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Background: In recent decades, the relationship between emotional disorders (i.e., depression and anxiety) and alterations in physiological functions (i.e., inflammation or metabolism) have been well supported. However, studies on a symptom-based approach have provided mixed results. Our study aims to gain insight into how subclinical statuses, featured by elevated depressive and/or anxious symptoms, may influence immunometabolic alterations in the concurrent relationship; and the development of metabolic diseases at 10-year follow-up: diabetes, hypertension and hypercholesterolemia. Methods: Data from 758 Greek adults [394 men (aged 41 ± 10 years) and 364 women (aged 37 ± 12 years)] were used. Four groups were created according to the levels of depressive and anxiety symptoms: (1) control group (CG), (2) depressive group (DG), (3) anxiety group (AG) and (4) depressive and anxiety group (DAG). Multi-indicator multi-causes (MIMIC) modeling was used to estimate metabolic function and inflammatory response scores, on a wide selection of blood biomarkers. Finally, a binary logistic regression was carried out to study the influence of symptoms on the development of the aforementioned metabolic diseases on a 10-year follow-up. Results: Group membership was not associated with metabolic function score. Conversely, DAG membership was related with higher inflammatory response score (B = 0.20, CI95 = 0.01, 0.40), with respect to the CG (p < 0.05). Both age and sex were significant variables in the calculation of both scores. Regarding disease at 10-year follow-up effect, risk of developing diabetes, hypertension and hypercholesterolemia was associated with age and socioeconomic status. Moreover, DG membership was significant for diabetes risk (OR = 2.08, CI95 = 1.00, 4.22) and DAG for hypercholesterolemia (OR = 1.68, CI95 = 1.16, 2.43). Limitations: Data on anti-inflammatory drugs and psychopharmacological medication were not collected in this study.Conclusions: Elevated symptoms of depression and anxiety accounts for inflammatory alterations at concurrent relationship and a higher risk of 10-year follow-up metabolic diseases. [ABSTRACT FROM AUTHOR]

Objective: To analyse the patterns of relationships between depressive symptoms and immunometabolic markers across longitudinal depression status in older people. Methods: A sample of 3349 older adults (55.21% women; initial age: m = 58.44, sd = 5.21) from the English Longitudinal Study of Ageing was used. Participants were classified according to their longitudinal depression status: minimal depressive symptoms (n = 2736), depressive episode onset (n = 481), or chronic depression (n = 132). Network analysis was used to study the relationships between depression symptoms (CES-D 8 items), inflammatory (white blood cell, C-reactive protein, fibrinogen) and metabolic biomarkers (metabolic syndrome markers). Results: Network structure remained invariant across groups. The minimal symptom group had higher overall strength than both clinical groups (p <.01). Moreover, significant relationships between symptoms and markers were observed across group-specific networks. C-reactive protein and effort symptom were positively connected in the minimal symptom group but not in the other groups. Loneliness and diastolic blood pressure were positively associated only in the chronic depression group. Finally, metabolic markers were identified as central nodes in the clinical status networks. Conclusion: The network analysis constitutes a useful approach to disentangle pathophysiological relationships that may maintain mental disorders in old age. [ABSTRACT FROM AUTHOR]

We compared the trajectory of activities of daily living (ADL) in a nationally representative sample of older Nigerians with their Spanish peers and identified factors to explain country-specific growth models. Data from two household multistage probability samples were used, comprising older adults from Spain (n = 2,011) and Nigeria (n = 1,704). All participants underwent assessment for ADL. Risk factors including sex, household income, urbanicity, years of education, depression, alcohol consumption and smoking were assessed using validated methods. State-space model in continuous time (SSM-CT) methods were used for trajectory comparison. Compared with Nigerians (µADL80=0.44, SE = 0.015, p < 0.001), Spanish older adults had higher disability scores (µADL80=1.23, SE = 0.021, p < 0.001). In SSM-CT models, the rate of increase in disability was faster in Nigerians (Nigeria: β = 0.061, p<.01; Spain: β = 0.028, p < 0.010). An increasing course of disability in the Spanish sample was predicted by female sex, lower education and depression diagnosis. The rate of increase in disability was faster in older Nigerians living in an economically disadvantaged context. [ABSTRACT FROM AUTHOR]

Objectives 1) To study the relationship between resilience resources (both social and individual) and emotional symptomatology (depression and anxiety symptoms), taking into account the potential indirect effects through perceived stress; 2) to investigate whether this network of relationships varies in different age groups. Method: A sample of 718 Brazilians completed self-reports on perceived stress, depressive and anxious symptomatology, social support and individual resilience. The sample comprised two age groups: a sample of adults aged 60 or older (n = 361; 38.78% men; Mage = 67.32 years, SDage = 5.76, range = 60-86), and a sample of younger adults (n = 357; 29.41% men; Mage = 41.37 years, SDage = 7.23, range = 18-59). Multigroup multiple indicator, multiple cause (MIMIC) modelling was used to test for the direct and indirect effects of resilience resources on emotional symptom development, considering the age groups. Results: The relationship between individual resilience resources and depressive or anxiety symptomatology was found to take place exclusively through stressfulness appraisal. On the other hand, social resilience resources showed a direct and indirect effect on emotional symptoms. This pattern of relationships was found to be invariant across age groups. Conclusion: Our findings suggest that both individual and social resilience resources are negatively related to both depressive and anxiety symptoms in adults regardless of age, thus opening the way to future research analysing how interventions may build resilience resources to minimise the influence of stressful and traumatic events across the lifespan. [ABSTRACT FROM AUTHOR]

Breast cancer constitutes a challenge for survival and wellbeing. Emotional distress may persist many years after cancer being cured. This study aimed to analyse how emotional symptomatology was present in breast cancer survivors. Additionally, it aimed to study the role of sleep difficulty and worry on symptom maintenance. A sample of 206 women (M= 56.07 years, SD= 11.56) was selected to form four groups: healthy controls, breast cancer patients, short-term and long-term survivors. Emotional distress, worry and sleep problems were assessed. Long-term survivors showed significantly higher levels of anxiety (p< .05). Anxiety was predicted by worry for all groups but with higher variance in long-term survivors (R2 adj= .47). Insomnia and age predicted depression in this group (R2 adj= .40). To conclude, long-term emotional distress was observed even after the threat of cancer passed. Our findings confirm the need to extend supportive care to meet survivors' needs. [ABSTRACT FROM AUTHOR]

Background: The concept of European psychologisation of depression versus somatisation in non-European populations has been the basis of several studies of cultural psychopathology in the general population. Little is currently known about cross-cultural differences and similarities in late-life depression symptom reporting. We cross-culturally compared symptom reporting in the context of Major Depressive Disorder (MDD) among community-dwelling older adults from Spain and Nigeria.Methods: We relied on data from two household multistage probability samples comprising 3,715 persons aged 65 years or older in the Spanish and Nigerian populations. All participants underwent assessments for MDD using the World Mental Health Survey version of the Composite International Diagnostic Interview. Cross-cultural comparison of broad somatic and psychological categories as well as relationship and influence of individual symptoms were analysed using the Symptom Network Analysis approach.Results: Current MDD was diagnosed in 232 and 195 older persons from Spain and Nigeria, respectively. The symptom network of the two samples were invariant in terms of global strength, S(GSPAIN , GNIGERIA ) = 7.56, P = .06, with psychological and somatic symptoms demonstrating centrality in both countries. However, country-specific relationships and influence of individual symptoms were found in the network structure of both samples, M(GSPAIN , GNIGERIA ) = 2.95, P < .01.Conclusion: Broad somatic and psychological symptoms categories contributed to the structural network of older Africans and their peers from the Spanish population. Variations in the relationship and influence of individual symptoms suggests that the functional and "communicative" role of individual symptoms may be differentiated by context specific imperatives. J Am Geriatr Soc 68:-, 2020. [ABSTRACT FROM AUTHOR]

This study aimed: (1) to identify heterogeneous trajectories of anxiety symptoms in early adolescence; (2) to analyze the relationships between risk factors and identified trajectories; (3) to study the association between anxiety symptom trajectories and depression symptom course. Anxiety and depressive symptoms of 825 participants (44.40% boys; mean initial age = 13.01, SD = 0.56) was assessed every 6 months over an 18-month period. Trajectory identification relied on latent-variable approach. As a result, 2-4 trajectories were identified for social phobia (SP), generalized anxiety (GA) and panic symptoms, revealing at least a low-symptom course and a trajectory of elevated symptoms (at-risk trajectory). Being girl and sibling cohabitation were related to at-risk trajectories, and a course of low effortful control and heightened negative affectivity. Finally, SP and GA symptoms were related to heightened depressive symptom courses. Relevant implications towards tailored prevention and intervention are highlighted to promote a healthy development across adolescence. [ABSTRACT FROM AUTHOR]

Background and Objectives There is a link between sensory and cognitive functioning across old age. However, there are no integrative measures for assessing common determinants of sensory-cognitive functioning. This study aims to develop a combined measure of sensory-cognitive functioning, and to identify heterogeneous trajectories and associated risk factors. Research Design and Methods Two thousand two hundred and fifty-five individuals aged 60 years and over selected from the first six waves (2002–2012) of the English Longitudinal Study of Ageing completed a set of five self-reported visual and hearing functioning items and four cognitive items. Several health-related outcomes were also collected. Results The common cause model presented longitudinal factorial invariance (Tucker-Lewis index [TLI] = 0.989; Comparative Fit Index [CFI] = 0.991; Root Mean Square Error of Approximation [RMSEA] = 0.026). A common factor explained 32%, 36%, and 26% of the visual, hearing, and cognitive difficulties, respectively. The developed sensory-cognitive measure predicted incident dementia over 10 years (area under the curve =.80; 95% confidence interval [CI] =.75,.86). A three-trajectory model was proved to fit better, according to growth mixture modeling. Low levels of education and household wealth, disability, diabetes, high blood pressure, depressive symptoms, and low levels of physical activity were risk factors associated with the classes showing trajectories with a steeper increase of sensory-cognitive difficulties. Discussion and Implications A time-invariant factor explains both sensory and cognitive functioning over 8 years. The sensory-cognitive measure derived from this factor showed a good performance for predicting dementia 10 years later. Several easily identifiable socioeconomic and health-related risk factors could be used as early markers of subsequent sensory-cognitive decline. Therefore, the proposed latent measure could be useful as a cost-effective indicator of sensory-cognitive functioning. [ABSTRACT FROM AUTHOR]

Background: The long-term trajectory of depressive symptoms has a heterogeneous pattern. Identifying factors associated with different trajectories and outcomes may have important theoretical and clinical implications. This study explored patterns of depressive symptom trajectory from adolescence to adulthood, and their relationship with subsequent psychiatric disorders.Method: A sample of 816 participants (58.8% girls; M = 16.58 years old at baseline, SD = 1.21) from a large community sample were interviewed four times during adolescence and adulthood. Depressive symptoms were also assessed. Symptom trajectory identification was based on latent class mixed modeling. Logistic regression was used for predicting emotional and drug use disorder over age 30.Results: Three trajectories of depressive symptoms were identified: "decreasing symptom" (decreasing trajectory of symptoms; 15.1% of participants), "increasing symptom" (initially decreasing pattern of symptoms and then increasing; 6.1% of participants), and "normative symptom" (consistently low symptom levels; 78.8% of participants). Predictors of the increasing symptom trajectory were high level of loneliness and state anxiety, presence of an emotional disorder, and low involvement in physical exercise at baseline. This trajectory membership predicted the development of anxiety disorders over age 30. Predictors of the decreasing symptom class were being female and high level of worry at baseline.Conclusions: Long-term trajectories of depressive symptoms are heterogeneous, with each trajectory having different predictors and are associated with different outcomes during adulthood. [ABSTRACT FROM AUTHOR]

• The three-class solution best fits the data with the classes that are characterised by adolescents with high probability of emotional disorders (Class I), high probability with behavioural disorders (Class II), and with low probability of mental disorders (Class III). • Adolescents in the emotional disorders comorbidity class were more likely to be girls, while as adolescents in the behavioural disorders comorbidity class were more likely to be boys. • Adolescents in the emotional and behavioural disorders comorbidity classes were more likely to live with their non-biological parents. The aim of this study was to identify the number of comorbidity profiles among adolescents. Sociodemographic factors associated with the comorbidity profiles were also examined. Latent class analysis was conducted using data from the National Comorbidity Survey Adolescent Supplement (NCS-A), a representative sample of adolescents (N = 10,123) in the United States. Latent classes were derived from 26 lifetime mental disorders which were assessed using the World Health Organization Composite International Diagnostic Instrument (CIDI). A three-class solution provided the best fit for the data, with classes labelled as comorbid emotional disorders (Class I), comorbid behavioural disorders (Class II), and normative (Class III). Class I (15.62% of the participants) included adolescents with a high probability of having anxiety, depressive, and intermittent explosive disorder. Class II (6.97%) was characterised by adolescents with a high probability of having substance use, behavioural disorders, and major depression. Class III (77.41%) was characterised by adolescents with a low probability of having any mental disorders. Characterising comorbid profile of mental disorders using person-based approach yields a higher-order classification that could have important clinical implications. [ABSTRACT FROM AUTHOR]

Background: This study aimed at depicting the course of depression symptoms over the old age, with a special interest in a) uncovering its relationships with sociodemographic and health-related factors; b) analysing its predictive role on healthy-ageing outcomes later in life.Methods: The sample comprised 8317 older adults (46.02% men) from the English Longitudinal Study of Ageing. Robust structural equation modelling was used to identify symptom trajectories and their relationships with time-varying factors. Trajectory class and covariates were used to predict outcomes (quality of life, satisfaction with life, and daily living functioning) in a 2-year follow-up.Results: Three trajectory classes (so-called, normative, subclinical, chronic symptom trajectories) were identified for both sexes. Rising hearing difficulties and history of psychiatric problems were consistently associated with the chronic symptom trajectory. Lower education level, history of psychiatric problems, and increasing visual difficulties were connected with the subclinical trajectories. Finally, participants with either a subclinical or a chronic symptom trajectory showed worse outcomes than the remaining participants in the follow-up.Conclusion: This study highlighted the presence of varying courses of depression symptoms (each showing some distinctive features from other another) over the old age, pointing to some relevant implications for clinical assessment and treatment prescription. [ABSTRACT FROM AUTHOR]

Although there is scientific evidence of the presence of immunometabolic alterations in major depression, not all patients present them. Recent studies point to the association between an inflammatory phenotype and certain clinical symptoms in patients with depression. The objective of our study was to classify major depression disorder patients using supervised learning algorithms or machine learning, based on immunometabolic and oxidative stress biomarkers and lifestyle habits. Taking into account a series of inflammatory and oxidative stress biomarkers (C-reactive protein (CRP), tumor necrosis factor (TNF), 4-hydroxynonenal (HNE) and glutathione), metabolic risk markers (blood pressure, waist circumference and glucose, triglyceride and cholesterol levels) and lifestyle habits of the participants (physical activity, smoking and alcohol consumption), a study was carried out using machine learning in a sample of 171 participants, 91 patients with depression (71.42% women, mean age = 50.64) and 80 healthy subjects (67.50% women, mean age = 49.12). The algorithm used was the support vector machine, performing cross validation, by which the subdivision of the sample in training (70%) and test (30%) was carried out in order to estimate the precision of the model. The prediction of belonging to the patient group (MDD patients versus control subjects), melancholic type (melancholic versus non-melancholic patients) or resistant depression group (treatment-resistant versus non-treatment-resistant) was based on the importance of each of the immunometabolic and lifestyle variables. With the application of the algorithm, controls versus patients, such as patients with melancholic symptoms versus non-melancholic symptoms, and resistant versus non-resistant symptoms in the test phase were optimally classified. The variables that showed greater importance, according to the results of the area under the ROC curve, for the discrimination between healthy subjects and patients with depression were current alcohol consumption (AUC = 0.62), TNF-α levels (AUC = 0.61), glutathione redox status (AUC = 0.60) and the performance of both moderate (AUC = 0.59) and vigorous physical exercise (AUC = 0.58). On the other hand, the most important variables for classifying melancholic patients in relation to lifestyle habits were past (AUC = 0.65) and current (AUC = 0.60) tobacco habit, as well as walking routinely (AUC = 0.59) and in relation to immunometabolic markers were the levels of CRP (AUC = 0.62) and glucose (AUC = 0.58). In the analysis of the importance of the variables for the classification of treatment-resistant patients versus non-resistant patients, the systolic blood pressure (SBP) variable was shown to be the most relevant (AUC = 0.67). Other immunometabolic variables were also among the most important such as TNF-α (AUC = 0.65) and waist circumference (AUC = 0.64). In this case, sex (AUC = 0.59) was also relevant along with alcohol (AUC = 0.58) and tobacco (AUC = 0.56) consumption. The results obtained in our study show that it is possible to predict the diagnosis of depression and its clinical typology from immunometabolic markers and lifestyle habits, using machine learning techniques. The use of this type of methodology could facilitate the identification of patients at risk of presenting depression and could be very useful for managing clinical heterogeneity. • Differences in inflammatory and oxidative stress biomarkers are found in some patients with major depressive disorder. • With the application of supervised machine learning algorithms, major depressive patients were optimally classified. • The study of immunometabolic biomarkers and lifestyle variables can help to disentangle the clinical heterogeneity of major depression. [ABSTRACT FROM AUTHOR]

Alterations in cognitive performance have been described in patients with major depressive disorder (MDD). However, the specific risk factors of these changes are not yet known. This study aimed to explore whether inmunometabolic parameters are related to cognitive performance in MDD in comparison to healthy controls (HC) Sample consisted of 84 MDD patients and 78 HC. Both groups were compared on the results of cognitive performance measured with the Cambridge Neuropsychological Test Automated Battery (CANTAB), the presence of metabolic syndrome (MetS) and an inflammatory/oxidative index calculated by a principal component analysis of peripheral biomarkers (tumor necrosis factor, C-reactive protein and 4-hydroxynonenal). A multiple linear regression was carried out, to study the relationship between inmunometabolic variables and the global cognitive performance, being the latter the dependent variable. Significant differences were obtained in the inflammatory/oxidative index between both groups (F (1157) = 12.93; p <.001), also in cognitive performance (F (1157) = 56.75; p <.001). The inmunometabolic covariate regression model (i.e., condition (HC/MDD), sex, age and medication loading, MetS, inflammatory/oxidative index and the interaction between MetS and inflammatory/oxidative index) was statistically significant (F (7157) = 11.24; p <.01) and explained 31% of variance. The condition, being either MDD or HD, (B=˗0.97; p <.001), age (B=˗0.28; p <.001) and the interaction between inflammatory/oxidative index and MetS (B=˗0.38; p =.02) were factors associated to cognitive performance. Sample size was relatively small. The cross-sectional design of the study limits the possibilities of analysis. Our results provide evidence on the conjoint influence of metabolic and inflammatory dysregulation on cognitive dysfunction in MDD patients. In this way, our study opens a line of research in immunometabolic agents to deal with cognitive decline associated with MDD. • MDD patients show dysregulation in an inflammatory index obtained from peripheral biomarkers. • Suffering from MDD, being older and having MetS with high inflammatory index are related to poorer cognitive performance. • Cognitive impairment in MDD is increased in patients in which metabolic and inflammatory dysregulation coexist. [ABSTRACT FROM AUTHOR]

Suicide is an international health concern with immeasurable impact from the perspective of human and social suffering. Prior suicide attempts, anxious and depressive symptoms, and relatively lower health-related quality of life (HRQoL) are among the most replicated risk factors for suicide. Our goal was to visualize the distribution of these features and their interconnections with use of a network analysis approach in individuals who recently attempted suicide. Individuals with a recent suicide attempt were recruited from nine University Hospitals across Spain as part of the SURVIVE cohort study. Anxious and depressive symptoms, and perceived HRQoL were included in the network analysis. Network structures were estimated with the EBICglasso model. Centrality measures and bridge symptoms connecting communities were explored. Subnetworks comparing younger and older individuals, and women and men were analyzed. A total of 1106 individuals with a recent suicide attempt were included. Depressed mood was the symptom with the greatest influence in the overall network, followed by anxiety symptoms such as feeling nervous, worrying, restless, and having difficulties to relax. Perceived general health was associated with increased suicidal ideation in the whole sample. Older people showed a specific connection between perceived general health and depressed mood. The cross-sectional design does not allow determination of established causality. Depressed mood was the core network's symptom and, therefore, an important target in the management and prevention of suicide. HRQoL had more influence on the network of older populations, in which it should be a primary focus. • Identifying risk factors for suicide is crucial for developing prevention programs. • Network analysis allows studying interrelations of symptoms in suicidal behaviors. • Depressed mood is the core symptom in individuals who recently attempted suicide. [ABSTRACT FROM AUTHOR]

• Depressive men had increased risk of metabolic dysregulation in old age. • Loneliness feelings put depressive women at higher risk of metabolic dysregulation. • Multimorbidity development was boosted by depression with loneliness in men and women. This study aimed to examine how loneliness contributes to metabolic dysregulation among older adults with depression and determine the relative contribution of loneliness to the development of chronic diseases in late adulthood. Harmonised data from the Ageing Trajectories of Health: Longitudinal Opportunities and Synergies (ATHLOS) project were used. Concretely, the sample comprised 6195 participants (53.95% women; M = 61.30 years, SD = 7.11) from three European cohorts. Three groups were considered: control group (CG); depressive symptom episode group (DEP); and a group with depression and loneliness (DEP + LONE). A metabolic score was estimated using anthropometric and blood indicators, by means of multi-indicator multi-causes (MIMIC) modelling and after controlling for sociodemographic and health-related covariates. Group-comparison was based on measurement-invariance procedures. Multimorbidity development was predicted at follow-up considering the study group and relevant covariates. All the analyses were sex-specific. As a result, measurement invariance revealed the influence of group (ΔCFI = −0.017 for male participants and ΔCFI = −0.009 for female ones) on metabolic scores in both sexes. Metabolic scores were significantly lower (i.e., they had more metabolic risk) in DEP + LONE women in comparison to women from the other groups. DEP men showed the lowest metabolic scores but those from the DEP + LONE group showed meaningfully lower scores than CG men (d = 1.35). In terms of multimorbidity prediction, DEP + LONE group membership significantly predicted the outcome in both sexes; DEP group membership significantly predicted multimorbidity at follow-up in women. In summary, these results highlight the relevant contribution of loneliness in depression-related metabolic dysregulation in the short- (concurrent metabolic risk) and long-term (chronic condition development). Moreover, sex-specific mechanisms seem to be involved in metabolic alterations of depressed people showing loneliness feelings. This study calls for action to reduce the impact of loneliness in old age and to promote healthy ageing. [ABSTRACT FROM AUTHOR]