Background: Physical inactivity is a risk factor for locomotive syndromes and functional limitations in middle-aged and older adults. Therefore, strategies to promote physical activity should be considered. This study investigated whether users of physical activity monitors were more physically active and exhibited a lower risk of locomotive syndrome, compared with non-users. Methods: We analyzed data from 742 Japanese adults aged 60–79 years. The participants were surveyed for their use of physical activity monitors in their daily lives. We also assessed the prevalence of locomotive syndrome. Results: We observed significantly higher physical activity levels in users compared with non-users. Moreover, the use of a physical activity monitor was significantly associated with decreased odds of locomotive syndrome (adjusted odds ratio [aOR]=0.48). Significantly lower risk of locomotive syndrome were observed in individuals who had used a monitor for >2 years (aOR=0.42) or had set a personal step goal (aOR=0.32). Conclusion Physical activity monitoring may increase engagement in physical activity-associated behavior. Therefore, monitoring could serve as a useful tool to promote physical health in middle-aged and older adults.

Background: Physical inactivity is a risk factor for locomotive syndromes and functional limitations in middle-aged and older adults. Therefore, strategies to promote physical activity should be considered. This study investigated whether users of physical activity monitors were more physically active and exhibited a lower risk of locomotive syndrome, compared with non-users. Methods: We analyzed data from 742 Japanese adults aged 60–79 years. The participants were surveyed for their use of physical activity monitors in their daily lives. We also assessed the prevalence of locomotive syndrome. Results: We observed significantly higher physical activity levels in users compared with non-users. Moreover, the use of a physical activity monitor was significantly associated with decreased odds of locomotive syndrome (adjusted odds ratio [aOR]=0.48). Significantly lower risk of locomotive syndrome were observed in individuals who had used a monitor for >2 years (aOR=0.42) or had set a personal step goal (aOR=0.32). Conclusion Physical activity monitoring may increase engagement in physical activity-associated behavior. Therefore, monitoring could serve as a useful tool to promote physical health in middle-aged and older adults.

Background: Physical inactivity is a risk factor for locomotive syndromes and functional limitations in middle-aged and older adults. Therefore, strategies to promote physical activity should be considered. This study investigated whether users of physical activity monitors were more physically active and exhibited a lower risk of locomotive syndrome, compared with non-users. Methods: We analyzed data from 742 Japanese adults aged 60–79 years. The participants were surveyed for their use of physical activity monitors in their daily lives. We also assessed the prevalence of locomotive syndrome. Results: We observed significantly higher physical activity levels in users compared with non-users. Moreover, the use of a physical activity monitor was significantly associated with decreased odds of locomotive syndrome (adjusted odds ratio [aOR]=0.48). Significantly lower risk of locomotive syndrome were observed in individuals who had used a monitor for >2 years (aOR=0.42) or had set a personal step goal (aOR=0.32). Conclusion Physical activity monitoring may increase engagement in physical activity-associated behavior. Therefore, monitoring could serve as a useful tool to promote physical health in middle-aged and older adults.

Background: Physical inactivity is a risk factor for locomotive syndromes and functional limitations in middle-aged and older adults. Therefore, strategies to promote physical activity should be considered. This study investigated whether users of physical activity monitors were more physically active and exhibited a lower risk of locomotive syndrome, compared with non-users. Methods: We analyzed data from 742 Japanese adults aged 60–79 years. The participants were surveyed for their use of physical activity monitors in their daily lives. We also assessed the prevalence of locomotive syndrome. Results: We observed significantly higher physical activity levels in users compared with non-users. Moreover, the use of a physical activity monitor was significantly associated with decreased odds of locomotive syndrome (adjusted odds ratio [aOR]=0.48). Significantly lower risk of locomotive syndrome were observed in individuals who had used a monitor for >2 years (aOR=0.42) or had set a personal step goal (aOR=0.32). Conclusion Physical activity monitoring may increase engagement in physical activity-associated behavior. Therefore, monitoring could serve as a useful tool to promote physical health in middle-aged and older adults.

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.

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.

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.

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.