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Validation of Sun Exposure and Vitamin D Intake Recall Questionnaires for Estimating Vitamin D Status
Author(s) -
Hall Laura Marie,
Stephensen Charles B,
Aronov Pavel A,
Hammock Bruce D,
Kimlin Michael G,
Slusser James R
Publication year - 2009
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.23.1_supplement.103.4
Subject(s) - sun exposure , vitamin d and neurology , medicine , vitamin , linear regression , food frequency questionnaire , regression analysis , physiology , zoology , environmental health , mathematics , statistics , biology , dermatology
Individual sun exposure and dietary intake both contribute to vitamin D status but simple, validated recall methods to assess these exposures are lacking. The objectives of our study were to validate both a sun exposure recall questionnaire, relative to a validated daily exposure log, and a vitamin D‐specific food frequency questionnaire (FFQ), relative to food records. We then assessed the ability of these methods, in conjunction with skin reflectance, to predict serum 25‐hydroxy vitamin D (25OHD) measured by LC‐MS. The study involved 72 healthy young adults each followed for 7‐8 wks during each season in Davis, CA. Spearman's correlation coefficients and validity coefficients were used to validate the methods. Multiple linear regression was used to predict serum 25OHD using sun exposure, skin reflectance and diet. The recall methods were highly correlated to the reference methods (sun: r = 0.83‐0.95, diet: r = 0.69‐0.77, p < 0.0001) and moderately correlated to serum 25OHD (sun: r = 0.40‐0.51, diet: r = 0.36‐0.37, p < 0.005). The recall measurements were all significant predictors of serum 25OHD (p < 0.05) and were not significantly different than the reference measurements in the regression model. These results show that the contribution of sun and diet to vitamin D status can be assessed using simple recall methods which may be used by nutritionists to predict individual needs for vitamin D intake. Grant Funding Source NIH Grant P60 MD00222 and USDA Project 5306‐51530‐006‐00D