Psychometric Properties of the Adult Self-Report: Data from over 11,000 American Adults

The first purpose of this study was to examine the factor structure of the Adult Self-Report (ASR) via traditional confirmatory factor analysis (CFA) and contemporary exploratory structural equation modeling (ESEM). The second purpose was to examine the measurement invariance of the ASR subscales across age groups. We used baseline data from the Adolescent Brain Cognitive Development study. ASR data from 11,773 participants were used to conduct the CFA and ESEM analyses and data from 11,678 participants were used to conduct measurement invariance testing. Fit indices supported both the CFA and ESEM solutions, with the ESEM solution yielding better fit indices. However, several items in the ESEM solution did not sufficiently load on their intended factors and/or cross-loaded on unintended factors. Results from the measurement invariance analysis suggested that the ASR subscales are robust and fully invariant across subgroups of adults formed on the basis of age (18–35 years vs. 36–59 years). Future research should seek to both CFA and ESEM to provide a more comprehensive assessment of the ASR

Typologies of Family Functioning and 24-h Movement Behaviors

Research on the importance of the family environment on children’s health behaviors is ubiquitous, yet critical gaps in the literature exist. Many studies have focused on one family characteristic and have relied on variable-centered approaches as opposed to person-centered approaches (e.g., latent profile analysis). The purpose of the current study was to use latent profile analysis to identify family typologies characterized by parental acceptance, parental monitoring, and family conflict, and to examine whether such typologies are associated with the number of movement behavior recommendations (i.e., physical activity, screen time, and sleep) met by children. Data for this cross-sectional observational study were part of the baseline data from the Adolescent Brain Cognitive Development (ABCD) study. Data were collected across 21 study sites in the United States. Participants included 10,712 children (female = 5143, males = 5578) aged 9 and 10 years (M = 9.91, SD = 0.62). Results showed that children were meaningfully classified into one of five family typologies. Children from families with high acceptance, medium monitoring, and medium conflict (P2; OR = 0.54; 95% CI, 0.39–0.76); high acceptance, medium monitoring, and high conflict (P3; OR = 0.28; 95% CI, 0.20, 0.40); low acceptance, low monitoring, and medium conflict (P4; OR = 0.24; 95% CI, 0.16, 0.36); and medium acceptance, low monitoring, and high conflict (P5; OR = 0.19; 95% CI, 0.12–0.29) were less likely to meet all three movement behavior recommendations compared to children from families with high acceptance, high monitoring, and low conflict (P1). These findings highlight the importance of the family environment for promoting healthy movement behaviors among children

Personality Profiles Identify Depressive Symptoms over Ten Years? A Population-Based Study

Little is known about the relationship between temperament and character inventory (TCI) profiles and depressive symptoms. Personality profiles are useful, because personality traits may have different effects on depressive symptoms when combined with different combinations of other traits. Participants were from the population-based Young Finns study with repeated measurements in 1997, 2001, and 2007 (n = 1402 to 1902). TCI was administered in 1997 and mild depressive symptoms (modified Beck's depression inventory, BDI) were reported in 1997, 2001, and 2007. BDI-II was also administered in 2007. We found that high harm avoidance and low self-directedness related strongly to depressive symptoms. In addition, sensitive (NHR) and fanatical people (ScT) were especially vulnerable to depressive symptoms. high novelty seeking and reward dependence increased depressive symptoms when harm avoidance was high. These associations were very similar in cross-sectional and longitudinal analysis. Personality profiles help in understanding the complex associations between depressive symptoms and personality

Social isolation and loneliness as risk factors for myocardial infarction, stroke and mortality : UK Biobank cohort study of 479 054 men and women

Objective To examine whether social isolation and loneliness (1) predict acute myocardial infarction (AMI) and stroke among those with no history of AMI or stroke, (2) are related to mortality risk among those with a history of AMI or stroke, and (3) the extent to which these associations are explained by known risk factors or pre-existing chronic conditions. Methods Participants were 479 054 individuals from the UK Biobank. The exposures were self-reported social isolation and loneliness. AMI, stroke and mortality were the outcomes. Results Over 7.1 years, 5731 had first AMI, and 3471 had first stroke. In model adjusted for demographics, social isolation was associated with higher risk of AMI (HR 1.43, 95% CI 1.3 to -1.55) and stroke (HR 1.39, 95% CI 1.25 to 1.54). When adjusted for all the other risk factors, the HR for AMI was attenuated by 84% to 1.07 (95% CI 0.99 to 1.16) and the HR for stroke was attenuated by 83% to 1.06 (95% CI 0.96 to 1.19). Loneliness was associated with higher risk of AMI before (HR 1.49, 95% CI 1.36 to 1.64) but attenuated considerably with adjustments (HR 1.06, 95% CI 0.96 to 1.17). This was also the case for stroke (HR 1.36, 95% CI 1.20 to 1.55 before and HR 1.04, 95% CI 0.91 to 1.19 after adjustments). Social isolation, but not loneliness, was associated with increased mortality in participants with a history of AMI (HR 1.25, 95% CI 1.03 to 1.51) or stroke (HR 1.32, 95% CI 1.08 to 1.61) in the fully adjusted model. Conclusions Isolated and lonely persons are at increased risk of AMI and stroke, and, among those with a history of AMI or stroke, increased risk of death. Most of this risk was explained by conventional risk factors.Peer reviewe

Network structure of depression symptomology in participants with and without depressive disorder : the population-based Health 2000-2011 study

Purpose Putative causal relations among depressive symptoms in forms of network structures have been of recent interest, with prior studies suggesting that high connectivity of the symptom network may drive the disease process. We examined in detail the network structure of depressive symptoms among participants with and without depressive disorders (DD; consisting of major depressive disorder (MDD) and dysthymia) at two time points. Methods Participants were from the nationally representative Health 2000 and Health 2011 surveys. In 2000 and 2011, there were 5998 healthy participants (DD-) and 595 participants with DD diagnosis (DD+). Depressive symptoms were measured using the 13-item version of the Beck Depression Inventory (BDI). Fused Graphical Lasso was used to estimate network structures, and mixed graphical models were used to assess network connectivity and symptom centrality. Network community structure was examined using the walktrap-algorithm and minimum spanning trees (MST). Symptom centrality was evaluated with expected influence and participation coefficients. Results Overall connectivity did not differ between networks from participants with and without DD, but more simple community structure was observed among those with DD compared to those without DD. Exploratory analyses revealed small differences between the samples in the order of one centrality estimate participation coefficient. Conclusions Community structure, but not overall connectivity of the symptom network, may be different for people with DD compared to people without DD. This difference may be of importance when estimating the overall connectivity differences between groups with and without mental disorders.Peer reviewe

Typologies of Family Functioning and 24-h Movement Behaviors

Research on the importance of the family environment on children’s health behaviors is ubiquitous, yet critical gaps in the literature exist. Many studies have focused on one family characteristic and have relied on variable-centered approaches as opposed to person-centered approaches (e.g., latent profile analysis). The purpose of the current study was to use latent profile analysis to identify family typologies characterized by parental acceptance, parental monitoring, and family conflict, and to examine whether such typologies are associated with the number of movement behavior recommendations (i.e., physical activity, screen time, and sleep) met by children. Data for this cross-sectional observational study were part of the baseline data from the Adolescent Brain Cognitive Development (ABCD) study. Data were collected across 21 study sites in the United States. Participants included 10,712 children (female = 5143, males = 5578) aged 9 and 10 years (M = 9.91, SD = 0.62). Results showed that children were meaningfully classified into one of five family typologies. Children from families with high acceptance, medium monitoring, and medium conflict (P2; OR = 0.54; 95% CI, 0.39–0.76); high acceptance, medium monitoring, and high conflict (P3; OR = 0.28; 95% CI, 0.20, 0.40); low acceptance, low monitoring, and medium conflict (P4; OR = 0.24; 95% CI, 0.16, 0.36); and medium acceptance, low monitoring, and high conflict (P5; OR = 0.19; 95% CI, 0.12–0.29) were less likely to meet all three movement behavior recommendations compared to children from families with high acceptance, high monitoring, and low conflict (P1). These findings highlight the importance of the family environment for promoting healthy movement behaviors among children

Childhood disruptive behaviour and school performance across comprehensive school: A prospective cohort study

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Does high optimism protect against the inter-generational transmission of high BMI? The Cardiovascular Risk in Young Finns Study

Objective: The transmission of overweight from one generation to the next is well established, however little is known about what psychosocial factors may protect against this familial risk. The aim of this study was to examine whether optimism plays a role in the intergenerational transmission of obesity. Methods: Our sample included 1043 participants from the prospective Cardiovascular Risk in Young FINNS Study. Optimism was measured in early adulthood (2001) when the cohort was aged 24-39 years. BMI was measured in 2001 (baseline) and 2012 when they were aged 35-50 years. Parental BMI was measured in 1980. Hierarchical linear regression and logistic regression were used to examine the association between optimism and future BMI/obesity, and whether an interaction existed between optimism and parental BMI when predicting BMI/obesity 11 years later. Results: High optimism in young adulthood demonstrated a negative relationship with high BMI in mid-adulthood, but only in women (beta = - 0.127, p = 0.001). The optimism x maternal BMI interaction term was a significant predictor of future BMI in women (beta = 0.588, p = 0.036). The logistic regression results confirmed that high optimism predicted reduced obesity in women (OR = 0.68, 95% CI, 0.55-0.86), however the optimism x maternal obesity interaction term was not a significant predictor (OR = 0.50, 95% CI, 0.10-2.48). Conclusions: Our findings supported our hypothesis that high optimism mitigated the intergenerational transmission of high BMI, but only in women. These findings also provided evidence that positive psychosocial factors such as optimism are associated with long-term protective effects on BMI in women.Peer reviewe

Cardiac stress reactivity and recovery of novelty seekers

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