Objectives: Vitamin D deficiency is highly prevalent and has been linked to increased morbidity and mortality. There has been an increase in testing for vitamin D with a concomitant increase in costs. While individual factors are significantly linked to vitamin D status, prior studies have not yielded a model predictive of vitamin D status or 25(OH)D levels. The purpose of this investigation was to determine if a prediction model of vitamin D could be developed using extensive demographic data and laboratory parameters. Methods: Patient data from 6 Veterans Administration Medical Centers were extracted from medical charts. Results: For the 14,920 available patients, several factors including triglyceride level, race, total cholesterol, body mass index, calcium level, and number of missed appointments were significantly linked to vitamin D status. However, these variables accounted for less than 15% of the variance in vitamin D levels. While the variables correctly classified vitamin D deficiency status for 71% of patients, only 33% of those who were actually deficient were correctly identified as deficient. Conclusion: Given the failure to find a sufficiently predictive model for vitamin D deficiency, we propose that there is no substitute for laboratory testing of 25(OH)D levels. A baseline vitamin D 3 daily replacement of 1000-2000 IU initially with further modification based on biannual testing appears to factor in the wide variation in dose response observed with vitamin D replacement and is especially important in high-risk groups such as ethnic minorities.

Aging increases the risk of both vitamin D deficiency and metabolic syndrome. Vitamin D deficiency and metabolic syndrome may be related, although there are mixed findings. Furthermore, literature suggests other factors such as physical fitness activity and smoking behavior are associated with Vitamin D deficiency and the development of metabolic syndrome. A number of studies have documented associations between Vitamin D levels and physical fitness activities, while other studies found correlations between Vitamin D levels, metabolic syndrome, and smoking behavior. However, no previous study has examined the links between physical fitness activity, smoking behavior, Vitamin D levels, and the risks for metabolic syndrome. The purpose of this study was to examine if smoking behavior and physical fitness activity moderated the relationship between Vitamin D deficiency and metabolic syndrome among older individuals. The research problem was addressed through the use of retrospective data collected from the National Health and Nutrition Examination Survey (NHANES) 2005-2006. This study utilized a quantitative, retrospective, cross-sectional design employing regression and correlational analysis to determine that Vitamin D deficiency (p = 0.02) predicts metabolic syndrome (n = 1570). However, neither physical activity (p = 0.99) nor smoking behavior (p = 0.23) moderated the relationship between Vitamin D deficiency and metabolic syndrome (n = 1570). The results of the study could give practitioners a better understanding and insights into the different risk factors to metabolic syndrome among older individuals, which can eventually enable primary and secondary prevention interventions.