Epidemiology and Health

Original Articles

Factors Associated with Insulin Resistance in a Middle-Aged Non-Obese Rural Population: The Chungju Metabolic Disease Cohort (CMC) Study: Sun Young Lim, Hee Sung Ha, Hyuk-Sang Kwon, Jin-Hee Lee, Hyeon Woo Yim, Kun-Ho Yoon, Won-Chul Lee, Ho-Young Son, Yong-Moon Park; Epidemiol Health. 2011;33:e2011009. Published online September 26, 2011; DOI: https://doi.org/10.4178/epih/e2011009

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Abstract

<sec><title>OBJECTIVES</title>We aimed to determine the characteristics affecting insulin resistance in non-obese middle-aged adults in a rural community.</sec><sec><title>METHODS</title>A total of 1,270 non-diabetic adults aged between 40 and 64 years old with body mass index (BMI) less than 25 kg/m2 were analyzed. Subjects with insulin resistance were defined as those who had the highest quartile value of the homeostasis model assessment of insulin resistance (HOMA-IR) in a non-diabetic population.</sec><sec><title>RESULTS</title>A total of 217 subjects (20.6%) had insulin resistance. Prevalence of metabolic syndrome was significantly higher in insulin-resistant subjects in both men (29.3% vs. 10.3%) and women (34.1% vs. 15.6%). Among metabolic syndrome components, elevated waist circumference and elevated triglyceride were higher in insulin-resistant subjects in both genders. After being controlled for socioeconomic status and lifestyle related covariates, the association between insulin resistance and BMI was statistically significant in the category of 23.0-24.9 kg/m2 in men (adjusted OR, 4.63; 95% confidence interval [95% CI], 1.77-12.15) using the category of 18.5-20.9 kg/m2 as a reference. In addition, the association between insulin resistance and abdominal obesity was statistically significant only for men (adjusted OR, 2.57; 95% CI, 1.29-5.11).</sec><sec><title>CONCLUSION</title>Insulin resistance appears to be highly associated with high BMI and abdominal obesity, even in non-obese, non-diabetic middle-aged men.</sec>

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Relapsing-remitting multiple sclerosis patients display an altered lipoprotein profile with dysfunctional HDL
Winde Jorissen, Elien Wouters, Jeroen F. Bogie, Tim Vanmierlo, Jean-Paul Noben, Denis Sviridov, Niels Hellings, Veerle Somers, Roland Valcke, Bart Vanwijmeersch, Piet Stinissen, Monique T. Mulder, Alan T. Remaley, Jerome J. A. Hendriks
Scientific Reports.2017;[Epub] CrossRef
Insulin Resistance of Normal Weight Central Obese Adolescents in Korea Stratified by Waist to Height Ratio: Results from the Korea National Health and Nutrition Examination Surveys 2008–2010
Won Kyoung Cho, Hyojin Kim, Hyun Young Lee, Kyung Do Han, Yeon Jin Jeon, In Ah Jung, Shin Hee Kim, Kyoung Soon Cho, So Hyun Park, Min Ho Jung, Byung-Kyu Suh
International Journal of Endocrinology.2015; 2015: 1. CrossRef
Impact of ENPP1 K121Q on Change of Insulin Resistance after Web-Based Intervention in Korean Men with Diabetes and Impaired Fasting Glucose
Ji Yeon Kang, Sook Hee Sung, Yeon Ju Lee, Tae In Choi, Seung Jin Choi
Journal of Korean Medical Science.2014; 29(10): 1353. CrossRef
Genetic determinants of cardiometabolic risk: A proposed model for phenotype association and interaction
Piers R. Blackett, Dharambir K. Sanghera
Journal of Clinical Lipidology.2013; 7(1): 65. CrossRef

Prevalence Rates and Risk Factors of Overweight and Obesity in Children and Adolescents: Using Korean National Health and Nutrition Examination Survey 2005 Data.: Shinkwan Kang, Soonduck Kim, Jesuk Lee; Korean J Epidemiol. 2008;30(2):188-197. Published online December 31, 2008; DOI: https://doi.org/10.4178/kje.2008.30.2.188

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Abstract

PURPOSE
To investigate the prevalence rates of overweight and obesty, and their associations in children and adolescents(12-18years) who were defined as normal weight, overweight , and obese.

METHODS

Korean National Health and Nutrition Examination Survey 2005 raw data was utilized. The data on the 669 subjects aged 12-18 consisted of variables from the health interview survey, health examination and nutrition survey, and health consciousness behavior survey. Overweight and obesity was evaluated by established body mass index criteria. Chi-squire and Fisher exact test were performed to analyze differences among normal, overweight and obese groups according to basic characteristics and health consciousness behavior. Logistic regression was used to analyze risk factors for the overweight and obese groups.

RESULTS

Overweight and obesity prevalence rates were 11.7% and 8.1%, respectively. Of the subjects from urban regions, 20% were overweight and 12.2% were obese. Of those from semi-urban regions, 10.2% were overweight and 3.8% were obese. Of those from rural regions, 9.0% were overweight and 10.1% were obese. The obesity rate in semi-urban regions were 0.38% times lower than the rural rate.

CONCLUSIONS

Geographical location constitutes a risk factor for overweight and obesity, which may influence preventative and education programs aimed at schools and the general community.

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Soo Kyoung Kim, Saegyeol Choi, Hyekyeong Kim
Korean Journal of Health Education and Promotion.2021; 38(1): 13. CrossRef
Regional Adolescent Obesity and Overweight Status in Korea from 2018–2019: Comparison between Two Data Sources
Dong-Hee Ryu, Su-Jin Lee
Healthcare.2021; 9(12): 1751. CrossRef
A Structural Model for Health Risk Behavior of Late Adolescents: Based on 2010 Korea Adolescent Health Survey
Young-Ju Jee, Young-Hae Kim
Journal of Korean Academy of Nursing.2014; 44(2): 179. CrossRef
Association between Obesity and Physical Activity about Middle and High School Students in Korea
Tae-Hee Park, Mi-Hwa Jung, Sun-Mi Jeong, Hyung-Su Park, Chae-Yeon Han, Sun-An Hong, Si-Young You, Kyung-Rye Moon
The Journal of the Korea institute of electronic communication sciences.2013; 8(3): 505. CrossRef
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Young Hwa Kong, Min Sun Kim, Dae-Yeol Lee
Annals of Pediatric Endocrinology & Metabolism.2013; 18(2): 65. CrossRef
Eating Habit, Body Image, and Weight Control Behavior by BMI in Korean Female High School Students - Using Korea Youth Risk Behavior Web-based Survey 2010 Data -
Mi-Hyun Kim
The Korean Journal of Food And Nutrition.2012; 25(3): 579. CrossRef
A Case of Severe Diabetic Ketoacidosis in a Child with Type 2 Diabetes
Jaesung Yu, Hyunju Jin, Joontae Ko, Hoseok Kang
Journal of Korean Society of Pediatric Endocrinology.2011; 16(1): 46. CrossRef
The Body Mass Index as a Prognostic Factor of Critical Care
So Yeon Lim, So I Kim, Yon Ju Ryu, Jin Hwa Lee, Eun Mi Chun, Jung Hyun Chang
The Korean Journal of Internal Medicine.2010; 25(2): 162. CrossRef
Obesity and Metabolic Syndrome among Children and Adolescents in Korea
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Journal of the Korean Medical Association.2010; 53(2): 142. CrossRef

A Study on the Relationship Between Smoking Habits and BMI of Adult Males.: Joo Hee Han, Myung Kim, Dae Hyu Oh, Hee Choul Ohrr; Korean J Epidemiol. 1998;20(1):39-50.

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Abstract PDF: Abstract
Smoking, obesity and diet are just a few of the multifactors which have been suggested to be associated with the risk of CHD. It is a common phenomenon that persons who stop smokin gain weight. This fear of gaining weight is often given as a reason for giving up to quit smoking. The purpose of this study is to find the effects of cessation of smoking on body weight and the difference of BMI distribution according to smoking habits. The subjects of this study were 72 techinical high school teachers in Seoul and Kyounggi-Do, 85 offical wokers of the S-Company and 81 auto industrial workers in PyoungTaek. The investigation for this study has been conducted from Oct. 27th to Oct. 31st 1997. The method was self-feported questionnaire survey which consists of general characterisics, smoking habits and its relevant questions. The questionnaires were revised after two-times of pre-tests, carried out for twenty subjects. The results are as follows ; 1. Smoking habits have significant relations with diet, exercise, drinking and the amount of daily smoking. 2. BMI among different smoking habits groups showed significant differences in following variables ; age, the interaction between exercise and smoking habits, drinking level, the interaction etween drinking level and smoking habits and the interaction between total smoking duration and smoking gabits. 3. The mean values of BMI are 23.5 in non-smoker, 23.8 in ex-smoker and 23.4 in current smoker. There are no statistically significant differencs among amoking habits. 4. The average of 2.14kg weight gain is witnessed after 6 months of the cessation of smoking. Current weight was high by 3.89kh in average compared to the pre-cessation weight(p=0.0001). 5. The odds ratio for gaining weight among ex-smokers is 8.94 in "increase or very increase" group in diet compared to those of "no change". 6. The multiple regression analysis has a significant model in current smoker(p=0.001). The mean BMI of those who were "very active" in exercise is higher than that of "inactive" or "active". The mean BMI of those who were "light or moderate ot heavy drinker" is lower than that of "non-drinker". The mean BMI of those who have the monthly income 1.5millions-1.99millions won is significantly higher than those having less than 1.5millions or more than 2.0millions won. The implication of this study could suggest that health education for smoking cessation needs new approches to minimize weight gain.; Summary

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