The level of vitamin D using the LC-MS/MS method and related factors in healthy Korean postmenopausal women.

AIM: The main purposes of the study were (i) to evaluate serum vitamin D concentration in the forms of 25(OH)D2 , 25(OH)D3 and total 25(OH)D in Korean postmenopausal women using the LC-MS/MS method, which offers increased sensitivity and selectivity; (ii) to determine the relationship between the bone turnover marker, parathyroid hormone (PTH) and 25(OH)D3 , total 25(OH)D separately; and (iii) to determine the factors that may be associated with vitamin D deficiency using body composition analysis and laboratory blood tests. METHOD: A total of 200 postmenopausal women were recruited from November 2012 to March 2014. To control for seasonal ultraviolet exposure time differences in serum 25(OH)D, laboratory tests were performed only from November to March when vitamin D is not synthesized. Independent relationships between 25(OH)D3 , total 25(OH)D and other variables were assessed by multiple regression analysis. RESULTS: The mean serum 25(OH)D2 , 25(OH)D3 and total 25(OH)D levels were 0.51 (±0.44) ng/mL, 14.23 (±7.05) ng/mL and 14.69 (±7.13) ng/mL, respectively. Both 25(OH)D3 and total 25(OH)D were positively correlated with erythrocyte sedimentation rate (ESR), Apo A-I and C-terminal cross-linked telopeptides of type I collagen in Korean postmenopausal women. Both serum 25(OH)D3 and total 25(OH)D were negatively correlated with alkaline phosphatase , PTH and percent body fat. However, osteocalcin showed a negative correlation (r = -0.451; P = 0.041) with only 25(OH)D3 and not with total 25(OH)D (r = -0.417; P = 0.064). CONCLUSION: Both 25(OH)D3 and total 25(OH)D were negatively correlated with PTH, a bone formation marker (alkaline phosphatase) and percent body fat. Both 25(OH)D3 and total 25(OH)D were positively correlated with a bone resorption marker (C-terminal cross-linked telopeptides of type I collagen), ESR and Apo A-I after multiple regression analysis.

Development of models for predicting biological age (BA) with physical, biochemical, and hormonal parameters.

Individual differences are the hallmark of aging. Chronological age (CHA) is known that fails to provide an accurate indicator of the aging but biological age (BA) estimates the functional status of an individual in reference to his or her chronological peers on the basis of how well he or she functions in comparison with others of the same CHA. Therefore, we developed models for predicting BA that can be applicable in clinical practice settings. This was a community-based cross-sectional study. Subjects were recruited from the health promotion center in Korea from 2001 to 2005. Among these, data obtained from the 3575 participants (1302 men and 2273 women) was used for clinical evaluation and statistical analysis. For our test battery we selected 25 parameters among the routine tests. For males, the best models were developed using 15, 7, 5, and 4 of the 25 chosen parameters for total, physical, biochemical and hormonal characteristics, respectively (R(2)=0.62, 0.38, 0.33, and 0.36, respectively). Similar to males, for the females, 14, 6, 8, and 3 parameters were developed as the models (R(2)=0.66, 0.40, 0.42, and 0.37, respectively). Our BA prediction models may be used as supplementary tools adding knowledge in the evaluation of aging status.