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Jae Jeong Yang 4 Articles
Determinants of Poor Self-rated Health in Korean Adults With Diabetes
Hwi-Won Lee, Minkyo Song, Jae Jeong Yang, Daehee Kang
J Prev Med Public Health. 2015;48(6):287-300.   Published online October 23, 2015
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  • 18 Crossref
AbstractAbstract PDFSupplementary Material
Self-rated health is a measure of perceived health widely used in epidemiological studies. Our study investigated the determinants of poor self-rated health in middle-aged Korean adults with diabetes.
A cross-sectional study was conducted based on the Health Examinees Study. A total of 9759 adults aged 40 to 69 years who reported having physician-diagnosed diabetes were analyzed with regard to a range of health determinants, including sociodemographic, lifestyle, psychosocial, and physical variables, in association with self-rated health status using multivariate logistic regression models. A p-value <0.05 was considered to indicate statistical significance.
We found that negative psychosocial conditions, including frequent stress events and severe distress according to the psychosocial well-being index, were most strongly associated with poor self-rated health (odds ratio [OR]Frequent stress events, 5.40; 95% confidence interval [CI], 4.63 to 6.29; ORSevere distress, 11.08; 95% CI, 8.77 to 14.00). Moreover, younger age and being underweight or obese were shown to be associated with poor self-rated health. Physical factors relating to participants’ medical history of diabetes, such as a younger age at diagnosis, a longer duration of diabetes, insulin therapy, hemoglobin A1c levels of 6.5% or more, and comorbidities, were other correlates of poor reported health.
Our findings suggest that, in addition to medical variables, unfavorable socioeconomic factors, and adverse lifestyle behaviors, younger age, being underweight or obese, and psychosocial stress could be distinc factors in predicting negative perceived health status in Korean adults with diabetes.


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    International Journal of Preventive Medicine.2024;[Epub]     CrossRef
  • Exploring factors associated with self‐rated health in individuals with diabetes and its impact on quality of life: Evidence from the Survey of Health, Ageing, and Retirement in Europe
    Rosa Marie Brückner, Aline Schönenberg, Rebecca Wientzek, Mandy Schreiber, Tino Prell
    Journal of Diabetes.2024;[Epub]     CrossRef
  • Gender Disparities in Healthy Aging: A Cross-National Comparative Study in the United States and South Korea from 2006 to 2016
    Lanlan Chu, Anjelynt Lor, Mary-Genevieve Moisan, Kieu My Phi
    The International Journal of Aging and Human Development.2023; 96(1): 33.     CrossRef
  • People with Diabetes Have Poorer Self-Rated Health (SRH) and Diabetes Moderates the Association between Age and SRH
    Weixi Kang, Antonio Malvaso
    Diseases.2023; 11(2): 73.     CrossRef
  • The Relationship between Self-Perceived Health and Physical Activity in the Mental Health of Korean Cancer Survivors
    Sungjung Kwak, Jieun Shin, Jong-Yeup Kim
    Healthcare.2023; 11(11): 1549.     CrossRef
  • Sleep Duration, Sleep Quality, and Insomnia in Association With Self-Rated Health: A Systematic Review and Meta-Analysis
    Sohrab Amiri
    Sleep Medicine Research.2023; 14(2): 66.     CrossRef
  • Diabetes Moderates the Link between Personality Traits and Self-Rated Health (SRH)
    Weixi Kang
    Healthcare.2023; 11(15): 2149.     CrossRef
  • Low Social Support and Risk for Depression in People With Type 2 Diabetes Mellitus: A Systematic Review and Meta-analysis
    Akhmad Azmiardi, Bhisma Murti, Ratih Puspita Febrinasari, Didik Gunawan Tamtomo
    Journal of Preventive Medicine and Public Health.2022; 55(1): 37.     CrossRef
  • Self-rated health and perceived environmental quality in Brunei Darussalam: a cross-sectional study
    Evi Nurvidya Arifin, Chang-Yau Hoon, Ly Slesman, Abby Tan
    BMJ Open.2022; 12(8): e060799.     CrossRef
  • Obesity, Disability and Self-Perceived Health Outcomes in Australian Adults: A Longitudinal Analysis Using 14 Annual Waves of the HILDA Cohort
    Syed Afroz Keramat, Khorshed Alam, Bright Opoku Ahinkorah, Md Sariful Islam, Md Irteja Islam, Md Zobayer Hossain, Sazia Ahmed, Jeff Gow, Stuart JH Biddle
    ClinicoEconomics and Outcomes Research.2021; Volume 13: 777.     CrossRef
  • Factors Associated with Poor Self-Rated Health in Cancer Patients
    Hyo Rim Ju, Ye Rim Jeon, Seo Young Kang, Jung Ah Lee, Young Sik Kim
    Korean Journal of Family Practice.2021; 11(5): 385.     CrossRef
  • Physical Exercise, Social Interaction, Access to Care, and Community Service: Mediators in the Relationship Between Socioeconomic Status and Health Among Older Patients With Diabetes
    Qingwen Deng, Wenbin Liu
    Frontiers in Public Health.2020;[Epub]     CrossRef
  • Self-rated health and the risk of incident type 2 diabetes mellitus: A cohort study
    Jin-Won Noh, Yoosoo Chang, Minsun Park, Young Dae Kwon, Seungho Ryu
    Scientific Reports.2019;[Epub]     CrossRef
  • Explaining the gender gap in health services use among Ghanaian community-dwelling older cohorts
    Razak M. Gyasi, David R. Phillips, Roman David
    Women & Health.2019; 59(10): 1089.     CrossRef
  • Gender, self-rated health and functional decline among community-dwelling older adults
    Razak M. Gyasi, David R. Phillips
    Archives of Gerontology and Geriatrics.2018; 77: 174.     CrossRef
  • Self‐reported oral health predicts tooth loss after five and ten years in a population‐based study
    Peter Meisel, Birte Holtfreter, Henry Völzke, Thomas Kocher
    Journal of Clinical Periodontology.2018; 45(10): 1164.     CrossRef
  • Body mass index and self-rated health in East Asian countries: Comparison among South Korea, China, Japan, and Taiwan
    Jin-Won Noh, Jinseok Kim, Youngmi Yang, Jumin Park, Jooyoung Cheon, Young Dae Kwon, Clemens Fürnsinn
    PLOS ONE.2017; 12(8): e0183881.     CrossRef
  • Self-rated health predicts decline in instrumental activities of daily living among high-functioning community-dwelling older people
    Kimiko Tomioka, Norio Kurumatani, Hiroshi Hosoi
    Age and Ageing.2016;[Epub]     CrossRef
Interaction of Body Mass Index and Diabetes as Modifiers of Cardiovascular Mortality in a Cohort Study
Seung Hyun Ma, Bo-Young Park, Jae Jeong Yang, En-Joo Jung, Yohwan Yeo, Yungi Whang, Soung-Hoon Chang, Hai-Rim Shin, Daehee Kang, Keun-Young Yoo, Sue Kyung Park
J Prev Med Public Health. 2012;45(6):394-401.   Published online November 29, 2012
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  • 13 Crossref
AbstractAbstract PDF

Diabetes and obesity each increases mortality, but recent papers have shown that lean Asian persons were at greater risk for mortality than were obese persons. The objective of this study is to determine whether an interaction exists between body mass index (BMI) and diabetes, which can modify the risk of death by cardiovascular disease (CVD).


Subjects who were over 20 years of age, and who had information regarding BMI, past history of diabetes, and fasting blood glucose levels (n=16 048), were selected from the Korea Multi-center Cancer Cohort study participants. By 2008, a total of 1290 participants had died; 251 and 155 had died of CVD and stroke, respectively. The hazard for deaths was calculated with hazard ratio (HR) and 95% confidence interval (95% CI) by Cox proportional hazard model.


Compared with the normal population, patients with diabetes were at higher risk for CVD and stroke deaths (HR, 1.84; 95% CI, 1.33 to 2.56; HR, 1.82; 95% CI, 1.20 to 2.76; respectively). Relative to subjects with no diabetes and normal BMI (21 to 22.9 kg/m2), lean subjects with diabetes (BMI <21 kg/m2) had a greater risk for CVD and stroke deaths (HR, 2.83; 95% CI, 1.57 to 5.09; HR, 3.27; 95% CI, 1.58 to 6.76; respectively), while obese subjects with diabetes (BMI ≥25 kg/m2) had no increased death risk (p-interaction <0.05). This pattern was consistent in sub-populations with no incidence of hypertension.


This study suggests that diabetes in lean people is more critical to CVD deaths than it is in obese people.



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    Family Medicine and Community Health.2024; 12(Suppl 1): e002340.     CrossRef
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    Kundan Solanki, Sajjan Rajpoot, Evgeny E. Bezsonov, Alexander N. Orekhov, Rohit Saluja, Anita Wary, Cassondra Axen, Kishore Wary, Mirza S. Baig
    PeerJ.2022; 10: e13651.     CrossRef
  • Obesity and metabolic outcomes in a safety-net health system
    Michael P. Huynh, Patrick T. Bradshaw, Michele M. Tana, Carly Rachocki, Ma Somsouk
    Biodemography and Social Biology.2020; 65(3): 257.     CrossRef
  • Lifestyle Factors and Gender-Specific Risk of Stroke in Adults with Diabetes Mellitus: A Case-Control Study
    Jian Guo, Tianjia Guan, Ying Shen, Baohua Chao, Mei Li, Longde Wang, Yuanli Liu
    Journal of Stroke and Cerebrovascular Diseases.2018; 27(7): 1852.     CrossRef
  • Nonlinear association of BMI with all-cause and cardiovascular mortality in type 2 diabetes mellitus: a systematic review and meta-analysis of 414,587 participants in prospective studies
    Francesco Zaccardi, Nafeesa N. Dhalwani, Dimitris Papamargaritis, David R. Webb, Gavin J. Murphy, Melanie J. Davies, Kamlesh Khunti
    Diabetologia.2017; 60(2): 240.     CrossRef
  • Determinants of mortality in patients with type 2 diabetes: a review
    Jana Engelmann, Ulf Manuwald, Constanze Rubach, Joachim Kugler, Andreas L. Birkenfeld, Markolf Hanefeld, Ulrike Rothe
    Reviews in Endocrine and Metabolic Disorders.2016; 17(1): 129.     CrossRef
  • Analysis between nitric oxide synthase 1 (NOS1) and risk of obesity
    Hyun Kyung Park, Su Kang Kim, Oh Young Kwon, Joo-Ho Chung, Seong-Kyu Lee
    Molecular & Cellular Toxicology.2016; 12(2): 217.     CrossRef
  • Association between different obesity measures and the risk of stroke in the EPIC Spanish cohort
    Itziar Abete, Larraitz Arriola, Nerea Etxezarreta, Imanol Mozo, Conchi Moreno-Iribas, Pilar Amiano, Nerea Egüés, Estibaliz Goyenechea, Adolfo Lopez de Munain, Maite Martinez, Noemi Travier, Carmen Navarro, Maria-Dolores Chirlaque, Maria-Jose Tormo, Diana
    European Journal of Nutrition.2015; 54(3): 365.     CrossRef
  • Relationship of body mass index and abdominal obesity in rural population of Krasnodarsky kray taken
    Elena V. Bolotova, Irina V. Samorodskaya, Irina M. Komissarova
    Obesity and metabolism.2015; 13(1): 25.     CrossRef
  • Associations of prediabetes with all-cause and cardiovascular mortality: A meta-analysis
    Yi Huang, Xiaoyan Cai, Peisong Chen, Weiyi Mai, Hongfeng Tang, Yuli Huang, Yunzhao Hu
    Annals of Medicine.2014; 46(8): 684.     CrossRef
  • High Peritoneal Transport Status Was Not Associated with Mortality in Peritoneal Dialysis Patients with Diabetes
    Naya Huang, Jiehui Chen, Li Fan, Qian Zhou, Qingdong Xu, Ricong Xu, Liping Xiong, Xueqing Yu, Haiping Mao, Zhanjun Jia
    PLoS ONE.2014; 9(10): e110445.     CrossRef
  • Body Mass Index and Mortality Among Japanese Patients With Type 2 Diabetes: Pooled Analysis of the Japan Diabetes Complications Study and the Japanese Elderly Diabetes Intervention Trial
    Shiro Tanaka, Sachiko Tanaka, Satoshi Iimuro, Yasuo Akanuma, Yasuo Ohashi, Nobuhiro Yamada, Atsushi Araki, Hideki Ito, Hirohito Sone
    The Journal of Clinical Endocrinology & Metabolism.2014; 99(12): E2692.     CrossRef
  • Validação cruzada entre o percentual de gordura mensurado pela absortometria radiológica de dupla energia e a equação de Deurenberg em idosas
    Piettra Moura Galvão-Pereira, Giselma Alcantara-Silva, Adriano Eduardo Lima-Silva, Dante Wanderley Lima, Amandio Aristides Rihan Geraldes
    Revista Brasileira de Geriatria e Gerontologia.2013; 16(4): 681.     CrossRef
Reliability and Data Integration of Duplicated Test Results Using Two Bioelectrical Impedence Analysis Machines in the Korean Genome and Epidemiology Study.
Boyoung Park, Jae Jeong Yang, Ji Hyun Yang, Jimin Kim, Lisa Y Cho, Daehee Kang, Chol Shin, Young Seoub Hong, Bo Youl Choi, Sung Soo Kim, Man Suck Park, Sue K Park
J Prev Med Public Health. 2010;43(6):479-485.
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  • 1 Crossref
AbstractAbstract PDF
The Korean Genome and Epidemiology Study (KoGES), a multicenter-based multi-cohort study, has collected information on body composition using two different bioelectrical impedence analysis (BIA) machines. The aim of the study was to evaluate the possibility of whether the test values measured from different BIA machines can be integrated through statistical adjustment algorithm under excellent inter-rater reliability. METHODS: We selected two centers to measure inter-rater reliability of the two BIA machines. We set up the two machines side by side and measured subjects' body compositions between October 2007 and December 2007. Duplicated test values of 848 subjects were collected. Pearson and intra-class correlation coefficients for inter-rater reliability were estimated using results from the two machines. To detect the feasibility for data integration, we constructed statistical compensation models using linear regression models with residual analysis and R-square values. RESULTS: All correlation coefficients indicated excellent reliability except mineral mass. However, models using only duplicated body composition values for data integration were not feasible due to relatively low R2 values of 0.8 for mineral mass and target weight. To integrate body composition data, models adjusted for four empirical variables that were age, sex, weight and height were most ideal (all R2>0.9). CONCLUSIONS: The test values measured with the two BIA machines in the KoGES have excellent reliability for the nine body composition values. Based on reliability, values can be integrated through algorithmic statistical adjustment using regression equations that includes age, sex, weight, and height.


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  • Nutritional Consequences and Management After Gastrectomy
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    Hanyang Medical Reviews.2011; 31(4): 254.     CrossRef
Seasonal Variation of Food Intake in Food Frequency Questionnaire among Workers in a Nuclear Power Plant.
Jae Jeong Yang, Sue Kyung Park, Hyun Sul Lim, Kwang Pil Ko, Younjhin Ahn, Yoon Ok Ahn
J Prev Med Public Health. 2007;40(3):239-248.
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  • 52 Download
  • 6 Crossref
AbstractAbstract PDF
This study was conducted to investigate the systematic error, such as seasonal change or inadequate food items, in a food frequency questionnaire administered to workers in a Nuclear Power Plant, Korea. METHODS: We performed three repeat-tests with 28 subjects on May 13, July 8 and Dec 16, 1992. Our food frequency questionnaire (FFQ) comprised 84 foods organized into 7 food-groups, and was composed of the items of usual intake frequency (8 categories) and the amount per intake (3 or 4 categories) over the previous year. We compared the means of intake frequency and the frequency of the portion-size according to each season using Repeated Measures ANOVA and Pearson's chisquare test with Fisher's exact test. RESULTS: We found the significant seasonal changes of several food items in intake frequency measurement. These items were typical seasonal foods such as mandarin orange, plum and green vegetables, while the single questions consisted of inadequate food items such as thick beef or similar soup and various kimchi products. Significant seasonal changes in portion-size were found in only two items: cooked rice-brown and fresh.frozen fishes. CONCLUSIONS: The systematic errors observed could caused loss of validity in the FFQ. Consideration should be given for seasonal variation in FFQ survey and methodological concerns are needed to improve the quality for measuring usual diet pattern.


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JPMPH : Journal of Preventive Medicine and Public Health