Hematological reference intervals for adult population of Debre Berhan town, North East Ethiopia

Abstract

Accurate hematological reference intervals are critical for proper disease diagnosis and patient management. However, many Ethiopian laboratories rely on reference intervals derived from Western populations, which may not reflect the genetic, environmental, and lifestyle factors of the local population. This study aimed to establish locally derived hematological reference intervals for adults in Debre Berhan town, North East Ethiopia. A community-based cross-sectional study was conducted in Debre Berhan town Northeast Ethiopia, from May to July 2024. Two hundred forty (120 male, 120 female) apparently healthy adults were recruited using convenient sampling. Sociodemographic data were collected via Interviewer-administered pre-tested questionnaire through KoBoToolbox. Aseptically collected venous blood samples were analyzed for hematological parameters using a Mindray 5150 analyzer. Data were analyzed using Stata version 17; the 2.5th and 97.5th percentiles were used to determine RIs, and the Mann-Whitney U test was used to assess gender-based differences, with statistical significance set at p < 0.05. The established 95% hematological reference intervals (2.5th–97.5th percentile) were: WBC (3.2–9.5 × 10⁹/L), neutrophils (1.1–6.4 × 10⁹/L), lymphocytes (1.2–3.3 × 10⁹/L), monocytes (0.2–0.7 × 10⁹/L), eosinophils (0.01–0.4 × 10^9/L), RBC (4.04–6.08 × 10¹²/L), Hgb (12.3–18.8 g/dL), Hct (37.0–54.0%), MCV (81.6–99.8 fL), MCH (27.6–34.4 pg), MCHC (32.8–35.4 g/L), RDW-CV (11.8–16.2%), and platelet (136.0-407 × 10⁹/L). Males showed significantly higher median values for monocyte and eosinophil counts, RBC, Hgb, Hct, MCH, and MCHC compared to females. Conversely, females exhibited significantly higher median platelet counts than males (p < 0.05). The reference intervals reported in this study strongly advocate for the implementation of population-specific reference intervals, ensuring accurate diagnoses and enhanced patient safety. The observed gender-based differences in hematological parameters also underscore the importance of employing gender-specific reference intervals to improve clinical decision-making.

Introduction

Assessing hematologic parameters in whole blood is crucial for evaluating a wide range of medical conditions, such as anemia, infections, and leukemia. Clinical interpretation of hematologic test results relies on reference intervals (RIs), which are typically defined as the range of values encompassing 95% of an apparently healthy population^1,2. Since laboratory results are often compared against these intervals, the accuracy of RIs is as significant for interpretation as the precision of the test results themselves³.

Hematological RIs are crucial for interpreting laboratory results, diagnosing diseases, and monitoring treatment outcomes. However, laboratory parameters are known to vary significantly among healthy individuals from different geographic regions due to factors such as ethnicity, genetics, demographics, nutrition, economic conditions, and environmental influences^4,5. Despite this variability, many African countries, including Ethiopia, continue to adopt RIs derived from European and North American populations without considering local differences. This practice increases the risk of misclassifying healthy individuals as having laboratory abnormalities or failing to detect underlying diseases^5,6. Additionally, hematological RIs sourced from textbooks are often not representative of the populations they are applied to⁶.

Adopting reference values from dissimilar population sources without accounting for local variations can lead to diagnostic errors, incorrect disease classification, additional unnecessary medical procedures, increased healthcare expenditures, and potential threats to patient well-being^7,8. Studies have shown that unless RIs are tailored to a population’s specific demographics and determined using comparable pre-analytical and analytical methods, they are unsuitable for clinical decision-making⁴.

In Ethiopia, a country with a highly diverse population and significant geographic variability, there is no nationally established hematological RI. Laboratories across the country rely on RIs derived from Western populations or manufacturer-provided values that do not reflect Ethiopia’s unique environmental and genetic characteristics^8–11. For instance, previous Ethiopian studies have demonstrated substantial differences in hematological parameters compared to Western-derived RIs^6,8. These discrepancies highlight the critical need for locally derived RIs to improve diagnostic accuracy and patient care.

In general, lack of appropriate local hematological RIs poses significant challenges for interpreting laboratory results in Ethiopia. This issue is particularly relevant in Debre Berhan town, where laboratories rely on non-local RIs despite the region’s unique high-altitude environment and different population characteristics. Recognizing these challenges, this study aims to establish hematological RI specific to the adult population of Debre Berhan town by employing approaches recommended by the Clinical and Laboratory Standards Institute (CLSI).

The establishment of hematological RIs specific to the adult population of Debre Berhan town is essential to address the limitations of relying on Western-derived RIs or generalized textbook values. These external references often fail to account for Ethiopia’s unique genetic, environmental, and demographic factors, leading to potential misdiagnoses and suboptimal patient care. This study bridges a critical gap by generating region-specific hematological RIs tailored to the unique characteristics of Debre Berhan’s population, thereby improving the accuracy of clinical decision-making and enhancing patient outcomes.

Beyond its local impact, the study significantly enhances the national endeavor to establish population-specific hematological RIs across Ethiopia by contributing valuable data. The findings complement existing research from other regions, enriching the national database on hematological parameters. Additionally, these results will serve as a baseline for future studies and provide policymakers and stakeholders with evidence-based insights to guide the development of targeted interventions and healthcare guidelines. Ultimately, by filling a crucial gap, the study promotes more accurate laboratory interpretations and improved patient care, thereby advancing the quality of healthcare in Ethiopia.

Methods

Study design, area and setting

A community-based cross-sectional study was carried out in Debre Berhan town, located in Northeast Ethiopia, from May to July 2024. Situated in the North Shewa Zone of the Amhara National Regional State, Debre Berhan lies approximately 130 km northeast of Addis Ababa and 695 km from Bahir Dar, the regional capital. The town, positioned at an altitude of 2840 m above sea level, experiences an average annual temperature ranging between 10 and 16 °C. As a healthcare hub for its residents and surrounding areas, Debre Berhan is equipped with one public referral hospital, one university teaching hospital, one private primary hospital, four health centers, nine health posts, and five private clinics offering various medical services.

Population

Inclusion in this study was based on specific criteria to ensure the selection of a healthy and representative sample of adults aged 18 to 65 years, residing in Debre Berhan town for at least five years to ensure acclimatization to local environmental conditions. All participants underwent a rigorous screening process to confirm good health, including a comprehensive medical history review, a physical examination, and seronegative laboratory findings for Human Immunodeficiency Virus, Hepatitis B surface antigen, Hepatitis C antibody, and syphilis.

Individuals were excluded if they had any history of chronic illnesses such as diabetes mellitus, chronic renal insufficiency, hypertension, ischemic heart disease, anemia, thyroid disorders, or liver disease. Exclusion criteria also included taking pharmacologically active substances; having a history of malaria in the past three months, jaundice, or major surgery in the previous year; pregnancy or lactation (identified through clinical assessment and/or urine HCG tests); donating blood within the last four months; receiving a blood transfusion in the past year; a history of drug abuse; occupational exposure to hazardous chemicals; smoking; regular alcohol consumption; or frequent Khat (Catha edulis) chewing.

Sample size and sampling technique

The sample size for this study was determined in accordance with CLSI guidelines, which recommend a minimum of 120 participants per partition for establishing reliable RIs¹². Accordingly, 120 males and 120 females were recruited using a convenient sampling method.

Data collection and laboratory methods

Data collection

Volunteers were interviewed face-to-face using a pre-tested and semi-structured questionnaire administered via KoBoToolbox to collect data on socio-demographic information. Anthropometric measueres and vital signs, including body temperature, blood pressure, and pulse rate, were measured using digital devices, and physical examinations were conducted by trained nurses.

Sample collection

Six milliliters of venous blood were collected from eligible blood donors under aseptic conditions. Three milliliters of whole blood were placed into a Dipotassium Ethylene Diaminetetraacetic acid (K2EDTA) vacutainer tube for Complete Blood Count (CBC) analysis, while the remaining three milliliters were transferred into a plain tube and centrifuged within two hours of collection for serological tests. Urine samples were collected from female participants using leak-free, clean containers to rule out pregnancy. All samples were labeled, stored in separate sealed containers, and transported at room temperature to the Hakim Gizaw Hospital laboratory within one hour of collection.

Laboratory analysis

Hematological parameters, including White Blood Cell (WBC) count, differential WBC count, platelet count, Red Blood Cell (RBC) count, Hemoglobin (Hgb), Hematocrit (HCT), Mean Corpuscular Volume (MCV), Mean Corpuscular Hemoglobin (MCH), Mean Corpuscular Hemoglobin Concentration (MCHC), and red cell distribution width (RDW), were analyzed using a Mindray 5150 automated hematology analyzer. Serological tests for Human Immunodeficiency virus, Hepatitis B surface antigen, Hepatitis C antibody, and syphilis were conducted on serum samples using commercially approved rapid test kits. A one-step qualitative pregnancy test was performed on urine samples to detect β-HCG. Thin and thick blood smears were prepared immediately after blood collection, air-dried, fixed (for thin smears), and stained with Giemsa stain for malaria screening. All tests were performed by well-trained laboratory technologists in accordance with the Standard operating procedure of Hakim Gizaw Hospital laboratory.

Quality control

To ensure consistency and accuracy, the questionnaire was initially prepared in English, translated into Amharic, and then back-translated into English. Before data collection, the questionnaire was pretested on 5% of the sample size in Chacha town, Northeast Ethiopia, and minor adjustments were made. Data collectors received training on the study’s purpose, participant rights, and data collection techniques. Trained clinical nurses collected socio-demographic and clinical data under supervision, while medical laboratory technologists performed the laboratory tests. The investigators closely monitored the data collection process, ensuring completeness, accuracy, and consistency, and provided timely feedback to data collectors.

To ensure safety and specimen integrity, protocols for sample collection, processing, and transportation were rigorously adhered. Samples were analyzed within two hours of collection, and any delayed samples were stored at 2–8 °C for a maximum of 12 h. Each day, internal quality control checks were conducted using three-level commercial quality control materials (low, normal, and high). Test samples were processed only if the quality control samples fell within the acceptable range. All laboratory procedures were conducted in accordance with the SOPs of Hakim Gizaw Hospital and followed the manufacturers’ recommendations.

Statistical analysis

The data collected via KoBoToolbox was cleaned, edited, and checked for completeness before being transferred to Stata version 17 for statistical analysis. Descriptive statistics were used to determine the median and interquartile ranges (IQR) of hematological RIs. The Dixon method was employed to identify outliers, and the Shapiro-Wilk test was used to assess the normality of the data distribution. To evaluate gender-related variations, the Mann-Whitney U test was applied. Reference intervals were calculated according to the CLSI guidelines using a non-parametric method to establish the median and IQR, as well as combined or separate 95% RIs (2.5th and 97.5th percentiles). These percentiles were considered as the lower and upper reference limits, respectively, covering 95% of the RI for each parameter. Statistical significance was determined at a p-value of less than 0.05.

Results

Socio demographic characteristics

A total of 240 healthy adults were enrolled in this study, with an equal number of participants from each gender group (120 males and 120 females). Their ages ranged from 18 to 50 years, with a median age of 28 years (IQR: 23, 34), and about 110 (45.8%) were within the age range of 26–35 years. One hundred forty-four (60%) were single in marital status, 160 (66.7%) had attended higher education, and 112 (46.7%) were government employees (Table 1).

Table 1.

Socio-demographic characteristics for healthy adults of Debre Berhan town, Northeast Ethiopia.

Variable	Category	Frequency (n = 240)	Percentage (%)
Gender	Male	120	50
	Female	120	50
Age group (years)	18–25	93	38.8
	26–35	110	45.8
	> 35	37	15.4
Marital status	Single	144	60
	Married	94	39.2
	Divorced	2	0.8
Educational status	No formal education	1	0.4
	Primary school (1–8)	1	0.4
	Secondary school (9–12)	78	32.5
	Higher education	160	66.7
Occupation	Government employee	112	46.7
	Non-government employee	55	22.9
	Self employed	9	3.7
	Student	48	20
	Housewife	9	3.7
	Unemployed	7	3

Hematological reference interval

The combined median and 95% RIs (2.5–97.5th percentiles) for hematological parameters were: 5.8 (3.2–9.5 × 10⁹/L) for WBC, 3.1 (1.1–6.4 × 10⁹/L) for absolute neutrophils, 2.0 (1.2–3.3 × 10⁹/L) for absolute lymphocyte, 0.4 (0.2–0.7 × 10⁹/L) for absolute Monocyte, 0.08 (0.01–0.4 × 10⁹/L) for absolute Eosinophil, 5.0 (4.04–6.08 × 10¹²/L) for RBC, 15.5 (12.3–18.8 g/dL) for Hgb, 45.2 (37.0–54.0%) for Hct, 90.4 (81.6–99.8 fl.) for MCV, 30.9 (27.6–34.4 pg) for MCH, 34.1 (32.8–35.4 g/L) for MCHC, 12.8 (11.8–16.2%) for RDW-CV and 275.5 (136.0-407 × 10⁹/L) for Platelet (Table 2).

Table 2.

Median and 95% RI values of hematological parameters for healthy adults of Debre Berhan town, Northeast Ethiopia.

Parameter	Unit	Median (IQR)	RI (2.5th–97.5th )
WBC	109/L	5.8 (4.6–7.1)	3.2–9.5
Neutrophil	109/L	3.1 (2.1–4.2)	1.1–6.4
Lymphocyte	109/L	2.0 (1.7–2.4)	1.2–3.3
Monocyte	109/L	0.4 (0.3–0.5)	0.2–0.7
Eosinophil	109/L	0.08 (0.05–0.1)	0.01–0.4
Neutrophil	%	53.8 (45.9–61.4)	31.0-72.9
Lymphocyte	%	36.7 (30.3–44.3)	19.7–58.0
Monocyte	%	6.8 (5.4–8.2)	3.8–11.2
Eosinophil	%	1.5 (0.8–2.6)	0.3–6.8
RBC	1012/L	5.0 (4.6–5.4)	4.04–6.08
Hgb	g/dL	15.5 (14.1–16.6)	12.3–18.8
Hct	%	45.2 (41.8–48.4)	37.0–54.0
MCV	Fl	90.4 (87.9–93.3)	81.6–99.8
MCH	Pg	30.9 (29.9–32.0)	27.6–34.4
MCHC	g/L	34.1 (33.6–34.5)	32.8–35.4
RDW-CV	%	12.8 (12.4–13.2)	11.8–16.2
Platelet	109/L	275.5 (228–318)	136.0-407

HCT hematocrit, Hgb hemoglobin, IQR interquartile range, MCH mean corpuscular hemoglobin, MCHC mean corpuscular hemoglobin concentration, MCV mean corpuscular volume, RBC red blood cell, RDW red cell distribution width, RI reference interval, WBC white blood cell.

Hematological reference interval based on gender

Males were reported to have significantly higher median values compared to females for absolute monocyte (10⁹/L) [0.4 (0.17–0.78) vs. 0.35 (0.18–0.73), p = 0.0202]; absolute eosinophil (10⁹/L) [0.09 (0.01–0.5) vs. 0.06 (0.01–0.3), p = 0.0068]; relative monocyte (%) [7 (4.3–11.8) Vs 6.3 (3.3–11.2), p = 0.0036]; relative eosinophil (%) [1.8 (0.3–8.8) Vs 1.2 (0.2–6.7), p = 0.0041]; RBC (10¹²/L) [5.3 (4.36–6.1) Vs 4.7 (3.96–5.9), p < 0.0001]; Hgb (g/dL)[16.6 (14.4–18.8) Vs 14.1 (11.3–18.1), p < 0.0001]; Hct (%) [48 (42.0-54.4) Vs 41.8 (33.7–53.2), p < 0.0001]; MCH (pg) [31.1 (28.3–34.6) Vs 30.7 (26.8–34.2),p = 0.0091]; and MCHC (g/L) [34.4 (33.3–35.5) Vs 33.8 (32.5–35.0),p < 0.0001]. However, the median platelet count (10⁹/L) were higher in females compared to males with a value of [299 (123.4-468.7) Vs 252.5 (136.2-366.8), p < 0.0001] (Table 3).

Table 3.

Median and 95% RI values of hematological parameters in relation to gender for healthy adults of Debre Berhan town, Northeast Ethiopia.

Parameter	Gender	Median (IQR)	RI (2.5th -97.5th )	P-value
WBC (109/L)	M	5.7 (4.2-7.0)	3.2–9.8	0.6048
	F	5.9 (4.6–7.1)	3.1–9.1
Neutrophil (109/L)	M	2.9 (2.1–4.3)	1.1–6.4	0.5429
	F	3.2 (2.0-4.2)	1.1–6.1
Lymphocyte (109/L)	M	2.0 1.7–2.5	1.0-3.2	0.9272
	F	2.1 (1.7–2.4)	1.3–3.3
Monocyte (109/L)	M	0.4 (0.31–0.52)	0.17–0.78	0.0202*
	F	0.35 (0.27–0.44)	0.18–0.73
Eosinophil (109/L)	M	0.09 (0.05–0.15)	0.01–0.5	0.0068*
	F	0.06 (0.04–0.13)	0.01–0.3
Neutrophil (%)	M	53.5 (46.1–61.6)	29.2–72.8	0.5849
	F	54.8 (45.6–61.3)	32.1–73.3
Lymphocyte (%)	M	36.6 (30.3–43.5)	17.6–61.2	0.7393
	F	36.8 (30.3–44.6)	20.4–56.8
Monocyte (%)	M	7 (6.0-8.5)	4.3–11.8	0.0036*
	F	6.3 (5.1–7.7)	3.3–11.2
Eosinophil (%)	M	1.8 (0.9–2.8)	0.3–8.8	0.0041*
	F	1.2 (0.7–2.3)	0.2–6.7
RBC (1012/L)	M	5.3 (5.1–5.5)	4.36–6.1	0.0001*
	F	4.7 (4.4–4.9)	3.96–5.9
Hgb (g/dL)	M	16.6 (15.8–17.3)	14.4–18.8	0.0001*
	F	14.1 (13.6–14.9)	11.3–18.1
Hct (%)	M	48 (46.1–50.2)	42.0-54.4	0.0001*
	F	41.8 (40.2–44.1)	33.7–53.2
MCV (fl.)	M	90 (88-93.3)	81.5–101.0	0.8684
	F	90.7 (87.7–93.6)	82.4–99.2
MCH (pg)	M	31.1 (30.4–32.0)	28.3–34.6	0.0091*
	F	30.7 (29.6–31.8)	26.8–34.2
MCHC (g/L)	M	34.4 (34.0-34.7)	33.3–35.5	0.0001*
	F	33.8 (33.4–34.1)	32.5–35.0
RDW-CV (%)	M	12.9 (12.6–13.2)	11.9–14.9	0.0527
	F	12.5 (12.2–13.5)	11.5–18.3
Platelet (109/L)	M	252.5 (219.5-288.5)	136.2-366.8	0.0001*
	F	299 (243–345)	123.4-468.7

*p values < 0.05: statistically significant difference.

Discussion

Hematological RIs are critical for interpreting laboratory results, diagnosing diseases, and monitoring patient health. However, these intervals vary significantly across populations due to factors such as genetics, age, gender, ethnicity, geographic location, and lifestyle. Therefore, this study aimed to establish hematological parameter RIs for healthy adults of Debre Berhan town, Northeast Ethiopia to provide accurate benchmarks for clinical and research purposes in the region.

The lower limit of the WBC RI in this study aligns with findings from Gondar, Northwest Ethiopia¹³, and Ghana¹⁴. However, it is higher than values reported in the Amhara region of Ethiopia⁴, Kenya⁹ and Zimbabwe¹⁵, but lower than those observed in Northeast Ethiopia¹⁰, Eritrea¹⁶, Saudi Arabia¹, India¹⁷, China¹⁸ and with the current practice in the study hospital (Table 4). Similarly, the upper limit of the WBC RI is comparable to studies conducted in China¹⁸, but exceeds reports from Gondar, Northwest Ethiopia¹³, Eritrea¹⁶, Kenya⁹, Ghana¹⁴, Zimbabwe¹⁵ and India¹⁷. Conversely, it is lower than findings from the Amhara region of Ethiopia⁴, Northeast Ethiopia¹⁰ and Saudi Arabia¹. These discrepancies are likely influenced by genetic, demographic, environmental, and methodological variations. The findings underscore the importance of establishing population-specific RIs to ensure accurate clinical assessments across diverse populations¹⁹.

Table 4.

Comparison of the hematological RIs obtained from this study with RIs from other studies.

Parameter	Gender	This study	Current practice	Other studies
				Dessie, Ethiopia10	Dire Dawa, Ethiopia8	Southwest Ethiopia6	Eritrea16	Ghana14	Zimbabwe15	Saudi Arabia1	China18
WBC (109/L)	C	3.2–9.5	4.0–10.0	3.49–11.3	NA	NA	3.4–9.0	3.16–7.73	2.9–7.9	3.6–10.6	3.64–9.39
	M	3.2–9.8	4.0–10.0	3.54–10.9	3.5–10.3	3.31–11.62	3.7–9.3	3.08–7.67	2.8–8.1	3.7–10.6	3.64–9.39
	F	3.1–9.1	4.0–10.0	3.47–11.8	3.8–10.2	3.24–10.05	3.3–8.9	3.28–7.85	3.3–8.3	3.5–10.6	3.64–9.39
Neutrophil (109/L)	C	1.1–6.4	2.0–7.0	1.22–7.04	NA	NA	NA	0.94–3.52	0.94–4.25	1.0–6.5	1.80–6.30
	M	1.1–6.4	2.0–7.0	0.74–6.47	1.4–6.8	1.01–7.22	NA	0.85–3.56	0.7727–3.9673	1.1–6.3	1.80–6.30
	F	1.1–6.1	2.0–7.0	1.25–7.87	1.4–7.0	1.08–6.69	NA	0.99–3.52	1.112–4.4401	1.0–6.6	1.80–6.30
Lymphocyte (109/L)	C	1.2–3.3	0.8–4.0	1.07–4.23	NA	NA	NA	1.31–3.38	1.2–3.49	1.3–3.8	1.06–3.20
	M	1.0–3.2	0.8–4.0	1.07–3.84	1.2–3.8	1.1–3.84	NA	1.19–3.34	1.1443–3.276	1.3–3.9	1.06–3.20
	F	1.3–3.3	0.8–4.0	0.88–4.25	1.3–4.0	1.2–3.98	NA	1.34–3.41	1.3396–3.7375	1.3–3.7	1.06–3.20
Monocyte (109/L)	C	0.2–0.7	0.12–1.20	0.10–1.01	NA	NA	NA	0.20–0.68	0.21–0.77	0.2–0.9	0.16–0.62
	M	0.17–0.78	0.12–1.20	0.12–1.00	NA	0.24–0.88	NA	0.19–0.70	0.212–0.7953	0.2–0.9	0.16–0.62
	F	0.18–0.73	0.12–1.20	0.08–1.05	NA	0.27–0.87	NA	0.20–0.66	0.211–0.7236	0.3–0.9	0.16–0.62
Eosinophil (109/L)	C	0.01–0.4	0.02–0.50	0.02–0.46	NA	NA	NA	0.02–0.20	0.02–0.61	0.0–0.4	0.02–0.52
	M	0.01–0.5	0.02–0.50	0.02–0.48	NA	0.05–1.21	NA	0.02–0.20	0.019–0.612	0.0–0.4	0.02–0.52
	F	0.01–0.3	0.02–0.50	0.01–0.41	NA	0.04–1.12	NA	0.02–0.19	0.0187–0.6228	0.0–0.4	0.02–0.52
RBC (1012/L)	C	4.04–6.08		3.98–6.12	NA	NA	4.07–6.02	3.97–6.28	4.1–6.6	NA	NA
	M	4.36–6.1	4.00–5.60	3.81–6.38	4.46–6.15	4.26–6.68	4.2–6.07	4.20–6.47	4.4–6.7	5.2–5.7	4.28–5.81
	F	3.96–5.9	3.5–5.00	4.06–5.85	3.81–5.49	4.02–6.15	4–5.7	3.83–5.71	3.9–5.9	4.5–5.0	3.81–5.13
Hgb (g/dL)	C	12.3–18.8		11.2–16.8	NA	NA	12.6–17.7	10.6–17.34	10.5–18.0
	M	14.4–18.8	12–18	11.3–17.5	12.4–17.5	12.06–18.76	12.6–17.8	12.35–17.75	13.2–18.3	12.9–17.9	13.3–17.5
	F	11.3–18.1	11–16	10.8–16.1	10.7–15.2	12.30–17.86	12.5–17.6	10.22–15.50	10.2–15.9	11.4–15.4	11.5–15.2
Hct (%)	C	37.0–54.0		35.4–52.0	NA	NA	38.3–54.4	31.0–50.7	34.7–54.2	NA	NA
	M	42.0–54.4	40.0–54.0	35.2–53.9	43.8–58.5	36.72–54.48	40.5–55	32.5–51.5	42.0–55.1	40–50	40.0–51.0
	F	33.7–53.2	37.0–47.0	35.4–49.8	37.7–52.0	36.86–51.59	37.9–52	29.0–45.3	33.9–48.7	40–50	35.0–46.0
MCV (fl.)	C	81.6–99.8	80–100	77.9–93.8	NA	NA	85.8–100	68.2–95.0	70.8–102.2	77.4–94.6	82.3–99.2
	M	81.5–101.0	80–100	77.0–93.6	86–104	74.8–93.94	85.7–100	67.3–96.5	72.8–102.6	77.6–95.0	82.3–99.2
	F	82.4–99.2	80–100	78.5–96.4	83–104	77.3–98.82	85.5–100	68.4–92.0	68.8–100.7	76.6–94.2	82.3–99.2
MCH (pg)	C	27.6–34.4	27–34	24.7–32.0	NA	NA	27.4–32.8	23.2–32.5	21.9–32.9	24.7–32.7	27.0–33.7
	M	28.3–34.6	27–34	24.7–32.4	24.6–31.1	24.86–32.84	28–33	23.3–32.7	22.9–33.5	24.5–31.9	27.0–33.7
	F	26.8–34.2	27–34	25.7–32.0	23.0–30.1	26.3–33.58	26.5–32.6	23.1–32.2	20.7–32.1	24.8–31.1	27.0–33.7
MCHC (g/L)	C	32.8–35.4	32–36	30.6–34.9	NA	NA	30.2–33.8	31.7–36.7	29.5–35.0	30.5–34.4	31.6–35.4
	M	33.3–35.5	32–36	30.4–34.9	27.6–30.0	32.06–36.5	30.4–33.7	31.4–36.6	29.8–35.4	30.4–34.5	31.6–35.4
	F	32.5–35.0	32–36	30.7–34.9	26.7–29.9	32.0–36.0	30–33.7	31.8–36.9	29.2–34.3	30.5–33.9	31.6–35.4
RDW(%)	C	11.8–16.2	11.0–16.0	12.1–13.8	NA	NA	12.3–15.6	8.7–14.4	NA	11.8–14.9	NA
	M	11.9–14.9	11.0–16.0	12.3–14.4	12.3–15.3	12.46–17.56	12.3–15.5	8.55–13.8	NA	11.7–14.8	NA
	F	11.5–18.3	11.0–16.0	11.9–13.6	12.4–15.7	12.4–15.59	12.3–17	8.7–14.94	NA	11.8–15.1	NA
Platelet (109/L)	C	136.0–407	100–450	131–391	NA	NA	134–344.2	140.2–384.0	138–384.8	219–303	127–350
	M	136.2–366.8	100–450	130–395	164–447	164.0–403.4	128.4–318.4	127.1–357.3	125.3–357.0	213.0–283.0	127–350
	F	123.4–468.7	100–450	144–434	177–442	202.3–444.5	145.4–351.6	158.88–405.0	163.8–431.0	229.2–327.2	127–350

This study found no significant difference in WBC counts between males and females, aligning with previous reports from Ethiopia^6,10,11, Eritrea¹⁶, Cameroon²⁰ and China¹⁸. However, significant gender differences were observed in monocyte and eosinophil counts, consistent with studies in Ethiopia¹⁰, Ghana¹⁴ and China¹⁸. The significant gender differences in monocyte and eosinophil counts are primarily driven by hormonal influences, particularly the effects of estrogen and other hormones, although the exact mechanisms behind these differences are not yet fully understood^10,21,22. Conversely, no significant gender differences were noted in neutrophil and lymphocyte counts, supporting findings from Ethiopia^6,10 and Ghana¹⁴.

The lower reference limit for RBC count in this study is comparable with findings from Northeast Ethiopia¹⁰, Eritrea¹⁶, Kenya⁹, Ghana¹⁴, and Zimbabwe¹⁵ but is higher than values reported in Gojjam, Ethiopia¹¹. The upper reference limit is consistent with studies conducted in Ethiopia^10,11 and Eritrea¹⁶ but is lower than those reported from Ghana¹⁴ and Zimbabwe¹⁵ (Table 4). These variations in RBC counts may be attributed to factors such as genetic differences, geographic and altitude-related influences, ethnic diversity, seasonal and dietary variations, as well as methodological discrepancies in laboratory analyses^4,10,23,24.

The lower reference limits for Hgb and HCT in this study are consistent with findings from Gojjam, Ethiopia¹¹ and Eritrea¹⁶, but higher than those reported in Northeast Ethiopia¹⁰, Kenya⁹, Tanzania²⁵, Ghana¹⁴ and Zimbabwe¹⁵ (Table 4). Similarly, the upper reference limits align with studies from Gojjam¹¹ and Bahir Dar²⁶, Ethiopia, but are higher than reports from Northeast Ethiopia¹⁰, Kenya⁹, Tanzania²⁵ and Ghana¹⁴. These elevated values may be attributed to the high-altitude location of Debre Berhan, where reduced oxygen levels trigger hypoxia-induced adaptations, such as increased erythropoietin production and reduced plasma volume, leading to higher Hgb and HCT levels^27–29. Additionally, dietary habits unique to northern Ethiopia, particularly the regular consumption of teff, a staple grain rich in bioavailable iron, may further contribute to these variations compared to other African regions^8,30.

In this study, significant gender differences were observed in red cell parameters (RBC, Hgb, and HCT), with males generally having higher levels than females. This pattern is consistent with findings from Ethiopia^4,10,13,26, Eritrea¹⁶, Cameroon²⁰, Nigeria³¹, Saudi Arabia¹ and China¹⁸ (Table 4). The gender differences in these parameters are primarily driven by hormonal and physiological factors. Testosterone in males enhances erythropoiesis by stimulating erythropoietin production, leading to increased RBC production and higher Hgb and HCT levels^32,33. Conversely, estrogen in females inhibits erythropoiesis and promotes RBC deformability, potentially reducing RBC counts³². Menstrual blood loss in women of reproductive age also contributes to lower Hgb and HCT levels^32,34. Additionally, genetic differences, such as variations in erythropoietin receptor expression, may contribute to these gender-based disparities³².

The RIs for red cell indices (MCV, MCH, and MCHC) in this study were comparable to the current practice, in the study hospital and with those reported in China¹⁸ but showed slight variations when compared to studies conducted in Ethiopia¹⁰, Eritrea¹⁶, Ghana¹⁴ Zimbabwe¹⁵ and Saudi Arabia¹ (Table 4). These differences may stem from genetic diversity, geographical and environmental factors, and methodological variations in laboratory analyses^10,35,36. In this study, the median values of MCH and MCHC were significantly higher in males than females, consistent with previous findings in Ethiopia^8,11. This gender disparity is attributed to physiological and hormonal influences, as testosterone in males enhances Hgb synthesis, resulting in higher MCH and MCHC levels. In contrast, estrogen in females inhibits RBC production, compounded by menstrual blood loss, which lowers Hgb levels. However, MCV showed no significant gender differences, likely because it is less affected by hormonal variations and remains relatively stable across genders^37–39.

The reference limit for RDW in this study was comparable to findings from Ethiopia^4,13 and Eritrea¹⁶, but higher than reports from Ghana¹⁴ and Saudi Arabia¹ (Table 4). Variations in RDW RIs across regions may result from differences in population characteristics, environmental factors, and laboratory methodologies. Since RDW is derived mathematically using MCV as the denominator, regional variations in MCV due to health or laboratory practices can also influence RDW measurements^10,40,41. Additionally, this study found no significant gender differences in RDW, consistent with previous reports from Ethiopia⁸ and Cameroon²⁰.

The lower reference limit for platelet count in this study was consistent with findings from Ethiopia^10,13, Eritrea¹⁶, Ghana¹⁴, Zimbabwe¹⁵ and China¹⁸, but lower than in Saudi Arabia¹ and higher than the current practice, in the study hospital some studies in Ethiopia^4,11 and Kenya⁹. The upper reference limit for platelet was comparable to studies from the Amhara region, Ethiopia⁴ and Kenya⁹ but exceeded reports from Northeast Ethiopia¹⁰, Gojjam, Ethiopia¹¹, Eritrea¹⁶, Ghana¹⁴, Zimbabwe¹⁵, Saudi Arabia¹, and China¹⁸, while being lower than in Gondar, Ethiopia¹³ (Table 4). These regional variations in platelet counts are likely due to genetic diversity, environmental factors such as altitude and diet, and differences in laboratory methodologies^42–44, highlighting the need for region-specific reference ranges to ensure accurate clinical interpretations.

In this study, the median platelet count was significantly higher in females than in males, consistent with previous findings from Ethiopia^8,10,11 and Cameroon²⁰. This gender difference is attributed to hormonal and physiological factors, as estrogen enhances platelet production by stimulating megakaryocyte activity, as shown in both human and animal studies^45,46. Additionally, menstrual blood loss in females may trigger a compensatory increase in platelet production to maintain hemostasis^46,47. These findings underscore the importance of establishing separate platelet RIs for males and females to ensure accurate clinical assessments.

This study makes a significant contribution as the first to establish hematological RIs specifically for adults in Debre Berhan, Ethiopia, filling a critical gap in localized data and reducing reliance on RI derived from other populations. The study’s rigorous approach is further enhanced by the fact that all laboratory procedures were conducted according to SOPs by qualified personnel, ensuring reliability and accuracy of the results.

However, the study has a few notable limitations. It focuses exclusively on adults, limiting its applicability to other age groups such as adolescents, children, and the elderly. Additionally, the cross-sectional design does not account for seasonal variations in hematological parameters, and the study did not explore the underlying factors driving variations in RIs, which could provide deeper insights into these differences. One other important limitation is the lack of data on values for pregnant mothers, which represents an area for future research. Despite these limitations, the findings emphasize the importance of developing population-specific RIs to enhance diagnostic accuracy and clinical decision-making tailored to local contexts.

Conclusion and recommendations

In conclusion, this study established locally derived hematological RIs for adults in Debre Berhan, revealing notable variations compared to RIs from other regions in Ethiopia and beyond. These differences highlight the limitations of applying non-localized values, which can lead to misdiagnosis and inappropriate clinical decisions. Marked gender-based differences were also observed, with males showing higher median values for monocyte and eosinophil counts, RBC count, Hgb, Hct, MCH, and MCHC, while females had remarkably higher median platelet counts. These findings highlight the influence of genetic, hormonal, and environmental factors on hematological parameters.

Given the observed regional and gender-based differences in RIs, it is recommended that healthcare facilities in Debre Berhan adopt these localized RIs to improve diagnostic accuracy and clinical management. Future research should focus on conducting longitudinal studies to explore seasonal and temporal variations in hematological parameters and investigate the underlying genetic, environmental, and lifestyle factors contributing to these differences. Additionally, expanding RIs to include other age groups and populations is important to ensure comprehensive applicability. Similar studies in other regions are also recommended to establish a national database of population-specific hematological RIs, further enhancing healthcare outcomes across diverse settings.

Abbreviations

CLSI

Clinical laboratory standard institute

HCT

Hematocrit

Hgb

Hemoglobin

IQR

Interquartile range

MCH

Mean corpuscular hemoglobin

MCHC

Mean corpuscular hemoglobin concentration

MCV

Mean corpuscular volume

RBC

Red blood cell

RDW

Red cell distribution width

RI

Reference interval

SOP

Standard operating procedures

WBC

White blood cell

Author contributions

A.K. made the most significant contributions to this manuscript, including conceiving the research idea, designing the methodology, supervising the project, securing funding, collecting and processing data, analyzing and interpreting results, conducting a comprehensive literature review, drafting the manuscript, and critically reviewing the final report. G.E., B.A., and A.T. played substantial roles by contributing to data collection, assisting in the literature review, and providing critical feedback on the manuscript drafts. T.A., YG., B.B.T., D.M.B., Z.M., and B.M., provided support with logistical tasks, data processing, and participated in discussions regarding methodology and revisions. All authors read and approved the final manuscript.

Funding

Debre Berhan University.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Declarations

Competing interests

The authors declare no competing interests.

Ethical approval and consent to participate

The study was conducted following ethical approval from the Institutional Review Board (IRB) of Asrat Woldeyes Health science campus, Debre Berhan University (Reference number: IRB 01/124/2016), with additional permission obtained from the Debre Berhan Blood Bank. Before data collection, informed written consent was obtained from all participants after they were thoroughly briefed on the study’s objectives, procedures, and voluntary nature. Participants were assured of their right to withdraw at any stage without consequences, and confidentiality of their data was strictly maintained. To ensure participants’ safety, those with abnormal findings were referred to appropriate healthcare facilities for follow-up care. All procedures adhered to ethical standards and regulatory guidelines to protect the rights and welfare of participants.