Future life expectancy with disability among elderly Chinese individuals: a forecast based on trends in stroke and dementia

Effectiveness of targeted financial aid on disability welfare for the ageing population in China: A quasi-experiment study

Background

Addressing the problem of disabilities and disability deterioration is a key task for healthy ageing. Financial aid has been an effective measure for vulnerable groups, especially ageing people with disabilities. However, the effects of targeted financial aid on preventing disability deterioration remain unknown. The Chinese government launched a targeted financial aid programme aimed at people with disabilities. In this study, we investigated the causal effects of such targeted financial aid on disability deterioration prevention for elderly people with disabilities in China.

Methods

The data set used in this study included 36 640 elderly individuals with disabilities in China between 2016-19. We constructed a quasi-experiment approach and used a difference-in-differences (DID) method to examine the counterfactual differences between the treatment group in four cities that implemented such targeted financial aid in 2018 and the control group in three cities that did not adopt the policy over the study period. We employed propensity score matching (PSM) jointly with DID to mitigate selective bias. For sensitivity analysis, we conducted supplementary analyses on alternative samples, focusing on each of the treated cities respectively. Besides the main outcome, we also used fixed effect models to test the impact of such financial aid on rehabilitation access.

Results

The targeted financial aid significantly reduced the possibility of disability deterioration for elderly people with severe disabilities (0.26%; P < 0.001). Using PSM-DID models, the impact remained significant (0.33%; P < 0.001). Moreover, financial aid was significantly related to their access to rehabilitation services (12.71%; P < 0.001). Further analysis showed the heterogenous effects of targeted financial aid across individual demographic and socioeconomic factors, as well as communities with and without rehabilitation facilities.

Conclusions

Targeted financial aid had a positive impact on preventing disability deterioration among elderly individuals aged ≥65 years with severe disabilities. Moreover, rehabilitation care had a potential mediating role in the relationship between targeted financial aid and disability deterioration prevention. This study highlights the effectiveness of targeted financial aid in preventing disability deterioration and improving rehabilitation care for people with disabilities.

Projection for dementia burden in China to 2050: a macro-simulation study by scenarios of dementia incidence trends

Background

It is unclear how temporal trends in dementia incidence, alongside fast-changing demography, will influence China's future dementia burden. We developed a Markov model that combines population trends in dementia, mortality, and dementia-related comorbidities, to forecast and decompose the burden of dementia in China to 2050.

Methods

Population-based Chinese ageing cohorts provided input data for a 10-health-state Markov macrosimulation model, IMPACT-China Ageing Model (CAM), to predict sex- and age-specific dementia prevalence among people aged 50+ by year to 2050. We assumed three potential future scenarios representing the range of likely dementia incidence trends: upward (+2.9%), flat (0%) or downward (-1.0%). Sensitivity analyses were conducted to examine uncertainty associated with trends in mortality rates and CVD incidence. The projected dementia burden was decomposed into population growth, population ageing, and changing dementia prevalence corresponding to the three incidence trend scenarios.

Findings

Under the upward trend scenario, the estimated number of people living with dementia is projected to rise to 66.3 million (95% uncertainty interval (UI) 64.7-68.0 million), accounting for 10.4% of the Chinese population aged 50+ by 2050. This large burden will be lower, 43.9 (95% UI 42.9-45.0) million and 37.5 (95% UI 36.5-38.4) million, if dementia incidence remains constant or decreases. Robustness of the projection is confirmed by sensitivity analyses. Decomposition of the change in projected dementia cases indicates dominate effects of increasing dementia prevalence and population ageing, and a relatively minor contribution from negative population growth.

Interpretation

Our findings highlight an impending surge in dementia cases in China in the forthcoming decades if the upward trend in dementia incidence continues. Public health interventions geared towards dementia prevention could play a pivotal role in alleviating this burgeoning disease issue.

Funding

National Science Foundation of China/UK Economic and Social Research Council.

Interpretable prediction models for disability in older adults with hypertension: the Chinese Longitudinal Healthy Longevity and Happy Family Study

BACKGROUND

Older adults with hypertension have a high risk of disability, while an accurate risk prediction model is still lacking. This study aimed to construct interpretable disability prediction models for older Chinese with hypertension based on multiple time intervals.

METHODS

Data were collected from the Chinese Longitudinal Healthy Longevity and Happy Family Study for 2008-2018. A total of 1602, 1108, and 537 older adults were included for the periods of 2008-2012, 2008-2014, and 2008-2018, respectively. Disability was measured by basic activities of daily living. Least absolute shrinkage and selection operator (LASSO) was applied for feature selection. Five machine learning algorithms combined with LASSO set and full-variable set were used to predict 4-, 6-, and 10-year disability risk, respectively. Area under the receiver operating characteristic curve was used as the main metric for selection of the optimal model. SHapley Additive exPlanations (SHAP) was used to explore important predictors of the optimal model.

RESULTS

Random forest in full-variable set and XGBoost in LASSO set were the optimal models for 4-year prediction. Support vector machine was the optimal model for 6-year prediction on both sets. For 10-year prediction, deep neural network in full variable set and logistic regression in LASSO set were optimal models. Age ranked the most important predictor. Marital status, body mass index, score of Mini-Mental State Examination, and psychological well-being score were also important predictors.

CONCLUSIONS

Machine learning shows promise in screening out older adults at high risk of disability. Disability prevention strategies should specifically focus on older patients with unfortunate marriage, high BMI, and poor cognitive and psychological conditions.

Moderating role of depression in the association between leisure activity and cognitive function among the disabled older people

Background

This study delves into the complex interaction between leisure activities and cognitive function in older people with disabilities, with a particular emphasis on the moderating influence of depression. Despite the well-documented cognitive benefits of leisure activities among the older people, the intricate relationship between depression and the association between leisure activities and cognitive function in this specific demographic has been rarely reported.

Methods

Drawing on data from the 2017-2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS), this study meticulously examined a cohort of 713 participants aged 65-89 years. We constructed a moderation model to examine the impact of leisure activity on cognitive function in older people with disabilities, with depression levels as a moderating variable.

Results

We found a positive association between engagement in leisure activities and cognitive function, highlighting the potential cognitive advantages associated with leisure engagement among disabled older people. However, the present analysis also reveals a significant moderation effect of depression on this relationship, shedding light on the nuanced nature of this association. Specifically, elevated levels of depression emerge as a critical moderator, attenuating the otherwise favorable impact of leisure activities on cognitive function among older people contending with disabilities.

Conclusion

In conclusion, the findings provide a compelling rationale for tailored interventions that comprehensively target both leisure activity engagement and concurrent depression management, effectively fostering improvements in cognitive function among the cohort of disabled older people.

Machine learning-based prediction of disability risk in geriatric patients with hypertension for different time intervals

BACKGROUND

The risk of disability in older adults with hypertension is substantially high, and prediction of disability risk is crucial for subsequent management. This study aimed to construct prediction models of disability risk for geriatric patients with hypertension at different time intervals, as well as to assess the important predictors and influencing factors of disability.

METHODS

This study collected data from the Chinese Longitudinal Healthy Longevity and Happy Family Study. There were 1576, 1083 and 506 hypertension patients aged 65+ in 2008 who were free of disability at baseline and had completed outcome information in follow-up of 2008-2012, 2008-2014, 2008-2018. We built five machine learning (ML) models to predict the disability risk. The classic statistical logistic regression (classic-LR) and shapley additive explanations (SHAP) was further introduced to explore possible causal factors and interpret the optimal models' decisions.

RESULTS

Among the five ML models, logistic regression, extreme gradient boosting, and deep neural network were the optimal models for detecting 4-, 6-, and 10-year disability risk with their AUC-ROCs reached 0.759, 0.728, 0.694 respectively. The classic-LR revealed potential casual factors for disability and the results of SHAP demonstrated important features for risk prediction, reinforcing the trust of decision makers towards black-box models.

CONCLUSION

The optimal models hold promise for screening out hypertensive old adults at high risk of disability to implement further targeted intervention and the identified key factors may be of additional value in analyzing the causal mechanisms of disability, thereby providing basis to practical application.

Equity in walking access to community home care facility resources for elderly with different mobility: A case study of Lianhu District, Xi'an

As the aging of China's population continues to deepen, a number of elderly care facilities relying on community platforms to provide home care services have been established in urban communities, effectively alleviating the problem of difficult community elderly care, while a spatial mismatch between the facilities and the elderly population has also emerged. To solve this problem, this paper analyzes the equity in walking access to community home care facilities for elderly people with different mobility abilities in Lianhu District of Xi'an City, taking the resources of community home care facilities as the research object. Firstly, the coverage rate of the facilities was calculated based on the 15-minute walking range of the elderly with different mobility, and the accessibility of the facilities was measured using the Kernel Density-type two-step moving search method. Then, Gini coefficient, Lorenz curve and location entropy were used to analyze the spatial matching pattern of facilities and elderly population. The results show that there is a serious spatial mismatch between the resources of community home care facilities and the elderly population with mobility restriction. In addition, the available facility area per capita is low for more than 80% of the elderly with mobility restriction, and the road network density has a significant impact on the access of the elderly with mobility restriction to the community home care facility resources. These research results indicate that the spatial layout and configuration of community home care facilities are unfair to the elderly with poor mobility, and that these elderly care facility configurations do not favor the disadvantaged groups.

Prevalence of self-care disability among older adults in China

BACKGROUND

Self-care disability among older adults is a global public health issue. However, it lacks the up-to-date information based on nationally representative, more comprehesive data in China.

METHODS

Using China's 2020 population census data, this paper provides a macro-analysis of the prevalence and socio-demographic characteristics of self-care disability among older adults.

RESULTS

25.5 million older adults aged 60 and over participated in the health status survey, of which 48.2% were male, and 51.8% were female. We find that the prevalence of self-care disability among older adults aged 60 and above in China is 2.34%, and the older the population, the higher the prevalence. A higher prevalence was reported by female older adults, rural older adults, and older adults in western China. Single (never married) and widowed older adults are at higher risk of self-care disability. Compared to 2010, the prevalence of self-care disability among older adults decreased. However, the urban-rural difference still exists. Self-care disabled older adults rely mainly on family members for livelihood and mainly cohabitate with them. While pension is an essential source of livelihood for urban older adults with self-care disability, fewer rural self-care disabled older adults rely on pension.

CONCLUSION

The prevalence of self-care disability among older adults aged 60 and over in China is low and has decreased compared to 2010. Older adults with self-care disability are not a homogeneous group, and they have apparent socio-demographic disparities and regional differences. The Chinese government should continue to reduce inequalities between urban and rural areas, especially in pension and long-term care systems.

Changes and Trend Disparities in Life Expectancy and Health-Adjusted Life Expectancy Attributed to Disability and Mortality From 1990 to 2019 in China

Objective

This study aims to investigate sex, age, and cause-specific contributions to changes and trend disparities in life expectancy (LE) and health-adjusted life expectancy (HALE) attributed to disability and mortality from 1990 to 2019 in China, which provides insight into policy-making, health systems planning, and resource allocation.

Methods

Contributions of disability and mortality to changes and trend disparities in LE and HALE were estimated with standard abridged life table, Sullivan's method, and decomposition method, using retrospective demographic analysis based on mortality and years lived with disability (YLD) rates extracted from Global Burden of Disease Study 2019 (GBD 2019).

Results

From 1990 to 2019, LE and HALE increased by 10.49 and 8.71 years for both sexes, mainly due to noncommunicable diseases (NCDs) (5.83 years, 55.58% for LE and 6.28 years, 72.10% for HALE). However, HIV/AIDS and sexually transmitted infections had negative effects on changes in LE (−0.03 years, −0.29%) and HALE (−0.05 years, −0.57%). Lung cancer and ischemic heart disease caused the biggest reduction in LE (−0.14 years, −1.33%) and HALE (−0.42 years, −4.82%). Also, cardiovascular diseases (−0.08 years, −0.92%), neurological disorders (−0.08 years, −0.92%), diabetes and kidney diseases (−0.06 years, −0.69%), and transport injuries (−0.06 years, −0.69%) had main negative disability effects in HALE. Moreover, life expectancy lived with disability (LED) increased by 1.78 years, mainly attributed to respiratory infections and tuberculosis (1.04 years, 58.43%) and maternal and neonatal disorders (0.78 years, 43.82%).

Conclusion

The LE and HALE in China have grown rapidly over the past few decades, mainly attributed to NCDs. It is necessary to further reduce the negative mortality effect of HIV/AIDS, lung cancer, colon and rectum cancer, pancreatic cancer, and ischemic heart disease and the negative disability effect of stroke, diabetes mellitus, and road injuries. In addition, the signs of disparities in mortality and disability of different sexes and ages call for targeted and precise interventions for key groups such as males and the elderly. According to the decomposition results, we may better determine the key objects of health policies that take into account substantial cause-specific variations to facilitate the realization of “healthy China 2030” plan.