Exploring a Potential Interaction Between the Effect of Specific Maternal Smoking Patterns and Comorbid Antenatal Depression in Causing Postpartum Depression.

Purpose: To explore a potential interaction between the effect of specific maternal smoking patterns and the presence of antenatal depression, as independent exposures, in causing postpartum depression (PPD). Methods: This case-control study of participants with singleton term births (N = 51220) was based on data from the 2017-2018 Pregnancy Risk Assessment Monitoring System. Multivariable log-binomial regression models examined the main effects of smoking patterns and self-reported symptoms of antenatal depression on the risk of PPD on the adjusted risk ratio (aRR) scale and tested a two-way interaction adjusting for covariates selected in a directed acyclic graph (DAG). The interaction effects were measured on the additive scale using relative excess risk due to interaction (RERI), the attributable proportion of interaction (AP), and the synergy index (SI). Causal effects were defined in a counterfactual framework. The E-value quantified the potential impact of unobserved/unknown covariates, conditional on observed covariates. Results: Among 6841 women in the sample who self-reported PPD, 35.7% also reported symptoms of antenatal depression. Out of 3921 (7.7%) women who reported smoking during pregnancy, 32.6% smoked at high intensity (≥10 cigarettes/day) in all three trimesters and 36.6% had symptoms of antenatal depression. The main effect of PPD was the strongest for women who smoked at high intensity throughout pregnancy (aRR 1.65; 95% CI: 1.63, 1.68). A synergistic interaction was detected, and the effect of all maternal smoking patterns was augmented, particularly in late pregnancy for Increasers and Reducers. Conclusion: Strong associations and interaction effects between maternal smoking patterns and co-occurring antenatal depression support smoking prevention and cessation interventions during pregnancy to lower the likelihood of PPD.

Examining the association of rurality with opioid-related morbidity and mortality in Georgia: A geospatial analysis.

INTRODUCTION: The US opioid epidemic continues to escalate, with overdose deaths being the most-used metric to quantify its burden. There is significant geographic variation in opioid-related outcomes. Rural areas experience unique challenges, yet many studies oversimplify rurality characterizations. Contextual factors, such as area deprivation, are also important to consider when understanding a community's need for treatment services and prevention programming. This study aims to provide a geospatial snapshot of the opioid epidemic in Georgia using several metrics of opioid-related morbidity and mortality and explore differences by rurality across counties. METHODS: This was a spatial ecologic study. Negative binominal regression was used to model the relationship of county rurality with four opioid-related outcomes - overdose mortality, emergency department visits, inpatient hospitalizations, and overdose reversals - adjusting for county-level sex, racial/ethnic, and age distributions. Area Deprivation Index was also included. RESULTS: There was significant geographic variation across the state for all four opioid-related outcomes. Counts remained highest among the metro areas. For rates, counties in the top quartile of rates varied by outcome and were often rural areas. In the final models, rurality designation was largely unrelated to opioid outcomes, with the exception of medium metro areas (inversely related to hospitalizations and overdose reversals) and non-core areas (inversely related to hospitalizations), as compared to large central metro areas. Higher deprivation was significantly related to increased ED visits and hospitalizations, but not overdose mortality and reversals. CONCLUSIONS: When quantifying the burden of the opioid epidemic in a community, it is essential to consider multiple outcomes of morbidity and mortality. Understanding what outcomes are problematic for specific communities, in combination with their demographic and socioeconomic context, can provide insight into gaps in the treatment continuum and potential areas for intervention. Additionally, compared to demographic and socioeconomic factors, rurality may no longer be a salient predictor of the severity of the opioid epidemic in an area.

Childhood Factors Associated With Unnatural Death Through Midadulthood.

Importance: Life expectancy is decreasing in the US. Without national efforts to address factors that support policies and programs directed at children living in areas of concentrated poverty, life expectancy will likely continue to decline while costs and suffering associated with unnatural deaths will increase. Objective: To identify which childhood factors are associated with death from unnatural causes through midadulthood. Design, Setting, and Participants: For this cohort study, longitudinal data on childhood characteristics came from a group-randomized intervention trial implemented in Baltimore City Public Schools, Baltimore, Maryland (baseline 1985-1986; all students entering first grade were selected to participate at age 6 years). Participants were followed up to midadulthood with a National Death Index search through December 31, 2020. Data analysis was performed from February to May 2023. Exposures: Exposures included individual factors (ie, sociodemographic characteristics, teacher-reported aggressive behavior, self-reported depression, anxiety, early alcohol and cannabis use, and assaultive violence exposure), family and peer factors (ie, household structure and education level, deviant peer affiliation, and parental monitoring), and neighborhood factors (ie, rates of neighborhood assault and public assistance). Main Outcomes and Measures: The main outcome was unnatural death, defined as death due to unintentional injury, suicide, and homicide. A National Death Index search ascertained participants who died by age 41 to 42 years and cause of death. Multivariable Cox proportional hazards models were used to identify whether the exposures were independently associated with future mortality by unnatural causes. Results: The initial trial included 2311 children, and longitudinal data were available for 2180 participants (median [IQR] age in first grade, 6.3 [6.0-6.5] years; 1090 female [50.0%]; 1461 Black [67.0%]; 1168 received free or reduced lunch in first grade [53.6%]). A total of 111 male participants (10.2%) and 29 female participants (2.7%) died; among those who died, 96 male participants (86.5%) and 14 female participants (48.3%) died of unnatural causes. Two factors remained significantly associated with mortality from unnatural causes: female sex was associated with reduced risk (hazard ratio, 0.13; 95% CI, 0.08-0.22), and neighborhood public assistance was associated with increased risk (hazard ratio, 1.89; 95% CI, 1.09-3.30). Conclusions and Relevance: In this urban population-based cohort study, no modifiable risk factors of mortality at the level of the individual (eg, depression or anxiety and substance use) or the family (eg, household education level) were identified. However, the degree of neighborhood poverty in early childhood was significantly associated with death by unnatural causes in early adulthood, suggesting that economic policies are needed to advance health equity in relation to premature mortality.

Trauma and Incarceration: A Latent Class Analysis of Lifetime Trauma Exposures for Individuals in Prison.

This paper aims to contribute to the knowledge base about the lives of individuals who experience incarceration in the U.S. in order to advance post-release intervention services. Research has shown that among the millions of Americans who cycle through prisons and jails each year, the majority are poor, in poor health, living in contexts of chronic violence, often with mental illness, and more than half are people of color. Of particular concern for this population are high rates of trauma exposure and PTSD, though the research in this area is underdeveloped, particularly for men. Using survey data gathered during a large (n = 1,516, 90% male) multi-state randomized control trial of a reentry intervention, this study used latent class analysis (LCA) to explore types and timing of trauma exposures across the life course. LCA has been found to be an effective statistical tool in intervention research for identifying high-risk groups and for informing the tailoring of interventions. This study found three latent classes: 1) Lifetime Interpersonal Polyvictimization, 2) Lifetime Environmental Exposures, and 3) Low Exposure. About one third of the sample fell within each class. Study findings indicate that not only should trauma-informed and trauma-specific interventions be the norm in reentry services, including for men, but that these interventions should target both individual and environmental factors.

A Community-Engaged Approach to Understanding Suicide in a Small Rural County in Georgia: A Two-Phase Content Analysis of Individual and Focus Group Interviews.

Suicide is a significant public health problem, with disproportionate rates in rural areas. Rural communities face substantial structural and cultural barriers to suicide prevention. This study aimed to gain a deeper understanding of the need for suicide prevention and gauge the appropriateness of prevention efforts in the context of a rural Georgia county by leveraging existing community resources and knowledge. Twenty one-on-one, semi-structured interviews and two focus groups were conducted, with participants recruited via purposive snowball sampling. Data analysis included qualitative deductive and inductive content analysis from individual interviews and focus groups with community stakeholders. The findings highlight how rural contexts exacerbate drivers of death by suicide and how the substantial loss of community members to suicide contributes to the ongoing crisis and reduces available support. Access to mental health care often depended on a connection to an established public system such as schools, a military base, or Veterans Administration. There were perceived gaps in crisis and post-crisis services, with participants actively trying to address these gaps and build community support through coalition building. This study contributes knowledge to contextual drivers of suicide in rural areas beyond individual-level risk factors. Community-engaged suicide prevention research in rural areas is promising, but there is a need to develop interventions to best support coalition building and capacity development.

The relationship between neighborhood typologies and self-rated health in Maryland: A latent class analysis.

Despite widespread evidence that neighborhood conditions impact health, few studies apply theory to clarify the physical and social factors in communities that drive health outcomes. Latent class analysis (LCA) addresses such gaps by identifying distinct neighborhood typologies and the joint influence that neighborhood-level factors play in health promotion. In the current study, we conducted a theory-driven investigation to describe Maryland neighborhood typologies and examined differences in area-level self-rated poor mental and physical health across typologies. We conducted an LCA of Maryland census tracts (n = 1384) using 21 indicators of physical and social characteristics. We estimated differences in tract-level self-rated physical and mental health across neighborhood typologies using global Wald tests and pairwise comparisons. Five neighborhood classes emerged: Suburban Resourced (n = 410, 29.6%), Rural Resourced (n = 313, 22.6%), Urban Underserved (n = 283, 20.4%), Urban Transient (n = 226, 16.3%), Rural Health Shortage (n = 152, 11.0%). Prevalence of self-rated poor physical and mental health varied significantly (p < 0.0001) by neighborhood typology, with the Suburban Resourced neighborhood class demonstrating the lowest prevalence of poor health and the Urban Underserved neighborhoods demonstrating the poorest health. Our results highlight the complexity of defining "healthy" neighborhoods and areas of focus to mitigate community-level health disparities to achieve health equity.

Immunologic profiling in schizophrenia and rheumatoid arthritis.

The negative relationship between schizophrenia (SCZ) and rheumatoid arthritis (RA) has been observed for 85 years, but the mechanisms driving this association are unknown. This study analyzed differences in profiles of cytokines (IL-1ß, IL-Ra, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, IFNγ, TNFα), selected genes (HLA-DRB1, IL1RN, HP2), and antibodies related to gluten sensitivity (AGA-IgG, AGA-IgA), celiac disease (tTG), and systemic autoimmunity (ANA, anti-CCP, RF) in 40 subjects with SCZ, 40 with RA, and 40 healthy controls (HC). HLA-DRB1*04:01 alleles were enriched in persons with SCZ and RA compared with HC, and the HP2/HP2 genotype was 2-fold more prevalent in AGA/tTG-positive versus negative SCZ patients. Patients with SCZ demonstrated 52.5% positivity for any of the antibodies tested, compared to 90% of RA patients and 30% of HC. Cluster analysis of the cytokines revealed three clusters: one associated with SCZ marked by high levels of IL-1Ra, one associated with HC, and one associated with both SCZ and RA marked by elevated levels of IFNγ, TNFα, and IL-6. These analyses suggest that stratification of SCZ patients by cytokine profile may identify unique SCZ subgroups and enable the use of currently available cytokine-targeted treatment strategies.

Geochemistry and Multiomics Data Differentiate Streams in Pennsylvania Based on Unconventional Oil and Gas Activity.

Unconventional oil and gas (UOG) extraction is increasing exponentially around the world, as new technological advances have provided cost-effective methods to extract hard-to-reach hydrocarbons. While UOG has increased the energy output of some countries, past research indicates potential impacts in nearby stream ecosystems as measured by geochemical and microbial markers. Here, we utilized a robust data set that combines 16S rRNA gene amplicon sequencing (DNA), metatranscriptomics (RNA), geochemistry, and trace element analyses to establish the impact of UOG activity in 21 sites in northern Pennsylvania. These data were also used to design predictive machine learning models to determine the UOG impact on streams. We identified multiple biomarkers of UOG activity and contributors of antimicrobial resistance within the order Burkholderiales. Furthermore, we identified expressed antimicrobial resistance genes, land coverage, geochemistry, and specific microbes as strong predictors of UOG status. Of the predictive models constructed (n = 30), 15 had accuracies higher than expected by chance and area under the curve values above 0.70. The supervised random forest models with the highest accuracy were constructed with 16S rRNA gene profiles, metatranscriptomics active microbial composition, metatranscriptomics active antimicrobial resistance genes, land coverage, and geochemistry (n = 23). The models identified the most important features within those data sets for classifying UOG status. These findings identified specific shifts in gene presence and expression, as well as geochemical measures, that can be used to build robust models to identify impacts of UOG development. IMPORTANCE The environmental implications of unconventional oil and gas extraction are only recently starting to be systematically recorded. Our research shows the utility of microbial communities paired with geochemical markers to build strong predictive random forest models of unconventional oil and gas activity and the identification of key biomarkers. Microbial communities, their transcribed genes, and key biomarkers can be used as sentinels of environmental changes. Slight changes in microbial function and composition can be detected before chemical markers of contamination. Potential contamination, specifically from biocides, is especially concerning due to its potential to promote antibiotic resistance in the environment. Additionally, as microbial communities facilitate the bulk of nutrient cycling in the environment, small changes may have long-term repercussions. Supervised random forest models can be used to identify changes in those communities, greatly enhance our understanding of what such impacts entail, and inform environmental management decisions.

The differential relationship of common health comorbidities with acculturative experiences in United States Latinxs.

•A novel conceptualization of acculturation and related experiences is related to comorbidity.•Different patterns emerge in the relationship between acculturative experiences and health.•Toxic stress and social support may play differential roles in the risk for health comorbidities.

The Relationship Between Latinxs' Acculturative Experiences and Mental and Behavioral Disorder in the National Latino and Asian American Study.

Mental and behavioral disorders are among the leading contributors to disability among US-residing Latinxs. When treated as a homogeneous group, important disparities in the prevalence of such disorders among Latinx subgroups (e.g., by ethnic heritage) are obscured. However, Latinxs may also be characterized by their acculturative experiences while living in the USA, such as discrimination, neighborhood context and family conflict. Latent Profile Analysis with distal outcomes was used to estimate differences in psychiatric disorder prevalence across acculturative subgroups. Data from 2,541 Latinx participants (age 18 +) in the National Latino and Asian American Study (NLAAS) were used to estimate differences in the proportion of three categories of DSM-IV disorder: depressive, anxiety and substance use by four latent subgroups of Latinxs based on their acculturative experiences. Latinxs reporting more positive acculturative experiences had the lowest prevalence of all three disorders (14.8%, 13.6% and 7.1%, respectively). Those whose lives were characterized by high levels of family conflict and discrimination combined with low levels of social cohesion and neighborhood safety had the highest disorder prevalence (34.0%, 26.6% and 22.5%; all p < 0.01 compared to positive experiences subgroup). Latinxs with moderate levels of discrimination and conflict, along with those with high conflict and cohesion, were better off as compared to those with high negative experiences and low cohesion. These latent subgroups of Latinxs according to their acculturative experiences hold important implications for identifying high-risk groups for developing a psychiatric disorder. Findings also point to the protective role of family and neighborhood cohesion when facing high levels of adversity, which may inform prevention and intervention efforts.

Naloxone availability in independent community pharmacies in Georgia, 2019.

BACKGROUND: Increasing the availability of naloxone among people who use opioids, and friends and family of past and present people who use opioids is a vitally important mission to reduce the occurrence of opioid-related overdose deaths. The purpose of this study was to determine the availability of naloxone in independent community pharmacies in Georgia. Secondary objectives include determining pharmacists' knowledge regarding the standing order and ability to counsel regarding naloxone. METHODS: A cross-sectional study using a secret shopper approach with phone contact was conducted over a period of 10 months. The study was population based and was conducted at all independent pharmacies in the state of Georgia. All independent community pharmacies in the state of Georgia were contacted and asked the naloxone questions with a 96% response rate (n = 520). RESULTS: Five hundred fifty-eight independent community pharmacies were called, with a 96% response rate (n = 520 pharmacies). Two hundred-twenty pharmacies reported having naloxone in stock. Of the 335 pharmacists asked, 174 (51.9%) incorrectly said that a prescription was required. The mean (SD) cash price was $148.02 (27.40), with a range of $0 to $300. Of 237 pharmacists asked who had naloxone in stock or who stated they could get naloxone in stock, 212 stated that they could demonstrate how to use it, 8 stated they could not, and 17 said that they possibly could or were unsure how to use it. CONCLUSIONS: This study provided insight into the limited availability of naloxone at independent community pharmacies in Georgia after the standing order was issued. The majority of pharmacists at independent pharmacies in Georgia were not using the publicly available state naloxone standing order. Additionally, the low availability of naloxone and its high cost for uninsured individuals are significant structural barriers for reducing opioid-related mortality.

Systematic Review of Psychosocial Smoking Cessation Interventions for People with Serious Mental Illness.

OBJECTIVE: Tobacco smoking is a major driver of premature mortality in people with serious mental illness (SMI; e.g., schizophrenia, bipolar disorder). This systematic literature review described randomized control trials of psychosocial smoking cessation interventions for people with SMI, rated their methodological rigor, evaluated the inclusion of racial/ethnic and sexual/gender minorities, and examined smoking cessation outcomes. Methods: Eligible studies included peer-reviewed articles published between 2009 and 2020 that examined psychosocial smoking cessation interventions in people with SMI. We used the Preferred Reporting Items for Systematic Review and Meta-analysis guidelines to conduct our review and the Methodological Quality Rating Scale to evaluate methodological rigor. Results: Eighteen studies were included. Ten were categorized as high methodological rigor given their study characteristics (e.g., longer follow-up) and eight as lower methodological rigor based on their characteristics (e.g., not intent-to-treat). Racial/ethnic and sexual/gender minorities were under-represented in these studies. A range of psychosocial interventions were examined including motivational enhancements, smoking cessation education, cognitive behavioral strategies, and contingency management. Most studies also provided smoking cessation medications (e.g., NRT, bupropion), although provision was not always uniform across treatment conditions. Three studies found the intervention condition achieved significantly higher abstinence from smoking compared to the comparison group. Seven studies found the intervention condition achieved significantly higher reductions in smoking compared to the comparison group. Conclusions: Studies finding significant differences between the intervention and comparison groups shared common evidenced-based components, including providing smoking cessation medications (e.g., NRT, bupropion), motivational enhancement techniques, and cessation education and skills training, but differed in intensity (e.g., number and frequency of sessions), duration, and modality (e.g., group, individual, technology). Methodological limitations and a small number of studies finding significant between-group differences prevent the identification of the most effective psychosocial smoking cessation interventions. Clinical trial designs (e.g., SMART, factorial) that control for the provision of psychosocial medications and allow for the identification of optimal psychosocial treatments are needed. Future studies should also ensure greater inclusion of racial/ethnic and sexual/gender minorities and should be culturally/linguistically adapted to improve treatment engagement and study outcomes.

Hotline Use in the United States: Results from the Collaborative Psychiatric Epidemiology Surveys.

Crisis hotlines are a fixture in providing mental health services to individuals experiencing mental and behavioral problems in the United States (U.S.). Despite this, and the growing need for easily-accessible, anonymous, and free services amidst the suicide and opioid crises, there is no study reporting U.S. national prevalence and correlates of hotline use. Data on n = 18,909 participants from the Collaborative Psychiatric Epidemiology Surveys (CPES), a group of three nationally-representative, population-based studies, were used to estimate the prevalence of lifetime and past 12-month hotline use. A series of logistic regression models examined sociodemographic, clinical history and service use correlates of hotline use. Lifetime and past 12-month hotline use was estimated at 2.5% and 0.5%, respectively. Being female, having a mental or behavioral disorder, experiencing suicidality, or interacting with other formal and informal sectors of the mental health service system were significant correlates of use. This study provides the first national estimates of crisis hotline usage in the U.S. Hotlines are more likely to be used by certain sociodemographic subgroups, but these differences may be due to differing psychiatric history and service use patterns. Efforts should be made to ensure that crisis hotlines are being utilized by other marginalized populations at high risk of suicide or overdose amidst the current public health crises in the U.S., such as racial/ethnic minorities or youth. To evaluate the role that crisis hotlines play in the mental health service system, national surveys should aim to monitor trends and correlates over time.

Refining acculturation measures for health research: Latina/o heterogeneity in the National Latino and Asian American Study.

OBJECTIVES: This study factor analyzes six scales relating to acculturation and related experiences among a nationally representative sample of United States-residing Latina/os (n = 2,541) from the National Latino and Asian American Study (NLAAS), using measurement invariance (MI) testing to explore differences in latent constructs by Latina/o subgroup. METHODS: Factor Analysis (FA) within an Exploratory Structural Equation Modeling framework was used to analyze the factor structure of six scales measuring acculturation and related experiences (i.e., acculturation [language use and preference], enculturation [ethnic identity], discrimination, neighborhood context, and family environment). We tested for MI by two important Latina/o subgroups: ethnic heritage and generational status. RESULTS: The underlying latent factors resulting from FA strongly aligned with the NLAAS subscales. No scale achieved full MI, yet the degree to which MI held varied greatly by scale and by subgroup. CONCLUSIONS: Findings show that Latina/os are heterogeneous, but that this often depends on the construct and subgrouping of interest. Future research should use these scales in a latent framework, accounting for the lack of MI, to ensure that the underlying acculturative constructs of interest are validly measured when investigating their association with mental health outcomes in this population.

Straw in Clay Bricks and Plasters-Can We Use Its Molecular Decay for Dating Purposes?

Dating of clay bricks (adobe) and plasters is a relevant topic not only for building historians in the Pannonian region. Especially in vernacular architecture in this region, clay with straw amendments is a dominant construction material. The paper presents the potential of the molecular decay of these amendments to establish prediction tools for age based on infrared spectroscopic measurements. Preliminary results revealed spectral differences between the different plant parts, especially culms, nodes, and ear spindles. Based on these results, a first prediction model is presented including 14 historic samples. The coefficient of determination for the validation reached 62.2%, the (RMSE) root mean squared error amounted to 93 years. Taking the limited sample amount and the high material heterogeneity into account, this result can be seen as a promising output. Accordingly, sample size should be increased to a minimum of 100 objects and separate models for the different plant parts should be established.

Ideal Cardiovascular Health in Racially and Ethnically Diverse People with Serious Mental Illness.

Cardiovascular disease is a primary contributor to premature death among people with serious mental illness (SMI). This study used baseline data (N=314) from an effectiveness trial testing a healthy lifestyle intervention for racial/ethnically diverse participants with overweight/obesity and SMI living in supportive housing. We examined the prevalence and correlates of a modified version of the American Heart Association (AHA) metric of ideal cardiovascular health (ICVH). Five AHA ICVH metrics (smoking, body mass index, diet, physical activity, and blood pressure) were used to create a composite ICVH score. The mean ICVH score was 3.15 (range 0-8). Multivariate analysis indicated that higher ICVH scores were associated with lifetime cancer diagnosis and better cardiorespiratory fitness. Lower scores were associated with female gender, racial/ethnic minority status, and antipsychotic use, suggesting that these subgroups of people with SMI may benefit from targeted screening and interventions to improve their cardiovascular health.

Engagement With Crisis Text Line Among Subgroups of Users Who Reported Suicidality.

OBJECTIVE: Despite the interest in technology-enhanced preventive interventions for suicidality, there is minimal peer-reviewed research on conversations of text message hotlines. In this large-scale study, the authors explored distinct classes of users of the Crisis Text Line who reported suicidality. Classes were based on texters' presenting psychosocial issues and were explored across frequency of hotline use and conversation number. METHODS: Data included 153,514 conversations from 122,909 individuals collected by the Crisis Text Line (2013-2017). Analyses were restricted to conversations from users who mentioned current or previous suicidality and excluded texters who discussed a third party. The authors used latent class analysis to identify distinct classes of texters on the basis of crisis counselor-assigned issue tags and across subgroups reflecting whether the conversation was the first or last contact with the hotline and frequency of use (one-time, two-time, or ≥3-time texters). RESULTS: Three classes emerged in all subsamples. The largest class, "lower distress," had the lowest prevalence of all issues. The second largest class, "anxious distress," had the highest prevalence of anxiety or stress and elevated depression. The smallest class, "relational distress," had the highest prevalence of depression and self-harm and higher probability of endorsing relational indicators. CONCLUSIONS: Psychological and relational issues mostly distinguished the three classes. Despite differing frequency of hotline usage, most texters who reported suicidal ideation and behaviors endorsed similar issues, and these issues did not seem to vary across conversations. Yet there appeared to be distinct subgroups of texters with different presenting issues, which may inform how crisis counselors tailor strategies for both low- and high-volume texters.

Heterogeneity of Latina/os' acculturative experiences in the National Latino and Asian American Study: a latent profile analysis.

PURPOSE: This study characterized unobserved subgroups of acculturative experiences among a nationally representative sample of U.S.-residing Latina/os (n = 2541) from the National Latino and Asian American Study. METHODS: Latent profile analysis was used to characterize the sample by acculturative experiences using nine-factor score indicators regarding discrimination, neighborhood context, family environment, acculturation (language use and preference), and enculturation (ethnic identity). Predictors of profile membership are also examined, including sociodemographics, Latina/o heritage (i.e., ethnic group), generational status, and two acculturative stress domains (legal and interpersonal). RESULTS: Four Latina/o subgroups were identified based on acculturative experiences. Profiles were differentiated by family context, neighborhood context, and discrimination: (1) positive experiences (n = 1,743, 69%), (2) cohesive conflict (n = 424, 17%), (3) marginalized conflict (n = 237, 9%), and (4) marginalized (n = 137, 5%). Generational status, heritage, and marital status were the salient predictors of profile membership. Among the foreign-born sample (n = 1617), legal acculturative stress also predicted profile membership. CONCLUSIONS: Latina/os have heterogeneous experiences living in the United States. Discrimination, family context, and neighborhood environment are more related to varying experiences as opposed to traditional measures of acculturation and enculturation. Future research should characterize Latina/o heterogeneity using these experiences rather than strictly by observed demographics, such as heritage or generational status.

Enduring mental health in the Baltimore epidemiologic catchment area follow-up study.

PURPOSE: To estimate the prevalence of enduring mental health (EMH) and examine important correlates of EMH 23 years later in the Baltimore Epidemiologic Catchment Area Follow-Up study. METHODS: We estimated the prevalence of EMH among 964 adults with diagnostic data at all four study waves (1981-2004). Those with EMH were compared to those with any mental or behavioral disorder by demographic, psychosocial, and health characteristics. We used forward selection models to identify the most important predictors of EMH. RESULTS: Twenty-six percent of participants met criteria for enduring mental health across the four waves. Neuroticism, GHQ-20 score, childhood conduct problems, female sex, maternal depression, and poor self-rated health were negatively associated with EMH. CONCLUSIONS: We identified several malleable factors associated with a decreased likelihood of enduring mental health. Interventions that target high neuroticism, childhood conduct problems, or maternal depression may increase the likelihood that children achieve EMH later in life. Identifying and treating other factors such as poor self-reported health and greater psychological distress may also keep sub-clinical symptoms from developing into a full mental or behavioral disorder.

Bacterial Community Dynamics in Dichloromethane-Contaminated Groundwater Undergoing Natural Attenuation.

The uncontrolled release of the industrial solvent methylene chloride, also known as dichloromethane (DCM), has resulted in widespread groundwater contamination in the United States. Here we investigate the role of groundwater bacterial communities in the natural attenuation of DCM at an undisclosed manufacturing site in New Jersey. This study investigates the bacterial community structure of groundwater samples differentially contaminated with DCM to better understand the biodegradation potential of these autochthonous bacterial communities. Bacterial community analysis was completed using high-throughput sequencing of the 16S rRNA gene of groundwater samples (n = 26) with DCM contamination ranging from 0.89 to 9,800,000 µg/L. Significant DCM concentration-driven shifts in overall bacterial community structure were identified between samples, including an increase in the abundance of Firmicutes within the most contaminated samples. Across all samples, a total of 6,134 unique operational taxonomic units (OTUs) were identified, with 16 taxa having strong correlations with increased DCM concentration. Putative DCM degraders such as Pseudomonas, Dehalobacterium and Desulfovibrio were present within groundwater across all levels of DCM contamination. Interestingly, each of these taxa dominated specific DCM contamination ranges respectively. Potential DCM degrading lineages yet to be cited specifically as a DCM degrading organisms, such as the Desulfosporosinus, thrived within the most heavily contaminated groundwater samples. Co-occurrence network analysis revealed aerobic and anaerobic bacterial taxa with DCM-degrading potential were present at the study site. Our 16S rRNA gene survey serves as the first in situ bacterial community assessment of contaminated groundwater harboring DCM concentrations ranging over seven orders of magnitude. Diversity analyses revealed known as well as potentially novel DCM degrading taxa within defined DCM concentration ranges, indicating niche-specific responses of these autochthonous populations. Altogether, our findings suggest that monitored natural attenuation is an appropriate remediation strategy for DCM contamination, and that high-throughput sequencing technologies are a robust method for assessing the potential role of biodegrading bacterial assemblages in the apparent reduction of DCM concentrations in environmental scenarios.