Latent class growth modeling of depression and anxiety in older adults: an 8-year follow-up of a population-based study

Biopsychosocial Factors That Influence Depression, Anxiety, and Neuropsychological Functions in the Aging Process

BACKGROUND

Aging is a process inherent to the human condition that is characterized by various biological, psychological, and social changes that can lead to certain mental health problems.

OBJECTIVE

This study aimed to understand and characterize how biological, psychological, and social factors influence mental health symptoms and neuropsychological function in the aging process.

METHODS

A sample consisting of 616 participants (73.8% female) aged between 50 and 90 years, (mean [SD]: 69.6 [17.2] years). Data collection involved a neuropsychological assessment carried out by a psychologist in a clinical interview session and the self-completion of a questionnaire.

RESULTS

Regression models revealed that depressive symptoms are explained by anxiety, psychological and environmental quality of life, and sleep habits. Anxiety symptoms are explained by depression, physical quality of life, and sleep habits. Statistically significant differences were identified between participants with and without anxiety in neuropsychological terms at the level of agnosia and praxis. Statistically significant differences were identified between participants with and without depression in neuropsychological terms at the level of memory, language, agnosia and praxis, and executive function (eg, prefrontal tests).

CONCLUSIONS

Depression and anxiety symptoms are associated and could negatively influence the aging process. Aging should be understood in an ecological way taking into account the action of biological, psychological, social, and environmental factors, as well as the relationship and influence between the different levels and factors. This knowledge is important for diagnosis, for clinical practice, and for the development and definition of public policies to promote healthy aging.

The longitudinal association between physical health and depressive symptoms over eight years: Evidence from the health and retirement study

BACKGROUND

The bidirectional relationship between physical health (PH) and depressive symptoms (DS) remains unclear.

METHODS

Data were extracted from the Health and Retirement Study in the United States. PH was measured with a composite of chronic diseases, functional limitations and difficulties in basic and instrumental activities of daily living, and DS with a modified Center for Epidemiological Studies of Depression. Latent growth curve models (LGCM) were employed to examine how the change in PH or DS affected their mutual trajectories in later life. In addition, multilevel models were utilized.

RESULTS

There were 6144 participants included, with an average age of 69.82 ± 6.85 years at baseline, of whom 3686 (59.99 %) were women. PH scores increased from 5.65 in 2010 to 7.72 in 2018, while depression scores increased from 1.14 to 1.31. LGCM results showed that the initial levels of PH and DS were associated (β = 0.558, P < .001), and the initial level of PH could predict the trajectory of DS (β = 0.089, P < .001). Likewise, the initial level of DS was also related to initial PH (β = -0.563, P < .001) but couldn't predict the trajectory of PH. Furthermore, the slopes of PH and DS were predicted bidirectionally by each other. Two-level logistic models further demonstrated the bidirectional association between PH and DS.

CONCLUSION

There was a bidirectional association between physical health and depressive symptoms, which highlights the necessity of comprehensive health management for older adults with poor physical health or depression symptoms.

Stability and Change in Mental Health Profiles from Middle Adulthood to Very Old Age

OBJECTIVES

This study investigates mental health (MH) through the dual-factor model, emphasizing both well-being and ill-being. Our objectives were to (1) identify MH profiles based on this model; (2) track these profiles over time; and (3) explore socio-demographic and physical health factors associated with these profiles.

METHODS

We employed Latent Transition Analysis on data from 5,561 individuals aged 39-92, using two waves from the Survey of Health, Ageing, and Retirement in Europe. Well-being was assessed via life satisfaction and quality of life, while ill-being was measured through depression and loneliness. The predictors were socio-demographic and physical health variables.

RESULTS

Four distinct MH profiles emerged, each with unique levels of well-being and ill-being. Stability was more common in adaptive profiles. Physical health was key in predicting transition.

CONCLUSIONS

Identifying MH profiles in old age enhances our understanding of how MH adapts with aging. This approach reveals the complexity of MH beyond traditional ill-being, underscoring the importance of well-being.

CLINICAL IMPLICATIONS

• The majority of older adults maintain good MH, suggesting a need for a paradigm shift toward enhancing well-being rather than solely treating ill-being.• Effective MH interventions should integrate both well-being and ill-being assessments to offer understanding and support.

20-Year trajectories of six psychopathological dimensions in patients with first-episode psychosis: Could they be predicted?

Patients with first-episode psychoses (FEP) exhibit heterogeneity in clinical manifestations and outcomes. This study investigated the long-term trajectories of six key psychopathological dimensions (reality-distortion, negative, disorganization, catatonia, mania and depression) in patients diagnosed with FEP. A total of 243 patients were followed up for 20 years and the trajectories of the dimensions were analysed using growth mixture modelling. These dimensions showed varied course patterns, ranging from two to five trajectories. Additionally, the study examined the predictive value of different factors in differentiating between the long-term trajectories. The exposome risk score showed that familial load, distal and intermediate risk factors, acute psychosocial stressors and acute onset were significant predictors for differentiating between long-term psychopathological trajectories. In contrast, polygenic risk score, duration of untreated psychosis and duration of untreated illness demonstrated little or no predictive value. The findings highlight the importance of conducting a multidimensional assessment not only at FEP but also during follow-up to customize the effectiveness of interventions. Furthermore, the results emphasize the relevance of assessing premorbid predictors from the onset of illness. This may enable the identification of FEP patients at high-risk of poor long-term outcomes who would benefit from targeted prevention programs on specific psychopathological dimensions.

Neural correlates of successful emotion recognition in healthy elderly: a multimodal imaging study

The ageing process is associated with reduced emotional recognition (ER) performance. The ER ability is an essential part of non-verbal communication, and its role is crucial for proper social functioning. Here, using the 'Cambridge Centre for Ageing and Neuroscience cohort sample', we investigated when ER, measured using a facial emotion recognition test, begins to consistently decrease along the lifespan. Moreover, using structural and functional MRI data, we identified the neural correlates associated with ER maintenance in the age groups showing early signs of ER decline (N = 283; age range: 58-89 years). The ER performance was positively correlated with greater volume in the superior parietal lobule, higher white matter integrity in the corpus callosum and greater functional connectivity in the mid-cingulate area. Our results suggest that higher ER accuracy in older people is associated with preserved gray and white matter volumes in cognitive or interconnecting areas, subserving brain regions directly involved in emotional processing.

Association between chronic disease and depression among older adults in China: the moderating role of social participation

OBJECTIVES

Depression is an increasingly serious mental health problem worldwide. Therefore, this study aimed to explore the association between chronic disease and depression and to further test the moderating role of social participation in this association.

STUDY DESIGN

This is a cross-sectional study.

METHODS

We screened 6421 subjects from the 2018 wave of the China Health and Retirement Longitudinal Study database. Social participation and depressive symptoms were assessed using the 12-item self-made scale and 10-item Center for Epidemiological Studies Depression Scale, respectively. Hierarchical regression was used to determine the main effect of chronic disease and depression and the moderating effect of social participation on the relationship between chronic disease and depression.

RESULTS

In this study, 3172 (49.40%) eligible participants were male, 4680 (72.90%) older adults were concentrated in the 65-74 years group, and 68.20% reported good health status. In addition, gender, area, education level, marital status, health status, health insurance, health service utilization, and physical activity intensity were significant factors associated with participants' depression status (P < 0.05). The results also showed that a higher number of chronic diseases were associated with a higher depression score after adjusting for confounders (single disease: β = 0.074, P < 0.001; multimorbidity: β = 0.171, P < 0.001) and that social participation played a moderating role in this association (β = -0.030, P < 0.05).

CONCLUSIONS

This study tentatively suggests that a higher number of chronic diseases are associated with rising depression scores in the older Chinese population. In addition, the moderating effect of social participation suggests that more active social engagement should be promoted in this population to alleviate the depressive mood.

Life satisfaction, positive affect, depression and anxiety symptoms, and their relationship with sociodemographic, psychosocial, and clinical variables in a general elderly population sample from Chile

Background

This study aims to describe the relationship between life satisfaction, positive affect, depression and anxiety symptoms with sociodemographic, psychosocial and clinical variables, and to identify the relative importance of these predictor groups.

Methods

We evaluated life satisfaction (SWLS), positive affect (PANAS), depressive (PHQ-9), and anxiety (GAI) symptoms and their association with sociodemographic, psychosocial and clinical variables in a multistage, random general population sample of fully functioning individuals aged 60-80 years from the Concepción province and Gran Santiago, Chile (n = 396). We performed weighted multiple regression analysis, considering the complex sample structure with age group, sex, and geographical area, complemented with general and conditional dominance analyses to estimate the relevance of the predictor groups.

Results

We found significant associations with the geographical area, sex, age, education level, household members, having a partner, employment status, caregiver status, economic satisfaction, presence of chronic diseases, medication use, and alcohol use. Satisfaction with health was the most important predictor for positive affect (p < 0.001), depressive (p < 0.001), and anxiety (p < 0.001) symptoms, while alcohol use was the most significant predictor for life satisfaction (p < 0.001).

Conclusion

Simultaneously studying the positive and negative dimensions of wellbeing and mental health in older adults allows for a more comprehensive perspective on the challenges faced during this stage of life. This study accounts for previously unknown associations and contributes to the identification of common and specific predictors in both dimensions.

Cretan Aging Cohort-Phase III: Methodology and Descriptive Characteristics of a Long-Term Longitudinal Study on Predictors of Cognitive Decline in Non-Demented Elderly from Crete, Greece

Identifying modifiable factors that may predict long-term cognitive decline in the elderly with adequate daily functionality is critical. Such factors may include poor sleep quality and quantity, sleep-related breathing disorders, inflammatory cytokines and stress hormones, as well as mental health problems. This work reports the methodology and descriptive characteristics of a long-term, multidisciplinary study on modifiable risk factors for cognitive status progression, focusing on the 7-year follow-up. Participants were recruited from a large community-dwelling cohort residing in Crete, Greece (CAC; Cretan Aging Cohort). Baseline assessments were conducted in 2013-2014 (Phase I and II, circa 6-month time interval) and follow-up in 2020-2022 (Phase III). In total, 151 individuals completed the Phase III evaluation. Of those, 71 were cognitively non-impaired (CNI group) in Phase II and 80 had been diagnosed with mild cognitive impairment (MCI). In addition to sociodemographic, lifestyle, medical, neuropsychological, and neuropsychiatric data, objective sleep was assessed based on actigraphy (Phase II and III) and home polysomnography (Phase III), while inflammation markers and stress hormones were measured in both phases. Despite the homogeneity of the sample in most sociodemographic indices, MCI persons were significantly older (mean age = 75.03 years, SD = 6.34) and genetically predisposed for cognitive deterioration (APOE ε4 allele carriership). Also, at follow-up, we detected a significant increase in self-reported anxiety symptoms along with a substantial rise in psychotropic medication use and incidence of major medical morbidities. The longitudinal design of the CAC study may provide significant data on possible modifiable factors in the course of cognitive progression in the community-dwelling elderly.

Psychometric Evaluation of the Chinese Version of Mild Cognitive Impairment Questionnaire among Older Adults with Mild Cognitive Impairment

BACKGROUND

There is a lack of instruments for measuring quality of life (QOL) in Chinese patients with mild cognitive impairment (MCI). This study aimed to translate the Mild Cognitive Questionnaire (MCQ) into the Chinese language and to evaluate the reliability and construct validity of the MCQ-Chinese among older adults with MCI.

METHODS

Linguistic translation and validation of the questionnaire were conducted according to the MCQ developer and Oxford University Innovation guidelines. After a pilot test, the final version of the MCQ-Chinese was applied to a convenience sample of older adults with MCI (n = 186). Cronbach's alpha and confirmatory factor analyses were used to assess the reliability and construct validity of the MCQ-Chinese. In addition, non-parametric analysis was used to assess convergent and discriminant validity.

RESULTS

The total scale and all the factors had good internal consistency, with Cronbach's alpha values ranging from 0.90 to 0.92. Confirmatory factor analysis indicated satisfactory goodness of fit for the 2-factor MCQ. The MCQ-Chinese had a good convergent validity, and the discriminant validity was confirmed with a significant difference in MCQ scores in different health conditions.

CONCLUSIONS

MCQ-Chinese is a reliable tool for assessing QOL among Chinese older adults with MCI.

Multimorbidity and Mental Health Trajectories Among Middle-Aged and Older U.S. Adults During the COVID-19 Pandemic: Longitudinal Findings From the COVID-19 Coping Study

Background and Objectives

This study aimed to examine the associations between multimorbidity at the COVID-19 pandemic onset and subsequent longitudinal trajectories of depressive symptoms, anxiety symptoms, and loneliness in middle-aged and older adults over a 12-month follow-up.

Research Design and Methods

Data were from monthly online questionnaires in the COVID-19 Coping Study of U.S. adults aged ≥55 from April/May 2020 through April/May 2021 (N = 4,024). Multimorbidity was defined as having ≥2 versus <2 chronic conditions at baseline. Mental health outcomes were assessed monthly as depressive symptoms (8-item Center for Epidemiologic Studies Depression scale), anxiety symptoms (5-item Beck Anxiety Inventory), and loneliness (3-item UCLA Loneliness Scale). We used multivariable-adjusted population- and attrition-weighted mixed-effects linear models to examine the longitudinal associations between multimorbidity and mental health symptoms.

Results

Multimorbidity at the pandemic onset was associated with elevated depressive (b = 0.37; 95% CI: 0.16-0.59) and anxiety (b = 0.39; 95% CI: 0.15-0.62) symptoms at baseline. Changes in symptoms for all three mental health outcomes were nonlinear over time, with worsening symptoms over the first 6 months of the pandemic (April/May to September/October 2020), followed by improvement in symptoms over the subsequent 6 months (September/October 2020 to April/May 2021). Middle-aged and older adults with multimorbidity experienced faster rates of change in anxiety symptoms and loneliness than those without multimorbidity, with persistently elevated mental health symptomatology throughout the follow-up.

Discussion and Implications

Results highlight the unique and persistent mental health risks experienced by middle-aged and older adults with multimorbidity during the COVID-19 pandemic. The observed improvements in symptoms underscore the mental resilience of these individuals, indicating their adaptation to the ongoing pandemic.