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Unable to make a model to predict vitamin D deficiency – Sept 2011

Can a model predictive of vitamin d status be developed from common laboratory tests and demographic parameters?

South Med J. 2011 Sep;104(9):636-9.
Peiris AN alan.peiris at va.gov , Bailey BA, Guha BN, Copeland R, Manning T.
From the Departments of Internal Medicine and Family Medicine, East Tennessee State University; and Mountain Home VAMC, Johnson City, TN.

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.

PMID: 21886082


VitaminDwWiki notes that they did seem to consider such important factors as:

  • age,
  • pregnancy
  • amount of time outdoors – and clothing
  • latitude
  • recent trauma or surgery
  • gut problems
  • kidney failure
  • lack of co-factors such as Magnesium
  • smoking
  • statins and other drugs

many of the above factors are not 'demographic'

See also VitaminDWiki

Possible Vitamin D Interactions

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