Diversity & Equality in Health and Care Open Access

Reference Intervals of Complete Blood Count in Healthy Adult Eritreans

Ahmed O Noury^1*, Omer A. Musa², Elmuiz Gasmalbari³, Barakat M Bakhit¹, Eyasu H Tesfamariam⁴, Danie Abraha⁵, Zekarias B Ghebre⁶, Omer Suleman⁷, Efrem G Tesfay⁸ and Filmon G Hailezghi^{9 1}Department of Physiology, Orotta College of Medicine and Health Sciences, Eritrea
²Department of Physiology, National Ribat Uinversity, Sudan
³Department of Biochemistry, Omdurman Islamic University, Sudan
⁴Department of Statistics, Eritrean Institute of Technology, Eritrea
⁵Department of Hematology, National Health Laboratory of Eritrea, Eritrea
⁶Department of Laboratory Technologist, Air Force Hospital, Eritrea
⁷Department of Hematology, Keren Hospital, Eritrea
⁸Department of Food Quality Control, Laboratory of Eritrea, Eritrea
⁹Zonal Laboratory Coordinator and Head of Massawa Hospital Laboratory, Eritrea
^*Correspondence: Ahmed O Noury, Department of Physiology, Orotta College of Medicine and Health Sciences, Eritrea, Email:

Received: 31-May-2023, Manuscript No. ipdehc-23-16740; Editor assigned: 02-Jun-2023, Pre QC No. ipdehc-23-16740; Reviewed: 16-Jun-2023, QC No. ipdehc-23-16740; Revised: 21-Jun-2023, Manuscript No. ipdehc-23-16740; Published: 28-Jun-2023, DOI: 10.21767/2049-5471.20.03.23

Introduction

Complete Blood Count (CBC) is the most frequently used laboratory investigation in health care. The most important aspect of laboratory test interpretation is the concept of reference interval (RI), where test values that fall inside the range are considered normal and those occurring outside the range are considered abnormal [1]. Population-based RI, which first came into use in human medicine in 1969, is the range of values that 95% of a healthy population fell within [2]. The reference ranges universally used are mostly from studies conducted in Western countries. However, these reference intervals differ based on many socio-demographic characteristics. Several factors such as age, gender, dietary patterns, ethnic differences and altitude affect the reference ranges for different groups and the Western RI may not be applicable in most regional settings [3]. The Clinical and Laboratory Standards Institute (CLSI) recommended each country should establish its organic standards to avoid misinterpretation of blood count results [4]. The objective of this study is to determine the Hematological reference intervals in healthy adult Eritreans.

Materials and Methods

Study Design

This is descriptive and cross-sectional.

Study Site

The study was conducted on Eritreans from all over the country in the period from 2019 up to 2022. Samples used in this study were collected from the following sites in Eretria:

• Central region (Asmara)

• Anseba region (Keren)

• Southern region (Mendefera) and

• Northern Red Sea region (Massawa)

Volunteer Recruitment

The areas from which participants were drawn were chosen using a multistage sampling technique (Stratified sample). The zone was the first-stage sampling unit. Out of several zones in the city, we chose one at random. The second stage involved a random sub-zone selection. We chose one of the zone's subzones at random. The third stage was the random selection of sub-zone blocks. We chose four blocks at random from the sub-zone. The fourth stage involved systematically selecting households from a randomly selected reference point. After identifying a household, we contacted the zone administrators and requested that one employer be assigned to educate the population of the intended blocks about the study's objectives. Recruitment was stratified into 4 age groups: 18-29, 30-39, 40-49, and 50-60 years. Before drawing blood, we obtained written informed consent from all participants. The team used a questionnaire to collect anthropometric measurements, demographic data, medical status, medical history, physical activity, and sleeping hours from each blood donor. Blood pressure and BMI measurements were taken for all participants.

Reference Population

This cross-sectional study included 942 healthy adult Eritreans from various social, ethnic, and professional groups. The Clinical and Laboratory Standards Institute guidelines were used to select participants for this study. Our reference sample included 331 men with an average age of 40 and 611 women with an average age of 41; the study lasted from November 2019 to January 2022.

Ethical Clearance

The Eritrean Ministry of Health's ethics committee granted ethical approval for this study.

Blood Collection

An early morning visit was from 8 AM to 12 AM. Blood samples were collected by a trained phlebotomist, blood drawn by venipuncture 2 ml of venous blood was collected into tetra-acetic acid (EDTA) vacutainer tubes for a complete blood count. Blood samples were transported to the laboratory, where all the analyses were conducted at the Hematology Department within 5 hours of blood extraction.

Statistical Analysis

Analysis was done in SPSS (Version 25) after a careful checkup on completeness, cleaning, and editing processes. Extreme values that might greatly affect the result within each gender were identified using the D/R ratio, where D is the absolute difference between an extreme observation (large or small) and the next largest (or smallest) observation, and R is the range (maximum-minimum). The identified extreme values were deleted if D/R ≥ 1/3 (4). Descriptive analysis of the demographic variables, stratified by gender, was performed using mean, median, standard deviation, frequencies, and percent, as appropriate. The Clinical Laboratory Standards Institute/International Federation for Clinical Chemistry (CLSI/IFCC) was employed to compute the reference intervals. As per the standard, a nonparametric method median (IQR), range (Minimum and maximum), combined and separate 95% RIs (2.5^th and 97.5^th percentiles), 95% CI for the lower limit of RI, and upper limit of RI were computed (using 1000 bootstrapped simple random sampling). Harris and Boyd test vis-à-vis Mann-Whitney U test, was performed to determine whether combined or separate RIs are needed [5,6]. However, results from Harris and Boyd were finally endorsed. Upon using Harris and Boyd, the statistical Z result was compared with a critical Z* value: Separate gender specific reference range are needed when Z>Z*.

To assess the relationship of the hematological parameters with the socio-demographic and basic background characteristics, the spearman rank correlation (for continuous variables), Mann-Whitney U test (categorical variables having dichotomous outcome), and Kruskal-Wallis test (categorical variables having more than two outcomes) were employed. Post-hoc analysis using the Bonferroni test was also performed for the results that were found to be significant using Kruskal-Wallis. Agreement between the currently estimated reference intervals and currently used RIs was performed using the Kappa statistic. Interpretation of the Kappa statistic was done using Landis and Koch classification [7].

Results

A total of 942 individuals volunteered to participate in our study and were included, including 331 males and 611 females. The percentages of male and female participants were 35.14% and 64.86% respectively. Combined and separate (male and female) descriptive characteristics, which include mean (SD), median (IQR), and range, of study participants for the four cities are displayed in Table 1. The combined mean age was 39.69 (± 12.38) years. The combined mean (SD) of height and weight were 1.62 (± 0.09) meters and 58.85 (12.23) kilograms, respectively. The combined mean body mass index was also 22.49 (± 4.56) kg/m2. Moreover, the combined mean (SD) values of SBP and DBP were 118.03 (16.32) and 76.32 (9.69) respectively. The mean sleeping hour (per day) of both males and females was 7.75 (0.86) hours. A detailed characterization of the study participants stratified by gender is given in Tables 1 and 2 (continuous variables and categorical variables).

Table 1: Socio-demographic and basic background characteristics of the study participants for continuous variables stratified by gender

Table 2: Socio-demographic and basic background characteristics of the study participants for categorical variables stratified by gender

Parameters that Demand Partitioned RI and their Distribution

As per the Harris and Boyd recommendation for the need in partitioning the reference interval by gender four hematological parameters, namely, Eosin, RBC, Hb, and HCT were essentially found to have separate RI (Table 3).

Table 3: Hematological parameters and need for partitioning of reference intervals by gender

To make comparisons with other studies, the reference intervals for all the parameters were computed separately (males and females) as well as the combined data.

Hematological Reference Intervals

Tables 4 and 5 shows the mean (SD), median (IQR), range (minimum to maximum), 95% reference range (2.5^th to 97.5^th percentile), 95% CI for the lower limit (2.5^th percentile), and 95% CI for the upper limit (97.5^th percentile).

As per the recommendation of Harris and Boyd, the combined median (2.5^th-97.5^th percentile) for both males and females of WBC, Lym, Mono, Neut, Baso, MCV, MCH, MCHC, RDW, RDW-SD, PLT and MPV were 6.37 (3.02 μL-13.55 μL × 103/μL), 39.34 (21.39%-60.54%), 8.98 (5.18%-14.54%), 49.13 (16.90%- 81.98%), 0.22 (0.00%-0.63%), 87.67 (76.58 fl-97.29 fl),27.53 (20.46 pg-32.70 pg), 31.38 (25.20 g/dl-35.30 g/dl), 14.65 (12.70%-18.60%), 41.58 (33.56-54.04), 286.83 (131.62 μL- 453.13 μL × 103/μL), and 8.92 (7.28 fL-11.01 fL) respectively.

The parameters that demand separate RI were Eosin, RBC, Hb, and HCT. Their respective median (2.5^th-97.5^th percentile) for males versus females were 3.86 (0.29%-16.68%) versus 1.80 (0.20%-6.73%), 5.57 (4.47 μL-7.69 μL × 106/μL) versus 4.97 (3.98 μL-6.38 μL × 106/μL), 15.28 (11.48 g/dl-17.99 g/dl) versus 13.50 (10.74 g/dl-16.54 g/dl), and 48.75 (38.96%-61.17%) versus 43.19 (34.86%-58.60%).

Table 4: Complete descriptive analysis of the hematological parameters along with the 95% reference range (2.5^th to 97.5^th percentile)

Table 5: Complete descriptive analysis of the hematological parameters along with the 95% reference range (2.5^th to 97.5^th percentile)

Correlation of the Hematological Parameters with the Continuous Background

The continuous background that found to have significant correlation with the hematological parameters is age, height, weight, BMI, SBP and DBP as shown in Table 6.

Table 6: Spearman's correlation of the hematological parameters with the continuous background

Discussion

The purpose of this study was to determine the hematological reference ranges of Eritrean healthy adults, identify factors that influence these values, and compare them to international and neighboring country values. In our study, Eritrean total white blood cell counts were similar to Caucasians, but we found an increased lymphocyte count and a decreased neutrophil count in comparison to Caucasians [8,9]. These findings are in contrast to the study carried out by Chen et al. who found that White subjects had a significantly higher WBC count in all age groups in comparison to black subjects [10]. Many African Americans have WBCs that are persistently below the normal range for people of European descent, a condition called benign ethnic Neutropenia. David et al. explained that neutropenia in Africans is due to a regulatory variant in the Duffy antigen receptor for the chemokines gene [11]. In our study, we found that Eritreans had higher hematocrit levels, higher hemoglobin levels, and higher RBCs than Caucasian and Africans. We hypothesized that the cause for this difference is likely due to altitude deference and Nutritional behavior; which is one of the factors affecting Hb and RBCs indices, Injera is the most important component of food in Eritrea. Teff is the main ingredient in injera, Teff is rich in carbohydrates, and fiber and has a complete set of essential amino acids. Teff is also particularly high in iron and has more calcium, copper, and zinc than other cereal grains in this regard, Alaunyte stated that The high Fe content of teff is reflected by the low prevalence of anemia in places where the teff grain is predominantly consumed [12,13].

The study made by Mohammed in pregnant Ethiopian women revealed that a decrease in the frequency of teff consumption was significantly associated with an increase in the likelihood of anemia [14]. We found significant gender effects on the CBC. Female participants had higher WBC, Lym, Baso, PLT, and MPV. while males had higher Mono, Eosin, RBC, HB, HCT, MCV, MCH, and MCHC The reasons for these differences have been attributed to factors such as the influence of the androgen hormone on erythropoiesis and decreased metabolic demand, decreased muscle mass, and lower iron stores due to menstruation in females, In this regard our findings are in agreement with previous studies [15-17].

In a recent study, Bachman et al. reported significantly increased erythropoietin levels and decreased ferritin and hepcidin with testosterone administration [18]. Interestingly, exogenous testosterone was used initially as a treatment for anemia. The American practice guideline on testosterone therapy recommends against the use of testosterone in patients with a hematocrit above 50%. In support of our findings of significantly increased Monocytes in males, many studies showed a decrease in the number of Monocytes when estrogen level is high [19-21]. A new study by Thiago et al. reveals testosterone administration in men increases Monocyte counts [22]. Our results agree with those from a recent study by Hartlet et al. found that Eosinophil is higher in males than in females in all age groups [23]. In this study, the mean WBCs, MPV, PLT, and Baso were significantly higher for women than men. Rukia in their study found that the women had higher white blood cell and platelet counts compared to men, which agrees with our findings [24]. Whereas Kaya have found significantly higher WBCs in men compared to females which are inconsistent with our findings [25]. The significant increase in platelet count and MPV in females might be due to the effect of estrogen on Megakaryopoiesis and platelet production according to previous research [26-28]. Our study also indicated that the variation among the data sets for Eosin, Baso, hemoglobin, RBC, and HCT of the four age groups was statistically significant. In the present study we found that with an increase in age, there is a significant increase in Baso. The present results are consistent with previous studies [29,30]. Other reports show no age-related changes in Basophile count [31]. The effects of aging on basophil must be explained by many mechanisms. First, aging increases basophil sensitivity to anti-IgE and IgE-mediated release ability of histamine [32]. Second, with aging, gut microbiota composition changes [33]. Basophil hematopoiesis and function are regulated by gut microbiota. The absence of gut microbiota leads to increased. Basophil frequencies however, with an increase in age, a significant decrease in RBC, HB, HCT, and PLT was observed [34]. Similar results have been reported by Isabel in their study MCV, MCH, and RDW showed a significant positive correlation with age, hemoglobin, hematocrit, RBC, and platelet count showed a significant negative correlation [35]. With the aging process the amount of growth hormone secreted declines, it is commonly believed that growth hormone stimulates erythropoiesis by increasing the oxygen consumption of tissues and thereby promoting tissue hypoxia, which in turn accelerates erythropoietin production by the kidneys [36]. Another hypothesis concerning the mechanisms that are responsible for the age-related changes of reduction may reflect a reduction in hematopoietic stem cell reserve during aging [37]. Therefore, there is a definite need to introduce age-specific reference ranges.

Author Contribution

Project administration, methodology review and editing were contributed by Ahmed O Noury, OA. Musa and Elmuiz. Data collection were contributed by Ahmed O Noury, Barakat, Daniel, Zekarias, Omer, Efrem and Filmon Data analysis and interpretation were contributed by Ahmed O Noury and Eyasu H Tesfamariam. Manuscript writing was contributed by Ahmed O Noury. Final approval of manuscript was contributed by all authors. All authors read and approved the final manuscript.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Availability of Data and Materials

Data supporting this study are included within the article.

Ethics Approval and Consent to Participate

The Eritrean Ministry of Health's ethics committee granted ethical approval for this study.

Consent for Publication

All authors have agreed to publish this manuscript.

Competing Interest

The authors declare no competing interests

References

1. Ridley J (2010) Essentials of clinical laboratory science. Nelson Education.
2. Boyd JC (2010) Defining laboratory reference intervals and decision limits: Populations, intervals, and interpretations. Asian J Androl. 12(1): 83-90

   [Crossref] [Google Scholar]

3. Iftikhar R, Khan NU, Iqbal Z, Kamran SM, Anwar MI, et al. (2017) Haematological parameters in different African populations: An experience from United Nations level 3 hospital. Pakistan Armed Forces Med J 67(6): 1068-1072.

   [Crossref] [Google Scholar]

4. Wayne P (2008) Defining, establishing and verifying reference intervals in the clinical laboratory: Approved guideline. Clin Lab Stand Inst 28(30): 28-30

   [Crossref] [Google Scholar]

5. Harris EK, Boyd JC (1990) On dividing reference data into subgroups to produce separate reference ranges. Clin Chem 36(2): 265-270.

   [Crossref] [Google Scholar]

6. Harris EK, Wong ET, Shaw ST (1991) Statistical criteria for separate reference intervals: Race and gender groups in creatine kinase. Clin Chem 37(9): 1580-1582.

   [Crossref] [Google Scholar]

7. Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 159-174.

   [Crossref] [Google Scholar]

8. Haddy TB, Rana SR, Castro O (1999) Benign ethnic neutropenia: What is a normal absolute neutrophil count? J Lab Clin Med 133(1): 15-22.

   [Crossref] [Google Scholar]

9. Nduka N, Aneke C, Owhochuku MS (1988) Comparison of some haematological indices of Africans and caucasians resident in the same Nigerian environment. Haematologia (Budap) 21(1): 57-63.

   [Crossref] [Google Scholar]

10. Chen W, Srinivasan SR, Xu J, Berenson GS (2010) Black-white divergence in the relation of white blood cell count to metabolic syndrome in preadolescents, adolescents, and young adults: The bogalusa heart study. Diabet Care 33(11): 2474-2476.

    [Crossref] [Google Scholar]

11. Reich D, Nalls MA, Kao WHL, Akylbekova EL, Tandon A, et al. (2009) Reduced neutrophil count in people of African descent is due to a regulatory variant in the Duffy antigen receptor for chemokines gene. PLoS Genet 5(1): e1000360.

    [Crossref] [Google Scholar]

12. Campo E, del Arco L, Urtasun L, Oria R, Mairal FA, et al. (2016) Impact of sourdough on sensory properties and consumers' preference of gluten-free breads enriched with teff flour. J Cereal Sci 67:75.
13. Alaunyte I, Stojceska V, Plunkett A, Derbyshire E (2014) Dietary iron intervention using a staple food product for improvement of iron status in female runners. J Int Soc Sports Nutr 11(1): 1-8.

    [Crossref] [Google Scholar]

14. Mohammed SH, Taye H, Sissay TA, Larijani B, Esmaillzadeh A, et al. (2019) Teff consumption and anemia in pregnant Ethiopian women: A case-control study. Eur J Nutr 58(5): 2011-2018.

    [Crossref] [Google Scholar]

15. Kibaya RS, Bautista CT, Sawe FK, Shaffer DN, Sateren WB, et al. (2008) Reference ranges for the clinical laboratory derived from a rural population reference ranges for the clinical laboratory derived from a rural population in Kericho, Kenya. PLoS One 3(10): e3327

    [Crossref] [Google Scholar]

16. Menard D, Mandeng MJ, Tothy MB, Kelembho EK, Clind L, et al. (2003) Immunohematological reference ranges for adults from the Central African Republic. Clin Diagn Lab Immunol 10(3): 443-445.

    [Crossref] [Google Scholar]

17. Wakeman L, Al-Ismail S, Benton A, Beddall A, Gibbs A, et al. (2007) Robust, routine haematology reference ranges for healthy adults. Int J Lab Hematol 29(4): 279-283.

    [Crossref] [Google Scholar]

18. Bachman E, Travison TG, Basaria S, Davda MN, Guo W, et al. (2014) Testosterone induces erythrocytosis via increased erythropoietin and suppressed hepcidin: Evidence for a new erythropoietin/hemoglobin set point. J Gerontol A Biol Sci Med Sci 69(6): 725-735.

    [Crossref] [Google Scholar]

19. Coviello AD, Kaplan B, Lakshman KM, Chen T, Singh AB, et al. (2008) Effects of graded doses of testosterone on erythropoiesis in healthy young and older men. J Clin Endocrinol Metab 93(3): 914-919.

    [Crossref] [Google Scholar]

20. Verthelyi D (2001) Sex hormones as immunomodulators in health and disease. Int Immunopharmacol 1(6): 983-993.

    [Crossref] [Google Scholar]

21. Burger HG, Hale GE, Robertson DM, Dennerstein L (2007) A review of hormonal changes during the menopausal transition: Focus on findings from the Melbourne women's midlife health project. Hum Reprod Update 13(6): 559-565.

    [Crossref] [Google Scholar]

22. Juca GT, Pencina KM, Guo W, Li Z, Huang G, et al. (2020) Differential effects of testosterone on circulating neutrophils, monocytes, and platelets in men: Findings from two trials. Andrology 8(5): 1324-1331.

    [Crossref] [Google Scholar]

23. Hartl S, Breyer MK, Burghuber OC, Ofenheimer A, Schrott A, et al. (2020) Blood eosinophil count in the general population: Typical values and potential confounders. Eur Respir J 55(5).

    [Crossref] [Google Scholar]

24. Kibaya RS, Bautista CT, Sawe FK, Shaffer DN, Sateren WB, et al. (2008) Reference ranges for the clinical laboratory derived from a rural population in Kericho, Kenya. Plos One 3(10): e3327.

    [Crossref] [Google Scholar]

25. Kaya H, Kiki I, Akarsu E, Gundogdu M, Basol Tekin S, et al. (2000) Hematological values of healthy adult population living at moderate altitude (1869 m, Erzurum, Turkey). Turk J Haematol 17(3): 123-128.

    [Crossref] [Google Scholar]

26. Cowman J, Dunne E, Oglesby I, Byrne B, Ralph A, et al. (2015) Age-related changes in platelet function are more profound in women than in men. Sci Rep 5(1): 1-7.

    [Crossref] [Google Scholar]

27. Dupuis M, Severin S, Esclassan NE, Arnal JF, Payrastre B, et al. (2019) Effects of estrogens on platelets and megakaryocytes. Int J Mol Sci 20(12): 311.

    [Crossref] [Google Scholar]

28. Guducu N, Kutay S, Sidar G, Gormus U, Kavak Z, (2019) The relationship of mean platelet volume with endogenous sex hormones and cardiovascular risk parameters In postmenopausal women. East J Med 19(1): 28-32.

    [Crossref] [Google Scholar]

29. Van Beek AA, Fransen F, Meijer B, De Vos P, Knol EF, et al. (2018) Aged mice display altered numbers and phenotype of basophils, and bone marrow derived basophil activation, with a limited role for aging-associated microbiota. Immun Ageing 15(1): 1-11.

    [Crossref] [Google Scholar]

30. Schwarzenbach HR, Nakagawa T, Conroy MC, De Weck AL (1982) Skin reactivity, basophil degranulation and IgE levels in ageing. Clin Exp Allergy 12(5): 465-473.

    [Crossref] [Google Scholar]

31. Valiathan R, Ashman M, Asthana D (2016) Effects of ageing on the immune system: Infants to elderly. Scand J Immunol 83(4): 255-266.

    [Crossref] [Google Scholar]

32. Marone G, Giugliano R, Lembo G, Ayala F (1986) Human basophil releasability. II. Changes in basophil releasability in patients with atopic dermatitis. J Invest Dermatol 87(1): 19-23.

    [Crossref] [Google Scholar]

33. Biagi E, Nylund L, Candela M, Ostan R, Bucci L, et al. (2010) Through ageing, and beyond: Gut microbiota and inflammatory status in seniors and centenarians. PlosOne 5(5): e10667.

    [Crossref] [Google Scholar]

34. Hill DA, Siracusa MC, Abt MC, Kim BS, Kobuley D, et al. (2012) Commensal bacteria derived signals regulate basophil hematopoiesis and allergic inflammation. Nat Med 18(4): 538-546.

    [Crossref] [Google Scholar]

35. Isabel B, Nicoleta NM, Jose R, Garzon D, Maria CI, et al. (2020) Evaluation of biochemical and hematological parameters in adults with down syndrome. Sci Reports 10(1) :e13755

    [Crossref] [Google Scholar]

36. Bijlani RL, Jaypee (2003) Understanding medical physiology: A textbook for medical students.
37. Warren LA, Rossi DJ (2009) Stem cells and aging in the hematopoietic system. Mech Ageing Dev 130(12): 46-53.

    [Crossref] [Google Scholar]