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Latent Variables Quantifying Neighborhood Characteristics and Their Associations with Poor Mental Health.

ABSTRACT: Neighborhood characteristics can have profound impacts on resident mental health, but the wide variability in methodologies used across studies makes it difficult to reach a consensus as to the implications of these impacts. The aim of this study was to simplify the assessment of neighborhood influence on mental health. We used a factor analysis approach to reduce the multi-dimensional assessment of a neighborhood using census tracts and demographic data available from the American Community Survey (ACS). Multivariate quantitative characterization of the neighborhood was derived by performing a factor analysis on the 2011-2015 ACS data. The utility of the latent variables was examined by determining the association of these factors with poor mental health measures from the 500 Cities Project 2014-2015 data (2017 release). A five-factor model provided the best fit for the data. Each factor represents a complex multi-dimensional construct. However, based on heuristics and for simplicity we refer to them as (1) Affluence, (2) Singletons in Tract, (3) African Americans in Tract, (4) Seniors in Tract, and (5) Hispanics or Latinos in Tract. African Americans in Tract (with loadings showing larger numbers of people who are black, single moms, and unemployed along with fewer people who are white) and Affluence (with loadings showing higher income, education, and home value) were strongly associated with poor mental health (R2=0.67, R2=0.83). These findings demonstrate the utility of this factor model for future research focused on the relationship between neighborhood characteristics and resident mental health.

SUBMITTER: Forthman KL

PROVIDER: S-EPMC7908478 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Latent Variables Quantifying Neighborhood Characteristics and Their Associations with Poor Mental Health.

Forthman Katherine L KL Colaizzi Janna M JM Yeh Hung-Wen HW Kuplicki Rayus R Paulus Martin P MP

International journal of environmental research and public health 20210129 3

Neighborhood characteristics can have profound impacts on resident mental health, but the wide variability in methodologies used across studies makes it difficult to reach a consensus as to the implications of these impacts. The aim of this study was to simplify the assessment of neighborhood influence on mental health. We used a factor analysis approach to reduce the multi-dimensional assessment of a neighborhood using census tracts and demographic data available from the American Community Sur ...[more]

PMID: 33572876

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Project description:(1) Background: There is a continuing discussion concerning the impact of preterm birth on Maternal-Infant bonding with inconsistent results. The large burden of preterm births calls for research to evaluate the impact of it on material psychological outcome in the early postpartum period. Thus, the aim of this study was to evaluate the relationship between maternal postpartum bonding with maternal mental health, socio-demographical factors, and child's characteristics. (2) Methods: A cross-sectional study design was used. In total, 72 women (a mean age of 31.44 years old) of preterm infants (mean gestational age = 33.54; range 24-36) filled out socio-demographic questionnaires, Postpartum Bonding Questionnaire (PBQ), Edinburgh Postpartum Depression Scale (EPDS), Postpartum Depression Screening Scale (PDSS), Generalized Anxiety Disorder Assessment (GAD-7), and Parental Stress Scale (PSS) 1-3 days post-delivery; (3) Results: The results analyses have shown positive correlations between the overall result of maternal postpartum bonding with stress (p < 0.01), maternal educational level (p < 0.01), maternal age (p < 0.05) and the number of children (p < 0.01). However, there were no significant relationships between other investigated variables. The results of linear regression have revelated the important role of the overall scores in experience of stress among mothers (explaining 49% of the variability). The mediating role of maternal stress on maternal postpartum bonding was not found. That relationship of maternal postpartum bonding and maternal stress was not moderated through socio-demographic variables. (4) Conclusions: In this study mothers of prematurely born children had a good level of Maternal-Infant bonding. Maternal stress was found to be a predictor of maternal postpartum bonding among the tested variables. Surprisingly, the study results did not show significant relationships between maternal postpartum bonding and maternal mental health (depression and anxiety).

Project description:Research about the mental health of children in Francophone West Africa is scarce. This paper examines the relationships between adverse childhood experiences, including exposure to violence and exploitation, and mental health outcomes among children living in ultra-poverty in rural Burkina Faso.This paper utilizes baseline data collected from 360 children ages 10-15 and 360 of their mothers recruited from twelve impoverished villages in the Nord Region of Burkina, located near the Sahel Desert and affected by extreme food insecurity. We used a Latent Class Analysis to identify underlying patterns of maltreatment. Further, the relationships between latent classes and mental health outcomes were tested using mixed effected regression models adjusted for clustering within villages.About 15% of the children in the study scored above the clinical cut-off for depression, 17.8% for posttraumatic stress disorder (PTSD), and 6.4% for low self-esteem. The study identified five distinct sub-groups (or classes) of children based on their exposure to adverse childhood experiences. Children with the highest exposure to violence at home, at work and in the community (Abused and Exploited class) and children not attending school and working for other households, often away from their families (External Laborer class), demonstrated highest symptoms of depression and trauma. Despite living in adverse conditions and working to assist families, the study also identified a class of children who were not exposed to any violence at home or at work (Healthy and Non-abused class). Children in this class demonstrated significantly higher self-esteem (b = 0.92, SE = 0.45, p<0.05) and lower symptoms of trauma (b = -3.90, SE = 1.52, p<0.05).This study offers insight into the psychological well-being of children in the context of ultra-poverty in Burkina Faso and associated context-specific adverse childhood experiences. Identifying specific sub-groups of children with increased exposure to life stressors has implications for program developers. Study findings indicate a further need to explore the mental health consequences of traumatic experiences within the context of ultra-poverty and to develop integrated economic and psychosocial interventions that prevent or mitigate childhood adversities linked with the family-level poverty and violence in the family.

Project description:BackgroundNursing home residents commonly experience poor sleep conditions. However, few studies have explored the potential sleep patterns among nursing home residents. This study aimed to identify the sleep patterns in nursing home residents, compare residents' characteristics across sleep patterns, and examine the relationships between sleep patterns and residents' mental health (i.e., depressive and anxiety symptoms).MethodsThis cross-sectional study was conducted in 27 nursing homes in Jinan, China, from March to June 2018. In total, 353 participants were recruited via convenience sampling, and of which, 326 completed the survey. A latent profile analysis was performed to identify sleep patterns based on the seven dimensions of the Pittsburgh Sleep Quality Index. Bivariate analyses were conducted to compare residents' characteristics among the sleep patterns. Mixed-effects logistic regression analyses were adopted to investigate the relationships between sleep patterns and residents' mental health.ResultsThree sleep patterns were identified, including 'good sleepers', 'poor sleepers without hypnotic use', and 'poor sleepers with hypnotic use'. Residents' gender, education, pain, instrumental activities of daily living, and number of chronic conditions were significantly differentiated across the sleep patterns. Compared with 'good sleepers', 'poor sleepers without hypnotic use' were significantly associated with more depressive symptoms (OR = 3.73, 95% CI = 2.09, 6.65, p < 0.001), but not with anxiety symptoms (OR = 2.04, 95% CI = 0.97, 4.29, p = 0.062); whereas 'poor sleepers with hypnotic use' had significantly more depressive (OR = 5.24, 95% CI = 2.54, 10.79, p < 0.001) and anxiety symptoms (OR = 5.02, 95% CI = 2.13, 11.83, p < 0.001).ConclusionsThis study reveals three distinct sleep patterns in nursing home residents and their significant associations with residents' mental health. These findings can inform future research to develop appropriate and tailored intervention strategies for improving sleep and promoting mental health for nursing home residents.

Dataset Information

Latent Variables Quantifying Neighborhood Characteristics and Their Associations with Poor Mental Health.

Publications

Latent Variables Quantifying Neighborhood Characteristics and Their Associations with Poor Mental Health.

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