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Association between Metabolic Syndrome and Osteoporosis: A Systematic Review and Meta-Analysis
Weida Liu1, Chuangshi Wang1, Jun Hao1
1Medical Research & Biometrics Center, Fuwai Hospital, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 102300, China.
Background:
Previous studies have reached mixed conclusions regarding the association between metabolic syndrome (MS) and osteoporosis. We aimed to perform a meta-analysis based on published studies that explored the association between osteoporosis and MS.
Methods:
To identify related literature, a systematic search of PubMed, Cochrane Library, and EMBASE databases from inception to June 2020 was performed. Original studies that reported the risk estimates of osteoporosis morbidity for two or three categories of bone mineral density (BMD) in patients with MS were selected. Two independent investigators screened and selected the articles. Summary odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using random-effects models.
Results:
Of 2632 identified studies, nine cross-sectional studies with 14 datasets were eligible for our meta-analysis. In seven studies (10 datasets), the summarized ORs of osteoporosis for MS were 0.72 (95% CI: 0.52-0.99). Subgroup analyses by gender showed that significant inverse associations were observed only in men (OR = 0.72, 95% CI: 0.55-0.96) but not in women (OR = 0.70, 95% CI: 0.41-1.22). The definition of MS, the source of the study population, and the adjustment of covariates affected the estimates. In two studies (4 datasets), there was no evidence for an association between MS and decreased BMD.
Conclusions:
Our findings demonstrated that MS was significantly associated with a lower osteoporosis risk. There might be gender differences in the association between MS and osteoporosis. In addition, the association was likely to relate to the definition of MS, the source of the study population, and the adjustment of covariates.
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