Predicting vitamin D deficiency in older Australian adults

Tran B., Armstrong B.K., McGeechan K., Ebeling P.R., English D.R., Kimlin M.G., Lucas R., Van Der Pols J.C., Venn A., Gebski V., Whiteman D.C., Webb P.M. and Neale R.E. (2013) Predicting vitamin D deficiency in older Australian adults. Clinical Endocrinology, 79 5: 631-640. doi:10.1111/cen.12203

Author Tran B.
Armstrong B.K.
McGeechan K.
Ebeling P.R.
English D.R.
Kimlin M.G.
Lucas R.
Van Der Pols J.C.
Venn A.
Gebski V.
Whiteman D.C.
Webb P.M.
Neale R.E.
Title Predicting vitamin D deficiency in older Australian adults
Journal name Clinical Endocrinology   Check publisher's open access policy
ISSN 0300-0664
Publication date 2013-11-01
Year available 2013
Sub-type Article (original research)
DOI 10.1111/cen.12203
Volume 79
Issue 5
Start page 631
End page 640
Total pages 10
Place of publication West Sussex, United Kingdom
Publisher Wiley-Blackwell Publishing
Language eng
Subject 2712 Endocrinology, Diabetes and Metabolism
Formatted abstract
There has been a dramatic increase in vitamin D testing in Australia in recent years, prompting calls for targeted testing. We sought to develop a model to identify people most at risk of vitamin D deficiency.
Design and Participants
This is a cross-sectional study of 644 60- to 84-year-old participants, 95% of whom were Caucasian, who took part in a pilot randomized controlled trial of vitamin D supplementation.
Baseline 25(OH)D was measured using the Diasorin Liaison platform. Vitamin D insufficiency and deficiency were defined using 50 and 25 nmol/l as cut-points, respectively. A questionnaire was used to obtain information on demographic characteristics and lifestyle factors. We used multivariate logistic regression to predict low vitamin D and calculated the net benefit of using the model compared with 'test-all' and 'test-none' strategies.
The mean serum 25(OH)D was 42 (SD 14) nmol/1. Seventy-five per cent of participants were vitamin D insufficient and 10% deficient. Serum 25(OH)D was positively correlated with time outdoors, physical activity, vitamin D intake and ambient UVR, and inversely correlated with age, BMI and poor self-reported health status. These predictors explained approximately 21% of the variance in serum 25(OH)D. The area under the ROC curve predicting vitamin D deficiency was 0·82. Net benefit for the prediction model was higher than that for the 'test-all' strategy at all probability thresholds and higher than the 'test-none' strategy for probabilities up to 60%.
Our model could predict vitamin D deficiency with reasonable accuracy, but it needs to be validated in other populations before being implemented.
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Non HERDC
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