The role of body mass index, insulin, and adiponectin in the relation between fat distribution and bone mineral density.
Despite the positive association between body mass index (BMI) and bone mineral density (BMD) and content (BMC), the role of fat distribution in BMD/BMC remains unclear. We examined relationships between BMD/BMC and various measurements of fat distribution and studied the role of BMI, insulin, and adiponectin in these relations. Using a cross-sectional investigation of 2631 participants from the Erasmus Rucphen Family study, we studied associations between BMD (using dual-energy X-ray absorptiometry (DXA]) at the hip, lumbar spine, total body (BMD and BMC), and fat distribution by the waist-to-hip ratio (WHR), waist-to-thigh ratio (WTR), and DXA-based trunk-to-leg fat ratio and android-to-gynoid fat ratio. Analyses were stratified by gender and median age (48.0 years in women and 49.2 years in men) and were performed with and without adjustment for BMI, fasting insulin, and adiponectin. Using linear regression (adjusting for age, height, smoking, and use of alcohol), most relationships between fat distribution and BMD and BMC were positive, except for WTR. After BMI adjustment, most correlations were negative except for trunk-to-leg fat ratio in both genders. No consistent influence of age or menopausal status was found. Insulin and adiponectin levels did not explain either positive or negative associations. In conclusion, positive associations between android fat distribution and BMD/BMC are explained by higher BMI but not by higher insulin and/or lower adiponectin levels. Inverse associations after adjustment for BMI suggest that android fat deposition as measured by the WHR, WTR, and DXA-based android-to-gynoid fat ratio is not beneficial and possibly even deleterious for bone.
Zillikens
M Carola
MC
Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands. m.c.zillikens@erasmusmc.nl
Uitterlinden
André G
AG
van Leeuwen
Johannes P T M
JP
Berends
Anne L
AL
Henneman
Peter
P
van Dijk
Ko Willems
KW
Oostra
Ben A
BA
van Duijn
Cornelia M
CM
Pols
Huibert A P
HA
Rivadeneira
Fernando
F
D015502:Absorptiometry, Photon; D052242:Adiponectin / Q000032:analysis / Q000097:blood*; D000273:Adipose Tissue / Q000378:metabolism / Q000503:physiopathology; D000328:Adult; D000367:Age Factors; D000886:Anthropometry; D015415:Biomarkers / Q000032:analysis / Q000097:blood; D001823:Body Composition / Q000502:physiology; D015992:Body Mass Index; D001842:Bone and Bones / Q000378:metabolism / Q000503:physiopathology; D015331:Cohort Studies; D015897:Comorbidity; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D007328:Insulin / Q000032:analysis / Q000097:blood*; D008297:Male; D008593:Menopause / Q000502:physiology; D008875:Middle Aged; D009765:Obesity / Q000453:epidemiology / Q000378:metabolism* / Q000503:physiopathology; D056128:Obesity, Abdominal / Q000453:epidemiology / Q000378:metabolism / Q000503:physiopathology; D010024:Osteoporosis / Q000453:epidemiology / Q000378:metabolism* / Q000503:physiopathology; D012727:Sex Characteristics
D052242:Adiponectin; D015415:Biomarkers; D007328:Insulin