Determinants of serum levels of vitamin D: a study of life-style, menopausal status, dietary intake, serum calcium, and PTH

Background: Low blood levels of vitamin D (25-hydroxy D3, 25OHD3) in women have been associated with an increased risk of several diseases. A large part of the population may have suboptimal 25OHD3 levels but high-risk groups are not well known. The aim of the present study was to identify determinants for serum levels of 25OHD3 in women, i.e. factors such as lifestyle, menopausal status, diet and selected biochemical variables. Methods: The study was based on women from the Malmo Diet and Cancer Study (MDCS), a prospective, population-based cohort study in Malmo, Sweden. In a previous case-control study on breast cancer, 25OHD3 concentrations had been measured in 727 women. In these, quartiles of serum 25OHD3 were compared with regard to age at baseline, BMI (Body Max Index), menopausal status, use of oral contraceptives or menopausal hormone therapy (MHT), life-style (e. g. smoking and alcohol consumption), socio-demographic factors, season, biochemical variables (i.e. calcium, PTH, albumin, creatinine, and phosphate), and dietary intake of vitamin D and calcium. In order to test differences in mean vitamin D concentrations between different categories of the studied factors, an ANOVA test was used followed by a t-test. The relation between different factors and 25OHD3 was further investigated using multiple linear regression analysis and a logistic regression analysis. Results: We found a positive association between serum levels of 25OHD3 and age, oral contraceptive use, moderate alcohol consumption, blood collection during summer/autumn, creatinine, phosphate, calcium, and a high intake of vitamin D. Low vitamin D levels were associated with obesity, being born outside Sweden and high PTH levels. Conclusions: The present population-based study found a positive association between serum levels of 25OHD3 and to several socio-demographic, life-style and biochemical factors. The study may have implications e. g. for dietary recommendations. However, the analysis is a cross-sectional and it is difficult to suggest Lifestyle changes as cause-effect relationships are difficult to assess.