Journal of Preventive Medicine and Public Health

Original Articles

Modeling Survival in Patients With Brain Stroke in the Presence of Competing Risks: Solmaz Norouzi, Mohammad Asghari Jafarabadi, Seyed Morteza Shamshirgaran, Farshid Farzipoor, Ramazan Fallah; J Prev Med Public Health. 2021;54(1):55-62. Published online December 7, 2020; DOI: https://doi.org/10.3961/jpmph.20.463

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Abstract PDF: Objectives
After heart disease, brain stroke (BS) is the second most common cause of death worldwide, underscoring the importance of understanding preventable and treatable risk factors for the outcomes of BS. This study aimed to model the survival of patients with BS in the presence of competing risks.
Methods
This longitudinal study was conducted on 332 patients with a definitive diagnosis of BS. Demographic characteristics and risk factors were collected by a validated checklist. Patients’ mortality status was investigated by telephone follow-up to identify deaths that may be have been caused by stroke or other factors (heart disease, diabetes, high cholesterol, etc.). Data were analyzed by the Lunn-McNeil approach at alpha=0.1.
Results
Older age at diagnosis (59-68 years: adjusted hazard ratio [aHR], 2.19; 90% confidence interval [CI], 1.38 to 3.48; 69-75 years: aHR, 5.04; 90% CI, 3.25 to 7.80; ≥76 years: aHR, 5.30; 90% CI, 3.40 to 8.44), having heart disease (aHR, 1.65; 90% CI, 1.23 to 2.23), oral contraceptive pill use (women only) (aHR, 0.44; 90% CI, 0.24 to 0.78) and ischemic stroke (aHR, 0.52; 90% CI, 0.36 to 0.74) were directly related to death from BS. Older age at diagnosis (59-68 years: aHR, 21.42; 90% CI, 3.52 to 130.39; 75-69 years: aHR, 16.48; 90% CI, 2.75 to 98.69; ≥76 years: aHR, 26.03; 90% CI, 4.06 to 166.93) and rural residence (aHR, 2.30; 90% CI, 1.15 to 4.60) were directly related to death from other causes. Significant risk factors were found for both causes of death.
Conclusions
BS-specific and non-BS-specific mortality had different risk factors. These findings could be utilized to prescribe optimal and specific treatment.; Summary

Birth Patterns and Delayed Breastfeeding Initiation in Indonesia: Tika Dwi Tama, Erni Astutik, Septa Katmawanti, Jauhari Oka Reuwpassa; J Prev Med Public Health. 2020;53(6):465-475. Published online October 26, 2020; DOI: https://doi.org/10.3961/jpmph.20.212

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Objectives
This study was conducted to examine the association between birth patterns (defined in terms of birth order and interval) with delayed breastfeeding initiation in Indonesia. Methods: A cross-sectional study was carried out using data from the Indonesian Demographic and Health Survey 2017. The weighted number of respondents was 5693 women aged 15-49 years whose youngest living child was less than 2 years old. Multivariable logistic regression was conducted to evaluate associations between birth patterns and delayed breastfeeding initiation after adjusting for other covariates. Results: This study found that 40.2% of newborns in Indonesia did not receive timely breastfeeding initiation. Birth patterns were significantly associated with delayed breastfeeding initiation. Firstborn children had 77% higher odds of experiencing delayed breastfeeding initiation (adjusted odds ratio, 1.77; 95% confidence interval, 1.02 to 3.04; p<0.05) than children with a birth order of 4 or higher and a birth interval ≤ 2 years after adjusting for other variables. Conclusions: Firstborn children had higher odds of experiencing delayed breastfeeding initiation. Steps to provide a robust support system for mothers, especially first-time mothers, such as sufficient access to breastfeeding information, support from family and healthcare providers, and national policy enforcement, will be effective strategies to ensure better practices regarding breastfeeding initiation.

Summary

Citations

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Modeling spatial determinants of initiation of breastfeeding in Ethiopia: A geographically weighted regression analysis
Samuel Hailegebreal, Yosef Haile, Binyam Tariku Seboka, Ermias Bekele Enyew, Tamiru Shibiru, Zeleke Abebaw Mekonnen, Shegaw Anagaw Mengiste, James Mockridge
PLOS ONE.2022; 17(9): e0273793. CrossRef
The Intervention of Maternal Nutrition Literacy Has the Potential to Prevent Childhood Stunting: Randomized Control Trials
Sirajuddin, Saifuddin Sirajuddin, Amran Razak, Ansariadi, Ridwan M Thaha, Toto Sudargo
Journal of Public Health Research.2021; 10(2): jphr.2021.2235. CrossRef

Brief Report

Estimating the Survival of Patients With Lung Cancer: What Is the Best Statistical Model?: Siavosh Abedi, Ghasem Janbabaei, Mahdi Afshari, Mahmood Moosazadeh, Masoumeh Rashidi Alashti, Akbar Hedayatizadeh-Omran, Reza Alizadeh-Navaei, Ehsan Abedini; J Prev Med Public Health. 2019;52(2):140-144. Published online February 18, 2019; DOI: https://doi.org/10.3961/jpmph.17.090

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Abstract PDF

Objectives
Investigating the survival of patients with cancer is vitally necessary for controlling the disease and for assessing treatment methods. This study aimed to compare various statistical models of survival and to determine the survival rate and its related factors among patients suffering from lung cancer.
Methods
In this retrospective cohort, the cumulative survival rate, median survival time, and factors associated with the survival of lung cancer patients were estimated using Cox, Weibull, exponential, and Gompertz regression models. Kaplan-Meier tables and the log-rank test were also used to analyze the survival of patients in different subgroups.
Results
Of 102 patients with lung cancer, 74.5% were male. During the follow-up period, 80.4% died. The incidence rate of death among patients was estimated as 3.9 (95% confidence [CI], 3.1 to 4.8) per 100 person-months. The 5-year survival rate for all patients, males, females, patients with non-small cell lung carcinoma (NSCLC), and patients with small cell lung carcinoma (SCLC) was 17%, 13%, 29%, 21%, and 0%, respectively. The median survival time for all patients, males, females, those with NSCLC, and those with SCLC was 12.7 months, 12.0 months, 16.0 months, 16.0 months, and 6.0 months, respectively. Multivariate analyses indicated that the hazard ratios (95% CIs) for male sex, age, and SCLC were 0.56 (0.33 to 0.93), 1.03 (1.01 to 1.05), and 2.91 (1.71 to 4.95), respectively.
Conclusions
Our results showed that the exponential model was the most precise. This model identified age, sex, and type of cancer as factors that predicted survival in patients with lung cancer.

Summary

Citations

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Qinying Sun, Xiangzhen Wei, Zhonglin Wang, Yan Zhu, Weiying Zhao, Yuchao Dong
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Nawapon Nakharutai, Patrinee Traisathit, Natthapat Thongsak, Titaporn Supasri, Pimwarat Srikummoon, Salinee Thumronglaohapun, Phonpat Hemwan, Imjai Chitapanarux
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Original Articles

Effects of Smoking on Menopausal Age: Results From the Korea National Health and Nutrition Examination Survey, 2007 to 2012: Hee Jung Yang, Pae Sun Suh, Soo Jeong Kim, Soon Young Lee; J Prev Med Public Health. 2015;48(4):216-224. Published online July 27, 2015; DOI: https://doi.org/10.3961/jpmph.15.021

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Abstract PDF

Objectives
Decreased fertility and impaired health owing to early menopause are significant health issues. Smoking is a modifiable health-related behavior that influences menopausal age. We investigated the effects of smoking-associated characteristics on menopausal age in Korean women.
Methods
This study used data from the Korea National Health and Nutrition Examination Survey from 2007 to 2012. Menopausal age in relation to smoking was analyzed as a Kaplan-Meier survival curve for 11 510 women (aged 30 to 65 years). The risk of entering menopause and experiencing early menopause (before age 48) related to smoking were assessed using a Cox proportional hazards model.
Results
The menopausal age among smokers was 0.75 years lower than that among non-smokers (p<0.001). The results of the Cox proportional hazards model showed pre-correction and post-correction risk ratios for entering menopause related to smoking of 1.26 (95% confidence interval [CI], 1.09 to 1.46) and 1.27 (95% CI, 1.10 to 1.47), respectively, and pre-correction and post-correction risk ratios for experiencing early menopause related to smoking of 1.36 (95% CI, 1.03 to 1.80) and 1.40 (95% CI, 1.05 to 1.85), respectively.
Conclusions
Smokers reached menopause earlier than non-smokers, and their risk for experiencing early menopause was higher.

Summary

Citations

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The Korean Journal of Physiology & Pharmacology.2022; 26(6): 501. CrossRef
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Mohd Rehan, Ummer R. Zargar, Ishfaq A. Sheikh, Saif A. Alharthy, Majed N. Almashjary, Adel M. Abuzenadah, Mohd A. Beg
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Cardiovascular Health Metrics and All-cause and Cardiovascular Disease Mortality Among Middle-aged Men in Korea: The Seoul Male Cohort Study: Ji Young Kim, Young-Jin Ko, Chul Woo Rhee, Byung-Joo Park, Dong-Hyun Kim, Jong-Myon Bae, Myung-Hee Shin, Moo-Song Lee, Zhong Min Li, Yoon-Ok Ahn; J Prev Med Public Health. 2013;46(6):319-328. Published online November 28, 2013; DOI: https://doi.org/10.3961/jpmph.2013.46.6.319

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Abstract PDF

Objectives

This study estimated the association of cardiovascular health behaviors with the risk of all-cause and cardiovascular disease (CVD) mortality in middle-aged men in Korea.

Methods

In total, 12 538 men aged 40 to 59 years were enrolled in 1993 and followed up through 2011. Cardiovascular health metrics defined the following lifestyle behaviors proposed by the American Heart Association: smoking, physical activity, body mass index, diet habit score, total cholesterol, blood pressure, and fasting blood glucose. The cardiovascular health metrics score was calculated as a single categorical variable, by assigning 1 point to each ideal healthy behavior. A Cox proportional hazards regression model was used to estimate the hazard ratio of cardiovascular health behavior. Population attributable risks (PARs) were calculated from the significant cardiovascular health metrics.

Results

There were 1054 total and 171 CVD deaths over 230 690 person-years of follow-up. The prevalence of meeting all 7 cardiovascular health metrics was 0.67%. Current smoking, elevated blood pressure, and high fasting blood glucose were significantly associated with all-cause and CVD mortality. The adjusted PARs for the 3 significant metrics combined were 35.2% (95% confidence interval [CI], 21.7 to 47.4) and 52.8% (95% CI, 22.0 to 74.0) for all-cause and CVD mortality, respectively. The adjusted hazard ratios of the groups with a 6-7 vs. 0-2 cardiovascular health metrics score were 0.42 (95% CI, 0.31 to 0.59) for all-cause mortality and 0.10 (95% CI, 0.03 to 0.29) for CVD mortality.

Conclusions

Among cardiovascular health behaviors, not smoking, normal blood pressure, and recommended fasting blood glucose levels were associated with reduced risks of all-cause and CVD mortality. Meeting a greater number of cardiovascular health metrics was associated with a lower risk of all-cause and CVD mortality.

Summary

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English Abstracts

Association Between Socioeconomic Status and All-Cause Mortality After Breast Cancer Surgery: Nationwide Retrospective Cohort Study.: Mi Jin Park, Woojin Chung, Sunmi Lee, Jong Hyock Park, Hoo Sun Chang; J Prev Med Public Health. 2010;43(4):330-340.; DOI: https://doi.org/10.3961/jpmph.2010.43.4.330

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Abstract PDF

OBJECTIVES
This study aims to evaluate and explain the socioeconomic inequalities of all-cause mortality after breast cancer surgery in South Korea. METHODS: This population based study included all 8868 females who underwent radical mastectomy for breast cancer between January 2002 and June 2003. Follow-up for mortality continued from January 2002 to June 2006. The patients were divided into 4 socioeconomic classes according to their socioeconomic status as defined by the National Health Insurance contribution rate. The relationship between socioeconomic status and all-cause mortality after breast cancer surgery was assessed using the Cox proportional hazards model with adjusting for age, the Charlson's index score, emergency hospitalization, the type of hospital and the hospital ownership. RESULTS: Those in the lowest socioeconomic status group had a significantly higher hazard ratio of 2.09 (95% CI =1.50 - 2.91) compared with those in the highest socioeconomic group after controlling for all the identifiable confounding variables. For all-cause mortality after radical mastectomy, all the other income groups showed significantly higher 3-year mortality rates than did the highest income group. CONCLUSIONS: The socioeconomic status of breast cancer patients should be considered as an independent prognostic factor that affects all-cause mortality after radical mastectomy, and this is possibly due to a delayed diagnosis, limited access or minimal treatment leading to higher mortality. This study may provide tangible support to intensify surveillance and treatment for breast cancer among low socioeconomic class women.

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Higher complication rates after management of lower extremity fractures in lower socioeconomic classes: Are risk adjustment models necessary?
Jeffrey M Henstenburg, Alexander M Lieber, Anthony J Boniello, Yehuda E Kerbel, Mitesh Shah
Trauma.2022; 24(2): 131. CrossRef
Income Disparity in Breast Cancer Incidence and Stage at Presentation: A National Population Study of South Korea
Seung-Ah Choe, Minji Roh, Hye Ri Kim, Soohyeon Lee, Myung Ki, Domyung Paek, Mia Son
Journal of Breast Cancer.2022; 25(5): 415. CrossRef
Pain-related Prescribing Patterns and Associated Factor in Breast Cancer Patients
Jin Lee, Ie Byung Park, Hwa Jeong Seo
Korean Journal of Clinical Pharmacy.2021; 31(2): 115. CrossRef
Higher breast cancer prevalence associated with higher socioeconomic status in the South Korean population; Has it resulted from overdiagnosis?
Seong-Woo Choi, So-Yeon Ryu, Mi-ah Han, Jong Park, Antonio Palazón-Bru
PLOS ONE.2018; 13(7): e0200484. CrossRef
Barriers to Cancer Care, Perceived Social Support, and Patient Navigation Services for Korean Breast Cancer Patients
Jung-won Lim
Social Work in Health Care.2015; 54(1): 47. CrossRef
Equity in health care: current situation in South Korea
Hong-Jun Cho
Journal of the Korean Medical Association.2013; 56(3): 184. CrossRef
Cancer Control and the Communication Innovation in South Korea: Implications for Cancer Disparities
Minsoo Jung
Asian Pacific Journal of Cancer Prevention.2013; 14(6): 3411. CrossRef
Performance of Papanicolaou Testing and Detection of Cervical Carcinoma In Situ in Participants of Organized Cervical Cancer Screening in South Korea
Mi Ah Han, Kui Son Choi, Hoo-Yeon Lee, Jae Kwan Jun, Kyu Won Jung, Sokbom Kang, Eun-Cheol Park, Konradin Metze
PLoS ONE.2012; 7(4): e35469. CrossRef

Cohort Study on the Association between Alcohol Consumption and the Risk of Colorectal Cancer in the Korean Elderly.: Hoi Jeong Lim, Byung Joo Park; J Prev Med Public Health. 2008;41(1):23-29.; DOI: https://doi.org/10.3961/jpmph.2008.41.1.23

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OBJECTIVES
We examined the association between alcohol consumption and incidence of colorectal cancer in elderly Koreans. METHODS: The cohort members (n=14,304) consisted of 4,834 males and 9,470 females derived from the Korea Elderly Pharmacoepidemiologic Cohort (KEPEC), a population-based dynamic cohort. They were aged 65 years old or older and lived in Busan between 1993-1998; they were beneficiaries of the Korean Medical Insurance Corporation (KMIC). Baseline information was surveyed by a self-administered, mailed questionnaire. This study population was restricted to 14,304 participants who reported alcohol drinking habits on the questionnaire and had not been diagnosed with colorectal cancer at baseline. The adjusted hazard ratios (aHR) of status, type, frequency and daily average amount of alcohol consumption were computed with Cox's proportional hazard model, with the never-drinkers as a reference group and controlling for age and gender. RESULTS: After 4.82 person-years of mean follow-up 112 cases of colorectal cancer occurred. The incidence densities of colorectal cancer were 161 (95% CI=123-200) for never-drinkers, 219 (95% CI=125-339) for ex-drinkers, and 137 (95% CI=84-189) for current-drinkers per 100,000 person-year. The status, type, frequency, and daily average amount of alcohol consumption were not significantly related to the incidence of colorectal cancer after controlling for age and gender. CONCLSIONS: There was no significant association between alcohol consumption and colorectal cancer among elderly people after controlling for age and gender.

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Wine consumption and colorectal cancer risk: a meta-analysis of observational studies
Weisong Xu, Hui Fan, Zhijuan Han, Yufeng Liu, Yiping Wang, Zhenming Ge
European Journal of Cancer Prevention.2019; 28(3): 151. CrossRef
Marital status and education as risk factors for colorectal cancer
A. Ruseva, D. Tochev, Z. Boneva, Y. Assyov, L. Georgieva, D. Nikolovska
Trakia Journal of Sciences.2019; 17(3): 224. CrossRef
Consumption of beer and colorectal cancer incidence: a meta-analysis of observational studies
Cheng Zhang, Min Zhong
Cancer Causes & Control.2015; 26(4): 549. CrossRef
Alcohol Drinking, Cigarette Smoking and Risk of Colorectal Cancer in the Korean Multi-center Cancer Cohort
Sooyoung Cho, Aesun Shin, Sue K. Park, Hai-Rim Shin, Soung-Hoon Chang, Keun-Young Yoo
Journal of Cancer Prevention.2015; 20(2): 147. CrossRef
The relationship between mild alcohol consumption and mortality in Koreans: a systematic review and meta-analysis
Ji-Eun Park, Tae-young Choi, Yeonhee Ryu, Sung-Il Cho
BMC Public Health.2015;[Epub] CrossRef
Attributable fraction of alcohol consumption on cancer using population-based nationwide cancer incidence and mortality data in the Republic of Korea
Sohee Park, Hai-Rim Shin, Boram Lee, Aesun Shin, Kyu-Won Jung, Duk-Hee Lee, Sun Ha Jee, Sung-Il Cho, Sue Kyung Park, Mathieu Boniol, Paolo Boffetta, Elisabete Weiderpass
BMC Cancer.2014;[Epub] CrossRef
Alcohol drinking and colorectal cancer risk: an overall and dose–response meta-analysis of published studies
V. Fedirko, I. Tramacere, V. Bagnardi, M. Rota, L. Scotti, F. Islami, E. Negri, K. Straif, I. Romieu, C. La Vecchia, P. Boffetta, M. Jenab
Annals of Oncology.2011; 22(9): 1958. CrossRef
Alcohol intake and risk of colorectal cancer: Results from the UK Dietary Cohort Consortium
J Y Park, C C Dahm, R H Keogh, P N Mitrou, B J Cairns, D C Greenwood, E A Spencer, I S Fentiman, M J Shipley, E J Brunner, J E Cade, V J Burley, G D Mishra, D Kuh, A M Stephen, I R White, R N Luben, A A Mulligan, K-T Khaw, S A Rodwell
British Journal of Cancer.2010; 103(5): 747. CrossRef
Alcohol Consumption and Digestive Cancer Mortality in Koreans: The Kangwha Cohort Study
Sang-Wook Yi, Jae Woong Sull, John Alderman Linton, Chung Mo Nam, Heechoul Ohrr
Journal of Epidemiology.2010; 20(3): 204. CrossRef
Baseline alcohol consumption, type of alcoholic beverage and risk of colorectal cancer in the European Prospective Investigation into Cancer and Nutrition-Norfolk study
Jin Young Park, Panagiota N. Mitrou, Christina C. Dahm, Robert N. Luben, Nicholas J. Wareham, Kay-Tee Khaw, Sheila A. Rodwell
Cancer Epidemiology.2009; 33(5): 347. CrossRef
A Novel Polymorphism rs1329149 of CYP2E1 and a Known Polymorphism rs671 of ALDH2 of Alcohol Metabolizing Enzymes Are Associated with Colorectal Cancer in a Southwestern Chinese Population
Huan Yang, Yanhong Zhou, Ziyuan Zhou, Jinyi Liu, Xiaoyan Yuan, Ketaro Matsuo, Toshiro Takezaki, Kazuo Tajima, Jia Cao
Cancer Epidemiology, Biomarkers & Prevention.2009; 18(9): 2522. CrossRef

Statistical Issues in Genomic Cohort Studies.: Sohee Park; J Prev Med Public Health. 2007;40(2):108-113.; DOI: https://doi.org/10.3961/jpmph.2007.40.2.108

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Abstract PDF: When conducting large-scale cohort studies, numerous statistical issues arise from the range of study design, data collection, data analysis and interpretation. In genomic cohort studies, these statistical problems become more complicated, which need to be carefully dealt with. Rapid technical advances in genomic studies produce enormous amount of data to be analyzed and traditional statistical methods are no longer sufficient to handle these data. In this paper, we reviewed several important statistical issues that occur frequently in large-scale genomic cohort studies, including measurement error and its relevant correction methods, cost-efficient design strategy for main cohort and validation studies, inflated Type I error, gene-gene and gene-environment interaction and time-varying hazard ratios. It is very important to employ appropriate statistical methods in order to make the best use of valuable cohort data and produce valid and reliable study results.; Summary

Original Articles

An Approach to Survey Data with Nonresponse: Evaluation of KEPEC Data with BMI.: Jieun Baek, Weechang Kang, Youngjo Lee, Byung Joo Park; Korean J Prev Med. 2002;35(2):136-140.

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Abstract PDF: OBJECTIVES
A common problem with analyzing survey data involves incomplete data with either a nonresponse or missing data. The mail questionnaire survey conducted for collecting lifestyle variables on the members of the Korean Elderly Phamacoepidemiologic Cohort(KEPEC) in 1996 contains some nonresponse or missing data. The proper statistical method was applied to evaluate the missing pattern of a specific KEPEC data, which had no missing data in the independent variable and missing data in the response variable, BMI. METHODS: The number of study subjects was 8,689 elderly people. Initially, the BMI and significant variables that influenced the BMI were categorized. After fitting the log-linear model, the probabilities of the people on each category were estimated. The EM algorithm was implemented using a log-linear model to determine the missing mechanism causing the nonresponse. RESULTS: Age, smoking status, and a preference of spicy hot food were chosen as variables that influenced the BMI. As a result of fitting the nonignorable and ignorable nonresponse log-linear model considering these variables, the difference in the deviance in these two models was 0.0034(df=1). CONCLUSION: There is a lot of risk if an inference regarding the variables and large samples is made without considering the pattern of missing data. On the basis of these results, the missing data occurring in the BMI is the ignorable nonresponse. Therefore, when analyzing the BMI in KEPEC data, the inference can be made about the data without considering the missing data.; Summary

The Cancer-preventive Potential of Panax ginseng: A Review of Human and Experimental Evidence.: Hai Rim Shin, Joon Youn Kim, Duk Hee Lee, Taik Koo Yun, Gareth Morgan, Harri Vainio; Korean J Prev Med. 2000;33(4):383-392.

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Abstract PDF: OBJECTIVE
We have reviewed the potential cancer preventive and other relevant properties of Panax ginseng C. A. Meyer, which has been traditionally used as a natural tonic in oriental countries. DATA IDENTIFICATION AND STUDY SELECTION: Publications on Panax ginseng and its relation to cancer were obtained from the Medline database (1983-2000) and by checking reference lists to find earlier reports. The reports cover experimental models and human studies on cancer-preventive activity, carcinogenicity and other beneficial or adverse effects. In addition, possible mechanisms of chemoprevention by ginseng were also considered. RESULTS: Published results from a cohort and two case-control studies in Korea suggest that the intake of ginseng may reduce the risk of several types of cancer. When ginseng was tested in animal models, a reduction in cancer incidence and multiplicity at various sites was noted. Panax ginseng and its chemical constituents have been tested for their inhibiting effect on putative carcinogenesis mechanisms (e.g., cell proliferation and apoptosis, immunosurveillance, angiogenesis); in most experiments inhibitory effects were found. CONCLUSION: While Panax ginseng C. A. Meyer has shown cancer preventive effects both in experimental models and in epidemiological studies, the evidence is currently not conclusive as to its cancer-preventive activity in humans. The available evidence warrants further research into the possible role of ginseng in the prevention of human cancer and carcinogenesis.; Summary

Health-Related Behaviors: Theoretical Models And Research Findings.: Sang Soo Bae; Korean J Prev Med. 1993;26(4):508-533.

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Abstract PDF: A wide range of health professionals have interest in changing the health behavior of individuals. To intervene effectively and to make informed judgements about how to measure the success of such interventions, health professionals must have an deep understanding of health behavior. This paper provides and overview of the thories of health-related behaviors and the strength and weakness of each, how the theories relate to others, and how they can be used in practice. The theories reviewed include Suchmann's stages of illness experience, Health belief model, Attribution theory, Fishbein's theory of reasoned action, Multiattribute utility models, Consumer information processing, and Andersen's models. Finally, this paper introduces the reader to interesting research findings in our country.; Summary

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