https://orcid.org/0000-0003-4241-1783
Figures
Abstract
Background
Hematologic malignancies have a great essential role in cancer global burden. Leukemia which two major subtypes based on the onset, is one of the common subtypes of this malignancy.
Method
For the GBD 2019 study, cancer registry data and vital registration system were used to estimate leukemia mortality. The Meta-Regression-Bayesian Regularized Trimmed (MR-BRT), Cause of Death Ensemble model (CODEm) and Spatiotemporal Gaussian Process Regression (ST-GPR) were used to model our data and estimate each quantity of interest. Mortality to incidence ratios (MIR) were used to generate incidence and survival from mortality rate. Prevalence and survival were used to generate years lived with disability (YLDs). Age-specific mortality and life expectancy at the same age were used to estimate years of life lost (YLLs). The sum of YLLs and YLDs generates DALYs.
Results
The total national incidence of leukemia increased from 6092 (UI 95%: 3803–8507) in 1990 to 6767 (4646–7890) new cases in 2019. However, leukemia age-standardized incidence ratio(ASIR) decreased from 11.6 (8–14.8) to 8.9 (6.2–10.3) new cases per 100,000 in this exact period. At the national level, deaths from leukemia increased 1.5-fold between 1990 and 2019, from 3287 (2284–4201) to 4424 (3137–5030), whereas the age-standardized death rate(ASDR) decreased from 8.3 (6.1–9.8) in 1990 to 6 (4.3–6.8) per 100,000 in 2019. In the study period, total leukemia DALYs decreased 12.2% and reached 162850 (110681–188806), in 2019. The age-standardized DALYs decreased 36.7% from 324.3 (224.8–413.4) in 1990 to 205.3 (140.3–237.8) in 2019. ASDR, DALYs, YLLs, and YLDs rate to high BMI was increasing while smoking and occupational exposure to benzene and formaldehyde were decreasing in the study period.
Citation: Poopak A, Saeedi Moghaddam S, Esfahani Z, Keykhaei M, Rezaei N, Rezaei N, et al. (2023) National and subnational burden of leukemia and its risk factors, 1990–2019: Results from the Global Burden of Disease study 2019. PLoS ONE 18(11): e0287917. https://doi.org/10.1371/journal.pone.0287917
Editor: Mohammad Asghari Jafarabadi, Tabriz University of Medical Sciences, ISLAMIC REPUBLIC OF IRAN
Received: September 21, 2022; Accepted: June 15, 2023; Published: November 30, 2023
Copyright: © 2023 Poopak et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The dataset used during the current study is available on the GBD Compare Tool website. (https://vizhub.healthdata.org/gbd-compare/).
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Abbreviations: ALL, Acute Lymphoblastic Leukemia; AML, Acute Myeloid Leukemia; ASDR, Age-standardized death rate; ASPR, Age-standardized prevalence rate; ASIR, Age-standardized incidence rate; BMI, Body-mass index; CODEm, Cause of Death Ensemble model; CLL, Chronic Lymphoblastic Leukemia; CLPD, Chronic lymphoproliferative disorders; CML, Chronic Myeloid Leukemia; CMPD, Chronic myeloproliferative disorders; DALYs, Disability-adjusted life years; GBD, Global Burden of Disease; GATHER, Guidelines for Accurate and Transparent Health Estimates Reporting; ICD, International Classification of Disease; MR-BRT, Meta-Regression-Bayesian Regularized Trimmed; MIR, Mortality to incidence ratio; NASBOD, National and Subnational Burden of Diseases, Injuries, and risk factors; PAF, Population attributable fraction; ST-GPR, Spatiotemporal Gaussian Process Regression; TMREL, Theoretical minimum risk exposure level; YLDs, Years lived with disability; YLLs, Years of life lost
Introduction
Iranians had a life expectancy of 79.6 in female individuals and 76.1 in male individuals. The 78.1% of DALYs number were due to non-communicable diseases encountered Iranian health-care system as a new challenge [1]. Cancer and malignancies are accredited for the major portion of these non-communicable diseases.
Hematologic malignancies have a great essential role in cancer global burden. Leukemia is one of the common subtypes of this heterogeneous malignancy. Leukemia is among the ten most common types of cancer worldwide (3.2% of all cancers). Men are more likely to be diagnosed with leukemia and die from leukemia compared to women. New cases of leukemia did not change significantly worldwide over the past decade, but the mortality rate of leukemia has been experiencing a 1.7% fall every year. It is showed that the lifetime risk of diagnosis with leukemia is 1.6%, and its risk increases by aging [2–4]. Although the mechanism of leukemia is not entirely demonstrated, several factors such as exposure to cancer-causing agents (chemicals), smoking, history of radiation therapy or chemotherapy, myelodysplastic syndromes, rare genetic syndromes, family history smoking, and high body-mass index (BMI) are thought to be involved [5–7].
Leukemia has two major subtypes based on the onset: acute and chronic. Acute leukemia has only two subgroups: Acute Lymphoblastic Leukemia (ALL), and Acute Myeloid Leukemia (AML). On the other hand, chronic lymphoproliferative disorders (CLPD) and chronic myeloproliferative disorders (CMPD) are two subgroups of chronic leukemia which Chronic Lymphoblastic Leukemia (CLL), and Chronic Myeloid Leukemia (CML) are the most common subtypes of them, respectively [8]. According to these subtypes of leukemia, it has a variety of mortality, incidence, prevalence, and DALYs [9]. The incident cases of leukemia in 2018 was 407,000, worldwide, with 309,000 established deaths. A study has shown between 1990 and 2017, ALL and CML experienced a decrease of incidence while CLL and AML incidences had increased in most countries. In the studied period, higher age-standardized incidence were observed in males. In addition, the incidence of leukemia in people aged above 70 has an inclining trend [10]. The trend of diseases could help us with policy decision making which could result in diseases control.
The Global Burden of Disease (GBD) project illustrates a perspective of global, regional, and national health status by assessing health statistics for several causes over a relatively long-time period [8, 11]. Here, we report the incidence, prevalence, mortality, disability-adjusted life years (DALYs), years of life lost (YLLs), and years lived with disability (YLDs) associated with leukemia in addition to attributed burden to risk factors at national and subnational levels between 1990 and 2019.
Materials and methods
In this study, we used the general approach of GBD 2019 to estimate incidence, prevalence, mortality, DALYs, YLLs, and YLDs associated with leukemia [8, 11]. The details of the GBD study and the general process of the burden estimation are further up than the scope of our study. So we review the methods from the GBD 2019 study with a focus on leukemia and the epidemiological quantities of interest. Our study is based on 5 categories of leukemia: Acute Lymphoblastic Leukemia (ALL), Acute Myeloid Leukemia (AML), Chronic Lymphoblastic Leukemia (CLL), Chronic Myeloid Leukemia (CML), and others.
Like GBD 2019, our study complies with the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER) statement. We used Python version 3.6.2, Stata version 13, and R version 3.5.0 to analyze our data [11]. We estimated incidence, prevalence, mortality, YLDs, YLLs, and DALYs—for five age groups (<5, 5 to 14, 15 to 49, 50 to 69, and ≥70); males, females, and both sexes combined. This study includes subnational analyses for each epidemiological quantity of interest.
The GBD used the International Classification of Disease (ICD) to map the cause list (including 29 cancer groups) and estimate cause-specific mortality [12]. Mapped ICD-10 codes for new cases (hospital/claim analyses) of Leukemia were: C91-C93.7, C93.9-C95.2, C95.7-C95.92, Z80.6, Z85.6 and Mapped ICD-10 codes for death due to Leukemia were C91-C91.0, C91.2-C91.3, C91.6, C92-C92.6, C93-C93.1, C93.3, C93.8, C94-C95.9 [11, 13]. As GBD 2019 study, MR-BRT (Meta-Regression-Bayesian Regularized Trimmed) was used to model the log of the ratios for each cause by age and sex. Further processed data were modeled using the Cause of Death Ensemble model (CODEm) and Spatiotemporal Gaussian Process Regression (ST-GPR) to estimate each quantity of interest by age and sex. To estimate cause-specific mortality, data were matched to the total all-cause deaths, which is calculated in GBD 2019 population, fertility, and mortality estimates. The cause-specific mortality and data of incidence registration were transformed mortality to incidence ratio (MIR). The incidence estimation was calculated by dividing leukemia-caused death by the MIR. To calculate YLDs, after estimating leukemia prevalence and survival rates, the prevalence was multiplied by specific disability. Deaths were multiplied by the life expectancy at that age to calculate YLLs. The sum of YLDs and YLLs calculated DALYs [14, 15]. DisMod-MR 2.1, a Bayesian meta-regression modeling tool, was used to assure consistency between all measured quantities [11].
The four risk factors for leukemia were smoking, high BMI, and occupational exposure to benzene and formaldehyde were considered as behavioral, metabolic and environmental/ occupational. We used published systematic reviews and meta-analyzed these relative risks to estimate relative risk as a function of exposure for each risk-outcome pair. Here in all of our risk factors were dichotomous. For each risk factor, a systematic search was conducted for published studies, household surveys, censuses, administrative data, ground monitor data, or remote sensing data to identify the relative risk of leukemia [16]. All data were fully anonymized before we accessed them. ST-GPR and DisMod-MR 2.1 were used to model the data. Standard deviation (SD) and mean were used to model dispersion and ensemble distribution measures, respectively [17, 18]. The theoretical minimum risk exposure level (TMREL) and 0 were determined as the low point of risk function for J-shaped or U-shaped risk functions and monotonically increasing risk functions. TMREL was generated by distortion of each risk-outcome pair by outcome relative global magnitude. To compute the population attributable fraction (PAF), we used the formula described in the previously published papers [8]. To prevent overestimating the PAF and the attributable burden for combinations of risks, we used the mediation matrix described in GBD 2017 [19].
Decomposition analysis was employed to find the proportion of population growth, age structure change, and incidence rate change on the overall change of incident cases from 1990 to 2019 [20].We used GBD standard population to calculate the age-standardized rate [21]. Also, each quantity point of estimation is reported with its 95% uncertainty interval (95% UI) to increase the constancy level of this study.
Results
Prevalence
The national prevalent cases of leukemia decreased from 29522 (95% UI: 15810–44076) in 1990 to 28774 (18001–35271) in 2019. Also, leukemia age-standardized prevalence rate (ASPR) decreased 21.0% (-44.4–28.9) in the same period. The prevalent cases of male with leukemia increased 1.3 fold. However, male ASPR as same as female with leukemia showed a decrease (Table 1). In these 30 years, trend of ASPR showed a decrease for first fifteen years and it started to rise after that. ASPR trend showed a constant decrease with a low slope (Fig 1). The majority proportion of ASPR were allocated to leukemia other than AML, ALL, CML, and CLL (Fig 2).
Shaded sections indicate 95% uncertainty intervals; DALYs = disability-adjusted life years.
DALYs = disability-adjusted life years.
While prevalent cases and prevalence rate of patients below 15 years old showed a significant decrease, prevalent cases and prevalence rate of patients above 15 years old increased either in male or female population. While patients aged below 5 years old had the highest prevalent cases and prevalence rate in 1990, patients aged 15 to 49 became the highest prevalent cases and patients above 70 became the highest prevalence rate in 2019 (Table 2).
Yazd, Fars, and Mazandaran had the highest ASPR among provinces in 2019 whereas Ardebil, Kurdistan, and Khorasan-e-Razavi were the highest in 1990 (Fig 3). The division of highest and lowest ASPR of provinces in 1990 was 2.5 and in 2019 was 2.7, representing an increase in provincial differences (S1 Table).
DALYs = disability-adjusted life years.
Incidence
The national incident cases of leukemia increased from 6092 (3803–8507) in 1990 to 6767 (4646–7890) in 2019. However, leukemia age-standardized incidence rate (ASIR) decreased from 11.6 (8.0–14.8) to 8.9 (6.2–10.3) per 100,000 in this exact period. Men’s incident cases of leukemia increased 1.3 fold between 1990 and 2019, though women’s incident cases of leukemia decreased 8.6% from 1990 to 2019. The ASIR decreased 33.1% and 15.1% for women and men, respectively (Table 1). The incident cases in the study period showed a decreasing trend till 2002 and a rise after that till 2019. ASIR trend showed a constant decrease in this period (Fig 1). Between 1990 and 2019, incident cases of leukemia increased by 11.1% in Iran which population growth was responsible for 44.0%, age structure change for 0.4%, and an incident change rate of -33.3%, based on the decomposition analysis (S2 Table). The majority proportion of ASIR were allocated to ALL and AML (Fig 2).
Although people aged 15 to 49 were recorded most incident cases of leukemia in 2019 (2258 [1519–2642]), with a 69.0% (37.0–120.8) increase from 1990, the highest incidence rate in 2019 were occurred among people above 70 years old (39.8 [30.7–44.9]), with 6.3% (-16.7–33.8) increase from 1990 (Table 2).
While Tehran, Khorasan-e-Razavi, and Fars were the three provinces with the highest new cases of leukemia, Fars, Yazd, and Khorasan-e-Razavi showed the highest leukemia ASIR, in 2019 (S2 Table and Fig 3). The division of highest and lowest ASIR of provinces in 1990 was 2.0 and in 2019 was 1.9, representing a slightly decrease in provincial differences (S1 Table).
Mortality
At the national level, deaths due to leukemia increased 1.3-fold between 1990 and 2019, from 3287 (2284–4201) to 4424 (3137–5030), whereas the age-standardized death rate (ASDR) decreased statistically significant from 8.3 (6.1–9.8) in 1990 to 6.0 (4.3–6.8) per 100,000 in 2019 (Table 1). The death number during this period remained the same till 2002, and it started to increase after that. Though, ASDR showed a decreasing trend in the same period (Fig 1). The highest proportion of ASDR was allocated to AML followed by ALL (Fig 2).
In 2019, leukemia deaths number increased in people aged above 15 and decreased in people aged below 15. Death rate had a decreasing trend in all age groups between 1990 and 2019 except men aged above 70, who had the highest death rate among all age groups, over the study period (Table 2).
Khorasan-e-Razavi remained the highest ASDR between 1990 and 2019 and followed by East Azerbaijan and Fars in 2019 (Fig 3). The division of highest and lowest ASDR of provinces in 1990 was 1.8 and in 2019 was 1.6, hence it shows a decrease in provincial differences (S1 Table).
Leukemia attributed ASDR to smoking decreased statistically significant (-25.8% [-39.2–0.3]), but attributed ASDR to high BMI increased in the study period (25.3% [-1.3–73.8]). Although leukemia attributed ASDR to occupational exposure to benzene and formaldehyde were inappreciable, they were increased and decreased non-statistically significant in the study period (1.3% [-18.1–33.2] and -16.0% [-34.5–12.5], respectively). The primary risk factor for leukemia attributed ASDR in men and women were smoking and high BMI, respectively (Table 3).
DALYs, YLLs, and YLDs
In the study period, total leukemia DALYs decreased 12.2% (-34.6–19.0) and reached 162850 (110681–188806) in 2019. The age-standardized DALYs rate decreased statistically significant by 36.7% (-50.4–17.4) from 324.3 (224.8–413.4) per 100,000 in 1990 to 205.3 (140.3–237.8) in 2019 (Table 1). The DALYs trend showed a decrease till 2002 then it increased for nearly ten years, and a decreasing trend started afterward (Fig 1). AML and ALL had the highest allocation of age-standardized DALYs rate (Fig 2).
Leukemia age-standardized DALYs rate were highest in Khorasan-e-Razavi, Yazd, and Hamadan (Fig 3). The division of highest and lowest age-standardized DALYs rate of provinces in 1990 was 2 and in 2019 was 1.7, illustrating a decrease in provincial differences (S1 Table).
Leukemia attributed age-standardized DALYs rate to smoking decreased statistically significant (-30.2% [-42.8–6.0]). However, attributed age-standardized DALYs rate to high BMI increased in the study period (20.3% [-2.8–70.1]). Smoking was a prominent risk factor for leukemia based on the attributed age-standardized DALYs rate in men, and high BMI was a primary risk factor in women (Table 3).
Total leukemia YLLs showed a 12.7% (-34.9–18.4) decrease from 182629 (119070–246118) in 1990 to 159421 (108624–184563) in 2019. Also, the age-standardized YLLs rate decreased 37.0% (-50.7–17.9) from 318.8 (221.1–407.4) per 100,000 to 200.8 (137–232.6) in the study period (Table 1). The three highest age-standardized YLLs rates were Khorasan-e-Razavi, Fars, and Hamadan in 2019, which Khorasan-e-Razavi stayed province with the highest age-standardized YLLs since 1990 (Fig 3). In the study period, while leukemia attributed age-standardized YLLs rate to high BMI increased (19.5% [-3.6–69.0]), leukemia attributed age-standardized YLLs rate to smoking, and occupational exposure to formaldehyde decreased by -30.8% (-43.2–6.9) and -15.4% (-34.1–13.4), respectively. Smoking with attributed age-standardized YLLs rate of nearly 40 per 100,000 and high BMI with nearly 15 per 100,000 were prominent risk factors in men and women, respectively (Table 3).
While the total YLDs increased 16.9% (-18.6–58.9) in the study period, the age-standardized YLDs rate decreased 17.7% (-37.4–21.8) (Table 1). Yazd, Fars, and Bushehr were the three provinces with the highest age-standardized YLDs rate in 2019 (Fig 3). In the study period, while leukemia attributed age-standardized YLDs rate to high BMI (67.7% [32.7–142.0]) and occupational exposure to benzene (46.3% [15.2–106.5]) and formaldehyde (20.4% [-7.6–72.3]) increased, leukemia attributed age-standardized YLDs rate to smoking decreased by 3.2% (-22.9–37.6). Smoking with attributed age-standardized YLDs rate of 1.07 per 100,000 was a prominent risk factor in men, and high BMI with 0.38 per 100,000 was a prominent risk factor in women (Table 3).
Discussion
This study used the GBD 2019 study results to analyze the national and subnational burden of leukemia in 31 provinces [8, 11]. Before our study, the mortality of leukemia was assessed in the National and Subnational Burden of Diseases, Injuries, and risk factors (NASBOD) [22]. Their results were different from our study in some aspects because of different methods and data sources. GBD 2019 used mathematical models and the updated cancer mortality to made estimation on leukemia more robust. The code models and covariates used in those were adjusted for GBD 2019. These modulations make our study more comprehensive and precise.
Our results showed that while the incidence of leukemia is experiencing an increasing trend in Iran, the ASIR is constantly decreasing over the study period. In global studies it has been demonstrated that the incidence of leukemia and ASIR had been observed the same trend as Iran [10]. In comparison with all hematologic malignancies which increased ASIR during 1990 to 2017, our study showed a decrease of ASIR [23]. The total death number of leukemia showed an increase, resulting from population growth, though the ASDR decreased in all provinces. The new chemotherapy regimens over past decades improved leukemia survival in most patients, which could be a probable cause for decreasing trend of ASDR [24–26]. Age-standardized DALYs rate showed a similar declining trend to ASDR since mortality of leukemia generates a significant proportion of leukemia DALYs. Also, the age-standardized YLLs rate decreased, whereas the age-standardized YLDs rate increased between 1990 and 2019. Global results of hematological malignancies supported this study and showed decrease of ASDR and DALYs in general between 1990 to 2017. Attributed age-standardized deaths, DALYs, YLLs, and YLDs rate to high BMI was increasing while smoking and occupational exposure to benzene and formaldehyde were decreasing in the study period. The Global Burden of leukemia has been assessed in a very recent study. They resulted decreased age-standardized rate of DALYs and deaths and increased age-standardized incidence rate, which Iran national and subnational results support global findings except the overall age-standardized incidence rate of hematological malignancies. In which besides leukemia, other hematological malignancies burden were assessed [23].
A significant decrease was observed in age-standardized leukemia incidence, which may have been at least partly driven by reduced exposure to risk factors, high-risk behavioral avoidance, and increased intake of folate and vitamins. This decrease of ASIR in leukemia has been in contrast in all hematological malignancies however, leukemia were exception in the recent global, regional, and national study of hematologic malignancies [23]. The study results were supported by that also, both studies claimed the increase of the incidents which may be due to the fact that new screening strategies has been developed [27, 28]. However, the lesser screening in Iran in comparison with developed countries brought the idea of higher ASIR in Iran which should be further investigated.
Leukemia mortality burden leveled off in this study period, probably after improvements of diagnosis at earlier stages and implementations of newer chemotherapy and treatment regimens [24]. However, in some provinces, non-guideline care is still common. Hence, leukemia outcomes could be improved by adherence to guideline recommendations. It has been shown in previous publications that improving access to healthcare services could control and decrease mortality of leukemia [29]. To further mortality of leukemia decrease, improvements in healthcare infrastructure, accessibility and education are required. Health inequalities between male and female, also between elderly and others should be minimized to improve the outcome of the leukemia and reduce mortality rate even more.
The national and subnational DALYs of leukemia decreased between 1990 and 2019 since the significant proportion of leukemia DALYs is associated with the mortality and YLLs of leukemia. Global study of hematological malignancies supported our findings of DALYs [23]. To reach further success in leukemia DALYs reduction and the burden control, we should first provide health equalities for all people around Iran, in all 31 provinces, with different socio-demographic statuses. Then, earlier diagnosis of leukemia should be prioritized through improving screening practices.
Based on the GBD database, we analyzed smoking, high BMI, and exposure to benzene and formaldehyde as possible risk factors for leukemia. Based on our findings about attributable risk factors, smoking was the first risk factor for men and the second for women. There are 1.3 billion smokers in the world, of whom men were five times more than women. The higher risk of childhood leukemia with paternal smoking status is reported in a study in 2019 [30]. High BMI was the first risk factor for women. In a cohort study, high BMI was associated with a higher mortality rate [31]. Hyperinsulinemia, high interstitial levels of adipocyte-released fuels, and chronic inflammation due to obesity are probable reasons for poorer outcomes of high BMI [32]. Benzene and formaldehyde, chemical reagents, have different genotoxic effects and chromosomal effects in carcinogenesis [22]. Maternal exposure during pregnancy is demonstrated to increase the risk of leukemia. Also, a higher concentration of benzene and formaldehyde existed in leukemia patients compared to controls [33]. This finding underlined the priority of environmental protection to reduce leukemia outcomes. So the dietary structure and behavioral risk factors should be controlled in order to control leukemia outcomes. Our results showed that in Iran, they were able to reduced exposure to smoking and occupational carcinogens but, poor control BMI in this country is increasing and followed consequences are visible. Hence, further policies and interventions are required to overcome this obstacle.
In addition, the annual repetition of GBD provides the required data and results to find out trends in the burden of diseases over time and hand over data to policymakers to assess the impact of their health programs and policies and compare their results within their region. In each round of GBD study, it improves its estimation by modulating its modeling process and adding new data resources. Innovative policies should take place to reduce the burden of the disease. First of all, no matter of gender, age, and province of residential equality in cancer care for all patients should be provided. All family physicians should be educated the early red flags of leukemia and refer the patients as soon as possible to a hemato-oncologist. Infrastructure of administrating the guideline treatments for every patient should be provided.
Strengths and limitations
The first and the most important strength of this study was that this study was the first study to address and illustrate the national and subnational burden of leukemia and its risk factors. Furthermore, MR-BRT, CODEm and ST-GPR were used to model our data and estimate the burden of leukemia. This study would help to have a better understanding of leukemia burden and to reduce controversies of leukemia across the country. Several limitations remain obstacles, such as different disease-coding system mapping systems, non-informative or wrongly-coded diseases redistribution, and modeling the inadequate data, which could be addressed by improving methods and registrations.
Conclusion
In this study, the age-standardized prevalence, incidence, mortality, and disability-adjusted life years (DALYs) rate of leukemia demonstrated a significant decrease over a 30-year period in Iran. The disparities observed between provinces were reduced, with the exception of prevalence. This emphasizes the need for policymakers to prioritize and emphasize access to healthcare and oncological treatments. The reductions observed may be attributed to advancements in treatment approaches and screening programs. It appears that some provinces in Iran have better control and treatment of leukemia, which may be linked to higher income and socioeconomic status, as well as unequal distribution and accessibility of healthcare professionals and systems. The leukemia estimates obtained through the Global Burden of Disease (GBD) study can be used to evaluate progress in cancer management and equity improvements across the country over a 30-year period.
Supporting information
S1 Table. Age-standardized rate of leukemia’s burden by sex and year at provincial level with percent change.
https://doi.org/10.1371/journal.pone.0287917.s001
(PDF)
S2 Table. Decomposition analysis of incident cases of leukemia by sex at national and provincial levels.
https://doi.org/10.1371/journal.pone.0287917.s002
(PDF)
Acknowledgments
We appreciate the aid of all colleagues in Non-communicable Diseases Research Center (NCDRC), and Endocrinology and Metabolism Research Institute, in Tehran University of Medical Sciences
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