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Development and Validation of a Nomogram Predicting Sarcopenia in Community-Dwelling Older Adults
Sook Kyoung Park1, Hyuk Joo Kim2, Young-Me Lee3
1Jeonbuk National University, Jeonju, South Korea.
None:
This study aimed to identify risk factors for sarcopenia and develop a nomogram to predict its probability among community-dwelling older adults. This cross-sectional secondary data analysis used the 2023 Korea National Health and Nutrition Examination Survey, which employed a stratified multistage clustered probability sampling method. Of the 6929 respondents, 1836 community-dwelling adults aged 65 years and older were included. Complex-sample logistic regression was used to identify significant risk factors, and a nomogram was developed using the resulting regression coefficients. Predictive accuracy was evaluated using the area under the receiver operating characteristic curve (AUC). Sarcopenia was significantly associated with the following risk factors: age, kidney disease, obesity status, chewing discomfort, and sedentary time. Compared to adults aged 65 to 69 years, those aged 75 to 79 had 2.80 times higher odds, and those aged 80 years and older had 5.01 times higher odds. Participants with kidney disease had 3.29 times higher odds than those without. Compared to obese individuals, the odds of sarcopenia were 17.04, 6.80, and 2.72 times higher for underweight, normal weight, and overweight individuals, respectively. Chewing discomfort increased the odds by 1.65 times, and each additional hour of sedentary time increased the risk by 7%. The nomogram included obesity, sedentary time, age, kidney disease, and chewing discomfort, with an AUC of 0.809. Obesity, sedentary behavior, age, kidney disease, and chewing discomfort were key factors affecting the risk of sarcopenia in older adults. The developed nomogram provides a practical tool for early identification of high-risk community-dwelling older adults. Future research should incorporate longitudinal data and objective indicators to enhance predictive models and validate the tools in practice.
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