Development of an algorithm to predict serum vitamin D levels using a simple questionnaire based on sunlight exposure

Sun exposure is the main determinant of vitamin D production. The aim of this study was to develop an algorithm to assess individual vitamin D status, independently of serum 25(OHD) measurement, using a simple questionnaire, mostly relying upon sunlight exposure, which might help select subjects requiring serum 25(OHD) measurement. Six hundred and twenty adult subjects living in a mountain village in Southern Italy, located at 954 m above the sea level and at a latitude of 40°50′11″76N, were asked to fill the questionnaire in two different periods of the year: August 2010 and March 2011. Seven predictors were considered: month of investigation, age, sex, BMI, average daily sunlight exposure, beach holidays in the past 12 months, and frequency of going outdoors. The statistical model assumes four classes of serum 25(OHD) concentrations: ≤10, 10–19.9, 20–29.9, and ≥30 ng/ml. The algorithm was developed using a two-step procedure. In Step 1, the linear regression equation was defined in 385 randomly selected subjects. In Step 2, the predictive ability of the regression model was tested in the remaining 235 subjects. Seasonality, daily sunlight exposure and beach holidays in the past 12 months accounted for 27.9, 13.5, and 6.4 % of the explained variance in predicting vitamin D status, respectively. The algorithm performed extremely well: 212 of 235 (90.2 %) subjects were assigned to the correct vitamin D status. In conclusion, our pilot study demonstrates that an algorithm to estimate the vitamin D status can be developed using a simple questionnaire based on sunlight exposure.