Urban-Rural Disparities in the Association Between Home- and Community-Based Service Utilization and Levels of Disability Among Chinese Older Adults With Disabilities.

Home- and community-based services (HCBS) are optimal ways to deal with disability problems among older adults. This study aims to analyze urban-rural disparities in the relationship between HCBS utilization and levels of disability among Chinese older adults with disabilities, so as to meet the long-term care needs of them. In applying the Andersen Behavioral Model, bivariate analysis and multivariate regression models were employed using data from 843 older adults with disabilities from the 2018 China Longitudinal Aging Social Survey (CLASS). After adjusting covariates, disability levels among Chinese older adults with disabilities were significantly correlated with HCBS utilization in urban areas but not in rural areas. The urban-rural disparities may be due to the low utilization of HCBS in rural areas (only 11.2%) among older adults with disabilities compared with their urban counterparts (22.7%).

Association between home and community-based services utilization and self-rated health among Chinese older adults with chronic diseases: evidence from the 2018 China Health and Retirement Longitudinal Study.

BACKGROUND: As global aging intensifies, older adults with chronic diseases are of increasing concern. Home and community-based services (HCBSs) have been proven to promote self-rated health (SRH) in older adults, but no research explored the associations between the use of overall HCBSs, three different types of HCBSs (health care, daily care, and social support services) and SRH among older adults with chronic diseases. Consequently, this study applies a national publicly available database to examine these associations among older adults with chronic diseases. METHODS: 8,623 older adults with chronic diseases (≥ 60 years old) were included in this study. SRH was evaluated applying a concise question with a 1 - 5 scale. HCBSs utilization was assessed through the question, "What kind of HCBSs were used in the community?". Univariate general linear regression models aimed to compare the mean values of SRH in terms of HCBSs utilization in each group. This study is a cross-sectional study design and the relationship between HCBSs utilization and SRH was assessed by multilevel linear regression. RESULTS: The mean score for SRH among the respondents was 3.19, of whom 20.55% used one or more HCBSs, 19.47% utilized health care services, 2.44% utilized social support services, and only 0.55% utilized daily care services. The use of HCBSs was found to be linked to SRH among older adults with chronic diseases (ß = 0.085, SE = 0.025, p < 0.001). SRH among older adults with chronic diseases was strongly linked to the use of health care and social support services (ß = 0.068, SE = 0.025, p < 0.001; ß = 0.239, SE = 0.063, p < 0.001, respectively). However, there was no significant association between the use of daily care services and SRH among older adults with chronic diseases. CONCLUSION: This study revealed that HCBSs utilization was positively and significantly linked to SRH in Chinese older adults with chronic diseases. Furthermore, this study supposes the low utilization of social support and daily care services may be due to a mismatch between supply and demand. The government should offer the targeted HCBSs for older adults with chronic diseases according to their unique features to enhance their health status.

Predicting mild cognitive impairment among Chinese older adults: a longitudinal study based on long short-term memory networks and machine learning.

Background: Mild cognitive impairment (MCI) is a transitory yet reversible stage of dementia. Systematic, scientific and population-wide early screening system for MCI is lacking. This study aimed to construct prediction models using longitudinal data to identify potential MCI patients and explore its critical features among Chinese older adults. Methods: A total of 2,128 participants were selected from wave 5-8 of Chinese Longitudinal Healthy Longevity Study. Cognitive function was measured using the Chinese version of Mini-Mental State Examination. Long- short-term memory (LSTM) and three machine learning techniques, including 8 sociodemographic features and 12 health behavior and health status features, were used to predict individual risk of MCI in the next year. Performances of prediction models were evaluated through receiver operating curve and decision curve analysis. The importance of predictors in prediction models were explored using Shapley Additive explanation (SHAP) model. Results: The area under the curve values of three models were around 0.90 and decision curve analysis indicated that the net benefit of XGboost and Random Forest were approximate when threshold is lower than 0.8. SHAP models showed that age, education, respiratory disease, gastrointestinal ulcer and self-rated health are the five most important predictors of MCI. Conclusion: This screening method of MCI, combining LSTM and machine learning, successfully predicted the risk of MCI using longitudinal datasets, and enables health care providers to implement early intervention to delay the process from MCI to dementia, reducing the incidence and treatment cost of dementia ultimately.

Association between home and community-based services and depressive symptoms in Chinese older adults: a multilevel analysis.

BACKGROUND: As the phenomenon of ageing continues to intensify, home and community-based services (HCBSs) have been increasingly important in China. However, the association between HCBSs utilization and depressive symptoms in older adults in China is unclear. Consequently, this study aimed to examine the association between HCBSs utilization and depressive symptoms in Chinese older adults. METHODS: This study included 7,787 older adults (≥ 60 years old) who were recruited within the framework of the 2018 China Health and Retirement Longitudinal Study (CHARLS). Depressive symptoms were assessed using the 10-item Center for Epidemiological Studies Depression Scale (CES-D-10). HCBSs utilization was assessed via the question, "What kind of HCBSs were being utilized in their community?". Data were analyzed using binary logistic regression models and generalized hierarchical linear models (GHLM). RESULTS: Of the 7,787 participants, 20.0% (n = 1,556) reported that they utilized HCBSs, and 36.7% (n = 2,859) were evaluated that they had depressive symptoms. After adjusting for individual- and province-level covariates, the HCBSs utilization was found to be associated with depressive symptoms (OR = 1.180, 95% CI: 1.035-1.346, p < 0.05). Additionally, the depressive symptoms were significantly associated with gender, residence, educational level, marital status, number of chronic diseases, self-rated health (SRH), smoking, and provincial Gross Domestic Product (GDP) per capita. CONCLUSIONS: This study found HCBSs utilization might be a protective factor against depressive symptoms in Chinese older adults. It is of utmost significance for the government to provide targeted HCBSs at the community level to address the unmet care needs of older adults, which can reduce the occurrence of negative emotions, consequently contributing to less severe depressive symptoms.

The relationship between home and community-based healthcare services utilization and depressive symptoms in older adults in rural China: a moderated mediation model.

BACKGROUND: Studies have shown a close association between home and community-based healthcare services (HCBHS) utilization and depressive symptoms in older adults. However, no studies have explored the underlying mechanism of this relationship in rural China. This study was designed to evaluate the roles of instrumental activities of daily living (IADL) and marital status in the association between HCBHS utilization and depressive symptoms in Chinese rural older adults. METHODS: Data were obtained from the 2018 China Health and Retirement Longitudinal Study, and 5,981 rural respondents (≥ 60 years old) were included. Depression scores were calculated using the ten-item Center for Epidemiological Studies Depression Scale. Moderated mediation analysis was carried out applying Hayes' PROCESS macro (Model 7). RESULTS: HCBHS utilization had a direct and negative effect on depressive symptoms. Furthermore, marital status moderated the association between HCBHS utilization and IADL, which belonged to the indirect influence of the first half on the association between HCBHS utilization and depressive symptoms. HCBHS utilization was associated with IADL in single but not in married respondents. CONCLUSION: The results demonstrated that marital status moderated the indirect relationship between HCBHS utilization and depressive symptoms, with HCBHS utilization being negatively associated with IADL among single but not married respondents. The government should focus on rural older adults, especially those who are single and have poor IADL function, and improve the provision of HCBHS to alleviate depressive symptoms.

Demand prediction of medical services in home and community-based services for older adults in China using machine learning.

Background: Home and community-based services are considered an appropriate and crucial caring method for older adults in China. However, the research examining demand for medical services in HCBS through machine learning techniques and national representative data has not yet been carried out. This study aimed to address the absence of a complete and unified demand assessment system for home and community-based services. Methods: This was a cross-sectional study conducted on 15,312 older adults based on the Chinese Longitudinal Healthy Longevity Survey 2018. Models predicting demand were constructed using five machine-learning methods: Logistic regression, Logistic regression with LASSO regularization, Support Vector Machine, Random Forest, and Extreme Gradient Boosting (XGboost), and based on Andersen's behavioral model of health services use. Methods utilized 60% of older adults to develop the model, 20% of the samples to examine the performance of models, and the remaining 20% of cases to evaluate the robustness of the models. To investigate demand for medical services in HCBS, individual characteristics such as predisposing, enabling, need, and behavior factors constituted four combinations to determine the best model. Results: Random Forest and XGboost models produced the best results, in which both models were over 80% at specificity and produced robust results in the validation set. Andersen's behavioral model allowed for combining odds ratio and estimating the contribution of each variable of Random Forest and XGboost models. The three most critical features that affected older adults required medical services in HCBS were self-rated health, exercise, and education. Conclusion: Andersen's behavioral model combined with machine learning techniques successfully constructed a model with reasonable predictors to predict older adults who may have a higher demand for medical services in HCBS. Furthermore, the model captured their critical characteristics. This method predicting demands could be valuable for the community and managers in arranging limited primary medical resources to promote healthy aging.

Does health literacy promote COVID-19 awareness? Evidence from Zhejiang, China.

Background: Health literacy (HL) is considered a crucial determinant of disease prevention and control. However, the role of HL in the Coronavirus Disease 2019 (COVID-19) pandemic has not been studied using provincial representative data among Chinese residents. This study aimed to assess the association between HL and COVID-19 awareness among Zhejiang residents based on the 2020 China Health Literacy Survey (CHLS). Methods: The study was conducted among 5,596 residents aged 15-69 in Zhejiang using multistage, stratified, and probability proportional to size sampling. COVID-19 awareness and HL were assessed using the "Chinese Citizen Health Literacy Questionnaire (2020)" in Zhejiang. The covariates were divided into predisposing factors, enabling factors, and need factors according to Anderson's model. Data were analyzed by the chi-square test and logistic regression. Results: The study showed that HL and COVID-19 awareness levels of residents were 24.84% and 8.06%, respectively, in Zhejiang in 2020. After adjusting for covariates, residents with adequate HL were more likely to have better COVID-19 awareness (odds ratio [OR] = 5.22, 95% CI = 4.13-6.59, p < 0.001). Three dimensions of HL (knowledge and attitudes, behavior and lifestyle, and health-related skills) were associated with COVID-19 awareness. Additionally, COVID-19 awareness was associated with age, occupation, family size, annual household income, and chronic conditions. Conclusion: COVID-19 awareness is significantly associated with HL, suggesting that promoting HL is an important component of health education, disease prevention, and health promotion in response to the COVID-19 pandemic and even possible public health emergencies in the future.

Can a multitiered copayment system affect people's healthcare-seeking behavior? A case study of Wenzhou, China.

BACKGROUND: Facilitating the primary health care (PHC) system and maintaining people's reasonable healthcare-seeking behavior are key to establishing a sustainable healthcare system. China has employed a multitiered copayment system/medical insurance differentiated payment policies to incentivize the public to utilize PHC services through its hierarchical medical care system; however, most people still prefer visiting tertiary care hospitals. We question whether the quality gap in healthcare services reduces the effect of the multitiered copayment system, which is considered an important factor in the lack of reform in the Chinese healthcare system. Thus, we explore the effect and influencing factors of the multitiered copayment system that drives primary healthcare-seeking behavior under the current situation with a large quality gap. We also consider the hypothetical situation of a reduced gap in the future. METHODS: This study used the hypothetical quality improvement scenario to elicit people's hypothetical behaviors, and a multistage stratified cluster random sampling method. This preliminary study was conducted in 2016 using 1829 individuals from four regions of Wenzhou in Zhejiang Province: Ouhai, Ruian, Yongjia, and Taishun. A descriptive statistical analysis, chi-square analysis, Fisher's exact test, and multinomial logistic regression model were performed to introduce the effect of the multitiered copayment system, and to explore the factors affecting the selection of PHC institutions at pre- and post-change phases. RESULT: The results show that compared with the large quality gap phase, the number of respondents who believed the multitiered copayment system had an effect on their selection of PHC institutions after the equalization of healthcare services quality increased threefold (from 14.0% to 50.8%). Moreover, the main determinants in people's selection of PHC institutions changed from age and needs variables (self-rated health status) to age, needs variables (self-rated health status) and enabling variables (distance to a medical care facility). CONCLUSION: The results indicate limited initial effects of the multitiered copayment system. However, they become more pronounced after the equalization of healthcare services quality. This study confirms that changes in the quality gap in healthcare services influence the effect of the multitiered copayment system. Hence, reducing this gap can help achieve the intended outcome of the tiered healthcare insurance schedule.

Are there gender differences in the trajectories of self-rated health among chinese older adults? an analysis of the Chinese Longitudinal Healthy Longevity Survey (CLHLS).

BACKGROUND: Self-rated health (SRH) is a good predictor of morbidity and mortality. Extensive research has shown that females generally report poorer SRH than males but still tend to live longer. Previous studies used cross-sectional or pooled data for their analyses while ignoring the dynamic changes in males' and females' SRH statuses over time. Furthermore, longitudinal studies, especially those that focus on older adults, typically suffer from the incompleteness of data. As such, the effect of dropout data on the trajectories of SRH is still unknown. Our objective is to examine whether there are any gender differences in the trajectories of SRH statuses in Chinese older adults. METHODS: The trajectories of SRH were estimated using the pattern-mixture model (PMM), a special latent growth model, under non-ignorable dropout data assumption. We analyzed the Chinese Longitudinal Healthy Longevity Survey (CLHLS) data of 15,613 older adults aged 65 years and above, collected from 2005 to 2014. RESULTS: The results demonstrated the effect of non-ignorable dropout data assumptions in this study. The previous SRH score was negatively associated with the likelihood of dropping out of the study at the next follow-up survey. Our results showed that both males and females in China perceive their SRH as decreasing over time. A significant gender difference was found in the average SRH score (female SRH was lower than male SRH) in this study. Nonetheless, based on the results obtained using the PMM, there are no gender differences in the trajectories of SRH at baseline as well as in the rate of decline among the total sample. The results also show that males and females respond to SRH predictors similarly, except that current drinking has a more pronounced positive effect on males and healthcare accessibility has a more pronounced positive effect on females. CONCLUSIONS: Our results suggest that missing data have an impact on the trajectory of SRH among Chinese older adults. Under the non-ignorable dropout data assumptions, no gender differences were found in trajectories of SRH among Chinese older adults. Males and females respond to SRH predictors similarly, except for current drinking habit and healthcare accessibility.