Prenatal exposure to particulate air pollution and gestational age at delivery in Massachusetts neonates 2001–2015

Qiu, Xinye; Fong, Kelvin C.; Shi, Liuhua; Papatheodorou, Stefania; Di, Qian; Just, Allan C.; Kosheleva, Anna; Messerlian, Carmen; Schwartz, Joel

doi:10.1097/ee9.0000000000000113

Cited by 14 publications

(14 citation statements)

References 58 publications

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“…These predicted

data have been used in previous work that have examined associations with birth outcomes in Massachusetts ( Fong et al. 2018 , 2019 ; Qiu et al. 2020 ).…”

Section: Methodsmentioning

confidence: 99%

Exposure to PM2.5 during Pregnancy and Fetal Growth in Eastern Massachusetts, USA

Leung

Weisskopf

Laden

et al. 2022

Environ Health Perspect

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Background: Prior studies have examined the association between fine particulate matter [PM in aerodynamic diameter ( )] and fetal growth with either limited spatial or temporal resolution. Objectives: In this study, we examined the association between exposure during pregnancy and fetal growth measures (ultrasound parameters and birth weight) in a pregnancy cohort using spatiotemporally resolved in Eastern Massachusetts, USA. Methods: We used ultrasound measures of biparietal diameter (BPD), head circumference, femur length, and abdominal circumference (AC), in addition to birth weight, from 9,446 pregnancies that were delivered at the Beth Israel Deaconess Medical Center from 2011–2016. We used linear mixed-effects models to examine the associations of in two exposure windows (the first 16 wk of pregnancy and the cumulative exposure up until the assessment of fetal growth) with anatomic scans (ultrasound ), growth scans (ultrasound ), and birth weight. All models were adjusted for sociodemographic characteristics, long-term trends, and temperature. Results: Higher exposure in the first 16 wk was associated with smaller fetal growth measures, where associations were particularly strong for BPD, AC, and birth weight. For example, a increase in was associated with a lower mean BPD -score of (95% CI: , ) before 24 wk, a lower mean AC -score of (95% CI: , ) after 24 wk, and a lower mean birth weight -score of (95% CI: , ). Analyses examining the associations with cumulative exposure up until the assessment of fetal growth produced attenuated associations. Conclusions: Higher gestational exposure to was associated with smaller fetal growth measures at levels below the current national standards. https://doi.org/10.1289/EHP9824

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“…These predicted

data have been used in previous work that have examined associations with birth outcomes in Massachusetts ( Fong et al. 2018 , 2019 ; Qiu et al. 2020 ).…”

Section: Methodsmentioning

confidence: 99%

Exposure to PM2.5 during Pregnancy and Fetal Growth in Eastern Massachusetts, USA

Leung

Weisskopf

Laden

et al. 2022

Environ Health Perspect

Self Cite

View full text Add to dashboard Cite

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“…In contrast, time-to-event analysis adjusts for seasonal conception patterns by design, because the Cox model with gestational age as time axis implies comparison of foetuses at the same gestational age (Auger et al, 2015). A nice feature of the quantile regression (Qiu et al, 2020) is the ease of clinical interpretability because the effect estimates are expressed in days of gestational age. Furthermore, both quantile regression and time-to-event analysis use the total population, increasing the sample size compared with the case-crossover design, and allow investigation of longer exposure windows.…”

Section: Discussionmentioning

confidence: 99%

“…The main feature of quantile regression is that it allows modelling the full gestational age as a continuous outcome, rather than using categorized measures of preterm birth based on predefined cut-off points of gestational age (Bind et al, 2016;Qiu et al, 2020). With this model, we estimated the effect of ambient temperature on specific quantiles of the gestational age distribution.…”

Section: Quantile Regressionmentioning

confidence: 99%

“…The main strength of this model is that it can evaluate associations at the tails of the gestational age distribution (a relevant feature in our study), still including the total population in the analysis, thus increasing the sample size and the statistical power. Also, it does not require normality of the outcome variable (Bind et al, 2016;Qiu et al, 2020). Finally, it allows for investigation of temporal windows of susceptibility during pregnancy because inclusion of longer-lags of exposure are not precluded in the statistical model.…”

Section: Quantile Regressionmentioning

confidence: 99%

“…Most studies relied on time-series designs (Liang et al, 2016;Schifano et al, 2013a;Vicedo-Cabrera et al, 2014), case-crossover designs (Auger et al, 2015;Basu et al, 2010) and time-to-event analyses (Kloog et al, 2015;Spolter et al, 2020;Wang et al, 2020). New approaches such as quantile regression have been employed in analogous studies of air pollution and preterm birth (Qiu et al, 2020). These various study designs offer slightly different approaches to the relevant research questions and bring different strengths and limitations.…”

Section: Introductionmentioning

confidence: 99%

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Associations between ambient temperature and risk of preterm birth in Sweden: a comparison of analytical approaches

Bont

Stafoggia

Nakstad

et al. 2022

ISEE Conference Abstracts

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Background: Evidence indicates that high temperatures are a risk factor for preterm birth. Increasing heat exposures due to climate change are therefore a concern for pregnant women. However, the large heterogeneity of study designs and statistical methods across previous studies complicate interpretation and comparisons. We investigated associations of short-term exposure to high ambient temperature with preterm birth in Sweden, applying three complementary analytical approaches. Methods: We included 560,615 singleton live births between 2014 and 2019, identified in the Swedish Pregnancy Register. We estimated weekly mean temperatures at 1-km 2 spatial resolution using a spatiotemporal machine learning methodology, and assigned them at the residential addresses of the study participants. The main outcomes of the study were gestational age in weeks and subcategories of preterm birth (<37 weeks): extremely preterm birth (<28 weeks), very preterm birth (from week 28 to <32), and moderately preterm birth (from week 32 to<37). Case-crossover, quantile regression and time-to-event analyses were applied to estimate the effects of short-term exposure to increased ambient temperature during the week before birth on preterm births. Furthermore, distributed lag nonlinear models (DLNM) were applied to identify susceptibility windows of exposures throughout pregnancy in relation to preterm birth. Results: A total of 1924 births were extremely preterm (0.4%), 2636 very preterm (0.5%), and 23,664 moderately preterm (4.2%). Consistent across all three analytical approaches (case-crossover, quantile regression and timeto-event analyses), higher ambient temperature (95th vs 50th percentile) demonstrated increased risk of extremely preterm birth, but associations did not reach statistical significance. In DLNM models, we observed no evidence to suggest an increased effect of high temperature on preterm birth risk. Even so, a suggested trend was observed in both the quantile regression and time-to-event analyses of a higher risk of extremely preterm birth with higher temperature during the last week before birth.

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Climate change, women’s health, and the role of obstetricians and gynecologists in leadership

Giudice

Llamas-Clark

DeNicola³

et al. 2021

Intl J Gynecology & Obste

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Climate change is one of the major global health threats to the world's population. It is brought on by global warming due in large part to increasing levels of greenhouse gases resulting from human activity, including burning fossil fuels (carbon dioxide), animal husbandry (methane from manure), industry emissions (ozone, nitrogen oxides, sulfur dioxide), vehicle/factory exhaust, and chlorofluorocarbon aerosols that trap extra heat in the earth's atmosphere. Resulting extremes of weather give rise to wildfires, air pollution, changes in ecology, and floods. These in turn result in displacement of populations, family disruption, violence, and major impacts on water quality and availability, food security, public health and economic infrastructures, and limited abilities for civil society to maintain citizen safety. Climate change also has direct impacts on human health and well-being. Particularly vulnerable populations are affected, including women, pregnant women, children, the disabled, and the elderly, who comprise the majority of the poor globally. Additionally, the effects of climate

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Prenatal exposure to particulate air pollution and gestational age at delivery in Massachusetts neonates 2001–2015

Abstract: Supplemental Digital Content is available in the text.

Cited by 14 publications

References 58 publications

Exposure to PM2.5 during Pregnancy and Fetal Growth in Eastern Massachusetts, USA

Exposure to PM2.5 during Pregnancy and Fetal Growth in Eastern Massachusetts, USA

Associations between ambient temperature and risk of preterm birth in Sweden: a comparison of analytical approaches

Climate change, women’s health, and the role of obstetricians and gynecologists in leadership

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