16 research outputs found
Adolescent depression beyond DSM definition: a network analysis
Calls for refning the understanding of depression beyond diagnostic criteria have been growing in recent years. We examined the prevalence and relevance of DSM and non-DSM depressive symptoms in two Brazilian school-based adolescent samples with two commonly used scales, the Patient Health Questionnaire (PHQ-A) and the Mood and Feelings Questionnaire (MFQ). We analyzed cross-sectional data from two similarly recruited samples of adolescents aged 14–16 years, as part of the Identifying Depression Early in Adolescence (IDEA) study in Brazil. We assessed dimensional depressive symptomatology using the PHQ-A in the frst sample (n=7720) and the MFQ in the second sample (n=1070). We conducted network analyses to study symptom structure and centrality estimates of the two scales. Additionally, we compared centrality of items included (e.g., low mood, anhedonia) and not included in the DSM (e.g., low self-esteem, loneliness) in the MFQ. Sad mood and worthlessness items were the most central items in the network structure of the PHQ-A. In the MFQ sample, self-hatred and loneliness, two non-DSM features, were the most central items and DSM and non-DSM items in this scale formed a highly interconnected network of symptoms. Furthermore, analysis of the MFQ sample revealed DSM items not to be more frequent, severe or interconnected than non-DSM items, but rather part of a larger network of symptoms. A focus on symptoms might advance research on adolescent depression by enhancing our understanding of the disorder.publishedVersio
Dynamic relationships between depressive symptoms and insulin resistance over 20 years of adulthood
Background. Bidirectional longitudinal relationships between depression and diabetes have been observed, but the dominant direction of their temporal relationships remains controversial.
Methods. The random-intercept cross-lagged panel model decomposes observed variables into a latent intercept representing the traits, and occasion-specific latent ‘state’ variables. This permits correlations to be assessed between the traits, while longitudinal ‘cross-lagged’ associations and cross-sectional correlations can be assessed between occasion-specific latent variables. We examined dynamic relationships between depressive symptoms and insulin resistance across five visits over 20 years of adulthood in the population-based Coronary Artery Risk Development in Young Adults (CARDIA) study. Possible differences based on population group (Black v. White participants), sex and years of education were tested. Depressive symptoms and insulin resistance were quantified using the Center for Epidemiologic Studies Depression (CES-D) scale and the homeostatic model assessment for insulin resistance (HOMA-IR), respectively.
Results. Among 4044 participants (baseline mean age 34.9 ± 3.7 years, 53% women, 51% Black participants), HOMA-IR and CES-D traits were weakly correlated (r = 0.081, p = 0.002). Some occasion-specific correlations, but no cross-lagged associations were observed overall. Longitudinal dynamics of these relationships differed by population groups such that HOMAIR at age 50 was associated with CES-D score at age 55 (β = 0.076, p = 0.038) in White participants only. Longitudinal dynamics were consistent between sexes and based on education.
Conclusions. The relationship between depressive symptoms and insulin resistance was best characterized by weak correlations between occasion-specific states and enduring traits, with weak evidence that insulin resistance might be temporally associated with subsequent depressive symptoms among White participants later in adulthood.publishedVersio
Dynamic relationships between depressive symptoms and insulin resistance over 20 years of adulthood
Background
Bidirectional longitudinal relationships between depression and diabetes have been observed, but the dominant direction of their temporal relationships remains controversial.
Methods
The random-intercept cross-lagged panel model decomposes observed variables into a latent intercept representing the traits, and occasion-specific latent ‘state’ variables. This permits correlations to be assessed between the traits, while longitudinal ‘cross-lagged’ associations and cross-sectional correlations can be assessed between occasion-specific latent variables. We examined dynamic relationships between depressive symptoms and insulin resistance across five visits over 20 years of adulthood in the population-based Coronary Artery Risk Development in Young Adults (CARDIA) study. Possible differences based on population group (Black v. White participants), sex and years of education were tested. Depressive symptoms and insulin resistance were quantified using the Center for Epidemiologic Studies Depression (CES-D) scale and the homeostatic model assessment for insulin resistance (HOMA-IR), respectively.
Results
Among 4044 participants (baseline mean age 34.9 ± 3.7 years, 53% women, 51% Black participants), HOMA-IR and CES-D traits were weakly correlated (r = 0.081, p = 0.002). Some occasion-specific correlations, but no cross-lagged associations were observed overall. Longitudinal dynamics of these relationships differed by population groups such that HOMA-IR at age 50 was associated with CES-D score at age 55 (β = 0.076, p = 0.038) in White participants only. Longitudinal dynamics were consistent between sexes and based on education.
Conclusions
The relationship between depressive symptoms and insulin resistance was best characterized by weak correlations between occasion-specific states and enduring traits, with weak evidence that insulin resistance might be temporally associated with subsequent depressive symptoms among White participants later in adulthood
State, trait, and accumulated features of the Alzheimer's Disease Assessment Scale Cognitive Subscale (ADAS-Cog) in mild Alzheimer's disease
Background
The Alzheimer's Disease Assessment Scale Cognitive Subscale (ADAS-Cog) is used to assess decline in memory, language, and praxis in Alzheimer's disease (AD).
Methods
A latent state–trait model with autoregressive effects was used to determine how much of the ADAS-Cog item measurement was reliable, and of that, how much of the information was occasion specific (state) versus consistent (trait or accumulated from one visit to the next).
Results
Participants with mild AD (n = 341) were assessed four times over 24 months. Praxis items were generally unreliable as were some memory items. Language items were generally the most reliable, and this increased over time. Only two ADAS-Cog items showed reliability >0.70 at all four assessments, word recall (memory) and naming (language). Of the reliable information, language items exhibited greater consistency (63.4% to 88.2%) than occasion specificity, and of the consistent information, language items tended to reflect effects of AD progression that accumulated from one visit to the next (35.5% to 45.3%). In contrast, reliable information from praxis items tended to come from trait information. The reliable information in the memory items reflected more consistent than occasion-specific information, but they varied between items in the relative amounts of trait versus accumulated effects.
Conclusions
Although the ADAS-Cog was designed to track cognitive decline, most items were unreliable, and each item captured different amounts of information related to occasion-specific, trait, and accumulated effects of AD over time. These latent properties complicate the interpretation of trends seen in ordinary statistical analyses of trials and other clinical studies with repeated ADAS-Cog item measures
Validation of a Tool to Evaluate Drug Prevention Programs Among Students
Background: School-based prevention programs have been implemented worldwide with the intention of reducing or delaying the onset of alcohol and drug use among adolescents. However, their effects need to be evaluated, being essential to use validated and reliable questionnaires for this purpose. This study aimed to verify the semantic validity and reliability of an instrument developed to evaluate the results of a government drug prevention program for schoolchildren called #Tamojunto2.0.Methods: This is a mixed methods study with quantitative (test-retest, confirmatory factor analysis and non-response evaluation) and qualitative analyses (focus group and field cards). The self-administered questionnaires were used for a sample of 262 eighth-grade students (elementary school II) in 11 classes of four public schools in the city of São Paulo.Results: The level of agreement was substantial (Kappa 0.60–0.79) or almost perfect (Kappa > 0.8) for almost all questions about the use of marijuana, alcohol, cigarettes, cocaine, crack, and binge drinking. The model fit indices, for almost all secondary outcomes, indicated that the modls underlying each scale, constituted by observed and latent variables, had a good fit adjustument. The focus groups and field cards provided high-quality information that helped the researchers identify the main difficulties in applying and understanding the questions.Conclusion: The questionnaire showed high factorial validity, reliability and understanding by adolescents. After the necessary changes, identified in this study, the questionnaire will be suitable to evaluate the results of the #Tamojunto2.0 program in a randomized controlled trial
Adolescent depression beyond DSM definition: a network analysis
Calls for refining the understanding of depression beyond diagnostic criteria have been growing in recent years. We examined the prevalence and relevance of DSM and non-DSM depressive symptoms in two Brazilian school-based adolescent samples with two commonly used scales, the Patient Health Questionnaire (PHQ-A) and the Mood and Feelings Questionnaire (MFQ). We analyzed cross-sectional data from two similarly recruited samples of adolescents aged 14-16 years, as part of the Identifying Depression Early in Adolescence (IDEA) study in Brazil. We assessed dimensional depressive symptomatology using the PHQ-A in the first sample (n = 7720) and the MFQ in the second sample (n = 1070). We conducted network analyses to study symptom structure and centrality estimates of the two scales. Additionally, we compared centrality of items included (e.g., low mood, anhedonia) and not included in the DSM (e.g., low self-esteem, loneliness) in the MFQ. Sad mood and worthlessness items were the most central items in the network structure of the PHQ-A. In the MFQ sample, self-hatred and loneliness, two non-DSM features, were the most central items and DSM and non-DSM items in this scale formed a highly interconnected network of symptoms. Furthermore, analysis of the MFQ sample revealed DSM items not to be more frequent, severe or interconnected than non-DSM items, but rather part of a larger network of symptoms. A focus on symptoms might advance research on adolescent depression by enhancing our understanding of the disorder
Adolescent depression beyond DSM definition: a network analysis
Calls for refning the understanding of depression beyond diagnostic criteria have been growing in recent years. We examined the prevalence and relevance of DSM and non-DSM depressive symptoms in two Brazilian school-based adolescent samples with two commonly used scales, the Patient Health Questionnaire (PHQ-A) and the Mood and Feelings Questionnaire (MFQ). We analyzed cross-sectional data from two similarly recruited samples of adolescents aged 14–16 years, as part of the Identifying Depression Early in Adolescence (IDEA) study in Brazil. We assessed dimensional depressive symptomatology using the PHQ-A in the frst sample (n=7720) and the MFQ in the second sample (n=1070). We conducted network analyses to study symptom structure and centrality estimates of the two scales. Additionally, we compared centrality of items included (e.g., low mood, anhedonia) and not included in the DSM (e.g., low self-esteem, loneliness) in the MFQ. Sad mood and worthlessness items were the most central items in the network structure of the PHQ-A. In the MFQ sample, self-hatred and loneliness, two non-DSM features, were the most central items and DSM and non-DSM items in this scale formed a highly interconnected network of symptoms. Furthermore, analysis of the MFQ sample revealed DSM items not to be more frequent, severe or interconnected than non-DSM items, but rather part of a larger network of symptoms. A focus on symptoms might advance research on adolescent depression by enhancing our understanding of the disorder
Dynamic relationships between depressive symptoms and insulin resistance over 20 years of adulthood
Background. Bidirectional longitudinal relationships between depression and diabetes have been observed, but the dominant direction of their temporal relationships remains controversial.
Methods. The random-intercept cross-lagged panel model decomposes observed variables into a latent intercept representing the traits, and occasion-specific latent ‘state’ variables. This permits correlations to be assessed between the traits, while longitudinal ‘cross-lagged’ associations and cross-sectional correlations can be assessed between occasion-specific latent variables. We examined dynamic relationships between depressive symptoms and insulin resistance across five visits over 20 years of adulthood in the population-based Coronary Artery Risk Development in Young Adults (CARDIA) study. Possible differences based on population group (Black v. White participants), sex and years of education were tested. Depressive symptoms and insulin resistance were quantified using the Center for Epidemiologic Studies Depression (CES-D) scale and the homeostatic model assessment for insulin resistance (HOMA-IR), respectively.
Results. Among 4044 participants (baseline mean age 34.9 ± 3.7 years, 53% women, 51% Black participants), HOMA-IR and CES-D traits were weakly correlated (r = 0.081, p = 0.002). Some occasion-specific correlations, but no cross-lagged associations were observed overall. Longitudinal dynamics of these relationships differed by population groups such that HOMAIR at age 50 was associated with CES-D score at age 55 (β = 0.076, p = 0.038) in White participants only. Longitudinal dynamics were consistent between sexes and based on education.
Conclusions. The relationship between depressive symptoms and insulin resistance was best characterized by weak correlations between occasion-specific states and enduring traits, with weak evidence that insulin resistance might be temporally associated with subsequent depressive symptoms among White participants later in adulthood
A peripheral neutrophil-related inflammatory factor predicts a decline in executive function in mild Alzheimer’s disease
Abstract
Background
Studies suggest a role of the innate immune system, including the activity of neutrophils, in neurodegeneration related to Alzheimer’s disease (AD), but prospective cognitive data remain lacking in humans. We aimed to investigate the predictive relationship between neutrophil-associated inflammatory proteins in peripheral blood and changes in memory and executive function over 1 year in patients with AD.
Methods
Participants with AD were identified from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Neutrophil gelatinase-associated lipocalin (NGAL), myeloperoxidase (MPO), interleukin-8 (IL-8), macrophage inflammatory protein-1 beta (MIP-1β), and tumor necrosis factor (TNF) were assayed by luminex immunofluorescence multiplex assay at baseline. Confirmatory factor analysis was used to test an underlying neutrophil associated plasma inflammatory factor. Composite z-scores for memory and executive function were generated from multiple tests at baseline and at 1 year. A multiple linear regression model was used to investigate the association of the baseline inflammatory factor with changes in memory and executive function over 1 year.
Results
Among AD patients (n = 109, age = 74.8 ± 8.1, 42% women, Mini Mental State Examination [MMSE] = 23.6 ± 1.9), the neutrophil-related inflammatory proteins NGAL (λ = 0.595, p < .001), MPO (λ = 0.575, p < .001), IL-8 (λ = 0.525, p < .001), MIP-1β (λ = 0.411, p = .008), and TNF (λ = 0.475, p < .001) were found to inform an underlying factor. Over 1 year, this inflammatory factor predicted a decline in executive function (β = − 0.152, p = 0.015) but not memory (β = 0.030, p = 0.577) in models controlling for demographics, brain atrophy, white matter hyperintensities, the ApoE ε4 allele, concomitant medications, and baseline cognitive performance.
Conclusions
An inflammatory factor constructed from five neutrophil-related markers in peripheral blood predicted a decline in executive function over 1 year in people with mild AD