The associations between exposure to trihalomethanes during pregnancy and adverse birth outcomes: A systematic review and meta-analysis

Chemosphere ◽  
2022 ◽  
pp. 133524
Author(s):  
Song-lin An ◽  
Shi-min Xiong ◽  
Xu-bo Shen ◽  
Yun-qiao Ni ◽  
Wei Chen ◽  
...  
Author(s):  
Sylvester Dodzi Nyadanu ◽  
Gizachew Assefa Tessema ◽  
Ben Mullins ◽  
Bernard Kumi-Boateng ◽  
Michelle Lee Bell ◽  
...  

Prenatal exposure to ambient air pollution and extreme temperatures are among the major risk factors of adverse birth outcomes and with potential long-term effects during the life course. Although low- and middle-income countries (LMICs) are most vulnerable, there is limited synthesis of evidence in such settings. This document describes a protocol for both an umbrella review (Systematic Review 1) and a focused systematic review and meta-analysis of studies from LMICs (Systematic Review 2). We will search from start date of each database to present, six major academic databases (PubMed, CINAHL, Scopus, MEDLINE/Ovid, EMBASE/Ovid and Web of Science Core Collection), systematic reviews repositories and references of eligible studies. Additional searches in grey literature will also be conducted. Eligibility criteria include studies of pregnant women exposed to ambient air pollutants and/or extreme temperatures during pregnancy with and without adverse birth outcomes. The umbrella review (Systematic Review 1) will include only previous systematic reviews while Systematic Review 2 will include quantitative observational studies in LMICs. Searches will be restricted to English language using comprehensive search terms to consecutively screen the titles, abstracts and full-texts to select eligible studies. Two independent authors will conduct the study screening and selection, risk of bias assessment and data extraction using JBI SUMARI web-based software. Narrative and semi-quantitative syntheses will be employed for the Systematic Review 1. For Systematic Review 2, we will perform meta-analysis with two alternative meta-analytical methods (quality effect and inverse variance heterogeneity) as well as the classic random effect model. If meta-analysis is infeasible, narrative synthesis will be presented. Confidence in cumulative evidence and the strength of the evidence will be assessed. This protocol is registered with PROSPERO (CRD42020200387).


2019 ◽  
Vol 215 ◽  
pp. 64-74.e6 ◽  
Author(s):  
Zhongzheng Niu ◽  
Karen Li ◽  
Chuanbo Xie ◽  
Xiaozhong Wen

Epidemiology ◽  
2009 ◽  
Vol 20 ◽  
pp. S67
Author(s):  
James Grellier ◽  
James Bennett ◽  
Evridiki Patelarou ◽  
Rachel Smith ◽  
Mireille Toledano ◽  
...  

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