Baseline haematological and biochemical reference values for healthy male adults from Mali

Baseline haematological and biochemical reference values for healthy male adults from Mali

Vita Serena^1,2,&, Miglietta Alessandro³, Lopalco Maurizio⁴, Terrazzini Nadia⁵, Sargentini Valeria⁶, Cella Eleonora⁷, Bachetoni Alessandra⁶, Dicuonzo Giordano⁸, Angeletti Silvia⁸, Ciccozzi Massimo⁷, Ceccarelli Giancarlo^1,2

 

¹Migrant Health Research Organisation (Mi-HeRO)-Centro di Ricerca Sulla Salute delle Popolazioni Mobili e Globale, Italy, ²Department of Public Health and Infectious Diseases, Sapienza University of Rome, Policlinico Umberto I, Rome, Italy, ³Units of Epidemiology and Preventive Medicine, Central Tuscany Health Authority, Florence, Italy, Italy, ⁴Sanitary Bureau of Asylum Seekers Center of Castelnuovo di Porto, Rome, Italy; Auxilium Società Cooperativa Sociale, Senise (PZ), Italy, ⁵School of Pharmacy and Biomolecular Sciences, University of Brighton, United Kingdom, ⁶Clinical Pathology, Department of Experimental Medicine, Sapienza University of Rome, Italy, ⁷Unit of Medical Statistics and Molecular Epidemiology, University Campus Bio-Medico of Rome, Italy, ⁸Clinical Pathology and Microbiology Laboratory, University Hospital Campus Bio-Medico of Rome, Italy.

 

 

^&Corresponding author
Serena Vita, Migrant Health Research Organisation (Mi-HeRO)-Centro di Ricerca Sulla Salute delle Popolazioni Mobili e Globale, Italy

 

 

 

 

Since 2012, Mali has been in the grip of an unprecedented political crisis, causing a constant and numerically significant migration to Southern Europe. As a consequence of the increase in migration flows, the need for access to diagnostic tests and medical evaluations by Malians is steadily growing in host countries. Therefore, general practitioners and clinicians need more information on the health status of asylum applicants, for diagnosis orientation and treatment decisions. Reference intervals (RIs) of haematologic indices have not yet been established in Mali and in most African countries. RIs have an important role in clinical practice and are used in disease screening as well in assessing disease progression and treatment response. The use of accurate RIs can reduce the risk of disease misdiagnosis, allows an early diagnosis and improves patient care. Guidelines by the International Federation of Clinical Chemistry (IFCC) recommend that every country establish RIs of healthy adult populations [1]. Common practice in African countries is to use laboratory reference values derived from data collected from populations living in industrialized countries [2]. Discrepancies between normal reference values in industrialized and African countries have been reported in the literature [3, 4], possibly due to factors such as age, sex and geographic origin of different ethnic groups [5, 6]. The main aim of our study was to determine RIs of hematological and clinical chemistry parameters in healthy male adults coming from Mali, recruited at the Asylum Seekers Center (ASC) in Castelnuovo di Porto, Italy. The secondary objective was to evaluate the impact of anthropometric, behavioral, social and metabolic variables on haematological and biochemical analyses.

 

 

This cross-sectional retrospective study was conducted on data from blood tests collected from adult Malians, within 3 months of their arrival in Italy, at the Internal Healthcare Facility (IHCF) of the ASC of Castelnuovo di Porto (Rome, Italy), between May and November 2014. In accordance with internal procedures, each Asylum Seeker (AS) who accessed the IHCF for the first time was interviewed using a standardized questionnaire focused on socio-demographic data and medical history. Medical staff conducted interviews with the support of mediators speaking the patient's mother tongue. Moreover, a physical examination, including the collection of vital signs and anthropometric data, was performed. The study was carried out in accordance with the Helsinki Declaration and data were collected and analyzed after receiving informed consent. Ethical approval was not required because the study was based on a retrospective analysis of data routinely collected and stored according to the Italian law on privacy (General authorization to process personal data for scientific research purposes granted by the Italian Data Protection Authority (1 March 2012 as published in Italy's Official Journal no. 72 dated 26 March 2012)).

 

Reference range analysis: haematological and chemistry laboratory tests included: erythrocytes (RBC), haemoglobin concentration (Hb), hematocrit (HCT), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), red blood cell distribution width (RDW), concentrations of leukocytes (WBC), lymphocytes (LYM), neutrophils (NEUT), monocytes (MON), eosinophils (EOS) and basophiles (BAS), absolute number and the percentages (%) of LYM/NEUT/MON/EOS or BAS, platelets (PLT), platelet distribution width (PDW), mean platelet volume (MPV), and plateletcrit (PCT), creatinine, azotemia, glucose, aspartate aminotransferase (AST), alanine aminotransferase (ALT). Partecipantswere also tested for HbsAg, and for antibodies against HIV and HCV.

 

Blood collection and testing methodologies: routine blood tests for hematology, blood chemistry, and virologic assessment were offered to all adults examined. For hematology, the blood was collected in a Becton Dickinson (BD) ethylene diamine tetra-acetic acid (EDTA) Vacutainer tube (Franklin Lakes, NJ, USA), while for biochemistry tests the blood was collected in a BD serum separation tube (SST) that was centrifuged (3,000 g, 3 minutes). All samples were analysed within 3 hours of collection. Blood samples were analysed using Sysmex XN 1000 automated hematology analyzer for complete blood counts, as recommended by the manufacturer. Dimension Vista 1500 Intelligent Lab System (Siemens) was used to analyze serum biochemical parameters. Hepatitis B virus surface antigen (HBsAg), hepatitis C virus antibody (HCV-Ab) and human immunodeficiency virus antibody (HIV-Ab) were detected by a third-generation enzyme linked immunoassay (Abbott).

 

Statistical methods: for each of the clinical, biochemical and haematological parameters of the study, reference values were determined at 2.5^th-97.5^th percentiles; mean, median and standard deviations (±SD) were also computed. Parametric student's t-test was used to determine any statistically significant differences between the age groups ≤25 and ≥26, smokers and no smokers, normal and abnormal Body Mass Index (BMI). BMI was considered abnormal if > 25 or < 18.5 according to World Health Organization (ref http://www.euro.who.int/en/health-topics/disease-prevention/nutrition/a-healthy-lifestyle/body-mass-index-bmi) In order to test for differences in the parameters in relation to the occupation (i.e. craftsman, farmer, student/unemployed, trader), one-way ANOVA with post-hoc analysis using the Scheffe test were conducted. Analyses were carried out using Stata 10.1 software; p<0.05 values were considered statistically significant.

 

 

Study population: out of 161 Malian males who had haematological and biochemical tests, 36 were excluded from the analysis due to factors that made them ineligible for study participation and could have affected their suitability for reference values. Of the 36 excluded, 25 (69.4%) were positives for HBsAg, 2(5.6%) were anti-HCV positives and 1 (2.7%) was double positive for HBsAg and anti-HCV. Moreover, 8(22.3%) partecipants were excluded because their analyses were performed 4 months after their arrival to the reception center. This left a total sample of 125 healthy participants from whom the reference ranges were calculated. Participants' median age was 25, ranging from 19 to 54 years-old (SD±6). Information on weight and height was available for 105 Malians. Most of them (n=83; 79.04%) had a normal BMI (18.75 - 24.78), 4 (3.80%) were underweight or in the mild thinness Class (i.e. BMI range: 17.28 - 18.08), 13 (12.38%) were overweight (i.e. BMI range: 25.06 - 29.73) and 2(1.90%) had an obesity class I (i.e. BMI 30.25 and 30.64 respectively). Thirty one participants (24.8%) stated to be smokers. More than half of the partecipants enrolled had no education (n=74; 63.79%). The principal occupation was farmer (n=36; 31.3%), followed by craftsman (n=29; 25.22%).

 

Clinical, haematological and biochemical parameters: the median reference values (2.5^th-97.5^th percentiles), mean and ±SD for clinical, haematological and biochemical parameters collected from all participants enrolled in the study are shown in Table 1. Data presented are calibrated on Malian healthy adult males, unweighted for anthropometric parameters and social factors.

 

Impact of anthropometric and social factors on clinical and laboratory parameters: samples were further stratified by age, BMI, smoker status and type of employment. The population was classified in 2 groups by age, young adults ≤25 years old and adults ≥26 years old, taking into account the median age (25 years). MCV/MCH/MON% and creatinine were statistically significantly higher in adults group (MCV p-value=0.01; MCH p-value=0.01; MON% p-value=0.02, creatinine p-value=0.01; data not shown), while PLT10^3 and EOS% were significantly higher in the young adults group (PLT10^3 p-value=0.01; EOS% p-value<0.01; (Annex 1). MPV, PCT, PDW and ALT were statistically significantly higher in the abnormal BMI group (MPV p-value=0.02; PCT p-value=0.02; PDW p-value=0.02; ALT p-value = 0.03; (Annex 1). No statistically significant differences were found between smoking and no-smoking groups (Annex 1) although HB, HCT and PLT 10^3 were at the limits of statistical significance (p=0.05). HB and HCT tended to be higher in no-smokers than in smokers, while PLT 10^3 were higher in smokers than in non-smokers. Participants enrolled in the study were divided in 4 groups, according to their type of employment: farmer, craftsman, trader, student/unemployed. Scheffe Post-hoc pairwise comparisons were performed among the four employment groups and statistically significant differences were found for the following parameters: MON% (p=0.03), EOS% (p=0.03), BAS% (p=0.01) and AST (p=0.01) (Annex 1). For MON%, comparisons showed noticeable differences (i) between farmers and craftsmen with significantly lower values (p=0.03) in farmers and (ii) between students/unemployed and craftsmen, with significantly lower values (p=0.03) in students/unemployed. For EOS%, comparisons indicated that the difference was statistically significant between traders and craftsmen (p=0.03) with traders showing higher values. For BAS%, the comparisons indicated that the difference was statistically significant between traders and farmers (p=0.01) with traders showing higher values. For AST, comparisons revealed statistically significant differences (i) between traders and craftsmen (p=0.01) with traders showing higher values and (ii) between traders and farmers (p=0.01), still with traders showing higher values (p= 0.01).

 

Comparison between reference values in Malian males and other countries: Table 2 and Table 2 (suite) show a summary, based on previously published data, of medians and unweighted lower and upper limits reference values (the lower limit defined as the 2.5^th percentile and the upper limit as the 97.5^th percentile, according to United States National Consensus Committee on Laboratory Standards of normal ranges for laboratory tests [7]), stratified by race and ethnicity [5, 6, 8-17]. Although most Malian normal ranges appeared to be close to the RIs reported for other race/ethnicities, some deviated significantly from the corresponding range in different populations. Figure 1 shows all African countries, for which, to our knowledge, reference ranges have been reported in the literature [5, 6, 8-16, 18-25]. Moreover, considering that Italian RIs are representative of South Europe normal ranges, the comparison between the reference values for Italian [26] and Malians patients is illustrated in Table 3. Figure 2 shows the comparison between the white cell differential count reference values for Italians and Malians.

 

 

The International Federation of Clinical Chemistry recommends that each country should establish their own RIs for healthy subjects [1]. RIs play a pivotal role in clinical practice and the accuracy of the values used can reduce the risk of disease misdiagnosis. In fact, about 60-70% of all clinical decisions regarding a patient's diagnosis and treatment or hospital admission and discharge are made on the basis on laboratory test results [27]. Haematological reference values have, so far, been determined for the Caucasian population [28, 29] but not yet for all other countries. Hence, RIs for analysis of haematological parameters in routinary clinical practice in Africa are generated from Caucasian adult populations living in developed countries [30]. However, as a result of clinical trials and preventive interventions for HIV, tuberculosis and malaria, in the past two decades RIs have been established in several African countries, especially in southern, east and west Africa. Unfortunately the data reported so far is rather variable, due to discrepancies in the statistical methods used. In future, it would be desirable to have more homogeneous methods and therefore comparable data. More than a million migrants and refugees crossed into Europe in 2015 and 153,842 asylum seekers landed on the Italian coasts [31]. It is important to assess the state of health of all migrants and the correct identification of RIs relevant to different races and ethnicities, would allow clinicians and practitioners to manage laboratory tests and therapies more efficiently. Since haematological reference values have never been established for Malian people, the present study aimed to evaluate the RIs for haematological and biochemical parameters in healthy Malian male adult asylum seekers (ASs) housed in the largest Italian ASC. Many factors influence haematological values such as sex, age, ethnic origin, geographic location, climate, body mass index (BMI), and genetic differences [5, 6, 32-34]. In accordance with the internal procedure, each Asylum Seeker (AS) who accessed at IHCF for the first time completed a standardized questionnaire focused on socio-demographic data and was given a physical examination, including the collection of vital signs and anthropometric data. The study group consisted exclusively of males, mainly due to the low percentage of women hosted at the ASC. Only migrants without any disease were included into the study. Most of them were in good health status, which was expected, as many studies before have reported that ASs are generally young and healthy and only present minor health problems [35-39]. Hence, because of the selection process, the assessed RIs were not influenced by sex and previous or actual, acute or chronic diseases. On the other hand, anthropometric and social factors had only a partial impact on haematological and biochemical RIs. When we analyzed the results considering the BMI, we found that in people with abnormal BMI some of the platelet parameters (MPV, PCT and RDW) deviated from RIs, probability due to the fact that those factors have been linked with an increased risk of microvascular blood flow resistance [40] and vascular mortality [41]. Regarding chronologic age, we found an increased value of MCV and MCH with aging in Malians, in both white and black people, as already reported in literature [42, 43]. In fact, it has been suggested that MCV increases gradually during early adulthood, levels off around middle adulthood,to rise again in old age. Thus, such fluctuations might be associated with differences in red blood cell survival [42].

 

In agreement with other studies, we found higher level of PLT and EOS in younger Malians, when compared with older partecipants, for reasons not yet fully understood [44]. Concerning the smoking-status, smokers seem to present higher level of PLT than no-smokers, probably due to an indirect effect of nicotine causing a release of platelets in peripheral circulation [45]. Surprisingly, in our analysis Hb and HCT tended to be higher in no-smokers than in smokers, unlikely the literature data [46, 47]. These observations need to be confirmed. Considering participants' work activity, statistically significant differences were found between farmers, craftsmen, traders and students/unemployed only for white cell differential count (MON%, EOS%, BAS%) and AST. These differences (especially with regard to eosinophils) could reflect an occupational exposure to alternative types of allergens or pathogens, despite the fact that, at the time of blood sampling, the patients had no symptoms or any sign of ongoing disease. When we compared the RIs of Malians with references of white Americans, African-Americans and Europeans, we observed some interesting differences. In particular, we found a distribution of normal Malian (and Kenyan) values for EOS largely different from non-Africa resident population. The high values of EOS observed in a portion of the Malian and Kenyan people, when assessed with European or American RIs, could lead the clinician to evaluate the patient as suffering from the condition of hypereosinophilia. However, considering the specific RIs for these populations, many "apparent" hypereosinophilic syndrome individuals fall within the normal ranges and their results can be considered a physiological finding. This evidence is confirmed by the observation that for up to 50% of the asymptomatic immigrants a cause for eosinophilia was never identified, despite exhaustive evaluation [48]. In clinical practice, the clinical evaluation of these patients prudentially required a critical approach. Given the epidemiology of parasitic diseases in sub-Saharan countries, in our opinion, a full examination on the possible causes of secondary hypereosinophilia is nevertheless recommended. Practitioners should be always aware of the possible impact of the use of incorrect RIs and its fallout on clinical and laboratory evaluation of subjects from different race/ethnicity. Another interesting observation was that the median value of MON tended to be higher in Malian than in European persons. Interestingly, studies showed that the mild relative monocytosis observed in West African patients may be indicative of an anti-malaria effect played by monocytes; in fact, these cells play a role in the quality of antimalarial response and may enhance the predisposition to a favourable clinical outcome [49]. Based on an adaptive-evolutionary point of view, it is possible that the greater RIs for monocytes in Malian population than in the Europeans can be somewhat linked to factors such as the one described above. According to the Clinical Laboratory Standards Institute (CLSI) Guideline recommendations, a minimum size of 120 observations from each category is needed [50] and although the sample size of our study is considered sufficient to define RIs, our research suffers many limitations and further larger studies are needed. In particular, the absence of a female sample reduces the quality of the information collected and the use of standardized questionnaire focused on socio-demographic data and medical history may have represented a source of bias. However, despite its limitations, this paper represents the first systematic collection of biochemical and haematological data from Malian healthy persons. Unlike other similar studies, the patients' state of health was not determined from the patient, but was defined in all patients by medical evaluation.

 

 

In conclusion, our data provide region-specific reference values which can be used to manage Malian patients (and populations with similar ethnic characteristics residents in neighboring areas) in and outside Africa. Taking into account the natural variations in the distributions of laboratory test results among racial/ethnic groups, this work will contribute to reduce disease misdiagnosis and to improve the quality of clinical care provided to migrants in the host country.

 

 

The authors declare no competing interest.

 

 

Serena Vita and Miglietta Alessandro: conception, design, acquisition and interpretation of data and drafting the manuscript Lopalco Maurizio: acquisition, analysis and interpretation of data Miglietta Alessandro: data analysis, interpretation. Sargentini Valeria, Bachetoni Alessandra: draft and review the manuscript Terrazzini Nadia: reviewing of several drafts of the manuscript Cella Eleonora, ED: collection of data and interpretation Angeletti Silvia, Dicuonzo Giordano, Ciccozzi Massimo: reviewing of several drafts of the manuscript for important intellectual content Ceccarelli Giancarlo had oversight of all stages of the research and critically reviewed the final draft.

 

 

Table 1: clinical and biochemical parameters of the study population

Table 2: comparison between reference values for Malian males and those from other countries

Table 2 (suite): comparison between reference values for Malian males and those from other countries

Table 3: comparison between haematological reference values for Italian (representative for South European population) and Malian males

Figure 1: african countries where haematological reference ranges have already been described (evidenced in black)

Figure 2: comparison between the white cell differential count reference values for Italian (representative for South European population) and Malians participants. Data are expressed as median and reference values (2.5^th-97.5^th percentiles). Horizontal lines show the lower and upper limits of normal range for the population analyzed (in black Malians, in gray Italians) and the dot on each line represents the estimated median value

 

 

Annex 1: stratification of the study population by age, BMI, smoking and employment status

 

 

1. Malati T. Whether western normative laboratory values used for clinical diagnosis are applicable to Indian population: an overview on reference interval. Indian Journal of Clinical Biochemistry. 2009; 24(2): 111-122. PubMed | Google Scholar


2. Wintrobe MM, Lee GR. Wintrobe's clinical hematology-10^th edition. The Williams & Wilkins Co, Baltimore, Md. 1999.


3. Badenhorst CJ, Fourie J, Steyn K, Jooste PL, Lombard CJ, Bourne L et al. The haematological profile of urban black Africans aged 15?64 years in the Cape Peninsula. East Afr Med J. 1995; 72(1): 19-24. PubMed | Google Scholar


4. Coetzee MJ, Badenhorst PN, de Wet JI, and Joubert G. Haematological condition of the San (Bushmen) relocated from Namibia to South Africa. S Afr Med J. 1994; 84(7): 416-420. PubMed | Google Scholar


5. Kibaya RS, Bautista CT, Sawe FK, Shaffer DN, Sateren WB, Scott PT et al. Reference ranges for the clinical laboratory derived from a rural population in Kericho, Kenya. PLoS One. 2008; 3(10): e3327. PubMed | Google Scholar


6. Saathoff E, Schneider P, Kleinfeldt V, Geis S, Haule D, Maboko L et al. Laboratory reference values for healthy adults from southern Tanzania. Trop Med Int Health. 2008; 13(5): 612-25. PubMed | Google Scholar


7. Sasse EA, Doumas BT, D'Orazio P, Eckfeldt JH, Evans SA, Graham GA et al. How to define and determine reference intervals in the clinical laboratory approved guideline second edition. NCCLS Document C28-A2. 2000; 20(13). Google Scholar


8. Tembe N, Joaquim O, Alfai E, Sitoe N, Viegas E, Macovela E et al. Reference values for clinical laboratory parameters in young adults in Maputo, Mozambique. PLoS One. 2014; 9(5): e97391. PubMed | Google Scholar


9. Koram K, Addae M, Ocran J, Adu-Amankwah S, Rogers W, Nkrumah F. Population based reference intervals for common blood haematological and biochemical parameters in the Akuapem North District. Ghana Med J. 2007; 41(4): 160-166. PubMed | Google Scholar


10. Mine M, Moyo S, Stevens P, Michael K, Novitsky V, Makhaola K et al. Immunohaematological reference values for HIV-negative healthy adults in Botswana. Afr J Lab Med. 2011; 1(1): 5-11. PubMed | Google Scholar


11. Yalew A, Terefe B, Alem M, Enawgaw B. Haematological reference intervals determination in adults at Gondar university hospital, Northwest Ethiopia. BMC Res Notes. 2016; 9: 483. PubMed | Google Scholar


12. Menard D, Mandeng MJ, Tothy MB, Kelembho EK, Gresenguet G, Talarmin A. Immunohaematological reference ranges for adults from the Central African Republic. Clin Diagn Lab Immunol. 2003; 10(3): 443-445. PubMed | Google Scholar


13. Karita E, Ketter N, Price MA, Kayitenkore K, Kaleebu P, Nanvubya A et al. CLSI-derived hematology and biochemistry reference intervals for healthy adults in eastern and southern Africa. PLoS One. 2009; 4(2): e4401. PubMed | Google Scholar


14. Kueviakoe IM, Segbena AY, Jouault H, Vovor A, Imbert M. Hematological reference values for healthy adults in Togo. ISRN Hematol. 2011; 2011: 736062. PubMed | Google Scholar


15. Lawrie D, Coetzee LM, Becker P, Mahlangu J, Stevens W, Glencross DK. Local reference ranges for full blood count and CD4 lymphocyte count testing. S Afr Med J. 2009; 99(4): 243-8. PubMed | Google Scholar


16. Samaneka WP, Mandozana G, Tinago W, Nhando N, Mgodi NM, Bwakura-Dangarembizi MF et al. Adult Hematology and Clinical Chemistry Laboratory Reference Ranges in a Zimbabwean Population. PLoS One. 2016; 11(11): e0165821. PubMed | Google Scholar


17. Lim E, Miyamura J, Chen JJ. Racial/Ethnic-Specific reference intervals for common laboratory tests: a comparison among Asians, Blacks, Hispanics, and White. Hawaii J Med Public Health. 2015; 74(9): 302-310. PubMed | Google Scholar


18. Böhler T, Kynast-Wolf G, Coulibaly B, Siè A, Kapaun A. Gender-specific distribution of hematological parameters in adults living in Nouna, Burkina Faso. Open Hematol J. 2008; 2: 1-4. Google Scholar


19. Adetifa IM, Hill PC, Jeffries DJ, Jackson-Sillah D, Ibanga HB, Bah G et al. Haematological values from a Gambian cohort--possible reference range for a West African population. Int J Lab Hematol. 2009; 31(6): 615-22. PubMed | Google Scholar


20. Cross JP, Heyns AD. Haematological reference values for the Basotho. S Afr Med J. 1983; 63(13): 480-483. PubMed | Google Scholar


21. Chisale MR, P Kumwenda, M Ngwira, B M'baya, BI Chosamata, and V Mwapasa. A pilot study to determine the normal haematological indices for young Malawian adults in Blantyre, Malawi. Malawi Med J. 2015; 27(3): 96-100. PubMed | Google Scholar


22. El Graoui O, Ellaabi S, Igala M, Elalloussi FZ, Nourchafi N, Mifdal H et al. Hematology reference intervals in Moroccan population. Clin Lab. 2014; 60(3): 407-11. PubMed | Google Scholar


23. Miri-Dashe T, Osawe S, Tokdung M, Daniel N, Choji RP, Mamman I. Comprehensive reference ranges for hematology and clinical chemistry laboratory parameters derived from normal Nigerian adults. PLoS One. 2014; 9(5): e93919.. PubMed | Google Scholar


24. Wane J. Etude des valeurs de reference de quelques parametres biologiques de l'adulte jeune en milieu urbain Zairois Kinshasa, DRC. Cliniques Universitaires du Mont Amba. 1985.


25. Sahr F, Hazra PK and Grillo TA. White blood cell count in healthy Sierra Leoneans. West Afr J Med. 1995; 14(2): 105-107. PubMed | Google Scholar


26. Buoro S, Apassiti Esposito S, Mecca T, Azzarà G, Cerutti L, Dominoni et al. Determinazione degli intervalli di riferimento dell'esame emocromocitometrico eseguito con analizzatore Sysmex XN 9000. Biochimica clinica. 2015; 39(4). Google Scholar


27. MayoClinic. Medical Laboratory Sciences. 2015. Accessed July 09 2017.


28. Bain B. "Normal ranges" in Blood cells: a practical guide-3^th edition. 2002. Blackwell Scientific Publications, Oxford UK.


29. Lewis SM. "Reference ranges and normal values" in Dacie and Lewis: practical haematology 3^rd edition. 2006. Churchill Levingstone,New York, NY, USA.


30. Bain BJ. Ethnic and sex differences in the total and differential white cell count and platelet count. J Clin Pathol. 1996; 49(8): 664-6. PubMed | Google Scholar


31. Global Migration Trends 2015. Global Migration Data Analisys Centre. 2015.


32. Bain B, Seed M, Godsland I. Normal values for peripheral blood white cell counts in women of four different ethnic origins. J Clin Pathol. 1984; 37(2): 188-193(2). PubMed | Google Scholar


33. Verma U, Shankar N, Madhu SV, Tandon OP, Madan N, Verma N. Relationship between iron deficiency anaemia and serum lipid levels in Indian adults. J Indian Med Assoc. 2010; 108(9): 555-558, 562. PubMed | Google Scholar


34. Barazzoni R, Gortan Cappellari G, Semolic A, Chendi E, Ius M, Situlin R et al. The Association between parameters and Insulin Resistance Is Modified by Body Mass Index-Results from the North-East Italy MoMa Population Study. PLoS ONE. 2014: 9(7): e101590. PubMed | Google Scholar


35. Russo G, Vita S, Miglietta A, Terrazzini N, Sannella A, Vullo V. Health profile and disease determinants among asylum seekers: a cross-sectional retrospective study from an Italian reception centre. J Public Health. 2016; 38(2): 212-22. PubMed | Google Scholar


36. Fuller-Thomson E, Noack AM, George U. Health decline among recent immigrants to Canada: findings from a nationally-representative longitudinal survey. Can J Public Health. 2011; 102(4): 273-80. PubMed | Google Scholar


37. Padovese V, Egidi AM, Melillo Fenech T, Podda Connor M, Didero D et al. Migration and determinants of health: clinical epidemiological characteristics of migrants in Malta (2010-11). J Public Health. 2014; 36(3): 368-74. PubMed | Google Scholar


38. Affronti M, Affronti A, Pagano S, Soresi M, Giannitrapani L, Valenti M et al. The health of irregular and illegal immigrants: analysis of day-hospital admissions in a department of migration medicine. Intern Emerg Med. 2011; 8(7): 561-6. PubMed | Google Scholar


39. Ceccarelli G, Sulekova LF, Milardi GL, Lopalco M, Vita S, Gabrielli S. Prevalence of intestinal parasitic infections among asylum seekers. Can Fam Physician. 2018; 64(2): 88. PubMed | Google Scholar


40. Akpinar I, Sayin MR, Gursoy YC, Aktop Z, Karabag T, Kucuk E et al. Plateletcrit and red cell distribution width are independent predictors of the slow coronary flow phenomenon J Cardiol. 2014; 63(2): 112-8. PubMed| Google Scholar


41. Slavka G, Perkmann T, Haslacher H, Greisenegger S, Marsik C, Wagner OF et al. Mean platelet volume may represent a predictive parameter for overall vascular mortality and Ischemic Heart Disease. Arter, Thromb, and Vasc Biol. 2011; 31(5): 1215-1218. PubMed


42. Gamaldo AA, Ferrucci L, Rifkind JM, Zonderman AB. Age-related changes in mean corpuscular volume in adult whites and african americans. J Am Geriatr Soc. 2011; 59(9): 1763-1764. PubMed | Google Scholar


43. Patel KV. Variability and heritability of hemoglobin concentration: an opportunity to improve understanding of anemia in older adults. Haematologica. 2008; 93(9): 1281-1283. PubMed | Google Scholar


44. Biino G, Santimone I, Minelli C, Sorice R, Frongia B, Traglia M et al. Age-and sex-related variations in platelet count in Italy: a proposal of reference ranges based on 40987 subjects' data. PLoS One. 2013; 8(1): e54289. PubMed | Google Scholar


45. Aghaji M, Nnabuko R, Uzuegbunam C, Oyeka IC. The relationship of white blood cells and platelet counts to cigarette smoking in adult Nigerians. Cen Afr J Med. 1990; 36(11): 273-278. PubMed | Google Scholar


46. Nordenberg D, Yip R, Binkin NJ. The effect of cigarette smoking on hemoglobin levels and anemia screening. JAMA. 1990; 264(12): 1556-9. PubMed | Google Scholar


47. Anandha Lakshmi S, Anandhi Lakshmanan, Ganesh Kumar P, and Saravanan A. Effect of intensity of cigarette smoking on haematological and lipid parameters. J Clin Diagn Res. 2014; 8(7): BC11-BC13. PubMed | Google Scholar


48. Libman MD, MacLean JD, Gyorkos TW. Screening for schistosomiasis, filariasis and strongyloidiasis among expatriates returning from the tropics. Clin Infect Dis. 1993; 17(3): 353. PubMed | Google Scholar


49. Halim NKD, Ajayi O, Oluwafemi F. Monocytosis in acute malaria infection. Niger J of Clin Pract. 2002; 5(2): 106-108. Google Scholar


50. Clinical and Laboratory Standards Institute. Defining, establishing and verifying reference intervals in the clinical laboratory; approved guideline-3^rd edition. National Committee for Clinical Laboratory Standards, Wayne, PA, USA C28-A3. 2008. Google Scholar