Individual-level Characteristics Research Articles

Association between Neighborhood Disadvantage and Health Status/Healthcare Utilization in Survivors of Blood or Marrow Transplantation (BMT) - a BMTSS Report

Background: Living in a disadvantaged neighborhood (reflecting neighborhood-level social determinants of health) is associated with poor health outcomes. BMT survivors remain at a high risk of long-term and late-occurring chronic health conditions that require anticipatory management. We hypothesized that neighborhood disadvantage would be associated with poor health status as reported by the BMT survivors, as well as poor utilization of the healthcare system.Methods: We leveraged data from BMTSS - a retrospective cohort study examining long-term outcomes among individuals who survived ≥2y following BMT performed at three institutions between 1974 and 2014. Participants in this analysis underwent a single BMT and completed the BMTSS survey, which captures sociodemographic characteristics and chronic health conditions. We graded chronic health conditions using CTCAE v5.0, and calculated a summative index that takes into account the number and grades of the conditions, where a higher score indicates more/worse conditions. The survey also captured self-reported health status (“In general would you say your health is: excellent, very good, good, fair or poor?”) and healthcare utilization (“When was your most recent routine check-up? <1y ago, 1-2y ago, 2-5y ago, ≥5y ago, never”). Neighborhood disadvantage was measured using the Area Deprivation Index (ADI), a validated composite indicator based on 17 US Census measures and percentiled as 0 (least deprived) to 100 (most deprived). BMT survivors were linked to ADI via census block group using home address at survey completion. Using multivariable ordered logit regression, we modeled the association between ADI and the odds of worse self-reported health or a longer time since a routine healthcare visit. Models were adjusted for available clinical factors (primary cancer diagnosis, donor source, conditioning intensity, chronic health conditions, chronic graft vs. host disease (GvHD), time from BMT) and individual-level sociodemographic characteristics (age at survey, sex, payor, race/ethnicity, education, income, marital status).Results: The cohort included 2,893 BMT survivors; median age at BMT was 47y (IQR: 30-58); median follow-up time was 9y (IQR: 5-16). Table 1 summarizes patient characteristics. Median ADI ranged from 14.0 in patients rating their health as excellent to 28.5 in those rating their health as poor, and from 21.0 in patients with visits <1y ago to 34.0 in patients reporting no visits [Fig 1]. In multivariable analyses, the odds of reporting worse health were higher for patients residing in more disadvantaged neighborhoods (OR per_unit_higher_ADI=1.005, p=0.003). Thus, for our cohort, a patient living in the most disadvantaged neighborhood (ADI=100) had 1.65 times the odds of reporting poor health compared to a patient living in the least disadvantaged neighborhood (ADI=1). Further, the odds of a longer time since the last routine physician visit were higher for patients living in more disadvantaged neighborhoods (OR per_unit_higher_ADI=1.007, p<0.001). Thus, a patient living in the most disadvantaged neighborhood had twice the odds (OR=2.06) of reporting no visits compared to a patient living in the least disadvantaged neighborhood.Conclusions: Conditional on surviving 2 or more years after BMT, living in a disadvantaged neighborhood was associated with poorer self-reported health and a longer time interval since a routine healthcare visit, after adjusting for self-reported individual socioeconomic indicators and chronic health conditions. The significant association between area deprivation and poorer self-reported health persisted after controlling for prior health care utilization. Our findings suggest that health status and access to healthcare are associated with characteristics of the built and social environment and deserve detailed examination in order to inform multi-level interventions that include policy. [Display omitted] DisclosuresArora: Syndax: Research Funding; Kadmom: Research Funding; Pharmacyclics: Research Funding.

The effect of language on financial inclusion

This study explores whether cross-country differences in financial inclusion can partly be attributed to language heterogeneity. We examine if the future time reference (FTR) component of a language affects intertemporal decision making of individuals when it comes to financial inclusion. We analyze this premise in the backdrop of the extant literature which demonstrates that speakers of languages that demonstrate weak-FTR tend to give relatively more importance to the future. Based on a sample of 78 countries and employing OLS, probit, and instrumental variable methods, we demonstrate that countries where the dominant language exhibits weak-FTR, the percentage of population making use of various financial services, is relatively higher. Further, we identify patience, educational attainment, and tax morale, as potential channels through which the weak-FTR component of language might impact financial inclusion. Our results are robust to controlling for cross-country and individual-level characteristics, language evolution, and alternate future marking behavioral indicators.

All-cause mortality and residential racial and ethnic segregation and composition as experienced differently by individual-level race, ethnicity, and gender: Mortality disparities in american communities data

Use a large nationally representative population to evaluate whether differences in mortality in relation to residential racial and ethnic segregation and diversity varied by gender, and race or Hispanic ethnicity in the United States. The Mortality Disparities in American Communities (MDAC) was used to evaluate mortality risk in relation to segregation. MDAC is a nationally representative record linkage of the 2008 American Community Survey data with mortality outcomes derived from the National Death Index through 2015. Gender-stratified mortality risk for White, Black, and Hispanic groups in relation to quartiles of residential segregation, composition, and diversity were modeled using parametric survival regression with an exponential distribution, adjusted for individual-level socioeconomic characteristics. The study population included >3,950,000 individuals and >273,000 all-cause mortality outcomes. Statistically significant differences in associations were observed with Black segregation vs. Hispanic segregation across Black or Hispanic groups; some differences in stratification by gender for Hispanic and Non-Hispanic Black groups, but gender-stratified associations were more similar in non-Hispanic Whites. Future multidisciplinary and ethnographic research is needed to identify the specific structural mechanisms by which these associations differ to support means by which to more effectively target public health interventions.

Do temporal trends of associations between short-term exposure to fine particulate matter (PM2.5) and risk of hospitalizations differ by sub-populations and urbanicity—a study of 968 U.S. counties and the Medicare population

While associations between short-term exposure to fine particulate matter (PM2.5) and risk of hospitalization are well documented and evidence suggests that such associations change over time, it is unclear whether these temporal changes exist in understudied less-urban areas or differ by sub-population. We analyzed daily time-series data of 968 continental U.S. counties for 2000–2016, with cause-specific hospitalization from Medicare claims and population-weighted PM2.5 concentrations originally estimated at 1km × 1 km from a hybrid model. Circulatory and respiratory hospitalizations were categorized based on primary diagnosis codes at discharge. Using modified Bayesian hierarchical modelling, we evaluated the temporal trend in association between PM2.5 and hospitalizations and whether disparities in this trend exist across individual-level characteristics (e.g., sex, age, race, and Medicaid eligibility as a proxy for socio-economic status) and urbanicity. Urbanicity was categorized into three levels by county-specific percentage of urban population based on urban rural delineation from the U.S. Census. In this cohort with understudied less-urban areas without regulatory monitors, we still found positive association between circulatory and respiratory hospitalization and short-term exposure to PM2.5, with higher effect estimates towards the end of study period. Consistent with current literature, we identified significant disparity in associations by race, socioeconomic status and urbanicity. We found that the percentage change in circulatory hospitalization rate per 10 μg/m3 increase in PM2.5 was higher in the 2008–2016 time period compared to the 2000–2007 period by 0.33% (95% posterior credible interval 0.22, 0.44%), 0.52% (0.33, 0.69%), and 0.67% (0.53, 0.83%) for low, medium and high tertiles of urban areas, respectively. We also observed significant differences in temporal trends of associations across socioeconomic status, sex, and age, indicating a possible widening in disparity of PM2.5-related health burden. This study raises the importance of considering environmental justice issues in PM2.5-related health impacts with respect to how associations may change over time.

Social and built neighborhood environments and blood pressure 6 years later: Results from the Hispanic Community Health Study/Study of Latinos and the SOL CASAS ancillary study

Neighborhood-level socioeconomic deprivation can increase risk for higher blood pressure or hypertension, while greater neighborhood safety and walkability may protect against hypertension. Large-scale prospective research, particularly among Hispanics/Latinos, is lacking. We examined cross-sectional and prospective associations between neighborhood environments and blood pressure and hypertension among 3851 Hispanic/Latinos enrolled in the Hispanic Community Health Study/Study of Latinos San Diego, CA cohort. Addresses from Visit 1 (2008–2011) were geocoded and neighborhood characteristics were determined as part of the SOL CASAS ancillary study. Home addresses were geocoded and home areas created using 800 m circular radial buffers. Neighborhood indices socioeconomic deprivation, residential stability, and social disorder were created using Census and other publicly available data. Walkability was computed as density of intersections, retail spaces, and residences. Greenness was measured via satellite imagery using the Normalized Difference Vegetation Index. Visit 1 and Visit 2 (2014–2017) clinical outcomes included systolic (SBP) and diastolic (DBP) blood pressure, as well as prevalent and 6-year incident hypertension, defined as SBP/DBP ≥140/90 mmHg or antihypertensive medication use. Complex survey regression models adjusted for covariates revealed cross-sectional associations between greater walkability and lower SBP (B = −0.05; 95% CI: −0.09, −0.003). In prospective analyses, greater neighborhood social disorder was related to increasing SBP (B = 0.05; 95% CI: 0.01, 0.09) and DBP (B = 0.07; 95% CI: 0.02, 0.12) over time. Greater socioeconomic deprivation (OR = 1.47; 95% CI: 1.06, 2.04) and greater social disorder (OR = 1.25; 95% CI: 1.02, 1.54) were associated with higher odds of incident hypertension. All other associations were not significant. Beyond individual-level characteristics, greater neighborhood social disorder and socioeconomic deprivation were related to adverse changes in blood pressure over 6 years among Hispanics/Latinos. Neighborhood social environment may help identify, or be an area for future intervention for, cardiovascular risk among Hispanics/Latinos.

Social Network Correlates of Mental Health among Rural-to-Urban Migrants in China.

Internal rural-to-urban migrants in China are facing a high risk of mental disorders. Previous research on mental health correlates and predictors among this population focused on individual-level characteristics, neglecting network-level indicators, and migrant–urbanite intergroup relationship. A cross-sectional survey was conducted in Beijing, China from December 2018 to January 2019. A convenience sample of 420 rural-to-urban migrants completed the Chinese 12-item General Health Questionnaire and reported their relationship with urbanites in the past six months. Multivariate linear regression models were used to test the association of the inter-hukou network with migrant mental health. Two indicators of the inter-hukou network were significantly associated with migrant mental health. Migrants were more mentally healthy if their proportion of weak ties in the inter-hukou network was no less than 50%. The more social support migrants received from the inter-hukou network, the better their mental health was. Meanwhile, there was a significant interaction effect between social support and sex, indicating that the same level of social support better protected the mental health of female migrants. Results suggest the importance of social network factors and migrant–urbanite ties for migrant mental health. Future efforts may need to mobilize and facilitate the inter-hukou network to improve migrant mental health.

Longitudinal impacts of greenness on cardiovascular disease conditions

Abstract Introduction Environmental determinants of health, such as greenness, play an increasing role in our understanding of cardiovascular disease, and can inform how to address geographic cardiovascular disparities. This study assesses the impact of greenness and changes in greenness on cardiovascular disease. Purpose The purpose of this study is to investigate the impact of greenness and changes in greenness on cardiovascular disease diagnoses. Methods The sample for this prospective, longitudinal study was comprised of 243,558 U.S. Medicare beneficiaries 65 years or older, residing on the same Census Block from 2011 through 2016, and who had a Miami-Dade residential 9-digit zip code. Analyses examined the impact of greenness, measured by mean block-level Normalized Difference Vegetation index (NDVI) from satellite imagery to incidence of new cardiovascular conditions including: acute myocardial infarction, atrial fibrillation, heart failure, ischemic heart disease, hypertension, and stroke/ transient ischemic attack. Zero-inflated poisson regression was used to model the odds of developing any new cardiovascular disease and number of new cardiovascular conditions based on block level greenness while adjusting for individual age, gender, race/ethnicity, number of baseline cardiovascular conditions, and neighborhood characteristics including income and walkability. Results Living in a higher greenness Census Block was associated with lower odds of having at least one new cardiovascular condition and having a small number of new conditions, adjusting for individual and neighborhood level characteristics. When compared to individuals living in the lowest tertile of greenness throughout the study, those individuals living in the highest tertile of greenness throughout the study had a 16% lower odds of having any new cardiovascular conditions (OR=0.84, 95% CI: 0.79–0.90, p&amp;lt;0.001) and among individuals developing at least one new cardiovascular disease, 4% fewer new cardiovascular conditions (OR=0.96, 95% CI: 0.92–0.99, p&amp;lt;0.05). When compared to individuals living in the lowest tertile of greenness throughout the study, those individuals living in areas that increased their greenness from the lowest tertile to the highest tertile of greenness had a 15% lower odds of having any new cardiovascular conditions (OR=0.85, 95% CI: 0.75–0.97, p&amp;lt;0.001) and among individuals developing at least one new cardiovascular disease, 9% fewer new cardiovascular conditions (OR=0.91, 95% CI: 0.83–0.99, p&amp;lt;0.05). Conclusions High greenness is associated with lower rates of cardiovascular conditions over time, both when greenness increases and when a Census Block maintains high greenness. It is remarkable that these effects appear in five years, a relatively short amount of time for a positive environmental impact; and that even for those who began in the lowest greenness tertile, an increase to the high greenness tertile had a significant effect. Funding Acknowledgement Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): Robert Wood Johnson Evidence for Action Grant

Associations of exposure to residential green space and neighborhood walkability with coronary atherosclerosis in Chinese adults

Residential green space and neighborhood walkability are important foundations of a healthy and sustainable city. Yet, their associations with atherosclerosis, the disease underlying clinical coronary heart disease (CHD), is unknown, especially in susceptible populations. We aim to explore the associations of exposure to residential green space and neighborhood walkability with coronary atherosclerosis. In this study of 2021 adults with suspected CHD, we evaluated the associations of exposure to green space (using Normalized Difference Vegetation Index [NDVI] and enhanced vegetation index [EVI] surrounding each participant's home) and neighborhood walkability (using walkability index and number of parks near home) with atherosclerosis (using coronary artery calcium score, CAC) using linear regression model adjusted for individual-level characteristics. Mediation analysis was further applied to explore potential mechanisms through the pathways of physical activity, air pollution, and psychological stress. In the primary model, an interquartile increase in annual mean NDVI and EVI within the 1-km area was associated with −15.8% (95%CI: 28.7%, −0.7%), and −18.6% (95%Cl: 31.3%, −3.6%) lower CAC score, respectively. However, an interquartile increase in the walkability index near home was associated with a 7.4% (95% CI: 0.1%, 15.2%) higher CAC score. The combined exposure to a green space area in a 1-km area and the walkability index were inversely associated with atherosclerosis, albeit with a smaller magnitude than a single-exposure model. The findings from a mediation analysis suggested that increased physical exercise and ameliorated particulate matter <2.5 μm (PM2.5) may partially contribute to the relationship between green space and atherosclerosis, and for walkability index, partially explained by increased PM2.5 exposure. Our study suggested a beneficial association between green space and atherosclerosis, but an adverse association between neighborhood walkability and atherosclerosis. Therefore, urban development that aims to improve neighborhood walkability should jointly account for enhancing green space properties from a public health perspective.

Estimation of Utility Values for Computing Quality-adjusted Life Years Associated With Homelessness.

There is a lack of data-driven evidence about the burden of homelessness, and lack of a holistic measure of effectiveness for evaluating interventions targeting homelessness. Quality-adjusted life years (QALYs) can help holistically capture the burden of homelessness, and facilitate the valuation and comparison of interventions designed to address homelessness. This study estimated utility values required to compute the QALYs associated with homelessness, and also examined individual-level characteristics that affect these values. The study is cross-sectional and derived from a large national survey conducted during the coronavirus disease 2019 pandemic. A sample of 6607 middle- and low-income adults in the United States. A self-completion standard gamble survey was used to estimate utility values associated with homelessness. Linear regression was used to analyze the association between individual-level characteristics and these utility values. The study estimated the average utility value associated with homelessness as 43.4% among the study participants. This implies that 1 year of life as a homeless individual is perceived to be equivalent to less than half a year of life as a stably housed individual in good health. The study also found that individuals who have experienced homelessness and financial distress value life as a homeless person considerably less than those who have not had these experiences. The method developed in this study can be used to estimate QALYs in studies evaluating homelessness interventions, thereby establishing the societal value of these interventions and informing policy and budgetary decision-making. Future studies estimating the utility values associated with homelessness in the general population, as well as specific homeless groups, are required to provide more generalizable evidence.

Risk Factors for COVID-19 Deaths Among Elderly Nursing Home Medicare Beneficiaries in the Prevaccine Period.

We evaluated prevaccine pandemic period COVID-19 death risk factors among nursing home (NH) residents. In a retrospective cohort study covering Medicare fee-for-service beneficiaries aged ≥65 years residing in US NHs, we estimated adjusted hazard ratios (HRs) using multivariate Cox proportional hazards regressions. Among 608251 elderly NH residents, 57398 (9.4%) died of COVID-19-related illness 1 April to 22 December 2020; 46.9% (26893) of these deaths occurred without prior COVID-19 hospitalizations. We observed a consistently increasing age trend for COVID-19 deaths. Racial/ethnic minorities shared similarly high risk of NH COVID-19 deaths with whites. NH facility characteristics for-profit ownership and low health inspection ratings were associated with higher death risk. Resident characteristics (male [HR, 1.69], end-stage renal disease [HR, 1.42], cognitive impairment [HR, 1.34], and immunocompromised status [HR, 1.20]) were death risk factors. Other individual-level characteristics were less predictive of death than in community-dwelling population. Low NH health inspection ratings and private ownership contributed to COVID-19 death risks. Nearly half of NH COVID-19 deaths occurred without prior COVID-19 hospitalization and older residents were less likely to get hospitalized with COVID-19. No substantial differences were observed by race/ethnicity and socioeconomic status for NH COVID-19 deaths.

Relationships between neighborhood collective efficacy and adolescent suicidal ideation

IntroductionUntil now, South Korean adolescent suicidal ideation literature has focused mainly on individual-level characteristics. Little is known about the contextual effects of social integration and social regulation on an individual's suicide behavior in South Korea as identified through the use of Durkheim's sociological insights. This study drew on Durkheim’s suicide and collective efficacy theories and analyzed the effects of the structural characteristics and collective efficacy of neighborhoods on adolescents’ suicidal ideation. MethodsThe data analyzed was from three sources: the 2013 Korean National Survey of the Present Status of Children (n = 1,915; 50.41% girls; mean age = 13.04 years), government census data from the Korea Statistical Information System, and administrative data from the Korea Ministry of Health and Welfare. The Hierarchical Generalized Linear Model was used to investigate the effects of neighborhood structural characteristics and collective efficacy on adolescent suicidal ideation. ResultsThere were no significant associations between neighborhood characteristics such as concentrated poverty, divorce rate, and residential instability; however, adoles cents' perceptions of collective efficacy in neighborhoods was associated with lower suicidal ideation after accounting for individual adolescent differences. ConclusionThe findings provide significant implications for the prevention of suicide in adolescents and suggest that enhancing the collective efficacy of neighborhoods through community-based intervention may be an important target of future suicide prevention strategies in South Korea.

Living While Black, Gay, and Poor: The Association of Race, Neighborhood Structural Disadvantage, and PrEP Utilization Among a Sample of Black Men Who Have Sex With Men in the Deep South.

Utilizing the Andersen Healthcare Utilization Model, we examined the role of neighborhood context on pre-exposure prophylaxis (PrEP) utilization among a sample of Black men who have sex with men (MSM) residing in a medium-sized city in the Deep South. Data were derived from a sample of 142 Black MSM aged 18-64 years who were eligible for PrEP from a community-based study known as "ACCELERATE!" We used multilevel structural equation modeling to assess PrEP use. Social support, sexual risk, and health care access were predictive of PrEP use. Notably, residing in a neighborhood with concentrated poverty was associated with decreased PrEP use. Our findings reveal neighborhood structural disadvantage is associated with decreased PrEP use among Black MSM, after adjusting of individual-level sociodemographic characteristics. There is an urgent need to develop HIV prevention interventions and programs that explicitly address structural-level factors to eliminate racial/ethnic differences in HIV.

Seeing the forest for the trees: Predicting attendance in trials for co-occurring PTSD and substance use disorders with a machine learning approach.

Objective: High dropout rates are common in randomized clinical trials (RCTs) for comorbid posttraumatic stress disorder and substance use disorders (PTSD + SUD). Optimizing attendance is a priority for PTSD + SUD treatment development, yet research has found few consistent associations to guide responsive strategies. In this study, we employed a data-driven pipeline for identifying salient and reliable predictors of attendance. Method: In a novel application of the iterative Random Forest algorithm (iRF), we investigated the association of individual level characteristics and session attendance in a completed RCT for PTSD + SUD (n = 70; women = 22 [31.4%]). iRF identified a group of potential predictor candidates for the total trial sessions attended; then, a Poisson regression model assessed the association between the iRF-identified factors and attendance. As a validation set, a parallel regression of significant predictors was conducted on a second, independent RCT for PTSD + SUD (n = 60; women = 48 [80%]). Results: Two testable hypotheses were derived from iRF's variable importance measures. Faster within-treatment improvement of PTSD symptoms was associated with greater session attendance with age moderating this relationship (p = .01): faster PTSD symptom improvement predicted fewer sessions attended among younger patients and more sessions among older patients. Full-time employment was also associated with fewer sessions attended (p = .02). In the validation set, the interaction between age and speed of PTSD improvement was significant (p = .05) and the employment association was not. Conclusions: Results demonstrate the potential of data-driven methods to identifying meaningful predictors as well as the dynamic contribution of symptom change during treatment to understanding RCT attendance. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Latent vehicle type propensity segments: Considering the influence of household vehicle fleet structure

This study applies latent class cluster analysis to a sample of 1,111 survey respondents in Georgia, identifying naturally occurring vehicle type segments based on the influence of both individual vehicle type choices and household vehicle fleet structures. The developed model identifies seven latent vehicle type propensity segments, six of which include individuals who reported being the main driver for (respectively) car, SUV/van, and truck. In three of those segments this was generally their only available vehicle, while in the other three the “main driver” vehicle accompanied other available household vehicles. The seventh segment captures individuals who are main drivers of multiple vehicle types, and who also have other household vehicles available for use. We generate user profiles and discuss differences across segments regarding individual-level characteristics (e.g., gender), household-level characteristics (e.g., household income), land-use and travel-related preferences (e.g., neighborhood type, share of household-serving trips), attitudes (e.g., materialistic), and targeted marketing data variables (e.g., support for charitable causes). Selected results suggest that women choose SUVs/vans due to both personal preferences (e.g., feeling safer while driving a large vehicle) and household responsibilities; show that vehicle-owning behaviors and attitudes are generally consistent, except that strong pro-vehicle-owning attitudes exist within vehicle-deficit households; and suggest that vehicle-deficit households may be less open to alternative fuel vehicles, possibly due to reliability concerns. Overall, this study provides a new perspective on vehicle type propensity segments, and examines the association of a novel range of general and travel-related attributes with these segments, yielding nuanced insights with potential policy implications.

Characteristics of Clinical Trial Participants with Duchenne Muscular Dystrophy: Data from the Muscular Dystrophy Surveillance, Tracking, and Research Network (MD STARnet).

Background: Therapeutic trials are critical to improving outcomes for individuals diagnosed with Duchenne muscular dystrophy (DMD). Understanding predictors of clinical trial participation could maximize enrollment. Methods: Data from six sites (Colorado, Iowa, Piedmont region North Carolina, South Carolina, Utah, and western New York) of the Muscular Dystrophy Surveillance, Tracking, and Research Network (MD STARnet) were analyzed. Clinical trial participation and individual-level clinical and sociodemographic characteristics were obtained from medical records for the 2000–2015 calendar years. County-level characteristics were determined from linkage of the most recent county of residence identified from medical records and publicly available federal datasets. Fisher’s exact and Wilcoxon two-sample tests were used with statistical significance set at one-sided p-value (<0.05) based on the hypothesis that nonparticipants had fewer resources. Results: Clinical trial participation was identified among 17.9% (MD STARnet site: 3.7–27.3%) of 358 individuals with DMD. Corticosteroids, tadalafil, and ataluren (PTC124) were the most common trial medications recorded. Fewer non-Hispanic blacks or Hispanics than non-Hispanic whites participated in clinical trials. Trial participants tended to reside in counties with lower percentages of non-Hispanic blacks. Conclusion: Understanding characteristics associated with clinical trial participation is critical for identifying participation barriers and generalizability of trial results. MD STARnet is uniquely able to track clinical trial participation through surveillance and describe patterns of participation.

Youth Mental Health First Aid: Examining the Influence of Pre-Existing Attitudes and Knowledge on Training Effectiveness.

Youth Mental Health First Aid (YMHFA) is a gatekeeper training designed to assist professionals in their identification and response to youth mental illness. Despite widespread implementation, few studies have examined how individual-level trainee characteristics may impact the effectiveness of this training. In this study, we examined how pre-existing knowledge and attitudes about youth mental illness (measured prior to participation in the program) influenced training outcomes. We used a sample of 987 child-serving professionals who completed the YMHFA training program to identify demographic and work-related factors that predicted pre-existing attitudes and knowledge. The sample was then divided into two groups based on pre-existing attitudes and knowledge. We examined training effectiveness across four constructs: knowledge, confidence, intentions to intervene, and stigma. Findings indicate that gender and work-related characteristics were associated with pre-existing knowledge and attitudes about youth mental illness. The magnitude of training effectiveness varied across pre-existing attitudes and knowledge. Those participants with above average attitudes and knowledge benefited little from the program, suggesting that universal implementation of YMHFA may not be an efficient use of resources. Suggestions for a tiered implementation plan that prioritizes professionals most in need of the training are discussed.

Global adoption of personal and social mitigation behaviors during COVID-19: The role of trust & confidence.

What influences the adoption of SARS-CoV-2 mitigation behaviors–both personal, such as mask wearing and frequent handwashing, and social, such as avoiding large gatherings and physical contact–across countries? Understanding why some individuals are more willing to change their behavior to mitigate the spread of a pandemic will not only help us to address the current SARS-CoV-2 pandemic but also to respond to future ones. Researchers have pointed to a variety of factors that may influence individual adoption of personal and social mitigation behaviors, including social inequality, risk perception, personality traits, and government policies. While not denying the importance of these factors, we argue that the role of trust and confidence has received insufficient attention to date. Our study explores whether there is a difference in the way trust and confidence in particular leaders and organizations affect individual compliance and whether this effect is consistent across different types of mitigation behaviors. Specifically, we utilize an original cross-national survey conducted during the first wave of the SARS-CoV-2 pandemic (May-June 2020) to investigate how trust in scientists, medical professionals, politicians, and religious leaders and confidence in global, national, and local health organizations affects individual compliance in 16 countries/territories across five world regions. Our analyses, which control for the aforementioned factors as well as several others, suggest that trust in politicians and confidence in national health ministries have the most consistent influence on whether individuals adopt both personal and social mitigation behaviors. Across our sample, we find that greater trust in politicians is associated with lower levels of individual compliance with public health directives, whereas greater confidence in the national health ministry is associated with higher levels of individual compliance. Our findings suggest the need to understand trust and confidence as among the most important individual level characteristics driving compliance when developing and delivering messaging about the adoption of mitigation behaviors. The content of the message, it seems, will be most effective when citizens across countries trust its source. Trusted sources, such as politicians and the national health ministry, should thus consider working closely together when determining and communicating recommended health behaviors to avoid contradicting one another.

The Role of Community-Level Factors on Disparities in COVID-19 Infection Among American Indian/Alaska Native Veterans.

ObjectivesAmerican Indian and Alaska Native (AI/AN) communities have been disproportionately affected by the coronavirus disease 2019 (COVID-19) pandemic. This study examines whether neighborhood characteristics mediate AI/AN versus White-non-Hispanic Veteran COVID-19 infection disparities, and whether mediation differs based on proximity to reservations.MethodsUsing Veteran Health Administration’s (VHA) national database of VHA users evaluated for COVID-19 infection (3/1/2020–8/25/2020), we examined whether census tract neighborhood characteristics (percent households overcrowded, without complete plumbing, without kitchen plumbing, and neighborhood socioeconomic status [n-SES]) mediated racial disparities in COVID-19 infection, using inverse odds-weighted logistic models controlling for individual-level characteristics. Using moderated mediation analyses, we assessed whether neighborhood mediating effects on disparities differed for those residing in counties containing/near federally recognized tribal lands (i.e., Contract Health Service Delivery Area [CHSDA] counties) versus not.ResultsThe percent of households without complete plumbing, percent without kitchen plumbing, and n-SES partially mediated AI/AN-White-non-Hispanic COVID-19 infection disparities (accounting for 17–35% of disparity) to a similar extent in CHSDA and non-CHSDA counties. The percent of households without kitchen plumbing had stronger mediating effects for CHSDA than non-CHSDA residents.ConclusionsNeighborhood-level social determinants of health may contribute to the disproportionate COVID-19 infection burden on AI/ANs; differences are exacerbated among AI/ANs living near reservations.

The individual, place, and wellbeing \u2013 a network analysis

BackgroundPrevious research has examined individual-level and place characteristics as correlates of subjective wellbeing, with many studies concluding that individual factors (e.g. health, finances) are more strongly related to wellbeing. However, this ‘dualistic’ approach has been challenged, with some arguing that it is impossible to disentangle the effects of the two domains, and that wellbeing should be considered as part of a network of mutually reinforcing relationships between individual, community and place characteristics. We used network analysis to explore these complex associations.MethodsData were from a large sample of adults from a socioeconomically disadvantaged region of the United Kingdom (N = 4319). Wellbeing was assessed using the 7-item version of the Warwick–Edinburgh Mental Wellbeing Scale (SWEMWBS). Mixed graphical networks were estimated including wellbeing, place and individual-characteristic variables as nodes.ResultsWe found a densely connected network in which wellbeing was associated, both directly and indirectly, with all of the individual, community and place characteristics assessed. Wellbeing was most strongly connected with individual characteristics, in particular financial difficulty and subjective physical health. However, controlling for all other variables in the network model, wellbeing was positively associated with local greenspace usage, civic agency, and neighbourhood cohesion, and negatively associated with housing disrepair. Greater specificity in these associations was observed when the wellbeing construct was broken down into its constituent parts.ConclusionsThese findings highlight the complex relationships that exist between individual, community and place characteristics in the context of subjective wellbeing, and that all domains need to be considered when developing population-level strategies to improve wellbeing. Further consideration needs to be given to how this might happen in practice, for example through a combination of consistent use of community engagement methodologies alongside Health in All Policy (HiAP) approaches.

1498Community-level risk factors for birth size of child in selected developing countries (1992-2018): multilevel analysis

Abstract Background We aimed to identify emerging community-level risk factors for birth size in the last two decades in developing countries, particularly in Bangladesh, India, Indonesia, and Nigeria, having the highest burden of low birth weight (LBW) births globally. Methods We used data from multiple rounds of the Demographic and Health Surveys (DHS) conducted throughout the last two decades in the selected countries. We applied multilevel binary logistic regression models and estimated the intra-correlation coefficient (ICC) and median odds ratio (MOR) with a 95% confidence interval (CI) to analyze community-level variation in the birth size of child. Results The odds of having a smaller than average size birth increased by 1.28 times (95% CI: 1.11-1.79) in Bangladesh (2014), 3.03 times (95% CI: 2.90-3.18) in India (2015-16), 1.40 times (95% CI: 1.28-1.58) in Indonesia (2017) and 2.32 times (95% CI: 2.15-2.53) in Nigeria (2018) when women moved from low-risk to high-risk communities. The children residing in communities with a higher level of female illiteracy, higher level of inadequate antenatal care visits (ANC), higher use of unimproved toilet facilities were more likely to born with smaller than average birth size during 1992-2018. Conclusions The study confirms a significant community-level variation in smaller than average birth size among all analysed countries. Community with higher levels of female illiteracy, inadequate ANC visits, use of unimproved toilet facilities emerged as significant risk factors throughout the last two decades. Key messages The community-level risk factors have an independent association with the birth size of child regardless of individual-level characteristics of women and children.