Person:

Dunn, Erin

Background: Social support is frequently linked to positive parenting behavior. Similarly, studies increasingly show a link between neighborhood residential environment and positive parenting behavior. However, less is known about how the residential environment influences parental social support. To address this gap, we examine the relationship between neighborhood concentrated disadvantage and collective efficacy and the level and change in parental caregiver perceptions of non-familial social support. Methodology/Principal Findings: The data for this study came from three data sources, the Project on Human Development in Chicago Neighborhoods (PHDCN) Study's Longitudinal Cohort Survey of caregivers and their offspring, a Community Survey of adult residents in these same neighborhoods and the 1990 Census. Social support is measured at Wave 1 and Wave 3 and neighborhood characteristics are measured at Wave 1. Multilevel linear regression models are fit. The results show that neighborhood collective efficacy is a significant ((\beta) = .04; SE = .02; p = .03), predictor of the positive change in perceived social support over a 7 year period, however, not of the level of social support, adjusting for key compositional variables and neighborhood concentrated disadvantage. In contrast concentrated neighborhood disadvantage is not a significant predictor of either the level or change in social support. Conclusion: Our finding suggests that neighborhood collective efficacy may be important for inducing the perception of support from friends in parental caregivers over time.

Background: Depression is a common source of human disability for which etiologic insights remain limited. Although abnormalities of monoamine neurotransmission, including dopamine, are theorized to contribute to the pathophysiology of depression, evidence linking dopamine-related genes to depression has been mixed. The current study sought to address this knowledge-gap by examining whether the combined effect of dopamine polymorphisms was associated with depressive symptomatology in both healthy individuals and individuals with depression. Methods: Data were drawn from three independent samples: (1) a discovery sample of healthy adult participants (n = 273); (2) a replication sample of adults with depression (n = 1,267); and (3) a replication sample of healthy adult participants (n = 382). A genetic risk score was created by combining functional polymorphisms from five genes involved in synaptic dopamine availability (COMT and DAT) and dopamine receptor binding (DRD1, DRD2, DRD3). Results: In the discovery sample, the genetic risk score was associated with depressive symptomatology (β = −0.80, p = 0.003), with lower dopamine genetic risk scores (indicating lower dopaminergic neurotransmission) predicting higher levels of depression. This result was replicated with a similar genetic risk score based on imputed genetic data from adults with depression (β = −0.51, p = 0.04). Results were of similar magnitude and in the expected direction in a cohort of healthy adult participants (β = −0.86, p = 0.15). Conclusions: Sequence variation in multiple genes regulating dopamine neurotransmission may influence depressive symptoms, in a manner that appears to be additive. Further studies are required to confirm the role of genetic variation in dopamine metabolism and depression.

Little is known about the unique contribution of schools vs neighborhoods in driving adolescent marijuana use. This study examined the relative contribution of each setting and the influence of school and neighborhood socioeconomic status on use. We performed a series of cross-classified multilevel logistic models predicting past 30-day adolescent (N = 18 329) and young adult (N = 13 908) marijuana use using data from Add Health. Marijuana use differed by age, sex, race/ethnicity, and public assistance in adjusted models. Variance parameters indicated a high degree of clustering by school (σ2 = 0.30) and less pronounced clustering by neighborhood (σ2 = 0.06) in adolescence when accounting for both levels simultaneously in a cross-classified multilevel model. Clustering by school persisted into young adulthood (σ2 = 0.08). Parental receipt of public assistance increased the likelihood of use during adolescence (odds ratio = 1.39; 95% confidence interval: 1.19–1.59), and higher parental education was associated with increased likelihood of use in young adulthood. These findings indicate that both contexts may be promising locations for intervention.

Population health scientists increasingly study how contextual-level attributes affect individual health. A major challenge in this domain relates to measurement, i.e., how best to measure and create variables that capture characteristics of individuals and their embedded contexts. This paper presents an illustration of multilevel factor analysis (MLFA), an analytic method that enables researchers to model contextual effects using individual-level data without using derived variables. MLFA uses the shared variance in sets of observed items among individuals within the same context to estimate a measurement model for latent constructs; it does this by decomposing the total sample variance-covariance matrix into within-group (e.g., individual-level) and between-group (e.g., contextual-level) matrices and simultaneously modeling distinct latent factor structures at each level. We illustrate the MLFA method using items capturing collective efficacy, which were self-reported by 2,599 adults in 65 census tracts from the Los Angeles Family and Neighborhood Survey (LAFANS). MLFA identified two latent factors at the individual level and one factor at the neighborhood level. Indicators of collective efficacy performed differently at each level. The ability of MLFA to identify different latent factor structures at each level underscores the utility of this analytic tool to model and identify attributes of contexts relevant to health. Electronic supplementary material The online version of this article (doi:10.1186/s12963-015-0045-1) contains supplementary material, which is available to authorized users.

People vary substantially in their ability to acquire and maintain social ties. Here, we use a combined epidemiological and individual differences approach to understand the childhood roots of adult social cognitive functioning. We assessed exposure to 25 forms of traumatic childhood experiences in over 5000 adults, along with measures of face discrimination, face memory, theory of mind, social motivation, and social support. Retrospectively-reported experiences of parental maltreatment in childhood (particularly physical abuse) were the most broadly and robustly associated with adult variations in theory of mind, social motivation, and social support. Adult variations in face discrimination and face memory, on the other hand, were not significantly associated with exposure to childhood adversity. Our findings indicate domains of social cognition that may be particularly vulnerable to the effects of adverse childhood environments, and suggest mechanisms whereby environmental factors might influence the development of social abilities.

Hair cortisol concentration (HCC) is a promising measure of long-term hypothalamus-pituitary-adrenal (HPA) axis activity. Previous research has suggested an association between HCC and psychological variables, and initial studies of inter-individual variance in HCC have implicated genetic factors. However, whether HCC and psychological variables share genetic risk factors remains unclear. The aims of the present twin study were to: (i) assess the heritability of HCC; (ii) estimate the phenotypic and genetic correlation between HPA axis activity and the psychological variables perceived stress, depressive symptoms, and neuroticism; using formal genetic twin models and molecular genetic methods, i.e. polygenic risk scores (PRS). HCC was measured in 671 adolescents and young adults. These included 115 monozygotic and 183 dizygotic twin-pairs. For 432 subjects PRS scores for plasma cortisol, major depression, and neuroticism were calculated using data from large genome wide association studies. The twin model revealed a heritability for HCC of 72%. No significant phenotypic or genetic correlation was found between HCC and the three psychological variables of interest. PRS did not explain variance in HCC. The present data suggest that HCC is highly heritable. However, the data do not support a strong biological link between HCC and any of the investigated psychological variables.

Background: Psychosocial characteristics have a strong effect on risk of depression, and their direct treatment with behavioral interventions reduces rates of depression. Because new‐onset poststroke depression (NPSD) is frequent, devastating, and often treatment‐resistant, novel preventive efforts are needed. As a first step toward developing behavioral interventions for NPSD, we investigated whether prestroke psychosocial factors influenced rates of NPSD in a manner similar to the general population. Methods and Results: Using the Women's Health Initiative, we analyzed 1424 respondents who were stroke‐free at enrollment and had no self‐reported history of depression from enrollment to their nonfatal ischemic stroke based on initiation of treatment for depression or the Burnam screening instrument for detecting depressive disorders. NPSD was assessed using the same method during the 5‐year poststroke period. Logistic regression provided odds ratios of NPSD controlling for multiple covariates. NPSD occurred in 21.4% (305/1424) of the analytic cohort and varied by stroke severity as measured by the Glasgow scale, ranging from 16.7% of those with good recovery to 31.6% of those severely disabled. Women with total anterior circulation infarction had the highest level (31.4%) of NPSD while those with lacunar infarction had the lowest (16.1%). Prestroke psychosocial measures had different associations with NPSD depending on functional recovery of the individual. Conclusions: There is a difference in the relationship of prestroke psychosocial status and risk of NPSD depending on stroke severity; thus it may be that the same preventive interventions might not work for all stroke patients. One size does not fit all.