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Background: Prenatal exposures to ambient air pollution and traffic have been associated with adverse birth outcomes, and may also lead to an increased risk of obesity. Obesity risk may be reflected in changes in body composition in infancy.
Objective: To estimate associations between prenatal ambient air pollution and traffic exposure, and infant weight and adiposity in a Colorado-based prospective cohort study.
Methods: Participants were 1125 mother-infant pairs with term births. Birth weight was recorded from medical records and body composition measures (fat mass, fat-free mass, and adiposity [percent fat mass]) were evaluated via air displacement plethysmography at birth (n = 951) and at ~5 months (n = 574). Maternal residential address was used to calculate distance to nearest roadway, traffic density, and ambient concentrations of fine particulate matter (PM) and ozone (O) via inverse-distance weighted interpolation of stationary monitoring data, averaged by trimester and throughout pregnancy. Adjusted linear regression models estimated associations between exposures and infant weight and body composition.
Results: Participants were urban residents and diverse in race/ethnicity and socioeconomic status. Average ambient air pollutant concentrations were generally low; the median, interquartile range (IQR), and range of third trimester concentrations were 7.3 μg/m (IQR: 1.3, range: 3.3-12.7) for PM and 46.3 ppb (IQR: 18.4, range: 21.7-63.2) for 8-h maximum O Overall there were few associations between traffic and air pollution exposures and infant outcomes. Third trimester O was associated with greater adiposity at follow-up (2.2% per IQR, 95% CI 0.1, 4.3), and with greater rates of change in fat mass (1.8 g/day, 95% CI 0.5, 3.2) and adiposity (2.1%/100 days, 95% CI 0.4, 3.7) from birth to follow-up.
Conclusions: We found limited evidence of an association between prenatal traffic and ambient air pollution exposure and infant body composition. Suggestive associations between prenatal ozone exposure and early postnatal changes in body composition merit further investigation.
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http://dx.doi.org/10.1016/j.envres.2020.109130 | DOI Listing |
Environ Res
September 2025
Department of Environmental Epidemiology, Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
While studies have examined associations between air pollution and subjective long COVID outcomes such as fatigue and symptoms, no studies have focused on objective lung health measures. This study aimed to assess the impact of air pollution, examined through different exposure methods (exposures assigned via geospatial model, versus residential and personal measurements) on pulmonary function and radiological abnormalities in long COVID patients. We recruited 95 patients who attended a hospital outpatient clinic 3-6 months post-infection, during which pulmonary function was assessed via spirometry (FEV1,FVC,FEV1/FVC ratio) and diffusion capacity for carbon monoxide (DLCO), along with a chest CT.
View Article and Find Full Text PDFMaturitas
September 2025
Department of Geriatrics, National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital Capital Medical University, Beijing, China; Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China. Electronic address:
Background: Falls are a major cause of disability. Whether exposure to ambient air pollution contributes to the occurrence of falls remains unclear.
Objective: To investigate the cross-sectional and longitudinal associations between ambient air pollution and the risk of falls in a community-dwelling adult population.
Paediatr Perinat Epidemiol
September 2025
Department of Medicine, Section of Epidemiology and Population Sciences, Baylor College of Medicine, Houston, Texas, USA.
Background: The few studies that have examined the impact of PM on reduced birthweight across different percentiles of the conditional birthweight distribution have produced equivocal findings, and only two assessed whether these associations varied by race/ethnicity or by racial/ethnic composition of the neighbourhood where mothers lived.
Objective: We evaluated racial/ethnic differences in the association between prenatal PM exposure and birthweight across the birthweight distribution in a retrospective cohort study comprising 102,986 full-term singleton births in Harris County, Texas (2019-2020).
Methods: Census tract-level daily PM concentrations were estimated using 'XGBoost-IDW Synthesis', and averaged exposures over pregnancy.
Environ Pollut
September 2025
School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China; State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
Ozone (O) is a primary pollutant affecting air quality in China, whose formation rate was non-linearly based on volatile organic compounds (VOCs) and nitrogen oxides (NOx). A comprehensive understanding of the key drivers governing O formation and its sensitivity to precursor variations presents a persistent research challenge, stemming from the complex interplay of underlying photochemistry, meteorology, and topography. To address this knowledge gap, we conducted synchronous measurements of O and its precursors at both an urban (JPU) and a mountain (LM) site in a typical city in eastern China, enabling concurrent evaluation of O formation sensitivity and diagnostic analysis of its underlying mechanisms.
View Article and Find Full Text PDFJ Environ Manage
September 2025
Department of Mechanical Engineering, University of Colorado Boulder, 1111 Engineering Drive, Boulder, CO, USA. Electronic address:
This study assesses the performance of the ADMS-Urban dispersion model in estimating 1-h mean nitrogen dioxide (NO) concentrations within the street canyons of Prague. While traditional air quality modeling that relies on sparse data from localized monitoring stations, this approach pioneers the integration of traffic, background, and rooftop sensor network, to archive a more granular validation of model outputs. The results demonstrate robust model performance, with FAC2 values ranging from 0.
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