Vitamin D and Mortality: an Individual Participant Data Meta-analysis of Standardized 25-hydroxyvitamin D

Vitamin D deficiency is a risk factor for mortality but existing data are limited by missing standardization of laboratory methods for 25-hydroxyvitamin D (25\[OH\]D). In a European consortium of eight cohort studies we use protocols of the Vitamin D Standardization Program (VDSP) to obtain standardized 25(OH)D data. Individual participant data (IPD) meta-analyses using a one step procedure will be performed to study associations of original and standardized 25(OH)D with all-cause, cardiovascular, and cancer mortality.

Vitamin D is involved in the regulation of calcium homeostasis and exerts beneficial effects on skeletal health. Serum levels of 25-hydroxyvitamin D (25\[OH\]D) are measured to assess vitamin D status, which is mainly determined by sunlight (ultraviolet-B) induced vitamin D production in the skin and, to a lesser extent, by dietary or supplemental vitamin D intake. A poor vitamin D status has emerged as a risk factor for various adverse health outcomes including mortality, but there exists controversy on the classification of vitamin D status and the shape of the association between 25(OH)D concentrations and mortality.

Existing knowledge on vitamin D status and mortality is limited by missing standardization of laboratory methods. Previous studies have shown that assay and laboratory differences have a significant impact on the reported 25(OH)D concentrations and thus on the association between 25(OH)D and health outcomes. Therefore, the Vitamin D Standardization Program (VDSP), a collaborative initiative led by the National Institutes of Health-Office of Dietary Supplements (NIH-ODS), has developed protocols for standardizing 25(OH)D data from current and previous surveys.

In this work, which is part of the EU-project 'Food-based solutions for eradication of vitamin D deficiency and health promotion throughout the life cycle' (ODIN), we aim to address the knowledge gap on the association between standardized 25(OH)D concentrations and mortality in a collaborative meta-analysis using individual participant data (IPD) from eight study cohorts across Europe. In detail, we will study associations of 25(OH)D with all-cause, cardiovascular, and cancer mortality. We use a one step approach for this meta-analysis, which has the advantage that IPD from all studies are modelled simultaneously whereas conventional two step approaches are based on aggregate data of each individual study. Considering that the majority of the individual studies of this meta-analysis have already reported on original 25(OH)D data we aim to compare original and standardized 25(OH)D concentrations regarding differences in reported concentrations and their associations with mortality.

Methods STUDY IDENTIFICATION \& SELECTION We established a collaboration to undertake this meta-analysis of IPD. Potential participants in a work-package of the EU Seventh Framework programme ODIN were invited to attend a one-day workshop in Amsterdam in November 2012 to discuss aims, implementation and development of the task. Invited European-based participants were identified on the basis of having recently published data from large prospective cohorts of vitamin D with mortality and cardiovascular outcomes. There were a number of prerequisites for inclusion of individual cohort studies in ODIN: It was necessary to have quality bio-banked samples for uniform sampling and analysis of selected samples, validated prospective data on clinical outcomes, willingness to collaborate and expertise in the field.

STUDIES \& PARTICIPANTS All individual cohorts are part of the ODIN Consortium. We will use IPD from eight independent prospective cohort studies from Norway, Germany, Denmark, the Netherlands and Iceland. Included studies are the 4th survey of the Tromsø study, the Ludwigshafen Risk and Cardiovascular Health Study (LURIC), the Age, Gene/Environment Susceptibility-Reykjavik Study (AGES), the New Hoorn Study (NHS), the Aarhus Mammography Cohort Study, the German Health Interview and Examination Survey for Adults (DEGS) and the old and young cohort of the Longitudinal Study on Ageing in Amsterdam (LASA). All cohort studies were conducted in accordance with the declaration of Helsinki and written informed consent was obtained from all study participants.

MEASUREMENT OF 25(OH)D According to the VDSP protocol we will conduct a sampling procedure to select a subset of 100-150 bio-banked serum samples from each individual cohort study for re-analysis of 25(OH)D by a standardized and certified liquid chromatography-tandem mass spectrometry (LC-tandem MS) method, which is traceable to the United States National Institute of Standards and Technology (NIST) higher order Reference Measurement Procedure. The re-analysed 25(OH)D values will be used to develop master regression equations for every present cohort study and to re-calibrate existing 25(OH)D measurements. The NHS has no previous 25(OH)D measurements and will be analysed in full.

GROUPING The IPD population will be divided into seven groups according to their 25(OH)D status at baseline. The allocation of individuals into one of the seven subgroups will be performed for original and standardized 25(OH)D measurements.

According to the Institute of Medicine (IOM) report 2011, thresholds for 25(OH)D groups will be assigned as severely vitamin D deficient (≤29•99 nmol/L), as two groups of patients at risk for inadequacy (from 30 to ≤ 39•99 nmol/L and 40 to ≤ 49•99 nmol/L), as vitamin D sufficient (from 50 to ≤ 75 nmol/L), as two groups of vitamin D levels which are not consistently associated with increased benefit (from 75 to ≤ 99•99 nmol/L; from 100 to ≤ 124•99 nmol/L) and as high vitamin D levels with reason for concern (≥ 125 nmol/L; to convert nmol/L to ng/mL divide by 2•496).

STATISTICAL ANALYSIS Differences between original and standardized 25(OH)D concentrations will be assessed by a paired-sample t-test. For comparisons of other baseline characteristics across baseline standardized vitamin D groups, we will use ANOVA for continuous and χ2 test for categorical data, as appropriate.

All-cause mortality is the primary outcome and is available in all participating cohort studies. Secondary outcomes are cardiovascular mortality and cancer mortality and are available in all cohort studies except of the NHS. All endpoints were sought in the greatest detail available from death certificates, municipal registries, medical records and local authorities.

All outcome analyses will be performed for original and standardized 25(OH)D values by means of IPD meta-analysis estimates and study-specific estimates. The analyses will be based on individuals with complete data on age, sex, body mass index (BMI), season of blood sampling, 25(OH)D levels, vital status at follow-up and follow-up-time. Follow-up time has to be \> 0 days. Participants with missing data will be excluded from the analysis and we will perform no data imputation.

Associations between 25(OH)D levels and all-cause mortality will be estimated using IPD in an one-step approach. In general, IPD meta-analyses following a one-step procedure were shown to be the more concise approach for binary outcomes compared to the frequently used two-step approach, were aggregated data is analysed. We will use a hierarchical, parametric survival model, which is more feasible compared to a Cox model when analysing binary outcomes. The single equation will be processed in a parametric, accelerated failure time (AFT) Weibull model, which appeared to fit best the underlying data against exponential, log-logistic and log-normal distributions. The model will be built using SAS PROC NLMIXED (SAS Institute Inc., 100 SAS Campus Drive, Cary, USA) and random intercept to account for random effects across cohort studies.

For the mortality analyses, 25(OH)D will be modelled using 1) a traditional categorical variable approach with groups according to the prior mentioned IOM classification, and 2) a restricted cubic splines approach. The cubic-splines approach was chosen to retain the continuous nature of 25(OH)D values and to calculate hazard ratios (HRs) with 95% confidence intervals (CI) at the mean value of each group. We chose the 25(OH)D group with the lowest mortality risk as the reference. Our outcome analyses will be cumulatively adjusted for risk factors of mortality and determinants of vitamin D status. In model 1 we adjust for age (in years), sex (male/female), and season of blood collection (Spring, Summer, Autumn, Winter). In model 2, our main statistical model, we additionally adjust for BMI (in kg/m²). In model 3, we additionally adjust for diabetes mellitus (yes/no) and arterial hypertension (yes/no), and in model 4 we add history of cancer (yes/no), history of cardiovascular disease (yes/no) and current smoking status as covariates (yes/no).

Additional adjustments have model two as reference model. Additional adjusting covariates are not available in every cohort study, so additional adjustments will only be performed in the studies that can provide those covariates.

First, supplemental intake of calcium (yes/no) will be added to model two. The first additional adjustment analysis wil be performed in all studies, but DEGS and LASA, young cohort, as no information on supplemental usage is available.

Second, supplemental intake of vitamin D (yes/no) will be added to model two in all studies but LASA, old and young cohort, and DEGS, as no information on supplemental usage of vitamin D is available in these studies.

Third, additional adjustment of model two for physical activity (three dummy variables for low, medium and high frequency of physical activity) will be processed in all studies but the Aarhus mammography cohort. For sensitivity analysis, we will also leave out DEGS, as the participants in DEGS have a high proportion of young, physically active individuals.

Fourth, adjustment for estimated glomerular filtration rate (eGFR; in mL/min/1•73m²) will be added to model two. The eGFR will be calculated from creatinine at baseline visit according to the four-variable Modification of Diet in Renal Disease (MDRD) Study equation and will be added to model two in all studies but NHS, as no creatinine measurements are available in NHS.

In a fifth analysis, adjustment for parathyroid hormone (in pmol/L) will be added to model two in all studies but NHS, Aarhus mammography cohort and LASA, young cohort.

In a sixth analysis, adjustment for C-reactive protein (in mg/L) will be added to model two in all studies but NHS, Aarhus mammography cohort and LASA, young cohort.

In a seventh analysis, adjustment for systolic blood pressure (in mm Hg) will be added to model two in all studies but the Aarhus mammography cohort, and DEGS.

In an eighth analysis, adjustment for low density lipoprotein cholesterol (in mmol/L) will be added to model two in all studies but the Aarhus mammography cohort, and DEGS.

In a ninth analysis, adjustment for glucose (in mmol/L) will be added to model two in all studies but the Tromsø Study, Aarhus mammography cohort, and DEGS.

All models on original 25(OH)D will be performed without NHS, as NHS had no original 25(OH)D measurements. For standardized 25(OH)D, we will compute all models 1) with data of NHS and 2) without data from NHS to provide comparable results between models of original and standardized 25(OH)D measurements.

Sensitivity Analyses Subgroup analyses will be performed to stratify for risk factors for vitamin D deficiency and mortality. In detail we stratified for sex (females/males), age groups (\<60 years; 60 to 69•9 years; 70+ years), BMI groups (\<25 kg/m²; 25\<30 kg/m²; ≥30 kg/m²), calcium supplementation (yes/no), vitamin D supplementation (yes/no), history of CVD (yes/no), and history of cancer (yes/no). A further sensitivity analysis will be restricted to individuals that died \> 1 year and \> 3 years after baseline examination and restricted to general population cohorts (i.e. all cohorts except LURIC).

Secondary outcomes To assess secondary outcomes of cardiovascular and cancer mortality, we utilize traditional Cox proportional hazards and the modified risks regression according to the method of Fine and Gray to account for competing risks. In brief, proportional hazards may not be satisfied in multi-centre settings, so baseline hazards are allowed to vary across single cohort studies.

Eligibility Criteria:
Inclusion Criteria:

Availability of quality bio-banked samples for uniform sampling and analysis of selected samples

Validated prospective data on clinical outcomes

Willingness to collaborate

Expertise in the field.

Exclusion Criteria:

Individuals with incomplete data on age, sex, body mass index (BMI), season of blood sampling, 25(OH)D levels, vital status at follow-up and follow-up-time.