Objective: Age at natural menopause (ANM) is usually defined as the age at the last menstrual bleeding followed by the absence of menses for 12 consecutive months. Although many studies have suggested an association between smoking and early age at natural menopause, evidence remains conflicting because some studies reported inconsistent or contrasting results. To resolve this ambiguity and to quantitatively evaluate the effect of smoking on ANM, we conducted a meta-analysis of the available data about smoking and ANM.
Methods: After extensive searching of public literature databases, a total of 11 studies were selected for this meta-analysis. Among them, the phenotype of the participants in five studies (dichotomous studies) was classified as early or late ANM, and odds ratio (OR) was used to evaluate the effect of smoking on early ANM. For the other six studies (continuous studies), mean and SD were provided for smoking and nonsmoking samples, and weighted mean difference (WMD) was used as the effect size.
Results: We found that smoking was significantly associated with early ANM in both dichotomous and continuous studies. The pooled effect was OR = 0.74 (95% CI, 0.60-0.91, P < 0.01) in the dichotomous studies. For the continuous studies, the pooled effect estimated by WMD was −1.12 (95% CI, −1.80 to −0.44, P = 0.04). After adjustment of the original data for heterogeneity, the pooled results changed only a little: OR = 0.67 (95% CI, 0.61-0.73, P < 0.01) for dichotomous studies and WMD = −0.90 (95% CI, −1.58 to −0.21, P = 0.01) for the continuous studies.
Conclusions: The results of our study suggest that smoking is a significant independent factor for early ANM.
The results of this study report the effect size of smoking on age at natural menopause. Smoking is suggested as a significant independent factor for early age at natural menopause.
From the 1Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, China; 2Department of Epidemiology and Biostatistics, School of Public Health, Central South University, Changsha, China; 3Department of Biostatistics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA; and 4School of Biological Sciences, University of Hong Kong, Hong Kong SAR.
Received February 28, 2011; revised and accepted May 18, 2011.
Funding/support: The study was supported by the Natural Science Foundation of China (NSFC; 30900810, 30771222, 31071097, 30600364), the NSFC-Canadian Institutes of Health Research (CIHR) Joint Health Research Initiative Proposal (30811120436), and the University of Hong Kong startup fund (to Volodymyr Dvornyk).
Financial disclosure/conflicts of interest: None reported.
Address correspondence to: Volodymyr Dvornyk, PhD, School of Biological Sciences, University of Hong Kong, Pokfulam Rd., Hong Kong SAR. E-mail: firstname.lastname@example.org