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"Sung Hi Kim"

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"Sung Hi Kim"

Original Articles
The Influence of Negative Mental Health on the Health Behavior and the Mortality Risk: Analysis of Korean Longitudinal Study of Aging from 2006 to 2014
Eun Ryeong Jun, Sung Hi Kim, Yoon Jeong Cho, Yun-A Kim, Joo Young Lee
Korean J Fam Med 2019;40(5):297-306.   Published online September 11, 2019
DOI: https://doi.org/10.4082/kjfm.18.0068
Background
Several studies have shown that negative mental health increases risky health behavior and mortality risk. We investigated the relationship between mental health and health behavior, and the causal association between mental health and mortality risk.
Methods
We used data from the 8-year (2006–2014) Korean Longitudinal Study of Aging with a cohort of 10,247 individuals (whom we divided into a younger group aged <65 years and an older group aged ≥65 years). Mental health was assessed with the following factors: depression, social engagement, and satisfaction of life. Health behavior was assessed with smoking, alcohol use, and regular exercise. Mortality risk was calculated using survival status and survival months as of 2014. Multiple logistic regression and Cox proportional hazard analysis were performed.
Results
Negative mental health was associated with current smoking and sedentary life style, but not with alcohol consumption. In addition, it was associated with an increase in all-cause mortality risk. The increase in mortality risk in the highest quartile (vs. lowest) was 1.71 times (hazard ratio [HR], 1.71; 95% confidence interval [CI], 1.12– 2.62) and 2.07 times (HR, 2.07; 95% CI, 1.60–2.67) for the younger and older group, respectively.
Conclusion
Our results show that mental health affects health behavior and mortality risk. A key inference from this study is that improving mental health can lead to positive changes in health behavior and reduce the risk of mortality.

Citations

Citations to this article as recorded by  
  • Effect of Lifestyle Counselling via a Mobile Application on Disease Activity Control in Inflammatory Arthritis: A Single-Blinded, Randomized Controlled Study
    Türker Kurt, Diana Vossen, Falk Schumacher, Johannes Strunk, Dmytro Fedkov, Christine Peine, Felix Lang, Abdullah Khalil, Ralph Brinks, Stefan Vordenbäumen
    Nutrients.2024; 16(10): 1488.     CrossRef
  • The Moderating Effect of Mental Health on the Relationship Between Cardiovascular Disease Awareness and Health Behaviors of Middle-Aged Korean Chinese Workers With Cardiovascular Risk Factors in Korea
    Yu Zhu Zhang, Seon Young Hwang
    Journal of Transcultural Nursing.2023; 34(2): 131.     CrossRef
  • Combined Effects of Depression and Chronic Disease on the Risk of Mortality: The Korean Longitudinal Study of Aging (2006-2016)
    Hyunji Kim, Sung Hi Kim, Yoon Jeong Cho
    Journal of Korean Medical Science.2021;[Epub]     CrossRef
  • KLoSA—Korean Longitudinal Study of Aging
    Jungun Lee
    Korean Journal of Family Medicine.2020; 41(1): 1.     CrossRef
  • Mortality and cause of death in physical activity and insufficient physical activity participants: a longitudinal follow-up study using a national health screening cohort
    Chanyang Min, Dae Myoung Yoo, Jee Hye Wee, Hyo-Jeong Lee, Soo Hwan Byun, Hyo Geun Choi
    BMC Public Health.2020;[Epub]     CrossRef
  • 6,397 View
  • 98 Download
  • 6 Web of Science
  • 5 Crossref
Background
We evaluated the effects of socioeconomic factors and psychosocial factors, both individually and combined, on all-cause mortality risk (mortality risk).
Methods
We conducted an 8-year (2006–2014) longitudinal analysis of 10,247 individuals who took part in the Korean Longitudinal Study of Aging, a nationwide survey of people aged 45–79 years. Socioeconomic vulnerability (SEV) was assessed with factors such as education, household income, commercial health insurance, and residential area. Mental health (MH) was assessed with factors such as depression, social engagement, and life satisfaction. The covariates were age, gender, marital status, cohabiting, number of chronic diseases, and health behaviors such as regular exercise, smoking, and alcohol intake. We used a Cox proportional hazard analysis to investigate the effects of SEV and MH on mortality risk and also to analyze the superimposed effects of SEV-MH on mortality risk.
Results
After the controlling for the covariates, high SEV and negative MH were found to be strong predictors of all-cause mortality. The highest quartile of SEV (vs. lowest) had a 1.70 times greater mortality risk (hazard ratio [HR], 1.70; 95% confidence interval [CI], 1.24–2.33) and the highest quartile of MH (vs. lowest) had a 2.13 times greater mortality risk (HR, 2.13; 95% CI, 1.72–2.64). Being in the highest quartile for both SEV and MH (vs. lowest) increased mortality risk more than 3 times (HR, 3.11; 95% CI, 2.20–4.40).
Conclusion
High SEV and negative MH were independently associated with increased mortality risk, and their superimposed effects were associated with an increased risk of mortality.

Citations

Citations to this article as recorded by  
  • Sustained Low Income, Income Changes, and Risk of All-Cause Mortality in Individuals With Type 2 Diabetes: A Nationwide Population-Based Cohort Study
    Hong Seok Lee, Jimin Clara Park, Inkwan Chung, Junxiu Liu, Seong-Su Lee, Kyungdo Han
    Diabetes Care.2023; 46(1): 92.     CrossRef
  • The role of social factors in the successful ageing – Systematic review
    J. Takács, C. Nyakas
    Developments in Health Sciences.2022; 4(1): 11.     CrossRef
  • Combined Effects of Depression and Chronic Disease on the Risk of Mortality: The Korean Longitudinal Study of Aging (2006-2016)
    Hyunji Kim, Sung Hi Kim, Yoon Jeong Cho
    Journal of Korean Medical Science.2021;[Epub]     CrossRef
  • KLoSA—Korean Longitudinal Study of Aging
    Jungun Lee
    Korean Journal of Family Medicine.2020; 41(1): 1.     CrossRef
  • 6,134 View
  • 64 Download
  • 3 Web of Science
  • 4 Crossref
Socioeconomic Status in Association with Metabolic Syndrome and Coronary Heart Disease Risk
Ji Young Kim, Sung Hi Kim, Yoon Jeong Cho
Korean J Fam Med 2013;34(2):131-138.   Published online March 20, 2013
DOI: https://doi.org/10.4082/kjfm.2013.34.2.131
Background

The purpose of this study was to examine the association of metabolic syndrome (MS) coronary heart disease (CHD) with socioeconomic status (SES).

Methods

The participants were 2,170 (631 men and 1,539 women), aged over 40 years who had visited for health screening from April to December in 2009. We classified them into three SES levels according to their education and income levels. MS was defined using the criteria of modified National Cholesterol Education Program Adult Treatment Panel III and CHD risk was defined using Framingham risk score (FRS) ≥ 10%.

Results

High, middle, and low SES were 12.0%, 73.7%, and 14.3%, respectively. The prevalence of MS was 18.1%. For high, middle, and low SES, after adjusted covariates (age, drinking, smoking, and exercise), odds ratios for MS in men were 1.0, 1.41 (confidence interval [CI], 0.83 to 2.38; P > 0.05), and 1.50 (CI, 0.69 to 3.27; P > 0.05), respectively and in women were 1.0, 1.74 (CI, 1.05 to 3.18; P < 0.05), and 2.81 (CI, 1.46 to 2.43; P < 0.05), respectively. The prevalence of FRS ≥ 10% was 33.5% (adjusted covariates were drinking, smoking, and exercise) and odds ratios for FRS ≥ 10% in men were 1.0, 2.86 (CI, 1.35 to 6.08; P < 0.001), and 3.12 (CI, 1.94 to 5.00; P < 0.001), respectively and in women were 1.0, 3.24 (CI, 1.71 to 6.12; P < 0.001), and 8.80 (CI, 4.50 to 17.23; P < 0.001), respectively.

Conclusion

There was an inverse relationship between SES and FRS ≥ 10% risk in men, and an inverse relationship between SES and both risk of MS and FRS ≥ 10% in women.

Citations

Citations to this article as recorded by  
  • The Impact of Physical Activity on Weight Loss in Relation to the Pillars of Lifestyle Medicine—A Narrative Review
    Natalia Niezgoda, Tomasz Chomiuk, Przemysław Kasiak, Artur Mamcarz, Daniel Śliż
    Nutrients.2025; 17(6): 1095.     CrossRef
  • Anthropometric and Physiological Measures in Individuals With At‐Risk Mental State (ARMS) Compared With Individuals With Schizophrenia: Findings From a Lower Middle‐Income Country
    M. O. Husain, M. Abid, A. B. Khoso, M. Riaz, F. Ahmed, S. Shakoor, S. Lane, N. Husain, G. Foussias, I. Qurashi, I. B. Chaudhry
    Early Intervention in Psychiatry.2025;[Epub]     CrossRef
  • Role of sex and gender-related variables in development of metabolic syndrome: A prospective cohort study
    Pouria Alipour, Zahra Azizi, Valeria Raparelli, Colleen M. Norris, Alexandra Kautzky-Willer, Karolina Kublickiene, Maria Trinidad Herrero, Khaled El Emam, Peter Vollenweider, Martin Preisig, Carole Clair, Louise Pilote
    European Journal of Internal Medicine.2024; 121: 63.     CrossRef
  • Association between Metabolic Syndrome and Risk of Hypopharyngeal Cancer: A Nationwide Cohort Study from Korea
    Jeong Wook Kang, Hyeon-Kyoung Cheong, Su Il Kim, Min Kyeong Lee, Young Chan Lee, In-Hwan Oh, Young-Gyu Eun
    Cancers.2023; 15(18): 4454.     CrossRef
  • Quality of diet and odds of metabolic syndrome in Iranian adults: Baseline results from the PERSIAN Kavar cohort study (PKCS)
    Hamid Ghalandari, Moein Askarpour, Mehran Nouri, Ali Reza Safarpour, Mohammad Reza Fattahi, Marzieh Akbarzadeh
    Nutrition, Metabolism and Cardiovascular Diseases.2023; 33(9): 1760.     CrossRef
  • Prevalence of Metabolic Syndrome in Women After Maternal Complications of Pregnancy: An Observational Cohort Analysis
    Emily Aldridge, Maleesa Pathirana, Melanie Wittwer, Susan Sierp, Shalem Y. Leemaqz, Claire T. Roberts, Gustaaf A. Dekker, Margaret A. Arstall
    Frontiers in Cardiovascular Medicine.2022;[Epub]     CrossRef
  • A prospective registry analysis of psychosocial and metabolic health between women with and without metabolic syndrome after a complicated pregnancy
    Emily Aldridge, K. Oliver Schubert, Maleesa Pathirana, Susan Sierp, Shalem Y. Leemaqz, Claire T. Roberts, Gustaaf A. Dekker, Margaret A. Arstall
    BMC Women's Health.2022;[Epub]     CrossRef
  • Socioeconomic Disparities in Cardiovascular Health in South Korea
    Chi-Young Lee, Eun-Ok Im
    Journal of Cardiovascular Nursing.2021; 36(1): 8.     CrossRef
  • Machine Learning to Predict the Progression of Bone Mass Loss Associated with Personal Characteristics and a Metabolic Syndrome Scoring Index
    Chao-Hsin Cheng, Ching-Yuan Lin, Tsung-Hsun Cho, Chih-Ming Lin
    Healthcare.2021; 9(8): 948.     CrossRef
  • Risk assessment of metabolic syndrome prevalence involving sedentary occupations and socioeconomic status
    Ming-Shu Chen, Chi-Hao Chiu, Shih-Hsin Chen
    BMJ Open.2021; 11(12): e042802.     CrossRef
  • Association between the living environment and the risk of arterial hypertension and other components of metabolic syndrome
    Agne Braziene, Abdonas Tamsiunas, Dalia Luksiene, Ricardas Radisauskas, Sandra Andrusaityte, Audrius Dedele, Jone Vencloviene
    Journal of Public Health.2020; 42(2): e142.     CrossRef
  • Relationship between the shift of socioeconomic status and cardiovascular mortality
    Jidong Sung, Yun-Mi Song, Kyung Pyo Hong
    European Journal of Preventive Cardiology.2020; 27(7): 749.     CrossRef
  • Western diet-induced fear memory impairment is attenuated by 6-shogaol in C57BL/6N mice
    Michael O. Gabriel, Maria Nikou, Oluwole B. Akinola, Daniela D. Pollak, Spyridon Sideromenos
    Behavioural Brain Research.2020; 380: 112419.     CrossRef
  • An Application of Metabolic Syndrome Severity Scores in the Lifestyle Risk Assessment of Taiwanese Adults
    Chih-Ming Lin
    International Journal of Environmental Research and Public Health.2020; 17(10): 3348.     CrossRef
  • The combined effect of socioeconomic status and metabolic syndrome on depression: the Korean National Health and Nutrition Examination Survey (KNHANES)
    B. Kim, E. Y. Park
    BMC Public Health.2020;[Epub]     CrossRef
  • The Relationship between the IFNG (rs2430561) Polymorphism and Metabolic Syndrome in Perimenopausal Women
    Daria Schneider-Matyka, Małgorzata Szkup, Aleksander Jerzy Owczarek, Marzanna Stanisławska, Anna Knyszyńska, Anna Lubkowska, Elżbieta Grochans, Anna Jurczak
    Medicina.2020; 56(8): 384.     CrossRef
  • The burden of metabolic syndrome in patients living with HIV/AIDS receiving care at referral hospitals of Northwest Ethiopia: A hospital-based cross-sectional study, 2019
    Alemu Gebrie
    Diabetes & Metabolic Syndrome: Clinical Research & Reviews.2020; 14(5): 1551.     CrossRef
  • Measurement of Socioeconomic Position in Research on Cardiovascular Health Disparities in Korea: A Systematic Review
    Chi-Young Lee, Yong-Hwan Lee
    Journal of Preventive Medicine and Public Health.2019; 52(5): 281.     CrossRef
  • Life Course Effects of Socioeconomic and Lifestyle Factors on Metabolic Syndrome and 10-Year Risk of Cardiovascular Disease: A Longitudinal Study in Taiwan Adults
    Chen-Mao Liao, Chih-Ming Lin
    International Journal of Environmental Research and Public Health.2018; 15(10): 2178.     CrossRef
  • Socio‐economic factors influencing the development of end‐stage renal disease in people with Type 1 diabetes – a longitudinal population study
    C. Toppe, A. Möllsten, S. Schön, G. Dahlquist
    Diabetic Medicine.2017; 34(5): 676.     CrossRef
  • Association between smoking and health outcomes in an economically deprived population: the Liverpool Lung Project
    F C Sherratt, J K Field, M W Marcus
    Journal of Epidemiology and Community Health.2017; 71(8): 806.     CrossRef
  • Cannabis use in people with severe mental illness: The association with physical and mental health – a cohort study. A Pharmacotherapy Monitoring and Outcome Survey study
    Jojanneke Bruins, Marieke GHM Pijnenborg, Agna A Bartels-Velthuis, Ellen Visser, Edwin R van den Heuvel, Richard Bruggeman, Frederike Jörg
    Journal of Psychopharmacology.2016; 30(4): 354.     CrossRef
  • Gender Difference in Osteoporosis Prevalence, Awareness and Treatment: Based on the Korea National Health and Nutrition Examination Survey 2008~2011
    Yunmi Kim, Jung Hwan Kim, Dong Sook Cho
    Journal of Korean Academy of Nursing.2015; 45(2): 293.     CrossRef
  • Very low rates of screening for metabolic syndrome among patients with severe mental illness in Durban, South Africa
    Shamima Saloojee, Jonathan K Burns, Ayesha A Motala
    BMC Psychiatry.2014;[Epub]     CrossRef
  • 5,262 View
  • 24 Download
  • 24 Crossref
The Diagnostic Criteria of Metabolic Syndrome and the Risk of Coronary Heart Disease according to Definitions in Men.
Hyouk Soo Seo, Sung Hi Kim, Soon Woo Park, Jong Yeon Kim, Geon Ho Lee, Hye Mi Lee
Korean J Fam Med 2010;31(3):198-207.   Published online March 20, 2010
DOI: https://doi.org/10.4082/kjfm.2010.31.3.198
Background
Early detection of metabolic syndrome (MS) is important to prevent complications. Yet, there is no internationally agreed definition for MS. This study was performed to compare the diagnostic criteria of MS using various definitions and agreements, and to find better definition for screening high risk group of coronary heart disease. Methods: The participants were 426 men above forty years old who had visited to have health screening in a general hospital in Daegu from March to December in 2007. The diagnostic criteria of MS and Kappa statistic were calculated according to the following five diagnostic definitions; modified World Health Organization (WHO), National Cholesterol Education Program Third Adult Treatment Panel (NCEP-ATP III), International Diabetes Federation (IDF), American Heart Association/National Heart, Lung and Blood Institute (AHA/NHLBI) and NCEP-ATP III modified waist circumference ≥ 90 cm (modified NCEP-ATP III). The sensitivity and specificity of each definition of MS were calculated with respect to high risk group by Framingham risk score (FRS). Results: The diagnostic criteria of MS were 6.6% by IDF, 7.7% by WHO, 10.6% by NCEP-ATP III, 18.1% by modified NCEP-ATP III and 22.3% by AHA/NHLBI. The kappa satistic ranged from 0.30 to 0.87. The sensitivity of each definition with respect to FRS was 8.3% in IDF, 13.4% in WHO, 15.3% in NCEP-ATP III, 27.4% in modified NCEP-ATP III and 32.5% in AHA/NHLBI. Conclusion: There was great difference in the diagnostic criteria of MS according to diagnostic definitions. The author suggests that AHA/NHLBI or modified NCEP-ATP III definition may be better for screening high risk group of coronary heart disease than others.

Citations

Citations to this article as recorded by  
  • Prevalence of metabolic syndrome and cardiovascular risk level in a vulnerable population
    Chun‐Ja Kim, JeeWon Park, Se‐Won Kang
    International Journal of Nursing Practice.2015; 21(2): 175.     CrossRef
  • 1,893 View
  • 14 Download
  • 1 Crossref
Estimation of Long-term Care among in-patients at a Veterans Hospital.
Sung Hi Kim
J Korean Acad Fam Med 2006;27(3):215-221.   Published online March 10, 2006
Background
: This study was done to estimate the size of long-term care in-patients in one Veterans Hospital. Using KADL and KIADL (developed in 2002, verified validity & reliability), we evaluated the activities of daily living among in-patients in Daegu Veterans Hospital.

Methods : During the two months in June and July 2003, interviews were conducted by two interviewers. Daegu Veterans Hospital is 300-bed hospital and 257 in-patients were interviewed. Information from patients, care-givers, nurses and others were obtained. We classified a patient as severely disabled requiring long-term care if one's total-KADL score over 16.

Results : The patients studied were representative of in-patients of Daegu Veterans Hospital. Their characteristics were males, old aged, slightly lower education but with high income compared to community based people. Among the total, 34% were classified as severe disabled (total-KALD score over 16) needing long-term care. The distribution of total-KADL was bi-modal (both the independent group and the dependent group occupied a high percentage). But the distribution of total-KIADL was more skewed to the independent group and we were able to estimate that the real long-term care need might be over 34%. Average admission period during the recent six months was 83.3 days in all-covered patients and 55.3 days in partial-covered patients. There was no significant correlation between the total-KADL/KIADL score and the admission period. It was suggested that Daegu Veterans Hospital was utilized as a long-term care hospital.

Conclusion : Among the total, 34% of admitted patients was classified as a long-term care group. Considering KIADL, the percentage of patients needing long-term care may be greater than those studied.
  • 1,350 View
  • 14 Download
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