Inter-Relationships Between Depressive Symptoms And Sleep Problems Among Older Adults With Depression: Findings of a National Survey in the USA.

The network structures of depressive and insomnia symptoms among cancer patients using propensity score matching: Findings from the Health and Retirement Study (HRS)

Background: Depressive and insomnia symptoms are common among older adults with chronic pain. We aimed to examine different chronic pain trajectories of older adults over an 8-year observation period and explore the network structures of depression and insomnia in each chronic pain group.Methods: The trajectories of pain in the USA-based Health and Retirement Study (HRS) data from 2010 to 2018 were examined using latent class growth analyses (LCGA) method. Depressive and insomnia symptoms were measured with the eight-item version of the Center for Epidemiological Studies Depression (CESD-8) Scale and the four-item Jenkins Sleep Scale (JSS-4), respectively. Network models were constructed using the Ising model. Central symptoms and bridge symptoms were identified via expectedInfluence (EI) and bridge EI, respectively.Results: A total of 11,132 older adults were included in the trajectory analysis, with three chronic pain trajectories identified, including “severe pain trajectory,” “moderate pain trajectory,” and “non or mild pain trajectory”. From these trajectories, “Lack of happiness” (CESD4), “Feeling depressed” (CESD1), and “Feeling sad” (CESD7) emerged as the most central symptoms, while “Feeling tired in the morning” (JSS4) was identified as the key bridge symptom. However, the findings may not be generalizable to other parts of the world outside the USA.Conclusion: Older adults with different chronic pain trajectories exhibited similar depression and insomnia network structure. Implementing timely interventions that target central and bridge symptoms might mitigate the co-occurrence of depression and insomnia in this population.

Depression and anxiety are global public health challenges among older adults. Square dancing, a popular activity for older Chinese adults, is believed to relieve these disturbances. This study compared the prevalence, severity, and network structures of depression and anxiety among older square dancers versus non-dancers (i.e., those who do not engage in square dancing). Propensity score matching (PSM) created square dancer and non-dancer groups using data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Depressive and anxiety symptoms were assessed with the 10-item Center for Epidemiological Studies Depression Scale (CESD-10) and the 7-item Generalized Anxiety Disorder Scale (GAD-7), respectively. Central symptoms and bridge symptoms were estimated in each group using expected influence (EI) and bridge EI, respectively. The study included 401 square dancers and a matched sample of 1163 non-dancers. The prevalence and severity of depression and anxiety were significantly lower among square dancers compared to non-dancers. In contrast, network structures of depressive and anxiety symptoms were similar between the two groups. "Uncontrollable worrying" and "Felt sadness" were the most central symptoms, and "Nervousness", "Bothered by things" and "Felt nervous/fearful" were key bridge symptoms across both groups. Participation in square dancing is associated with reduced overall prevalence and severity of depression and anxiety among older adults, but is not associated with a unique network structure of these syndromes compared to non-participation. Consequently, psychosocial interventions developed for depression and anxiety based on the network structure of non-dancers may also be applicable for square dancers who experience anxiety and depression.

Association between internet exclusion and depressive symptoms among older adults: panel data analysis of five longitudinal cohort studies

Background The complex relationships across depressive symptoms in older adults may differ across countries. We aimed to generate symptom networks of depressive symptoms in older adults and explore different patterns of depressive symptoms across countries from a mechanism perspective. Methods We used harmonized data on 126,025 individuals ≥65 yrs from the Health and Retirement Study (HRS) family data from US, Mexico, UK, China, Israel, European countries, and Korea. We constructed dynamic networks with eight depressive symptoms using cross-lagged panel network analysis. Results We identified two patterns in the networks of depressive symptoms: sadness-centered pattern and non-sadness-centered pattern. In the sadness-centered pattern, “felt sad” was the strongest predictor of other depressive symptoms in the United State (rs=4.38), Mexico (rs=4.96), and European and Israel (rs=4.61). Moreover, “felt depression” was found to have strong relationship with “felt sad” (r=0.586, 0.599, and 0.598, respectively). In the non-sadness-centered pattern, “bothered by little things” had the highest node strength in England (rs=8.16) and “could not get going” had the highest node strength in Korea (rs=10.18). Discussion Our study demonstrated two patterns in the networks of depressive symptoms in older adults. In the sadness-centered pattern, a combined intervention for analyzing the cause of sadness and alleviating it should be considered. Keywords: Global health; Depression; Older adults; Symptom network

Within the global population, depression and anxiety are common among older adults. Tai Chi is believed to have a positive impact on these disturbances. This study examined the network structures of depression and anxiety among older Tai Chi practitioners vs non-practitioners. Propensity score matching (PSM) was used to construct a non-practitioner group based on Chinese Longitudinal Healthy Longevity Survey (CLHLS) data. 346 Tai Chi practitioners and 1019 non-practitioners were included. The prevalence and severity rates of depression were significantly lower among Tai Chi practitioners compared to non-practitioners though there was no group difference for anxiety. Network analysis showed that, among Tai Chi practitioners, "Felt sadness", "Uncontrollable worrying" and "Trouble relaxing" were the most central symptoms. In contrast, among non-practitioners, the most central symptoms were "Felt sadness", "Uncontrollable worrying", and "Nervousness". Key bridge symptoms linking depressive and anxiety symptoms were "Worry too much", "Bothered by things" and "Uncontrollable worrying" in Tai Chi practitioners and "Nervousness", "Felt nervous/fearful" and "Sleep quality" in non-practitioners. This study underscored how practising Tai Chi is associated with reduced overall prevalence and severity of depression and different interactions of depressive and anxiety symptoms among older adults. Central and bridge symptoms differed between Tai Chi practitioners and non-practitioners.

Emergent neuropsychiatric symptoms and sleep disorders among older adults in nursing homes who have depressive symptoms and are at risk of dementia: A network analysis.

Background: Estimating the prevalence of depressive and anxiety symptoms among older adults with different health conditions can inform mental health services for this population during the corona virus disease-2019 (COVID-19) pandemic. Method: A search of 12 scientific databases identified 17 studies with 11,237 Chinese older adults who were infected by COVID-19, were generally healthy, or had chronic illnesses. Meta-analysis was used to estimate the overall prevalence of depressive and anxiety symptoms in these three groups. Assessment criteria, region, and time phase of the pandemic were tested as sources of heterogeneity. Results: With an average risk of bias score of 6.71 (range = 6–8), the majority of included studies employed appropriate statistical methods, used validated measurement tools, and had adequate response rates; however, they might have deficiencies in sample frame, sampling method, and sample size. Within the COVID-19, general, and chronic illness groups, the prevalence of depressive symptoms was 27%, 26%, and 61%, respectively, and the prevalence of anxiety symptoms was 14%, 23%, and 85%, respectively. Among generally healthy older adults, anxiety was more prevalent during the Phase 2 (March–April 2020) of the pandemic compared with other time phases. Conclusions: The results have implications for addressing the mental health problems of Chinese older adults, especially those with chronic illnesses, during the COVID-19 pandemic.

Network analysis of depression, anxiety, insomnia and quality of life among Macau residents during the COVID-19 pandemic

BackgroundAs a result of the coronavirus disease 2019 (COVID-19) outbreak, many countries have imposed movement restrictions and implemented lockdowns. However, evidence from a variety of nations showed that the COVID-19 outbreak and its associated quarantine measures triggered a wide range of psychological problems, such as anxiety, depression, and stress in the general population. As a result, the purpose of this study was to determine the prevalence and predictors of depression, anxiety, and stress symptoms among Tepi town residents during the pandemic lockdown.MethodologyA community-based cross-sectional survey was conducted among residents of Tepi town from September 15 through September 25, 2020, and residents who have lived in Tepi town for at least 6 months were included. We have employed the depression, anxiety, and stress scale 21 (DASS-21) to evaluate depression, anxiety, and stress. The Chi-squared test of association and logistic regression were used to identify factors associated with depression, anxiety, and stress among residents of Tepi town. For all statistical analysis, we used (IBM) SPSS version 25.ResultsAccording to the current study, the prevalence of depression, anxiety, and stress symptoms were 37.7%, 39.0%, and 44.2%, respectively, among residents of Tepi town. Estimated odds of having depression, anxiety, and stress were as follows: for being female 6.315, 4.591, and 3.155; smoking 1.787, 1.883, and 1.787; sleep problem 2.613, 2.254, and 1.721; chewing Khat 2.156, 2.053, and 2.110; quarantine for 14 days 2.251, 1.902, and 1.960; and frequent use of social media 3.126, 1.849, and 3.126 times more likely as compared to their corresponding reference group respectively. The odds of developing depression and anxiety respectively were as follows: for alcohol consumption 2.438 and 1.797 times higher than their corresponding reference group respectively. Those exposed to COVID-19 were 3.870 times more likely to develop depression symptoms. Estimated odds of having anxiety and stress symptoms for fear of COVID-19 were 1.776 and 1.835; social interactions altered were 3.197 and 2.069, moderate levels of hope were 2.687 and 2.849 respectively. The odds ratio for those taking traditional preventive medicine, and having family members infected with COVID-19 were 2.475 and 1.837 times more likely to experience anxiety symptoms respectively.ConclusionIn this study, the prevalence of depression, anxiety, and stress symptoms was found to be high among residences in Tepi town. Being female, chewing Khat, smoking, being quarantined for 14 days, frequently using social media, and having sleeping problems were all found to be significantly associated with an increased risk of developing depression, anxiety, and stress symptoms, whereas alcohol consumption and family members infected by COVID-19 were considerably linked to depression and anxiety symptoms. Fear of COVID-19, influence on social interaction and having a moderate level of hope were substantially related to stress and anxiety symptoms, while taking preventive medicine was found to be a significant factor in anxiety symptoms among Tepi town residences. Interventions should be made to improve the mental health of Tepi residents.

Prevalence of depressive symptoms and psychological distress in Japanese university-enrolled students before and during the coronavirus disease 2019 pandemic.

BACKGROUND: Older adults with multiple chronic conditions represent a vulnerable group with health issues intricately intertwined, making them more susceptible to mental health issues such as depression and anxiety. To identify central and bridge symptoms to implement effective interventions, this study constructed a network model of depression and anxiety symptoms among older adults with MCCs, exploring the correlations among specific symptoms. METHODS: This study used the data from the 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS) to construct a network model for depression and anxiety symptoms among older people with MCCs. Depression and anxiety symptoms were assessed by using the Center for Epidemiologic Studies Depression Scale-10 (CESD-10) and the Generalized Anxiety Disorder Scale-7 (GAD-7). Network analysis was used to identify the central symptoms and bridge symptoms between the network of depression and anxiety symptoms. The network stability was examined by a case-dropping bootstrap procedure. RESULTS: Network analysis revealed that nodes GAD2 (Uncontrollable worry) and CESD3(Felt sadness) were the most primary symptoms and GAD1(Nervousness), CESD1 (Bother by things), CESD10 (Sleep quality), and GAD3 (Excessive worry) were bridge symptoms of the anxiety-depression network. CONCLUSION: Central symptoms and bridge symptoms played a critical role in the anxiety-depression symptoms network. Future research should explore intervention strategies for these symptoms to improve the mental health of older adults with MCCs.

BACKGROUNDDepression is a significant risk factor for diabetes, particularly type 2 diabetes. However, depressive symptoms differ from clinical depression. Previous research has not fully considered the relationship between the trajectory of depressive symptoms and the risk of developing diabetes over time.AIMTo investigate the association between depressive symptoms, their trajectories, and the risk of developing diabetes in two prospective cohort studies.METHODSIn the first phase we analyzed the association between depressive symptoms and the risk of developing diabetes separately using the Health and Retirement Study (HRS). Depressive symptom trajectories were assessed by examining changes in depressive symptoms at baseline and again 8 years later. We then identified specific depressive symptom trajectories that increased the risk of diabetes in the second phase. Finally, we confirmed the association between depressive symptoms and their trajectories with diabetes risk using the English Longitudinal Study of Ageing (ELSA) as a validation study. Depressive symptom trajectories were categorized into five states based on changes in the modified 8-item Center for Epidemiological Studies-Depression scores: Persistently high; increasing; fluctuating; decreasing; and persistently low. Diabetes mellitus was defined as self-reported, physician-diagnosed diabetes. Cox proportional hazards models were used to assess hazard ratios (HR) and 95% confidence intervals (CI), adjusting for potential confounders.RESULTSIn the first phase a total of 27658 participants were included (HRS: 18633, ELSA: 9025), among whom 6582 had depressive symptoms (HRS: 4547, ELSA: 2035), 6407 had somatic depressive symptoms (HRS: 4414, ELSA: 1993), and 26415 had cognitive-affective depressive symptoms (HRS: 17755, ELSA: 8660). We found that overall depressive symptoms (HRS: HR = 1.14, 95%CI: 1.07-1.22; ELSA: HR = 1.18, 95%CI: 1.03-1.34) and somatic depressive symptoms (HRS: HR = 1.14, 95%CI: 1.07-1.22; ELSA: HR = 1.25, 95%CI: 1.10-1.42) increased the risk of diabetes, while cognitive depressive symptoms were not associated with diabetes risk. Over an 8-year follow-up we identified 19729 trajectories of overall, somatic, and cognitive-affective depressive symptoms (HRS: 13918, ELSA: 5811). In the second phase we found that persistently high (HRS: HR = 1.22, 95%CI: 1.06-1.40, ELSA: HR = 1.54, 95%CI: 1.16-2.05 in total and HRS: HR = 1.24, 95%CI: 1.07-1.43, ELSA: HR = 1.79, 95%CI: 1.36-2.35 in somatic) and fluctuating (HRS: HR = 1.09, 95%CI: 1.01-1.17, ELSA: HR = 1.33, 95%CI: 1.14-1.55 in total and HRS: HR = 1.10, 95%CI: 1.02-1.18, ELSA: HR = 1.31, 95%CI: 1.13-1.53 in somatic) trajectories of overall and somatic depressive symptoms increased the risk of diabetes, while increasing trajectories may also raise diabetes risk. However, decreasing trajectories were not associated with diabetes risk. Cognitive-affective depressive symptoms showed no association with diabetes risk regardless of trajectory changes. Sensitivity analyses confirmed the reliability of the findings.CONCLUSIONPersistently high and fluctuating trajectories of overall and somatic depressive symptoms increased the risk of diabetes, while decreasing trajectories were not associated with diabetes risk. In contrast trajectories of cognitive-affective depressive symptoms show no relationship with diabetes risk. Focusing on depressive symptom trajectories, particularly those of somatic depressive symptoms, represented a viable strategy for future diabetes prevention.

While cardiovascular disease and cancer share common risk factors and exhibit complex bidirectional interplay, evidence regarding the interacting and joint effects of frailty and depressive symptoms on the risk of cardio-oncology comorbidity in older adults remains scarce. This study aimed to examine the association between frailty and depressive symptoms with the risk of cardio-oncology comorbidity, and to explore their interacting and joint effects. This study harmonized data from three prospective, nationally representative cohort studies: China Health and Retirement Longitudinal Study (CHARLS), the English Longitudinal Study of Ageing (ELSA), and the Health and Retirement Study (HRS). The final analytical sample included 10,937 participants aged ≥ 65 years without baseline cardio-oncology comorbidity. Frailty and depressive symptoms were assessed at baseline. Cardio-oncology comorbidity was ascertained based on self-reported physician diagnoses of cardiovascular disease and cancer. Cox proportional hazards models were utilized to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Multiplicative and additive interaction analyses were conducted, followed by joint association evaluations. Frailty (CHARLS HR = 1.71; ELSA HR = 1.41; HRS HR = 1.38) and depressive symptoms (CHARLS HR = 1.27; ELSA HR = 1.20; HRS HR = 1.18) were independently associated with significantly increased cardio-oncology comorbidity risk. While interaction analyses demonstrated the absence of significant multiplicative or additive interactions, the joint effect analysis revealed that cardio-oncology comorbidity risk was elevated among individuals with both frailty and depressive symptoms by 80% in CHARLS, 57% in ELSA, and 47% in HRS compared to those with neither condition. Concurrent frailty and depressive symptoms constitute the highest-risk phenotype for cardio-oncology comorbidity in community-dwelling older adults. These findings suggest that combined assessment of frailty and depressive symptoms may improve baseline risk stratification of cardio-oncology comorbidity.

Background: The coronavirus disease 19 (COVID-19) was declared a global pandemic on 11 March 2020. To date, a limited number of studies have examined the impact of this pandemic on healthcare-seeking behaviors of older populations. This longitudinal study examined personal characteristics linked to COVID-19 outcomes as predictors of self-reported delayed healthcare services attributed to this pandemic, among U.S. adults, ≥50 years of age. Methods: Secondary analyses were performed using cross-sectional data (1413 participants) and longitudinal data (2881 participants) from Health and Retirement Study (HRS) (2006–2018) linked to the 2020 HRS COVID-19 Project (57% female, mean age: 68 years). Demographic, socioeconomic, lifestyle and health characteristics were evaluated in relation to delayed overall, surgical and non-surgical healthcare services (“Since March 2020, was there any time when you needed medical or dental care, but delayed getting it, or did not get it at all?” and “What type of care did you delay”) using logistic regression and Ensemble machine learning for cross-sectional data as well as mixed-effects logistic modeling for longitudinal data. Results: Nearly 32.7% delayed healthcare services, 5.8% delayed surgical services and 31.4% delayed non-surgical services. Being female, having a college degree or higher and 1-unit increase in depression score were key predictors of delayed healthcare services. In fully adjusted logistic models, a history of 1 or 2 cardiovascular and/or metabolic conditions (vs. none) was associated with 60–70% greater odds of delays in non-surgical services, with distinct findings for histories of hypertension, cardiovascular disease, diabetes and stroke. Ensemble machine learning predicted surgical better than overall and non-surgical healthcare delays. Conclusion: Among older adults, sex, education and depressive symptoms are key predictors of delayed healthcare services attributed to the COVID-19 pandemic. Delays in surgical and non-surgical healthcare services may have distinct predictors, with non-surgical delays more frequently observed among individuals with a history of 1 or 2 cardiovascular and/or metabolic conditions.