Jie Hu , George D. Papandonatos , Tongzhang Zheng , Joseph M. Braun , Bin Zhang , Wenyu Liu , Chuansha Wu , Aifen Zhou , Simin Liu , Stephen L. Buka , Kunchong Shi , Wei Xia , Shunqing Xu , Yuanyuan Li
{"title":"产前金属混合物暴露与出生体重:两项前瞻性队列研究的两阶段分析","authors":"Jie Hu , George D. Papandonatos , Tongzhang Zheng , Joseph M. Braun , Bin Zhang , Wenyu Liu , Chuansha Wu , Aifen Zhou , Simin Liu , Stephen L. Buka , Kunchong Shi , Wei Xia , Shunqing Xu , Yuanyuan Li","doi":"10.1016/j.eehl.2022.09.001","DOIUrl":null,"url":null,"abstract":"<div><p>The understanding of the impact of prenatal exposure to metal mixtures on birth weight is limited. We aimed to identify metal mixture components associated with birth weight and to determine additional pairwise interactions between metals showing such associations. Concentrations of 18 metals were measured using inductively coupled plasma mass spectrometry in urine samples collected in the 3rd trimester from a prenatal cohort (discovery; n = 1849) and the Healthy Baby Cohort (replication; n = 7255) in Wuhan, China. In the discovery set, we used two penalized regression models, i.e., elastic net regression for main effects and a lasso for hierarchical interactions, to identify important mixture components associated with birth weight, which were then replicated. We observed that 8 of the 18 measured metals were retained by elastic net regression, with five metals (vanadium, manganese, iron, cesium, and barium) showing negative associations with Z-scores for birth weight and three metals (cobalt, zinc, and strontium) showing positive associations. In replication set, associations remained significant for vanadium (<em>β</em> = −0.035; 95% confidence interval [CI], −0.059 to −0.010), cobalt (<em>β</em> = 0.073; 95% CI, 0.049 to 0.097), and zinc (<em>β</em> = 0.040; 95% CI, 0.016 to 0.065) after Bonferroni correction. We additionally identified and replicated a single pairwise interaction between iron and copper exposure on birth weight (<em>P</em> < 0.001). Using a two-stage analysis, we identified and replicated individual metals and additional pairwise interactions-associated birth weight. The approach could be used in other studies estimating the effect of complex mixtures on human health.</p></div>","PeriodicalId":29813,"journal":{"name":"Eco-Environment & Health","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772985022000291/pdfft?md5=1ca38a9d565fad0cbe199fda436e9b30&pid=1-s2.0-S2772985022000291-main.pdf","citationCount":"7","resultStr":"{\"title\":\"Prenatal metal mixture exposure and birth weight: A two-stage analysis in two prospective cohort studies\",\"authors\":\"Jie Hu , George D. Papandonatos , Tongzhang Zheng , Joseph M. Braun , Bin Zhang , Wenyu Liu , Chuansha Wu , Aifen Zhou , Simin Liu , Stephen L. Buka , Kunchong Shi , Wei Xia , Shunqing Xu , Yuanyuan Li\",\"doi\":\"10.1016/j.eehl.2022.09.001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The understanding of the impact of prenatal exposure to metal mixtures on birth weight is limited. We aimed to identify metal mixture components associated with birth weight and to determine additional pairwise interactions between metals showing such associations. Concentrations of 18 metals were measured using inductively coupled plasma mass spectrometry in urine samples collected in the 3rd trimester from a prenatal cohort (discovery; n = 1849) and the Healthy Baby Cohort (replication; n = 7255) in Wuhan, China. In the discovery set, we used two penalized regression models, i.e., elastic net regression for main effects and a lasso for hierarchical interactions, to identify important mixture components associated with birth weight, which were then replicated. We observed that 8 of the 18 measured metals were retained by elastic net regression, with five metals (vanadium, manganese, iron, cesium, and barium) showing negative associations with Z-scores for birth weight and three metals (cobalt, zinc, and strontium) showing positive associations. In replication set, associations remained significant for vanadium (<em>β</em> = −0.035; 95% confidence interval [CI], −0.059 to −0.010), cobalt (<em>β</em> = 0.073; 95% CI, 0.049 to 0.097), and zinc (<em>β</em> = 0.040; 95% CI, 0.016 to 0.065) after Bonferroni correction. We additionally identified and replicated a single pairwise interaction between iron and copper exposure on birth weight (<em>P</em> < 0.001). Using a two-stage analysis, we identified and replicated individual metals and additional pairwise interactions-associated birth weight. 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Prenatal metal mixture exposure and birth weight: A two-stage analysis in two prospective cohort studies
The understanding of the impact of prenatal exposure to metal mixtures on birth weight is limited. We aimed to identify metal mixture components associated with birth weight and to determine additional pairwise interactions between metals showing such associations. Concentrations of 18 metals were measured using inductively coupled plasma mass spectrometry in urine samples collected in the 3rd trimester from a prenatal cohort (discovery; n = 1849) and the Healthy Baby Cohort (replication; n = 7255) in Wuhan, China. In the discovery set, we used two penalized regression models, i.e., elastic net regression for main effects and a lasso for hierarchical interactions, to identify important mixture components associated with birth weight, which were then replicated. We observed that 8 of the 18 measured metals were retained by elastic net regression, with five metals (vanadium, manganese, iron, cesium, and barium) showing negative associations with Z-scores for birth weight and three metals (cobalt, zinc, and strontium) showing positive associations. In replication set, associations remained significant for vanadium (β = −0.035; 95% confidence interval [CI], −0.059 to −0.010), cobalt (β = 0.073; 95% CI, 0.049 to 0.097), and zinc (β = 0.040; 95% CI, 0.016 to 0.065) after Bonferroni correction. We additionally identified and replicated a single pairwise interaction between iron and copper exposure on birth weight (P < 0.001). Using a two-stage analysis, we identified and replicated individual metals and additional pairwise interactions-associated birth weight. The approach could be used in other studies estimating the effect of complex mixtures on human health.
期刊介绍:
Eco-Environment & Health (EEH) is an international and multidisciplinary peer-reviewed journal designed for publications on the frontiers of the ecology, environment and health as well as their related disciplines. EEH focuses on the concept of “One Health” to promote green and sustainable development, dealing with the interactions among ecology, environment and health, and the underlying mechanisms and interventions. Our mission is to be one of the most important flagship journals in the field of environmental health.
Scopes
EEH covers a variety of research areas, including but not limited to ecology and biodiversity conservation, environmental behaviors and bioprocesses of emerging contaminants, human exposure and health effects, and evaluation, management and regulation of environmental risks. The key topics of EEH include:
1) Ecology and Biodiversity Conservation
Biodiversity
Ecological restoration
Ecological safety
Protected area
2) Environmental and Biological Fate of Emerging Contaminants
Environmental behaviors
Environmental processes
Environmental microbiology
3) Human Exposure and Health Effects
Environmental toxicology
Environmental epidemiology
Environmental health risk
Food safety
4) Evaluation, Management and Regulation of Environmental Risks
Chemical safety
Environmental policy
Health policy
Health economics
Environmental remediation