospatial information technologies (e.g. geographic information systems (GIS) and remote sensing (RS)) to more robustly refine estimates of ambient exposure and quantify the linkages and differences between outdoor, indoor and personal exposure estimates.

Geospatial-Temporal and Demand Models for Opioid Admissions, Implications for Policy.

Background: As the opioid epidemic continues, understanding the geospatial, temporal, and demand patterns is important for policymakers to assign resources and interdict individual, organization, and country-level bad actors. Methods: GIS geospatial-temporal analysis and extreme-gradient boosted random forests evaluate ICD-10 F11 opioid-related admissions and admission rates using geospatial analysis, demand analysis, and explanatory models, respectively. The period of analysis was January 2016 through September 2018. Results: The analysis shows existing high opioid admissions in Chicago and New Jersey with emerging areas in Atlanta, Salt Lake City, Phoenix, and Las Vegas. High rates of admission (claims per 10,000 population) exist in the Appalachian area and on the Northeastern seaboard. Explanatory models suggest that hospital overall workload and financial variables might be used for allocating opioid-related treatment funds effectively. Gradient-boosted random forest models accounted for 87.8% of the variability of claims on blinded 20% test data. Conclusions: Based on the GIS analysis, opioid admissions appear to have spread geographically, while higher frequency rates are still found in some regions. Interdiction efforts require demand-analysis such as that provided in this study to allocate scarce resources for supply-side and demand-side interdiction: Prevention, treatment, and enforcement.

Residential proximity to waste sites and industrial facilities and chromosomal anomalies in offspring.

A few studies have found chromosomal anomalies in offspring associated with a maternal residence near waste sites, but did not examine the effect of living near industrial facilities, and most combined specific anomalies into heterogeneous groups. With a case-control study design, we investigated whether maternal residential proximity to hazardous waste sites or industrial facilities with chemical air emissions was associated with chromosomal anomalies in births. Maternal residences of 2099 Texas births with chromosomal anomalies and 4368 control births without documented malformations were related to boundaries of hazardous waste sites and street addresses of industrial facilities through geographic information systems. With adjustment for maternal age, race/ethnicity, and education, maternal residence within 1mile of a hazardous waste site (relative to farther away) was not associated with chromosomal anomalies in offspring except for Klinefelter variants among Hispanic births (odds ratios (OR) 7.9, 95% confidence interval (CI) 1.1-42.4). Women 35 years or older who lived within 1mile of industries with emissions of heavy metals were two times more likely (95% CI 1.1-4.1) than women living farther away to have offspring with chromosomal anomalies including trisomies 13, 18, or 21 or sex chromosome abnormalities. Among women 40 years or older, maternal residence within a mile of industries with solvent emissions was associated with chromosomal anomalies in births (OR 4.8, 95% CI 1.2-42.8). Study findings suggest some relation between residential proximity to industries with emissions of solvents or heavy metals and chromosomal anomalies in births to older mothers.

Industrial air pollution and low birth weight: a case-control study in Texas, USA.

Many studies have investigated associations between maternal residential exposures to air pollutants and low birth weight (LBW) in offspring. However, most studies focused on the criteria air pollutants (PM2.5, PM10, O3, NO2, SO2, CO, and Pb), and only a few studies examined the potential impact of other air pollutants on LBW. This study investigated associations between maternal residential exposure to industrial air emissions of 449 toxics release inventory (TRI) chemicals and LBW in offspring using a case-control study design based on a large dataset consisting of 94,106 LBW cases and 376,424 controls in Texas from 1996 to 2008. Maternal residential exposure to chemicals was estimated using a modified version of the emission-weighted proximity model (EWPM). The model takes into account reported quantities of annual air emission from industrial facilities and the distances between the locations of industrial facilities and maternal residence locations. Binary logistic regression was used to compute odds ratios measuring the association between maternal exposure to different TRI chemicals and LBW in offspring. Odds ratios were adjusted for child's sex, birth year, gestational length, maternal age, education, race/ethnicity, and public health region of maternal residence. Among the ten chemicals selected for a complete analysis, maternal residential exposures to five TRI chemicals were positively associated with LBW in offspring. These five chemicals include acetamide (adjusted odds ratio [aOR] 2.29, 95% confidence interval [CI] 1.24, 4.20), p-phenylenediamine (aOR 1.63, 95% CI 1.18, 2.25), 2,2-dichloro-1,1,1-trifluoroethane (aOR 1.41, 95% CI 1.20, 1.66), tributyltin methacrylate (aOR 1.20, 95% CI 1.06, 1.36), and 1,1,1-trichloroethane (aOR 1.11, 95% CI 1.03, 1.20). These findings suggest that maternal residential proximity to industrial air emissions of some chemicals during pregnancy may be associated with LBW in offspring.