Examining the impact of functional disability and cognitive impairment on mental health of Chinese elderly

Interaction between activities of daily living and cognitive function on risk of depression

Objective

There is a lack of literature about the joint effects of activities of daily living (ADL) limitation and cognitive impairment on depression. This study aimed to estimate the association of ADL limitation and cognitive impairment with depression among Chinese older adults aged 65 and above and to test their interaction on both additive and multiplicative scales.

Methods

Data was drawn from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), including 11,025 eligible participants. Logistic regression models were fitted, and both multiplicative and additive interactions for ADL limitation and cognitive impairment were tested.

Results

A total of 3,019(27.4%) participants reported depressive symptoms. After controlling for potential confounding factors, ADL limitation and cognitive impairment were both positively associated with depression. The adjusted additive interaction of basic and instrumental activities of daily living limitation were 2.47 (95%CI:1.92-3.19) and 3.67 (95%CI:2.88-4.66), respectively, but the multiplicative interaction items were both insignificant.

Conclusion

ADL limitation and cognitive impairment were both risk factors for depression among Chinese older adults. Moreover, the significant interaction of ADL limitation and cognitive impairment was found in the additive model, suggesting that improving ADL may be helpful in reducing the risk of depression among older people with cognitive impairment.

Enhancing understanding of healthy aging based on time-varying dependencies among multidimensional health, life satisfaction, and health behaviors of older adults aged 60 years and over

BACKGROUND

Healthy aging is a process of not only achieving good health but also increasing the life satisfaction of older adults aged 60 years and over, in which health behaviors play an important role. There is a lack of research on the time-varying dependencies between health, life satisfaction, and health behaviors, impeding a deeper understanding of healthy aging.

PURPOSE

To develop an integrated framework for modeling the interrelationships among the components of healthy aging between multiple time slices.

METHODS

Based on the Chinese Longitudinal Healthy Living Survey (CLHLS) data in the three waves of 2011/2012, 2014, and 2017/2018, Bayesian network and dynamic Bayesian network are jointly employed to study the relationships among the components of healthy aging within one time slice, as well as to explore the time-varying dependencies among the components between time slices.

RESULTS

The results of structure learning reveal the direction of effects between different dimensions of health, with mental health and social health affecting physical health and self-rated health affecting both physical and mental health. In addition, health behaviors are found to affect mental health and social health, while self-rated health can influence life satisfaction. The parameters learned from the data show the magnitude and direction of concurrent effects, one-period lagged effects and two-period lagged effects between the factors, which find that the time-varying dependencies vary but are generally positive, long-term, and accumulative over time. In addition, the results of autoregressive effects show the positive predictive effects of health and life satisfaction.

CONCLUSIONS

It confirms the influence pathway from health behaviors to multidimensional health to life satisfaction, and the time-varying dependencies among the components of healthy aging, which facilitates a deeper understanding of healthy aging. Combining the results of autoregressive effects and descriptive statistics, it further indicates that healthy aging is a comprehensive result arising from interactions of multiple factors. Policymakers should guide older adults aged 60 years and over to adopt healthier behaviors and ensure the long-term sustainability and continuity of policies.

Urban-rural disparities in the prevalence and trends of depressive symptoms among Chinese elderly and their associated factors

BACKGROUND

This study aimed to examine urban-rural disparities in the prevalence and trends of depressive symptoms (DS) among Chinese elderly and associated factors.

METHODS

A total of 8025, 7808, and 4887 respondents aged 60 years and above were selected from the China Family Panel Studies (CFPS) in 2016, 2018, and 2020, respectively. DS was assessed using a short version of Center for Epidemiologic Studies Depression Scale (CES-D). Twenty-two associated factors from six categories were included in random forest (RF) models. All urban-rural comparisons were conducted based on good model performance.

RESULTS

The DS prevalence among all rural elderly was significantly higher than corresponding urban elderly. This disparity continued to widen among younger elderly, while it continued to narrow among older elderly. The top 10 common leading factors were sleep quality, self-rated health, life satisfaction, memory ability, child relationship, IADL disability, marital status, educational level, and gender. Urban-rural disparities in sleep quality, interpersonal trust, and child relationship continued to widen, while disparities in multimorbidity, hospitalization status, and frequency of family dinner continued to narrow.

LIMITATION

This study may exist recall bias and lacks causal explanation.

CONCLUSIONS

Significant and continuing disparities in the DS prevalence were observed between urban and rural elderly in China, showing opposite trends in younger and older elderly. The top 10 leading associated factors for DS were nearly consistent across urban and rural elderly, with sleep quality having strongest contribution. Urban-rural disparities in associated factors also showed different trends. This study provides a reference for mental health promotion among Chinese elderly.

Family function, anxiety and depression in adults with disabilities: a network analysis

Background

The prevalence of family dysfunction, anxiety and depression is high in people with disabilities due to long-term activity constraints and social difficulties. Recently, although studies have attempted to provide guidance for family therapy by focusing on the relationship between family function and negative emotions, the specific effects of improved family function during family therapy on alleviation of anxiety and depressive symptoms have been obscured. Thus, this study attempted to elucidate the impact of specific family functioning on specific symptoms of anxiety and depression through network analysis.

Methods

Family APGAR Index Questionnaire (APGAR), Generalized Anxiety Scale (GAD-7), and Patient Health Questionnaire Depression Scale (PHQ-9) were used to survey 897 adults with disabilities in Sichuan Province. Meanwhile, network analysis for studying the relationship between anxiety, depression and family functioning among the disabled via R software.

Results

The network analysis showed that (1) Nodes PHQ4 ("Energy"), APGAR3 ("Growth"), GAD1 ("Nervousness") and GAD4 ("Relaxing Trouble") were central nodes in the network model; (2) Bridge nodes linking family function, anxiety and depressive symptoms in the sample were PHQ9 ("Suicide ideation"), PHQ6 ("Worthlessness"), GAD1 ("Nervousness") and GAD5 ("Restlessness"); (3) The node APGAR5 ("Resolve") directly connects the bridge symptoms PHQ9 ("Suicide ideation") and PHQ8 ("Motor").

Conclusion

This study suggests that therapists could target the resolve of family members during family therapy to reduce suicidal ideation and enhance the level of activity of people with disabilities, thereby improving the network of anxiety and depression symptoms and alleviating negative emotions of people with disabilities.

A network analysis of anxiety and depression symptoms in Chinese disabled elderly

BACKGROUND

Mental health is an essential dimension of healthy aging. The number and severity of disabled elderly in China show an increasing tendency year by year. Due to their impaired ability of daily activities, reduced social participation and reduced self-care ability, they are more prone to depression and anxiety.

METHOD

We included 2131 individuals aged 65 and older from the Chinese Longitudinal Healthy Longevity Survey (CLHLS 2017-2018). We used the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10) and the Generalized Anxiety Disorder scale-7 (GAD-7) to assess depression and anxiety, respectively. The structure of depressive and anxiety symptoms was characterized using "Expected Influence" and "Bridge Expected Influence" as centrality indices in the symptom network. Network stability was tested using a case-dropping bootstrap procedure. Finally, a Network Comparison Test (NCT) was conducted to examine whether network characteristics differed by gender.

RESULTS

Network analysis revealed that nodes CESD3 (Felt sadness), GAD2 (Uncontrollable worry), and GAD4 (Trouble relaxing) were the primary symptoms of the anxiety-depression network. Anxiety and depression were united by the symptoms of CESD9 (Could not get going), GAD1 (Nervousness or anxiety), CESD10 (Sleep quality), and GAD4 (Trouble relaxing). Additionally, Gender did not significantly affect the network structure.

CONCLUSION

Central symptoms (e.g., felt sadness, uncontrollable worry and trouble relaxing) and key bridge symptoms (e.g., could not get going, nervousness and anxiety) in the depressive and anxiety symptoms network may be used as potential targets for intervention among disabled elderly who is at risk for or suffer from depressive and anxiety symptoms.