Assessing the impact of the local environment on birth outcomes: a case for HLM

Multi-Dimensional Comparison of the Impact Mechanism of the Self-Rated Health Status of Urban and Rural Residents in Chinese Social Environments

Self-rated health status (SRHS) reflects individuals' social environment, and the difference between urban and rural areas in China further highlights the impact of social environment on health. This paper aimed to systematically analyze and compare the impact mechanism of the SRHS of urban and rural residents from multiple dimensions, i.e., time, space, and scale. Drawing on data from the Chinese General Social Survey (CGSS) and China Statistical Yearbook, we used spatial, cross, and HLM analyses. Results indicate that: (1) From 2010 to 2017, the overall SRHS level of Chinese residents gradually declined; the gradient pattern of east, middle, and west became more marked, and the health level in rural areas generally fell behind that of urban areas. (2) The focus of SRHS moved toward mental health, and people's perceptions of the social environment gradually became a key factor affecting health. (3) In the long term, the gradient allocation of medical service resources could narrow the gap between urban and rural areas to comprehensively improve regional health levels.

Associations between maternal residential proximity to air emissions from industrial facilities and low birth weight in Texas, USA

BACKGROUND

Most previous studies examining associations between maternal exposures to air pollutants during pregnancy and low birth weight (LBW) in offspring focused on criteria air pollutants (PM_2.5, PM₁₀, O₃, NO₂, SO₂, CO, and Pb). The relationship between non-criteria air pollutants and LBW is understudied and requires greater coverage.

OBJECTIVES

This study investigated associations between maternal residential exposure to industrial air pollutants during pregnancy and LBW in offspring.

METHODS

This study used a case-control study design that included 94,106 term LBW cases and 376,424 controls. It covered 78 air pollutants common to both the Toxics Release Inventory (TRI) and ground air quality monitoring databases in Texas during 1996-2008. A modified version of the Emission Weighted Proximity Model (EWPM), calibrated with ground monitoring data, was used to estimate maternal residential exposure to industrial air pollutants during pregnancy. Binary logistic regression analyses were performed to calculate odds ratios (ORs) reflecting the associations of maternal exposure to industrial air pollutants and LBW in offspring, adjusted for child's sex, gestational weeks, maternal age, education, race/ethnicity, marital status, prenatal care, tobacco use during pregnancy, public health region of maternal residence, and year of birth. In addition, the Bonferroni correction for multiple comparisons was applied to the results of logistic regression analysis.

RESULTS

Relative to the non-exposed reference group, maternal residential exposure to benzene (adjusted odds ratio (aOR) 1.06, 95% confidence interval (CI) 1.04, 1.08), benzo(g,h,i)perylene (aOR 1.04, 95% CI 1.02, 1.07), cumene (aOR 1.05, 95% CI 1.03, 1.07), cyclohexane (aOR 1.04, 95% CI 1.02, 1.07), dichloromethane (aOR 1.04, 95% CI 1.03, 1.07), ethylbenzene (aOR 1.05, 95% CI 1.03, 1.06), ethylene (aOR 1.06, 95% CI 1.03, 1.09), mercury (aOR 1.04, 95% CI 1.02, 1.07), naphthalene (aOR 1.03, 95% CI 1.01, 1.05), n-hexane (aOR 1.06, 95% CI 1.04, 1.08), propylene (aOR 1.06, 95% CI 1.03, 1.10), styrene (aOR 1.06, 95% CI 1.04, 1.08), toluene (aOR 1.05, 95% CI 1.03, 1.07), and zinc (fume or dust) (aOR 1.10, 95% CI 1.06, 1.13) was found to have significantly higher odds of LBW in offspring. When the estimated exposures were categorized into four different groups (zero, low, medium, and high) in the analysis, eleven of the fourteen air pollutants, with the exception of benzo(g,h,i)perylene, ethylene, and propylene, remained as significant risk factors.

CONCLUSIONS

Results indicate that maternal residential proximity to industrial facilities emitting any of the fourteen pollutants identified by this study during pregnancy may be associated with LBW in offspring. With the exception of benzene, ethylbenzene, toluene, and zinc, the rest of the fourteen air pollutants are identified as LBW risk factors for the first time by this study. Further epidemiological, biological, and toxicological studies are suggested to verify the findings from this study.

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 (PM_2.5, 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.

Validity of the Emission Weighted Proximity Model in estimating air pollution exposure intensities in large geographic areas

BACKGROUND

Accurate estimates of air pollution exposure intensities are important to support environmental epidemiology analyses that require data covering large geographic areas over multiple years. The Emission Weighted Proximity Model (EWPM) and the National-Scale Air Toxics Assessment (NATA) are two viable approaches for obtaining estimate exposure intensities. The advantages of the EWPM include its simplicity and significantly lower costs of implementation. However, very limited data are available regarding the validity of the results from the EWPM and how these results would fare when compared with those from the NATA.

METHODS

This study evaluates the validity of the estimated exposure intensities from the EWPM through a correlation analysis with ground monitoring data obtained by the Texas Commission on Environmental Quality (TCEQ). The monitoring data used in the comparison included 27 non-criteria air pollutants at 48 monitoring sites in Texas in 2005. In addition, this study compares the results from the EWPM with those from NATA using the TCEQ data as a gold standard.

RESULTS

Analysis results suggest that estimated exposure intensities from the EWPM and the NATA were comparable when the intensities from both approaches are used to categorize environmental exposure intensities into different levels in relative terms.

CONCLUSION

These findings suggest that the EWPM is a valid alternative approach to the NATA in situations where epidemiological analysis requires both environmental data and health outcome data that cover a large geographic area over multiple years.

Spatial variations in the associations of term birth weight with ambient air pollution in Georgia, USA

Birth weight is an important indicator of overall infant health and a strong predictor of infant morbidity and mortality, and low birth weight (LBW) is a leading cause of infant mortality in the United States. Numerous studies have examined the associations of birth weight with ambient air pollution, but the results were inconsistent. In this study, a spatial statistical technique, geographically weighted regression (GWR) is applied to explore the spatial variations in the associations of birth weight with concentrations of ozone (O3) and fine particulate matter (PM2.5) in the State of Georgia, USA adjusted for gestational age, parity, and six other socioeconomic, behavioral, and land use factors. The results show considerable spatial variations in the associations of birth weight with both pollutants. Significant positive, non-significant, and significant negative relationships between birth weight and concentrations of each air pollutant are all found in different parts of the study area, and the different types of the relationships are affected by the socioeconomic and urban characteristics of the communities where the births are located. The significant negative relationships between birth weight and O3 indicate that O3 is a significant risk factor of LBW and these associations are primarily located in less-urbanized communities. On the other hand, PM2.5 is a significant risk factor of LBW in the more-urbanized communities with higher family income and education attainment. These findings suggest that environmental and health policies should be adjusted to address the different effects of air pollutants on birth outcomes across different types of communities to more effectively and efficiently improve birth outcomes.

Spatial variability of the effect of air pollution on term birth weight: evaluating influential factors using Bayesian hierarchical models

BACKGROUND

Epidemiological studies suggest that air pollution is adversely associated with pregnancy outcomes. Such associations may be modified by spatially-varying factors including socio-demographic characteristics, land-use patterns and unaccounted exposures. Yet, few studies have systematically investigated the impact of these factors on spatial variability of the air pollution's effects. This study aimed to examine spatial variability of the effects of air pollution on term birth weight across Census tracts and the influence of tract-level factors on such variability.

METHODS

We obtained over 900,000 birth records from 2001 to 2008 in Los Angeles County, California, USA. Air pollution exposure was modeled at individual level for nitrogen dioxide (NO2) and nitrogen oxides (NOx) using spatiotemporal models. Two-stage Bayesian hierarchical non-linear models were developed to (1) quantify the associations between air pollution exposure and term birth weight within each tract; and (2) examine the socio-demographic, land-use, and exposure-related factors contributing to the between-tract variability of the associations between air pollution and term birth weight.

RESULTS

Higher air pollution exposure was associated with lower term birth weight (average posterior effects: -14.7 (95 % CI: -19.8, -9.7) g per 10 ppb increment in NO2 and -6.9 (95 % CI: -12.9, -0.9) g per 10 ppb increment in NOx). The variation of the association across Census tracts was significantly influenced by the tract-level socio-demographic, exposure-related and land-use factors. Our models captured the complex non-linear relationship between these factors and the associations between air pollution and term birth weight: we observed the thresholds from which the influence of the tract-level factors was markedly exacerbated or attenuated. Exacerbating factors might reflect additional exposure to environmental insults or lower socio-economic status with higher vulnerability, whereas attenuating factors might indicate reduced exposure or higher socioeconomic status with lower vulnerability.

CONCLUSIONS

Our Bayesian models effectively combined a priori knowledge with training data to infer the posterior association of air pollution with term birth weight and to evaluate the influence of the tract-level factors on spatial variability of such association. This study contributes new findings about non-linear influences of socio-demographic factors, land-use patterns, and unaccounted exposures on spatial variability of the effects of air pollution.

Modeling spatial effects of PM(2.5) on term low birth weight in Los Angeles County

Air pollution epidemiological studies suggest that elevated exposure to fine particulate matter (PM2.5) is associated with higher prevalence of term low birth weight (TLBW). Previous studies have generally assumed the exposure-response of PM2.5 on TLBW to be the same throughout a large geographical area. Health effects related to PM2.5 exposures, however, may not be uniformly distributed spatially, creating a need for studies that explicitly investigate the spatial distribution of the exposure-response relationship between individual-level exposure to PM2.5 and TLBW. Here, we examine the overall and spatially varying exposure-response relationship between PM2.5 and TLBW throughout urban Los Angeles (LA) County, California. We estimated PM2.5 from a combination of land use regression (LUR), aerosol optical depth from remote sensing, and atmospheric modeling techniques. Exposures were assigned to LA County individual pregnancies identified from electronic birth certificates between the years 1995-2006 (N=1,359,284) provided by the California Department of Public Health. We used a single pollutant multivariate logistic regression model, with multilevel spatially structured and unstructured random effects set in a Bayesian framework to estimate global and spatially varying pollutant effects on TLBW at the census tract level. Overall, increased PM2.5 level was associated with higher prevalence of TLBW county-wide. The spatial random effects model, however, demonstrated that the exposure-response for PM2.5 and TLBW was not uniform across urban LA County. Rather, the magnitude and certainty of the exposure-response estimates for PM2.5 on log odds of TLBW were greatest in the urban core of Central and Southern LA County census tracts. These results suggest that the effects may be spatially patterned, and that simply estimating global pollutant effects obscures disparities suggested by spatial patterns of effects. Studies that incorporate spatial multilevel modeling with random coefficients allow us to identify areas where air pollutant effects on adverse birth outcomes may be most severe and policies to further reduce air pollution might be most effective.

Interactive and independent associations between the socioeconomic and objective built environment on the neighbourhood level and individual health: a systematic review of multilevel studies

BACKGROUND

The research question how contextual factors of neighbourhood environments influence individual health has gained increasing attention in public health research. Both socioeconomic neighbourhood characteristics and factors of the built environment play an important role for health and health-related behaviours. However, their reciprocal relationships have not been systematically reviewed so far. This systematic review aims to identify studies applying a multilevel modelling approach which consider both neighbourhood socioeconomic position (SEP) and factors of the objective built environment simultaneously in order to disentangle their independent and interactive effects on individual health.

METHODS

The three databases PubMed, PsycINFO, and Web of Science were systematically searched with terms for title and abstract screening. Grey literature was not included. Observational studies from USA, Canada, Australia, New Zealand, and Western European countries were considered which analysed simultaneously factors of neighbourhood SEP and the objective built environment with a multilevel modelling approach. Adjustment for individual SEP was a further inclusion criterion.

RESULTS

Thirty-three studies were included in qualitative synthesis. Twenty-two studies showed an independent association between characteristics of neighbourhood SEP or the built environment and individual health outcomes or health-related behaviours. Twenty-one studies found cross-level or within-level interactions either between neighbourhood SEP and the built environment, or between neighbourhood SEP or the built environment and individual characteristics, such as sex, individual SEP or ethnicity. Due to the large variation of study design and heterogeneous reporting of results the identification of consistent findings was problematic and made quantitative analysis not possible.

CONCLUSIONS

There is a need for studies considering multiple neighbourhood dimensions and applying multilevel modelling in order to clarify their causal relationship towards individual health. Especially, more studies using comparable characteristics of neighbourhood SEP and the objective built environment and analysing interactive effects are necessary to disentangle health impacts and identify vulnerable neighbourhoods and population groups.

Multilevel analysis of air pollution and early childhood neurobehavioral development

To investigate the association between the ambient air pollution levels during the prenatal and postnatal stages and early childhood neurobehavioral development, our study recruited 533 mother-infant pairs from 11 towns in Taiwan. All study subjects were asked to complete childhood neurobehavioral development scales and questionnaires at 6 and 18 months. Air pollution, including particulate matter ≤10 μm (PM10), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and hydrocarbons, was measured at air quality monitoring stations in the towns where the subjects lived. Multilevel analyses were applied to assess the association between air pollution and childhood neurobehavioral development during pregnancy and when the children were 0 to 6 months, 7 to 12 months, and 13 to 18 months old. At 18 months, poor subclinical neurodevelopment in early childhood is associated with the average SO2 exposure of prenatal, during all trimesters of pregnancy and at postnatal ages up to 12 months (first trimester β = -0.083, se = 0.030; second and third trimester β = -0.114, se = 0.045; from birth to 12 months of age β = -0.091, se = 0.034). Furthermore, adverse gross motor below average scores at six months of age were associated with increased average non-methane hydrocarbon, (NMHC) levels during the second and third trimesters (β = -8.742, se = 3.512). Low-level SO2 exposure prenatally and up to twelve months postnatal could cause adverse neurobehavioral effects at 18 months of age. Maternal NMHC exposure during the 2nd and 3rd trimesters of pregnancy would be also associated with poor gross motor development in their children at 6 months of age.

Assessing the impact of race, social factors and air pollution on birth outcomes: a population-based study

BACKGROUND

Both air pollution exposure and socioeconomic status (SES) are important indicators of children's health. Using highly resolved modeled predictive surfaces, we examine the joint effects of air pollution exposure and measures of SES in a population level analysis of pregnancy outcomes in North Carolina (NC).

METHODS

Daily measurements of particulate matter <2.5 μm in aerodynamic diameter (PM2.5) and ozone (O3) were calculated through a spatial hierarchical Bayesian model which produces census-tract level point predictions. Using multilevel models and NC birth data from 2002-2006, we examine the association between pregnancy averaged PM2.5 and O3, individual and area-based SES indicators, and birth outcomes.

RESULTS

Maternal race and education, and neighborhood household income were associated with adverse birth outcomes. Predicted concentrations of PM2.5 and O3 were also associated with an additional effect on reductions in birth weight and increased risks of being born low birth weight and small for gestational age.

CONCLUSIONS

This paper builds on and complements previous work on the relationship between pregnancy outcomes and air pollution exposure by using 1) highly resolved air pollution exposure data; 2) a five-year population level sample of pregnancies; and 3) including personal and areal level measures of social determinants of pregnancy outcomes. Results show a stable and negative association between air pollution exposure and adverse birth outcomes. Additionally, the more socially disadvantaged populations are at a greater risk; controlling for both SES and environmental stressors provides a better understanding of the contributing factors to poor children's health outcomes.

The social determinants of infant mortality and birth outcomes in Western developed nations: a cross-country systematic review

Infant mortality (IM) and birth outcomes, key population health indicators, have lifelong implications for individuals, and are unequally distributed globally. Even among western industrialized nations, striking cross-country and within-country patterns are evident. We sought to better understand these variations across and within the United States of America (USA) and Western Europe (WE), by conceptualizing a social determinants of IM/birth outcomes framework, and systematically reviewing the empirical literature on hypothesized social determinants (e.g., social policies, neighbourhood deprivation, individual socioeconomic status (SES)) and intermediary determinants (e.g., health behaviours). To date, the evidence suggests that income inequality and social policies (e.g., maternal leave policies) may help to explain cross-country variations in IM/birth outcomes. Within countries, the evidence also supports neighbourhood SES (USA, WE) and income inequality (USA) as social determinants. By contrast, within-country social cohesion/social capital has been underexplored. At the individual level, mixed associations have been found between individual SES, race/ethnicity, and selected intermediary factors (e.g., psychosocial factors) with IM/birth outcomes. Meanwhile, this review identifies several methodological gaps, including the underuse of prospective designs and the presence of residual confounding in a number of studies. Ultimately, addressing such gaps including through novel approaches to strengthen causal inference and implementing both health and non-health policies may reduce inequities in IM/birth outcomes across the western developed world.

Income inequality, parental socioeconomic status, and birth outcomes in Japan

The purpose of this study was to investigate the impact of income inequality and parental socioeconomic status on several birth outcomes in Japan. Data were collected on birth outcomes and parental socioeconomic status by questionnaire from Japanese parents nationwide (n = 41,499) and then linked to Gini coefficients at the prefectural level in 2001. In multilevel analysis, z scores of birth weight for gestational age decreased by 0.018 (95% confidence interval (CI): -0.029, -0.006) per 1-standard-deviation (0.018-unit) increase in the Gini coefficient, while gestational age at delivery was not associated with the Gini coefficient. For dichotomous outcomes, mothers living in prefectures with middle and high Gini coefficients were 1.24 (95% CI: 1.05, 1.47) and 1.23 (95% CI: 1.02, 1.48) times more likely, respectively, to deliver a small-for-gestational-age infant than mothers living in more egalitarian prefectures (low Gini coefficients), although preterm births were not significantly associated with income distribution. Parental educational level, but not household income, was significantly associated with the z score of birth weight for gestational age and small-for-gestational-age status. Higher income inequality at the prefectural level and parental educational level, rather than household income, were associated with intrauterine growth but not with shorter gestational age at delivery.

Ambient air pollution, birth weight and preterm birth: a systematic review and meta-analysis

Low birth weight and preterm birth have a substantial public health impact. Studies examining their association with outdoor air pollution were identified using searches of bibliographic databases and reference lists of relevant papers. Pooled estimates of effect were calculated, heterogeneity was quantified, meta-regression was conducted and publication bias was examined. Sixty-two studies met the inclusion criteria. The majority of studies reported reduced birth weight and increased odds of low birth weight in relation to exposure to carbon monoxide (CO), nitrogen dioxide (NO(2)) and particulate matter less than 10 and 2.5 microns (PM(10) and PM(2.5)). Effect estimates based on entire pregnancy exposure were generally largest. Pooled estimates of decrease in birth weight ranged from 11.4 g (95% confidence interval -6.9-29.7) per 1 ppm CO to 28.1g (11.5-44.8) per 20 ppb NO(2), and pooled odds ratios for low birth weight ranged from 1.05 (0.99-1.12) per 10 μg/m(3) PM(2.5) to 1.10 (1.05-1.15) per 20 μg/m(3) PM(10) based on entire pregnancy exposure. Fewer effect estimates were available for preterm birth and results were mixed. Pooled odds ratios based on 3rd trimester exposures were generally most precise, ranging from 1.04 (1.02-1.06) per 1 ppm CO to 1.06 (1.03-1.11) per 20 μg/m(3) PM(10). Results were less consistent for ozone and sulfur dioxide for all outcomes. Heterogeneity between studies varied widely between pollutants and outcomes, and meta-regression suggested that heterogeneity could be partially explained by methodological differences between studies. While there is a large evidence base which is indicative of associations between CO, NO(2), PM and pregnancy outcome, variation in effects by exposure period and sources of heterogeneity between studies should be further explored.

The association between neighbourhoods and adverse birth outcomes: a systematic review and meta-analysis of multi-level studies

Many studies have examined the role of neighbourhood environment on birth outcomes but, because of differences in study design and modelling techniques, have found conflicting results. Seven databases were searched (1900-2010) for multi-level observational studies related to neighbourhood and pregnancy/birth. We identified 1502 articles of which 28 met all inclusion criteria. Meta-analysis was used to examine the association between neighbourhood income and low birthweight. Most studies showed a significant association between neighbourhood factors and birth outcomes. A significant pooled association was found for the relationship between neighbourhood income and low birthweight [odds ratio = 1.11, 95% confidence interval: 1.02, 1.20] whereby women who lived in low income neighbourhoods had significantly higher odds of having a low birthweight infant. This body of literature was found to consistently document significant associations between neighbourhood factors and birth outcomes. The consistency of findings from observational studies in this area indicates a need for causal studies to determine the mechanisms by which neighbourhoods influence birth outcomes.

The effects of socioeconomic status and indices of physical environment on reduced birth weight and preterm births in Eastern Massachusetts

BACKGROUND

Air pollution and social characteristics have been shown to affect indicators of health. While use of spatial methods to estimate exposure to air pollution has increased the power to detect effects, questions have been raised about potential for confounding by social factors.

METHODS

A study of singleton births in Eastern Massachusetts was conducted between 1996 and 2002 to examine the association between indicators of traffic, land use, individual and area-based socioeconomic measures (SEM), and birth outcomes (birth weight, small for gestational age and preterm births), in a two-level hierarchical model.

RESULTS

We found effects of both individual (education, race, prenatal care index) and area-based (median household income) SEM with all birth outcomes. The associations for traffic and land use variables were mainly seen with birth weight, with an exception for an effect of cumulative traffic density on small for gestational age. Race/ethnicity of mother was an important predictor of birth outcomes and a strong confounder for both area-based SEM and indices of physical environment. The effects of traffic and land use differed by level of education and median household income.

CONCLUSION

Overall, the findings of the study suggested greater likelihood of reduced birth weight and preterm births among the more socially disadvantaged, and a greater risk of reduced birth weight associated with traffic exposures. Results revealed the importance of controlling simultaneously for SEM and environmental exposures as the way to better understand determinants of health.

Influences of study design and location on the relationship between particulate matter air pollution and birthweight

A large number of studies have identified a relationship between particulate matter air pollution and birthweight. Although reported associations are small and varied, they have been identified in studies from places around the world. Exposure assignment, covariates and study inclusion criteria vary among studies. To examine the effect of these and other study characteristics on associations between particulate matter and birthweight, US birth records for singletons delivered at 40 weeks gestation in 2001-03 during the months of March, June, September and December were linked to quarterly estimates of pollution exposure, both particulate matter exposure and exposure to multiple pollutants, by county of residence and month of birth. Annual, 9-month and trimester-specific exposures were assigned. Among births linked to particulate matter exposure there was a small association between coarse particle exposure and birthweight (beta -13 g per 10 microg/m(3) increase [95% CI -18.3 g, -7.6 g]) after controlling for maternal factors; this association was attenuated slightly and remained statistically significant after further adjustment for contextual factors, year of birth, region, or urban-rural status. The associations were slightly weaker among births linked to multiple pollutant exposure than among births linked to just particulate matter exposure. The association varied markedly by region, ranging from a decrement of 43 g per 10 microg/m(3)[95% CI -58.6 g, -27.6 g] in the north-west to a null association in the south-west. Trimester findings were smaller, yet remained significant and varied regionally. The association between fine particle exposure and birthweight varied considerably, with an overall small positive association that became null after control for region. This study found that wide regional differences in association may contribute to the varied published findings. The association between coarse particle exposure and birthweight appeared robust, if small; fine particles had no overall association with birthweight.