Cosinor modelling of seasonal variation in 25-hydroxyvitamin D concentrations in cardiovascular patients in Norway
European Journal of Clinical Nutrition advance online publication 25 November 2015; doi: 10.1038/ejcn.2015.200
E Degerud1, R Hoff2, O Nygård3,4, E Strand3, D W Nilsen3,5, J E Nordrehaug3,4, Ø Midttun6, P M Ueland3,7, S de Vogel8 and J Dierkes1
1Department of Clinical Medicine, University of Bergen, Bergen, Norway
2The Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
3Department of Clinical Science, University of Bergen, Bergen, Norway
4Department of Heart Disease, Haukeland University Hospital, Bergen, Norway
5Department of Cardiology, Stavanger University Hospital, Stavanger, Norway
6Bevital AS, Bergen, Norway
7Laboratory of Clinical Biochemistry, Haukeland University Hospital, Bergen, Norway
8Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
Correspondence: E Degerud, Department of Clinical Medicine, University of Bergen, PO Box 7804, Bergen 5020, Norway. E-mail: eirikdegerud at gmail.com
Background/objectives: Seasonal variation may reduce the validity of 25-hydroxyvitamin D (25OHD) as a biomarker of vitamin D status. Here we aimed to identify potential determinants of seasonal variation in 25OHD concentrations and to evaluate cosinor modelling as a method to adjust single 25OHD measurements for seasonal variation.
Subjects/methods: In Caucasian cardiovascular patients (1999–2004), we measured 25OHD by liquid chromatography tandem mass spectrometry in 4116 baseline and 528 follow-up samples. To baseline values, we fitted a cosinor model for monthly concentrations of 25OHD. Using the model, we estimated each patient’s adjusted annual 25OHD value. Further, we studied how covariates affected the annual mean 25OHD concentration and seasonal variation of the study cohort. To evaluate the model, we predicted follow-up measurements with and without covariates and compared accuracy with carrying forward baseline values and linear regression adjusting for season, common approaches in research and clinical practice, respectively.
Results: The annual mean (59.6 nmol/l) was associated with participants’ age, gender, smoking status, body mass, physical activity level, diabetes diagnosis, vitamin D supplement use and study site (adjusted models, P<0.05). Seasonal 25OHD variation was 15.8 nmol/l, and older age (>62 years) was associated with less variation (adjusted model, P=0.025). Prediction of follow-up measurements was more accurate with the cosinor model compared with the other approaches (P<0.05). Adding covariates to cosinor models did not improve prediction (P>0.05).
Conclusions: We find cosinor models suitable and flexible for analysing and adjusting for seasonal variation in 25OHD concentrations, which is influenced by age.
"Cosinor analysis uses the least squares method to fit a sine wave to a time series"
Reasons to be careful about "adjusting Vitamin D levels for season" include:
- Less seasonal variation if dark skin
- Less seasonal variation if elderly
- Less seasonal variation if female
- Less seasonal variation if Crohn's
- More seasonal variation if smoke, . . .
- Vitamin D in elderly Irish with 800 IU did not vary with season – Nov 2010
- Black infants had far lower vitamin D levels which did not vary with season – Jan 2013
- Some people need more vitamin D to get the same response – perhaps due to genes – Nov 2014
- Crohn’s Disease – strange things such as no change of vitamin D levels with season – Dec 2014
- Not all Vitamin D levels follow the season – Asthma, Rhinitis, … – March 2019
- How you might double your response to vitamin D
- Vitamin D Deficiency varies widely with season in young women, but not in old - April 2018