Can a Model Predictive of Vitamin D Status Be Developed From Common Laboratory Tests and Demographic Parameters?

Peiris, Alan N.; Bailey, Beth A.; Guha, Bhuvana; Copeland, Rebecca; Manning, Todd

doi:10.1097/smj.0b013e3182297169

Cited by 12 publications

(21 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Finally, cross-sectional studies report that higher vitamin D levels are associated with better lipid profiles, though vitamin D therapy does not improve the lipid profile (20). Triglyceride levels explained 5% of the variance in serum 25(OH)D levels in the Veterans Affairs study (7). Measurement of triglycerides might improve the performance of the VIDSUN questionnaire.…”

Section: Discussionmentioning

confidence: 99%

“…A three-day food diary correlated weakly, but significantly (r=0.20, P=0.04), with serum 25(OH)D levels among 165 ambulatory postmenopausal women living in the San Francisco Bay area (6). A third chart review study (7) of 14,920 veterans reported that triglyceride levels, race, season of vitamin D measurement, total cholesterol, BMI and serum calcium together accounted for 12% of the variance in serum 25(OH)D levels, with triglycerides accounting for almost 5% of the variance. The study did not identify a model that could predict either vitamin D levels or vitamin D status (7) but notably did not assess participants’ intake of vitamin D from supplements, diet or sun exposure.…”

Section: Introductionmentioning

confidence: 99%

“…A third chart review study (7) of 14,920 veterans reported that triglyceride levels, race, season of vitamin D measurement, total cholesterol, BMI and serum calcium together accounted for 12% of the variance in serum 25(OH)D levels, with triglycerides accounting for almost 5% of the variance. The study did not identify a model that could predict either vitamin D levels or vitamin D status (7) but notably did not assess participants’ intake of vitamin D from supplements, diet or sun exposure. Among 3,055 postmenopausal women participating in the Women's Health Initiative Study (8), 21% of the variance in serum 25(OH)D levels was explained by vitamin D intake from food and supplements, waist circumference, exercise habits, race and latitude of residence.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Can a questionnaire predict vitamin D status in postmenopausal women?

Nabak¹,

Johnson

Keuler

et al. 2013

Public Health Nutr.

View full text Add to dashboard Cite

Objective Our objective was to determine whether a questionnaire can identify subjects with vitamin D insufficiency (VDI). Design Subjects completed the vitamin D and sun (VIDSUN) questionnaire and we measured their serum 25(OH)D levels. We assessed the sensitivity and specificity of the questionnaire to identify VDI (25(OH)D level <50 nmol/L). Setting Clinical Research Unit, University of Wisconsin-Madison Subjects Postmenopausal women Results We recruited 609 postmenopausal women with a mean ± SD age of 61 ± 6 years, of whom 113 (19%) had VDI. Subjects with VDI were more likely to be Black (17% vs. 2%, p<0.001), heavier (BMI 33±7 kg/m2 vs. 29±7 kg/m2, p<0.001) and less likely to tan in the past year (49% vs. 72%, p<0.001), use sunscreen (57% vs. 72%, p<0.001) or report sun exposure in the last three months. They consumed less vitamin D from supplements (86±210 vs. 188±344 IU/day, p=0.003). In logistic regression models, Black race, BMI, suntan within one year, sun exposure in the past three months, sunscreen use and supplemental vitamin D intake were the most useful questions to identify VDI. From these six items, a composite score ≤2.25 demonstrated ≥89% sensitivity but ≤35% specificity for VDI. Conclusion The VIDSUN questionnaire provides an initial tool to identify postmenopausal women at high or low risk of VDI. Existing studies suggest that inclusion of physical activity and triglyceride levels might improve the performance of the VIDSUN questionnaire.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Can a questionnaire predict vitamin D status in postmenopausal women?

Nabak¹,

Johnson

Keuler

et al. 2013

Public Health Nutr.

View full text Add to dashboard Cite

show abstract

“…concluded that predicted 25(OH)D scores do not adequately reflect serum 25(OH)D concentrations, and Peiris et al [13]. argued that vitamin D status cannot be reliably predicted and that common laboratory tests are required, especially for high-risk groups.…”

Section: Discussionmentioning

confidence: 99%

“…Past studies have used multiple linear regression (MLR) modelling to develop these predictive models. However, the final models typically explain only a small proportion of the total variability in 25(OH)D concentration, that is, the coefficient of determination (R 2 ) values from such predictive models have ranged from 0.13 to 0.42[8], [9], [10], [11], [12], [13]. In some publications, predicted and actual 25(OH)D levels have been compared in a validation sample, with Spearman(9,10) or Pearson(12) correlation coefficients ranging from 0.23 to 0.51.…”

Section: Introductionmentioning

confidence: 99%

A Novel Approach for Prediction of Vitamin D Status Using Support Vector Regression

2013

View full text Add to dashboard Cite

BackgroundEpidemiological evidence suggests that vitamin D deficiency is linked to various chronic diseases. However direct measurement of serum 25-hydroxyvitamin D (25(OH)D) concentration, the accepted biomarker of vitamin D status, may not be feasible in large epidemiological studies. An alternative approach is to estimate vitamin D status using a predictive model based on parameters derived from questionnaire data. In previous studies, models developed using Multiple Linear Regression (MLR) have explained a limited proportion of the variance and predicted values have correlated only modestly with measured values. Here, a new modelling approach, nonlinear radial basis function support vector regression (RBF SVR), was used in prediction of serum 25(OH)D concentration. Predicted scores were compared with those from a MLR model.MethodsDeterminants of serum 25(OH)D in Caucasian adults (n = 494) that had been previously identified were modelled using MLR and RBF SVR to develop a 25(OH)D prediction score and then validated in an independent dataset. The correlation between actual and predicted serum 25(OH)D concentrations was analysed with a Pearson correlation coefficient.ResultsBetter correlation was observed between predicted scores and measured 25(OH)D concentrations using the RBF SVR model in comparison with MLR (Pearson correlation coefficient: 0.74 for RBF SVR; 0.51 for MLR). The RBF SVR model was more accurately able to identify individuals with lower 25(OH)D levels (<75 nmol/L).ConclusionUsing identical determinants, the RBF SVR model provided improved prediction of serum 25(OH)D concentrations and vitamin D deficiency compared with a MLR model, in this dataset.

show abstract