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.
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 Dinsufficiency 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 Dinsufficient 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.
Authors: T Merlijn; K M A Swart; P Lips; M W Heymans; E Sohl; N M Van Schoor; C J Netelenbos; P J M Elders Journal: Osteoporos Int Date: 2018-05-28 Impact factor: 4.507
Authors: Sofia Cardoso; Alejandro Santos; Rita S Guerra; Ana S Sousa; Patrícia Padrão; Pedro Moreira; Cláudia Afonso; Teresa F Amaral; Nuno Borges Journal: BMC Geriatr Date: 2017-10-31 Impact factor: 3.921
Authors: Mary Waterhouse; Dallas R English; Bruce K Armstrong; Catherine Baxter; Briony Duarte Romero; Peter R Ebeling; Gunter Hartel; Michael G Kimlin; Donald S A McLeod; Rachel L O'Connell; Jolieke C van der Pols; Alison J Venn; Penelope M Webb; David C Whiteman; Rachel E Neale Journal: Contemp Clin Trials Commun Date: 2019-02-20