Associations between birth outcomes and maternal PM2.5 exposure in Shanghai: A comparison of three exposure assessment approaches
Introduction
Preterm birth and low birth weight have been widely documented as significant predictors of infant mortality and have negative long-term effects in adulthood (CDC, 2002; Rogers and Velten, 2011; Swamy, 2011). Liu et al. (2015) estimated that in 2013, preterm birth ranked as the leading cause of death before age 5 and was responsible for 15.4% (0.965 million) of deaths before age 5 globally. Adverse birth outcomes in association with maternal exposure to PM2.5 (fine particulate matter with an aerodynamic diameter of 2.5 μm or less) have been studied in various populations (Li et al., 2017; Polichetti et al., 2013). While results from recent meta-analyses support the link between maternal PM2.5 exposure and adverse birth outcomes, substantial heterogeneity in health effect estimates exists among different studies (Sun et al., 2015; Sun et al., 2016). This heterogeneity is partly due to differences in exposure assessment methods, and the authors reported that studies assessing individual-level exposures tended to report stronger associations relative to studies assessing regional-level exposures. In addition, similar to many other health endpoints reported in the literature, the overwhelming majority of the included studies in these meta-analyses were conducted in the U.S. where PM2.5 levels are relatively low. Studies in highly polluted regions such as China can further elucidate the magnitude of PM2.5-associated health effects at high exposure levels. However, ground measurements of PM2.5 concentrations are often very sparse or nonexistent in most part of the developing world. For countries where the air quality monitoring network was established recently, lack of long-term measurements remains an obstacle to studying the association between adverse birth outcomes and exposure to PM2.5. Additionally, measurements from ground central monitors have limited spatial representativeness. Previous studies used specific buffers, ranging from 6.4 km to 50 km in radius, around monitoring stations to select study populations and assign exposure, with the intent of reducing exposure error (Chang et al., 2011; Darrow et al., 2011; Hyder et al., 2014). However, this method reduces sample size, and an optimal cutoff distance is difficult to determine.
To assess historical air pollution levels and characterize local-scale variability in air pollution, satellite-retrieved aerosol optical depth (AOD) has been used to predict ground PM2.5 concentrations during the past decade (Seltenrich, 2014). Polar-orbiting satellites have global coverage, long data records, and high spatiotemporal resolution, but missingness in satellite data has raised concerns regarding its use in epidemiological studies. Annually, 30 to 70% satellite retrievals can be missing due to cloud cover and high surface reflectance in East Asia (Xiao et al., 2016). Unfortunately, situations that lead to failed satellite retrievals often influence the production and deposition of PM2.5, e.g. cloud cover leads to reduced photochemical reactions. Thus, using satellite predictions without accounting for the non-random missingness may result in exposure misclassification. Strickland et al. (2016) evaluated the influence of missing satellite-derived PM2.5 predictions on the association between short-term PM2.5 exposure and pediatric emergency department visits in Georgia, US. They reported that, in general, a large proportion of missing satellite predictions tended to overestimate regional average PM2.5 exposure compared with ground measurements and led to lower health association estimates. To date, studies on the influence of missing satellite data on PM2.5 longer-term exposure assessment are very limited.
We developed a gap-filling method that provided full-coverage daily PM2.5 predictions at 1-km resolution using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product (Xiao et al., 2017). In this study, we analyzed the associations between birth outcomes (birth weight and preterm birth) and maternal PM2.5 exposure in Shanghai, China, during 2011–2014, and compared the estimated health effects using three exposure metrics: satellite predictions with missingness, gap-filled satellite predictions with complete coverage, and measurements from ground central monitors.
Section snippets
Data and outcome assessments
Shanghai is located on the east coast of China (Fig. A.1) and is one of the largest cities in the world with >24 million residents. Benefiting from the establishment of a special economic zone in 1993, Pudong New Area as well as Shanghai has become one the most economically developed regions in China as well as in East Asia. Birth registration data for live births between January 1st, 2011 and December 31st, 2014 were obtained from Pudong New Area Centers for Disease Control and Prevention
Results
The annual average PM2.5 concentrations from satellite predictions and central-site measurements in 2014 are shown in Fig. 1. PM2.5 concentrations decreased from west to east. Characteristics of the study population are shown in Table 1. The mean birth weight among term births was 3389 g, with a standard deviation of 403 g. The preterm birth rate in Shanghai during 2011–2014 was 4.41% and the term LBW rate was 0.95%. Previous studies reported higher preterm birth rate in China (4.8%) during
Discussion
In this study, we observed associations between maternal PM2.5 exposure during all exposure windows and adverse birth outcomes, including decreased birth weight, increased risk of term LBW, and increased risk of preterm birth in a highly polluted region. Exposure assessment approaches affected the estimated health effects, and satellite based exposures that did not account for missing data led to lower magnitude health effect estimates. Maternal age and parental education levels appeared to
Conclusions
We reported decreased birth weight as well as increased risk of preterm birth and term LBW in association with maternal PM2.5 exposure in Shanghai, China, from 2011 to 2014. The magnitude of associations between maternal PM2.5 exposure and birth outcomes was slightly higher than previously reported findings. Health association estimates were influenced by exposure assessment approaches, and when using satellite predictions for exposure assessment, researchers should account for missing data. We
Acknowledgments
This work was supported by the National Institutes of Health [grant number R01ES027892]; the Public Welfare Research Program of National Health and Family Planning Commission of China [grant number 201502003]; and the General Program of Health Bureau of Shanghai Pudong New Area [grant number PW2016A-6].
The authors have no conflict of interest to declare.
References (48)
- et al.
Examination of the community multiscale air quality (CMAQ) model performance over the North American and European domains
Atmos. Environ.
(2012) - et al.
An epidemiological survey on low birth weight infants in China and analysis of outcomes of full-term low birth weight infants
BMC Pregnancy and Childbirth
(2013) - et al.
Sources and contents of air pollution affecting term low birth weight in Los Angeles County, California, 2001–2008
Environ. Res.
(2014) - et al.
Association between ambient fine particulate matter and preterm birth or term low birth weight: an updated systematic review and meta-analysis
Environ. Pollut.
(2017) - et al.
Global, regional, and national causes of child mortality in 2000–13, with projections to inform post-2015 priorities: an updated systematic analysis
Lancet
(2015) - et al.
Ambient air pollution and low birthweight: a European cohort study (ESCAPE)
Lancet Respir. Med.
(2013) - et al.
Particulate air pollution, fetal growth and gestational length: the influence of residential mobility in pregnancy
Environ. Res.
(2016) - et al.
Ambient air pollution and preterm birth: a prospective birth cohort study in Wuhan, China
Int. J. Hyg. Environ. Health
(2016) - et al.
Maternal inflammation, growth retardation, and preterm birth: insights into adult cardiovascular disease
Life Sci.
(2011) - et al.
The associations between birth weight and exposure to fine particulate matter (PM 2.5) and its chemical constituents during pregnancy: a meta-analysis
Environ. Pollut.
(2016)
Associations between prenatal exposure to air pollution, small for gestational age, and term low birthweight in a state-wide birth cohort
Environ. Res.
Methodological issues in studies of air pollution and reproductive health
Environ. Res.
Full-coverage high-resolution daily PM 2.5 estimation using MAIAC AOD in the Yangtze River Delta of China
Remote Sens. Environ.
Current smoking in pregnant women in five geographical areas of China: a cross-sectional survey
Lancet
An analysis of the medical indications for preterm birth in an obstetrics and gynaecology teaching hospital in Shanghai, China
Midwifery
Maternal occupation during pregnancy, birth weight, and length of gestation: combined analysis of 13 European birth cohorts
Scand. J. Work Environ. Health
Infant mortality and low birth weight among black and white infants--United States, 1980–2000
MMWR Morb. Mortal. Wkly Rep.
Time-to-event analysis of fine particle air pollution and preterm birth: results from North Carolina, 2001–2005
Am. J. Epidemiol.
A spatial time-to-event approach for estimating associations between air pollution and preterm birth
J. R. Stat. Soc.: Ser. C: Appl. Stat.
Maternal exposure to particulate air pollution and term birth weight: a multi-country evaluation of effect and heterogeneity
Environ. Health Perspect.
Maternal smoking as a confounder in studies of air pollution and infant mortality
Epidemiology
Ambient air pollution and birth weight in full-term infants in Atlanta, 1994–2004
Environ. Health Perspect.
Effects of maternal age and age-specific preterm birth rates on overall preterm birth rates—United States, 2007 and 2014
MMWR Morb. Mortal. Wkly Rep.
Outdoor air pollution, preterm birth, and low birth weight: analysis of the world health organization global survey on maternal and perinatal health
Environ. Health Perspect.
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These authors contribute equally to this work.