Association of red blood cell distribution width (RDW) with mortality in the Third National Health and Nutrition Examination Survey (NHANES III). Rates of all-cause, cardiovascular, cancer, and chronic lower respiratory tract disease deaths increased significantly across quintiles (Ptrend < .05 for all), whereas the rate of external-cause deaths (eg, due to accident or intent) did not (Ptrend = .94).
Association of red blood cell distribution width (RDW) with inflammation in the Third National Health and Nutrition Examination Survey. The age-standardized prevalence of a C-reactive protein (CRP) level greater than 3.0 mg/L (to convert to nanomoles per liter, multiply by 9.524) increased significantly across quintiles of RDW (Ptrend < .001). Error bars represent SE.
Perlstein TS, Weuve J, Pfeffer MA, Beckman JA. Red Blood Cell Distribution Width and Mortality Risk in a Community-Based Prospective Cohort. Arch Intern Med. 2009;169(6):588–594. doi:10.1001/archinternmed.2009.55
Red blood cell distribution width (RDW), an automated measure of red blood cell size heterogeneity (eg, anisocytosis) that is largely overlooked, is a newly recognized risk marker in patients with established cardiovascular disease (CVD). It is unknown whether RDW is associated with mortality in the general population or whether this association is specific to CVD.
We examined the association of RDW with all-cause mortality and with CVD, cancer, and chronic lower respiratory tract disease mortality in 15 852 adult participants in the Third National Health and Nutrition Examination Survey (1988-1994), a nationally representative sample of the US population. Mortality status was obtained by matching to the National Death Index, with follow-up through December 31, 2000.
Estimated mortality rates increased 5-fold from the lowest to the highest quintile of RDW after accounting for age and 2-fold after multivariable adjustment (Ptrend < .001 for each). A 1–SD increment in RDW (0.98%) was associated with a 23% greater risk of all-cause mortality (hazard ratio [HR], 1.23; 95% confidence interval [CI], 1.18-1.28) after multivariable adjustment. The RDW was also associated with risk of death due to CVD (HR, 1.22; 95% CI, 1.14-1.31), cancer (1.28; 1.21-1.36), and chronic lower respiratory tract disease (1.32; 1.17-1.49).
Higher RDW is associated with increased mortality risk in this large, community-based sample, an association not specific to CVD. Study of anisocytosis may, therefore, yield novel pathophysiologic insights, and measurement of RDW may contribute to risk assessment.
Red blood cell distribution width (RDW) is an automated measure of the heterogeneity of red blood cell sizes (eg, anisocytosis) and is routinely performed as part of a complete blood cell count.1- 3 The RDW is used in the differential diagnosis of anemia, but otherwise has received little attention. In a recent exploratory analysis of a large contemporary clinical heart failure trial (the CHARM [Candesartan in Heart Failure: Assessment of Reduction in Mortality and Morbidity] Program),4 higher RDW was found to be a strong and independent predictor of increased risk of mortality and adverse cardiovascular (CV) outcomes. The investigators confirmed these findings in a clinical database of patients who had undergone cardiac catheterization at Duke University Medical Center. A subsequent analysis of the Cholesterol and Recurrent Events trial,5 which included patients who had a previous myocardial infarction but no evidence of heart failure, reported that higher RDW strongly and independently predicted all-cause mortality and adverse CV outcomes. Thus, higher RDW was associated with an adverse prognosis in 3 separate cohorts of patients with established CV disease (CVD). Whether this association is present in the general population and whether the association of RDW with mortality risk is specific to CVD have not been examined.
The National Health and Nutrition Examination Survey (NHANES) is a nationally representative examination of the US population. The NHANES III has been linked to the National Death Index, allowing prospective examination of mortality risk. We used this publicly available resource to examine whether RDW is associated with mortality risk in the general population. Based on the previously described findings,4,5 we were interested in the association of RDW with all-cause and CV mortality. In addition, there have been cross-sectional associations of RDW with chronic lung disease and cancer,6,7 although no prospective data are available for these outcomes. We, therefore, also examined the association of RDW with death due to lung disease and cancer to explore whether an observed association of RDW with mortality is specific to CVD. Herein, we present our findings of the association of RDW with risk of all-cause, CV, cancer, and chronic lower respiratory tract disease mortality in the NHANES III.
The NHANES is designed to assess the health and nutritional status of adults and children in the United States. The NHANES III was conducted from 1988 to 1994. A stratified, multistage sample design was used to produce a nationally representative sample of the noninstitutionalized US civilian population. The survey included questionnaires, a physical examination, and laboratory tests. Detailed documentation of the NHANES III procedures is available elsewhere.8 The NHANES was approved by the National Center for Health Statistics institutional review board, and all the participants gave informed consent.
Participants reported their attained educational level as the highest grade or year of school completed. Self-reported race/ethnicity was classified in the NHANES III as non-Hispanic white, non-Hispanic black, Mexican American, or other. Physical activity was defined by self-reported activity level relative to peers of similar age (less, same, or more). Smoking status was defined as current, former, or never; pack-years of smoking was also calculated. Participants reported their alcohol intake in terms of the number of days of alcohol consumption during the previous 12 months and the average number of drinks consumed on these days; from this, we derived an average number of drinks per week.
The RDW, hemoglobin level, and mean corpuscular volume were determined using the Coulter Counter Model S-PLUS JR (Beckman Coulter, Inc.; Hialeah, Florida), with Coulter histogram differential count as part of a complete blood cell count.9 The reference range for RDW was 11.8% to 14.8%. A central laboratory reviewed hematology data for accuracy and completeness.10 Serum creatinine, albumin, and iron levels were measured using a multichannel analyzer (Roche Hitachi 737; Boehringer Mannheim Diagnostics, Indianapolis, Indiana). Serum folate and vitamin B12 levels were measured using a radioassay kit (Quantaphase Folate; Bio-Rad Laboratories, Hercules, California). Serum total and high-density lipoprotein cholesterol levels were measured using the Hitachi 704 Analyzer (Boehringer Mannheim Diagnostics). C-reactive protein (CRP) concentration was quantified by latex-enhanced nephelometry using a modification of the Behring latex-enhanced CRP assay on the Behring Nephelometer Analyzer System (Siemans Healthcare Diagnostics; Deerfield, Illinois); the lower limit of detection was 3.0 mg/L (to convert to nanomoles per liter, multiply by 9.524). Detailed information regarding laboratory procedures is available elsewhere.9,10
We defined CVD as self-report of a physician diagnosis of myocardial infarction, heart failure, or stroke; cancer as self-report of a diagnosis of nonskin cancer; and lung disease as self-report of a diagnosis of asthma, chronic bronchitis, or emphysema. A diagnosis of hypertension was assigned if the individual reported a physician diagnosis of hypertension or taking prescription medications for hypertension or, on examination, if systolic blood pressure was 140 mm Hg or greater or diastolic blood pressure was 90 mm Hg or greater. A diagnosis of hypercholesterolemia was assigned if the participant reported a physician diagnosis of hypercholesterolemia or taking prescription medications for hypercholesterolemia or if the total cholesterol level was 240 mg/dL or greater (to convert to millimoles per liter, multiply by 0.0259). A diagnosis of diabetes mellitus was assigned if the patient reported a physician diagnosis of diabetes mellitus or taking prescription medications (insulin or oral agents) for diabetes mellitus, if the nonfasting plasma glucose level was 200 mg/dL or greater (to convert to millimoles per liter, multiply by 0.0555), or if the fasting plasma glucose level was 126 mg/dL or greater. The estimated glomerular filtration rate was determined from serum creatinine using the Modification of Diet in Renal Disease Study equation, and chronic kidney disease was defined as an estimated glomerular filtration rate of less than 60 mL/min.11,12 Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared and was categorized as normal weight (BMI of <25), overweight (BMI of 25.0-29.9), or obese (BMI of ≥30). We defined anemia as a hemoglobin level of less than 13.9 g/dL (to convert to grams per liter, multiply by 10.0) in men and less than 12.0 g/dL in women.
The National Death Index is a central computerized database of all certified deaths in the United States since 1979. Probabilistic matching based on 12 identifiers for each participant (eg, Social Security Number and name) was used to link NHANES III and National Death Index records. Mortality follow-up occurred through December 31, 2000. A calibration study13 applying identical matching methods to the NHANES I Follow-up Survey found an overall correct classification of vital status of 98.5%.
The International Classification of Diseases, Ninth Revision (ICD-9),14 was used to classify deaths that occurred through 1998; otherwise, the ICD-1014 was used. Cause-specific mortality was categorized as CVD (ICD-9 codes 390-448; ICD-10 codes I00-I99), malignant neoplasm (ie, cancer) (ICD-9 codes 140-208; ICD-10 codes C00-C97), and chronic lower respiratory tract disease (ICD-9 codes 490-496; ICD-10 codes J40-J47). External-cause deaths (eg, accidental and violence related) were classified as ICD-9 codes E800 to E999 or ICD-10 codes U01 to U03 and V01 to Y89.
There were 18 512 nonpregnant participants 20 years and older with mortality follow-up. Of these, 15 852 participants had RDW measurements and are included in this analysis.
The NHANES uses a multistage probability sampling design to select participants representative of the civilian, noninstitutionalized US population.15 All the analyses account for the sampling design and use sample weights; these account for unequal probabilities of selection and include adjustments for noncoverage and nonresponse. For age-standardized results, we used the 1990 US census population as the reference standard (age groups: 20-29, 30-39, 40-49, 50-59, 60-69, and >69 years). We used SAS-callable (version 9.1; SAS Institute Inc, Cary, North Carolina) SUDAAN (version 9.01; Research Triangle Institute, Research Triangle Park, North Carolina).
The primary outcome was all-cause mortality. Secondary outcomes were death due to CVD, cancer, and chronic lower respiratory tract disease. We used Cox proportional hazards models to estimate the relative risk of mortality corresponding to a 1–SD increment in RDW (0.98%).16 We did not find evidence of important deviations from linearity in the association between RDW and mortality risk. The association of RDW with mortality was also estimated across quintiles of RDW. We used time in the study as the time scale for analysis, calculated as the time from the NHANES procedure to death or December 31, 2000, whichever occurred earlier. We repeated the analyses using age as the time scale for analysis and obtained nearly identical results, which is expected for an outcome such as death, whose baseline hazard varies exponentially with age.17 Neither RDW nor any covariate violated the proportional hazards assumption, tested by including time-dependent covariates in the models. Relative risks are expressed as hazard ratios (HRs) with 95% confidence intervals (CIs). For cause-specific analyses, we censored participants at the time of death from causes other than the cause of interest.
We first fit a model (model 1) adjusting for the demographic factors of age (continuous, in years), sex, and race/ethnicity (non-Hispanic white, non-Hispanic black, Mexican American, and other) to describe the association of RDW with mortality risk. We noted that RDW was associated with behavioral and other potential mortality risk factors; we, therefore, constructed additional models to explore to what extent RDW might be associated with mortality risk after accounting for commonly considered risk factors. The first of these models (model 2) additionally adjusted for the behavioral and social factors of physical activity level, educational level (continuous), smoking (smoking status and pack-years), and BMI and was used to model the outcomes of cancer and respiratory tract mortality. The second of these models (model 3) additionally adjusted for the CV risk factors of systolic blood pressure, hypertension, hemoglobin A1c level, diabetes mellitus, total to high-density lipoprotein cholesterol ratio, hypercholesterolemia, estimated glomerular filtration rate, and chronic kidney disease and was used to model all-cause and CV mortality. In adjusting for these CV risk factors, we included continuous variables (eg, systolic blood pressure) to minimize residual confounding and categorical variables (eg, use of antihypertensive medication) to use information obtained in the medical history.
We also performed analyses of all-cause mortality stratified by age (<50 vs ≥50 years), sex, race/ethnicity, smoking status, diabetes mellitus, anemia, and chronic kidney disease. We excluded the category of “other” from the analyses of race/ethnicity due to the small size and heterogeneous nature of this group. For each of these stratified analyses, we formally tested variation in the association of RDW with mortality across the subgroup levels by fitting models containing cross-products between the subgroup levels and RDW. We also fit models adjusting for hemoglobin level and for iron, folate, and vitamin B12 levels to address whether the association of RDW with mortality risk might be due to confounding by anemia or anemia-related nutrient deficiencies, respectively. A change in the estimated regression coefficient for RDW greater than 20% was considered evidence of significant confounding.
Hypothesis testing was 2-tailed, with P < .05 considered statistically significant. To reduce the impact of chance findings in the multiple6 exploratory interaction analyses, we considered P < .007 (.05 ÷ 7) statistically significant.
The demographic and lifestyle factors of older age, non-Hispanic black race/ethnicity, lower educational level, less physical activity relative to peers, BMI, and active smoking were associated with higher RDW (Table 1). The CV risk factors of hypertension, hypercholesterolemia, and chronic kidney disease were also associated with higher RDW, as was prevalent CVD. Lung disease was more common in those with higher RDW, whereas a diagnosis of cancer was not associated with RDW. Hemoglobin, mean corpuscular volume, serum folate, and iron levels were inversely associated with RDW, whereas vitamin B12 level was not associated with RDW.
There were 2629 deaths in the 15 852 participants during a mean of 8.7 years of follow-up. Age-standardized mortality rates progressively rose with increasing RDW quintile, and the highest quintile of RDW, compared with the lowest, was associated with a greater than 5-fold increased risk of death (Figure 1). After adjustment for age, sex, and race/ethnicity, a 1-SD increment in RDW was associated with a 27% increased risk (HR, 1.27; 95% CI, 1.21-1.33) of all-cause mortality (Table 2). Additional adjustment for demographic and lifestyle factors partially attenuated this estimate (HR, 1.24; 95% CI, 1.19-1.30), and further adjustment for CV risk factors did not. Examining this relationship by RDW quintile revealed that the highest quintile of RDW, compared with the lowest, was significantly associated with a doubling of the risk of all-cause mortality after full multivariable adjustment (Table 3). Exclusion of individuals with RDW levels outside of the reference range did not attenuate the association of RDW with mortality risk (model 3, remaining n = 13 080; HR, 1.34; 95% CI, 1.17-1.53).
Age-standardized CV death rates significantly increased across RDW quintiles (P < .001) (Figure 1). There were 1220 deaths attributed to CVD. A 1-SD increment in RDW was significantly associated with 22% increased risk (Table 2), and the highest quintile of RDW, compared with the lowest, was significantly associated with 134% increased risk of CV mortality after multivariable adjustment (Table 3). Excluding participants with CVD at baseline (n = 1218) did not change this result (model 3: HR, 1.23, 95% CI, 1.12-1.33).
There were 564 deaths attributed to cancer. A 1-SD increment in RDW was significantly associated with a 28% increased risk (Table 2), and the highest quintile of RDW, compared with the lowest, was significantly associated with an 88% increased risk of death due to cancer after multivariable adjustment (Table 3). Excluding participants with cancer at baseline (n = 602) partially attenuated this result (model 2: HR, 1.23; 95% CI, 1.14-1.33).
There were 115 deaths attributed to chronic lower respiratory tract disease. A 1-SD increment in RDW was associated with a 32% increased risk (Table 2), and the highest quintile of RDW, compared with the lowest, was associated with a 5.9-fold increased risk of death due to chronic lower respiratory tract disease after multivariable adjustment (Table 3). Excluding participants with lung disease at baseline (n = 2004) did not change the result (model 2: HR, 1.31; 95% CI, 1.19-1.45).
There were 114 deaths attributed to external causes; RDW was not associated with an external cause of death (Figure 1 and Table 3).
We performed stratified analyses to examine the consistency of the association of RDW with mortality risk in several subgroups of interest (Table 4). The association of RDW with all-cause mortality risk was consistent in subgroups defined by age, sex, smoking status, diabetes mellitus, anemia, and chronic kidney disease (Pinteraction > .007 for all).
We found no evidence that the association between RDW and all-cause mortality risk was substantially changed by further adjustment for hemoglobin, mean corpuscular volume, iron folate, or vitamin B12 levels in participants who had these data available (n = 7536). Additional adjustment for serum albumin level or alcohol intake also did not change the results.
We hypothesized that the association of RDW with mortality risk may, in part, be due to the promotion of anisocytosis and chronic disease by inflammation. We, therefore, examined the association of RDW with CRP level, a marker of inflammation. The age-standardized prevalence of a high CRP level (>3.0 mg/L) increased 2.7-fold from the lowest to the highest RDW quintile (Figure 2). Fitting a model in which we regressed RDW on all the covariates in model 3, and on CRP level, revealed an independent association between CRP concentration and RDW (P < .001). Furthermore, elevated CRP level was associated with a 45% increased mortality risk (model 1: HR, 1.45; 95% CI, 1.30-1.62), an association that was attenuated somewhat by additional adjustment for RDW (1.34; 1.20-1.50). Finally, there was no apparent difference in the risk estimates for RDW in individuals with elevated CRP levels (1.23; 1.16-1.30) compared with those with low CRP levels (1.20; 1.13-1.27), which suggested that the association of RDW with mortality did not depend on the presence of inflammation.
The principal finding of this examination of 15 852 community-dwelling adults is that greater red blood cell size heterogeneity, as reflected by higher RDW, is strongly associated with risk of all-cause mortality. In addition, we found that higher RDW predicted CV, cancer, and chronic lower respiratory tract disease mortality. These results did not seem to be confounded by anemia or anemia-related nutrient deficiencies. Also, the association of RDW with mortality risk was observed across the entire range of RDWs and was not driven by RDWs outside the reference range because excluding individuals with an abnormal RDW did not attenuate the association of RDW with mortality risk.
The magnitude of risk associated with higher RDW that we observed is similar to that observed in previous examinations of patients with preexisting CVD.4,5 On average, a 1-SD increment in RDW was associated with a relative risk of all-cause mortality of 1.2, and the highest quintile of RDW and the highest quartile in the Cholesterol and Recurrent Events trial were associated with an approximately 2-fold increased mortality risk.
This examination of the relation of RDW to cancer and lung disease mortality was prompted by reports of corresponding cross-sectional associations, but no prospective data for these outcomes have been reported. Grant and colleagues7 found that RDW was inversely associated with lung function in a community-based sample. Ozkalemkas et al6 and Seitanides et al18 found that elevated RDW was associated with bone marrow involvement in cancer, and Spell and colleagues19 observed that elevated RDW was common in colon cancer. The present findings suggest that the relevance of higher RDW to mortality risk is not specific to a single organ system or process.
The biological mechanisms underlying the association of higher RDW with mortality risk is unclear. It seems unlikely that anisocytosis itself is a causal factor in risk, but we cannot eliminate this possibility. Increased anisocytosis is most commonly thought of as a consequence of anemia or anemia-related nutrient deficiency. We did not find that the association of RDW with mortality risk depends on these factors. Inflammation may alter erythropoiesis, red blood cell circulation half-life, and red blood cell membrane deformability, factors that might increase anisocytosis.20 Anemia of chronic disease is, in fact, characterized by increased RDW, independent of iron status.21 We hypothesized that the association of RDW with mortality risk may be due to underlying inflammation because inflammation is increasingly appreciated to contribute to the pathogenesis of chronic disease.22- 24 The present data support an association of anisocytosis with inflammation and suggest that the association of RDW with mortality risk may, in part, be due to an effect of inflammation on anisocytosis and risk. We did not find that the association of RDW with mortality risk entirely depends on inflammation because the risk associated with RDW was not significantly diminished in participants with a low CRP level compared with those with a high CRP level. It is also important to note that this data set cannot determine the temporal association of anisocytosis with inflammation.
Because RDW is widely available at no additional cost to the routinely performed complete blood cell count and is highly reproducible, it may serve as an important biomarker.25 The strength of RDW's association with mortality risk that we and others have observed compares favorably with established risk factors. It is unknown, however, if the risk associated with RDW is modifiable or if RDW itself is modified by current therapies that alter prognosis.
The NHANES sample is designed to represent the noninstitutionalized US population. The comprehensive examination allowed adjustment for many important covariates. The number of events provides stable estimates of risk associated with RDW. These strengths, along with a focused analysis based on previous work from more restricted populations, make it less likely that the present consistent results are spurious.
A few limitations warrant consideration. It may be that serial measurements of RDW would allow better characterization of the association of RDW with risk, and these data do not address RDW's relation to incident nonfatal disease. The association of RDW with mortality risk may, in part, be due to its association with prevalent disease. We did not find that excluding participants with diagnosed CVD, cancer, or lung disease affected the association of RDW with the respective disease-specific mortality risk; however, an association of RDW with occult disease may, in part, be responsible for these findings. Perhaps the most important limitation is the uncertainty of the biologic underpinning for greater RDW and its association with risk. We hope that these results provide a stimulus for investigations into mechanisms underlying anisocytosis.
In summary, we made the novel observation that higher RDW is strongly and independently associated with risk of all-cause and CV, cancer, and chronic lower respiratory tract disease mortality in a community-based sample. These results suggest that study of anisocytosis may yield important pathophysiologic insights and that RDW may contribute to the identification of individuals at higher risk.
Correspondence: Todd S. Perlstein, MD, MMSc, Cardiovascular Division, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, 75 Francis St, Boston, MA 02115 (firstname.lastname@example.org).
Accepted for Publication: October 16, 2008.
Author Contributions: Dr Perlstein had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Perlstein, Pfeffer, and Beckman. Acquisition of data: Perlstein and Beckman. Analysis and interpretation of data: Perlstein, Weuve, Pfeffer, and Beckman. Drafting of the manuscript: Perlstein. Critical revision of the manuscript for important intellectual content: Weuve, Pfeffer, and Beckman. Statistical analysis: Weuve. Obtained funding: Beckman. Administrative, technical, and material support: Beckman. Study supervision: Pfeffer and Beckman.
Financial Disclosure: None reported.
Funding/Support: This study was supported by training grant T32 HL07604 from the National Heart, Lung, and Blood Institute and an American College of Cardiology Foundation/Merck Research Fellowship Award (Dr Perlstein); by grant ES R01-ES05257 from the National Institutes of Health and contract 045821 from the Robert Wood Johnson Foundation (Dr Weuve); and by Career Development Award 1-06-CD-01 from the American Diabetes Association (Dr Beckman).