The issue of confounding in epidemiological studies of ambient air pollution and pregnancy outcomes

The spatial modification of the non-linear effects of ambient oxides of nitrogen during pregnancy on birthweight in a South African birth cohort

Birthweight is strongly associated with infant mortality and is a major determinant of infant survival. Several factors such as maternal, environmental, clinical, and social factors influence birthweight, and these vary geographically, including across low, middle, and economically advanced countries. The aim of the study was to investigate the geographical modification of the effect of oxides of nitrogen exposure on birthweight adjusted for clinical and socio-demographic factors. Data for the study was obtained from the Mother and Child in the Environment birth cohort study in Durban, South Africa. Pregnant females were selected from public sector antenatal clinics in low socioeconomic neighborhoods. Land use regression models were used to determine household level antenatal exposure to oxides of nitrogen (NOx). Six hundred and seventy-seven births were analysed, using the geoadditive model with Gaussian distribution and identity link function. The newborns in the cohort had a mean birthweight of 3106.5 g (standard deviation (SD): 538.2 g and the maternal mean age was 26.1 years (SD: 5.7). A spatially modified NOx exposure-related effect on birthweight was found across two geographic regions in Durban. Prenatal exposure to NOx was also found to have a non-linear effect on the birthweight of infants. The study suggested that incorporating spatial variability is important to understand and design appropriate policies to reduce air pollution in order to prevent risks associated with birthweight.

Ambient air pollution and pregnancy outcomes: A comprehensive review and identification of environmental public health challenges

There is a growing number of studies on the association between ambient air pollution and adverse pregnancy outcomes, but their results have been inconsistent. Consequently, a comprehensive review of this research area is needed. There was a wide variability in studied pregnancy outcomes, observed gestational windows of exposure, observed ambient air pollutants, applied exposure assessment methods and statistical analysis methods Gestational duration, preterm birth, (low) birth weight, and small for gestational age/intrauterine growth restriction were most commonly investigated pregnancy outcomes. Gestational windows of exposure typically included were whole pregnancy period, 1st, 2nd, 3rd trimester, first and last gestational months. Preterm birth was the outcome most extensively studied across various gestational windows, especially at the beginning and at the end of pregnancy. Particulate matter, nitrogen dioxide, ozone, and carbon monoxide were the most commonly used markers of ambient air pollution. Continuous monitoring data were frequently combined with spatially more precisely modelled estimates of exposure. Exposure to particulate matter and ozone over the entire pregnancy was significantly associated with higher risk for preterm birth: the pooled effect estimates were 1.09 (1.03-1.16) per 10 μg/m³ increase in particulate matter with an aerodynamic diameter of 10 µm or less (PM₁₀)_,1.24 (1.08-1.41) per 10 μg/m³ increase in particulate matter with an aerodynamic diameter of 2.5 µm or less (PM_2.5), and 1.03 (1.01-1.04) per 10 ppb increase in ozone. For pregnancy outcomes other than PTB, ranges of observed effect estimates were reported due to smaller number of studies included in each gestational window of exposure. Further research is needed to link the routine pregnancy outcome data with spatially and temporally resolved ambient air pollution data, while adjusting for commonly defined confounders. Methods for assessing exposure to mixtures of pollutants, indoor air pollution exposure, and various other environmental exposures, need to be developed.

Using a Clustering Approach to Investigate Socio-Environmental Inequality in Preterm Birth-A Study Conducted at Fine Spatial Scale in Paris (France)

Background & Objectives: Today, to support public policies aiming to tackle environmental and health inequality, identification and monitoring of the spatial pattern of adverse birth outcomes are crucial. Spatial identification of the more vulnerable population to air pollution may orient health interventions. In this context, the objective of this study is to investigate the geographical distribution of the risk of preterm birth (PTB, gestational age ≤36 weeks) at the census block level in in city of Paris, France. We also aimed to assess the implication of neighborhood characteristics including air pollution and socio-economic deprivation. Material & Methods: Newborn health data are available from the first birth certificate registered by the Maternal and Child Care department of Paris. All PTB from January 2008 to December 2011 were geocoded at the mother residential census block. Each census block was assigned a socioeconomic deprivation level and annual average ambient concentrations of NO₂. A spatial clustering approach was used to investigate the spatial distribution of PTB. Results: Our results highlight that PTB is non-randomly spatially distributed, with a cluster of high risk in the northeastern area of Paris (RR = 1.15; p = 0.06). After adjustment for socio-economic deprivation and NO₂ concentrations, this cluster becomes not statistically significant or shifts suggesting that these characteristics explain the spatial distribution of PTB; further, their combination shows an interaction in comparison with SES or NO₂ levels alone. Conclusions: Our results may inform the decision makers about the areas where public health efforts should be strengthened to tackle the risk of PTB and to choose the most appropriate and specific community-oriented health interventions.

Improving predictive asthma algorithms with modelled environment data for Scotland: an observational cohort study protocol

INTRODUCTION

Asthma has a considerable, but potentially, avoidable burden on many populations globally. Scotland has some of the poorest health outcomes from asthma. Although ambient pollution, weather changes and sociodemographic factors have been associated with asthma attacks, it remains unclear whether modelled environment data and geospatial information can improve population-based asthma predictive algorithms. We aim to create the afferent loop of a national learning health system for asthma in Scotland. We will investigate the associations between ambient pollution, meteorological, geospatial and sociodemographic factors and asthma attacks.

METHODS AND ANALYSIS

We will develop and implement a secured data governance and linkage framework to incorporate primary care health data, modelled environment data, geospatial population and sociodemographic data. Data from 75 recruited primary care practices (n=500 000 patients) in Scotland will be used. Modelled environment data on key air pollutants at a horizontal resolution of 5 km×5 km at hourly time steps will be generated using the EMEP4UK atmospheric chemistry transport modelling system for the datazones of the primary care practices' populations. Scottish population census and education databases will be incorporated into the linkage framework for analysis. We will then undertake a longitudinal retrospective observational analysis. Asthma outcomes include asthma hospitalisations and oral steroid prescriptions. Using a nested case-control study design, associations between all covariates will be measured using conditional logistic regression to account for the matched design and to identify suitable predictors and potential candidate algorithms for an asthma learning health system in Scotland.Findings from this study will contribute to the development of predictive algorithms for asthma outcomes and be used to form the basis for our learning health system prototype.

ETHICS AND DISSEMINATION

The study received National Health Service Research Ethics Committee approval (16/SS/0130) and also obtained permissions via the Public Benefit and Privacy Panel for Health and Social Care in Scotland to access, collate and use the following data sets: population and housing census for Scotland; Scottish education data via the Scottish Exchange of Data and primary care data from general practice Data Custodians. Analytic code will be made available in the open source GitHub website. The results of this study will be published in international peer reviewed journals.

Association between pregnancy exposure to air pollution and birth weight in selected areas of Norway

BACKGROUND

Exposure to air pollution has adverse effects on cardiopulmonary health of adults. Exposure to air pollution in pregnancy may affect foetal development. However, the evidence of such effect remains inconsistent. We investigated the effects of exposure to air pollution during pregnancy on birth outcomes.

METHODS

This study, based within the Norwegian Mother and Child Cohort Study (MoBa), includes 17,533 participants living in the two largest cities in Norway: Oslo and Bergen, and their two surrounding counties: Akershus and Hordaland. Air pollution levels at residential addresses were estimated using land use regression models and back-extrapolated to the period of each pregnancy using continuous monitoring station data. Birth outcomes were birth weight, low birth weight, gestational age, and preterm delivery obtained from the Medical Birth Registry of Norway. Information on lifestyle factors was collected from MoBa questionnaires completed by mothers during pregnancy. Linear and logistic regression models were used to analyse the associations between pregnancy NO2 exposure and birth outcomes.

RESULTS

We found a statistically significant negative association between pregnancy exposure to NO2 and birth weight -43.6 (95%CI -55.8 to -31.5) g per 10 μg/m(3) NO2. However, after adjusting for either area or the combination of parity and maternal weight, no substantive effects of air pollution exposure were evident.

CONCLUSIONS

Exposure to air pollution during pregnancy was associated with decrease in birth weight, but area-related and lifestyle factors attenuated this association. We found no statistically significant associations of air pollution exposure with gestational age, low birth weight or preterm delivery.

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.

Place of work and residential exposure to ambient air pollution and birth outcomes in Scotland, using geographically fine pollution climate mapping estimates

OBJECTIVES

A relationship between ambient air pollution and adverse birth outcomes has been found in a large number of studies that have mainly used a nearest monitor methodology. Recent research has suggested that the effect size may have been underestimated in these studies. This paper examines associations between birth outcomes and ambient levels of residential and workplace sulphur dioxide, particulates and Nitrogen Dioxide estimated using an alternative method - pollution climate mapping.

METHODS

Risk of low birthweight and mean birthweight (for n=21,843 term births) and risk of preterm birth (for n=23,086 births) were modelled against small area annual mean ambient air pollution concentrations at work and residence location adjusting for potential confounding factors for singleton live births (1994-2008) across Scotland.

RESULTS

Odds ratios of low birthweight of 1.02 (95% CI, 1.01-1.03) and 1.07 (95% CI, 1.01-1.12) with concentration increases of 1 µg/m(3) for NO2 and PM10 respectively. Raised but insignificant risks of very preterm birth were found with PM10 (relative risk ratio=1.08; 95% CI, 1.00 to 1.17 per 1 µg/m(3)) and NO2 (relative risk ratio=1.01; 95% CI, 1.00 to 1.03 per 1 µg/m(3)). An inverse association between mean birthweight and mean annual NO2(-1.24 g; 95% CI, -2.02 to -0.46 per 1 µg/m(3)) and PM10 (-5.67 g; 95% CI, -9.47 to -1.87 per 1 µg/m(3)). SO2 showed no significant associations.

CONCLUSIONS

This study highlights the association between air pollution exposure and reduced newborn size at birth. Together with other recent work it also suggests that exposure estimation based on the nearest monitor method may have led to an under-estimation of the effect size of pollutants on birth outcomes.

A spatial time-to-event approach for estimating associations between air pollution and preterm birth

The paper describes a Bayesian spatial discrete time survival model to estimate the effect of air pollution on the risk of preterm birth. The standard approach treats prematurity as a binary outcome and cannot effectively examine time varying exposures during pregnancy. Time varying exposures can arise either in short-term lagged exposures due to seasonality in air pollution or long-term cumulative exposures due to changes in length of exposure. Our model addresses this challenge by viewing gestational age as time-to-event data where each pregnancy becomes at risk at a prespecified time (e.g. the 28th week). The pregnancy is then followed until either a birth occurs before the 37th week (preterm), or it reaches the 37th week, and a full-term birth is expected. The model also includes a flexible spatially varying baseline hazard function to control for unmeasured spatial confounders and to borrow information across areal units. The approach proposed is applied to geocoded birth records in Mecklenburg County, North Carolina, for the period 2001-2005.We examine the risk of preterm birth that is associated with total cumulative and 4-week lagged exposure to ambient fine particulate matter.

A method to detect residual confounding in spatial and other observational studies

BACKGROUND

Residual confounding is challenging to detect. Recently, we described a method for detecting confounding and justified it primarily for time-series studies. The method depends on an indicator with 2 key characteristics: (1) it is conditionally independent (given measured exposures and covariates) of the outcome, in the absence of confounding, misspecification, and measurement errors; and (2) like the exposure, it is associated with confounders, possibly unmeasured. We proposed using future exposure levels as the indicator to detect residual confounding. This choice seems natural for time-series studies because future exposure cannot have caused the event, yet they could be spuriously related to it. A related question addressed here is whether an analogous indicator can be used to identify residual confounding in a study based on spatial, rather than temporal, contrasts.

METHODS

Using directed acyclic graphs, we show that future air pollution levels may have the characteristics appropriate for an indicator of residual confounding in spatial studies of environmental exposures. We empirically evaluate performance for spatial studies using simulations.

RESULTS

In simulations based on a spatial study of ambient air pollution levels and birth weight in Atlanta, and using ambient air pollution 1 year after conception as the indicator, we were able to detect residual confounding. The discriminatory ability approached 100% for some factors intentionally omitted from the model, but was very weak for others.

CONCLUSION

The simulations illustrate that an indicator based on future exposures can have excellent ability to detect residual confounding in spatial studies, although performance varied by situation.

Temporal variation in air pollution concentrations and preterm birth-a population based epidemiological study

There is growing evidence of adverse birth outcomes due to exposure to air pollution during gestation. However, recent negative studies are also reported. The aim of this study was to assess the effect of ozone and vehicle exhaust exposure (NO(2)) on the length of the gestational period and risk of preterm delivery. We used data from the Swedish Medical Birth Registry on all vaginally delivered singleton births in the Greater Stockholm area who were conceived during 1987-1995 (n = 115,588). Daily average levels of NO(2) (from three measuring stations) and ozone (two stations) were used to estimate trimester and last week of gestation average exposures. Linear regression models were used to assess the association between the two air pollutants and three exposure windows, while logistic regression models were used when analyzing associations with preterm delivery (<37 weeks gestation). Five percent were born preterm. The median gestational period was 40 weeks. Higher levels of ozone during the first trimester were associated with shorter gestation as well as with an elevated risk of preterm delivery, the odds ratio from the most complex model was 1.06 (95% CI: 1.00-1.13) per 10 μg/m(3) increase in the mean daily 8-h maximum concentration. Higher levels of ozone during the second trimester were associated with shorter gestation but the elevated risk of preterm delivery was not statistically significant. Higher levels of ozone and NO(2) during the last week of gestation were associated with a shorter duration of gestation and NO(2) also with preterm delivery. There were no significant associations between first and second trimester NO(2) exposure estimates and studied outcomes. The effect of first trimester ozone exposure, known to cause oxidative stress, was smallest among women who conceived during autumn when vitamin D status, important for fetal health, in Scandinavian women is the highest.

Time-to-event analysis of fine particle air pollution and preterm birth: results from North Carolina, 2001-2005

Exposure to air pollution during pregnancy has been suggested to be a risk factor for preterm birth; however, epidemiologic evidence remains mixed and limited. The authors examined the association between ambient levels of particulate matter <2.5 μm in aerodynamic diameter (PM(2.5)) and the risk of preterm birth in North Carolina during the period 2001-2005. They estimated the risks of cumulative and lagged average exposures to PM(2.5) during pregnancy via a 2-stage discrete-time survival model. The authors also considered exposure metrics derived from 1) ambient concentrations measured by the Air Quality System (AQS) monitoring network and 2) concentrations predicted by statistically fusing AQS data with process-based numerical model output (the Statistically Fused Air and Deposition Surfaces (FSD) database). Using the AQS measurements, an interquartile-range (1.73 μg/m(3)) increase in cumulative PM(2.5) exposure was associated with a 6.8% (95% posterior interval: 0.5, 13.6) increase in the risk of preterm birth. Using the FSD-predicted levels and accounting for prediction error, the authors also found significant adverse associations between trimester 1, trimester 2, and cumulative PM(2.5) exposure and preterm birth. These findings suggest that exposure to ambient PM(2.5) during pregnancy is associated with increased risk of preterm birth, even in a region characterized by relatively good air quality.

The International Collaboration on Air Pollution and Pregnancy Outcomes: initial results

BACKGROUND

The findings of prior studies of air pollution effects on adverse birth outcomes are difficult to synthesize because of differences in study design.

OBJECTIVES

The International Collaboration on Air Pollution and Pregnancy Outcomes was formed to understand how differences in research methods contribute to variations in findings. We initiated a feasibility study to a) assess the ability of geographically diverse research groups to analyze their data sets using a common protocol and b) perform location-specific analyses of air pollution effects on birth weight using a standardized statistical approach.

METHODS

Fourteen research groups from nine countries participated. We developed a protocol to estimate odds ratios (ORs) for the association between particulate matter ≤ 10 μm in aerodynamic diameter (PM₁₀) and low birth weight (LBW) among term births, adjusted first for socioeconomic status (SES) and second for additional location-specific variables.

RESULTS

Among locations with data for the PM₁₀ analysis, ORs estimating the relative risk of term LBW associated with a 10-μg/m³ increase in average PM₁₀ concentration during pregnancy, adjusted for SES, ranged from 0.63 [95% confidence interval (CI), 0.30-1.35] for the Netherlands to 1.15 (95% CI, 0.61-2.18) for Vancouver, with six research groups reporting statistically significant adverse associations. We found evidence of statistically significant heterogeneity in estimated effects among locations.

CONCLUSIONS

Variability in PM₁₀-LBW relationships among study locations remained despite use of a common statistical approach. A more detailed meta-analysis and use of more complex protocols for future analysis may uncover reasons for heterogeneity across locations. However, our findings confirm the potential for a diverse group of researchers to analyze their data in a standardized way to improve understanding of air pollution effects on birth outcomes.

Ambient air pollution and birth weight in full-term infants in Atlanta, 1994-2004

BACKGROUND

An emerging body of evidence suggests that ambient levels of air pollution during pregnancy are associated with fetal growth.

OBJECTIVES

We examined relationships between birth weight and temporal variation in ambient levels of carbon monoxide, nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone, particulate matter ≤ 10 μm in diameter (PM₁₀), ≤ 2.5 μm (PM(2.5)), 2.5 to 10 µm (PM(2.5-10)), and PM(2.5) chemical component measurements for 406,627 full-term births occurring between 1994 and 2004 in five central counties of metropolitan Atlanta.

METHODS

We assessed relationships between birth weight and pollutant concentrations during each infant's first month of gestation and third trimester, as well as in each month of pregnancy using distributed lag models. We also conducted capture-area analyses limited to mothers residing within 4 miles (6.4 km) of each air quality monitoring station.

RESULTS

In the five-county analysis, ambient levels of NO₂, SO₂, PM(2.5) elemental carbon, and PM(2.5) water-soluble metals during the third trimester were significantly associated with small reductions in birth weight (-4 to -16 g per interquartile range increase in pollutant concentrations). Third-trimester estimates were generally higher in Hispanic and non-Hispanic black infants relative to non-Hispanic white infants. Distributed lag models were also suggestive of associations between air pollutant concentrations in late pregnancy and reduced birth weight. The capture-area analyses provided little support for the associations observed in the five-county analysis.

CONCLUSIONS

Results provide some support for an effect of ambient air pollution in late pregnancy on birth weight in full-term infants.