Influence of age and gender on red blood cell distribution width.

Abstract

Keywords: agin gender g; ed ; r blood cell distribution width. Tothe Editor, We have read with interest the recently published article by Lippi et al. [1] in Clinical Chemistry and Laboratory Medicine about red blood cell distribution width (RDW) and its association with age and gender. RDW is an inex-pensive, easy to calculate parameter that reflects aniso-cytosis which, in recent years, has received growing attention [2] . High RDW has been found to be associated with multiple conditions, such as cardiovascular events [3, 4] or inflammatory diseases [5, 6] . In the paper by Lippi et al. [1] , a strong dependence of RDW upon age and gender is shown in a large popula-tion (n = 1907) of actual and former healthy blood donors. The authors presented evidence of an important associa-tion of increasing RDW with aging. More interestingly, they reported that the proportion of subjects with RDW higher than 14.6% (considered as a biomarker of morbid-ity and mortality in general population [7] ) increased from 6% in < 41 years up to 75% in those older than 90 years [1] . These findings could carry important implications in clinical practice and research dealing with RDW and its association with several conditions, as age (and gender) should be considered an important confounding factor. However, the data reported by Lippi et al. [1] should be carefully evaluated since their sample, although free of diseases, is composed of blood donors in whom habitual marrow stimulation could have an effect on RDW values. This could lead to overestimating the effect of aging on RDW. To further clarify this issue, we have retrospectively analyzed data retrieved from 809 healthy subjects (380 males/429 females) belonging to the La Fe University Hospital staff at the Preventive Medicine Service between 2008 and 2013 to investigate the association of RDW with age and gender. The subjects were explored for diseases and a routine biochemical panel was performed to further discard subjacent conditions. Exclusion criteria included organic (hepatic, cardiac, liver or renal disease), malig-nant, hematological, infectious or inflammatory disease, previous history of ischemic heart disease or stroke, previ-ous thromboembolism, treatment with rheological drugs and secondary obesity (hypothyroidism, Cushing syn-drome) and anemia. Mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), hemoglobin and RDW were deter-mined with the hematological autoanalyzer Sysmex XE-2100 (Kobe, Japan). The normality of distributions was analyzed using the Kolgomorov-Smirnov test. The Kruskal-Wallis test with Dunn ’ s comparisons was used to compare the median values of RDW between age groups ( < 20, 20 – 29, 30 – 39, 40 – 4, 950 – 5, 960 – 6, 9 ≥ 0). 7The Mann-Whitney test was used to compare median values between genders in each age group. In addition, the proportion of subjects with RDW higher than 14.6% among age groups was compared using the χ 2 est -t . The association between variables was explored by means of Spearman ’ s correlation coefficient ( ρ ) and multivariate regression analysis, being RDW the dependent variable and hemoglobin, MCV, MCH, gender and age independ-ent variables [adjusted β coefficients ( β *) have been reported]. Statistical analyses were performed using the SPSS (IBM Corporation, Armonk, NY, USA) and Graphpad