Background: The use of transport other than cars is a modifiable factor in the association between driving cessation and social frailty. Clarifying this relationship may serve as a new preventive measure against social frailty among current non-drivers. This study examined the potential association of driving status and transport use with social frailty, as well as between the frequency of transport use and social frailty, among current non-drivers. Methods: This study included 977 middle-aged and older adults (average age, 65.3±4.8 years). The participants were classified as transport users (more than a few times a week) and transport non-users (less than a few times a month). Based on driving status and transport use, the groups were further classified into current driver, current non-driver/transport user, and current non-driver/transport non-user groups. The relationships between driving status, transport use, and social frailty were examined using multiple logistic regression. Results: The current non-driver group and the transport non-user group were significant association with a higher social frailty. The current non-driver/transport user group showed no association with social frailty compared with the current driver group. The odds ratio for the social frailty rate for The current non-driver/transport non-user group was 2.14 (95% confidence interval, 1.25–3.73). Conclusions Participants who neither drive nor take transport showed significant associations with increased social frailty. Compared with current driver/transport use, current non-driver/transport non-use was associated with social frailty.

Background: The use of transport other than cars is a modifiable factor in the association between driving cessation and social frailty. Clarifying this relationship may serve as a new preventive measure against social frailty among current non-drivers. This study examined the potential association of driving status and transport use with social frailty, as well as between the frequency of transport use and social frailty, among current non-drivers. Methods: This study included 977 middle-aged and older adults (average age, 65.3±4.8 years). The participants were classified as transport users (more than a few times a week) and transport non-users (less than a few times a month). Based on driving status and transport use, the groups were further classified into current driver, current non-driver/transport user, and current non-driver/transport non-user groups. The relationships between driving status, transport use, and social frailty were examined using multiple logistic regression. Results: The current non-driver group and the transport non-user group were significant association with a higher social frailty. The current non-driver/transport user group showed no association with social frailty compared with the current driver group. The odds ratio for the social frailty rate for The current non-driver/transport non-user group was 2.14 (95% confidence interval, 1.25–3.73). Conclusions Participants who neither drive nor take transport showed significant associations with increased social frailty. Compared with current driver/transport use, current non-driver/transport non-use was associated with social frailty.

Background: The use of transport other than cars is a modifiable factor in the association between driving cessation and social frailty. Clarifying this relationship may serve as a new preventive measure against social frailty among current non-drivers. This study examined the potential association of driving status and transport use with social frailty, as well as between the frequency of transport use and social frailty, among current non-drivers. Methods: This study included 977 middle-aged and older adults (average age, 65.3±4.8 years). The participants were classified as transport users (more than a few times a week) and transport non-users (less than a few times a month). Based on driving status and transport use, the groups were further classified into current driver, current non-driver/transport user, and current non-driver/transport non-user groups. The relationships between driving status, transport use, and social frailty were examined using multiple logistic regression. Results: The current non-driver group and the transport non-user group were significant association with a higher social frailty. The current non-driver/transport user group showed no association with social frailty compared with the current driver group. The odds ratio for the social frailty rate for The current non-driver/transport non-user group was 2.14 (95% confidence interval, 1.25–3.73). Conclusions Participants who neither drive nor take transport showed significant associations with increased social frailty. Compared with current driver/transport use, current non-driver/transport non-use was associated with social frailty.

Background: This study examined the association between memory function and reduced olfactory and gustatory function among independent community-dwelling older adults. Methods: This cross-sectional study included 127 older adults (65.4% women). We assessed their memory, odor, and taste identification skills. Open essence (OE) test and taste strips (TS) were used to identify hyposmia (OE test ≤6) and hypogeusia (TS test ≤8), respectively. Results: Participants with severe hyposmia had significantly poorer memory functions compared to participants without severe hyposmia. After adjusting for covariates, multivariate logistic regression models revealed a significant association between immediate recognition performance and a decreased likelihood of severe hyposmia (odds ratio=0.65; 95% confidence interval 0.47–0.90). We observed no significant association between taste function and memory. Conclusion Memory function may be associated with olfactory impairment in older adults.

Background: This study aimed to investigate the potential association between the combination of low physical activity and low dietary diversity with mild cognitive impairment (MCI) in older Japanese adults. Methods: Data from 600 older adults (mean age, 74.1±6.4 years; women, 62.0%) were analyzed. We evaluated dietary variety based on the Food Frequency Score (FFS; maximum 30 points) by assessing the 1-week consumption frequencies of ten foods. An FFS of ≤16 indicated low dietary diversity. We assessed MCI using the National Center for Geriatrics and Gerontology Functional Assessment Tool. Physical activity levels was determined based on participant responses to two questions: “Do you engage in moderate levels of physical exercise or sports aimed at health?” and “Do you engage in low levels of physical exercise aimed at health?” Participants who responded “No” to both questions were classified as having low physical activity levels. We classified the participants into robust, low-dietary diversity, low-physical activity, and coexistence groups. Results: The overall prevalence of MCI was 20.7%, with rates in the robust, low dietary diversity, low physical activity, and coexistence groups of 17.7%, 24.7%, 25.0%, and 41.9%, respectively. Multiple logistic regression analysis revealed that low dietary diversity and physical activity were associated with MCI in older adults (odds ratio=2.80, 95% confidence interval 1.22–6.28). Conclusion The results of the present study demonstrated the association of the co-occurrence of low dietary diversity and low physical activity with MCI. Older adults with both risk factors may require early detection, as well as physical activity and dietary interventions.

Background: This study aimed to investigate the potential association between the combination of low physical activity and low dietary diversity with mild cognitive impairment (MCI) in older Japanese adults. Methods: Data from 600 older adults (mean age, 74.1±6.4 years; women, 62.0%) were analyzed. We evaluated dietary variety based on the Food Frequency Score (FFS; maximum 30 points) by assessing the 1-week consumption frequencies of ten foods. An FFS of ≤16 indicated low dietary diversity. We assessed MCI using the National Center for Geriatrics and Gerontology Functional Assessment Tool. Physical activity levels was determined based on participant responses to two questions: “Do you engage in moderate levels of physical exercise or sports aimed at health?” and “Do you engage in low levels of physical exercise aimed at health?” Participants who responded “No” to both questions were classified as having low physical activity levels. We classified the participants into robust, low-dietary diversity, low-physical activity, and coexistence groups. Results: The overall prevalence of MCI was 20.7%, with rates in the robust, low dietary diversity, low physical activity, and coexistence groups of 17.7%, 24.7%, 25.0%, and 41.9%, respectively. Multiple logistic regression analysis revealed that low dietary diversity and physical activity were associated with MCI in older adults (odds ratio=2.80, 95% confidence interval 1.22–6.28). Conclusion The results of the present study demonstrated the association of the co-occurrence of low dietary diversity and low physical activity with MCI. Older adults with both risk factors may require early detection, as well as physical activity and dietary interventions.

Background: This study aimed to investigate the potential association between the combination of low physical activity and low dietary diversity with mild cognitive impairment (MCI) in older Japanese adults. Methods: Data from 600 older adults (mean age, 74.1±6.4 years; women, 62.0%) were analyzed. We evaluated dietary variety based on the Food Frequency Score (FFS; maximum 30 points) by assessing the 1-week consumption frequencies of ten foods. An FFS of ≤16 indicated low dietary diversity. We assessed MCI using the National Center for Geriatrics and Gerontology Functional Assessment Tool. Physical activity levels was determined based on participant responses to two questions: “Do you engage in moderate levels of physical exercise or sports aimed at health?” and “Do you engage in low levels of physical exercise aimed at health?” Participants who responded “No” to both questions were classified as having low physical activity levels. We classified the participants into robust, low-dietary diversity, low-physical activity, and coexistence groups. Results: The overall prevalence of MCI was 20.7%, with rates in the robust, low dietary diversity, low physical activity, and coexistence groups of 17.7%, 24.7%, 25.0%, and 41.9%, respectively. Multiple logistic regression analysis revealed that low dietary diversity and physical activity were associated with MCI in older adults (odds ratio=2.80, 95% confidence interval 1.22–6.28). Conclusion The results of the present study demonstrated the association of the co-occurrence of low dietary diversity and low physical activity with MCI. Older adults with both risk factors may require early detection, as well as physical activity and dietary interventions.

Background: Dementia is a critical late-life health issue that occurs among members of aging societies. This study examined the relationships between eating out, dietary diversity, and mild cognitive impairment (MCI) among community-dwelling older adults. Methods: We analyzed data from 597 older adults (median age 73.0 years, interquartile range 69.0–78.0 years; 62.6% females). We applied the food frequency score to evaluate diet variety and the weekly consumption frequencies of ten food items were determined. The National Center for Geriatrics and Gerontology Functional Assessment Tool (NCGG-FAT) was used to evaluate MCI. Finally, we asked the participants how often they ate out each month; those who replied "none" were categorized into the "non-eating out" group. Results: The overall prevalence of MCI was 122 (20.4%), with a higher prevalence in the low dietary diversity group than in the high dietary diversity group (28.6% vs. 18.6%). After adjusting for covariates, the participants who self-described as not eating out were independently associated with low dietary diversity (odds ratio [OR]=1.97, 95% confidence interval [CI] 1.20–3.20), while low dietary diversity was associated with MCI (OR=1.72; 95% CI 1.02–2.87). Structural equation models revealed that not eating out had no direct effect on MCI but was associated with MCI via low dietary diversity (root mean square error of approximation=0.030, goodness-of-fit index=0.999, and adjusted goodness-of-fit index=0.984). Conclusions Although non-eating out may not have a direct effect on MCI, an indirect relationship may exist between eating-out habits and MCI via dietary diversity status.