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Safoura Ghasemi

Safoura Ghasemi

Academic rank: Assistant Professor
ORCID: https://orcid.org/0000-0003-4819-6447
Education: PhD.
ScopusId: 56397840600
Faculty: Sport Sciences
Address: Arak University
Phone:

Research

Title
Relationship of Weight and Body Mass Index with Femur and Lumbar Vertebrae Bone Mineral Density and Content in Premenopausal Women
Type
JournalPaper
Keywords
Relationship of Weight and Body Mass Index with Femur and Lumbar Vertebrae Bone Mineral Density and Content in Premenopausal Women
Year
2015
Journal Physical Treatments
DOI
Researchers Safoura Ghasemi ، Heydar Sadeghi ، Zahra Basiri ، Ahmad Tahammoli Roudsari

Abstract

Purpose: Given that weight and body mass index (BMI) are considered as modifiable factors in osteoporosis, the present study aimed to examine the relationship of weight and BMI with bone mineral density (BMD) and bone mineral content (BMC) at the femur and lumbar vertebrae in perimenopausal women. Methods: In this descriptive-correlational study, we measured the bone density of the femur and lumbar vertebrae (L1-L4) of 40 women in perimenopause stage (Mean±SD age: 42.85±1.86 years; Mean±SD weight: 69.55±10.97 kg; Mean±SD height: 159.42±6.01 cm; and Mean±SD BMI: 27.60±4.04 kg/m2) using a bone densitometry system. The study data were analyzed using descriptive statistics, analysis of variance (ANOVA), the Pearson correlation coefficient, and regression analysis, at 0.05 significance level. All analyses were performed using SPSS v. 21. Results: Women in the normal group were significantly different from women in the obese group with regard to BMD and BMC (P=0.001). Weight and BMI were positively correlated with BMD and BMC. Weight and BMI, together, could explain 42% and 37% of the variance of BMD and BMC at the lumbar vertebrae, respectively; and 70% and 63% of the variance of BMD and BMC at the total hip, respectively. Conclusion: The results of the present study support the predictive role of weight and BMI in BMD and BMC. Therefore, future studies are suggested to examine other effective factors with larger samples.