Association between cigarette smoking and the risk of dysmenorrhea: A meta-analysis of observational studies

• Published in: PloS one 2020-04, Vol.15 (4), p.e0231201-e0231201
• Main Authors: Qin, Lu-Lu, Hu, Zhao, Kaminga, Atipatsa Chiwanda, Luo, Bang-An, Xu, Hui-Lan, Feng, Xiang-Lin, Liu, Jia-He
• Format: Article
• Language: English
• Subjects: Abdomen; Adolescent; Adult; Asia - epidemiology; Biology and Life Sciences; Child; Cigarette smoking; Cigarette Smoking - adverse effects; Cigarettes; Confidence intervals; Cross-sectional studies; Dysmenorrhea - epidemiology; Epidemiology; Europe - epidemiology; Female; Finite element method; Gynecology; Heterogeneity; Humans; Medical ethics; Medicine; Medicine and Health Sciences; Menstruation; Meta-analysis; Middle Aged; North America - epidemiology; Observational studies; Observational Studies as Topic; Oceania - epidemiology; Odds Ratio; Pain; Physical Sciences; Public health; Research and Analysis Methods; Risk Factors; Science Policy; Sensitivity analysis; Smokers - statistics & numerical data; Smoking; Smoking - adverse effects; Smoking Cessation; Social Sciences; Statistical analysis; Studies; Subgroups; Tobacco Smoking - adverse effects; Womens health; Young Adult
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0231201

Emerging studies have found inconsistent results on the potential relationship between cigarette smoking and dysmenorrhea. Therefore, the aim of this study was to quantitatively synthesize the previous findings on the preceding relationship using meta-analysis. Previous studies on the association between cigarette smoking and dysmenorrhea, published not later than November 2019, were systematically searched, using MeSH heading and/or relevant terms, in the electronic databases of PubMed, Medline, Web of Science and EMBASE. The I2 statistic was used to assess heterogeneity, whose source was explored using subgroup analysis. A pooled effect size was obtained using random effects model, and sensitivity analysis was performed to assess the consistency of the pooled effect size. After a rigorous screening process, 24 studies involving 27,091 participants were included in this meta-analysis. The results indicated that smokers were 1.45 times more likely to develop dysmenorrhea than non-smokers (odds ratio (OR) = 1.45, 95% confidence interval (CI): 1.30-1.61). In addition, individuals classified as currently smoking were 1.50 times more likely to develop dysmenorrhea than those who were classified as never smoking (OR = 1.50, 95% CI: 1.33-1.70), whereas being a former smoker was 1.31 times more likely to develop dysmenorrhea than being a never smoker (OR = 1.31, 95% CI: 1.18-1.46). Sensitivity analysis showed that exclusion of any single study did not materially alter the overall combined effect. The evidence from this meta-analysis indicated a significant association between cigarette smoking (both current and former smoking) and dysmenorrhea. The adverse effects of smoking provide further support for prevention of dysmenorrhea and emphasize the need to target women.