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The present study examined relationships between socioeconomic status (SES) and obesity and body mass index (BMI) as well as the effects of health-related behavioral and psychological factors on the relationships.
A cross-sectional population-based study was conducted on Korean adults aged 20 to 79 years using data from the 2001, 2005, and 2007 to 2009 Korea National Health and Nutrition Examination Survey. Multivariate logistic and linear regression models were used to estimate odds ratios of obesity and mean differences in BMI, respectively, across SES levels after controlling for health-related behavioral and psychological factors.
We observed significant gender-specific relationships of SES with obesity and BMI after adjusting for all covariates. In men, income, but not education, showed a slightly positive association with BMI (
Results confirmed gender-specific disparities in the associations of SES with obesity and BMI among adult Korean population. Focusing on intervention for health-related behaviors may be effective to reduce social inequalities in obesity.
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Several previous studies have found that healthy behaviors substantially reduce non-communicable disease incidence and mortality. The present study was performed to estimate the prevalence of four modifiable healthy behaviors and a healthy lifestyle among Korean adults according to socio-demographic and regional factors.
We analyzed data from 199 400 Korean adults aged 19 years and older who participated in the 2010 Korean Community Health Survey. We defined a healthy lifestyle as a combination of four modifiable healthy behaviors: non-smoking, moderate alcohol consumption, regular walking, and a healthy weight. We calculated the prevalence rates and odds ratios of each healthy behavior and healthy lifestyle according to socio-demographic and regional characteristics.
The prevalence rates were as follows: non-smoking, 75.0% (53.7% in men, 96.6% in women); moderate alcohol consumption, 88.2% (79.7% in men, 96.9% in women); regular walking, 45.0% (46.2% in men, 43.8% in women); healthy weight, 77.4% (71.3% in men, 73.6% in women); and a healthy lifestyle, 25.5% (16.4% in men, 34.6% in women). The characteristics associated with a low prevalence of healthy lifestyle were male gender, younger age (19 to 44 years of age), low educational attainment, married, living in a rural area, living in the Chungcheong, Youngnam, or Gwangwon-Jeju region, and poorer self-rated health.
Further research should be implemented to explore the explainable factors of disparities for socio-demographic and regional characteristics to engage in the healthy lifestyle among adults.
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To measure the prevalence of behavioural risk factors for obesity among urban adolescent school children in Chennai, India.
This study was performed as a cross-sectional study using a World Health Organization-designed Global School-based Student Health Survey questionnaire (modified for India) among adolescent school children studying in 30 randomly selected secondary and higher secondary schools in Chennai city. 1842 adolescents studying in the VIII to XII standards were randomly selected for the study.
In the present study, 40.7% of the students ate fruit one or more times per day and 74.5% of the students ate vegetables one or more times per day. Nearly 20% of the students ate fast food items on 4 to 7 days during the previous week. Among the students, 30.4% watched television for more than two hours per day. Nearly 68% of the girls and 22% of the boys did not participate in outdoor sports activities. When the pattern of physical activity of the students was assessed, it was observed that 15.6% were inactive, 43.4% were minimally active, and the remaining 41.0% belonged to the category of health enhancing physical activity. Among the students, 6.2% were overweight and 5.2% were obese.
The prevalence of risk factors for obesity was quite high among the adolescents. This study also showed that a great proportion of overweight/obese adolescents had a correct perception of their body weight and they were making efforts to modify risk factors such as television viewing, computer use, a sedentary lifestyle, and unhealthy dietary habits.
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