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Original Article
Smoking-attributable Mortality in Korea, 2020: A Meta-analysis of 4 Databases
Eunsil Cheon, Yeun Soo Yang, Suyoung Jo, Jieun Hwang, Keum Ji Jung, Sunmi Lee, Seong Yong Park, Kyoungin Na, Soyeon Kim, Sun Ha Jee, Sung-il Cho
J Prev Med Public Health. 2024;57(4):327-338.   Published online July 3, 2024
DOI: https://doi.org/10.3961/jpmph.23.471
  • 2,039 View
  • 245 Download
  • 1 Web of Science
  • 1 Crossref
AbstractAbstract AbstractSummary PDFSupplementary Material
Objectives
Estimating the number of deaths caused by smoking is crucial for developing and evaluating tobacco control and smoking cessation policies. This study aimed to determine smoking-attributable mortality (SAM) in Korea in 2020.
Methods
Four large-scale cohorts from Korea were analyzed. A Cox proportional-hazards model was used to determine the hazard ratios (HRs) of smoking-related death. By conducting a meta-analysis of these HRs, the pooled HRs of smoking-related death for 41 diseases were estimated. Population-attributable fractions (PAFs) were calculated based on the smoking prevalence for 1995 in conjunction with the pooled HRs. Subsequently, SAM was derived using the PAF and the number of deaths recorded for each disease in 2020.
Results
The pooled HR for all-cause mortality attributable to smoking was 1.73 for current men smokers (95% confidence interval [CI], 1.53 to 1.95) and 1.63 for current women smokers (95% CI, 1.37 to 1.94). Smoking accounted for 33.2% of all-cause deaths in men and 4.6% in women. Additionally, it was a factor in 71.8% of men lung cancer deaths and 11.9% of women lung cancer deaths. In 2020, smoking was responsible for 53 930 men deaths and 6283 women deaths, totaling 60 213 deaths.
Conclusions
Cigarette smoking was responsible for a significant number of deaths in Korea in 2020. Monitoring the impact and societal burden of smoking is essential for effective tobacco control and harm prevention policies.
Summary
Korean summary
한국의 흡연율은 상당 수준 감소하였지만 흡연의 장기적인 건강영향은 지속적으로 나타나고 있다. 4개의 대규모 코호트와 1995년 흡연율을 사용하여 2020년 한국의 흡연기인 사망자수를 산출한 결과 남성 53,930명, 여성 6283명으로 총 60,213명이였다. 효과적인 담배규제와 금연 정책을 위하여 장기적인 사망자수 모니터링이 필요할 것이다.
Key Message
Despite the significant decrease in smoking rates in South Korea, the long-term health effects of smoking continue to manifest. Our analysis using four large-scale cohorts and 1995 smoking prevalence revealed that in 2020, the number of smoking-attributable death in South Korea was 53,930 for men and 6,283 for women, totaling 60,213. Long-term monitoring is necessary for effective tobacco control and smoking cessation policies.

Citations

Citations to this article as recorded by  
  • The economic cost of direct smoking in South Korea
    Kristine Namhee Kwon, Kangyeon Lee, Wankyo Chung
    Preventive Medicine Reports.2024; 46: 102865.     CrossRef
Perspective
Epidemiological Model for Conventional Tobacco Control Measures and Tobacco Endgame Policies
Heewon Kang, Sung-il Cho
J Prev Med Public Health. 2023;56(5):481-484.   Published online September 26, 2023
DOI: https://doi.org/10.3961/jpmph.23.239
  • 1,783 View
  • 112 Download
  • 2 Web of Science
  • 2 Crossref
AbstractAbstract AbstractSummary PDFSupplementary Material
Epidemiological models, also known as host-agent-vector-environment models, are utilized in public health to gain insights into disease occurrence and to formulate intervention strategies. In this paper, we propose an epidemiological model that incorporates both conventional measures and tobacco endgame policies. Our model suggests that conventional measures focus on relationships among agent-vector-host-environment components, whereas endgame policies inherently aim to change or eliminate those components at a fundamental level. We also found that the vector (tobacco industry) and environment (physical and social surroundings) components were insufficiently researched or controlled by both conventional measures and tobacco endgame policies. The use of an epidemiological model for tobacco control and the tobacco endgame is recommended to identify areas that require greater effort and to develop effective intervention measures.
Summary
Korean summary
이 연구는 기존의 담배규제와 관련된 역학 모형을 확장하여 담배 수요를 줄이기 위한 조치인 MPOWER 정책과 담배 종결전의 주요 정책을 아우르는 개념적 모형을 제시하였다. 각 정책을 개념적 모형 내 배치한 결과, MPOWER 정책은 모형 내 구성요소 간의 연결을 끊는 것을 목표로 하는 반면, 종결전 정책은 모형 내 요소들을 영구적으로 변화시키거나 제거하려는 특성을 가지고 있는 것으로 나타났다. 담배규제정책이 개체, 병원체, 벡터 및 환경 요소에 대한 균형 잡힌 포트폴리오를 갖추고 있는지 평가하기 위해 이 개념적 모형을 활용할 수 있다.
Key Message
We extended the conceptual epidemiological model for tobacco control by incorporating measures to reduce the demand for tobacco (MPOWER measures) and key endgame policies. The model suggests that MPOWER measures focus on disconnecting the relationships between model components, while endgame policies aim to permanently change or eliminate the components themselves. This model can be used to examine whether a country or jurisdiction's tobacco control policy maintains a balanced portfolio across agent, host, vector, and environmental factors.

Citations

Citations to this article as recorded by  
  • Public support for tobacco endgame policies in South Korea: Findings from the 2020 International Tobacco Control Korea Survey
    Heewon Kang, Wonjeong Yoon, Hong Gwan Seo, Sungkyu Lee, Sujin Lim, Gil-yong Kim, Su Young Kim, Steve S Xu, Mi Yan, Anne C K Quah, Janet Chung-Hall, Lorraine V Craig, Coral E Gartner, Geoffrey T Fong, Sung-il Cho
    Tobacco Control.2024; : tc-2023-058454.     CrossRef
  • Decrease in household secondhand smoking among South Korean adolescents associated with smoke-free policies: grade-period-cohort and interrupted time series analyses
    Hana Kim, Heewon Kang, Sung-il Cho
    Epidemiology and Health.2023; : e2024009.     CrossRef
Brief Report
Utilization of the Unlinked Case Proportion to Control COVID-19: A Focus on the Non-pharmaceutical Interventional Policies of the Korea and Japan
Yeri Jeong, Sanggu Kang, Boeun Kim, Yong Jin Gil, Seung-sik Hwang, Sung-il Cho
J Prev Med Public Health. 2023;56(4):377-383.   Published online June 21, 2023
DOI: https://doi.org/10.3961/jpmph.23.056
  • 3,456 View
  • 92 Download
AbstractAbstract AbstractSummary PDFSupplementary Material
Objectives
Korea and Japan have managed the spread of coronavirus disease 2019 (COVID-19) using markedly different policies, referred to as the “3T” and “3C” strategies, respectively. This study examined these differences to assess the roles of active testing and contact tracing as non-pharmaceutical interventions (NPIs). We compared the proportion of unlinked cases (UCs) and test positivity rate (TPR) as indicators of tracing and testing capacities.
Methods
We outlined the evolution of NPI policies and investigated temporal trends in their correlations with UCs, confirmed cases, and TPR prior to the Omicron peak. Spearman correlation coefficients were reported between the proportion of UCs, confirmed cases, and TPR. The Fisher r-to-z transformation was employed to examine the significance of differences between correlation coefficients.
Results
The proportion of UCs was significantly correlated with confirmed cases (r=0.995, p<0.001) and TPR (r=0.659, p<0.001) in Korea and with confirmed cases (r=0.437, p<0.001) and TPR (r=0.429, p<0.001) in Japan. The Fisher r-to-z test revealed significant differences in correlation coefficients between the proportion of UCs and confirmed cases (z=16.07, p<0.001) and between the proportion of UCs and TPR (z=2.12, p=0.034) in Korea and Japan.
Conclusions
Higher UCs were associated with increases in confirmed cases and TPR, indicating the importance of combining testing and contact tracing in controlling COVID-19. The implementation of stricter policies led to stronger correlations between these indicators. The proportion of UCs and TPR effectively indicated the effectiveness of NPIs. If the proportion of UCs shows an upward trend, more testing and contact tracing may be required.
Summary
Korean summary
“3T”전략과 “3C”전략으로 대표되는 한국과 일본의 코로나 19 유행 시기의 NPI 정책을 비교하고, 접촉자 추적 및 검사 역량의 지표로 감염경로를 알 수 없는 확진자(unlinked case)와 검사 양성률(TPR)의 역할을 평가하였다. 감염경로를 알 수 없는 확진자(UC)는 전체 확진자수 증가 및 검사 양성률의 증가와 관련이 있었으며, 이는 COVID-19 통제에 있어 검사와 접촉자 추적을 적절히 조합하는 것이 중요함을 보여준다.
Editorials
Our Valuable Contributors: Reviewers of 2022
Sung-il Cho
J Prev Med Public Health. 2023;56(2):99-99.   Published online March 31, 2023
DOI: https://doi.org/10.3961/jpmph.23.125
  • 1,426 View
  • 89 Download
PDF
Summary
Our Valuable Contributors: Reviewers of 2021
Sung-il Cho
J Prev Med Public Health. 2022;55(2):115-115.   Published online March 31, 2022
DOI: https://doi.org/10.3961/jpmph.22.100
  • 2,524 View
  • 107 Download
PDF
Summary
Our Valuable Contributors: Reviewers of 2020
Sung-il Cho
J Prev Med Public Health. 2021;54(2):85-85.   Published online March 31, 2021
DOI: https://doi.org/10.3961/jpmph.21.108
  • 2,824 View
  • 126 Download
PDF
Summary
COVID-19: Perspective
Interpretation of the Basic and Effective Reproduction Number
Jun-Sik Lim, Sung-Il Cho, Sukhyun Ryu, Son-Il Pak
J Prev Med Public Health. 2020;53(6):405-408.   Published online October 20, 2020
DOI: https://doi.org/10.3961/jpmph.20.288
  • 7,865 View
  • 397 Download
  • 11 Crossref
AbstractAbstract PDF
In epidemiology, the basic reproduction number (R0) is a term that describes the expected number of infections generated by 1 case in a susceptible population. At the beginning of the coronavirus disease 2019 (COVID-19) pandemic, R0 was frequently referenced by the public health community and the wider public. However, this metric is often misused or misinterpreted. Moreover, the complexity of the process of estimating R0 has caused difficulties for a substantial number of researchers. In this article, in order to increase the accessibility of this concept, we address several misconceptions related to the threshold characteristics of R0 and the effective reproduction number (Rt). Moreover, the appropriate interpretation of the metrics is discussed. R0 should be considered as a population-averaged value that pools the contact structure according to a stochastic transmission process. Furthermore, it is necessary to understand the unavoidable time lag for Rt due to the incubation period of the disease.
Summary

Citations

Citations to this article as recorded by  
  • Risk perceptions and behaviors concerning rural tourism and economic-political drivers of COVID-19 policy in 2020
    Brandon Lieberthal, Sarah Jackson, Sandra de Urioste-Stone, Mumtaz Alam
    PLOS ONE.2024; 19(4): e0299841.     CrossRef
  • Exploring data sources and mathematical approaches for estimating human mobility rates and implications for understanding COVID-19 dynamics: a systematic literature review
    Yogesh Bali, Vijay Pal Bajiya, Jai Prakash Tripathi, Anuj Mubayi
    Journal of Mathematical Biology.2024;[Epub]     CrossRef
  • Effective Reproduction Number of Smear-Positive Pulmonary Tuberculosis in Iran: A Registry-Based Study (2011-2021)
    Maryam Rastegar, Vahid Fakoor, Eisa Nazar, Mahshid Nasehi, Saeed Sharafi, Mohammad Taghi Shakeri
    Journal of Research in Health Sciences.2024; 24(4): e00633.     CrossRef
  • Hepatitis C Virus Dynamic Transmission Models Among People Who Inject Drugs
    Shiferaw Bekele Woyesa, Kellemuwa Desalegn Amente
    Infection and Drug Resistance.2023; Volume 16: 1061.     CrossRef
  • Modeling the time-dependent transmission rate using gaussian pulses for analyzing the COVID-19 outbreaks in the world
    Setianto Setianto, Darmawan Hidayat
    Scientific Reports.2023;[Epub]     CrossRef
  • A review on COVID-19 transmission, epidemiological features, prevention and vaccination
    Yuqin Zhang, Gonghua Wu, Shirui Chen, Xu Ju, Wumitijiang Yimaer, Wangjian Zhang, Shao Lin, Yuantao Hao, Jing Gu, Jinghua Li
    Medical Review.2022; 2(1): 23.     CrossRef
  • A measure to estimate the risk of imported COVID-19 cases and its application for evaluating travel-related control measures
    Heewon Kang, Kyung-Duk Min, Seonghee Jeon, Ju-Yeun Lee, Sung-il Cho
    Scientific Reports.2022;[Epub]     CrossRef
  • Study on the interaction between different pathogens of Hand, foot and mouth disease in five regions of China
    Zimei Yang, Jia Rui, Li Qi, Wenjing Ye, Yan Niu, Kaiwei Luo, Bin Deng, Shi Zhang, Shanshan Yu, Chan Liu, Peihua Li, Rui Wang, Hongjie Wei, Hesong Zhang, Lijin Huang, Simiao Zuo, Lexin Zhang, Shurui Zhang, Shiting Yang, Yichao Guo, Qinglong Zhao, Shenggen
    Frontiers in Public Health.2022;[Epub]     CrossRef
  • Transmission dynamics and control of two epidemic waves of SARS-CoV-2 in South Korea
    Sukhyun Ryu, Sheikh Taslim Ali, Eunbi Noh, Dasom Kim, Eric H. Y. Lau, Benjamin J. Cowling
    BMC Infectious Diseases.2021;[Epub]     CrossRef
  • Basic reproduction number of African swine fever in wild boars (Sus scrofa) and its spatiotemporal heterogeneity in South Korea
    Jun-Sik Lim, Eutteum Kim, Pan-Dong Ryu, Son-Il Pak
    Journal of Veterinary Science.2021;[Epub]     CrossRef
  • The detection of the epidemic phase of COVID-19 and the timing of social distancing policies in Korea
    Woohyeon Kim
    Public Health.2021; 201: 89.     CrossRef
COVID-19: Brief Report
The Evolving Policy Debate on Border Closure in Korea
Su JIn Kang, Jihyun Moon, Heewon Kang, Heekyoung Nam, Sangwoo Tak, Sung-Il Cho
J Prev Med Public Health. 2020;53(5):302-306.   Published online September 11, 2020
DOI: https://doi.org/10.3961/jpmph.20.213
  • 4,981 View
  • 137 Download
  • 5 Crossref
AbstractAbstract PDFSupplementary Material
Objectives
In this paper, we aimed to investigate the evolving debate over border closure in Korea during the coronavirus disease 2019 (COVID-19) pandemic, to address the main themes associated with border closure, and to discuss the factors that need to be considered when making such decisions.
Methods
We collated and reviewed previously conducted review studies on border closures during infectious disease outbreaks to derive relevant themes and factors.
Results
According to our systematic review on border closures and travel restrictions, the effects of such containment efforts are limited. We suggest considering the following factors when determining whether to impose border closure measures: (1) disease characteristics, (2) timeliness of implementation, (3) transmission delay and the basic reproduction number, (4) globalization and pandemics, and (5) social and economic costs.
Conclusions
Our assessment indicates that the effects of border closures are at best temporary and limited. Alternative measures must be contemplated and implemented to suppress the spread of COVID-19 in particular and infectious diseases more broadly.
Summary

Citations

Citations to this article as recorded by  
  • Schengen Borders as Lines that Continue to Separate? Media Representations of Pandemic Dimensions of Insecurity in Eastern German Border Regions to Poland
    Nona Renner, Judith Miggelbrink, Kristine Beurskens, Antonia Zitterbart
    Journal of Borderlands Studies.2022; 37(4): 825.     CrossRef
  • Classification Schemes of COVID-19 High Risk Areas and Resulting Policies: A Rapid Review
    Olalekan A. Uthman, Olatunji O. Adetokunboh, Charles Shey Wiysonge, Sameh Al-Awlaqi, Johanna Hanefeld, Charbel El Bcheraoui
    Frontiers in Public Health.2022;[Epub]     CrossRef
  • A measure to estimate the risk of imported COVID-19 cases and its application for evaluating travel-related control measures
    Heewon Kang, Kyung-Duk Min, Seonghee Jeon, Ju-Yeun Lee, Sung-il Cho
    Scientific Reports.2022;[Epub]     CrossRef
  • Towards sustainable airport waste management through the adoption of a "green" airport strategy: The case of Incheon International Airport
    Glenn Baxter
    Clean Technologies and Recycling.2022; 2(4): 247.     CrossRef
  • Pathways between COVID-19 public health responses and increasing overdose risks: A rapid review and conceptual framework
    Tribesty Nguyen, Jane A. Buxton
    International Journal of Drug Policy.2021; 93: 103236.     CrossRef
COVID-19: Editorial
Academic Community’s Efforts to Guide the Fight Against Coronavirus Disease 2019 (COVID-19) Epidemic in Korea
Sung-il Cho
J Prev Med Public Health. 2020;53(2):65-66.   Published online March 31, 2020
DOI: https://doi.org/10.3961/jpmph.20.084
  • 6,516 View
  • 437 Download
  • 7 Crossref
PDFSupplementary Material
Summary

Citations

Citations to this article as recorded by  
  • In Silico Infection Analysis (iSFA) Identified Coronavirus Infection and Potential Transmission Risk in Mammals
    Yanyan Zou, Xiaojian Cao, Bing Yang, Lulu Deng, Yangyang Xu, Shuang Dong, Wentao Li, Chengchao Wu, Gang Cao
    Frontiers in Molecular Biosciences.2022;[Epub]     CrossRef
  • The roles of primary care doctors in the COVID-19 pandemic: consistency and influencing factors of doctor's perception and actions and nominal definitions
    Chenbin Yang, Jiana Yin, Jiongjiong Liu, Jinying Liu, Qin Chen, Hui Yang, Yunchao Ni, Bingcan Li, Yanmei Li, Jin Lin, Ziwei Zhou, Zhangping Li
    BMC Health Services Research.2022;[Epub]     CrossRef
  • Effectiveness of negative pressure isolation stretcher and rooms for SARS-CoV-2 nosocomial infection control and maintenance of South Korean emergency department capacity
    Sang-Chul Kim, So Yeon Kong, Gwan-Jin Park, Ji-Han Lee, Joon-Kee Lee, Mou-Seop Lee, Heon Seok Han
    The American Journal of Emergency Medicine.2021; 45: 483.     CrossRef
  • Mental Health of Physical Therapy Students in Clinical Practice during the COVID-19 Pandemic: A Cross-sectional Survey in Gwangju and Jeollanam-do, South Korea
    Se Ju Park, Seong Geun Yeo, Byeong Geun Kim
    The Journal of Korean Physical Therapy.2021; 33(3): 131.     CrossRef
  • Anxiety and Depression in Physical Therapists during the COVID-19 Pandemic: A Cross-sectional Survey in Gwangju, South Korea
    Se-Ju Park, Ho-Jin Jeong, Byeong-Geun Kim
    Journal of The Korean Society of Physical Medicine.2021; 16(2): 23.     CrossRef
  • Innovative countermeasures can maintain cancer care continuity during the coronavirus disease-2019 pandemic in Korea
    Soohyeon Lee, Ah-reum Lim, Min Ja Kim, Yoon Ji Choi, Ju Won Kim, Kyong Hwa Park, Sang Won Shin, Yeul Hong Kim
    European Journal of Cancer.2020; 136: 69.     CrossRef
  • The Evolving Policy Debate on Border Closure in Korea
    SuJin Kang, Jihyun Moon, Heewon Kang, Heekyoung Nam, Sangwoo Tak, Sung-Il Cho
    Journal of Preventive Medicine and Public Health.2020; 53(5): 302.     CrossRef
Editorials
Our Valuable Contributors: Reviewers of 2019
Sung-il Cho
J Prev Med Public Health. 2020;53(2):72-72.   Published online March 31, 2020
DOI: https://doi.org/10.3961/jpmph.20.081
  • 3,103 View
  • 100 Download
PDF
Summary
Our Valuable Contributors: Reviewers of 2018
Sung-il Cho
J Prev Med Public Health. 2019;52(2):71-71.   Published online March 29, 2019
DOI: https://doi.org/10.3961/jpmph.19.054
  • 4,111 View
  • 109 Download
PDF
Summary
Our Valuable Contributors: Reviewers of 2017
Sung-il Cho
J Prev Med Public Health. 2018;51(2):63-63.   Published online March 30, 2018
DOI: https://doi.org/10.3961/jpmph.18.060
  • 4,788 View
  • 121 Download
PDF
Summary
Original Article
Concordance in the Health Behaviors of Couples by Age: A Cross-sectional Study
Seungmin Jeong, Sung-Il Cho
J Prev Med Public Health. 2018;51(1):6-14.   Published online November 27, 2017
DOI: https://doi.org/10.3961/jpmph.17.137
  • 10,970 View
  • 256 Download
  • 15 Crossref
AbstractAbstract PDFSupplementary Material
Objectives
To investigate concordance in the health behaviors of women and their partners according to age and to investigate whether there was a stronger correlation between the health behaviors of housewives and those of their partners than between the health behaviors of non-housewives and those of their partners.
Methods
We used data obtained from women participants in the 2015 Korea Community Health Survey who were living with their partners. The outcome variables were 4 health behaviors: smoking, drinking, eating salty food, and physical activity. The main independent variables were the partners’ corresponding health behaviors. We categorized age into 4 groups (19-29, 30-49, 50-64, and ≥ 65 years) and utilized multivariate logistic regression analysis, stratifying by age group. Another logistic regression analysis was stratified by whether the participant identified as a housewife.
Results
Data from 64 971 women older than 18 years of age were analyzed. Of the 4 health behaviors, the risk of smoking (adjusted odds ratio [aOR], 4.65; 95% confidence interval [CI], 3.93 to 5.49) was highest when the participant’s partner was also a smoker. Similar results were found for an inactive lifestyle (aOR, 2.56; 95% CI, 2.45 to 2.66), eating salty food (aOR, 2.48; 95% CI, 2.36 to 2.62); and excessive drinking (aOR, 1.89; 95% CI, 1.80 to 1.98). In comparison to non-housewives, housewives had higher odds of eating salty food.
Conclusions
The health behaviors of women were positively correlated with those of their partners. The magnitude of the concordance differed by age group.
Summary

Citations

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  • Let’s Enjoy an Evening on the Couch? A Daily Life Investigation of Shared Problematic Behaviors in Three Couple Studies
    Theresa Pauly, Janina Lüscher, Corina Berli, Christiane A. Hoppmann, Rachel A. Murphy, Maureen C. Ashe, Wolfgang Linden, Kenneth M. Madden, Denis Gerstorf, Urte Scholz
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    International Journal of Behavioral Medicine.2024; 31(2): 215.     CrossRef
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    Theresa Pauly, Janina Lüscher, Lea Olivia Wilhelm, Melanie Alexandra Amrein, George Boateng, Tobias Kowatsch, Elgar Fleisch, Guy Bodenmann, Urte Scholz
    JMIR mHealth and uHealth.2024; 12: e49576.     CrossRef
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    Fredo Tamara, Jonny K. Fajar, Gatot Soegiarto, Laksmi Wulandari, Andy P. Kusuma, Erwin A. Pasaribu, Reza P. Putra, Muhammad Rizky, Tajul Anshor, Maya Novariza, Surya Wijaya, Guruh Prasetyo, Adelia Pradita, Qurrata Aini, Mario V.P.H. Mete, Rahmat Yusni, Ya
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    Mitchell Conery, Struan F. A. Grant
    Annals of Human Biology.2023; 50(1): 258.     CrossRef
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    Tanya B. Horwitz, Jared V. Balbona, Katie N. Paulich, Matthew C. Keller
    Nature Human Behaviour.2023; 7(9): 1568.     CrossRef
  • Similarities in cardiometabolic risk factors among random male-female pairs: a large observational study in Japan
    Naoki Nakaya, Kumi Nakaya, Naho Tsuchiya, Toshimasa Sone, Mana Kogure, Rieko Hatanaka, Ikumi kanno, Hirohito Metoki, Taku Obara, Mami Ishikuro, Atsushi Hozawa, Shinichi Kuriyama
    BMC Public Health.2022;[Epub]     CrossRef
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    Jessica K. Perrotte, Eric C. Shattuck, Colton L. Daniels, Xiaohe Xu, Thankam Sunil
    BMC Public Health.2021;[Epub]     CrossRef
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    Naoki Nakaya, Tian Xie, Bart Scheerder, Naho Tsuchiya, Akira Narita, Tomohiro Nakamura, Hirohito Metoki, Taku Obara, Mami Ishikuro, Atsushi Hozawa, Harold Snieder, Shinichi Kuriyama
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    Bon Kim, Kyungmin Kim, Jeffrey A. Burr, Joohyun Kim, Gyounghae Han
    Journal of Applied Gerontology.2021; 40(10): 1320.     CrossRef
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    Nutrients.2020; 12(11): 3332.     CrossRef
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Editorials
Our Valuable Contributors: Reviewers of 2016
Sung-il Cho
J Prev Med Public Health. 2017;50(2):67-67.   Published online March 29, 2017
DOI: https://doi.org/10.3961/jpmph.17.003
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Our Valuable Contributors: Reviewers of 2015
Sung-il Cho
J Prev Med Public Health. 2016;49(2):79-79.   Published online March 31, 2016
DOI: https://doi.org/10.3961/jpmph.15.033
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JPMPH : Journal of Preventive Medicine and Public Health
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