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"Sung-Hi Kim"

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"Sung-Hi Kim"

Original Articles
The Relationship between Smoking Level and Metabolic Syndrome in Male Health Check-up Examinees over 40 Years of Age
Gwang-Yul Hwang, Yoon-Jeong Cho, Rae-Ho Chung, Sung-Hi Kim
Korean J Fam Med 2014;35(5):219-226.   Published online September 24, 2014
DOI: https://doi.org/10.4082/kjfm.2014.35.5.219
Background

The objective of this study was to investigate the relationship between smoking and metabolic syndrome in men.

Methods

This cross-sectional study included 1,852 men over age 40 who underwent health screening from April 2009 to December 2010. We classified them into three smoking levels as non-, intermediate-, and heavy-smoker, considering their smoking status (non, ex, current) and amount (0, 1-29, ≥30 pack year [PYR]). The relationship between smoking level and metabolic syndrome was analyzed by logistic regression analysis, after covariates (age, body mass index, education, house income, alcohol intake, and physical activity) were controlled.

Results

The proportions of non-, intermediate-, and heavy-smokers were 31.8%, 56.2%, and 12.0%, respectively. Odds ratios (ORs) and 95% confidence intervals (95% CIs) for metabolic syndrome were 1.0, 1.58 (1.09-2.23), 1.92 (1.29-2.81) in non-, intermediate-, and heavy-smokers, respectively. For heavy-smokers compared with non-smokers, ORs and 95% CIs of a lower high density lipoprotein cholesterol, higher triglyceride, and higher fasting glucose were 2.47 (1.63-3.74), 1.71 (1.17-2.52), and 1.43 (1.02-2.00), respectively. In current-smokers, we divided into three subgroups according to PYR, and compared with 1-19 PYR, ORs and 95% CIs of 20-29 PYR and ≥30 PYR for metabolic syndrome were 2.07 (1.14-3.74) and 3.06 (1.66-5.62), respectively.

Conclusion

This study showed a positive dose-response relationship between smoking level and metabolic syndrome in men.

Citations

Citations to this article as recorded by  
  • Meta-analysis of the effects of smoking and smoking cessation on triglyceride levels
    Angela van der Plas, Meagan Antunes, Sandrine Pouly, Guillaume de La Bourdonnaye, Matthew Hankins, Annie Heremans
    Toxicology Reports.2023; 10: 367.     CrossRef
  • Association of environmental tobacco smoke exposure with metabolic syndrome: A longitudinal Cohort Study of 71,055 never smokers
    Hyo-In Choi, Seung Jae Lee, Jeong Gyu Kang, Sung Ho Lee, Bum Soo Kim, Byung Jin Kim
    Nutrition, Metabolism and Cardiovascular Diseases.2022; 32(11): 2534.     CrossRef
  • Predictive costs in medical care for Koreans with metabolic syndrome from 2009 to 2013 based on the National Health Insurance claims dataset
    Jeong Seon Yoo, Eun Yeong Choe, Yoo Mee Kim, Se Hwa Kim, Young Jun Won
    The Korean Journal of Internal Medicine.2020; 35(4): 936.     CrossRef
  • Lifestyle recommendations for the prevention and management of metabolic syndrome: an international panel recommendation
    Pablo Pérez-Martínez, Dimitri P. Mikhailidis, Vasilios G. Athyros, Mónica Bullo, Patrick Couture, María I. Covas, Lawrence de Koning, Javier Delgado-Lista, Andrés Díaz-López, Christian A. Drevon, Ramón Estruch, Katherine Esposito, Montserrat Fitó, Marta G
    Nutrition Reviews.2017; 75(5): 307.     CrossRef
  • Cigarette smoking/cessation and metabolic syndrome
    Genovefa D. Kolovou, Vana Kolovou, Sophie Mavrogeni
    Clinical Lipidology.2016; 11(1): 6.     CrossRef
  • Comparison of waist to height ratio and body indices for prediction of metabolic disturbances in the Korean population: the Korean National Health and Nutrition Examination Survey 2008–2011
    Seok Hui Kang, Kyu Hyang Cho, Jong Won Park, Jun Young Do
    BMC Endocrine Disorders.2015;[Epub]     CrossRef
  • 4,701 View
  • 26 Download
  • 5 Web of Science
  • 6 Crossref
Association of Leisure Time Physical Activity and Metabolic Syndrome over 40 Years
Mi-Young Park, Sung-Hi Kim, Yoon-Jeong Cho, Rae-Ho Chung, Ki-Tae Lee
Korean J Fam Med 2014;35(2):65-73.   Published online March 24, 2014
DOI: https://doi.org/10.4082/kjfm.2014.35.2.65
Background

This study aimed to investigate the relationship between leisure time physical activities (LTPA) and metabolic syndrome (MS).

Methods

Five thousand seven hundred and thirty two adults 40 years old or older were enrolled in the study from April 2009 to December 2010. National Cholesterol Education Program's Adult Treatment Panel III was used for the criteria of MS, and Minnesota Leisure Time Physical Activity Questionnaire was used to measure LTPA. After adjusted covariates (age, hypertension, smoking, drinking, education level, household income level, work time physical activities, and menopause for females), the relationship between LTPA and MS was analyzed using logistic regression analysis.

Results

The prevalence of MS was 22.8% in men, and 14.1% in women. Average LTPA was 1,498 kcal/wk in men, and 1,308 kcal/wk in women. After adjustment for covariates, the odds ratios of middle and low LTPA compared with high LTPA were 1.06 (0.87-1.34), 1.54 (1.08-1.75), for women, this same association was not seen in men. The prevalence of MS was 22.8% in men and 14.1% in women, and their LTPA burned 1,498 and 1,308 kcal/wk, respectively. When the odds ratio of MS for the high LTPA group was set at 1.0, the odds ratio of MS was 1.06 (0.87-1.34) in the middle LTPA group and 1.54 (1.08-1.75) in the low LTPA group in women, which showed that the MS risk increased when the LTPA was lower. This same association was not seen in men.

Conclusion

LTPA was independently associated with metabolic syndrome, but only for women.

Citations

Citations to this article as recorded by  
  • Prediction of Cardiorespiratory Fitness Level of Young Healthy Women Using Non-Exercise Variables
    Emilian Zadarko, Karolina H. Przednowek, Zbigniew Barabasz, Maria Zadarko-Domaradzka, Edyta Nizioł-Babiarz, Tomasz Hulewicz, Klaudia Niewczas-Czarna, Maciej Huzarski, Janusz Iskra, Élvio Rúbio Gouveia, Krzysztof Przednowek
    Applied Sciences.2023; 13(24): 13251.     CrossRef
  • Acculturation, Physical Activity, and Metabolic Syndrome in Asian American Adults
    Jingxi Sheng, Demetrius A. Abshire, Sue P. Heiney, Michael D. Wirth
    Journal of Transcultural Nursing.2022; 33(6): 675.     CrossRef
  • Relationship Between Physical Activity, Selected Lifestyle Behaviour and Metabolic Disease Risk among Municipality Employees in South Africa
    Takalani Clearance , Makama Andries Mo, Gert Lukas Stry, Abel Lamina Tor
    Asian Journal of Epidemiology.2019; 13(1): 20.     CrossRef
  • Metabolic syndrome: prevalence and risk factors in Korean gout patients
    Jae Hyun Jung, Gwan Gyu Song, Jong Dae Ji, Young Ho Lee, Jae-Hoon Kim, Young Ho Seo, Sung Jae Choi
    The Korean Journal of Internal Medicine.2018; 33(4): 815.     CrossRef
  • Relationship between Marital Status and Metabolic Syndrome in Korean Middle-Aged Women: The Sixth Korea National Health and Nutrition Examination Survey (2013–2014)
    Young-Ah Jung, Li-Ly Kang, Ha-Nui Kim, Hoon-Ki Park, Hwan-Sik Hwang, Kye-Yeung Park
    Korean Journal of Family Medicine.2018; 39(5): 307.     CrossRef
  • The Relationship between Socioeconomic Status and Metabolic Syndrome, Using Structural Equation Modelling
    Sung Hi Kim
    Korean Journal of Health Promotion.2016; 16(2): 92.     CrossRef
  • Concordance between muscle mass assessed by bioelectrical impedance analysis and by dual energy X-ray absorptiometry: a cross-sectional study
    Fanny Buckinx, Jean-Yves Reginster, Nadia Dardenne, Jean-Louis Croisiser, Jean-François Kaux, Charlotte Beaudart, Justine Slomian, Olivier Bruyère
    BMC Musculoskeletal Disorders.2015;[Epub]     CrossRef
  • 5,080 View
  • 28 Download
  • 7 Web of Science
  • 7 Crossref
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