Epidemiological and Clinical Correlates of Leukemia Ascertained in a Multiethnic Cohort of Pakistan

Rehana Yasmin1,2, Rashda Abbasi2*, Tariq Saeed2, Madiha Sadiq2, Nuzhat Yasmeen3, Muhammad Iqbal4, A. Khuzaim Alzahrani5, Nadeem Kizilbash5, Ugur Bilge6,

Nafees Ahmad2 and Sajid Malik1*

1Human Genetics Program, Department of Zoology, Faculty of Biological Sciences, Quaid-I-Azam University, 45320, Islamabad, Pakistan

2 Institute of Biomedical and Genetic Engineering, 44000, Islamabad, Pakistan

3 Department of Oncology, Pakistan Institute of Medical Sciences, 44080, Islamabad. Pakistan

4 Institute of Radiotherapy and Nuclear Medicine, 25121, Peshawar, Pakistan

5 Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, Northern Border University, Arar-91431, Saudi Arabia

6 Department of Biostatistics and Medical Informatics, Faculty of Medicine, Akdeniz University, Antalya, Turkey

ABSTRACT

Leukemia is one of the most prevalent cancers among pediatric malignancies and causes huge economic burden. In this case-control study epidemiological, environmental, life-style related risk factors and phenotypic characteristics of leukemia subtypes were investigated in Pakistani population. A total of 1500 subjects, including 616 patients and 884 controls were recruited through a retrospective cross-sectional sampling design. Descriptive summaries were generated, and risk factors were analyzed through logistic regression. We identified Pathan ethnicity (OR=2.85; 95%CI=2.29-3.54), no formal education (OR=3.36; 95%CI=2.62-4.32), poor diet (OR=2.34; 95%CI=1.79-3.06), lower BMI (OR=1.95; 95%CI=1.50-2.60), parental consanguinity (OR=2.13; 95%CI=1.67-2.71), positive family history (OR=4.24; 95%CI=2.18-8.26), rural residential setup (OR=2.93; 95%CI=2.10-4.10), drinking of groundwater (OR=2.25; 95%CI=1.6479-3.0964), wooden fuel (OR= 3.97; 95%CI=3.14-5.01), carbonated drinks (OR=1.25, 95%CI=1.00-1.57) and tobacco usage (OR=1.57, 95%CI=1.24-1.98) as significant risk factors for leukemia. However, odds ratios were significantly lower for patients using microwave oven (OR=0.25; 95%CI=0.18-0.35), and perfumes (OR=0.42; 95%CI=0.33-0.53). Males exhibit an increased risk for lymphoid leukemia as compared to myeloid leukemia (OR=1.97; 95%CI=1.38-2.80). Paraclinical parameters indicated that 71% of the cases had >50% of blast cells. Leukocytosis (OR= 9.06; 95% CI=6.46-12.71), anemia (OR= 15.84; 95% CI=11.84-21.21), low hemoglobin (OR=8.11; 95% CI=6.35-10.37), thrombocytopenia (OR=32.40; 95% CI=21.57-48.68), lymphocytosis (OR= 3.41; 95% CI=2.55-4.57), and neutropenia (OR=7.32; 95% CI=5.59-9.60) had significantly higher odd ratio for leukemia patients. Leukemia risk factors are mainly relevant to exposure due to rural residence, poor lifestyle, and family history of the disease. The disease incidence can be minimized by designing and implementing risk mitigation strategies.

Article Information

Received 02 February 2023

Revised 20 February 2023

Accepted 29 March 2023

Available online 13 May 2023

(early access)

Published 24 September 2024

Authors’ Contribution

RY conceptualization, data collection, data curation, formal analysis, methodology, writing original draft. RA conceptualization, methodology, investigation. TS and MS data collection, data curation. AKA, NK and UB data analysis. MI and NY data curation, visualization. NA writing review and editing, validation. SM conceptualization, formal analysis, software, writing review and editing.

Key words

Leukemia, Epidemiology, Cross-sectional study, Retrospective, Risk factors

DOI: https://dx.doi.org/10.17582/journal.pjz/20221215141236

* Corresponding author: r.abbasi@daad-alumni.de, malik@qau.edu.pk

0030-9923/2024/0006-2523 $ 9.00/0

Copyright 2024 by the authors. Licensee Zoological Society of Pakistan.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Introduction

Leukemia is a heterogeneous group of clonal hematologic malignancies characterized by the abnormal proliferation of hematopoietic cells interrupting the normal function of blood and bone marrow. General manifestations of leukemia include fever or chills, dyspnea, persistent fatigue, weakness, recurrent infections, weight loss, swollen lymph nodes, enlarged liver or spleen, and bruising (Castro et al., 2015; Louvigne et al., 2020). It is subdivided into acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), chronic lymphocytic leukemia (CLL), and chronic myelogenous leukemia (CML) as major divisions. Leukemia is the most common type of cancer in children (Ferlay et al., 2015). Incidence of leukemia subtypes varies according to geography, age, gender, and race, and exhibits different clinical features, treatment response, relapse kinetics, and relapse sites (Belurkar et al., 2013). Leukemia accounts for numerous morbidities and mortalities worldwide. In 2015, there were 606,000 estimated new cases of leukemia worldwide and 353,000 deaths (Fitzmaurice et al., 2017). In general, the global burden of leukemia increased slightly from 1990 to 2017 (Lin et al., 2021). In 2020, there were 60,530 estimated morbidities and 23100 mortalities due to leukemia in the US, alone (Siegel et al., 2021). Mortality due to leukemia has descended recently, but leukemia is still a highly prevalent disease that leads to considerable disability and increased economic costs. It not only results in a major personal burden but also affects families and the economic structures of countries.

In Pakistan, leukemia is one of the recurrent cancers in the general population and is the second most prevalent cancer among pediatric malignancies (Shahid et al., 2021). In Pakistan, leukemia patients have a poor quality of life in Pakistan (Malik et al., 2021). Further, weak socioeconomic status, lower literacy rate, and socially stigmatized situation are directly or indirectly adding up to the disease burden (Khokhar et al., 2020). Being a lower economic country, Pakistan is facing major problems in the health sector. There is a gross deficit of oncological services, and every oncologist deals with 1300-1500 patients annually, even in the country’s developed province, Punjab (Khokhar et al., 2020). Lack of qualified, trained oncologists, poor healthcare infrastructure, limited access to healthcare facilities, and deficiency of equipment for diagnosis are the major factors affecting the control and prevention of blood cancers in Pakistan.

The unavailability of countrywide leukemia prevalence statistics, absence of any planning and prevention strategies; and lack of educational and research programs are making the situation intimidating. The financial burden of leukemia care is huge and overwhelming due to factors like unstable economy/currency, huge unemployment, and the import of instruments and drugs for leukemia diagnosis and treatment in Pakistan. Previous literature demonstrates the existence of significantly worse survival among economically disadvantaged patients (Acharya et al., 2016). Therefore, it is highly desired to focus on leukemia prevention as the healthcare resources of the country are limited.

Epidemiological integrated transdisciplinary research is needed for estimation of the actual leukemia burden in Pakistan, identification of contributing risk factors, and designing feasible prevention strategies for leukemia unique to the Pakistani population. In this context, the present epidemiological case-control study was designed to investigate the bio-demographic attributes of leukemia patients and to identify potential risk factors associated with leukemia in the multiethnic Pakistani population.

MATERIALS AND METHODS

Patients of all gender, age group, and ethnicities from the Pakistani population suffering from any sub-type of leukemia, both newly diagnosed or actively on treatment, were included in the study without bias, While Patients of other closely related cancers i.e., lymphoma, myeloproliferative neoplasms (CML exempted), and off-treatment leukemia patients were excluded from the study. For comparison, age, gender, and ethnicity matched healthy controls, belonging to similar areas, environmental conditions, and socio-economic status were randomly collected during 2017-2020. About 70% of the eligible controls consented to participate in the study, the hesitant controls were majorly comprised of children. The detailed medical records of the patients were acquired and data on clinical diagnosis, demography, lifestyle, and risk factors were obtained. Data were systematically collected by trained researchers through direct onsite interviews (conducted for each patient individually as they get recruited for the study during the sampling span, to minimize the time lag between the diagnosis and interview) with the participants/guardians (children), on a mixed questionnaire, containing both open-ended and closed-ended questions based on the type of variable in question. The definitions of the demographic variables were obtained from Pakistan Demographic and Health Survey (Nips, 2019).

Sample and study parameters

The patients and controls were categorized into five groups based on their age; infants (<1 year), preschoolers (1.1-5 years), children (5.1-15 years), adolescents, and young adults (AYAs; 15.1-39 years), and aged (39.1 and>). The risk factors considered for this study were weight, diet, education, parental consanguinity, family history of cancer, area, drinking water source, fuel type used in the household (wood or natural gas), use of carbonated drink, perfume use, and tobacco use (Supplementary Tables I and II).

Body mass index (BMI) was derived from the height and weight (patients weights at the time of diagnosis were considered) taken during the sampling. Age and gender-specific indices were used for BMI/percentile calculation. According to international standards, a child’s weight below the 5th percentile, 6-85 percentile, and >85 percentile were considered as underweight, normal, and overweight respectively. In adults, individuals with BMI <18.5kg/m2 were considered underweight, with BMI of 18.5kg/m2-24.9kg/m2 as normal, while BMI >24.9kg/m2 were considered overweight. Tobacco use (Active/ parental: in case of children) included both smoking (cigarette; active/passive) and smokeless (pan, baerri, powdered tobacco) forms. Diet is categorized into standard and poor diet. A standard diet includes an intake of fruit, vegetables, legumes, nuts, whole grains, and meat. A poor diet is a diet lacking one or more of the food groups (WHO, 2019). Participants in the study, who were unable to consume any major group of bio-nutrients like proteins or carbohydrates, continuously for longer than WHO recommended durations were considered to have a poor diet. For each patient, a detailed pedigree was constructed. Parental marriage types up to the second cousin with inbreeding coefficient of F=0.0156 were considered consanguineous. Individuals who obtained some level (primary; 5 years, secondary; 10 years, graduation; 14 years, masters; 16 years, and so on) of formal education were considered educated while children below the age of 5 years were placed in the inadmissible category and individuals who have not obtained any form of school education were placed in no formal education category.

Hematological fluctuations of blood cellular count for all study participants were also compared in this study. Hematologic parameters consist of white blood cells (WBCs), red blood cells (RBCs), hemoglobin (Hb), platelets, lymphocyte%, and neutrophils%. All the parameters were categorized into increment, normal, and decrement categories according to the employed reference standard level for children, adults, males, and females, in the country (Supplementary Table III).

Statistical analysis

Descriptive statistical methods were used to summarize the clinical characteristics, demographic, and lifestyle-related factors of the study participants. We determined potential demographic, lifestyle, and clinical risk factors by using univariate logistic regression, comparing each parameter between patients and controls. The comparison was performed on three distinct levels: (i). compared overall numbers of patients and controls against each variable (Supplementary Table IV and V), (ii). Categorizing both patients and controls in age groups (<1, 1.1-5, 5.1-15, 15.1-39, >39 years; Table I) and then performed a group-to-group comparison of patients and controls against each variable (Supplementary Table VI), (iii). To identify the high-risk age group within the patients, the age groups within the patients cohort were compared with one another (Supplementary Table VII). In age group-wise comparison, a group vs a group and a group vs all other groups (additive model) assessment was implied separately for every variable, in both (ii) and (iii) levels of comparison. The percentage of the missing data was excluded in the respective statistical analysis to avoid its interference with the assessment. Odds ratios with 95% confidence intervals were calculated to identify the presence and strength of the association. A p-value of < 0.05 was considered statistically significant.

Results

Sample characteristics

A total of 1500 samples were collected, which comprised 616 patients and 884 age, gender, and ethnicity-matched controls for comparison. Detailed clinical and paraclinical reports were obtained for 92% of the patients remaining were not available. Among all, the data of 594 patients and 884 controls were included in the analysis, and 22 patients were excluded due to incomplete data.

 

Table I. Type-wise distribution of leukemia patients.

Age groups (Years)	Patients								Controls	Net Total
	Leukemia subtype				Disease origin		Disease type		Total	Total	Overall number
	ALL	CLL	AML	CML	Lymphoid	Myeloid	Acute	Chronic
	N (%)	N (%)	N (%)	N (%)	N (%)	N (%)	N (%)	N (%)	N (%)	N (%)	N
<1	6 (1.01)	0 (0)	0 (0)	1 (0.17)	6 (1.01)	1 (0.17)	6 (1.01)	1 (0.17)	7 (1.18)	10 (1.13)	17
1.1-5	108 (18.18)	0 (0)	6 (1.01)	2 (0.34)	108 (18.18)	8 (1.35)	114 (19.19)	2 (0.34)	116 (19.53)	74 (8.37)	190
5.1-15	150 (25.25)	0 (0)	18 (3.03)	3 (0.51)	150 (25.25)	21 (3.54)	168 (28.28)	3 (0.51)	171 (28.79)	117 (13.24)	288
15.1-39	72 (12.12)	1 (0.17)	31 (5.22)	44 (7.41)	73 (12.29)	75 (12.63)	103 (17.34)	45 (7.58)	148 (24.92)	503 (56.9)	651
39.1 and >	16 (2.69)	29 (4.88)	24 (4.04)	83 (13.97)	45 (7.58)	107 (18.01)	40 (6.73)	112 (18.86)	152 (25.59)	180 (20.36)	332
Total	352 (59.26)	30 (5.05)	79 (13.3)	133 (22.39)	382 (64.31)	212 (35.69)	431 (72.56)	163 (27.44)	594 (100)	884 (100)	1478

 

For abbreviations, see Figure 1.

Among the total 616 patients, 67% were male and 33% were female. An overall male to female ratio of 2:1 has been observed in leukemia patients. The highest occurrence of leukemia was seen in children 5 to 15 years of age (28.79%) and individuals >39 years old of age (25.59%). The details of all the variables included in the study are given in Supplementary Tables I, II, and III.

Leukemia subtypes

In type-wise distribution, ALL was the most prevalent group (59%), affecting children mostly, followed by CML (22%) affecting the AYAs age group. Among ALL, 73% of the patients were having acute (majorly consisting of children and Adolescent and young adults (AYAs)) and 26 % were suffering from chronic leukemia (common in aged individuals). Similarly, 65% were having leukemias of lymphoid origin, while 35% were having myeloid leukemia (Table I, Fig. 1).

 

Gender, ethnicity, education, and leukemia risk

In the present study, the male gender has about a 2-fold increased risk for lymphoid leukemia as compared to myeloid leukemia (OR=1.97, 95%CI 1.38-2.80). AYAs have a 2.31-fold higher risk for myeloid leukemia compared to all other age groups of patients (OR=2.31, 95%CI 1.58-3.38). Age group >39.1 has a 21.46-fold high risk for chronic leukemia as compared to all other age groups of patients (OR= 21.46; 95%CI=13.49-34.14) (Supplementary Table VII, Fig. 5). The risk for Pathan ethnicity has a 2.8-fold increased risk as compared to controls (OR=2.85; 95% CI=2.29-3.54). The risk of no education in leukemia patients has a significantly increased risk as compared to controls (OR=3.36; 95% CI=2.62-4.32; Supplementary Table IV, Fig. 2).

 

Diet, weight, and leukemia risk

Overall, patients with a poor diet have a 2.34-fold higher risk for leukemia as compared to controls (OR=2.34; 95% CI=1.79-3.06; Supplementary Table IV, Fig. 2), while patients in the age group 5.1-15 with a poor diet face a higher risk for leukemia in comparison to matched controls (OR=2.70; 95% CI=1.55-4.59; Supplementary Table VI, Fig. 4).

 

Lower BMI significantly increased the risk for leukemia in this study as compared to controls (OR=1.95; 95% CI=1.50-2.60; Fig. 2). Pre-schoolers (1.1-5 years) with lower BMI have a significant, 7.9-fold higher risk for leukemia, as compared to patients in the age group 5.1-15 years (OR=7.92; 95% CI=3.71-16.88) and 28.37-fold higher risk in comparison to the additive risk of all other age groups (OR=28.37; 95% CI=3.74-58.57) of the patients (Supplementary Table VII, Figs. 5, 6).

Consanguinity and family history as a risk factor for leukemia

Patients with the parental consanguineous union had a 2-fold higher, significant risk for leukemia as compared to controls (OR=2.13; 95% CI=1.67-2.71; Supplementary Table IV, Fig. 2). Particularly, patients in the age group 5.1-15 with parental consanguinity have been observed to have an increased risk for leukemia in comparison to controls (OR= 1.6, 95% CI=1.03-2.39: Supplementary Table VI, Fig. 4). In this study, the patients with a family history of leukemia/solid cancers, have 4-fold increased risk for leukemia as compared to controls (OR= 4.24, 95% CI=2.18-8.26: Supplementary Table IV, Fig. 2).

Lifestyle and residential risk factors

In this study, patients living in the rural residential setup have a 2.9-fold increase, a significant risk for leukemia as compared to controls (OR=2.93, 95% CI=2.10-4. 10; Supplementary Table IV, Fig. 2). The leukemia patients in the age group 5.1-15, residing in a rural area, have 1.7-fold higher risk (OR=2.70; 95% CI=1.82-4.02), as compared to age-matched controls. A similar relationship was shown by the preschoolers (1.1-5 years) (OR=1.92; 95% CI=1.23-2.99). However, no such association was identified in adult patients (Supplementary Table VI, Fig. 4).

 

Consuming groundwater as a primary drinking water source has been associated with an increased risk for leukemia in this study (OR=2.25; 95% CI=1.6479-3.0964; Supplementary Table IV, Fig. 2). Particularly, the risk is significant for children (OR= 2.17; 95% CI=1.47-3.21) and preschoolers (OR= 1.76, 95% CI 1.13-2.75), respectively, in comparison to controls. No such association was seen in adults (OR=0.90; 95% CI=0.54-1.49; Supplementary Table VI, Fig. 4).

 

Wood use as a domestic source of fuel has a significant association with higher leukemia risk as compared to controls (OR= 3.97; 95% CI=3.14-5.01; Supplementary Table IV, Fig. 2). Particularly, children in families doing wood burning, have an elevated risk for leukemia in comparison to controls (OR= 2.01; 95% CI=1.32-3.07). No such significant association was seen in any other age group (Supplementary Table VI, Fig. 4).

The extended family setup has no overall significant risk for leukemia as compared to controls in this study; however, the preschoolers and children living in an extended family setup, have 2 (OR=2.26; 95% CI=1.43-3.58), and 3-fold increased risk (OR=3.12; 95% CI=2.05-4.77), to get the disease, respectively, when compared to the same age groups in controls. However, in adult patients, no significant increased risk was observed in comparison to adult controls (Supplementary Table VI, Fig. 4).

The consumption of carbonated drinks has been linked to an increase in leukemia risk by 25% in the present study (OR=1.25; 95% CI=1.00-1.57; Supplementary Table IV, Fig. 2).

 

Tobacco use (active/passive) is observed to significantly increase leukemia risk by 57% (OR=1.57; 95% CI=1.24-1.98; Fig. 2). In age group comparison, the risk was significant for the patients belonging to age group >39.1 those were using tobacco in comparison to age-matched controls (OR=2.23; 95% CI=1.37-3.62; Supplementary Table VI, Fig. 4).

Factors protecting against leukemia

In the present study, perfume use (OR= 0.42; 95% CI=0.33-0.53) and the use of microwave oven (OR= 0.25; 95% CI=0.18-0.35) were associated with a lower risk of leukemia and identified as a protective factor for the studied population (Supplementary Table IV, Fig. 2).

Hematological variables

In the current study, blast cell percentages data were obtained for patients. About 71% of the cases had >50% blast cells while 29 % had ≤50% blast cells in which most of the cases have more than 20% of blast cells (Supplementary Table III). In myeloid leukemia, age group 39.1 and > has a significant odd ratio of 5.71 for blast cell % of ≤50%, in comparison to lymphoid leukemia when compared to all other age groups (OR= 5.71; 95% CI=2.01-16.23). In chronic leukemia, blast cell ≤50% for age group >39.1 is significantly higher than acute leukemia when compared to all other groups (OR= 27.6857; 95% CI= 7.7824-98.4913; p < 0.0001; Supplementary Table VII, Figs. 5, 6). Hyperleukocytosis (OR= 9.06; 95% CI=6.46-12.71), anemia (OR=15.84; 95% CI=11.84-21.21), lower hemoglobin level (OR= 8.11; 95% CI=6.35-10.37), thrombocytopenia (OR=32.40; 95% CI=21.57-48.68), lymphocytosis (OR=3.41; 95% CI=2.55-4.57), and neutropenia (OR=7.32; 95% CI=5.59-9.60) were the significant hematological and paraclinical risk factors associated to leukemia in the studied population (Supplementary Table V, Fig. 3).

Discussion

We investigated demography, clinical aspects, and environmental and lifestyle risk factors for leukemia patients in comparison to matched controls. This study provides a measured magnitude of clinical-epidemiological risk factors associated with leukemia in the Pakistani population. The clinical and paraclinical parameters addressed in the present study were assessed to compare with the previous literature and healthy controls from the same population.

ALL was found as the most frequent leukemia subtype and Pathan ethnicity (Caucasian with debatable ancestry) was at higher risk for leukemia. Countries neighboring Pakistan also reported ALL being the highest occurring leukemia subtype, particularly in white children (Jha and Kumar, 2021). Previous literature showed that white ethnicities are more prone to leukemia compared to other ethnicities (Bispo et al., 2020). Differences in leukemia incidence on the base of race/ethnicity could be explained by variances in genetic susceptibility to environmental risk factors. Geographical variations play a role in leukemia distribution across the globe. It was further observed that All was common in children and adolescents while CML was frequent in adults. This finding is consistent with the data published from other countries (Hoglund et al., 2015; Katz et al., 2015).

In the present study, no education is a significant risk factor for leukemia. The observations of the present study are supported by previous literature (Mwaka et al., 2016; Saeed et al., 2019). These studies elaborate on the protective role of education in leukemia and the higher risk of leukemia with no education. No education can lead to higher incidence and lower survival of leukemia patients directly due to lack of awareness, unhealthy lifestyle, and indirectly through financial inabilities.

Poor diet and lower BMI have been identified as significant risk factors for leukemia in the present study. Poor diet is directly related to lower BMI. Studies reported the prevalence of malnutrition in children and adolescents (0-19 years of age) (Ferlay et al., 2015). High frequency of undernutrition and lower BMI in leukemia patients from developing countries have been associated with worse treatment outcomes, and poor survival due to lower tolerance to chemotoxicity and anti-neoplastic agents when presented at the time of diagnosis (Amankwah et al., 2016; Yazbeck et al., 2016). The mechanisms by which nutritional status might influence cancer outcomes are hypothesized to be the differential metabolic effects based on body composition (Joffe et al., 2019). Contrary to the current study observation, some previous cohort studies have recommended that diet is not associated with leukemogenesis (Saberi et al., 2014). These inconsistencies might be due to differences in study design and the population under study. The weight status of leukemia patients and its impact on risk and treatment outcome is highly debatable.

A family history of cancer (leukemia, solid cancer) and parental consanguinity are identified as significant risk factors for leukemia in this present study. Association of leukemia with consanguinity (Sandner et al., 2019; Mahmood et al., 2020) and additional features of positive family history indicate involvement of recessive cancer genes (Kakaje et al., 2020). Consanguinity has complicated interactions that might affect the susceptibility to certain cancers and it is known to increase the probability of having homozygosity in the genes predisposing to leukemia (Stieglitz and Loh, 2013).

In the present study, a rural residential setup, groundwater consumption, and wood usage as a source of fire are identified as significant risk factors for leukemia. Previous studies have associated these risk factors directly with leukemia and other cancers (Saeed et al., 2019; Kassahun et al., 2020; Mahmood et al., 2020; Jamy et al., 2022). Less access to supportive care in rural areas is also likely a contributing factor. In rural setups, people mostly use groundwater for drinking and burn wood as a fuel source, both of which are associated with inflammation and cancer. Pakistan is an agricultural country, exposed to heavy metals contaminated groundwater, which in turn is directly associated with increased leukemia risk (Rahmani et al., 2022). Heavy metals derivatives can react with side groups of proteins and enzymes, leading to genetic mutations. Contaminated groundwater with agricultural chemicals and heavy metals is a potential risk factor for leukemia in the population. In rural setups where agriculture is a major profession of the inhabitants, exposure to agrochemicals is common. The continued use of contaminated groundwater with heavy metals, insecticides, herbicides, and their naturally derived compounds for drinking and irrigation can trigger several health manifestations in the human body. Also, the particulate and gaseous compounds produced as a result of wood combustion are linked to adverse health outcomes via systemic oxidative stress, including cancer and increased mortality due to leukemia (Avenbuan and Zelikoff, 2020). Exposure to tobacco use either directly or indirectly has also been identified in the present study as a risk factor for leukemia, like other studies (Fiebelkorn and Meredith, 2018; Frederiksen et al., 2020). The use of smokeless tobacco use has also been associated with cancer (Saeed et al., 2019).

Carbonated drinks have been observed to significantly increase leukemia risk in the present study. Likewise, a previous study reported an increased risk for childhood all due to consumption of cola-based drinks (Thomopoulos et al., 2015). The artificial sweeteners used in carbonated drinks have carcinogenic potential; however, there are also studies with no positive association of carbonated drinks with hematopoietic cancer (Bernardo et al., 2016).

Perfume and microwave oven usage has been observed as protective factors for leukemia in this study. To our knowledge, these factors have not been reported or considered in previous studies. There could be several potential justifications for these protective effects. The base/medium used in perfumery in Asian countries mostly consists of plant-based oils and fragrances are reported to have anticancer/anti-leukemic properties and the potential to induce apoptosis in vitro (Hung et al., 2020; Mileva et al., 2021). Along with this, perfume usage by the population is linked to general cleanliness and health consciousness, which is direct prevention. In Pakistan, the microwave oven is employed occasionally, for heating food items, instead of cooking them. This infrequent use and the fact that microwave uses weak electromagnetic waves to heat the food can potentially explain why microwave oven is not posing any risk to leukemia in the studied population; However, we do not have information regarding the frequency of microwave oven use in the study participants. The latest study claimed that the use of microwave ovens for food processing is not a risk for carcinogenesis (Guzik et al., 2022). However, exposure to strong electromagnetic fields (EMF) has been considered to increase the risk of leukemia (Ghahremani et al., 2020).

Regarding the etiology of leukemia, as this study indicated, there is the interaction of nutritional (poor diet, carbonated drinks), genetic (family history, consanguinity), and factors like poor lifestyle (lack of education, consumption of underground water, indoor burning of wood and biomass) in the development of leukemia in Pakistani population. There are changing trends in leukemia incidence due to changing demographic and lifestyle factors. Improvements in these factors hold the potential to improve the cancer burden. With the advent of proper epidemiological and trans-disciplinary research, using evidence-based local data, we can expect identification of associated risk factors and improvement in leukemia incidence and mortality.

Conclusion

The identification of risk factors for the Pakistani population will help the health community to address the high incidence of leukemia and design preventive strategies based on exposure to these risk factors encountered by the local population specifically and the world population in general. The limitations of the study could be small sample size in certain groups and missing data of variables.

Acknowledgments

We are grateful to Mr. Muhammad Afzaal (Pakistan Institute of Medical Sciences), Ms. Sapna Usman (Department of Zoology, Quaid-i-Azam University), and families of the patients for their cooperation in this study.

Funding

No funding to disclose.

IRB and ethical approval

The study protocol was approved by the Ethical Review Committees of Quaid-i-Azam University (Letter No. DEBS/2016-619), Islamabad, Institute of Biomedical and Genetic Engineering (IB and GE) (Letter No. IBGE/SARK/09/1205/2012), Islamabad, and Shaheed Zulfiqar Ali Bhutto Medical University, Islamabad (Letter No. 1-1/2015/ERB/SZAMBU). The sample size was calculated by using the Daniel equation (a variant for the disease of unknown prevalence). Registered leukemia patients were enrolled from tertiary care hospitals in Islamabad and Peshawar after informed written consent of the patient/legal guardian, according to the Helsinki II declaration, from March 2017 to January 2020, and 90% of the eligible patients agreed to participate in the study.

The study was approved by the Ethics and Research Committee (details, methodology section). All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the Helsinki declaration and its later amendments or comparable ethical standards.

Patient consent statement

Informed written consents were taken from study participants according to the Helsinki II declaration

Supplementary material

There is supplementary material associated with this article. Access the material online at: https://dx.doi.org/10.17582/journal.pjz/20221215141236

Statement of conflict of interest

The authors have declared no conflict of interest.

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