High red blood cell distribution width is associated with the metabolic syndrome

Abstract

OBJECTIVES: High values of Red Blood Cell Distribution Width (RDW) have been associated with adverse outcome in various clinical settings. The mechanism behind this association is not clear. The Metabolic Syndrome (MetS) is a chronic inflammatory disorder that increases the risk for cardiovascular disease and death. The aim of our study was to evaluate the association between high RDW and the MetS in a relatively large cohort of patients.

METHODS: A cohort of 3,529 consecutive patients undergoing coronary angiography was used to evaluate the association between RDW and the MetS. The association was assessed by using a logistic regression. Cox’s regression analysis was used to evaluate the impact of RDW on long term mortality.

RESULTS: The mean age was 65 years (range 24–97), with 27% women. Overall, 30% were diagnosed with metabolic syndrome. The prevalence of MetS was 29% in patients with RDW <14% and 34% in patients with RDW ≥14% (P = 0.003).

Using multivariate analysis, RDW values above 14% were independently associated with MetS (odds ratio 1.2 [95% CI 1.0–1.4], P = 0.043). Among all the criteria of the metabolic syndrome, hypertension, elevated glucose levels and abdominal obesity were associated with high RDW, with hypertension being the strongest criteria, with an increased risk of 1.8 fold ([95% CI 1.5–2.1]; P = 0.001). During follow up (1614 ± 709 days, 2–2763 days), long term mortality was 8% in the low RDW group and 28% in the high RDW group (p < 0.001).

CONCLUSION: RDW ≥14% is independently associated with higher rates of metabolic syndrome and long-term all-cause mortality.

Keywords

RDW Metabolic Syndrome biomarkers hs-crp inflammation obesity

1 Introduction

Red blood cell distribution width (RDW) is a numerical measure of the variability in size of circulating erythrocytes. High RDW values indicate greater variation in size. RDW is a novel, independent predictor of prognosis in patients with various cardiovascular diseases [9 , 46] and is associated with increased risk of mortality in the general population [11 , 31] and among patients referring for coronary angiography [10, 36]. The mechanism underlying the increased risk associated with elevated RDW values is not clear.

The incidence of metabolic syndrome (MetS) has been increasing in the current era, with prevalence varying from 8% to 43% in men and from 7% to 56% in women worldwide, mainly due to increase in abdominal adiposity [14, 17].

MetS was defined by the National Cholesterol Education Program’s Adult Treatment Panel III report (ATP III) [13] as the presence of any three of the following characteristics: obesity, high levels of triglycerides (TG), low levels of high-density lipoprotein (HDL), hypertension, and impaired fasting glucose levels. Patients diagnosed with the metabolic syndrome (MetS) have a higher risk for major adverse cardiac events [12 , 42].

The aim of the present study was to evaluate the association between high RDW and MetS in a relatively large cohort of unselected consecutive male and female patients referred for coronary angiography. Our hypothesis was that patients with higher RDW values will have a higher prevalence of MetS. Such a correlation could further improve our understanding of this novel biomarker and may guide clinicians on a possible treatment approach in patients with elevated RDW.

2 Methods

The data was collected as part of the Tel Aviv Prospective Angiographic Survey (TAPAS). TAPAS is a prospective, single-center registry which enrolls all patients undergoing cardiac catheterization at the Tel Aviv Medical Center [2 , 40]. The study cohort consisted of consecutive patients referred for coronary angiography in our institution for various clinical presentations. The study was approved by the institutional ethics committee and all subjects signed a written informed consent for participation.

Arterial blood was obtained from all participants via their arterial access puncture sites as a part of the coronary angiography procedure. The complete blood count and RDW were measured by the Beckman coulter (LH 750 model), and normal levels were set by the manufacturer at 12–15%. Hemoglobin A1c levels were measured by the use of reagents, calibrators and control materials from Bayer Diagnostics (Berkshire, England) on the ADVIA 1650. High-density lipoprotein (HDL) cholesterol levels were determined by the Bayer Advia 1650 chemistry analyzer. Low-density lipoprotein (LDL) cholesterol levels were calculated by total cholesterol, HDL cholesterol and triglyceride (TG) levels using the Friedwald equation: LDL = total cholesterol – HDL – TG/5.

Metabolic syndrome (MetS) was diagnosed according to current guidelines [13]. Briefly, waist circumference ≥102 cm in men and ≥88 cm in women, Triglycerides ≥150 mg/dL, HDL-C <40 mg/dL in men and HDL-C <50 mg/dL in women, elevated blood pressure with ≥130 mmHg systolic pressure and/or ≥85 mm Hg diastolic pressure, and fasting glucose ≥100 mg/dL. The presence of 3 or more of the individual criteria was categorized as MetS.

2.1 Statistical analysis

Categorical variables were compared using Chi-square test and continuous variables by t-test (presented as means with standard deviations, SD) or by Kruksal Wallis / Mann Whitney test (medians with interquartile range, IQR). Continuous variables were tested for normal distribution using Kolmogorov–Smirnov test and Q-Q Plots.

We divided our cohort into two groups according to their RDW values (14%) in the evaluation of the metabolic syndrome by using the CHAID method [16]. The CHAID method chooses the best cutoff of a continuous variable using automatic repeated CHI tests. Logistic regression was used to assess the impact of metabolic and inflammatory biomarkers in addition to RDW on the incidence of metabolic syndrome. Cox’s regression analysis was used to evaluate the impact of RDW on long term mortality. Significant variables found in Univariate analysis (Table 1) were used in the regression models.

A two-tailed p < 0.05 was considered statistically significant. All analyses were performed with the SPSS 21.0 software (SPSS Inc., Chicago, IL).

3 Results

A total of 3,529 consecutive patients undergoing coronary angiography were included in this study. The mean age was 65 (range 24–97) and 27% were women. MetS was classified according to the current guidelines and was present in 30% of the patients. Diabetes mellitus was diagnosed in 22% of the patients (Table 1).

RDW values ranged from 10.9% to 32.3% (mean 13.83% ± 1.5%), and 30% of the patients had an RDW value ≥14%. We divided our cohort into 2 groups using a cutoff of RDW 14% that was found to be predictive of MetS.

The prevalence of MetS was 29% in patients with RDW <14% and 34% in patients with RDW ≥14% (P = 0.003) (Table 2) (Fig. 1).

High RDW was significantly associated with older age and more co-morbidities (hypertension, diabetes mellitus, peripheral vascular disease, ischemic heart disease, myocardial infarction and coronary artery bypass surgery) (Table 1).

In multivariate analyses, high RDW (≥14%) was associated with MetS after adjusting for age, gender, anemia, white blood cell count, mean corpuscular volume and ischemic heart disease (odds ratio 1.2 [95% CI 1.0–1.4]; P = 0.043).

During follow up (1614 ± 709 days, 2–2763 days), long term mortality was 8% in the low RDW group (RDW <14%) comparing to 28% in the high RDW group (RDW ≥14%) (p < 0.001). After adjustment, the high RDW group had an increased risk for all-cause mortality of 2.2 fold ([95% CI 1.8–2.7]; P < 0.001) (Fig. 2).

Among all the criteria of MetS, hypertension, elevated glucose levels and abdominal obesity were associated with high RDW, with hypertension being the strongest criteria, with an increased risk of 1.8 fold ([95% CI 1.5–2.1]; P = 0.001).

A significant association was observed between high RDW and inflammatory biomarkers, such as C-reactive protein, white blood cells and fibrinogen (Table 4).

4 Discussion

In the present study, we evaluated the association between high RDW and the metabolic syndrome. We demonstrated that elevated RDW values (≥14%) were associated with increased risk for developing MetS and for long term all-cause mortality. Among all the criteria of MetS, hypertension was the strongest factor with increased risk of 1.8 fold. In addition, elevated RDW values were associated with increased inflammatory biomarkers.

RDW reflects the variability in size of circulating red blood cells and is used in the diagnosis of anemia. RDW is a novel strong and independent predictor of all-cause mortality [11, 18]. The mechanism by which elevated RDW is associated with adverse outcomes remains unclear. Our results are in accordance with previous studies demonstrating an association between RDW and inflammatory markers [23 , 35].

Metabolic syndrome (MetS) is a cluster of metabolic abnormalities and has been correlated with increased risk for major adverse cardiac events [25, 42].

Recent publications have demonstrated that M MetS patients are at higher risk for the occurrence of cancer [21] and suffer from increased risk for all-cause mortality and cardiovascular mortality [26]. Some have argued that the metabolic syndrom is an arbitrary concept [24 , 34], yet many use it in routine clinical practice.

Our large cohort, including both genders, allowed us to conduct subgroup analyses and examine the relationship between RDW and MetS, and each criteria of the syndrome.

Published data regarding the possible association between RDW and MetS is scarce. Vaya et al. [44], demonstrated an independent association between MetS and RDW, with abdominal obesity being the strongest criteria. This study was based on a relatively small cohort (150 patients) compared to our study. Another cross-sectional study, [36] which was part of the Ibermutuamur CArdiovascular RIsk Assessment (ICARIA) plan, also showed that MetS was associated with the highest quartile of RDW (>14%). Although this study was conducted on a large population, it was consisted mostly of young healthy individuals who are not representative of the medically treated population. Obesity has been linked to hemorheological changes in the blood and could be part of the mechanism leading to increased RDW [45].

Our study is novel by its large consecutive population and by evaluating a variety of chronic diseases in association with high RDW (Table 1). As in previous studies, we also used the cutoff of RDW ≥14% and confirmed our assumption that high RDW is associated with MetS. In contrast to Vaya et al., we found that most of the criteria of METS, except for low HDL and TG, are significantly associated to high RDW, with hypertension being the strongest.

The association of MetS and adverse outcome can be explained by the mechanism of more advanced atherosclerosis, and a greater systemic inflammation [29]. MetS is a cluster of risk factors and can be treated effectively by evidence based therapies [3, 26]. Yet, despite this accumulating data, it was shown that healthcare providers fail to recognize the magnitude of the problem and to address its implications [28].

The association between RDW and MetS can be explained by increased inflammation. Proinflammatory cytokines have been found to inhibit erythropoietin-induced erythrocyte maturation, which is reflected in part by an increase in RDW [10, 32]. These assumptions are supported by our findings (Table 4) which show a significant relation between high RDW and C-reactive protein, white blood cells and fibrinogen. Previous studies have shown that there are structural changes in the erythrocyte membrane among women with features of metabolic syndrome [1]. Sesso et al., showed that elevated C-reactive protein levels are associated with future development of hypertension, which suggests that hypertension is in part of an inflammatory disorder [38]. This finding correlates with our finding that hypertension had the strongest association with elevated RDW among the MetS criteria.

This important finding could help raise vigilance among physicians for early evaluation and diagnosis of MetS, just by a routinely used blood test. Future studies are needed in order to determine if RDW is increased in early stages before the diagnosis of MetS can be done. This may allow early recognition of high risk patients susceptible to suffer from METS and may prevent its associated complications.

Study limitations: First, this is a single center study. Second, our study was observational and therefore, cause and effect relationship between RDW and outcomes cannot be established. Third, we do not have data regarding bleeding events in our cohort. A caveat of this study is that we do not have data on the levels of folic acid, vitamin B12, and iron, nor on the reticulocyte count, erythropoietin levels, measures of hemolysis, or detailed liver function test results, all of which might affect RDW values. Those variables had been investigated among our patients only when there were clinical indications to do so. Therefore, the potential for subclinical deficiencies in each of these variables cannot be ruled out, although the mean corpuscular volume of our subjects was within the normal range (85), making significant deficiencies unlikely.

5 Conclusions

Elevated RDW is associated with increased risk of METS and long term mortality in patients undergoing coronary angiography. Patients with METS demonstrate abnormal metabolic and inflammatory biomarkers regardless of their clinical presentation.

Conflict of interest

None on the part of any author.

Financial disclosure

None.

Funding/support

None.

References

Anichkov

D.A.

, Maksina

A.G.

and Shostak

N.A.

, Relationships between erythrocyte membrane properties and components of metabolic syndrome in women, Med Sci Monit 11(4) (2005), CR203–CR210.

Arbel

, et al., Admission glucose: Fasting glucose, HbA1c levels and the SYNTAX score in non-diabetic patients undergoing coronary angiography, Clin Res Cardiol 103(3) (2014), 223–227.

Arbel

, et al., Comparison of values of wide-range C-reactive protein to high-sensitivity C-reactive protein in patients undergoing coronary angiography, Am J Cardiol 99(11) (2007), 1504–1506.

Arbel

, et al., Erythrocyte aggregation as a cause of slow flow in patients of acute coronary syndromes, Int J Cardiol 154(3) (2012), 322–327.

Arbel

, et al., Hyperglycemia in patients referred for cardiac catheterization is associated with preexisting diabetes rather than a stress-related phenomenon: A prospective cross-sectional study, Clin Cardiol 37(8) (2014), 479–484.

Arbel

, et al., Impact of estimated glomerular filtration rate on vascular disease extent and adverse cardiovascular events in patients without chronic kidney disease, Can J Cardiol 29(11) (2013), 1374–1381.

Arbel

, et al., Inverse correlation between coronary and retinal blood flows in patients with normal coronary arteries and slow coronary blood flow, Atherosclerosis 232(1) (2014), 149–154.

Arbel

, et al., Lack of correlation between coronary blood flow and carotid intima media thickness, Clin Hemorheol Microcirc 56(4) (2014), 371–381.

Arbel

, et al., Red blood cell distribution width (RDW) and long-term survival in patients with ST elevation myocardial infarction, Thromb Res 134(5) (2014), 976–979.

10.

Arbel

, et al., Red blood cell distribution width and 3-year outcome in patients undergoing cardiac catheterization, J Thromb Thrombolysis 37(4) (2014), 469–474.

11.

Arbel

, et al., Red blood cell distribution width and the risk of cardiovascular morbidity and all-cause mortality. A population-based study, Thromb Haemost 111(2) (2014), 300–307.

12.

Arbel

, et al., Relation of metabolic syndrome with long-term mortality in acute and stable coronary disease, Am J Cardiol 115(3) (2015), 283–287.

13.

Assmann

, et al., Harmonizing the definition of the metabolic syndrome: Comparison of the criteria of the Adult Treatment Panel III and the International Diabetes Federation in United States American and European populations, Am J Cardiol 99(4) (2007), 541–548.

14.

Beltran-Sanchez

, et al., Prevalence and trends of metabolic syndrome in the adult U.S. population: 1999–2010, J Am Coll Cardiol 62(8) (2013), 697–703.

15.

Borne

, et al., Red cell distribution width and risk for first hospitalization due to heart failure: A population-based cohort study, Eur J Heart Fail 13(12), 1355–1361.

16.

Breiman

, F.J. , Olsen

R.A.

and Stone

C.J.

, Classification and regression trees. Belmont, CA: Wadsworth International Group, 1984, pp. 203–215.

17.

Cameron

A.J.

, Shaw

J.E.

and Zimmet

P.Z.

, The metabolic syndrome: Prevalence in worldwide populations, Endocrinol Metab Clin North Am 33(2) (2004), 351–375. table of contents.

18.

Cavusoglu

, et al., Relation between red blood cell distribution width (RDW) and all-cause mortality at two years in an unselected population referred for coronary angiography, Int J Cardiol 141(2), 141–146.

19.

Chen

P.C.

, et al., Red blood cell distribution width and risk of cardiovascular events and mortality in a community cohort in Taiwan, Am J Epidemiol 171(2), 214–220.

20.

Dabbah

, et al., Relation between red cell distribution width and clinical outcomes after acute myocardial infarctionm, Am J Cardiol 105(3), 312–317.

21.

Esposito

, et al., Metabolic syndrome and risk of cancer: A systematic review and meta-analysis, Diabetes Care 35(11), 2402–2411.

22.

Felker

G.M.

, et al., Red cell distribution width as a novel prognostic marker in heart failure: Data from the CHARM Program and the Duke Databank, J Am Coll Cardiol 50(1) (2007), 40–47.

23.

Forhecz

, et al., Red cell distribution width in heart failure: Prediction of clinical events and relationship with markers of ineffective erythropoiesis, inflammation, renal function, and nutritional state, Am Heart J 158(4) (2009), 659–666.

24.

Ghanassia

, et al., Limited predictive value of the IDF definition of metabolic syndrome for the diagnosis of insulin resistance measured with the oral minimal model, Ann Biol Clin (Paris) 67(5) (2009), 535–542.

25.

Hoffmann

, et al., Impact of the metabolic syndrome on angiographic and clinical events after coronary intervention using bare-metal or sirolimus-eluting stents, Am J Cardiol 100(9) (2007), 1347–1352.

26.

Katzmarzyk

P.T.

, et al., Metabolic syndrome, obesity, and mortality: Impact of cardiorespiratory fitness, Diabetes Care 28(2) (2005), 391–397.

27.

Lee

W.S.

and Kim

T.Y.

, Relation between red blood cell distribution width and inflammatory biomarkers in rheumatoid arthritis, Arch Pathol Lab Med 134(4) (2010), 505–506.

28.

Lewis

S.J.

, et al., Self-reported prevalence and awareness of metabolic syndrome: Findings from SHIELD, Int J Clin Pract 62(8) (2008), 1168–1176.

29.

Marso

S.P.

, et al., Plaque composition and clinical outcomes in acute coronary syndrome patients with metabolic syndrome or diabetes,, JACC Cardiovasc Imaging 5(3 Suppl), S42–S52.

30.

Patel

K.V.

, et al., Red blood cell distribution width and the risk of death in middle-aged and older adults, Arch Intern Med 169(5) (2009), 515–523.

31.

Perlstein

T.S.

, et al., Red blood cell distribution width and mortality risk in a community-based prospective cohort, Arch Intern Med 169(6) (2009), 588–594.

32.

Pierce

C.N.

and Larson

D.F.

, Inflammatory cytokine inhibition of erythropoiesis in patients implanted with a mechanical circulatory assist device, Perfusion 20(2) (2005), 83–90.

33.

Reaven

, Why a cluster is truly a cluster: Insulin resistance and cardiovascular disease, Clin Chem 54(5) (2008), 785–787.

34.

Reaven

G.M.

, The metabolic syndrome: Is this diagnosis necessary? Am J Clin Nutr 83(6) (2006), 1237–1247.

35.

Sanchez-Chaparro

M.A.

, et al., Higher red blood cell distribution width is associated with the metabolic syndrome: Results of the Ibermutuamur CArdiovascular RIsk assessment study, Diabetes Care 33(3) (2010), e40.

36.

Sanchez-Chaparro

M.A.

, et al., Higher red blood cell distribution width is associated with the metabolic syndrome: Results of the Ibermutuamur CArdiovascular RIsk assessment study, Diabetes Care 33(3), e40.

37.

Sangoi

M.B.

, et al., Relation between red blood cell distribution width and mortality after acute myocardial infarction, Int J Cardiol 146(2), 278–280.

38.

Sesso

H.D.

, et al., C-reactive protein and the risk of developing hypertension, JAMA 290(22) (2003), 2945–2951.

39.

Steinvil

, et al., Anemia and inflammation have an additive value in risk stratification of patients undergoing coronary interventions, J Cardiovasc Med (Hagerstown) 16(2) (2015), 106–111.

40.

Steinvil

, et al., Time to rheology in acute myocardial infarction: Inflammation and erythrocyte aggregation as a consequence and not necessarily as precursors of the disease, Clin Res Cardiol 99(10) (2010), 651–656.

41.

Tonelli

, et al., Relation between red blood cell distribution width and cardiovascular event rate in people with coronary disease, Circulation 117(2) (2008), 163–168.

42.

Uchida

, et al., Impact of metabolic syndrome on various aspects of microcirculation and major adverse cardiac events in patients with ST-segment elevation myocardial infarction, Circ J 76(8), 1972–1979.

43.

van Kimmenade

R.R.

, et al., Red blood cell distribution width and 1-year mortality in acute heart failure, Eur J Heart Fail 12(2), 129–136.

44.

Vaya

, et al., Association of erythrocyte deformability with red blood cell distribution width in metabolic diseases and thalassemia trait, Clin Hemorheol Microcirc (2014) (a head of print).

45.

Wiewiora

, et al., Association between hemorheological alteration and clinical diagnosis of metabolic syndrome among patients qualified for bariatric surgery, Clin Hemorheol Microcirc 56(2) (2014), 101–109.

46.

Zalawadiya

S.K.

, et al., Red cell distribution width and risk of coronary heart disease events, Am J Cardiol 106(7), 988–993.