Difference of depression between widowed and non-widowed older people in China: A network analysis approach

A latent profile analysis and network analysis of anxiety and depression symptoms in Chinese widowed elderly

BACKGROUND

Widowhood, as a traumatic event in the aging process, may lead to adverse psychological consequences such as anxiety and depression. However, the heterogeneity of anxiety and depression comorbidity patterns in widowed elderly and the interrelationships between symptoms have not been adequately studied.

METHOD

10,239 elderly aged 65 years and older were screened from the Chinese Longitudinal Healthy Longevity Survey (CLHLS 2017-2018), to assess depression and anxiety using the Center for Epidemiologic Studies Depression Scale (CESD) and the 7-item Generalized Anxiety Disorder Questionnaire (GAD). The subgroups of widowed elderly with similar patterns of symptoms were identified by latent profile analysis (LPA). The structure of anxiety-depressive comorbidity network was characterized using "bridge expected influence" as centrality indices. Network stability was tested using a case drop bootstrap program. A network comparison test (NCT) was performed to examine the differences in network characteristics across LPA subgroups.

RESULT

LPA identified dichotomous profiles: low comorbid (n = 4457) and high comorbid (n = 692). NCT revealed a significant difference in the global strength between networks (S = 0.631, p < 0.001). GAD1 (Nervousness or anxiety) is the common bridging symptom for both networks, while the bridging symptom for the high comorbidity network also includes GAD3 (Generalized worry).

LIMITATIONS

Cross-sectional methods are unable to verify causal relationships, and further randomized controlled trials are warranted.

CONCLUSION

Anxiety-depressive pattern in Chinese widowed elderly can be categorized into a low comorbid or a high comorbid group. GAD3 (Generalized worry) can be used as the core intervention target during intervention.

Social activities and depressive symptoms among migrant middle-aged and older adults in China: a network analysis

Background

This study investigated the central symptom within the depression network and examined the relationship between social activities and depressive symptoms among migrant middle-aged and older adults in China.

Methods

We analyzed data from 1,926 migrants aged 45 and older, derived from the 2018 China Health and Retirement Longitudinal Study (CHARLS). Using network analysis, we identified the central depressive symptom and assessed the association between various social activities and depressive symptoms.

Results

Network analysis revealed that depressed mood was the most central symptom. Regarding mitigation of depressive symptoms, informal social activities predominantly influenced positive emotions and somatic symptoms. Formal activities were mainly revealed through positive emotions. Solitary activities were manifested primarily through positive emotions and somatic symptoms. In addition, informal and solitary activities showed a stronger correlation with the alleviation of depressive symptoms compared to formal activities.

Conclusion

The findings underscore the importance of addressing depressed mood in treating depression among migrant middle-aged and older adults. Recognizing the differential impacts of various social activities can aid in the development of customized prevention and intervention strategies aimed at enhancing the mental well-being of this demographic in China.

Purpose in life, loneliness and depression among patients with substance use disorders in the psychiatric hospitals in Ghana

Substance use disorder is a global mental health issue. Purpose in life, Loneliness and depression are key indicators of poor mental health, and people with substance use disorder are more likely to experience low purpose in life, depression, and loneliness. This study aims to further the understanding of purpose in life, depression and loneliness among substance use disorders (SUD) patients in three hospitals in Ghana. It uses a cross-sectional survey design. A total of 425 SUD inpatients were screened. Beck Depression Inventory-II, the revised UCLA Loneliness Scale, and the Purpose in Life Test were utilised to measure depression, loneliness, and purpose in life respectively. Data were analysed using the SPSS version 23 for Windows. Data from 378 participants were collected for this study using a cross sectional survey design; after data cleaning, frequency tables (for categorical variables) and descriptive statistics (for continuous variables) were used to summarise the demographics and the three outcome variables depression, purpose in life, and loneliness. Our findings indicate that overall, participants are more likely to experience low sense of purpose in life, depression, and loneliness compared to the general population. There was no statistically significant relationship between depression and loneliness (r = 0.030, p = 0.567). There was a statistically significant negative relationship between depression and purpose in life (r = -0.514, p < 0.001). There was a statistically significant positive relationship between purpose in life and loneliness (r = 0.147, p = 0.004). There was no gender difference in depression, purpose in life, and loneliness among SUDs patients in psychiatric hospitals. There were no significant differences in purpose in life, depression and loneliness based on marital status. It is anticipated that the findings of this study will inform policies and clinical practice regarding service provision for patients with SUDs.

The development of depressive symptoms in older adults from a network perspective in the English Longitudinal Study of Ageing

An increased understanding of the interrelations between depressive symptoms among older populations could help improve interventions. However, studies often use sum scores to understand depression in older populations, neglecting important symptom dynamics that can be elucidated in evolving depressive symptom networks. We computed Cross-Lagged Panel Network Models (CLPN) of depression symptoms in 11,391 adults from the English Longitudinal Study of Ageing. Adults aged 50 and above (mean age 65) were followed over 16 years throughout this nine-wave representative population study. Using the eight-item Center for Epidemiological Studies Depression Scale, we computed eight CLPNs covering each consecutive wave. Across waves, networks were consistent with respect to the strength of lagged associations (edge weights) and the degree of interrelationships among symptoms (centrality indices). Everything was an effort and could not get going displayed the strongest reciprocal cross-lagged associations across waves. These two symptoms and loneliness were core symptoms as reflected in strong incoming and outgoing connections. Feeling depressed was strongly predicted by other symptoms only (incoming but not strong outgoing connections were observed) and thus was not related to new symptom onset. Restless sleep had outgoing connections only and thus was a precursor to other depression symptoms. Being happy and enjoying life were the least central symptoms. This research underscores the relevance of somatic symptoms in evolving depression networks among older populations. Findings suggest the central symptoms from the present study (everything was an effort, could not get going, loneliness) may be potential key intervention targets to mitigate depression in older adults.

The core inflammatory factors in patients with major depressive disorder: a network analysis

Introduction

The symptoms of major depressive disorder (MDD) vary widely. Psycho-neuro-inflammation has shown that MDD's inflammatory factors can accelerate or slow disease progression. This network analysis study examined the complex interactions between depressed symptoms and inflammatory factors in MDD prevention and treatment.

Measures

We gathered participants' inflammatory factor levels, used the Hamilton Depression Scale (HAMD-17), and network analysis was used to analyzed the data. Network analysis revealed the core inflammatory (nodes) and their interactions (edges). Stability and accuracy tests assessed these centrality measures' network robustness. Cluster analysis was used to group persons with similar dimension depressive symptoms and examine their networks.

Results

Interleukin-1β (IL-1β) is the core inflammatory factor in the overall sample, and IL-1β-interleukin-4 (IL-4) is the strongest correlation. Network precision and stability passed. Network analysis showed significant differences between Cluster 1 (with more severe anxiety/somatization and sleep disruption) and Cluster 3 (with more severe retardation and cognitive disorders), as well as between Cluster 2 (with more severe anxiety/somatization, sleep disruption and body weight) and Cluster 3. IL-1β is the core inflammatory factor in Cluster 1 and Cluster 2, while tumor necrosis factor alpha (TNF-α) in Cluster 3.

Conclusion

IL-1β is the central inflammatory factor in the network, and there is heterogeneity in the core inflammatory factor of MDD with specific depressive dimension symptoms as the main manifestation. In conclusion, inflammatory factors and their links should be prioritized in future theoretical models of MDD and may provide new research targets for MDD intervention and treatment.

Prevalence, correlates, and network analysis of depression and its associated quality of life among ophthalmology nurses during the COVID-19 pandemic

Background

Nurses in Ophthalmology Department (OD) had a high risk of infection during the novel coronavirus disease 2019 (COVID-19) pandemic. This study examined the prevalence, correlates, and network structure of depression, and explored its association with quality of life (QOL) in Chinese OD nurses.

Methods

Based on a cross-sectional survey, demographic and clinical data were collected. Depression was measured with the 9-item Self-reported Patient Health Questionnaire (PHQ-9), and QOL was measured using the World Health Organization Quality of Life Questionnaire-brief version (WHOQOL-BREF). Univariate analyses, multivariate logistic regression analyses, and network analyses were performed.

Results

Altogether, 2,155 OD nurses were included. The overall prevalence of depression among OD nurses was 32.71% (95%CI: 30.73-34.70%). Multiple logistic regression analysis revealed that having family or friends or colleagues who were infected (OR = 1.760, p = 0.003) was significantly associated with higher risk of depression. After controlling for covariates, nurses with depression reported lower QOL (F(1, 2,155) = 596.784, p < 0.001) than those without depression. Network analyses revealed that 'Sad Mood', 'Energy Loss' and 'Worthlessness' were the key central symptoms.

Conclusion

Depression was common among OD nurses during the COVID-19 pandemic. Considering the negative impact of depression on QOL and daily life, regular screening for depression, timely counselling service, and psychiatric treatment should be provided for OD nurses, especially those who had infected family/friends or colleagues. Central symptoms identified in network analysis should be targeted in the treatment of depression.

Prevalence of depression and its association with quality of life in patients after pacemaker implantation during the COVID-19 pandemic: A network analysis

Background

This study was designed to investigate the prevalence and predictors of depression in patients after pacemaker implantation during the COVID-19 pandemic in addition to identifying specific depressive symptoms associated with quality of life (QOL) using network analysis (NA).

Methods

This cross-sectional, observational study was conducted in China between July 1, 2021, and May 17, 2022. Descriptive analysis was used to calculate depression prevalence. Univariate analyses were used to compare differences in demographic and clinical characteristics between depressed and non-depressed patients following pacemaker implantation. Binary logistic regression analysis was used to assess factors independently associated with depression. Network analysis “expected influence,” and flow function indexes were used to identify symptoms central to the depression network of the sample and depressive symptoms that were directly associated with QOL, respectively. Network stability was examined using a case-dropping bootstrap procedure.

Results

In total, 206 patients implanted with a pacemaker met the study entry criteria and completed the assessment. The overall prevalence of depression (PHQ-9 total score ≥ 5) was 39.92% [95% confidence interval (CI) = 29.37−42.47%]. A binary logistic regression analysis revealed that patients with depression were more likely to report a poor health status (p = 0.031), severe anxiety symptoms (p &lt; 0.001), and fatigue (p &lt; 0.001). In the network model for depression, “Sad mood,” “Poor Energy,” and “Guilt” were the most influential symptoms. “Fatigue” had the strongest negative association with QOL, followed by “Sad mood” and “Appetite”.

Conclusion

Depression is common among patients having undergone pacemaker implantation during the COVID-19 pandemic. Anxiety, central symptoms of depression (i.e., “Sad mood”, “Poor Energy”, and “Guilt”) and depressive symptoms linked to QOL (i.e., “Sad mood”, “Appetite”, and “Fatigue”) identified in this study are promising targets for interventions and preventive measures for depression in patients who have undergone pacemaker implants.

Symptom Structure of Depression in Older Adults on the Qinghai-Tibet Plateau: A Network Analysis

Previous studies have confirmed that depression among residents in high-altitude areas is more severe, and that depression may be more persistent and disabling in older adults. This study aims to identify the symptom structure of depression among older adults on the Qinghai-Tibet Plateau (the highest plateau in the world) from a network perspective. This cross-sectional study enrolled 507 older adults (ages 60-80 years old) from the Yushu Prefecture, which is on the Qinghai-Tibet Plateau, China. Depressive symptoms were self-reported using the shortened Center for Epidemiological Studies-Depression Scale (CES-D-10). Then, a Gaussian graphical model (GGM) of depression was developed. Poor sleep, fear, and hopelessness about the future exhibited high centrality in the network. The strongest edge connections emerged between unhappiness and hopelessness about the future, followed by hopelessness about the future and fear; hopelessness about the future and poor sleep; fear and unhappiness; and then poor sleep and unhappiness in the network. The findings of this current study add to the small body of literature on the network structure and complex relationships between depressive symptoms in older adults in high-altitude areas.

The relationship between gender, marital status and depression among Chinese middle-aged and older people: Mediation by subjective well-being and moderation by degree of digitization

The purposes of this study were to investigate the effects of gender and marital status on depression among middle-aged and older people in China, and to explore the mediating effect of subjective well-being and the moderating effect of degree of digitization in the relationship between subjective well-being and depression. A total of 15,586 Chinese middle-aged and older people (≥ 45 years old) were included in the study using data from the 2018 China Health and Retirement Longitudinal Survey (CHARLS). T-test, ANOVA, hierarchical regression and Bootstrap methods were adopted to test the mediating role of subjective well-being and the moderating role of degree of digitization. The results showed that middle-aged and older women were more likely to suffer from depression than men, and married middle-aged and older people were less likely to be depressed than those who were separated or divorced, widowed and never married. Subjective well-being partially mediated the relationship between gender and depression, and masked the relationship between marital status and depression, and all five dimensions it contains also played a mediating role. Degree of digitization moderated the effect of subjective well-being on depression. Simple slope tests indicated that the effect of subjective well-being on depression increased as degree of digitization increased. In conclusion, to address the mental health problems of middle-aged and older people brought about by the ageing and digital society, we should start by improving their subjective well-being and promoting their integration into the digital society.

Network analysis of depressive and anxiety symptoms in adolescents during and after the COVID-19 outbreak peak

BACKGROUND

This study examined the extent to which the network structure of anxiety and depression among adolescents identified during the peak of the COVID-19 pandemic could be cross-validated in a sample of adolescents assessed after the COVID-19 peak.

METHODS

Two cross-sectional surveys were conducted between February 20 and 27, 2020 and between April 11 and 19, 2020, respectively. Depressive and anxiety symptoms were assessed using the 20-item Center for Epidemiological Studies-Depression and 7-item Generalized Anxiety Disorder, respectively. Anxiety-depression networks of the first and second assessments were estimated separately using a sparse Graphical Gaussian Model combined with the graphical least absolute shrinkage and selection operator method. A Network Comparison Test was conducted to assess differences between the two networks.

RESULTS

The most central symptoms in the first and second survey networks were Depressed affect and Nervousness. Compared with connections in the first survey network, connections in the second survey network analysis between Relax-Nervousness-Depressed affect-Interpersonal problems (diff, contrast: second survey-first survey. diff=-0.04, P = 0.04; diff=-0.03, P = 0.03; diff=-0.03, P = 0.04), and Irritability-Somatic complaints (diff=-0.04, P = 0.02) were weaker while connections of Somatic complaints-Nervousness (diff=0.05, P<0.001), Somatic complaints-Depressed affect (diff=0.03, P = 0.009), and Irritability-Control worry-Restlessness (diff=0.02, P = 0.03; diff=0.05, P = 0.02) were stronger.

CONCLUSIONS

Depressed affect emerged as a robust central symptom and bridge symptom across Anxiety-Depression networks. Considering the negative impact of depression and anxiety on daily life, timely interventions targeting depressed affect should be implemented to reduce the co-occurrence of anxious and depressive symptoms among adolescents during the COVID-19 pandemic.

Network Analysis of Depressive Symptomatology in Underweight and Obese Adults

BACKGROUND

Depressive symptoms can affect people's quality of life and social environment. In addition, in severe situations, they can lead to suicidal behaviors.

OBJECTIVE

This study aimed to analyze the differences in depressive symptoms in underweight and obese Peruvian adults.

METHODS

A cross-sectional study was carried out based on secondary data obtained from the Instituto Nacional de Estadística e Informática (INEI), Lima, Peru. A sample of 10 053 participants was considered, of which 55.96% were women. Two Gaussian plot models were estimated and the levels of depressive symptomatology were compared between the 2 groups (adults with underweight and obese).

RESULTS

A total of 1510 (15.02%) were underweight adults and 8543 (84.98%) were obese adults. There were differences in the reporting of depressive symptoms in the underweight group; the most central items were "Depressed mood" (PH2), "Tiredness/low energy" (PH4), and "Psychomotor difficulties" (PH8).

CONCLUSION

This study provides new evidence on the dynamic relationship between depressive symptoms according to the body mass index categories (underweight and obese) assessed.