Predicting vitamin D deficiency in older Australian adults

B Tran; B K Armstrong; K McGeechan; P R Ebeling; D R English; Michael G Kimlin; R Lucas; J C Van Der Pols; A Venn; V Gebski; D C Whiteman; P M Webb; R E Neale

doi:10.1111/cen.12203

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Predicting vitamin D deficiency in older Australian adults

Journal article

Peer reviewed

Predicting vitamin D deficiency in older Australian adults

B Tran, B K Armstrong, K McGeechan, P R Ebeling, D R English, Michael G Kimlin, R Lucas, J C Van Der Pols, A Venn, V Gebski, …

Clinical Endocrinology, Vol.79(5), pp.631-640

2013

DOI: https://doi.org/10.1111/cen.12203

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Abstract

vitamin D deficiency

Objective 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. Measurements 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. Results 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%. Conclusion Our model could predict vitamin D deficiency with reasonable accuracy, but it needs to be validated in other populations before being implemented. © 2013 John Wiley & Sons Ltd.

Details

Title: Predicting vitamin D deficiency in older Australian adults
Authors: B Tran (Author) - Queensland Institute of Medical Research
B K Armstrong (Author) - University of Sydney
K McGeechan (Author) - University of Sydney
P R Ebeling (Author) - University of Melbourne
D R English (Author) - University of Melbourne
Michael G Kimlin (Author) - Queensland University of Technology
R Lucas (Author) - Australian National University
J C Van Der Pols (Author) - Queensland Institute of Medical Research
A Venn (Author) - Menzies Research Institute Tasmania
V Gebski (Author) - University of Sydney
D C Whiteman (Author) - Queensland Institute of Medical Research
P M Webb (Author) - Queensland Institute of Medical Research
R E Neale (Author) - Queensland Institute of Medical Research
Publication details: Clinical Endocrinology, Vol.79(5), pp.631-640
Publisher: Wiley-Blackwell Publishing Ltd.
Date published: 2013
DOI: 10.1111/cen.12203
ISSN: 0300-0664
Organisation Unit: University of the Sunshine Coast, Queensland; School of Health and Sport Sciences - Legacy
Language: English
Record Identifier: 99449330402621
Output Type: Journal article

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Collaboration types: Domestic collaboration
Web Of Science research areas: Endocrinology & Metabolism

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