Individual-level exposure to disaster, neighborhood environmental characteristics, and their independent and combined associations with depressive symptoms in women

Neighborhood-level economic characteristics and depression and PTSD symptoms among Houstonians who have experienced Hurricane Harvey and COVID-19

Little is known about how neighborhood economic characteristics relate to risk of depression and Posttraumatic Stress Disorder (PTSD) in the context of multiple disasters. We sampled 88 super neighborhoods in Houston, Texas and surveyed 872 residents who were living in Houston during Hurricane Harvey and COVID-19 and lived in the same residence since Hurricane Harvey, about their demographics and symptoms of depression and PTSD. Using data from the American Community Survey, we estimated neighborhood-level unemployment, median income, and income inequality (i.e., Gini coefficient). We investigated whether these underlying neighborhood socioeconomic factors were associated with the mental health consequences of mass traumatic events. We examined associations between neighborhood-level constructs and individual-level depression and PTSD, using multilevel linear models. Partially adjusted multilevel models showed that lower neighborhood median income was associated with higher symptom scores of PTSD, while greater neighborhood income inequality was associated with higher symptom scores of depression and PTSD. However, fully adjusted models showed that these associations are better accounted for by event-specific stressors and traumas. These findings suggest that in the context of multiple large scale traumatic events, neighborhood socioeconomic context may structure individual-level exposure to stressful and traumatic events.

Examining the effects of cumulative environmental stressors on Gulf Coast child and adolescent health

This study examines how community-level cumulative environmental stress affects child and adolescent emotional distress and chronic health conditions both directly and indirectly through stressors at the household, family, and individual levels. Data comes from the Women and their Children's Health (WaTCH) Study, which sought to understand the health implications of exposure to the 2010 Deepwater Horizon oil spill (DHOS) among a cohort of 596 mothers with children ages 10 to 17 in southeastern Louisiana. Community-level environmental stress was measured using a newly developed geospatial index. Household-level stressors included previous hurricane impacts, impacts of DHOS, degree of financial difficulty, and degree of housing physical decay. Family stressors included maternal depression, self-rated physical health, and degree of parenting stress. Child stress was based on perceived stress; child mental health was based on serious emotional disturbance; and child physical health was based on diagnosis of chronic illness. Structural equation modeling used weighted least squares means and variance and theta parameterization. Results showed a significant negative direct path between community-level cumulative environmental stress and child/adolescent serious emotional disturbance and chronic illness. However, the indirect relationship through household, family, and individual-level stressors was significant and positive for both child/adolescent serious emotional disturbance and chronic illness. These findings point to the centrality of the household and family in determining child and adolescent physical and mental health outcomes in communities exposed to frequent disasters and ongoing environmental stressors.

An Assessment of Environmental Health Measures in the Deepwater Horizon Research Consortia

Research consortia play a key role in our understanding of how environmental exposures influence health and wellbeing, especially in the case of catastrophic events such as the Deepwater Horizon oil spill. A common challenge that prevents the optimal use of these data is the difficulty of harmonizing data regarding the environmental exposures and health effects across the studies within and among consortia. A review of the measures used by members of the Deepwater Horizon Research Consortia highlights the challenges associated with balancing timely implementation of a study to support disaster relief with optimizing the long-term value of the data. The inclusion of common, standard measures at the study design phase and a priori discussions regarding harmonization of study-specific measures among consortia members are key to overcoming this challenge. As more resources become available to support the use of standard measures, researchers now have the tools needed to rapidly coordinate their studies without compromising research focus or timely completion of the original study goals.

Potential Impact of 2020 US Decennial Census Data Collection on Disaster Preparedness and Population Mental Health

Increasing in frequency and impact in the United States and worldwide, disasters can lead to serious mental health consequences. Although US census data are essential for disaster preparedness and the identification of community-level risk factors for adverse postdisaster mental health outcomes, the US Census Bureau faces many challenges as we approach 2020 Decennial Census data collection. Despite the utility of the information provided by the Census and American Community Survey (ACS), the 2020 US Census and subsequent ACS data face threats to validity. As a result, public health funding could be misallocated, and disaster preparedness and response efforts misinformed; this can also contribute to the worsening of mental health inequities, particularly in the context of disaster. Undercutting the Census and the ACS, rich data sources that allow representation of all people in the United States, is a step backward in our effort to mitigate the population mental health consequences of disasters.

PTSD symptom profiles among Louisiana women affected by the 2010 Deepwater Horizon Oil Spill: A latent profile analysis

BACKGROUND

Few prior studies have investigated the latent class structure of PTSD using DSM-5 symptoms.

METHODS

To describe latent PTSD profiles among women who resided in Deepwater Horizon Oil Spill (DHOS)-affected coastal Louisiana communities, we used data from women enrolled in The Women and Their Children's Health (WaTCH) Study. Latent profile analysis was performed on the 20-item PTSD Checklist for DSM-5 (PCL-5) and model fit statistics for 2-class through 6-class solutions were compared. The pseudo-class draws method was employed on the best class solution to compare key covariates (including demographics, mental health indicators, DHOS exposure indicators, and trauma exposures) across classes.

RESULTS

Among 1997 women (mean age 46.63 ± 12.14 years, 56.8% white, mean trauma categories 6.09 ± 2.98, 9.55% previously diagnosed with PTSD), model fit statistics supported a five-class solution: low symptoms (mean PCL-5 = 4.10), moderate without mood alterations (mean = 19.73), moderate with mood alterations (mean = 34.24), severe without risk-taking (mean = 55.75), and severe with risk-taking (mean = 53.80). Women in the low-symptom class were significantly more likely to be white, have finished high school, have an income of at least $40,001 per year, be married or living with a partner, and endorse fewer trauma categories than women in the four symptomatic classes. Women with moderate to severe symptoms often had co-morbid depressive symptoms and no prior PTSD diagnosis.

LIMITATIONS

This study was limited by use of self-reported data and one-time assessment of PTSD symptoms.

DISCUSSION

Five distinct latent profiles of DSM-5 PTSD symptoms consisted of notably different individuals. Most affected women did not report prior PTSD diagnosis. Future research and practice identifying and addressing barriers to care for trauma-affected women in these communities is warranted.

Broken (windows) theory: A meta-analysis of the evidence for the pathways from neighborhood disorder to resident health outcomes and behaviors

The criminological "broken windows" theory (BWT) has inspired public health researchers to test the impact of neighborhood disorder on an array of resident health behaviors and outcomes. This paper identifies and meta-analyzes the evidence for three mechanisms (pathways) by which neighborhood disorder is argued to impact health, accounting for methodological inconsistencies across studies. A search identified 198 studies (152 with sufficient data for meta-analysis) testing any of the three pathways or downstream, general health outcomes. The meta-analysis found that perceived disorder was consistently associated with mental health outcomes, as well as substance abuse, and measures of overall health. This supported the psychosocial model of disadvantage, in which stressful contexts impact mental health and related sequelae. There was no consistent evidence for disorder's impact on physical health or risky behavior. Further examination revealed that support for BWT-related hypotheses has been overstated owing to data censoring and the failure to consistently include critical covariates, like socioeconomic status and collective efficacy. Even where there is evidence that BWT impacts outcomes, it is driven by studies that measured disorder as the perceptions of the focal individual, potentially conflating pessimism about the neighborhood with mental health.

Depression among Black Youth; Interaction of Class and Place

Although high socioeconomic status (SES) is traditionally conceptualized as a health protective factor, recent literature has documented positive associations between SES (e.g., income) and depression among Blacks, including Black youth. To extend the results of this recent literature, the current study used the Family and Community Health Study (FACHS) data to examine the multiplicative effects of gender, place, and SES on average depressive symptoms of Black youth over a long period of time. FACHS, 1997⁻2017, followed 889 Black children aged 10⁻12 years old for up to 18 years. Depressive symptoms were measured in seven waves. The main predictors of interest were two SES indicators, parent education and family income measured at baseline (1997). Main outcome of interest was average depressive symptoms over the 18 year follow up period. Place of residence and gender were the focal moderators. Linear regression models were used for data analysis. In the pooled sample, living in a predominantly White area was associated with higher average depressive symptoms over time, however, this association was fully explained by higher perceived racial discrimination in the predominantly White areas. We found an interaction between income and place of residence on average depressive symptoms, suggesting that higher income is associated with more depressive symptoms in predominantly White compared to predominantly Black areas. Place did not interact with parent education on average depressive symptoms. Gender also did not interact with education or income on depressive symptoms. Findings suggest that place and SES may interact on depressive symptoms of Black youth, with high income becoming a risk factor for depressive symptoms in predominantly White areas. How SES indicators, such as income, protect or become a risk factor depend on other contextual factors, such as place of residence. There is a need to reduce discrimination experienced by Blacks, especially in predominantly White areas. Meanwhile, Black youth who live in predominantly White areas may require additional help that enhances their coping.