Kosuke Saida

This study aimed to identify the characteristics of community-dwelling older people who are difficult to reach by mail survey in anticipation of a future infectious disease crisis. A baseline survey of 1808 community-dwelling older people was conducted in May 2021, and a follow-up survey of 935 respondents was conducted in May 2023. Factors predictive of responding to the follow-up survey included age at baseline, sex, comorbidities, living with family, long-term care insurance, a history of falls, the Simple Frailty Index, and a Questionnaire on Changes in Lifestyle in the Past Month (QCL). Participants were divided into the responding (n = 330) and non-responding (n = 605) groups. Binomial logistic regression analysis was used to analyze items that showed significant differences in the between-group comparison: odds ratios (ORs) of 2.36, 1.84, 1.69, 1.57, and 1.20 for living alone, having comorbidities, having long-term care insurance, fatigue, and reduced ability to communicate, respectively. If social distancing is required in the future, we believe that face-to-face support should be prioritized for people who live alone, have comorbidities, use long-term care insurance, or are aware of fatigue and limited communication, as it is highly unlikely that they will be able to continue exchanging written information.

This study aimed to test the hypothesis that knowledge derived from indirect assessments can be used to identify fall risk factors during a period of social distancing. A baseline survey of 1953 community-dwelling older adults was conducted in May 2020, with a follow-up survey performed in May 2023 to assess the situation 3 years later. In total, 339 individuals were followed from baseline to follow-up. Baseline age, sex, Questionnaire for Change of Life, Frailty Screening Index, and Questionnaire for Medical Checkup of Old-Old (QMCOO) scores and subscales were used to determine fall predictors. In addition, history of falls in the past year was assessed at follow-up (outcome). The participants were categorized into fall (n = 78) and non-fall (n = 261) groups. Using binary logistic regression analysis, items that showed significant differences in a between-group comparison were analyzed, and age and history of falls, which were sub-items of the QMCOO, were identified as predictors of falls. Although special assessments may be required during periods of social distancing, we believe that it is important for these assessments to continue being performed as they are performed during normal times.

The frequency of falls increases with age. In Japan, the population is aging rapidly, and fall prevention measures are an urgent issue. However, assessing fall risk during the coronavirus disease pandemic was complicated by the social distancing measures implemented to prevent the disease, while traditional assessments that involve actual measurements are complicated. This prospective cohort study predicted the risk of falls in community-dwelling older adults using an assessment method that does not require actual measurements. A survey was conducted among 434 community-dwelling older adults to obtain data regarding baseline attributes (age, sex, living with family, use of long-term care insurance, and multimorbidity), Frailty Screening Index (FSI) score, and Questionnaire for Medical Checkup of Old-Old (QMCOO) score. The participants were categorized into fall (n = 78) and non-fall (n = 356) groups. The binomial logistic regression analysis showed that it is better to focus on the QMCOO sub-item score, which focuses on multiple factors. The items significantly associated with falls were Q5 (odds ratio [OR] 1.95), Q8 (OR 2.33), and Q10 (OR 3.68). Our results were similar to common risk factors for falls in normal times. During the pandemic, being able to gauge the risk factors for falls without actually measuring them was important.