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Bone mineral density in femoral neck is positively correlated to circulating insulin-like growth factor (IGF)-I and IGF-binding protein (IGFBP)-3 in Swedish men.

https://arctichealth.org/en/permalink/ahliterature190890
Source
Calcif Tissue Int. 2002 Jan;70(1):22-9
Publication Type
Article
Date
Jan-2002
Author
P. Gillberg
H. Olofsson
H. Mallmin
W F Blum
S. Ljunghall
A G Nilsson
Author Affiliation
Department of Medical Sciences, University Hospital, S-75185 Uppsala, Sweden.
Source
Calcif Tissue Int. 2002 Jan;70(1):22-9
Date
Jan-2002
Language
English
Publication Type
Article
Keywords
Absorptiometry, Photon
Adult
Aged
Aged, 80 and over
Aging - physiology
Bone Density
Femur Neck - metabolism - radiography
Gonadal Steroid Hormones - blood
Humans
Insulin-Like Growth Factor Binding Protein 3 - blood
Insulin-Like Growth Factor I - analysis
Lumbar Vertebrae - metabolism - radiography
Male
Middle Aged
Regression Analysis
Sweden
Abstract
Studies on the hormonal regulation of bone metabolism in men have indicated covariation between insulin-like growth factor-I (IGF-I) and sex hormones with bone mineral density (BMD). In this study the relationships between BMD in total body, lumbar spine, femoral neck, distal and ultradistal (UD) radius and circulating levels of IGFs, IGF binding proteins (IGFBPs), and sex steroids were investigated in 55 Swedish men between 22 and 85 (52 +/- 18, mean +/- SD) years of age. BMD in total body, distal and UD radius, and femoral neck was positively correlated with serum IGF-I (r = 0.31 to 0.49), IGF-II (r = 0.32 to 0.48), IGFBP-3 (r = 0.37 to 0.53), and free androgen index (FAI) (r = 0.32 to 0.40), and negatively with IGFBP-1 (r = -0.37 to -0.41) and IGFBP-2 (r = -0.29 to -0.41) levels. A positive correlation was observed between BMD in femoral neck and estradiol/SHBG ratio (r = 0.34, P = 0.01). Age correlated negatively with serum IGF-I, IGF-II, IGFBP-3, FAI, estradiol/SHBG ratio, and BMD in total body, distal and UD radius, and femoral neck, and positively with IGFBP-1, IGFBP-2, and SHBG levels. According to stepwise multiple regression analyses, a combination of weight, IGFBP-3, and testosterone accounted for 43% of the variation in BMD in femoral neck, 34% in ultradistal radius and 48% in total body (P
PubMed ID
11907704 View in PubMed
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Screening for osteopenia and osteoporosis: selection by body composition.

https://arctichealth.org/en/permalink/ahliterature213486
Source
Osteoporos Int. 1996;6(2):120-6
Publication Type
Article
Date
1996
Author
K. Michaëlsson
R. Bergström
H. Mallmin
L. Holmberg
A. Wolk
S. Ljunghall
Author Affiliation
Department of Orthopaedics, Central Hospital, Västerås, Sweden.
Source
Osteoporos Int. 1996;6(2):120-6
Date
1996
Language
English
Publication Type
Article
Keywords
Absorptiometry, Photon
Adult
Aged
Body Composition
Body mass index
Bone Density - physiology
Bone Diseases, Metabolic - diagnosis - etiology - radiography
Cross-Sectional Studies
Female
Humans
Mass Screening
Middle Aged
Osteoporosis - diagnosis - etiology - radiography
Predictive value of tests
Random Allocation
Regression Analysis
Retrospective Studies
Risk factors
Sweden
Abstract
There is a great need for simple means of identifying persons at low risk of developing osteoporosis, in order to exclude them from screening with bone mineral measurements, since this procedure is too expensive and time-consuming for general use in the unselected population. We have determined the relationships between body measure (weight, height, body mass index, lean tissue mass, fat mass, waist-to-hip ratio) and bone mineral density (BMD) in 175 women of ages 28-74 years in a cross-sectional study in a county in central Sweden. Dual-energy X-ray absorptiometry was performed at three sites: total body, L2-4 region of lumbar spine, and neck region of the proximal femur. Using multiple linear regression models, the relationship between the dependent variable, BMD, and each of the body measures was determined, with adjustment for confounding factors. Weight alone, in a multivariate model, explained 28%, 21% and 15% of the variance in BMD of total body, at the lumbar spine and at the femoral neck according to these models. The WHO definition of osteopenia was used to dichotomize BMD, which made it possible, in multivariate logistic regression models, to estimate the risk of osteopenia with different body measures categorized into tertiles. Weight of over 71 kg was associated with a very low risk of being osteopenic compared with women weighing less than 64 kg, with odds ratios (OR) of 0.01 (95% confidence interval (CI) 0.00-0.09), 0.06 (CI 0.02-0.22) and 0.13 (CI 0.04-0.42) for osteopenia of total body, lumbar spine and femoral neck, respectively. Furthermore a sensitivity/specificity analysis revealed that, in this population, a woman weighing over 70 kg is not likely to have osteoporosis. Test specifics of a weight under 70 kg for osteoporosis (BMD less than 2.5 SD compared with normal young women) of femoral neck among the postmenopausal women showed a sensitivity of 0.94, a specificity of 0.36, positive predictive value (PPV) of 0.21, and negative predictive value (NPV) of 0.97. Thus, exclusion of the 33% of women with the highest weight meant only that 3% of osteoporotic cases were missed. The corresponding figures for lumbar spine were sensitivity 0.89, specificity 0.38, PPV 0.33, and NPV 0.91. All women who were defined as being osteoporotic of total body weighed under 62 kg. When the intention was to identify those with osteopenia of total body among the postmenopausal women we attained a sensitivity of 0.92 and a NPV of 0.91 for a weight under 70 kg, whereas we found that weight could not be used as an exclusion criterion for osteopenia of femoral neck and lumbar spine. Our data thus indicate that weight could be used to exclude women from a screening program for postmenopausal osteoporosis.
PubMed ID
8704349 View in PubMed
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