Changes in frailty and lifestyle among community-dwelling older adults: A two-point cross-sectional study during and after the COVID-19 pandemic in Japan.

We aimed to verify the characteristics of lifestyles and frailty among older adults during and after the COVID-19 pandemic. This two-point cross-sectional study conducted a baseline survey (BL) in 2020 and a follow-up survey (FU) in 2023 with community-dwelling individuals aged ≥65 years in Japan. The 700 and 572 participants in the BL and FU were analyzed. We compared frailty occurrence and lifestyle characteristics between both surveys. In the BL and FU, 38.3 %, 52.4 %, and 9.3 % and 29.4 %, 59.4 %, and 11.2 % of the individuals were classified as robust, pre-frail, and frail, respectively, showing a significant decrease in the number of robust, and an increase in the number of pre-frail. A significant decrease in dietary intake was observed among robust individuals in the FU, with an overall significant decrease in communication opportunities in the BL. Therefore, lifestyle changes due to infection control measures may have a delayed impact on frailty.

Fall Risk Prediction for Community-Dwelling Older Adults: Analysis of Assessment Scale and Evaluation Items without Actual Measurement.

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.

[Categorization of the health status and its transition of community-dwelling older adults during the coronavirus disease (COVID-19) epidemic].

AIM: The purpose of this study was to categorize and clarify transitions in the health status of older adults living in the community during the coronavirus disease (coronavirus disease 2019: COVID-19) pandemic. METHODS: The participants were older adults (≥65 years of age) who lived in Takasaki City, Gunma Prefecture. The survey items included basic information and subjective health perception (questionnaire for medical checkup of old-old). Latent class analyses were conducted for the first (baseline) and second surveys (6 months). The scores for each item were compared to identify the characteristics of each class at baseline and at 6 months. In addition, transitions in class affiliation from baseline to 6 months were summarized. RESULTS: A total of 434 of 1,953 participants (mean age: 79.1 years, 98 males and 336 females) completed the survey (22.2%). In both time periods, the responses were categorized into four classes: 1) good, 2) poor physical, oral and cognitive function, 3) poor social status and lifestyle, and 4) poor in all except social status and lifestyle. During 6 months of follow-up, a transition from the generally good class to the poor physical, oral and cognitive functions class was observed in many cases. CONCLUSIONS: The health status of the older adults living in the community was classified into four classes, and changes in health status occurred even within a short period of time during the COVID-19 pandemic.

Factors associated with falls during voluntary self-isolation among community-dwelling older people: a longitudinal study.

[Purpose] We aimed to explore the factors that predict falls in community-dwelling older people over 6 months during their voluntary self-isolation for the coronavirus disease (SARS-CoV-2). [Participants and Methods] In this longitudinal study, we surveyed older people aged ≥65 years living in Takasaki City, Gunma Prefecture, using a questionnaire. We investigated the relationship between the frailty screening index and fall rate. [Results] A total of 588 older adults (response rate, 35.7%) filled and returned the questionnaire during the study period. Of these, 391 participants who had not applied for long-term care insurance and had completed the data on the response items were included in the study. Based on their responses in the survey questionnaire, 35 (8.95%) participants were grouped into the fall group and 356 into the non-fall group. Subsequently, the "no" response to "Can you recall what happened 5 minutes ago?" and "yes" response to "Have you felt tired for no reason (in the past 2 weeks)?" were identified as the significant factors associated with falls. [Conclusion] It is important to pay attention to the subjective evaluation of patients' cognitive decline and fatigue to prevent falls owing to the implementation of SARS-CoV-2 countermeasures.

Associated factors of new subjective cognitive decline complaints after a 6-month period among community-dwelling older adults during the COVID-19 pandemic in Japan.

BACKGROUND: The aim of this study was to determine the number of new subjective cognitive decline (SCD) complaints and associated factors in community-dwelling older adults during the COVID-19 pandemic in Japan. METHOD: A prospective cohort study was conducted in two periods: May to June 2020, and November 2020 to January 2021. We mailed a questionnaire to 1953 older adults in the first survey, and received 700 responses in the second. We analysed 534 participants without SCD in the first survey. We collected data on sociodemographic characteristics and administered the Questionnaire for Medical Checkup of Old-Old (QMCOO) to assess respondents' health condition. SCD was operationally defined using the QMCOO as reports of (1) forgetfulness, and (2) difficulty in naming dates. The subjects were divided into two groups by their condition at the second survey: an SCD (new SCD complaints) and a no-SCD (no new SCD complaints) group. RESULTS: A total of 85 (15.9%) participants had new SCD complaints. The Mann-Whitney U-test and chi-squared test showed that the SCD group had significantly more risk factors of SCD: walking speed (P = 0.001), smoking (P = 0.001), and existence of person with whom the patient could consult when disordered (P = 0.002). Multiple logistic regression analysis revealed that walking speed (odds ratio (OR) = 2.115, 95% confidence interval (CI): 1.259-3.553) and the presence of person to consult (OR = 3.619, 95% CI: 1.553-8.433) were significant related factors of new SCD complaints. CONCLUSION: Maintenance of physical condition and social support were associated with new SCD complaints during the COVID-19 pandemic.

Relationship between consistent subjective cognitive decline and occurrence of falls six months later.

PURPOSE: To examine the association between consistent subjective cognitive decline and fall occurrence six months later. METHOD: A cohort study was conducted at two time points in community-dwelling older adults. The first survey was conducted from May to July 2020 and the second from November 2020 to January 2021. Older adults without missing data who had not fallen during the past year were analyzed. The questionnaire included sociodemographic data, a questionnaire for medical checkup of older adults, and a frailty screening index. We divided the participants into three groups according to the occurrence of subjective cognitive decline (SCD): 1) no SCD (did not complain of SCD at both time points), 2) unstable SCD (complained of SCD once), and 3) consecutive SCD (consistently complained of SCD). Multiple logistic regression analysis was used to examine the association between fall occurrence and SCD. Fall occurrences were obtained from the second survey. RESULTS: In total, 322 participants were included in the analysis. The numbers of patients with no SCD, unstable SCD, and consecutive SCD were 226 (70.2%), 61 (19.0%), and 35 (10.9%), respectively. In the second survey, the number of falls was 26 (8.1%). Multiple logistic regression analysis showed that consecutive SCD was associated with fall occurrence, even after adjusting for age, sex, comorbidity, cohabitants, and frailty status (OR:3.143, 95% CI:1.076-9.388); however, unstable SCD was not (OR:2.348, 95% CI:0.816-6.468). CONCLUSION: Consistent complaints of SCD were associated with the occurrence of falls. We highlighted the importance of evaluating SCD over time when considering falls.

Factors for the change in frailty status during the COVID-19 pandemic: A prospective cohort study over six- and 12-month periods in Japan.

We aimed to verify the frailty status and the factors associated with the change in frailty status during the COVID-19 pandemic. A three-wave cohort study was conducted every six months, from May to July 2020, November 2020 to January 2021, and again from May to July 2021. The frailty status was assessed using the frailty screening index. Multivariate generalized linear mixed-effects models were used to determine whether changes in frailty status were associated with health conditions and lifestyle. The 404 survey forms were analyzed. Decline in chewing function (beta = 0.552) and leg muscle strength weakness (beta = 0.515) were significantly associated with the change in frailty status over six months, and leg muscle strength weakness (beta = 0.512) was significantly associated over 12 months. Risk factors associated with worsening health should be assessed for appropriate support. It is especially important to assess subjective leg muscle weakness in older adults.

[An investigation to discriminate frailty based on the Questionnaire for medical checkup of old-old: A pilot study using the item response theory].

AIM: This study aimed to investigate a method for scoring the questionnaire for medical checkup of old-old (QMCOO) and to clarify a cut-off score for the discrimination of frailty. METHODS: Survey forms were distributed to 2,586 older adults. For old-old adults, the item characteristics of the QMCOO were indicated using the item response theory (IRT). A receiver operating characteristic (ROC) analysis was performed using the total score of the fitting model of QMCOO for suggesting a cut-off score to discriminate frailty. The cross-validity of the cut-off score was verified among young-old adults. RESULTS: Among 1,680 adults who responded, data from 975 old-old and 421 young-old adults were analyzed. The method for scoring zero or one on each item in QMCOO conformed to the IRT model. The item discrimination and difficulty met the criteria. An ROC analysis showed that the area under the curve (AUC) and cut-off score for the discrimination of frailty were 0.871 and 4 points (sensitivity = 0.811, specificity = 0.766, positive likelihood ratio [LR+] = 3.469, and negative likelihood ratio [LR-] = 0.247), respectively. For young-old adults, the AUC and cut-off score were 0.874 and 4 points (sensitivity = 0.741, specificity = 0.817, LR+= 4.053, and LR- = 0.317), respectively. CONCLUSIONS: The method for scoring zero or one on each item of the QMCOO was valid. A cut-off score of 4 for the discrimination of frailty demonstrated the interpretability of the QMCOO, while the usefulness of the QMCOO in young-old adults demonstrated cross-validity.

Risk factors for falls among community-dwelling older adults during voluntary self-isolation: analysis based on frailty screening index subscales.

[Purpose] This study aimed to assess fall-related risk factors among community-dwelling older adults during a period of voluntary self-isolation for preventing the spread of COVID-19. [Participants and Methods] This was a cross-sectional study. Survey questionnaire forms were distributed to 2,586 community-dwelling older adults in Takasaki City, Gunma Prefecture, Japan. Completed questionnaires were returned by mail. [Results] Of the 1,645 people who responded, 1,040 people aged 65 and over who did not apply for long-term care insurance and fully completed the questionnaire were included in this study. Since no in-person measurements were required, we utilized the Frailty Screening Index for the evaluations. We evaluated the relationship between questionnaire responses and fall rates among community-dwelling older adults. Among the results, "yes" responses to "Do you think you walk more slowly than before?" were identified as significantly associated with falls. [Conclusion] One must pay careful attention to subjectively assessing decreases in walking speed as a fall prevention measure during periods of self-restraint to prevent the spread of COVID-19 infection.

[Construct validity in structural perspectives of the Questionnaire for medical checkup of old-old among community-dwelling older adults: A pilot study of a countermeasure against COVID-19].

AIM: This study aimed to clarify the construct validity of the Questionnaire for medical checkup of old-old (QMCOO). METHODS: In this cross-sectional study, questionnaires including the QMCOO were distributed to 1,953 older adults, and responses were returned by mail. We conducted an exploratory factor analysis (EFA) for the QMCOO among older participants (age ≥75 years) and extracted the relevant factors. Next, we structured the model for the QMCOO based on these factors and conducted a confirmatory factor analysis (CFA) using structural equation modeling. We conducted a CFA among young-older participants (age 65 to <75 years) for the same model. RESULTS: Of the 1,110 (53.5%) adults who responded, data from the 994 respondents who provided complete answers were analyzed. Five factors were extracted from the results of the EFA: physical and mental condition, relationship with society, eating and smoking, chance for exercise, and cognitive function. The results of the CFA were as follows: comparative fit index (CFI) = 0.899, adjusted goodness of fit index (AGFI) = 0.965, root mean square error of approximation (RMSEA) = 0.034, and standardized root mean square residual (SRMR) = 0.040. Meanwhile, the results for young-older participants were as follows: CFI = 0.886, AGFI = 0.942, RMSEA = 0.035, and SRMR = 0.048. CONCLUSIONS: The QMCOO assessed health condition and was composed of multiple factors associated with frailty. The CFA results indicated that the model fit was good. The QMCOO showed sufficient structural validity. Therefore, the construct validity of the QMCOO was shown.

Transition to frailty in older Japanese people during the coronavirus disease 2019 pandemic: a prospective cohort study.

BACKGROUND: Globally, lifestyles have changed to prevent the spread of coronavirus disease 2019 (COVID-19). Therefore, we aimed to understand health and lifestyle conditions associated with frailty transition over 6 months and devise a method for identifying frailty among community-dwelling older people during the COVID-19 pandemic. METHOD: This community-based prospective cohort study was conducted from May to July 2020 (baseline) and November 2020 to January 2021 (follow-up) in Japan, with 1,953 community-dwelling older people (≥65 years) at baseline. To identify transition from non-frailty at baseline to frailty at follow-up, the Frailty Screening Index was used. For predicting frailty transition, two self-reported questionnaires assessing health and lifestyle conditions were employed. RESULTS: Overall, 706 individuals returned the baseline and follow-up questionnaires. Among the 492 non-frail older people at baseline, there was a 9.8% increase in frailty transition. The adjusted model for frailty transition by age, sex, multimorbidity, and living arrangements indicated that forgetfulness (odds ratio [OR] 2.74, 95% confidence interval [CI]: 1.00 to 7.51), falls in the past year (OR 2.26, 95% CI: 1.08 to 4.74), and subjective leg muscle weakness (OR 1.83, 95% CI: 1.05 to 3.21) were predictors of frailty transition. The combination of age ≥75 years and subjective leg muscle weakness showed moderate sensitivity, specificity, and % accuracy (0.688, 0.696, and 69.5%, respectively). CONCLUSIONS: Approximately 10% of older people showed new transitions to frailty over 6 months during the COVID-19 pandemic. A combination of age and subjective leg muscle weakness is a feasible measure to optimally identify frailty transition.

Construct validity of the Questionnaire for Older Senior Citizens based on a confirmatory factor analysis: A study during the period of self-restraint to prevent the spread of coronavirus disease 2019.

AIM: This study aims to clarify the construct and criterion-related validity of the Questionnaire for Older Senior Citizens (QO) during the COVID-19 pandemic. METHODS: This cross-sectional study was conducted in Japan between November 11, 2020 and January 10, 2021. Of the 1645 (63.5%) older adults who responded, data from 900 participants were analyzed. First, we conducted an exploratory factor analysis (EFA) among older-older adults (aged ≥75 years) and extracted the factors. Next, we conducted a confirmatory factor analysis (CFA) using structural equation modeling. We also conducted this analysis among younger-older adults (aged ≥65 and <75 years) using the same model. Moreover, we compared each item of the QO with frailty status. RESULTS: Results of the EFA revealed six factors: social conditions and lifestyle, subjective conditions, cognitive functions, physical activity, oral functions, and physical functions. The results of the CFA were as follows: comparative fit index (CFI) = 0.971, adjusted goodness of fit index (AGFI) = 0.978, root mean square error of approximation (RMSEA) = 0.018, and standardized root mean square residual (SRMR) = 0.030. The results among the younger-older adults were as follows: CFI = 0.880, AGFI = 0.940, RMSEA = 0.037, and SRMR = 0.048. Many QO items were significantly associated with frailty (P < 0.05). CONCLUSIONS: Among the older-older adults group, the model used for the QO has sufficient suitability and construct validity; among the younger-older adults group, there also is sufficient questionnaire suitability. Moreover, the QO has criterion related validity with frailty. Geriatr Gerontol Int 2021; 21: 1018-1025.

Actual Frailty Conditions and Lifestyle Changes in Community-Dwelling Older Adults Affected by Coronavirus Disease 2019 Countermeasures in Japan: A Cross-Sectional Study.

INTRODUCTION: Because of the countermeasures to prevent the spread of coronavirus disease 2019 (COVID-19) in Japan, it is easy to predict that the suspension of local activities and changes in lifestyle that lead to decreased activity will result in increased frailty and prefrailty rates in older adults. OBJECTIVE: To clarify the actual frailty conditions and lifestyle changes among community-dwelling older adults affected by COVID-19 countermeasures in Japan. METHODS: This cross-sectional study was conducted between May 8 and June 12, 2020. Self-reported questionnaires were distributed to 1,078 older adults aged ≥65 years. We used the frailty screening index to assess frailty status and developed the Questionnaire for Change of Life (QCL) to assess lifestyle changes, the amount of daily movement, leg muscle strength, meal size, worry or anxiety, and opportunities to talk to people. The differences in prevalence rates of frailty, prefrailty, and robustness between this study and the reference based on the Japanese meta-analysis were verified using the chi-square goodness of fit test. We compared each of the QCL results among the frailty, prefrailty, and robust groups using Fisher's exact test. RESULTS: Of 680 older adults (63.1%) analyzed, 60 (8.8%) had frailty and 354 (52.1%) had prefrailty. There was a significant difference between the observed and expected prevalence based on the reference (p = 0.018). The frailty status was significantly associated with lifestyle changes. In participants with frailty, the amount of daily movement, leg muscle strength, and meal size significantly decreased (p < 0.001), whereas worry or anxiety significantly increased (p = 0.040). In contrast, regardless of the frailty status, opportunities to talk to people decreased. CONCLUSION: The prevalence of frailty and prefrailty might have increased due to the effects of COVID-19 countermeasures. Moreover, the lifestyle of community-dwelling older adults affected by COVID-19 countermeasures has changed. Lifestyle changes were more pronounced among older adults with frailty.

Factors associated with falls in community-dwelling older adults: an analysis based on subscales of the frailty screening index.

[Purpose] We aimed to obtain new findings by investigating the relationship between the presence or absence of falls and the results from the Frailty Screening Index (FSI), which can be easily carried out. [Participants and Methods] A total of 780 community-dwelling older adults (age ≥65 years) were classified based on whether they had fallen in the past year as those who had fallen at least once (fall group), and those who had not (non-fall group). We compared the study groups using sub-items of the FSI to extract more specific fall-related factors. The FSI is a questionnaire that comprises five items with simple 'yes/no' responses. [Results] The following three out of five sub-items of the FSI were extracted as fall-related factors: 1) "no" to the question, "Do you do physical exercise, like walking, at least once a week?"; 2) "yes" to the question, "Do you think you walk slower than before?"; and 3) "yes" to the question, "Have you felt tired for no reason (in the past two weeks)?" [Conclusion] The study results suggest the significance of paying attention to participant responses to the sub-items on the FSI, instead of merely determining their frailty risk based on their total score.

Did the number of older adults with frailty increase during the COVID-19 pandemic? A prospective cohort study in Japan.

PURPOSE: To clarify the actual frail status over 6 months with the COVID-19 countermeasures. METHODS: This prospective cohort study was conducted between the baseline assessment from May 11 to July 10 in 2020, and the follow-up assessment from November 11, 2020, to January 10, 2021, in Japan. The survey forms were distributed among 1953 community-dwelling older adults. Frailty status was assessed using the Frailty Screening Index. RESULTS: In total, 702 older adults (35.2%) returned the survey forms, and 593 (mean age = 78.8 years, and 77.4% females) older adults without missing values for the survey forms were analyzed. Pre-frail and frail prevalence were 55.0 and 7.9% at the baseline, and 57.3 and 11.8% at the follow-up, respectively. Frailty transition that indicated transition from robust or pre-frail at the baseline to frail at the follow-up was 9.9%. CONCLUSION: Increase in frailty might indicate frailty related to implementation of COVID-19 countermeasures.

Association between frailty and changes in lifestyle and physical or psychological conditions among older adults affected by the coronavirus disease 2019 countermeasures in Japan.

AIM: This study aimed to clarify the association between frailty and changes in lifestyle and physical or psychological conditions among community-dwelling older adults affected by the coronavirus disease 2019 countermeasures in Japan. METHODS: This cross-sectional study was carried out between 8 May and 12 June 2020 in Japan. Self-reported questionnaires were distributed among 1353 older adults. To assess frailty, we used the frailty screening index. To assess changes in lifestyle and physical or psychological conditions, we developed the Questionnaire for Change of Life (QCL), which comprised five items related to frailty. Cronbach's α was calculated as a measure of internal consistency of QCL. We compared the score for each item in the QCL between the frailty and non-frailty groups. Multiple logistic regression analysis was used to show the factors that affect frailty status. RESULTS: In total, 856 older adults (63.3%) were analyzed. A total of 83 participants (9.7%) had frailty, and 755 participants (90.3%) had non-frailty. Cronbach's α for QCL was 0.552. We observed a significant decrease in daily movement, leg muscle strength and meal size among older adults with frailty compared with non-frailty (P < 0.001). Subjective leg muscle strength (odds ratio 3.257, 95% confidence interval 2.236-4.746) was negatively correlated with frailty. CONCLUSIONS: We suggest that each individual QCL item should be used in analyses involving the QCL. This report showed that subjective lifestyle changes affected by the coronavirus disease 2019 countermeasures were associated with frailty status. In particular, as older adults were aware of a decrease in their leg muscle strength, they were significantly more frail. Geriatr Gerontol Int 2021; 21: 39-42.

Do lifestyle measures to counter COVID-19 affect frailty rates in elderly community dwelling? Protocol for cross-sectional and cohort study.

INTRODUCTION: Local activities that functioned to prevent frailty in the elderly have been suspended or reduced as a countermeasure against COVID-19. As a result, frailty rates are expected to increase, and frailty is expected to worsen as a secondary problem associated with COVID-19 countermeasures. Therefore, this study aims to determine the extent of frailty in the elderly associated with lifestyle changes implemented as COVID-19 countermeasures, to ascertain actual lifestyle changes and clarify the existence of Corona-Frailty. We will also conduct Corona-Frailty screening to verify the effect of support provided as feedback to supporters of the elderly. METHODS AND ANALYSIS: The survey target area is Takasaki City, Gunma Prefecture, Japan. Phase I aims to verify the short-term effects of COVID-19. A questionnaire will be distributed to 465 community-dwelling elderly people, and responses will be obtained by post. Frailty will be evaluated using the Frailty Screening Index. Respondents who are frail and have had many changes in their lifestyle will be screened as high-risk people, and feedback will be provided to local supporters. The aim of Phase II will be to verify the long-term effects of COVID-19 and the effect of screening. A similar survey will be distributed twice after the first survey, once after 6 months and again after 1 year and the frailty rate will be tested. Furthermore, out of the subjects identified with frailty in Phase I, the progress of those who were screened and those who were not screened will be compared between groups. ETHICS AND DISSEMINATION: This study has been approved by the Research Ethics Committee of the Takasaki University of Health and Welfare (approval number: 2009). The results of this study will be reported to the policymaker, presented at academic conferences and published in peer-reviewed journals. TRIAL REGISTRATION NUMBER: UMIN000040335.

Quantitative evaluation of subjective posture recognition by physiotherapists using a 3D motion capture.

[Purpose] This study evaluated subjective posture recognition by physiotherapists with expertise in posture, examined the quantification of posture using a three-dimensional (3D) motion capture, and described posture-based characteristics. [Participants and Methods] We photographed good, normal, and bad postures in 12 participants using an infrared camera, and the resultant data were analyzed. [Results] We observed the largest displacement from a good to a bad posture in the tenth thoracic vertebra on the X-axis in the anterior-posterior direction in comparison with other index points. Further, we observed considerable differences between good and bad postures compared with other index points. Moreover, we noted significant differences between the amount of displacement between good to a normal posture and from a good to a bad posture. The vertical displacement of the Z-axis was smaller than other index points. [Conclusion] Th10 captured features from the three postures. The X-axis was displaced most between good and bad postures. Further, the amount of displacement on the Z-axis was less between good and bad posture, rendering it difficult to capture features. Therefore, the findings reported herein can be used to compare the front and rear directions of the X-axis for capturing postural changes.