Background: During postural control, older adults are more dependent on proprioception than are young adults. Ankle proprioception, which plays an important role in maintaining postural balance, decreases with age. Published studies are insufficient to establish a significant age difference in postural sway resulting from the known age-related decrease in ankle proprioception and do not examine various detailed test conditions. Objects: The present study aimed to compare ankle proprioception between older and younger groups along dimensions of position vs. force proprioception and dorsiflexion vs. plantarflexion. The present study also aimed to compare postural sway between young and older women during quiet standing under two sensory conditions. Methods: We recruited seven young women aged 21–24 and seven older women aged 60–63. Ankle proprioception was assessed as the accuracy of the joint position sense (JPS) and the force sense (FS). Postural sway was assessed using center-of-pressure measurements recorded during quiet standing under two sensory positions: eyes open and eyes closed with head tilted back. Results: Older women had lower JPS in dorsiflexion and lower FS in plantarflexion than did younger women. We found no significant age differences in JPS in plantarflexion or in FS in dorsiflexion. We observed a main effect of group on postural sway in two sway parameters out of three. We observed significant differences in JPS with dorsiflexion, and in FS with plantarflexion. Conclusion: Proprioception for ankle plantar flexor decreased more significantly with aging than did that for ankle dorsiflexor, accounting for the impaired postural balance observed in older women.

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.