Title: Relationship between metabolic syndrome and its components withbone densitometry in postmenopausal women
Abstract:Background: Prevention of osteoporosis and bone fracture and the relationship between metabolic
syndrome and bone density are controversial issues.
The aim of this study: The aim of this study was t...Background: Prevention of osteoporosis and bone fracture and the relationship between metabolic
syndrome and bone density are controversial issues.
The aim of this study: The aim of this study was to evaluate the association between metabolic syndrome
and its components with bone mineral density in post menopausal women referred for bone mineral
density (BMD) test.
Methods: A total of 143 postmenopausal women with at least one year of menopause experience
participated in this cross-sectional study. Demographic and anthropometric characteristics for all
participants were collected. Also, biochemical parameters including fasting blood sugar, Cholesterol
(HDL and LDL), triglyceride were measured. Association between the components of metabolic syndrome
and bone densitometry were analyzed by statistical methods.
Results: In this study, 72% of participants did not have metabolic syndrome. Among them, 43.4% and 28.7%
had osteoporosis and normal density, respectively. Of remaining participants with metabolic syndrome,
12.6% and 15.4% had osteoporosis and normal density, respectively. Among the metabolic syndrome
components, waist circumference, HDL cholesterol, and waist to hip ratio were significantly associated
with bone mass (P < 0.05). Osteoporotic women had lower waist circumference and waist to hip ratio and
higher HDL than women without osteoporosis. On the other hand, women with metabolic syndrome did
not have significant differences than women without metabolic syndrome in terms of lumbar and
femoral neck density (P > 0.05).
Conclusion: Results from this study showed that metabolic syndrome and its components did not induce
bone mass loss. The discrepancies of the studies in this area call for more large scale studies in population
so as to prevent women problems in this area.Read More
Publication Year: 2017
Publication Date: 2017-01-01
Language: en
Type: article
Access and Citation
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot