Dimension reduction of 911 Good Samaritan Laws: Drawing inferences from policy surveillance.

BACKGROUND: 911 Good Samaritan Laws (GSLs) extend legal protection to people reporting drug overdoses who may otherwise be in violation of controlled substance laws. Mixed evidence suggests GSLs decrease overdose mortality, but these studies overlook substantial heterogeneity across states. The GSL Inventory exhaustively catalogs features of these laws into four categories: breadth, burden, strength, and exemption. The present study reduces this dataset to reveal patterns in implementation, facilitate future evaluations, and to produce a roadmap for the dimension reduction of further policy surveillance datasets. METHODS: We produced multidimensional scaling plots visualizing the frequency of co-occurring GSL features from the GSL Inventory as well as similarity among state laws. We clustered laws into meaningful groups by shared features; produced a decision tree identifying salient features predicting group membership; scored their relative breadth, burden, strength, and exemption of immunity; and associated groups with state sociopolitical and sociodemographic variables. RESULTS: In the feature plot, breadth and strength features segregate from burdens and exemptions. Regions in the state plot differentiate quantity of substances immunized, burden of reporting requirements, and immunity for probationers. State laws may be clustered into five groups distinguished by proximity, salient features, and sociopolitical variables. DISCUSSION: This study reveals competing attitudes toward harm reduction that underly GSLs across states. These analyses provide a roadmap for the application of dimension reduction methods to policy surveillance datasets, accommodating their binary structure and longitudinal observations. These methods preserve higher-dimensional variance in a form amenable to statistical evaluation.

Review and inventory of 911 Good Samaritan Law Provisions in the United States.

BACKGROUND: 911 Good Samaritan Laws (GSLs) confer limited legal immunity to bystanders in possession of controlled substances who report emergency overdoses. While these laws may decrease opioid overdose mortality, current literature reduces GSLs to a small number of variables, overlooking substantial differences in implementation and statutory context which dramatically alter their applicability. METHODS: We identified all state GSLs and their legislative history, characterizing features into four categories using a novel framework: breadth of protected activities, burden placed on Good Samaritans, strength of protection, and exemption in coverage. When protections depended on the nature of the controlled substance, heroin served as a common point of comparison. RESULTS: GSLs vary substantially across states and time. Protections depend on the quantity of substances involved and may extend to the person experiencing the overdose or persons reporting their own overdose. Protected offenses range from possession of controlled substances to drug-induced homicide. In some states, Good Samaritans must complete substance use treatment or administer naloxone to retain protections. Immunity ranges from protection from arrest to merely procedural protections at trial, and may even exclude persons in possession of opioids. Exemptions target persons engaging in chronic substance use, such as persons invoking protection multiple times or previously reporting an overdose. CONCLUSION: States offer Good Samaritans substantially different protections even when the statutes confer nominally comparable immunities. Accommodating this heterogeneity will enhance the validity of future studies into these laws and their efficacy.

Case growth analysis to inform local response to COVID-19 epidemic in a diverse U.S community.

Early detection of new outbreak waves is critical for effective and sustained response to the COVID-19 pandemic. We conducted a growth rate analysis using local community and inpatient records from seven hospital systems to characterize distinct phases in SARS-CoV-2 outbreak waves in the Greater Houston area. We determined the transition times from rapid spread of infection in the community to surge in the number of inpatients in local hospitals. We identified 193,237 residents who tested positive for SARS-CoV-2 via molecular testing from April 8, 2020 to June 30, 2021, and 30,031 residents admitted within local healthcare institutions with a positive SARS-CoV-2 test, including emergency cases. We detected two distinct COVID-19 waves: May 12, 2020-September 6, 2020 and September 27, 2020-May 15, 2021; each encompassed four growth phases: lagging, exponential/rapid growth, deceleration, and stationary/linear. Our findings showed that, during early stages of the pandemic, the surge in the number of daily cases in the community preceded that of inpatients admitted to local hospitals by 12-36 days. Rapid decline in hospitalized cases was an early indicator of transition to deceleration in the community. Our real-time analysis informed local pandemic response in one of the largest U.S. metropolitan areas, providing an operationalized framework to support robust real-world surveillance for outbreak preparedness.

Trends and Correlates of Breakthrough Infections With SARS-CoV-2.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) delta variant has been hypothesized to decrease the efficacy of COVID-19 vaccines. Factors associated with infections with SARS-CoV-2 after vaccination are unknown. In this observational cohort study, we examined two groups in Harris County, Texas: (1) individuals with positive Nucleic Acid Amplification test between 12/14/2020 and 9/30/2021 and (2) the subset of individuals fully vaccinated in the same time period. Infected individuals were classified as a breakthrough if their infection occurred 14 days after their vaccination had been completed. Among fully vaccinated individuals, demographic and vaccine factors associated with breakthrough infections were assessed. Of 146,731 positive SARS-CoV-2 tests, 7.5% were breakthrough infections. Correlates of breakthrough infection included young adult age, female, White race, and receiving the Janssen vaccine, after adjustments including the amount of community spread at the time of infection. Vaccines remained effective in decreasing the probability of testing positive for SARS-CoV-2. The data indicate that increased vaccine booster uptake would help decrease new infections.

Analysis of Annual Costs of Mobile Clinics in the Southern United States.

INTRODUCTION: Mobile clinics provide an efficient manner for delivering healthcare services to at-risk populations, and there is a need to understand their economics. This study analyzes the costs of operating selected mobile clinic programs representing service categories in dental, dental/preventive, preventive care, primary care/preventive, and mammography/primary care/preventive. METHODS: The methodology included a self-reported survey of 96 mobile clinic programs operating in Texas, North Carolina, Georgia, and Florida; these states did not expand Medicaid and have a large proportion of uninsured individuals. Data were collected over an 8-month period from November 2016 to July 2017. The cost analyses were conducted in 2018, and were analyzed from the provider perspective. The average annual estimated costs; as well the costs per patient in each mobile clinic program within different service delivery types were assessed. Costs reported in the study survey were classified into recurrent direct costs and capital costs. RESULTS: Results indicate that mean operating costs range from about $300 000 to $2.5 million with costs increasing from mammography/primary care/preventive delivery to dental/preventive. The majority of mobile clinics provided dental care followed by dental/preventive. The cost per patient visit for all mobile clinic service types ranged from $65 to $529, and appears to be considerably less than those reported in the literature for fixed clinic services. CONCLUSION: The overall costs of all delivery types in mobile clinics were lower than the costs of providing care to Medicare beneficiaries in federally funded health centers, making mobile clinics a sound economic complement to stationary healthcare facilities.

Wellness project implementation within Houston's Faith and Diabetes initiative: a mixed methods study.

BACKGROUND: Faith-based health promotion has shown promise for supporting healthy lifestyles, but has limited evidence of reaching scale or sustainability. In one recent such effort, volunteers from a diverse range of faith organizations were trained as peer educators to implement diabetes self-management education (DSME) classes within their communities. The purpose of this study was to identify factors associated with provision of these classes within six months of peer-educator training. METHODS: This study used the Consolidated Framework for Implementation Research (CFIR) to identify patterns from interviews, observations, attendance records, and organizational background information. Two research team members thematically coded interview transcripts and observation memos to identify patterns distinguishing faith organizations that did, versus did not, conduct DSME classes within six months of peer-educator training. Bivariate statistics were also used to identify faith organizational characteristics associated with DSME class completion within this time frame. RESULTS: Volunteers from 24 faith organizations received peer-educator training. Of these, 15 led a DSME class within six months, graduating a total of 132 participants. Thematic analyses yielded two challenges experienced disproportionately by organizations unable to complete DSME within six months: [1] Their peer educators experienced DSME as complex, despite substantial planning efforts at simplification, and [2] the process of engaging peer educators and leadership within their organizations was often more difficult than anticipated, despite initial communication by Faith and Diabetes organizers intended to secure informed commitments by both groups. Many peer educators were overwhelmed by training content, the responsibility required to start and sustain DSME classes, and other time commitments. Other priorities competed for time in participants' lives and on organizational calendars, and scheduling processes could be slow. In an apparent dynamic of "crowding out," coordination was particularly difficult in larger organizations, which were less likely than smaller organizations to complete DSME classes despite their more substantial resources. CONCLUSIONS: Initial commitment from faith organizations' leadership and volunteers may not suffice to implement even relatively short and low cost health promotion programs. Faith organizations might benefit from realistic previews about just how challenging it is to make these programs a sufficiently high organizational and individual priority.

The utility of a system dynamics approach for understanding cumulative health risk from exposure to environmental hazards.

The potential of system dynamics modeling to advance our understanding of cumulative risk in the service of optimal health is discussed. The focus is on exploring system dynamics modeling as a systems science methodology that can provide a framework for examining the complexity of real-world social and environmental exposures among populations-particularly those exposed to multiple disparate sources of risk. The discussion also examines how system dynamics modeling can engage a diverse body of key stakeholders throughout the modeling process, promoting the collective assessment of assumptions and systematic gathering of critical data. Though not a panacea, system dynamics modeling provides a promising methodology to complement traditional research methods in understanding cumulative health effects from exposure to multiple environmental and social stressors.

Innovating patient care delivery: DSRIP's interrupted time series analysis paradigm.

INTRODUCTION: Adoption of Medicaid Section 1115 waiver is one of the many ways of innovating healthcare delivery system. The Delivery System Reform Incentive Payment (DSRIP) pool, one of the two funding pools of the waiver has four categories viz. infrastructure development, program innovation and redesign, quality improvement reporting and lastly, bringing about population health improvement. BACKGROUND: A metric of the fourth category, preventable hospitalization (PH) rate was analyzed in the context of eight conditions for two time periods, pre-reporting years (2010-2012) and post-reporting years (2013-2015) for two hospital cohorts, DSRIP participating and non-participating hospitals. The study explains how DSRIP impacted Preventable Hospitalization (PH) rates of eight conditions for both hospital cohorts within two time periods. METHODS: Eight PH rates were regressed as the dependent variable with time, intervention and post-DSRIP Intervention as independent variables. PH rates of eight conditions were then consolidated into one rate for regressing with the above independent variables to evaluate overall impact of DSRIP. An interrupted time series regression was performed after accounting for auto-correlation, stationarity and seasonality in the dataset. RESULTS: In the individual regression model, PH rates showed statistically significant coefficients for seven out of eight conditions in DSRIP participating hospitals. In the combined regression model, the coefficient of the PH rate showed a statistically significant decrease with negative p-values for regression coefficients in DSRIP participating hospitals compared to positive/increased p-values for regression coefficients in DSRIP non-participating hospitals. CONCLUSION AND IMPLICATIONS: Several macro- and micro-level factors may have likely contributed DSRIP hospitals outperforming DSRIP non-participating hospitals. Healthcare organization/provider collaboration, support from healthcare professionals, DSRIP's design, state reimbursement and coordination in care delivery methods may have led to likely success of DSRIP. LEVEL OF EVIDENCE: IV, a retrospective cohort study based on longitudinal data.

Methods for Evaluating the Combined Effects of Chemical and Nonchemical Exposures for Cumulative Environmental Health Risk Assessment.

Cumulative risk assessment (CRA) has been proposed as a means of evaluating possible additive and synergistic effects of multiple chemical, physical and social stressors on human health, with the goal of informing policy and decision-making, and protecting public health. Routine application of CRA to environmental regulatory and policy decision making, however, has been limited due to a perceived lack of appropriate quantitative approaches for assessing combined effects of chemical and nonchemical exposures. Seven research projects, which represented a variety of disciplines, including population health science, laboratory science, social sciences, geography, statistics and mathematics, were funded by the US Environmental Protection Agency (EPA) to help address this knowledge gap. We synthesize key insights from these unique studies to determine the implications for CRA practice and priorities for further research. Our analyses of these seven projects demonstrate that the necessary analytical methods to support CRA are available but are ultimately context-dependent. These projects collectively provided advancements for CRA in the areas of community engagement, characterization of exposures to nonchemical stressors, and assessment of health effects associated with joint exposures to chemical and psychosocial stressors.

Reducing the Cost of Medicaid: A Multistate Simulation.

According to some estimates, the United States wastes as much as 30% of health care dollars. Some of that waste can be mitigated by reducing certain costs associated with Medicaid. We chose 5 areas of savings applicable to Medicaid: (1) modification of physician payment models to reduce unnecessary care, (2) development of a medication adherence program for patients dually eligible for Medicaid and Medicare support ("dual eligibles"), (3) improvement in unnecessary admissions and readmissions for dual eligibles, (4) reduction in emergency department visits among children in Medicaid and dual-eligible beneficiaries, and (5) improvement in adoption of end-of-life advance directives. We chose the states from both ends of the spending spectrum: the 5 with the lowest annual Medicaid expenditures: Wyoming, South Dakota, Montana, Vermont, and Alaska, and those with the highest: California, New York, Texas, Pennsylvania, and Florida. This spectrum demonstrates the range of potential cost-saving measures, from US $23.6 million in Wyoming to US $3.4 billion in California. We conclude that there are a number of ways to reduce Medicaid spending and improve quality. To the extent that states have already adopted programs addressing the same problems, our approach may be supplementary but the total savings may be achieved with a combination of current initiative and those described here. As Medicaid creates savings, physician payment could be increased to attract more physicians into caring for Medicaid patients.

A Population-Based Approach to Mapping Vulnerability to Diabetes.

Of the 382 million people worldwide with diabetes, and if current trends continue, nearly half a billion people worldwide will have diabetes by 2035. Two-thirds of current diabetics are living in urban centers and the urban concentration of individuals with diabetes is on the rise. The problem is that in the absence of widespread clinical testing, there is no reliable way to predict which segments of the population are the most vulnerable to the onset of diabetes. Knowing who the most vulnerable are, and where they live, can guide the efficient allocation of prevention resources. Toward this end, we introduce the concept of composite vulnerability, which includes both group and individual-level attributes, and we provide a demonstration of its application to a large urban setting. The components of composite vulnerability are estimated using a novel, population-based, procedure that relies on sample survey data and nonparametric statistical techniques. First, cluster analysis identified three multivariate profiles of adult residents with type 2 diabetes, based on 35 socioeconomic indicators. Second, the undiagnosed population was screened for vulnerability based on their resemblance or fit to these multivariate profiles. Geographic neighborhoods with high concentrations of "vulnerables" could then be identified. In parallel, recursive partitioning found the best predictors of type 2 diabetes in this urban population, combined them with indicators of disadvantage, and applied them to residents in the selected neighborhoods to establish relative levels of composite vulnerability. Neighborhoods with high concentrations of residents manifesting composite vulnerability can be easily identified for targeting community-based prevention measures.

The combined effect of ambient ozone exposure and toxic air releases on hospitalization for asthma among children in Harris County, Texas.

This study represents an analysis of the effect of exposure to ambient ozone and toxic air releases on hospitalization for asthma among children in Harris County, Texas. Our study identified temporal and spatial variations in asthma hospitalization across the study region and explored the combined effect of exposure to ambient ozone and air toxics on asthma hospitalization. Asthma hospitalization hot spots and clusters were mostly not located on zip codes with reported high quantities of total air releases of chemical pollutants. There was no significant interaction between ambient ozone exposure and toxic air releases relative to asthma hospitalization. The major predictor of asthma hospitalization was season, with hospitalization rate per 10,000 people for asthma being highest in winter period when ozone levels are usually lowest.

Participants' perceptions of interactions with community health workers who promote behavior change: a qualitative characterization from participants with normal, depressive and anxious mood states.

BACKGROUND: Interventions that promote healthier lifestyles among Latinos often involve community health workers (CHWs). CHWs can effectively advocate for healthier lifestyles and may be pivotal in addressing such mental health conditions as depression and anxiety. The goal of this study was to characterize the relationship dynamics between Latino participants and CHWs, from the participant's perspective. We aimed to determine if CHW-delivered community interventions effected behavior change, especially among participants who reported anxiety and depression. METHODS: Semi-structured interviews were conducted with a purposive sample of 28 Latino participants that was based on a mental health scoring strata. Participants completed a lifestyle intervention that included multiple home visits from CHWs to promote physical activity and healthful food choice. Interviews were conducted in the participant's preferred language (English or Spanish). Transcribed interviews were analyzed using a grounded theory approach until concept saturation was achieved. RESULTS: The sample was primarily female (82%), lower socioeconomic status (64%), and mean age of 50 years. Participants discussed the rapport building and professionalism of CHWs as a feature that facilitated strong, positive relationships and lifestyle behavior changes. Participants described how CHWs patterned their change approaches, which were similar to commonly used therapeutic techniques in the treatment of anxiety and depression. While anxiety and depression were described as having an impact on behavior change, most, but not all, participants who reported negative mood states said that the CHW relationship helped in changing that state to some extent. CONCLUSIONS: Participants' perceptions indicated that positive personal changes were influenced by CHWs. Only participants who reported consistently poor scores for depression, anxiety or both reported negative or neutral experiences with the CHWs. This study lends qualitative support to the use of CHWs as extenders of care, particularly in areas that have a shortage of primary and mental health care providers.

Association of Dietary Intake and Biomarker Levels of Arsenic, Cadmium, Lead, and Mercury among Asian Populations in the United States: NHANES 2011-2012.

BACKGROUND: We have recently shown that biomarker levels of selected metals are higher in Asians than in other U.S. ethnic groups, with important differences within selected Asian subgroups. Much of this difference may be dietary in origin; however, this is not well established. OBJECTIVE: We evaluated dietary intake of toxic metals as a source of increased biomarker levels of metals among U.S. Asians. METHODS: We estimated daily food consumption and dietary intake of arsenic, cadmium, lead, and mercury by combining 24-hr dietary intake recall data from the 2011-2012 National Health and Nutrition Examination Survey (NHANES) with data from the USDA Food Composition Intake Database and FDA Total Dietary Study. We analyzed associations between dietary metal intake and biomarker levels of the metals using linear regression. Further, estimated food consumption and metal intake levels were compared between Asians and other racial/ethnic groups (white, black, Mexican American, and other Hispanic) and within three Asian subgroups (Chinese, Indian Asian, and other Asians). RESULTS: Significant associations (p < 0.05) were found between biomarker levels and estimated dietary metal intake for total and inorganic arsenic and mercury among Asians. Asians had the highest daily fish and rice consumption across the racial/ethnic groups. Fish was the major contributor to dietary mercury and total arsenic intake, whereas rice was the major contributor to inorganic arsenic dietary intake. Fish consumption across the Asian subgroups varied, with Asian Indians having lower fish consumption than the other Asian subgroups. Rice consumption was similar across the Asian subgroups. CONCLUSIONS: We confirmed that estimated dietary intake of arsenic (total and inorganic) and mercury is significantly associated with their corresponding biomarkers in U.S. Asians, using nationally representative data. In contrast, estimated dietary intake of cadmium and lead were not significantly associated with their corresponding biomarker levels in U.S. Asians. Citation: Awata H, Linder S, Mitchell LE, Delclos GL. 2017. Association of dietary intake and biomarker levels of arsenic, cadmium, lead, and mercury among Asian populations in the United States: NHANES 2011-2012. Environ Health Perspect 125:314-323; http://dx.doi.org/10.1289/EHP28.

Biomarker Levels of Toxic Metals among Asian Populations in the United States: NHANES 2011-2012.

INTRODUCTION: The Centers for Disease Control and Prevention (CDC) recently found that Asians have considerably higher biomarker levels of cadmium, lead, mercury, and arsenic than whites, blacks, Mexican Americans, and other Hispanics in the United States. OBJECTIVE: Our goal was to further evaluate the higher metal biomarker levels among Asians. METHODS: Biomarker data (blood cadmium, blood lead, blood mercury, urinary total arsenic, and urinary dimethylarsinic acic) from individuals ≥ 6 years of age were obtained from the 2011-2012 National Health and Nutrition Examination Survey (NHANES). We compared geometric mean levels of these five metal biomarkers in Asians with those of four other NHANES race/ethnic groups (white, black, Mexican American, and other Hispanic), and across three Asian subgroups (Chinese, Asian Indian, and other Asian). We also evaluated associations between biomarker levels and sociodemographic, physical, dietary, and behavioral covariates across the Asian subgroups. RESULTS: Asians had significantly higher levels of all five metal biomarkers than other race/ethnic groups (p < 0.05), regardless of sociodemographic, physical, dietary, behavioral, or geographic characteristics. We also found variations in biomarker levels across the Asian subgroups. In general, Asian Indians had lower levels than the other two Asian subgroups, except for blood lead. The following characteristics were found to be significant predictors of several biomarker levels: sex, age, education, birthplace, smoking, and fish consumption. CONCLUSIONS: Overall, the Asian group had the highest geometric mean biomarker levels for all of the five metal variables. Furthermore, we provided evidence that significant variations in the biomarker levels are present across the Asian subgroups in the United States. Citation: Awata H, Linder S, Mitchell LE, Delclos GL. 2017. Biomarker levels of toxic metals among Asian populations in the United States: NHANES 2011-2012. Environ Health Perspect 125:306-313; http://dx.doi.org/10.1289/EHP27.

Area-level Socioeconomic Inequalities in the Use of Mammography Screening: A Multilevel Analysis of the Health of Houston Survey.

BACKGROUND: An emerging literature reports that women who reside in socioeconomically deprived communities are less likely to adhere to mammography screening. This study explored associations between area-level socioeconomic measures and mammography screening among a racially and ethnically diverse sample of women in Texas. METHODS: We conducted a cross-sectional, multilevel study linking individual-level data from the 2010 Health of Houston Survey and contextual data from the U.S. Census. Women ages 40 to 74 years (n = 1,541) were included in the analyses. We examined tract-level poverty, unemployment, education, Hispanic and Black composition, female-headed householder families, and crowding as contextual measures. Using multilevel logistic regression modeling, we compared most disadvantaged tracts (quartiles 2-4) to the most advantaged tract (quartile 1). RESULTS: Overall, 64% of the sample was adherent to mammography screening. Screening rates were lower (p < .05) among Hispanics, those foreign born, women aged 40 to 49 years, and those with low educational attainment, unemployed, and without health insurance coverage. Women living in areas with high levels of poverty (quartile 2 vs. 1: odds ratio [OR], 0.50; 95% CI, 0.30-0.85), Hispanic composition (quartile 3 vs. 1: OR, 0.54; 95% CI, 0.32-0.90), and crowding (quartile 4 vs. 1: OR, 0.53; 95% CI, 0.29-0.96) were less likely to have up-to-date mammography screening, net of individual-level factors. CONCLUSION: Our findings highlight the importance of examining area-level socioeconomic inequalities in mammography screening. The study represents an advance on previous research because we examined multiple area measures, controlled for key individual-level covariates, used data aggregated at the tract level, and accounted for the nested structure of the data.

Associations between contextual factors and colorectal cancer screening in a racially and ethnically diverse population in Texas.

BACKGROUND: Colorectal cancer is the third most commonly diagnosed cancer and the third leading cause of cancer death in the United States. Increased attention has been given to understanding the role of local contexts on cancer screening behaviors. We examined the associations between multiple tract-level socioeconomic measures and adherence to colorectal cancer screening (CRCS) in Harris County and the City of Houston, Texas. METHODS: We conducted a cross-sectional multilevel study linking individual-level data on CRCS from the 2010 Health of Houston Survey with contextual data from the U.S. Census and the U.S. Department of Housing and Urban Development. We examined tract-level poverty, education, employment, income inequality, and foreclosure measures across 543 Census tracts. Analyses were limited to individuals aged 50-74 years (N=1720). RESULTS: Overall, 58.0% of the sample was adherent to any recommended CRCS test. In bivariate analyses, increasing levels of area poverty, low education, unemployment, and foreclosures were associated with lower odds of adherence to CRCS. After controlling for individual-level covariates, only tract-level unemployment remained associated with adherence to CRCS (adjusted OR=0.80; 95% CI: 0.66-0.99; P=.037). CONCLUSIONS: Neighborhood socioeconomic disadvantage is increasingly recognized as a determinant of health, and our study suggests that the contextual effect of area unemployment may extend to cancer screening outcomes. Our finding is important to cancer control planners because we identified a contextual marker of disparity that can be used to target local interventions to promote CRCS and thereby reduce cancer disparities among non-adherent individuals who reside in communities with high unemployment rates.

Houston's Novel Strategy to Control Hazardous Air Pollutants: A Case Study in Policy Innovation and Political Stalemate.

Although ambient concentrations have declined steadily over the past 30 years, Houston has recorded some of the highest levels of hazardous air pollutants in the United States. Nevertheless, federal and state regulatory efforts historically have emphasized compliance with the National Ambient Air Quality Standard for ozone, treating "air toxics" in Houston as a residual problem to be solved through application of technology-based standards. Between 2004 and 2009, Mayor Bill White and his administration challenged the well-established hierarchy of air quality management spelled out in the Clean Air Act, whereby federal and state authorities are assigned primacy over local municipalities for the purpose of designing and implementing air pollution control strategies. The White Administration believed that existing regulations were not sufficient to protect the health of Houstonians and took a diversity of both collaborative and combative policy actions to mitigate air toxic emissions from stationary sources. Opposition was substantial from a local coalition of entrenched interests satisfied with the status quo, which hindered the city's attempts to take unilateral policy actions. In the short term, the White Administration successfully raised the profile of the air toxics issue, pushed federal and state regulators to pay more attention, and induced a few polluting facilities to reduce emissions. But since White left office in 2010, air quality management in Houston has returned to the way it was before, and today there is scant evidence that his policies have had any lasting impact.

Predictors of Serious Psychological Distress in an Urban Population.

While there are state and national estimates of serious psychological distress (SPD), these are not useful for targeting local mental health interventions or for addressing the needs of sub-populations at increased risk for SPD. This cross-sectional study uses data from the population-based 2010 Health of Houston Survey (n = 5,116) to examine (1) the prevalence of SPD and its determinants in Houston area and (2) predictors of the utilization of mental health services among people with SPD. The prevalence of SPD among the Houston area adult population was 7 %, more than twice the national average. Correlates of SPD included: being female, under 65, lacking emotional support, smoking, having poor health status and financial distress. The odds of utilizing health services by those with SPD were affected by financial distress, insurance, employment and perceived need for services, among other factors. Interventions should be tailored to mitigate risk factors for SPD and to improve access to mental health services in the SPD sub-population.

Social Determinants of Health in Environmental Justice Communities: Examining Cumulative Risk in Terms of Environmental Exposures and Social Determinants of Health.

Residents of environmental justice (EJ) communities may bear a disproportionate burden of environmental health risk, and often face additional burdens from social determinants of health. Accounting for cumulative risk should include measures of risk from both environmental sources and social determinants. This study sought to better understand cumulative health risk from both social and environmental sources in a disadvantaged community in Texas. Key outcomes were determining what data are currently available for this assessment, clarifying data needs, identifying data gaps, and considering how those gaps could be filled. Analyses suggested that the traditionally defined EJ community in Port Arthur may have a lower environmental risk from air toxics than the rest of the City of Port Arthur (although the entire city has a higher risk than the average for the state), but may have a larger burden from social determinants of health. However, the results should be interpreted in light of the availability of data, the definitions of community boundaries, and the areal unit utilized. Continued focus on environmental justice communities and the cumulative risks faced by their residents is critical to protecting these residents and, ultimately, moving towards a more equitable distribution and acceptable level of risk throughout society.