Predicting vitamin D deficiency in older Australian adults

Bich Tran, Bruce K. Armstrong, Kevin McGeechan, Peter R. Ebeling, Dallas R. English, Michael G. Kimlin, Robyn Lucas, Jolieke C. Van Der Pols, Alison Venn, Val Gebski, David C. Whiteman, Penelope M. Webb, Rachel E. Neale*

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

39 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)631-640
Number of pages10
JournalClinical Endocrinology
Volume79
Issue number5
DOIs
Publication statusPublished - Nov 2013
Externally publishedYes

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