Maternal Exposure to Metal Components of PM and Low Birth Weight in New Mexico, USA

Overview

Journal Environ Sci Pollut Res Int

Publisher Springer

Specialties Environmental Health
Toxicology

Date 2023 Aug 22

PMID 37608181

Authors

Yanhong Huang

Xi Gong

Lin Liu

Li Luo

Shuguang Leng

Yan Lin

Affiliations

Soon will be listed here.

Abstract

Infants with low birth weight (LBW) are more likely to have health problems than normal weight infants. In studies examining the associations between particulate matter (PM) exposures and LBW, there is a tendency to focus on PM as a whole. However, insufficient information is available regarding the effects of different components of PM on birth weight. This study identified the associations between maternal exposure to 10 metal components of PM and LBW in offspring based on small area (divided by population size) level data in New Mexico, USA, from 2012 to 2016. This study used a pruned feed-forward neural network (pruned-FNN) approach to estimate the annual average exposure index to each metal component in each small area. The linear regression model was employed to examine the association between maternal PM metal exposures and LBW rate in small areas, adjusting for the female percentage and race/ethnicity compositions, marriage status, and educational level in the population. An interquartile range increase in maternal exposure to mercury and chromium of PM increased LBW rate by 0.43% (95% confidence interval (CI): 0.18-0.68%) and 0.63% (95% CI: 0.15-1.12%), respectively. These findings suggest that maternal exposure to metal components of air pollutants may increase the risk of LBW in offspring. With no similar studies in New Mexico, this study also posed great importance because of a higher LBW rate in New Mexico than the national average. These findings provide critical information to inform further epidemiological, biological, and toxicological studies.

Citing Articles

Industrial air pollution and low birth weight in New Mexico, USA.

Gong X, Huang Y, Duong J, Leng S, Zhan F, Guo Y J Environ Manage. 2023; 348:119236.

PMID: 37857221 PMC: 10829484. DOI: 10.1016/j.jenvman.2023.119236.

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