Regional differences in the associations of diet quality, obesity, and possible sarcopenia using the seventh Korea National Health and Nutrition Examination Survey (2016-2018) (original) (raw)
Table 1. General characteristics of study participants by residential area
Values are presented as unweighted number (weighted %) [standard error].
1
Using the chi-square test, accounting for the complex survey design.
2
The number of chronic disease was categorized into 3 groups according to the number of diseases diagnosed among hypertension, diabetes, and dyslipidemia.
3
Using regression models after taking into account the complex survey design.
Table 2. General characteristics of participants according to their obesity and sarcopenia status
Values are presented as unweighted number (weighted %) [standard error].
Normal, non-sarcopenia and non-obesity; Obesity, non-sarcopenia and obesity; Sarcopenia, sarcopenia and non-obesity; Sarcopenic obesity, sarcopenia and obesity.
1
Using the chi-square test, accounting for the complex survey design.
2
The number of chronic diseases was categorized into 3 groups according to the number of diseases diagnosed among hypertension, diabetes, and dyslipidemia.
Table 3. Korean Healthy Eating Index (KHEI) scores according to obesity and sarcopenia status and stratified by residential area1
Values are presented as mean±standard error.
Normal, non-sarcopenia and non-obesity; OB, non-sarcopenia and obesity; SAR, sarcopenia and non-obesity; SAR OB, sarcopenia and obesity.
1
Means and p for trend are obtained using generalized linear regression models after adjusting for age and gender.
Table 4. Korea Healthy Eating Index (KHEI) scores and odds ratios for obesity, sarcopenia, and sarcopenic obesity, stratified by residential area1
Values are presented as odds ratio (95% confidence interval).
Normal, non-sarcopenia and non-obesity; Obesity, non-sarcopenia and obesity; Sarcopenia, sarcopenia and non-obesity; Sarcopenic obesity, sarcopenia and obesity.
1
The explanatory variable was KHEI in a continuous format; Odds ratios were obtained using multinomial logistic regression models after adjusting for age, gender, household type, household income, education, smoking, drinking, physical activity, food security status, and the number of chronic diseases; The odds ratios can be interpreted as the risk for obesity, sarcopenia, or sarcopenic obesity relative to normal status if a subject’s KHEI score were to increase by 1 unit, with the other variables in the model held constant.