Abstract
Vitamin D deficiency is highly prevalent in the U.S. population and is associated with numerous diseases, including those characterized by inflammatory processes. We aimed to investigate the link between vitamin D status and anaemia, hypothesizing that lower vitamin D status would be associated with increased odds of anaemia, particularly anaemia with inflammation. A secondary aim was to examine the effects of race in the association between vitamin D status and anaemia. We conducted a cross-sectional analysis in a cohort of generally healthy adults in Atlanta, GA (N=638). Logistic regression was used to evaluate the association between vitamin D status and anaemia. Serum 25-hydroxyvitamin D (25(OH)D) < 50 nmol/l (compared to 25(OH)D ≥ 50 nmol/l) was associated with anaemia in bivariate analysis (OR 2.64; 95% CI 1.43, 4.86). There was significant effect modification by race (P=0.003), such that blacks with 25(OH)D < 50 nmol/l had increased odds of anaemia (OR 6.42; 95% CI 1.88, 21.99), versus blacks with 25(OH)D ≥ 50 nmol/l, controlling for potential confounders; this association was not apparent in whites. When categorized by subtype of anaemia, blacks with 25(OH)D < 50 nmol/l had significantly increased odds of anaemia with inflammation compared to blacks with serum 25(OH)D ≥ 50 nmol/l (OR 8.42; 95% CI 1.96, 36.23); there was no association with anaemia without inflammation. In conclusion, serum 25(OH)D < 50 nmol/l was significantly associated with anaemia, particularly anaemia with inflammation, among blacks in a generally healthy adult U.S. cohort.
Keywords: Vitamin D, anaemia, inflammation, haemoglobin, hepcidin, African American
Introduction
Vitamin D deficiency has been well described in the U.S. population. Results from the National Health and Nutrition Examination Survey (NHANES) 2001-2006 suggest that vitamin D deficiency is highly prevalent in the U.S. population with approximately 32% of adults exhibiting vitamin D deficiency (defined as serum 25-hydroxyvitamin D (25(OH)D) concentrations < 50 nmol/l) and approximately 76% exhibiting vitamin D insufficiency (defined as serum 25(OH)D concentrations < 75 nmol/l). The prevalence is increased in blacks compared to other race and ethnic groups, where the prevalence of vitamin D deficiency and insufficiency have been reported to be 73% and 97%, respectively (1). The high prevalence of vitamin D deficiency may have important implications for extra-skeletal health as vitamin D deficiency is associated with a number of disease processes including heart disease, cancer, and infections (2-4). Recently, vitamin D deficiency has also been found to be associated with anaemia (5, 6).
Anaemia is characterized by a decrease in concentration of red blood cells or haemoglobin, resulting in impaired oxygen transport throughout the body. Furthermore, it is associated with a number of chronic conditions including kidney disease and cardiovascular disease (7, 8). The association between vitamin D status and anaemia has been shown in various populations including children, the elderly, chronic kidney disease patients, and those with heart failure (5, 9-11). However, the relationship between anaemia and vitamin D status in the generally healthy adult U.S. population has not been well described.
Previous studies have revealed that the strongest association between vitamin D status and anaemia may be with anaemia of inflammation (5). The mechanism underlying this relationship involves the antimicrobial peptide, hepcidin, a hormone involved in the regulation of iron recycling in the body that is induced by pro-inflammatory cytokines including interleukin-6 (IL-6) (12-14). Under chronic inflammatory conditions, iron can become sequestered within cells of the reticuloendothelial system and unavailable for erythropoiesis, which may ultimately lead to anaemia (15, 16). Recently, vitamin D has been reported to lower inflammatory cytokines implicated in the pathophysiology of anaemia of inflammation (17), and suppress expression of hepcidin mRNA (18). Thus, vitamin D may reduce the risk of anaemia through its anti-inflammatory effects.
The aim of the current paper is to examine the association between vitamin D status and anaemia in a generally healthy adult population. Based on the putative mechanism that vitamin D lowers pro-inflammatory cytokines, we hypothesized that lower vitamin D status would be associated with increased odds of anaemia, particularly anaemia with inflammation. Additionally, given that the prevalence of vitamin D deficiency is higher in blacks compared to whites, and lower haemoglobin concentrations have been reported in blacks compared to whites (19, 20), we hypothesized that there would be significant effect modification by race in the association between vitamin D and anaemia.
Materials and Methods
Study population
Participants were recruited from the Emory University/Georgia Institute of Technology (Georgia Tech) Predictive Health Initiative cohort within the Center for Health Discovery and Well Being (21). This is a cohort of generally healthy adults (age ≥ 18 years) living in the Atlanta area and working in a university setting. Recruitment into the cohort was based on invitation to a random list of Emory employees and members of the Emory and Georgia Tech communities. Exclusion was based on hospitalization for acute or chronic disease within the previous year; severe psychosocial disorder within the previous year; addition of new prescription medications to treat a chronic condition within the previous year (with the exception of changes in anti-hypertensive or anti-diabetic agents); history of substance/drug abuse or alcoholism; current active malignant neoplasm; history of malignancy other than localized basal cell cancer of the skin during the previous 5 years; uncontrolled or poorly controlled autoimmune, cardiovascular, endocrine, gastrointestinal, hematologic, infectious, inflammatory, musculoskeletal, neurologic, psychiatric or respiratory disease; and any acute illness in the twelve weeks before baseline visits. Participants enrolled between January 2008 and February 2013 with available serum 25(OH)D and haemoglobin concentrations were included in the current analysis. This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving human subjects were approved by the Emory University Institutional Review Board. Written informed consent was obtained from all participants.
Data collection
Upon enrolment, participants completed questionnaires on demographic information, personal and family health history, current health status, and medication and supplement use. Physical activity was assessed via the Cross-Cultural Activity Participation Study (CAPS) Physical Activity Questionnaire (22), and glomerular filtration rate was estimated, as a marker of kidney function, using the Modification of Diet in Renal Disease (MDRD) equation (23). Venepuncture for biochemical measurements was performed after an overnight fast. Serum 25(OH)D concentrations were measured commercially via liquid chromatography/tandem mass spectrometry in a laboratory that participates in the Vitamin D External Quality Assessment Scheme (Quest Diagnostics, Tucker, GA, USA). Markers of iron status were measured as follows: serum ferritin via immunoassay, total serum iron and iron binding capacity via spectrophotometry, and haemoglobin and haematocrit via high performance liquid chromatography (Quest Diagnostics, Tucker, GA, USA). Serum high-sensitivity C-reactive protein (CRP) was measured using nephelometry (Quest Diagnostics, Tucker, GA, USA). Serum IL-6, IL-8, tumor necrosis factor- α (TNF-α), and interferon-gamma (IFN-γ) concentrations were measured using a Fluorokine® MultiAnalyte Profiling multiplex kit (R&D Systems, Minneapolis, MN, USA) with a Bioplex analyzer (Bio-Rad, Hercules, CA, USA).
Definitions
Anaemia was defined based on the World Health Organization criteria as haemoglobin concentration < 130 g/l for men, and < 120 g/l for women (24). Anaemia was further categorized into subtypes based on inflammation status. Participants with anaemia who had CRP concentrations > 3 mg/l or were in the upper quartile of IL-6 concentration (≥ 1.76 pg/ml) were classified as having anaemia with inflammation. Those with CRP concentrations ≤ 3 mg/l or who were in the lower three quartiles of IL-6 concentrations (< 1.76 pg/ml) were classified as having anaemia without inflammation. The CRP cut-point used was based on the American Heart Association determination of an increased risk of heart disease with CRP concentrations > 3 mg/l (25). Given its role in upregulating hepcidin expression (14), IL-6 was incorporated into our definition of inflammation; however in the absence of a standard clinical cut-point, inflammation was defined based on the upper quartile of IL-6 in our dataset. Participants were determined to be nutrient deficient if they had evidence of iron deficiency (serum ferritin < 12 μg/l and transferrin saturation < 15%) (26) or low serum vitamin B12 (levels < 147.6 pmol/l) (5). Other nutritional measures related to anaemia of nutrient deficiency, such as folate, were not available for this cohort.
Statistical Analysis
Descriptive statistics were examined for all variables. Continuous variables were reported as means and standard deviations (SD) for normally distributed variables or medians and interquartile ranges (IQR) for non-normally distributed variables; categorical variables were presented as numbers of subjects and percentages. Continuous variables not following a normal distribution were logarithmically transformed (serum ferritin, and all inflammatory markers) for modelling. For variables requiring log transformation with values of zero (IL-6, TNF-α, and IFN-γ), a constant of 1 was added to all non-missing values. Differences in demographic and biochemical variables by serum 25(OH)D status (dichotomized as serum 25(OH)D < 50 nmol/l compared to serum 25(OH)D concentrations ≥ 50 nmol/l, based on the Institute of Medicine (IOM) guidelines (27), and by race (whites compared to blacks) were examined using two sample t-tests for normally distributed continuous variables, Wilcoxon-Mann-Whitney tests for non-normally distributed continuous variables, and Chi-Square or Fisher’s exact test for categorical variables. Pearson correlations and simple linear regression analyses were performed to examine bivariate associations of vitamin D status with biomarkers related the anaemia, haemoglobin and serum iron. To further explore these associations, multivariable linear regression analyses were performed with haemoglobin and serum iron as dependent variables and vitamin D status was the independent variable, controlling for age, sex, race, BMI, IL-6, and CRP as a priori covariates.
Simple logistic regression was used to examine demographic, health history, and biochemical variables associated with anaemia. Multivariable logistic regression was used to assess the association between vitamin D status (independent variable) and anaemia (dependent variable). Variables that were significantly association with anaemia in bivariate analysis were included as covariates in these models. We assessed for an interaction between vitamin D status and race using a likelihood ratio test, given that both vitamin D status and anaemia prevalence are known to differ by race group (1, 19-20).
To further explore the association of vitamin D status with anaemia with and without inflammation, multivariable logistic regression analyses were performed using anaemia with inflammation and anaemia without inflammation as dependent variables and vitamin D status as the independent variable. We assessed for interaction between race and vitamin D status using a likelihood ratio test, and included the same covariates used in the overall anaemia models (with the exception of inflammatory markers given their use in the definition of the anaemia with inflammation outcome). All analyses were performed using SAS v 9.3 (SAS Institute, Inc., Cary, NC), with a two-sided P value < 0.05 used to define statistical significance.
Results
Participant Characteristics
Of the 719 participants enrolled in the Emory/Georgia Tech Predictive Health Institute cohort as of February 2013, 638 had available serum 25(OH)D and haemoglobin levels and were included in the current analysis. Demographic characteristics of these participants, as a whole and by vitamin D status (25(OH)D < 50 nmol/l vs 25(OH)D ≥ 50 nmol/l), are shown in Table 1. Among the whole cohort, the mean age was 48.3 (SD 10.9) years, and approximately two thirds of the participants were female. Race and ethnicity was based on self-report and those in this cohort were primarily non-Hispanic or Latino; 72% were white, 23% were black/African American, 5% were Asian, and 1% identified as another race. For the regression analyses, participants were restricted to white and black/African American (n 602). This was a relatively highly educated and affluent population. The cohort was generally overweight, and while participants were healthy by self-report, some did report a history of stable chronic conditions including hypertension and diabetes. Characteristics which differed by vitamin D status included age, race, education, income, BMI, comorbidities, supplementation, and season of study visit. Among the participants with serum 25(OH)D < 50 nmol/l the mean age was younger (P < 0.001), a greater proportion were black/African American (P < 0.001), a greater proportion reported less education (P= 0.007) and lower income (P= 0.007), the mean BMI was greater (P < 0.001), there was a higher prevalence of hypertension (P < 0.001) and diabetes (P = 0.002), and a lower proportion took any vitamin D (P < 0.001) or multivitamin supplements (P < 0.001), compared to those with serum 25(OH)D concentrations ≥ 50 nmol/l. Compared to whites, blacks in our cohort were younger (P = 0.002), a higher proportion were female (P < 0.001), had lower education and income levels (P < 0.001), had higher BMIs (P < 0.001), had a higher prevalence of hypertension (P < 0.001) and diabetes (P = 0.04), and a higher proportion reported taking vitamin D supplements (P = 0.004) (Table S1).
Table 1.
Demographic, socioeconomic, and health status characteristics of Emory-Georgia Tech Predictive Health Initiative cohort (2008-2013)*, by serum 25(OH)D status (number and percentage of subjects, mean and standard deviation)
| Characteristic | All (n 638) | 25(OH)D < 50 nmol/l (n 116) | 25(OH)D ≥ 50 nmol/l (n 522) | P† | |||
|---|---|---|---|---|---|---|---|
|
| |||||||
| n | % | n | % | n | % | ||
| Age‡, years | < 0.001 | ||||||
| Mean | 48.3 | 45.3 | 49.0 | ||||
| SD | 10.9 | 11.3 | 10.7 | ||||
| Sex | 0.10 | ||||||
| Male | 206 | 32.3 | 30 | 25.9 | 176 | 33.7 | |
| Female | 432 | 67.7 | 86 | 74.1 | 346 | 66.3 | |
| Ethnicity‡ | 0.21 | ||||||
| Hispanic or Latino | 9 | 1.4 | 3 | 2.6 | 6 | 1.2 | |
| Non-Hispanic or Latino | 628 | 98.6 | 113 | 97.4 | 515 | 98.9 | |
| Race‡ | < 0.001 | ||||||
| White | 457 | 71.7 | 50 | 43.1 | 407 | 78.1 | |
| Black/African American | 145 | 22.8 | 57 | 49.1 | 88 | 16.9 | |
| Asian | 29 | 4.6 | 8 | 6.9 | 21 | 4.0 | |
| Other | 6 | 0.9 | 1 | 0.9 | 5 | 1.0 | |
| Education§,‡ | 0.007 | ||||||
| Less than high school | 2 | 0.3 | 0 | 0 | 2 | 0.4 | |
| Completed high school | 17 | 2.7 | 4 | 3.5 | 13 | 2.5 | |
| Some college | 99 | 15.5 | 31 | 26.7 | 68 | 13.1 | |
| Four years of college | 151 | 23.7 | 25 | 21.6 | 126 | 24.2 | |
| Any graduate school | 368 | 57.8 | 56 | 48.3 | 312 | 59.9 | |
| Annual household income‡ | 0.007 | ||||||
| ≤ $50,000/yr | 68 | 11.3 | 20 | 18.4 | 48 | 9.7 | |
| >$50,000-$100,000/yr | 117 | 29.4 | 38 | 34.9 | 139 | 28.2 | |
| >$100,000 - $200,000/yr | 217 | 36.1 | 35 | 32.1 | 182 | 36.9 | |
| >$200,000/yr | 140 | 23.3 | 16 | 14.7 | 124 | 25.2 | |
| Physical activity∥,‡ | 154 | 24.3 | 29 | 25.0 | 125 | 24.1 | 0.84 |
| BMI‡, kg/m2 | <0.001 | ||||||
| Mean | 28.0 | 32.6 | 27.0 | ||||
| SD | 6.5 | 8.7 | 5.3 | ||||
| Current smoker‡ Comorbidities | 35 | 5.5 | 10 | 8.7 | 25 | 4.8 | 0.10 |
| History of hypertension‡ | 126 | 19.8 | 36 | 31.3 | 90 | 17.2 | <0.001 |
| History of diabetes‡ | 34 | 5.3 | 13 | 11.3 | 21 | 4.0 | 0.002 |
| eGFR ≥ 60 ml/min/1.73m2‡ | 621 | 97.8 | 115 | 99.1 | 506 | 97.5 | 0.48 |
| Any vitamin D supplementation¶ | 262 | 41.1 | 20 | 17.2 | 242 | 46.4 | <0.001 |
| Multivitamin use | 211 | 30.1 | 16 | 13.8 | 195 | 37.4 | <0.001 |
| Iron supplement use‡ | 10 | 1.9 | 3 | 3.5 | 7 | 1.6 | 0.22 |
| Season of visit‡ | 0.03 | ||||||
| Winter | 137 | 21.5 | 24 | 20.7 | 113 | 21.7 | |
| Spring | 103 | 16.2 | 29 | 25.0 | 74 | 14.2 | |
| Summer | 187 | 29.4 | 33 | 28.5 | 154 | 29.6 | |
| Fall | 210 | 33.0 | 30 | 25.9 | 180 | 34.6 | |
Restricted to participants with available vitamin D and haemoglobin values
Two sample t-test for continuous variables, Chi-sq or Fisher’s exact test for categorical variables, comparing 25(OH)D < 50 nmol/l and 25(OH)D ≥ 50 nmol/l
Education refers to highest educational achievement; less than high school defined as less than 12th grade, completed high school defined as completion of 12th grade, some college defined as less than 4 years of college, and any graduate school includes both graduate and post-graduate education
Meet CAPS guidelines for moderate physical activity
Vitamin D supplementation from any source (alone, in combined supplement, or in multivitamin)
age: n 116 and n 521 for 25(OH)D < 50 nmol/l and 25(OH)D ≥ 50 nmol/l, respectively; ethnicity: n 116 and n 521 for 25(OH)D < 50 nmol/l and 25(OH)D ≥ 50 nmol/l, respectively; race: n 116 and n 521 for 25(OH)D < 50 nmol/l and 25(OH)D ≥ 50 nmol/l, respectively; education: n 116 and n 521 for 25(OH)D < 50 nmol/l and 25(OH)D ≥ 50 nmol/l, respectively; income: n 109 and n 493 for 25(OH)D < 50 nmol/l and 25(OH)D ≥ 50 nmol/l, respectively; physical activity: n 116 and n 518 for 25(OH)D < 50 nmol/l and 25(OH)D ≥ 50 nmol/l, respectively; BMI: n 115 and n 521 for 25(OH)D < 50 nmol/l and 25(OH)D ≥ 50 nmol/l, respectively; smoking: n 115 and n 521 for 25(OH)D < 50 nmol/l and 25(OH)D ≥ 50 nmol/l, respectively; hypertension: n 115 and n 522 for 25(OH)D < 50 nmol/l and 25(OH)D ≥ 50 nmol/l, respectively; diabetes: n 115 and n 522 for 25(OH)D < 50 nmol/l and 25(OH)D ≥ 50 nmol/l, respectively; eGFR: n 116 and n 519 for 25(OH)D < 50 nmol/l and 25(OH)D ≥ 50 nmol/l, respectively; iron supplementation: n 86 and n 431 for 25(OH)D < 50 nmol/l and 25(OH)D ≥ 50 nmol/l, respectively; season: n 116 and n 521 for 25(OH)D < 50 nmol/l and 25(OH)D ≥ 50 nmol/l, respectively
Among the entire cohort, approximately 50% of the participants had serum 25(OH)D concentrations < 75 nmol/l, 18% had serum 25(OH)D concentrations < 50 nmol/l, and 3% had serum 25(OH)D concentrations < 30 nmol/l. The mean serum 25(OH)D concentration was in the range considered sufficient (Table 2). Mean haemoglobin was above the threshold for anaemia. Mean and median measures of iron status were all within normal ranges (28). Approximately, eight percent of the cohort was anaemic, and of these, 4.9 percent of the cohort had anaemia with inflammation and 3.3 percent of the cohort had anaemia without inflammation. There were 16 anaemic participants with evidence of nutrient deficiency (15 with iron deficiency and one with low serum vitamin B12). Those with serum 25(OH)D concentrations < 50 nmol/l had lower haemoglobin (P = 0.008), haematocrit (P = 0.03), and serum iron concentrations (P < 0.001), and higher CRP (P < 0.001), and IL-6 concentrations (P < 0.001) compared to those with serum 25(OH)D ≥ 50 nmol/l. Furthermore, there was a higher prevalence of anaemia overall (P = 0.001) and specifically anaemia with inflammation among those with serum 25(OH)D concentrations < 50 nmol/l (P < 0.001). Compared to whites, blacks in our cohort had lower serum 25(OH)D concentrations (P < 0.001), lower haemoglobin concentrations (P < 0.001), haematocrit (P < 0.001), and serum iron concentrations (P < 0.001), and higher CRP (P < 0.001) and IL-6 concentrations (P < 0.001) (Table S2). Blacks also had a higher prevalence of vitamin D deficiency (P < 0.001), and anaemia (P < 0.001).
Table 2.
Iron status and inflammatory markers of Emory-Georgia Tech Predictive Health Initiative cohort (2008-2013), by serum 25(OH)D status (Mean values with their standard deviations, median values with interquartile range (IQR), number of subjects and percentages)
| All (n 638) | 25(OH)D < 50 nmol/l (n 116) | 25(OH)D ≥ 50 nmol/l (n 522) | |||||
|---|---|---|---|---|---|---|---|
|
| |||||||
| Mean | SD | Mean | SD | Mean | SD | P* | |
| Serum 25(OH)D (nmol/l) | 76.1 | 30.5 | 37.4 | 8.7 | 84.9 | 26.7 | <0.001 |
| Whites | 82.4 | 30.2 | 40.2 | 8.0 | 87.7 | 27.9 | |
| Blacks | 57.9 | 23.7 | 35.3 | 8.6 | 72.8 | 18.2 | |
| Haemoglobin (g/l) | 137.9 | 14.8 | 134.8 | 15.9 | 138.6 | 13.2 | 0.008 |
| Whites | 140.7 | 12.9 | 139.9 | 17.4 | 140.8 | 12.3 | |
| Blacks | 129.2 | 12.5 | 128.9 | 11.2 | 129.4 | 13.3 | |
| Haematocrit (%) | 40.7 | 3.8 | 40.0 | 4.3 | 40.8 | 3.6 | 0.03 |
| Serum ferritin (μg/l)† | 0.34 | ||||||
| Median | 62.5 | 55.0 | 63.0 | ||||
| IQR | 91.0 | 77.0 | 92.0 | ||||
| Serum iron (μmol/l) | 16.8 | 6.3 | 14.9 | 5.6 | 17.3 | 6.4 | <0.001 |
| Iron binding capacity (μmol/l) | 64.0 | 9.8 | 64.2 | 9.9 | 65.0 | 9.6 | 0.41 |
| Serum CRP (mg/l)†,‡ | <0.001 | ||||||
| Median | 1.5 | 3.2 | 1.4 | ||||
| IQR | 2.7 | 4.4 | 2.2 | ||||
| Serum IL-6 (pg/ml)†,‡ | <0.001 | ||||||
| Median | 1.0 | 1.6 | 1.0 | ||||
| IQR | 1.4 | 2.1 | 1.23 | ||||
| Serum IL-8 (pg/ml)†,‡ | 0.28 | ||||||
| Median | 8.2 | 8.7 | 8.2 | ||||
| IQR | 5.5 | 7.3 | 5.2 | ||||
| Serum TNF-α (pg/ml)†,‡ | 0.41 | ||||||
| Median | 3.7 | 4.0 | 3.7 | ||||
| IQR | 2.5 | 2.7 | 2.4 | ||||
| Serum IFN-γ (pg/ml)†,‡ | 0.09 | ||||||
| Median | 0.2 | 0.1 | 0.2 | ||||
| IQR | 0.3 | 0.3 | 0.4 | ||||
|
| |||||||
| n | % | n | % | n | % | P | |
|
| |||||||
| Anaemia | 52 | 8.2 | 18 | 15.5 | 34 | 6.5 | 0.001 |
| Anaemia with inflammation§ | 31 | 4.9 | 15 | 12.9 | 16 | 3.1 | <0.001 |
| Anaemia without inflammation‡ | 21 | 3.3 | 3 | 2.6 | 18 | 3.4 | 0.78 |
Two sample t-tests for normally distributed continuous variables, Wilcoxon-Mann-Whitney test for non-normally distributed continuous variables, Chi-Sq or Fisher’s exact test for categorical variables
Median and IQR given for non-normally distributed variables
Anaemia with inflammation defined as anaemia with serum CRP > 3 mg/l or upper quartile of IL-6 (≥ 1.76 pg/ml); anaemia without inflammation defined as anaemia with CRP ≤ 3mg/l or quartiles 1-3 of IL-6 (<1.76 pg/ml)
CRP: n 116 and n 521 for 25(OH)D < 50 nmol/l and 25(OH)D ≥ 50 nmol/l, respectively; IL-6: n 114 and n 509 for 25(OH)D < 50 nmol/l and 25(OH)D ≥ 50 nmol/l, respectively; IL-8: n 114 and n 510 for 25(OH)D < 50 nmol/l and 25(OH)D ≥ 50 nmol/l, respectively; TNF-α: n 114 and n 510 for 25(OH)D < 50 nmol/l and 25(OH)D ≥ 50 nmol/l, respectively; IFN-γ: n 114 and n 510 for 25(OH)D < 50 nmol/l and 25(OH)D ≥ 50 nmol/l, respectively
Associations of vitamin D status with markers of iron status
In simple linear regression analysis, serum 25(OH)D was positively associated with haemoglobin concentrations (β ± SE: 0.05 ± 0.02, P=0.004); however adjustment for age, sex, race, BMI, CRP, and IL-6, attenuated the significance (P=0.23). Serum 25(OH)D was positively associated with serum iron concentrations (β ± SE: 0.04 ± 0.01, P<0.001, Figure 1), and the association remained significant after adjusting for age, sex, race, BMI, CRP, and IL-6 (β ± SE: 0.02 ± 0.01, P=0.006).
Fig. 1.
Correlation between vitamin D status (serum 25-hydroxyvitamin D (25(OH)D)) and total circulating iron concentrations in participants of the Emory/Georgia Tech Predictive Health Initiative cohort (2008 – 2013), n 638. Total serum iron was positively correlated with serum 25(OH)D concentration (Pearson’s r=0.2, P<0.001), and this association remained statistically significant after adjusting for age, sex, race, BMI, CRP, and IL-6 (β ± SE: 0.02 ± 0.01, P=0.006).
Association of vitamin D status with anaemia
Serum 25(OH)D as a continuous variable was significantly associated with decreased odds of anaemia (OR 0.98; 95% CI 0.97, 0.99). Odds of anaemia were increased when participants were dichotomized by various serum 25(OH)D cut-points for vitamin D insufficiency/deficiency: < 75 nmol/l (OR 2.15; 95% CI 1.18, 3.92), < 50 nmol/l (OR 2.64; 95% CI 1.43, 4.86), < 30 nmol/l (OR 4.97; 95% CI 1.84, 13.41). These associations remained significant after adjustment for season (OR25(OH)D <75 nmol/l 2.10; 95% CI 1.15, 3.85; OR25(OH)D < 50 nmol/l 2.54; 95% CI 1.37, 4.72, OR25(OH)D < 30 nmol/l 5.02; 95% CI 1.82, 13.85). Additional variables associated with anaemia in bivariate analysis included inflammatory markers CRP, IL-6, and IL-8, black race, female gender, BMI, history of diabetes, and lower annual income, age, and iron supplement intake (Table S3). TNF-α and IFN-γ, waist circumference, physical activity, smoking status, history of hypertension, education, multivitamin use, and vitamin D supplementation were not significantly associated with anaemia.
There was a significant interaction between race and vitamin D status (P = 0.003), such that the association between vitamin D status and anaemia remained significant only among blacks (Table 3). After adjustment for significant anaemia covariates from the bivariate analyses (age, sex, BMI, CRP, IL-6, IL-8, use of iron supplements, income, and diabetes) the odds of anaemia were 6 times higher for blacks with serum 25(OH)D < 50 nmol/l compared to blacks with serum 25(OH)D ≥ 50 nmol/l (OR 6.42; 95% CI 1.88, 21.99) (Table 3).
Table 3.
Association of serum 25(OH)D < 50 nmol/l and anaemia, stratified by race (Odds ratios and their 95% confidence intervals)
| All | White | Black | ||||
|---|---|---|---|---|---|---|
|
| ||||||
| OR*, † | 95% CI | OR* | 95% CI | OR* | 95% CI | |
| Unadjusted‡ | 2.64 | 1.43, 4.86 | 0.77 | 0.33, 1.81 | 5.36 | 2.00, 14.33 |
| Model 1§ | 2.02 | 0.99, 4.14 | 0.69 | 0.28, 1.68 | 5.36 | 1.88, 15.28 |
| Model 2∥ | 1.75 | 0.84, 3.63 | 0.55 | 0.22, 1.40 | 5.08 | 1.74, 14.85 |
| Model 3¶ | 2.08 | 0.92, 4.73 | 0.62 | 0.22, 1.75 | 6.42 | 1.88, 21.99 |
Odds ratio comparing 25(OH)D < 50 nmol/l vs. 25(OH)D ≥ 50 nmol/l
Race not included as covariate due to evidence of interaction (P=0.003)
Crude association between 25(OH)D < 50 nmol/l and anaemia, n 602
Adjusted for age, sex, BMI, n 599
Model 1 + adjustment for CRP, IL-6, IL-8, n 586
Model 2 + adjustment for use of iron supplements, income, and history of diabetes, n 465
The magnitude of effect in blacks increased when vitamin D status was defined by 25(OH)D < 30 nmol/l and 25(OH)D ≥ 30 nmol/l (fully adjusted OR 17.3; 95% CI 2.27, 132.0). There was no significant association between anaemia and vitamin D status defined by 25(OH)D < 75 nmol/l and ≥ 75 nmol/l after adjustment for the same covariates.
Association of vitamin D status with subtypes of anaemia
The crude association between serum 25(OH)D < 50 nmol/l and anaemia with inflammation was statistically significant (OR 4.51; 95% CI 2.13, 9.55). However, there was significant effect modification by race (P = 0.03) such that in stratified analyses, controlling for age, sex, BMI, use of iron supplements, income, and history of diabetes, blacks with serum 25(OH)D concentrations < 50 nmol/l had 8 times higher odds of having anaemia with inflammation compared to blacks with serum 25(OH)D ≥ 50 nmol/l (OR 8.64; 95% CI 2.01, 37.23) (Table 4). The association between vitamin D status and anaemia with inflammation was not statistically significant in whites. When we excluded those with evidence of nutrient deficiency from the anaemia with inflammation outcome, the crude association between vitamin D status and anaemia with inflammation remained statistically significant (OR 4.29, 95% CI 1.80, 10.23); however, the limited sample size with this sub-analysis precluded adjustment for the anaemia covariates controlled for above. The crude association between vitamin D status and anaemia without inflammation was not statistically significant (OR 0.74; 95% CI 0.22, 2.57).
Table 4.
Association of serum 25(OH)D < 50 nmol/l and anaemia with inflammation, stratified by race (Odds ratios and their 95% confidence intervals)
| All | White | Black | ||||
|---|---|---|---|---|---|---|
|
| ||||||
| OR*, † | 95% CI | OR* | 95% CI | OR* | 95% CI | |
| Unadjusted‡ | 4.51 | 2.13, 9.55 | 1.31 | 0.51, 3.40 | 8.93 | 2.49, 32.04 |
| Model 1§ | 2.61 | 1.10, 6.17 | 0.98 | 0.36, 2.72 | 7.44 | 1.93, 28.75 |
| Model 2∥ | 3.14 | 1.23, 7.99 | 1.20 | 0.39, 3.68 | 8.64 | 2.01, 37.23 |
Odds ratio comparing 25(OH)D < 50 nmol/l vs. 25(OH)D ≥ 50 nmol/l
Race not included as covariate due to evidence of interaction (P=0.03)
Crude association between 25(OH)D < 50 nmol/l and anaemia, n 602
Adjusted for age, sex, BMI, n 599
Model 1 + adjustment for use of iron supplements, income, and history of diabetes, n 474
Discussion
This study reports an association between vitamin D status and anaemia in a generally healthy, working adult population. There were several notable findings: 1) we found a significant positive association between serum 25(OH)D concentrations and serum iron; 2) 25(OH)D < 50 nmol/l was associated with increased odds of anaemia in blacks, but not in whites, and 3) the association between vitamin D status and anaemia among blacks was especially prominent in anaemia with inflammation, consistent with our hypothesis that vitamin D that would be associated particularly with anaemia with inflammation.
Our results are supported by other epidemiologic studies which have demonstrated inverse associations between vitamin D status and odds of anaemia in patients with chronic kidney disease, and heart failure (11, 12). These studies indicate a consistent inverse association between vitamin D status and odds of anaemia. Our analysis adds to the literature by suggesting that the association may pertain particularly to anaemia with inflammation. However, there have been few trials examining the impact of vitamin D supplementation on anaemia. Lin, et al, showed in patients undergoing hemodialysis, treatment with the active form of vitamin D, calcitriol, was effective in improving anaemia of chronic kidney disease (29). In a study of patients with myelodysplastic syndromes, Mellibovsky, et al, demonstrated that treatment with calcitriol resulted in increases in hematologic markers including haemoglobin (30). Further investigation is needed to better understand the therapeutic effects of vitamin D supplementation on anaemia, especially in generally health persons.
Our findings are consistent with the hypothesized mechanisms underlying the vitamin D-anaemia relationship. Anaemia resulting from chronic inflammation is characterized by disturbances in iron regulation such that iron becomes sequestered in cells of the reticuloendothelial system as a result of the action of pro-inflammatory markers, such as IL-6, on hepcidin, the global regulator of iron metabolism (14, 15). Hepcidin acts on ferroportin, the iron exporter on the surface of enterocytes, macrophages, and hepatocytes, resulting in its internalization and degradation, preventing iron efflux from the cell (31). This leads to a decrease in iron available in circulation for erythropoiesis and heme synthesis (despite adequate iron stores and total body iron), ultimately leading to anaemia (15, 16). Vitamin D is thought to temper the effect of inflammation-induced anaemia by decreasing the secretion of pro-inflammatory cytokines. Our group recently demonstrated through a series of in vitro studies, that vitamin D can decrease the release of cytokines IL-6 and IL-1β from macrophages, and down-regulate hepcidin and up-regulate ferroportin expression in human monocytes (17). These findings are consistent with those of Bacchetta, et al, showing that treatment of hepatocytes and monocytes with vitamin D, resulted in decreased expression of hepcidin mRNA (18). In support of this putative mechanism for the role of vitamin D in iron metabolism, our findings showed that serum 25(OH)D concentrations were positively associated with serum iron concentrations, suggesting that increases in vitamin D status may lead to increases in circulating iron available for use in erythropoiesis and heme synthesis. Furthermore, in our cohort, vitamin D deficiency was associated with anaemia with inflammation but not with anaemia without inflammation, supporting a potential role for vitamin D in iron recycling in the context of inflammation.
In our cohort, the association between vitamin D status and odds of anaemia was significant only among blacks. The odds of anaemia were approximately 6 times higher for blacks with serum 25(OH)D < 50 nmol/l compared to blacks with serum 25(OH)D ≥ 50 nmol/l, though the confidence intervals around the estimate were relatively wide. The magnitude of effect was even greater for blacks with serum 25(OH)D < 30 nmol/l compared to those with 25(OH)D≥30 nmol/l (OR 17.3; 95% CI 2.27, 132.0), though the estimate remained imprecise. A potential explanation for the racial differences in the association between vitamin D status and anaemia is the racial difference in circulating inflammatory markers. Increased IL-6 expression in African Americans compared to Caucasians has been demonstrated in human umbilical vein endothelial cells (32). Further, a systematic review of 32 population-based studies found higher CRP concentrations in non-whites compared to whites (33). Similarly, in our population, IL-6 and CRP were significantly increased in blacks compared to whites. Moreover, the magnitude of effect for the association of serum 25(OH)D < 50 nmol/l with odds of anaemia with inflammation increased above that of anaemia overall. Thus, higher inflammation in blacks may be augmenting the association between vitamin D status and anaemia in this racial group compared to whites.
There are currently no race-specific cut-offs for anaemia. However, it is known that blacks have a higher prevalence of vitamin D deficiency and lower haemoglobin concentrations compared to whites (1, 19, 20). The clinical significance of this is not well understood. Vitamin D deficiency may provide one potential explanation for the differences observed in haemoglobin concentration and anaemia prevalence between blacks and whites.
Strengths of this study were a large sample size and a well-characterized cohort. However, this was a cross-sectional analysis, leaving us unable to conclude causality in the vitamin D-anaemia associations observed, and reverse causality bias cannot be excluded. We were also unable to measure hepcidin concentrations and, therefore, could not directly examine the putative mechanism underlying the vitamin D and anaemia association observed. Health status and socioeconomic variables were collected via self-administered questionnaires; thus recall error may be a limiting factor. Our population was self-selected from individuals invited to participate in the Emory-Georgia Tech Predictive Health Initiative. In addition, the majority of participants reported high income and education level and are therefore not representative of the general population. However, one may expect such a population to have regular access to health resources; thus the persistence of the vitamin D-anaemia association is noteworthy. Additional prospective studies exploring the relationship between vitamin D status and anaemia, including those in low-income populations, are warranted.
In conclusion, our results suggest that lower vitamin D status is associated with anaemia, particularly anaemia with inflammation, among blacks in a generally healthy and high socioeconomic cohort residing in Atlanta, GA. Given the duel burden of vitamin D deficiency and anaemia prevalence among blacks, our findings have important public health implications. Clinical trials in racially diverse populations are necessary to elucidate the therapeutic effect of vitamin D supplementation on anaemia.
Acknowledgments
Financial Support: Information upon which this work is based is from the Emory/Georgia Tech Predictive Health Participant Database, and is supported by the National Center for Advancing Translational Sciences of the National Institutes of Health (UL1 TR000454). Other sources of support for this study include grants from the National Institutes of Health (E.M.S., grant number T32 DK007734), (J.A.A., grant numbers T32 DK007298, K01 DK102851), (T.R.Z., grant number K24 RR023356) and the Emory-Egleston Children’s Research Center (S.M.Z.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The funders had no role in the design, analysis or writing of this article.
Abbreviations
- 25(OH)D
25-hydroxyvitamin D
- CKD
chronic kidney disease
- CRP
C-reactive protein
- eGFR
estimated glomerular filtration rate
- IFN-γ
interferon-γ
- IL-6
interleukin-6
- IL-8
interleukin-8
- TNF-α
tumor necrosis factor-α
Footnotes
Conflict of Interest: None
Authorship: EMS, JAA, and VT formulated the research question; GSM and TRZ had leading roles in the cohort study design, implementation, and data collection; EMS, JAA, and VT analysed data; EMS, JAA, GSM, SMZ, TRZ, and VT wrote the article; EMS and VT had primary responsibility for final content. All authors read and approved the final manuscript.
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