Simple prediction model for vitamin D deficiency in women with osteoporosis or risk factors for osteoporosis in Thailand.

INTRODUCTION

In Thailand, the assessment of vitamin D status by measuring 25-hydroxyvitamin D[25(OH)D] levels in individuals at risk for osteoporosis is constrained by limited facilities and high costs. This study aimed to create a clinical model for predicting vitamin D deficiency in women with osteoporosis or risk factors for osteoporosis.

MATERIALS AND METHODS

This was a cross-sectional study of 490 women. All participants had 25(OH)D levels measured. A questionnaire was used to assess factors related to vitamin D status. Vitamin D deficiency was defined as 25(OH)D levels < 30 ng/mL. Logistic regression analyses were conducted to investigate predictors of vitamin D deficiency. In the model, odds ratios (ORs) were converted into simple scores. The optimal cutoff for women at a high risk of vitamin D deficiency was established. Internal validation was assessed using a Bootstrap.

RESULTS

Sixty percent had vitamin D deficiency. The final model for predicting vitamin D deficiency consisted of a body mass index ≥ 25 kg/m (OR:1.15), lack of exercise (OR:1.59), exercise 1-2 times/week (OR:1.40), sunlight exposure < 15 min/day (OR:1.70), no vitamin D supplementation (OR:8.76), and vitamin D supplementation of 1-20,000 IU/week (OR:2.31). The area under the curve was 0.747. At a cutoff of 6.6 in total risk score (range 4-13.6), the model predicted vitamin D deficiency with a sensitivity of 71.9 % and a specificity of 65.3 %. The internal validation by Bootstrap revealed a ROC of 0.737.

CONCLUSIONS

In women at risk of osteoporosis, a simple risk score can identify individuals with a high risk of vitamin D deficiency. These women could benefit from vitamin D supplementation without requiring 25(OH)D measurements.