Search

Background Researchers have emphasized the importance of examining how different factors affect men’s and women’s functional status over time. To date, the literature is unclear about whether sex affects the rate of change in disability in middle to older age. Researchers have further emphasized the importance of examining how different factors affect men’s and women’s functional status over time. We examined (a) sex differences in disability trends and (b) the determinants of the rate of change in disability for men and women 50 years and older. Methods This study utilized the Taiwan Longitudinal Study on Aging Survey, a nationally representative database (four waves of survey data 1996–2007, N = 3429). We modeled and compared the differences in disability trends and the influences of determinants on trends among men and women using multiple-indicator and multiple-group latent growth curves modeling (LGCM). Equality constraints were imposed on 10 determinants across groups. Results Once disability began, women progressed toward greater disability 18% faster than men. Greater age added about 1.2 times the burden to the rate of change in disability for women than men (p p p pmen and women pmen pwomen Conclusions Age may widen the sex gap in the rate of change in disability. However, both sexes benefit from participating in leisure-time activities. Promoting health literacy improves health outcomes and physical function among women.

Additional file 1: Supplementary Table 1. Detailed Descriptions of the Measures (N = 3249). Supplementary Table 2. Descriptive Results and Factor Loadings of Nonlinear Unconditional LGCM for Disability Trends in Four Waves of Survey Data (N = 3429).

Additional file 2: Supplementary Figure 1. Disability Trends of Men and Women Over 11 years of study period.

Supplemental material, sj-pdf-1-jag-10.1177_07334648211032419 for Continuous Use of Home Care Services and Functional Performance: A Population-Based Approach by Tzu-Ying Chiu, Hsiao-Wei Yu and Ya-Mei Chen in Journal of Applied Gerontology

Supplemental material, sj-pdf-1-jag-10.1177_07334648211032419 for Continuous Use of Home Care Services and Functional Performance: A Population-Based Approach by Tzu-Ying Chiu, Hsiao-Wei Yu and Ya-Mei Chen in Journal of Applied Gerontology

Additional file 1. Appendix. Complete list of categories and competencies with the final Likert score on the three-round Delphi.

A growing body of evidence documents pervasive social and demographic factors relating to disparities in long-term care (LTC). In 2007, Taiwan implemented its Ten-year Long-Term Care Plan version 1.0 (TLTCP 1.0) that aimed to develop a home-and community-based (HCBS) LTC system. In 2016, Taiwan began to implement TLTCP 2.0. To continue providing effective LTC, this study aimed to assess the disparities in access to LTC services using Taiwan’s LTC claim database from 2010 to 2013. A total of 87,438 older adults who had applied for LTC services from the TLTCP 1.0 were included. The study assessed LTC disparities related to five sociodemographic factors, including age, gender, living status, urbanization, and income status. Sixteen types of LTC services, including HCBS, home-based professional care, meal services, transportation, and institutional services were assessed. After controlling for the level of disability, we found that those who were older-old (age 80> over), male, and low-income were less likely to use HCBS, but more likely to use institutions services (p < 0.001). We also found that those who lived in the city were more likely to use HCBS and transportation services (p < 0.001). Yet, older adults living alone were more likely to use home care and meal services but not other types of LTC services (p < 0.001). In conclusion, the social disparities in access to LTC services in Taiwan remains, suggesting LTC 2.0 should continue monitoring and placing the LTC equity issue on the top priority.

Background: Google Trends has demonstrated the capability to both monitor and predict epidemic outbreaks. The connection between Internet searches for dementia information and dementia incidence and dementia-related outpatient visits remains unknown. Objective: This study aimed to determine whether Google Trends could provide insight into trends in dementia incidence and related outpatient visits in Taiwan. We investigated and validated the local search terms that would be the best predictors of new dementia cases and outpatient visits. We further evaluated the nowcasting (ie, forecasting the present) and forecasting effects of Google Trends search trends for new dementia cases and outpatient visits. The long-term goal is to develop a surveillance system to help early detection and interventions for dementia in Taiwan. Methods: This study collected (1) dementia data from Taiwan’s National Health Insurance Research Database and (2) local Internet search data from Google Trends, both from January 2009 to December 2011. We investigated and validated search terms that would be the best predictors of new dementia cases and outpatient visits. We then evaluated both the nowcasting and the forecasting effects of Google Trends search trends through cross-correlation analysis of the dementia incidence and outpatient visit data with the Google Trends data. Results: The search term “dementia + Alzheimer’s disease” demonstrated a 3-month lead effect for new dementia cases and a 6-month lead effect for outpatient visits ( r =.503, P =.002; r =.431, P =.009, respectively). When gender was included in the analysis, the search term “dementia” showed 6-month predictive power for new female dementia cases ( r =.520, P =.001), but only a nowcasting effect for male cases ( r =.430, P =.009). The search term “neurology” demonstrated a 3-month leading effect for new dementia cases ( r =.433, P =.008), for new male dementia cases ( r =.434, P =.008), and for outpatient visits ( r =.613, P