Occupational Risk Factors and Hypertensive Disorders in Pregnancy: A Systematic Review.
Emanuela SpadarellaVeruscka LesoLuca FontanaAngela GiordanoIvo IavicoliPublished in: International journal of environmental research and public health (2021)
Hypertensive disorders in pregnancy (HDP), including gestational hypertension (GH) and preeclampsia (PE), characterize a major cause of maternal and prenatal morbidity and mortality. In this systematic review, we tested the hypothesis that occupational factors would impact the risk for HDP in pregnant workers. MEDLINE, Scopus, and Web of Knowledge databases were searched for studies published between database inception and 1 April 2021. All observational studies enrolling > 10 pregnant workers and published in English were included. Un-experimental, non-occupational human studies were excluded. Evidence was synthesized according to the risk for HDP development in employed women, eventually exposed to chemical, physical, biological and organizational risk factors. The evidence quality was assessed through the Newcastle-Ottawa scale. Out of 745 records identified, 27 were eligible. No definite conclusions could be extrapolated for the majority of the examined risk factors, while more homogenous data supported positive associations between job-strain and HDP risk. Limitations due to the lack of suitable characterizations of workplace exposure (i.e., doses, length, co-exposures) and possible interplay with personal issues should be deeply addressed. This may be helpful to better assess occupational risks for pregnant women and plan adequate measures of control to protect their health and that of their children.
Keyphrases
- pregnant women
- pregnancy outcomes
- risk factors
- systematic review
- blood pressure
- healthcare
- meta analyses
- mental health
- endothelial cells
- preterm birth
- big data
- type diabetes
- early onset
- randomized controlled trial
- birth weight
- induced pluripotent stem cells
- emergency department
- social support
- quality improvement
- air pollution
- climate change
- adipose tissue
- machine learning
- growth hormone
- health information
- insulin resistance