• Journal of Sasang Constitutional Medicine
• /
• v.34 no.3
• /
• pp.41-49
• /
• 2022

Background Abdominal obesity, a major public health concern, is related to many health problems. In addition, it is influenced by individual characteristics. We investigated sleep quality and physical activity (PA) as risk factors for abdominal obesity, according to the Sasang constitutional medicine. Methods In this cross-sectional study, we analyzed data from 5,221 community-based participants. Sleep quality and PA were measured using structured questionnaires, and abdominal obesity was classified according to waist circumference. Sasang constitution (SC) was classified as Taeeumin (TE), Soeumin (SE), or Soyangin (SY) type, using an established SC questionnaire. Chi-square test and logistic regression analysis were performed to access the association of sleep quality and PA with abdominal obesity in individuals stratified according to the SC types. Results The percentage of poor sleep quality and inactive PA was the highest in the SE type, and the higher prevalence of abdominal obesity was found in the TE type. After adjusting for variables, inactive PA was associated with abdominal obesity in the TE type (OR=1.694, 95% CI=1.42-2.021), and in the SE type, abdominal obesity was associated with poor sleep quality (OR=1.688, 95% CI=1.091-2.611) and low PA (OR=2.127, 95% CI=1.163-3.89). Moreover, the combination of these two factors were also significantly associated with abdominal obesity in the TE and SE types. Conclusion Abdominal obesity was associated with sleep quality and PA, and these results were different in each SC type. Taking various associated lifestyles and individual characteristics in consideration may contribute to better management of abdominal obesity in clinical practice.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.18 no.1
• /
• pp.119-127
• /
• 2018

The formal data used in the business is managed in a table form without normalization due to lack of understanding and application of data modeling. If the balance of the database design is destroyed, it affects the speed of response to the data query, and the data obesity becomes high. In this paper, it is investigated how data obesity improved through database design through optimized data modeling. The data query path was clearly visualized by square design through data modeling based on the relationship between object (data) and object, from the radial and task - oriented isolation design where data obesity is excessive. In terms of data obesity, the obesity degree of the current research support database was 57.2%, but it was 16.2% in the new research support database, and the data obesity degree was reducd by 40.5%. In addition, by minimizing redundancy of data, the database has been improved to ensure the accuracy and integrity of the data.

• Journal of Obesity & Metabolic Syndrome
• /
• v.26 no.1
• /
• pp.23-27
• /
• 2017

Background: In Korea, the prevalence of obesity has steadily increased, and the socioeconomic burden of obesity has increased along with it. In 2015, the National Health Insurance Service (NHIS) signed a memorandum of understanding with the Korean Society for the Study of Obesity (KSSO), providing limited open access to its databases so that the status of obesity and obesity management could be investigated. Methods: Using NHIS databases, we analyzed nationwide population-based studies for obesity using the definition of obesity (body mass index ${\geq}25kg/m^2$) in subjects over the age of 20. Age and sex standardization were used for all data. Results: The KSSO released the 'Obesity Fact Sheet 2016' using the 2006-2015 NHIS Health Checkup database. The prevalence of obesity steadily increased from 28.7% in 2006 to 32.4% in 2015, and the prevalence of abdominal obesity also steadily increased from 18.4% in 2009 to 20.8% in 2015. The prevalence of class II obesity steadily increased from 2006 to 2015, such that the total prevalence was 4.8% in 2015 (5.6% in men and 4.0% in women). The highest prevalence of obesity was found in Jeju Island, while the lowest prevalence was found in Daegu City. The highest prevalence of abdominal obesity was also found in Jeju Island, while the lowest prevalence was found in Gwangju City. Conclusion: Based on the Obesity Fact Sheet 2016, a strategy for reducing the prevalence of obesity is needed, especially in Korean men.

• Korean Journal of Community Nutrition
• /
• v.28 no.5
• /
• pp.363-375
• /
• 2023

Objectives: The objective of this study was to identify factors associated with adolescent obesity, as well as any new factors that correlated with a change in the rate of obesity over time. Methods: The study used 5-yearly data collected by the Korea Youth Risk Behavior Survey starting from the year 2006 up until 2021 (data from 2nd, 7th, 11th, and 17th surveys were analyzed). Factors such as demographics, dietary factors, health behavioral factors, and mental health factors were studied. All data were analyzed using IBM SPSS 27.0, employing chi-square tests and multiple logistic regression analysis. Results: This study included data from a total of 255,200 participants. Factors contributing to obesity varied with time. Over the survey duration of 15 years, low academic achievement, parents with low levels of education, low frequency of fruit consumption, low frequency of fast food intake, long periods of being seated, and high levels of stress were significantly associated with a high rate of obesity. Factors that showed a new correlation with an increase in obesity rates included living with single parents, low frequency of muscle strengthening exercises, and experiencing intense sadness and despair in the past year. Factors that were correlated with a change in obesity rates over time included household economic status, frequency of carbonated beverage consumption, frequency of intense physical activity, and frequency of alcohol consumption. Breakfast intake and smoking were not significantly associated with obesity rates in the 15-year period. Conclusions: While several factors associated with obesity remained consistent over time, several new factors have emerged in response to social, economic, and environmental changes contributed to a change in obesity rate over time. Therefore, to prevent and manage adolescent obesity, continuous research into the new emergent factors contributing to obesity is needed.

• Journal of Korean Medicine for Obesity Research
• /
• v.4 no.1
• /
• pp.125-137
• /
• 2004

Objective: The purpose of this study is to investigate how to use the Quality of Life(QoL) of obesity and to study the report cases which measure QoL on obesity. Method: This study investigate the definition of Health-related Quality of Life(HRQoL), the measurement of Health-related Quality of Life, and the papers of Health-related Quality of Life on obesity through the books and medicine journals of HRQoL and obesity. Conclusions: 1. The QoL includes role functional ability, the degree and quality of social and community interaction, psychological state, somatic feeling, and life satisfaction than personal health and social well-being. 2. The investigator needs to evaluate the reliability, validity and sensitivity of the scale, and the appropriateness of the instrument for the target population When he decides measurement. 3. The investigator have the well-drilled supporter or himself managed the data and study population to prevent missing data. 4. The investigator should decide which is needed on obesity a obesity-specific or broad-ranging instrument, or both.

• Health Policy and Management
• /
• v.25 no.3
• /
• pp.152-161
• /
• 2015

We analyze the determinants of obesity and the chronic diseases using the Korea Health Panel data. Also we analyze the effect of obesity and the chronic diseases on the health care expenditures. Through this study, to reduce the health care expenditures, we suggest the policy implication that might curb the obesity and the chronic diseases. We estimate the determinants of obesity, the chronic diseases, and the health care expenditures using 2SLS (two stage least squares) estimation method under the simultaneous equations framework. Result says that obesity and chronic diseases significantly have positive effects on the health care expenditures. Also the determinants of the health care expenditures that have positive effects are age, income and health care utilization variables.

• Honam Mathematical Journal
• /
• v.43 no.4
• /
• pp.717-739
• /
• 2021

We used blood data to predict obesity by complementing the BMI risk, because some blood factors are significantly associated with obesity. For the sampling method, a two-step stratified colony sampling method was used based on sixteen blood factors collected by the Korea National Health and Nutrition Examination Survey(KNHANES). We identify the number of effective blood data of obesity in the final model as 6 ~ 8 factors that differ somewhat depending on age and gender. Also, the coefficient of determination that represents the predictive power of obesity in the regression model is the highest for both men and women of aged 19 and in their 20s and 30s, and the predictive power decreases with increasing age.

• Journal of Korean Biological Nursing Science
• /
• v.25 no.1
• /
• pp.32-42
• /
• 2023

Purpose: This study aimed to investigate the association between obesity and high-sensitivity C-reactive protein (hs-CRP) levels in Korean adults without cardiovascular disease (CVD). Methods: The subjects were 3,634 adults, and data were extracted from the seventh Korea National Health and Nutrition Examination Survey (KNHANES VII-3). A complex sampling design analysis was applied to reflect the stratified and clustered weights. The data were analyzed using the complex sample Rao-Scott chi-square test and multiple logistic regression analysis (in SPSS for Windows version 26.0). Obesity, according to body mass index (BMI), was defined as obesity (BMI = 25-29.9 kg/m²), high obesity (BMI = 30-34.9 kg/m²), and super-high obesity (BMI ≥ 35 kg/m²), and abdominal obesity (AO) was defined as a waist circumference (WC) ≥ 90 cm in males and WC ≥ 85 cm in females. Results: The odds ratios for moderate CVD risk (hs-CRP; 1-3 mg/dL) were 2.21, 4.16, and 7.13 in the obesity, high obesity, and super-high obesity groups, respectively, compared to the normal BMI group. The odds ratio for moderate CVD risk was 2.18 in males with AO and 1.88 in females with AO. The odds ratios for high CVD risk (hs-CRP > 3 mg/L) were 4.40 and 17.55 in the high obesity and super-high obesity groups, respectively, compared to the normal BMI group. Conclusion: This study provides evidence that early detection and prevention programs for CVD should include obesity-related interventions aiming to modulate hs-CRP.

• Journal of the Korean Society of School Health
• /
• v.22 no.1
• /
• pp.61-65
• /
• 2009

AIMS: Korean National Growth Chart was newly developed at 2007. Prevalence of obesity is expected to be changed according to reference data. This study was performed to compare the prevalence of obesity based on the newly developed growth curve with that of previous data. We also investigate the incidence of obesity, overweight, and normal criteria by two kinds of growth curves. Method: We obtained weight, height from 438 middle school students and 1786 high school students. We divided enrolled students into four groups (middle school boys, middle school girls, high school boys, high school girls). The obese, over weight group was defined as BMI(body mass index) more than 95th, 85th${\sim}$94th percentile respectively for age and sex. Obesity by relative weight was defined more than 20% of ideal body weight. We compare the prevalence of obesity in each group by the newly developed Korean National Growth Chart in 2007 and that in 1998. Result: Prevalence of obesity by BMI based on 2007 Korean National Growth Chart and that in 1998 were 8.2-12.9% and 9.0-20.4% respectively. The concordance rate were 99.0%-100% in obese group and 45.0%-91.9% in overweight group according to two kinds of reference data. Prevalence of obesity by relative weight was 11.7-23.0% that was same between 2007 Korean National Growth Chart and that in 1998 except middle school boys group. Conclusion: We found that there is a decrease in prevalence of Obesity by BMI based on 2007 Korean National Growth Chart. It is necessary to evaluate correlation between criteria for obesity and obesity related comorbid conditions for finding proper BMI or relative weight cut off value to prevent obesity and obesity related complications effectively.

• Physical Therapy Korea
• /
• v.28 no.3
• /
• pp.177-185
• /
• 2021

Background: Muscle undergoes change continuously with aging. Sarcopenia, in which muscle mass decrease with aging, is associated with various diseases, the risk of falling, and the deterioration of quality of life. Obesity and sarcopenia also have a synergy effect on the disease of the older adults. Objects: This study examined the risk factors for sarcopenia, sarcopenic obesity, and sarcopenia without obesity and developed prediction models. Methods: This machine-learning study used the 2008-2011 Korea National Health and Nutrition Examination Surveys in the analysis. After data curation, 5,563 older participants were selected, of whom 1,169 had sarcopenia, 538 had sarcopenic obesity, and 631 had sarcopenia without obesity; the remaining 4,394 were normal. Decision tree and random forest models were used to identify risk factors. Results: The risk factors for sarcopenia chosen by both methods were body mass index (BMI) and duration of moderate physical activity; those for sarcopenic obesity were sex, BMI, and duration of moderate physical activity; and those for sarcopenia without obesity were BMI and sex. The areas under the receiver operating characteristic curves of all prediction models exceeded 0.75. BMI could predict sarcopenia-related disease. Conclusion: Risk factors for sarcopenia-related diseases should be identified and programs for sarcopenia-related disease prevention should be developed. Data-mining research using population data should be conducted to enhance the effectiveness of early treatment for people with sarcopenia-related diseases through predictive models.