Pattern of weight gain in pregnant women in slum areas of Hamadan using multilevel ordinal regression.

BACKGROUND: Adequate gestational weight gain (GWG) is an important factor for maternal and fetal health. This is especially important in low-income and slum areas due to limited access to health services and malnutrition. Thus, the purpose of this study is to evaluate the pattern of GWG changes in the slum areas of Hamadan in Iran. METHODS: In this longitudinal study, the study sample consisted of 509 pregnant women who referred to nine health care clinics in the slum areas of Hamadan. Women's weight gain based on the recommended GWG by U.S. Institute of Medicine (IOM) was divided into three categories: Inadequate weight gain, Adequate weight gain, and Excessive weight gain. In order to evaluate the trend of GWG, a multi-level ordinal model was used. RESULTS: According to pre-pregnancy BMI, a little more than half people (56.6%) were overweight or obese. 85.4% women in the first trimester and 49.1% in the second trimester did not have adequate GWG, but in the third trimester (38.9%) had adequate GWG. Based on multivariate analysis, pre- pregnancy BMI has a significant effect on the odds of inadequate GWG (P-value = 0.021); with one unit increase in pre-pregnancy BMI, the odds of inadequate GWG grows by 1.07 times compared to adequate and excessive GWG. CONCLUSIONS: In general, women did not have adequate weight gain in the first and second trimesters.Thus, designing appropriate interventions to achieve optimal GWG seems to be necessary in slums.

Zero-augmented beta-prime model for multilevel semi-continuous data: a Bayesian inference.

Semi-continuous data characterized by an excessive proportion of zeros and right-skewed continuous positive values appear frequently in medical research. One example would be the pharmaceutical expenditure (PE) data for which a substantial proportion of subjects investigated may report zero. Two-part mixed-effects models have been developed to analyse clustered measures of semi-continuous data from multilevel studies. In this study, we propose a new flexible two-part mixed-effects model with skew distributions for nested semi-continuous cost data under the framework of a Bayesian approach. The proposed model specification consists of two mixed-effects models linked by the correlated random effects: Part I) a model on the occurrence of positive values using a generalized logistic mixed model; and Part II) a model on the magnitude of positive values using a linear mixed model where the model errors follow skew distributions including beta-prime (BP). The proposed method is illustrated with pharmaceutical expenditure data from a multilevel observational study and the analytic results are reported by comparing potential models under different skew distributions. Simulation studies are conducted to assess the performance of the proposed model. The DIC3, LPML, WAIC, and LOO as the Bayesian model selection criteria and measures of divergence used to compare the models.

Health and economic impacts of ambient air particulate matter (PM2.5) in Karaj city from 2012 to 2019 using BenMAP-CE.

The present study aims to estimate the effects of PM2.5 on the health and economy of Karaj city from 2012 to 2019. In this study, mortality attributed to long-term exposure to PM2.5 and its spatial distribution in Karaj over the 2012-2019 period were estimated using the Global Exposure Mortality Model (GEMM) concentration-response function and BenMAP software. PM2.5 hourly concentration data of air quality monitoring stations were used to estimate PM2.5 for the whole city of Karaj. The economic effects of this pollutant were also assessed using the value of statistical life (VSL) method. The results showed that the annual average PM2.5 concentration during the studied time increased and was higher than the air quality guideline levels recommended by the World Health Organization. Also, the annual number of deaths attributed to PM2.5 in adults (older than 25 years) was estimated to be about 1200. The highest to lowest proportions of PM2.5-related deaths were non-accidental mortality, ischemic heart attack, stroke, acute respiratory tract infection, chronic obstructive pulmonary disease (COPD), and lung cancer, in the order of their appearance. The results showed that the economic loss attributed to this pollutant was estimated at 380 to 504 million USD per year. Due to the effects of PM2.5 on health and the economy in this city, we suggest conducting special planning to control and reduce the concentration of ambient air particulate matter by improving the public transportation system and updating industrial processes.

Prevalence of renal scaring caused by urinary tract infections in children: a systematic review and meta-analysis.

PURPOSE. SOURCES OF INFORMATION: Urinary tract infection (UTI) is the second most common infection in children, the most important complication of which is renal scarring. The aim of present study was to evaluate the prevalence of renal scarring after UTI in children through systematic review and meta-analysis. METHODS: The international databases of Science Direct, PubMed, Scopus, and Web of Science and the Google Scholar search engine were searched using standard keywords. The sources found were from 2010 to 2020 and the search stage was updated until 2021.02.16. Data were analyzed using STATA-14 software and the significance level was considered at P<0.05. RESULTS: In 29 studies with a sample size of 9,986 children, the prevalence of renal scarring in children was estimated at 35% (95% CI: 29-41). Also, the prevalence of renal scarring was in girls 61% (95% CI: 40-81) and in boys 34% (95% CI: 11-57). The prevalence of unilateral renal scarring in children was 56% (95% CI: 48-65) and bilateral renal scarring was 31% (95% CI: 14-48). In addition, the prevalence of scar was 54% in children with reflux and 12% in children without vesicoureteral reflux. CONCLUSIONS: More than one third of people under the age of 18 after UTI have renal scarring. The prevalence of this complication in girls is about 2 times higher than that in boys and in people with reflux, it is about 4 times higher than people who do not have urinary reflux. Also, about half of people under the age of 18 suffer from unilateral renal scarring and about one third of them suffer from bilateral renal scarring.

Robust inference in the joint modeling of multilevel zero-inflated Poisson and Cox models.

A popular method for simultaneously modeling of correlated count response with excess zeros and time to event is by means of the joint models. In these models, the likelihood-based methods (such as expectation-maximization algorithm and Newton-Raphson) are used for estimating the parameters, but in the presence of contaminations, these methods are unstable. To overcome this challenge, we extend the M-estimator methods and propose a robust estimator approach to obtain a robust estimation of the regression parameters in the joint model. Our proposed algorithm has two steps (Expectation and Solution). In the expectation step, the likelihood function is expected by conditioning on the observed data and in the solution step, the parameters are computed, with solving robust estimating equations. Therefore, this algorithm achieves robustness by applying robust estimating equations and weighted likelihood in the S-step. Simulation studies under various situations of contaminations show that the robust algorithm gives us consistent estimates with a smaller bias than likelihood-based methods. The application section uses data on factors affecting fertility and birth spacing.

Identifying factors associated with the hospital readmission rate among patients with major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) is a common recurrent mental disorder and one of the leading causes of disability in the world. The recurrence of MDD is associated with increased psychological and social burden, limitations for the patient, family, and society; therefore, action to reduce and prevent the recurrence of this disorder or hospital readmissions for depression among the patients is essential. METHODS: The data of this retrospective cohort study were extracted from records of 1005 patients with MDD hospitalized in Farshchian hospital in Hamadan city, Iran (2011-2018). The hospital readmissions rate due to depression episodes was modeled using generalized Poisson regression (GPR). Demographic and clinical characteristics of the patients were considered as explanatory variables. SAS v9.4 was used (P < 0.05). RESULTS: A majority of the patients were male (66.37%). The mean (standard deviation) of age at onset of MDD and the average number of hospital readmissions were 32.39 (13.03) years and 0.53 (1.84), respectively (most patients (74.3%) did not experience hospital readmissions). According to the results of the GPR, the lower age at the onset of the disease (IRR = 1.02;P = 0.008), illiteracy (IRR = 2.06;P = 0.003), living in urban areas (IRR = 1.56;P = 0.015), history of psychiatric illnesses in the family (IRR = 1.75;P = 0.004), history of emotional problems (IRR = 1.42;P = 0.028) and having medical disorders (IRR = 1.44;P = 0.035) were positively associated with the number of hospitalizations. CONCLUSION: According to our findings, urbanization, early onset of the disease, illiteracy, family history of mental illness, emotional problems, and medical disorders are among major risk factors associated with an increased number of hospital readmissions of MDD.

Investigating the effect of behavioral and demographic characteristics of Iranian women on the number of children ever born.

Background: The number of children ever born (CEB) to a woman, as an index of her fertility behavior, are interesting for the governments and demographer policymakers. In recent years, a notable reduction of fertility and population aging in Iran has caused concern among politicians, and it has led to starting new changes in demographic policies. Therefore, to adopting new demographic and health policies programs, identification of factors that affecting CEB is essential. Methods: To evaluate determinant factors on CEB, information of 20093 married Iranian women aged between 15 and 54 years has been analyzed from the Iranian National Institute of Health Research survey. Based on the structure of data and the possible influential unobserved population heterogeneity on CEB in each city and province, a multilevel count regression model was applied. The analysis was performed using the 'R' software (version 3.5) with a significant level of 0.05. Results: Findings show that the mean and median number of CEB was 2.82 and 2.00 for all women, respectively. Meanwhile, these values were 4.56 and 4.00 for the women who reached menopause. There was a significant unobserved heterogeneity affecting CEB in each province (σp=0.018). Also, the results of the multilevel model show that living in an urban area (RR=0.90), higher age at first marriage (RR=0.96), higher education (RR=0.84, RR=0.81), and exposure to mass media (RR=0.87) decrease the risk ratio of the number of CEB (p <0.001). Conclusion: It seems that the tendency of women to academic education and their access to mass media has a significant effect on reducing childbearing. Therefore, in future planning, attention to these two factors can be useful and helpful to move to increase fertility.

Mapping Drug Prescription, Polypharmacy, and Pharmaceutical Spending in Older Adults in Iran: A Multilevel Analysis Based on Claims Data.

Background: To date, comprehensive data on drug utilization in Iranian people are lacking. The purpose of this study was to graphically describe drug prescription, polypharmacy, and pharmaceutical spending in > 3 million Iranian elderly people. Methods: In this multilevel cross-sectional study, using administrative claims data provided by the Iran Health Insurance Organization (IHIO), we assessed drug claims and drug costs in 2018 in >3 million individuals living in Iran and who have been insured with health insurance (Bimeh Salamat). In particular, we analyzed the prevalence of polypharmacy and pharmaceutical spending use according to the annual Report of Iranian Health Insurance Organization. Multilevel ordinal logistic and multilevel beta regression models were used to analyze the data. Significance level was set as P ≤ .05 and CI at 95%. Results: Nationally, the mean number of drug prescriptions per patient was 1.46 (SD, 0.81). The mean number of prescribed drugs per patient was 4.32 (SD, = 3.04). The drug cost for each elderly patient was $6.86 (interquartile range (IQR), 12.26), with $4.96 and $1.76 for the insurance and the insured shares, respectively. For elderly women, the odds of polypharmacy (excessive and nonexcessive vs no polypharmacy) were 1.164 (95% CI, 1.142 to 1.186) times that of elderly men. In addition, in the spring season, the odds of polypharmacy were 1.274 (95% CI, 1.241 to 1.309) times that of the winter. Similarly, polypharmacy was strongly higher among patients who had noncommunicable diseases (OR, 2.174; 95% CI, 2.069 to 2.275 (P < 0.001)). Conclusion: The high prevalence of hyper prescription in Iran elderly people may indicate a need for interventions aiming at deprescribing drugs with an unfavorable benefit-risk profile. The best practice guidelines should be developed for improved medical practice in the prescription of medications for such a vulnerable population.

Pattern and determinant factors of birth intervals among Iranian women: a semi-parametric multilevel survival model.

The interval between successive pregnancies (birth interval) is one of the main indexes used to evaluate the health of a mother and her child. This study evaluated birth intervals in Iran using data from the Iranian Multiple Indicators Demographic and Health Survey (IrMIDHS) conducted in 2010-2011. A total of 20,093 married Iranian women aged 15-54 years from the whole country constituted the study sample. Based on the nature of sampling and the unobserved population heterogeneity for birth intervals in each city and province, a multilevel survival frailty model was applied. Data were analysed for women's first three birth intervals. The median first and second birth intervals were 30.3 and 39.7 months respectively. Higher education, Caesarean delivery, contraceptive use and exposure to public mass media were found to decrease the hazard rate ratio (HRR) of giving birth. Meanwhile, higher monthly income increased the hazard of giving birth. The results suggest that public mass media can play an effective role in encouraging women to have the recommended birth interval. Furthermore, increasing family income could encourage Iranian couples to decrease the time to their next birth.

Association between psychosocial, organizational and personal factors and prevalence of musculoskeletal disorders in office workers.

The purpose of this study was to investigate the relationship between organizational and personal (individual) factors with the prevalence of musculoskeletal disorders (MSDs) in office workers of the Iranian Gas Transmission Company. The participants rated two questionnaires - the standardized Nordic Musculoskeletal Questionnaire to measure the prevalence of MSDs, and the Veterans Healthcare Administration All Employee Survey questionnaire (2004 version) - to measure psychosocial, organizational and individual aspects of job satisfaction and workplace climate. The highest prevalence of MSDs was found in the lower back (49.7%) and neck (49.0%) regions. Results of the logistic regression models showed that some psychosocial and organizational factors and also some individual factors were associated with prevalence of MSDs (p < 0.05).These findings illustrate the need to consider all elements of the work system as a whole in future studies and in organizational planning.

A two-component Bayesian mixture model to identify implausible gestational age.

Background: Birth weight and gestational age are two important variables in obstetric research. The primary measure of gestational age is based on a mother's recall of her last menstrual period. This recall may cause random or systematic errors. Therefore, the objective of this study is to utilize Bayesian mixture model in order to identify implausible gestational age. Methods: In this cross-sectional study, medical documents of 502 preterm infants born and hospitalized in Hamadan Fatemieh Hospital from 2009 to 2013 were gathered. Preterm infants were classified to less than 28 weeks and 28 to 31 weeks. A two-component Bayesian mixture model was utilized to identify implausible gestational age; the first component shows the probability of correct and the second one shows the probability of incorrect classification of gestational ages. The data were analyzed through OpenBUGS 3.2.2 and 'coda' package of R 3.1.1. Results: The mean (SD) of the second component of less than 28 weeks and 28 to 31 weeks were 1179 (0.0123) and 1620 (0.0074), respectively. These values were larger than the mean of the first component for both groups which were 815.9 (0.0123) and 1061 (0.0074), respectively. Conclusion: Errors occurred in recording the gestational ages of these two groups of preterm infants included recording the gestational age less than the actual value at birth. Therefore, developing scientific methods to correct these errors is essential to providing desirable health services and adjusting accurate health indicators.

Two-part zero-inflated negative binomial regression model for quantitative trait loci mapping with count trait.

Poisson regression models provide a standard framework for quantitative trait locus (QTL) mapping of count traits. In practice, however, count traits are often over-dispersed relative to the Poisson distribution. In these situations, the zero-inflated Poisson (ZIP), zero-inflated generalized Poisson (ZIGP) and zero-inflated negative binomial (ZINB) regression may be useful for QTL mapping of count traits. Added genetic variables to the negative binomial part equation, may also affect extra zero data. In this study, to overcome these challenges, I apply two-part ZINB model. The EM algorithm with Newton-Raphson method in the M-step uses for estimating parameters. An application of the two-part ZINB model for QTL mapping is considered to detect associations between the formation of gallstone and the genotype of markers.

Supervised wavelet method to predict patient survival from gene expression data.

In microarray studies, the number of samples is relatively small compared to the number of genes per sample. An important aspect of microarray studies is the prediction of patient survival based on their gene expression profile. This naturally calls for the use of a dimension reduction procedure together with the survival prediction model. In this study, a new method based on combining wavelet approximation coefficients and Cox regression was presented. The proposed method was compared with supervised principal component and supervised partial least squares methods. The different fitted Cox models based on supervised wavelet approximation coefficients, the top number of supervised principal components, and partial least squares components were applied to the data. The results showed that the prediction performance of the Cox model based on supervised wavelet feature extraction was superior to the supervised principal components and partial least squares components. The results suggested the possibility of developing new tools based on wavelets for the dimensionally reduction of microarray data sets in the context of survival analysis.

Zero-Inflated Count Regression Models in Solving Challenges Posed by Outlier-Prone Data; an Application to Length of Hospital Stay.

Introduction: Ignoring outliers in data may lead to misleading results. Length of stay (LOS) is often considered a count variable with a high frequency of outliers. This study exemplifies the potential of robust methodologies in enhancing the accuracy and reliability of analyses conducted on skewed and outlier-prone count data of LOS. Methods: The application of Zero-Inflated Poisson (ZIP) and robust Zero-Inflated Poisson (RZIP) models in solving challenges posed by outlier LOS data were evaluated. The ZIP model incorporates two components, tackling excess zeros with a zero-inflation component and modeling positive counts with a Poisson component. The RZIP model introduces the Robust Expectation-Solution (RES) algorithm to enhance parameter estimation and address the impact of outliers on the model's performance. Results: Data from 254 intensive care unit patients were analyzed (62.2% male). Patients aged 65 or older accounted for 58.3% of the sample. Notably, 38.6% of patients exhibited zero LOS. The overall mean LOS was 5.89 (± 9.81) days, and 9.45% of cases displayed outliers. Our analysis using the RZIP model revealed significant predictors of LOS, including age, underlying comorbidities (p<0.001), and insurance status (p=0.013). Model comparison demonstrated the RZIP model's superiority over ZIP, as evidenced by lower Akaike information criteria (AIC) and Bayesians information criteria (BIC) values. Conclusions: The application of the RZIP model allowed us to uncover meaningful insights into the factors influencing LOS, paving the way for more informed decision-making in hospital management.

Longitudinal machine learning model for predicting systolic blood pressure in patients with heart failure.

Objective: Systolic blood pressure (SBP) strongly indicates the prognosis of heart failure (HF) patients, as it is closely linked to the risk of death and readmission. Hence, maintaining control over blood pressure is a vital factor in the management of these patients. In order to determine significant variables associated with changes in SBP over time and assess the effectiveness of classical and machine learning models in predicting SBP, this study aimed to conduct a comparative analysis between the two. Methods: This retrospective cohort study involved the analysis of data from 483 patients with HF who were admitted to Farshchian Heart Center located in Hamadan in the west of Iran, and hospitalized at least two times between October 2015 and July 2019. To predict SBP, we utilized a linear mixed-effects model (LMM) and mixed-effects least-square support vector regression (MLS-SVR). The effectiveness of both models was evaluated based on the mean absolute error and root mean squared error. Results: The LMM analysis revealed that changes in SBP over time were significantly associated with sex, body mass index (BMI), sodium, time, and history of hypertension (P-value < 0.05). Furthermore, according to the MLS-SVR analysis, the four most important variables in predicting SBP were identified as history of hypertension, sodium, BMI, and triglyceride. In both the training and testing datasets, MLS-SVR outperformed LMM in terms of performance. Conclusions: Based on our results, it appears that MLS-SVR has the potential to serve as a viable alternative to classical longitudinal models for predicting SBP in patients with HF.

Balance-energy of resting state network in obsessive-compulsive disorder.

Stability of the brain functional network is directly linked to organization of synchronous and anti-synchronous activities. Nevertheless, impact of arrangement of positive and negative links called links topology requires to be well understood. In this study, we investigated how topology of the functional links reduce balance-energy of the brain network in obsessive-compulsive disorder (OCD) and push the network to a more stable state as compared to healthy controls. Therefore, functional associations between the regions were measured using the phase synchrony between the EEG activities. Subsequently, balance-energy of the brain functional network was estimated based on the quality of triadic interactions. Occurrence rates of four different types of triadic interactions including weak and strong balanced, and unbalanced interactions were compared. In addition, impact of the links topology was also investigated by looking at the tendency of positive and negative links to making hubs. Our results showed although the number of positive and negative links were not statistically different between OCD and healthy controls, but positive links in OCDs' brain networks have more tendency to make hub. Moreover, lower number of unbalanced triads and higher number of strongly balanced triad reduced the balance-energy in OCDs' brain networks that conceptually has less requirement to change. We hope these findings could shed a light on better understanding of brain functional network in OCD.

Musculoskeletal disorders among female carpet weavers in Iran.

The aim of this study was to determine factors associated with self-reported upper extremity musculoskeletal disorders (UEMSDs) among female carpet weavers. Data on demographic characteristics and workplace factors were collected from 626 female carpet weavers. Type of carpet weaving looms, weaving style (Persian vs. Turkish), daily working hours and work experience as well as personal factors including age and marital status were significantly and independently associated with self-reported UEMSDs (p < 0.05), while education, handedness and weight of weaving comb were not. A major finding of this study was the significant association between weaving style and UEMSDs. Better measures of the biomechanical requirements of carpet weaving tasks in Persian and Turkish weaving types are required to understand better their influences on the health of weavers and on UEMSDs in particular. Poor workstation design, in particular, design inappropriate for the anthropometric dimensions of weavers, was a major risk factor for musculoskeletal symptoms in carpet weaving. Therefore, this industry should develop equipment adapted to women's sizes and shapes. PRACTITIONER SUMMARY: This article provides an insight into the risk factors associated with self-reported UEMSDs among female carpet weavers, identifying major factors associated with upper extremity musculoskeletal symptoms and exploring guidelines for designing weaving workstations.

Comparative study of laminin332-γ2 chain expression in oral lichen planus and squamous cell carcinoma by immunohistochemistry.

BACKGROUND: Classification of oral lichen planus (OLP) as a condition with malignant potential is still controversial. One of the major properties of malignancy is invasion. Ln332-γ2 chain plays a critical role in invasive activity of cancer cells. This study aims to compare Ln332-γ2 chain expression in OLP, oral epithelial dysplasia (OED) and oral squamous cell carcinoma (OSCC). METHODS: Ln332-γ2 expression was evaluated in 16 epithelial hyperplasia with no dysplasia (group A), 16 OLP (group B), 18 OED (group C) and 18 OSCC (group D) by immunohistochemistry. RESULTS: Except in A group, Ln332-γ2 expression was detected in other groups. There was a significant difference in Ln332-γ2 expression among B, C and D groups as well as between B and D, C and D groups (P<0.001). However, there was no significant difference between B and C groups (P=0.999). CONCLUSIONS: According to the findings of this study, the likelihood of similarity of OLP with premalignant dysplastic lesion can be suggested. This is not corroborating OLP definitive transformation to an OSCC. But it might be advisable that OLPs with >10% Ln332- γ2 expression may have a higher risk of cellular invasion occurrence and malignant transformation.

Modeling of smoking intensity by age at smoking onset among Iranian adult male using generalized additive model.

Because the age at which a person first starts smoking has such a strong correlation with future smoking behaviours, it's crucial to examine its relationship with smoking intensity. However, it is still challenging to accurately prove this relationship due to limitations in the methodology of the performed studies. Therefore the main purpose of this study is to evaluate the potential risk factors affecting the intensity of smoking, especially the age of smoking onset among Iranian adult male smokers over 18 years of age using a generalized additive model (GAM). In GAM a latent variable with logistic distribution and identity link function was considered. Data from 913 Iranian male current smokers over the age of 18 was evaluated from a national cross-sectional survey of non-communicable disease (NCD) risk factors in 2016. Individuals were classified into: light, moderate, and heavy smokers. A GAM was used to assess the relationship. The results showed that 246 (26.9%) subjects were light smokers, 190 (20.8%) subjects were moderate smokers and 477 (52.2%) subjects were heavy smokers. According to the GAM results, the relationship was nonlinear and smokers who started smoking at a younger age were more likely to become heavy smokers. The factors of unemployment (OR = 1.364, 95% CI 0.725-2.563), retirement (OR = 1.217, 95% CI 0.667-2.223), and exposure to secondhand smoke at home (OR = 1.364, 95% CI 1.055-1.763) increased the risk of heavy smoking. but, smokers with high-income (OR = 0.742, 95% CI 0.552-0.998) had a low tendency to heavy smoking. GAM identified the nonlinear relationship between the age of onset of smoking and smoking intensity. Tobacco control programs should be focused on young and adolescent groups and poorer socio-economic communities.

Assessing the Factors Affecting Cesarean Section Selection in Iranian Women Using Multilevel Count Models with Excess Zeros.

BACKGROUND: Iran has ranked second in the frequency of cesarean delivery (CD) and this rate in 2014 has increased by 56 percent. The CD has multiple complications for the woman and newborn, and due to the women's readmission after surgery impose additional costs to the countries. Although CD has many complications and is not recommended by obstetrician and midwives; some factors affect the choice of this method of delivery. METHODS: We used data from the Iranian Institute for Health Sciences Research (IIHSR) in 2015. We studied the effects of factors such as socioeconomic and demographic factors and supplemental insurance status in the choice of CD. We used multilevel Zero-Inflated models for the modeling of data. RESULTS: The employed women resident in urban areas with the high-income and age greater than 34-yr old and supplemental insurance more likely chose CD. On the other hand, women with high education level, women who use at least one media (e.g. Radio, television, etc.) and women that use contraceptive methods have chosen the less CD. CONCLUSION: Our findings highlighted the importance of supplemental insurance and socio-economic status in choosing a CD by women. However, in some cases especially in the rich class of society, the high cost of this type of delivery does not affect the choice decrease of it, and governments should adopt rigorous policies in using this method.