Conceived and designed the experiments: EH MCB CP. Performed the experiments: DJB. Analyzed the data: DJB. Contributed reagents/materials/analysis tools: EH DJB MCB CP. Wrote the paper: EH DJB. Obtained funding: EH. Made figures: DJB.
The authors have declared that no competing interests exist.
Vitamin D deficiency has been suggested as a cardiovascular risk factor, but little is known about underlying mechanisms or associations with inflammatory or hemostatic markers. Our aim was to investigate the association between 25-hydroxyvitamin D [25(OH)D, a measure for vitamin D status] concentrations with pre-clinical variations in markers of inflammation and hemostasis.
Serum concentrations of 25(OH)D, C-reactive protein (CRP), fibrinogen, D-dimer, tissue plasminogen activator (tPA) antigen, and von Willebrand factor (vWF) were measured in a large population based study of British whites (aged 45y). Participants for the current investigation were restricted to individuals free of drug treated cardiovascular disease (n = 6538). Adjusted for sex and month, 25(OH)D was inversely associated with all outcomes (
Current vitamin D status was associated with tPA concentrations, and to a lesser degree with fibrinogen and D-dimer, suggesting that vitamin D status/intake may be important for maintaining antithrombotic homeostasis.
Vitamin D deficiency has been suggested to contribute to the high and rising worldwide prevalence of cardiovascular disease (CVD)
The strongest evidence for a relation between vitamin D metabolism and CVD risk has been obtained from clinical studies reporting a marked reduction in mortality following administration of vitamin D analogues to patients with end-stage renal disease
To date there is relatively little evidence from population-based studies on the associations of 25(OH)D with indicators of inflammation or hemostasis, and to what extent possible co-variation is affected by adiposity. Obesity is a key determinant for the circulating 25(OH)D concentrations
The geometric mean of 25(OH)D concentration was 52.77 nmol/l (95% CI 52.18, 53.36).
Values are geometric means (95% confidence intervals) standardized by sex.
25-hydroxyvitamin D, nmol/l | ||||
Number | Geometric Mean |
<25 nmol/l | >125 nmol/l | |
(%) | (95%CI) | % |
% |
|
Men | 3270 (50.0) | 53.6 (52.8, 54.5) | 6.2 (203) | 1.4 (46) |
Women | 3268 (50.0) | 51.9 (51.1, 52.8) | 8.4 (273) | 1.4 (45) |
0.003 | 0.0007 | 0.9 | ||
<25 | 2361 (36.1) | 55.1 (54.0, 56.2) | 7.5 (178) | 2.2 (52) |
25–30 | 2737 (41.9) | 54.2 (53.3, 55.1) | 5.8 (159) | 1.2 (32) |
>30 | 1440 (22.0) | 46.8 (45.7, 47.9) | 9.7 (139) | 0.5 (7) |
≤0.0001 | 0.04 | ≤0.0001 | ||
Quartile 1 | 1642 (25.1) | 57.4 (56.0, 58.7) | 6.8 (111) | 2.8 (46) |
Quartile 2 | 1639 (25.1) | 55.2 (54.0, 56.4) | 6.2 (102) | 1.8 (29) |
Quartile 3 | 1627 (24.9) | 52.6 (51.4, 53.7) | 6.1 (100) | 0.7 (11) |
Quartile 4 | 1618 (24.8) | 46.6 (45.6, 47.6) | 9.9 (160) | 0.2 (4) |
Unknown | 0.2 (12) | 44.8 (29.4, 68.3) | 25.0 (3) | 8.3 (1) |
≤0.0001 | 0.003 | ≤0.0001 | ||
No | 3206 (49.0) | 49.6 (48.8, 50.4) | 9.4 (300) | 1.2 (37) |
Yes | 3236 (49.5) | 56.3 (55.4, 57.2) | 5.0 (163) | 1.7 (54) |
Unknown | 96 (1.5) | 48.0 (43.2, 53.2) | 13.5 (13) | 0.0 (0) |
≤0.0001 | ≤0.0001 | 0.07 | ||
<1 hours/day | 745 (11.4) | 56.3 (54.5, 58.2) | 5.8 (43) | 2.3 (17) |
1–2 hours/day | 3455 (52.8) | 54.9 (54.1, 55.7) | 5.5 (191) | 1.6 (54) |
≥3 hours/day | 2056 (31.4) | 48.9 (47.9, 49.9) | 9.9 (204) | 0.9 (19) |
Unknown | 282 (4.3) | 47.7 (44.9, 50.5) | 13.5 (38) | 0.4 (1) |
≤0.0001 | ≤0.0001 | 0.01 | ||
None | 3039 (46.5) | 54.2 (53.3, 55.1) | 6.1 (185) | 1.3 (41) |
Ex-smoker | 1795 (27.5) | 54.8 (53.7, 55.9) | 5.1 (91) | 1.3 (23) |
1–19 per day | 762 (11.7) | 50.3 (48.5, 52.1) | 10.4 (79) | 1.7 (13) |
≥20 per day | 720 (11.0) | 45.5 (43.8, 47.2) | 14.4 (104) | 1.9 (14) |
Unknown | 222 (3.4) | 51.8 (48.8, 55.1) | 7.7 (17) | 0.0 (0) |
≤0.0001 | ≤0.0001 | 0.2 | ||
Non-drinker | 378 (5.8) | 46.1 (44.0, 48.4) | 11.4 (43) | 0.0 (0) |
Light <7 drinks/wk | 3155 (48.3) | 52.1 (51.3, 52.9) | 7.5 (237) | 1.0 (31) |
Moderate 7–13 drinks/wk | 1651 (25.3) | 55.6 (54.4, 56.9) | 5.6 (92) | 1.8 (30) |
Heavy 14–21 drinks/wk | 746 (11.4) | 55.9 (54.1, 57.8) | 4.8 (36) | 2.5 (19) |
Very heavy >21 drinks/wk | 590 (9.0) | 49.7 (47.7, 51.8) | 10.7 (63) | 1.7 (10) |
Unknown | 18 ( 0.3) | 41.5 (31.5, 54.6) | 27.8 (5) | 5.6 (1) |
0.01 | 0.9 | 0.0003 | ||
I & II | 2675 (40.9) | 53.3 (52.4, 54.2) | 6.7 (180) | 1.4 (38) |
III non-manual | 1363 (20.9) | 52.2 (50.9, 53.5) | 7.9 (107) | 1.1 (15) |
III manual | 1220 (18.7) | 54.5 (53.1, 56.0) | 6.1 (74) | 2.0 (25) |
IV & IV | 1013 (15.5) | 51.2 (49.8, 52.7) | 8.0 (81) | 1.0 (10) |
Other | 267 (4.1) | 48.8 (45.9, 51.8) | 12.7 (34) | 1.1 (3) |
0.007 | 0.02 | 0.8 |
*Values are
**Waist circumference quartiles: for men; 65.4–90.6, 90.7–96.7, 96.8–103.5, 103.6–151.2 cm; for women; 56.2–75.8, 75.9–82.6, 82.7–91.6, 91.7–138.3 cm.
†Classes I&II are managerial/professional, IV/V unskilled manual. “Other” includes cohort members who are institutionalised, retired, unemployed and other unclassifiable.
Adjusted for sex and month of measurement only, 25(OH)D was associated with all inflammatory and hemostatic outcomes (p≤0.01 for CRP, fibrinogen, D-dimer and tPA, p = 0.015 for vWF,
Model 1 (solid line): adjusted for month of measurement and sex. Model 2 (dashed, short): adjusted for lifestyle and social indicators (physical activity, time spent watching TV/using PC, smoking, alcohol consumption and birth and adult social class), month of measurement and sex. Model 3 (dashed, long): adjusted for adiposity (BMI and waist circumference), lifestyle/social indicators, month of measurement, and sex. Values are coefficients from linear regression (reference <25nmol/l), 95% confidence intervals presented for Model 3 by the shaded area.
Given the strong influence of season on 25(OH)D concentrations
Values are from the partial regression of the harmonic components; Model 1 (solid line) adjusted for respiratory infections, alcohol consumption, PC/TV time, physical activity and social class at birth and adulthood, and Model 2 (dashed line, shown with 95% confidence intervals) in addition to above adjusted for 25-hydroxyvitamin D. Tick marks denote average concentrations (SDS, predicted from random effects models) with 95% confidence intervals shown by error bars. Predicted means for CRP from linear models, no seasonal pattern observed (p>0.8). *p-values from the product of coefficient mediation test used to assess the 25(OH)D mediation effect on the seasonal patterns in the outcomes.
We observed a strong cross-sectional association between circulating 25(OH)D and tPA concentrations in participants free of clinical CVD, and a seasonal pattern for tPA that was largely mediated by 25(OH)D in this population. These findings, together with the weaker evidence observed for a relation of 25(OH)D with D-dimer and fibrinogen, suggest a role for current vitamin D status in determining thrombolytic profile before progression to CVD.
A specific methodological challenge for these cross-sectional analyses arose from the strong association of adiposity both with 25(OH)D concentrations and the inflammatory/hemostatic markers under study. In addition to the conventional approach of evaluating the direct association between 25(OH)D and the outcomes adjusting for potential confounders (most importantly, body mass index and waist circumference), we evaluated seasonal variation in the outcomes and the mediating influence of 25(OH)D on the observed patterns. These analyses supported a relation of 25(OH)D with tPA, and interestingly, also to lesser extent with D-dimer and fibrinogen. The seasonal pattern seen in vWF was not affected by 25(OH)D, nor did we observe evidence for a direct cross-sectional association, hence, this confirms the lack of evidence for any association between vitamin D status and circulating vWF concentrations in our study.
Risk of myocardial infarction and other thrombotic complications is typically higher during the winter months than during the summer
Increased concentrations of tPA and D-dimer are thought to serve as markers for aggravated fibrinolytic activity reflecting increased future burden of CVD
Hypovitaminosis D is believed to have wide-ranging influences on vascular physiology, which include both direct (e.g. influences on endothelial cells) and indirect pathways (endocrine, immunomodulatory)
Discussion regarding optimal status for 25(OH)D concentration is ongoing, and there is some debate about whether a threshold exists
The main strength of this study lies in the large sample of participants, which provided adequate power for detailed investigation of the associations between these inter-related health indicators. Moreover, as data collection covered the full seasonal range, we were able to obtain further support for the key findings from the independent evaluation of seasonal patterns in inflammatory and hemostatic markers. Given the exceptional information available from the 1958BC, we were able to adjust for multiple factors in our analyses thereby controlling for confounding introduced by demographic, lifestyle or social variations. Final models evaluating the independent effect of 25(OH)D on inflammatory and hemostatic outcomes were adjusted for quadratic terms in both BMI and waist circumference in order to control for adiposity as fully as possible. The full attenuation of the association between 25(OH)D with CRP and fibrinogen after adjustment for the available indicators suggests that these measures were sufficient for this purpose.
Comparison between the effect of adjustment for 25(OH)D concentrations in the observed seasonal patterns in the inflammatory/hemostatic factors, and the direct associations between 25(OH)D and these outcomes, demonstrates the limitations of cross-sectional analysis of data and the problem of possible over/under adjustment. Given the strong influence of obesity on 25(OH)D concentrations, the latter would be expected to be associated with any factor that is strongly related to obesity (given a tolerable degree of measurement error and sufficient sample size). This argues for the need to adjust for obesity fully to reduce the likelihood of a false positive association due to confounding. However, it could also be argued that adjustment for adiposity may lead to an underestimation of associations between 25(OH)D and inflammatory/hemostatic markers given that adiposity is a key determinant for 25(OH)D
Some further limitations need to be considered in relation to these findings. Given the observational design, we cannot prove causality or fully discount residual confounding by unmeasured variations. Residual confounding may also affect our seasonal mediation models; however, relevant confounders are likely to differ given that potential factors presumed important for the direct associations (such as adiposity) would not necessarily have seasonal patterns. Although 25(OH)D is the best indicator for vitamin D status in humans
Current vitamin D status was associated with circulating concentrations of tPA and D-dimer, which may suggest a role for vitamin D in maintaining antithrombotic homeostasis. Further studies, including randomised controlled trials, are needed to demonstrate the role of vitamin D metabolism in cardiovascular health, and whether vitamin D supplementation or improved vitamin D status could have beneficial effects.
Written consent for the use of information in medical studies was obtained from the cohort members. The 45y biomedical survey of the 1958BC was approved by the South-East Multi-Centre Research Ethics Committee (ref: 01/1/44).
Participants in this study are from the 1958 British birth cohort, which included all births in England, Scotland, and Wales during one week in March 1958 (
Venous blood samples were obtained without prior fasting and posted to collaborating laboratories. Fibrinogen was determined by the Clauss method and CRP assayed by nephelometry (Dade Behring) on citrated plasma samples after one thaw cycle. vWF antigen was measured by Decollates enzyme-linked immunosorbent assay (elisa) and tPA antigen by Biopool elisa. 25(OH)D was measured using automated application of the IDS OCTEIA elisa on the Dade-Behring BEP2000 analyser (sensitivity of 5.0 nmol/l, linearity ≤155 nmol/l, intra-assay variation CV 5.3–7.4% and inter-assay variation CV 7.7–8.5%)
Demographic, lifestyle and social factors have been described in detail previously
To describe the distribution of 25(OH)D concentration we used dichotomous indicators for levels below 25 nmol/l and above 125 nmol/l and a categorised factor into 25 nmol/l divisions with minimum <25 nmol/l and maximum ≥125 nmol/l tails. The natural logarithmic transformation was used to calculate geometric means to adjust the skewed distribution.
Inflammatory and hemostatic markers were transformed to gender-specific standard deviation scores (SDS) to compare variation across models. The SDS values were used as response variables in linear mixed effects regression models. Initial analyses included validation and graphical examination of data, statistical evaluation of linear and quadratic terms for 25(OH)D, adiposity measures (BMI and waist circumference), and single and joint effects of these measures on the inflammatory/hemostatic outcomes. Continuous measures were used in testing for interactions between the adiposity measures and 25(OH)D on the outcomes. For D-dimer three outlying observations were identified from graphical examination and model diagnostics (leverage and/or influence >2SD), and excluded from further analysis. We fitted linear regression models in three stages, starting with simple associations between 25(OH)D (categorized into 10 nmol/l groups, minimum <25 nmol/l and maximum ≥125 nmol/l tails) and the SDS inflammatory/hemostatic outcomes (model 1), next adjusting in addition for demographic, lifestyle and social factors (model 2), and finally adjusting for adiposity in addition to lifestyle and social factors (model 3). Models (1–3) included covariates gender and month of measurement and models with fibrinogen SDS as the outcome included laboratory assay batch. We also created an additional 25(OH)D category variable of <25, 25–74.9 and ≥75 nmol/l to summarize the effect size and repeated analyses for model 3. Missing information on the lifestyle factors (
Seasonal variations were modeled using sine and cosine functions
Without the hierarchical structure implied by the random effects terms we may have under-estimated the standard error on the intercept. The
To quantify the seasonal effect of 25(OH)D on the outcomes we used the concept of mediation analysis
We thank Dr Ian Gibb and Steve Turner (Royal Victoria Infirmary, Newcastle-upon-Tyne) for carrying out the 25(OH)D assays; and Professor Gordon Lowe and Dr Ann Rumley (Department of Medicine, Glasgow Royal Infirmary University NHS Trust, Glasgow) for processing measures of fibrinogen, C-reactive protein, tPA, vWF and D-dimer. Data were provided by the Centre for Longitudinal Studies, Institute of Education, University of London (original data producers).