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.

Background/Purpose: Previous studies have suggested that environmental factors, such as weather, atmospheric temperature, humidity and seasonal change, may affect the disease activity of rheumatoid arthritis (RA). In the present study, we aimed to determine whether RA disease activity, including patient’s global assessment (PtGA), is influenced by seasonal variation, using a nationwide Japanese cohort database, NinJa (National Database of Rheumatic Diseases by iR-net in Japan). Methods: RA patients, who were registered in NinJa, are evaluated at any point during the indicated year. We analyzed data from RA patients (n=8,726), whose PtGA, pain visual analog scale (VAS) and physician’s global assessment (PhGA) data were available in NinJa 2012. In the present study, spring was defined as from March to May, summer as from June to November, Fall as from September to November and winter as from December to February. Age, sex, disease duration, number of tender joints, swollen joints, pain VAS, PtGA, PhGA, ESR, CRP, stage, class and mHAQ were also included as explanatory variables. Results: Univariable analysis using NinJa 2012 database revealed that PtGA, pain VAS and disease activity score (DAS)-28 were lowest during the fall months with statistical significance, which was reproducible in NinJa 2011 database analysis. On the other hand, multivariate analysis revealed that pain VAS, mHAQ and the number of swollen joints were the main determinants of PtGA, and seasonal variation was not identified as a statistically significant factor. Conclusion: We have clearly demonstrated that PtGA was lowest in fall. Seasonal changes can thus affect RA, although to a lesser degree than pain and activity of daily living, which should be taken into account when examining RA patients to better understand their symptoms.