State-Level Firearm Laws and Firearm Homicide in US Cities: Heterogenous Associations by City Characteristics.

Despite well-studied associations of state firearm laws with lower state- and county-level firearm homicide, there is a shortage of studies investigating differences in the effects of distinct state firearm law categories on various cities within the same state using identical methods. We examined associations of 5 categories of state firearm laws-pertaining to buyers, dealers, domestic violence, gun type/trafficking, and possession-with city-level firearm homicide, and then tested differential associations by city characteristics. City-level panel data on firearm homicide cases of 78 major cities from 2010 to 2020 was assessed from the Centers for Disease Control and Prevention's National Vital Statistics System. We modeled log-transformed firearm homicide rates as a function of firearm law scores, city, state, and year fixed effects, along with time-varying city-level confounders. We considered effect measure modification by poverty, unemployment, vacant housing, and income inequality. A one z-score increase in state gun type/trafficking, possession, and dealer law scores was associated with 25% (95% confidence interval [CI]:-0.37,-0.1), 19% (95% CI:-0.29,-0.07), and 17% (95% CI:-0.28, -0.4) lower firearm homicide rates, respectively. Protective associations were less pronounced in cities with high unemployment and high housing vacancy, but more pronounced in cities with high income inequality. In large US cities, state-level gun type/trafficking, possession, and dealer laws were associated with lower firearm homicide rates, but buyers and domestic violence laws were not. State firearm laws may have differential effects on firearm homicides based on city characteristics, and city-wide policies to enhance socioeconomic drivers may add benefits of firearm laws.

Associations between a Novel Measure of Census Tract-Level Credit Insecurity and Frequent Mental Distress in US Urban Areas, 2020.

Access to and utilization of consumer credit remains an understudied social determinant of health. We examined associations between a novel, small-area, multidimensional credit insecurity index (CII), and the prevalence of self-reported frequent mental distress across US cities in 2020. The census tract-level CII was developed by the Federal Reserve Bank of New York using Census population information and a nationally representative sample of anonymized Equifax credit report data. The CII was calculated for tracts in 766 cities displayed on the City Health Dashboard at the time of analysis, predominantly representing cities with over 50,000 residents. The CII combined data on tract-level participation in the formal credit economy with information on the percent of individuals without revolving credit, percent with high credit utilization, and percent with deep subprime credit scores. Tracts were classified as credit-assured, credit-likely, mid-tier, at-risk, or credit-insecure. We used linear regression to examine associations between the CII and a modeled tract-level measure of frequent mental distress, obtained from the CDC PLACES project. Regression models were adjusted for neighborhood economic and demographic characteristics. We examined effect modification by US region by including two-way interaction terms in regression models. In adjusted models, credit-insecure tracts had a modestly higher prevalence of frequent mental distress (prevalence difference = 0.38 percentage points; 95% CI = 0.32, 0.44), compared to credit-assured tracts. Associations were most pronounced in the Midwest. Local factors impacting credit access and utilization are often modifiable. The CII, a novel indicator of community financial well-being, may be an independent predictor of neighborhood health in US cities and could illuminate policy targets to improve access to desirable credit products and downstream health outcomes.

Building Public Health Surveillance 3.0: Emerging Timely Measures of Physical, Economic, and Social Environmental Conditions Affecting Health.

In response to rapidly changing societal conditions stemming from the COVID-19 pandemic, we summarize data sources with potential to produce timely and spatially granular measures of physical, economic, and social conditions relevant to public health surveillance, and we briefly describe emerging analytic methods to improve small-area estimation. To inform this article, we reviewed published systematic review articles set in the United States from 2015 to 2020 and conducted unstructured interviews with senior content experts in public heath practice, academia, and industry. We identified a modest number of data sources with high potential for generating timely and spatially granular measures of physical, economic, and social determinants of health. We also summarized modeling and machine-learning techniques useful to support development of time-sensitive surveillance measures that may be critical for responding to future major events such as the COVID-19 pandemic. (Am J Public Health. 2022;112(10):1436-1445. https://doi.org/10.2105/AJPH.2022.306917).

Community Health Worker Intervention in Subsidized Housing: New York City, 2016-2017.

From April 2016 to June 2017, the Health + Housing Project employed four community health workers who engaged residents of two subsidized housing buildings in New York City to address individuals' broadly defined health needs, including social and economic risk factors. Following the intervention, we observed significant improvements in residents' food security, ability to pay rent, and connection to primary care. No immediate change was seen in acute health care use or more narrowly defined health outcomes.

Health and Health Determinant Metrics for Cities: A Comparison of County and City-Level Data.

We evaluated whether using county-level data to characterize public health measures in cities biases the characterization of city populations. We compared 4 public health and sociodemographic measures in 447 US cities (percent of children living in poverty, percent of non-Hispanic Black population, age-adjusted cardiovascular disease mortality, life expectancy at birth) to the same measures calculated for counties that contain those cities. We found substantial and highly variable city-county differences within and across metrics, which suggests that use of county data to proxy city measures could hamper accurate allocation of public health resources and appreciation of the urgency of public health needs in specific locales.

Extended-Release Naltrexone to Prevent Opioid Relapse in Criminal Justice Offenders.

BACKGROUND: Extended-release naltrexone, a sustained-release monthly injectable formulation of the full mu-opioid receptor antagonist, is effective for the prevention of relapse to opioid dependence. Data supporting its effectiveness in U.S. criminal justice populations are limited. METHODS: In this five-site, open-label, randomized trial, we compared a 24-week course of extended-release naltrexone (Vivitrol) with usual treatment, consisting of brief counseling and referrals for community treatment programs, for the prevention of opioid relapse among adult criminal justice offenders (i.e., persons involved in the U.S. criminal justice system) who had a history of opioid dependence and a preference for opioid-free rather than opioid maintenance treatments and who were abstinent from opioids at the time of randomization. The primary outcome was the time to an opioid-relapse event, which was defined as 10 or more days of opioid use in a 28-day period as assessed by self-report or by testing of urine samples obtained every 2 weeks; a positive or missing sample was computed as 5 days of opioid use. Post-treatment follow-up occurred at weeks 27, 52, and 78. RESULTS: A total of 153 participants were assigned to extended-release naltrexone and 155 to usual treatment. During the 24-week treatment phase, participants assigned to extended-release naltrexone had a longer median time to relapse than did those assigned to usual treatment (10.5 vs. 5.0 weeks, P<0.001; hazard ratio, 0.49; 95% confidence interval [CI], 0.36 to 0.68), a lower rate of relapse (43% vs. 64% of participants, P<0.001; odds ratio, 0.43; 95% CI, 0.28 to 0.65), and a higher rate of opioid-negative urine samples (74% vs. 56%, P<0.001; odds ratio, 2.30; 95% CI, 1.48 to 3.54). At week 78 (approximately 1 year after the end of the treatment phase), rates of opioid-negative urine samples were equal (46% in each group, P=0.91). The rates of other prespecified secondary outcome measures--self-reported cocaine, alcohol, and intravenous drug use, unsafe sex, and reincarceration--were not significantly lower with extended-release naltrexone than with usual treatment. Over the total 78 weeks observed, there were no overdose events in the extended-release naltrexone group and seven in the usual-treatment group (P=0.02). CONCLUSIONS: In this trial involving criminal justice offenders, extended-release naltrexone was associated with a rate of opioid relapse that was lower than that with usual treatment. Opioid-use prevention effects waned after treatment discontinuation. (Funded by the National Institute on Drug Abuse; ClinicalTrials.gov number, NCT00781898.).

City-Level Measures of Health, Health Determinants, and Equity to Foster Population Health Improvement: The City Health Dashboard.

OBJECTIVES: To support efforts to improve urban population health, we created a City Health Dashboard with area-specific data on health status, determinants of health, and equity at city and subcity (census tract) levels. METHODS: We developed a Web-based resource that includes 37 metrics across 5 domains: social and economic factors, physical environment, health behaviors, health outcomes, and clinical care. For the largest 500 US cities, the Dashboard presents metrics calculated to the city level and, where possible, subcity level from multiple data sources, including national health surveys, vital statistics, federal administrative data, and state education data sets. RESULTS: Iterative input from city partners shaped Dashboard development, ensuring that measures can be compared across user-selected cities and linked to evidence-based policies to spur action. Reports from early deployment indicate that the Dashboard fills an important need for city- and subcity-level data, fostering more granular understanding of health and its drivers and supporting associated priority-setting. CONCLUSIONS: By providing accessible city-level data on health and its determinants, the City Health Dashboard complements local surveillance efforts and supports urban population health improvement on a national scale.

Evaluation of the Substance Abuse Research and Education Training (SARET) program: Stimulating health professional students to pursue careers in substance use research.

BACKGROUND: We developed and implemented the Substance Abuse Research Education and Training (SARET) program for medical, dental, nursing, and social work students to address the dearth of health professionals pursuing research and careers in substance use disorders (SUD). SARET has 2 main components: (1) a novel online curriculum addressing core SUD research topics, to reach a large number of students; (2) a mentored summer research experience for in-depth exposure. METHODS: Modules were integrated into the curricula of the lead institution, and of 5 external schools. We assessed the number of Web modules completed and their effect on students' interest in SUD research. We also assessed the impact of the mentorship experience on participants' attitudes and early career trajectories, including current involvement in SUD research. RESULTS: Since 2008, over 24,000 modules have been completed by approximately 9700 individuals. In addition to integration of the modules into curricula at the lead institution, all 5 health-professional partner schools integrated at least 1 module and approximately 5500 modules were completed by individuals outside the lead institution. We found an increase in interest in SUD research after completion of the modules for students in all 4 disciplines. From 2008 to 2015, 76 students completed summer mentorships; 8 students completed year-long mentorships; 13 published in SUD-related journals, 18 presented at national conferences, and 3 are actively engaged in SUD-related research. Mentorship participants reported a positive influence on their attitudes towards SUD-related clinical care, research, and interprofessional collaboration, leading in some cases to changes in career plans. CONCLUSIONS: A modular curriculum that stimulates clinical and research interest in SUD can be successfully integrated into medical, dental, nursing, and social work curricula. The SARET program of mentored research participation fostered early research successes and influenced career choice of some participants. Longer-term follow-up will enable us to assess more distal careers of the program.

Integration and Evaluation of Substance Abuse Research Education Training (SARET) into a Master of Social Work program.

BACKGROUND: The Substance Abuse Research and Education Training (SARET) program is funded by the National Institutes of Drug Abuse in 2006 as a novel approach to spark interest in substance abuse research among medical, dental, nursing, and social work graduate students through a Web-based curriculum and research mentorships. This report presents the initial integration of the intervention in a Master of Social Work (MSW) program, the components of the program, and the mixed-methods evaluation of its effect on students' attitudes towards substance abuse research and treatment. METHODS: SARET comprises 2 main components: stipend-supported research mentorships and a Web-based module series, consisting of 6 interactive, multimedia modules addressing core SA research topics, delivered via course curricula and in the research mentorships. An initial evaluation was designed to assess SARET's acceptability and short-term impact on participants' interest in SA research. The components of this Web-based curriculum evaluation include focus group feedback on the relevance of the modules to SW students, number of courses into which the modules were integrated with number of module completions, changes in interest in SA research associated with module completion. RESULTS: The full series of Web-based modules has been integrated across several courses in the social work curriculum, and social work students have become integral participants in the summer mentored research experience. One hundred eighteen students completed at least 1 module and 42 students completed all 6 modules. Neurobiology, Screening, and Epidemiology were the most widely viewed modules. Students reported positive impact on their vision of SA-related clinical care, more positive attitudes about conducting research, and in some cases, change in career. CONCLUSIONS: The SARET program's modules and summer mentored research increased clinical and research interest related to SUDs, as well as interprofessional attitudes among social work students. Participants have shown some early research success. Longer-term follow-up will enable us to continue to assess the effectiveness of the program.

Impact of an Intervention to Improve Weekend Hospital Care at an Academic Medical Center: An Observational Study.

BACKGROUND: Hospital care on weekends has been associated with delays in care, reduced quality, and poor clinical outcomes. OBJECTIVE: The purpose of this study was to evaluate the impact of a weekend hospital intervention on processes of care and clinical outcomes. The multifaceted intervention included expanded weekend diagnostic services, improved weekend discharge processes, and increased physician and care management services on weekends. DESIGN AND PATIENTS: This was an interrupted time series observational study of adult non-obstetric patients hospitalized at a single academic medical center between January 2011 and January 2014. The study included 18 months prior to and 19 months following the implementation of the intervention. Data were analyzed using segmented regression analysis with adjustment for confounders. MAIN MEASURES: The primary outcome was average length of stay. Secondary outcomes included percent of patients discharged on weekends, 30-day readmission rate, and in-hospital mortality rate. KEY RESULTS: The study included 57,163 hospitalizations. Following implementation of the intervention, average length of stay decreased by 13 % (95 % CI 10-15 %) and continued to decrease by 1 % (95 % CI 1-2 %) per month as compared to the underlying time trend. The proportion of weekend discharges increased by 12 % (95 % CI 2-22 %) at the time of the intervention and continued to increase by 2 % (95 % CI 1-3 %) per month thereafter. The intervention had no impact on readmissions or mortality. During the post-implementation period, the hospital was evacuated and closed for 2 months due to damage from Hurricane Sandy, and a new hospital-wide electronic health record was introduced. The contributions of these events to our findings are not known. We observed a lower inpatient census and found differences in patient characteristics, including higher rates of Medicaid insurance and comorbidities, in the post-Hurricane Sandy period as compared to the pre-Sandy period. CONCLUSIONS: The intervention was associated with a reduction in length of stay and an increase in weekend discharges. Our longitudinal study also illuminated the challenges of evaluating the effectiveness of a large-scale intervention in a real-world hospital setting.

Syndemic vulnerability, sexual and injection risk behaviors, and HIV continuum of care outcomes in HIV-positive injection drug users.

Limited investigations have been conducted on syndemics and HIV continuum of care outcomes. Using baseline data from a multi-site, randomized controlled study of HIV-positive injection drug users (n = 1,052), we examined whether psychosocial factors co-occurred, and whether these factors were additively associated with behavioral and HIV continuum of care outcomes. Experiencing one type of psychosocial problem was significantly (p < 0.05) associated with an increased odds of experiencing another type of problem. Persons with 3 or more psychosocial problems were significantly more likely to report sexual and injection risk behaviors and were less likely to be adherent to HIV medications. Persons with 4 or more problems were less likely to be virally suppressed. Reporting any problems was associated with not currently taking HIV medications. Our findings highlight the association of syndemics not only with risk behaviors, but also with outcomes related to the continuum of care for HIV-positive persons.

The relationship between primary prescription opioid and buprenorphine-naloxone induction outcomes in a prescription opioid dependent sample.

BACKGROUND AND OBJECTIVES: This analysis aims to: (1) compare induction experiences among participants who self-reported using one of the four most commonly reported POs, and (2) examine factors associated with difficult bup-nx induction. Our hypothesis, based on previous research and current guidelines, is that those on longer-acting opioids will have experienced more difficult inductions. METHODS: The Prescription Opioid Addiction Treatment Study (POATS) was a multi-site, randomized clinical trial, using a two-phase adaptive treatment research design. This analysis examines bup-nx induction of participants who self-reported primary PO use of methadone, ER-oxycodone, IR-oxycodone, and hydrocodone (n = 69). Analyses examined characteristics associated with difficult induction, defined as increased withdrawal symptoms measured by the Clinical Opiate Withdrawal Scale (COWS) after the first bup-nx dose with higher scores denoting greater withdrawal symptoms/severity. RESULTS: Contrary to our hypothesis, difficult induction experiences did not differ by primary PO type. Those who experienced a post-induction increase in COWS score had lower pre-dose COWS scores compared to those who did not experience a post-induction increase in COWS score (10.09 vs. 12.77, t(624) = -13.56, p < .001). Demographics characteristics, depression, and pain history did not predict a difficult induction. CONCLUSIONS AND SCIENTIFIC SIGNIFICANCE: Difficult bup-nx inductions were not associated with participants' primary PO. Severity of withdrawal, measured with the COWS, was an important variable, reminding clinicians that bup-nx should not be commenced prior to evidence of moderate opioid withdrawal. These findings add to the evidence that with careful procedures, bup-nx can used with few difficulties in PO-dependent patients. (Am J Addict 2014;23:343-348).

Association of weekend continuity of care with hospital length of stay.

OBJECTIVE: The purpose of this study was to evaluate the association of physician continuity of care with length of stay, likelihood of weekend discharge, in-hospital mortality and 30-day readmission. DESIGN: A cohort study of hospitalized medical patients. The primary exposure was the weekend usual provider continuity (UPC) over the initial weekend of care. This metric was adapted from an outpatient continuity of care index. Regression models were developed to determine the association between UPC and outcomes. SETTING: An academic medical center. MAIN OUTCOME MEASURE: Length of stay which was calculated as the number of days from the first Saturday of the hospitalization to the day of discharge. RESULTS: Of the 3391 patients included in this study, the prevalence of low, moderate and high UPC for the initial weekend of hospitalization was 58.7, 22.3 and 19.1%, respectively. When compared with low continuity of care, both moderate and high continuity of care were associated with reduced length of stay, with adjusted rate ratios of 0.92 (95% CI 0.86-1.00) and 0.64 (95% CI 0.53-0.76), respectively. High continuity of care was associated with likelihood of weekend discharge (adjusted odds ratio 2.84, 95% CI 2.11-3.83) but was not significantly associated with mortality (adjusted odds ratio 0.72, 95% CI 0.29-1.80) or readmission (adjusted odds ratio 0.88, 95% CI 0.68-1.14) when compared with low continuity of care. CONCLUSIONS: Increased weekend continuity of care is associated with reduced length of stay. Improvement in weekend cross-coverage and patient handoffs may be useful to improve clinical outcomes.

How patients understand the term "nonmedical use" of prescription drugs: insights from cognitive interviews.

BACKGROUND: With rising rates of prescription drug abuse and associated overdose deaths, there is great interest in having accurate and efficient screening tools that identify nonmedical use of prescription drugs in health care settings. The authors sought to gain a better understanding of how patients interpret questions about misuse of prescription drugs, with the goal of improving the accuracy and acceptability of instruments intended for use in primary care. METHODS: A total of 27 English-speaking adult patients were recruited from an urban safety net primary care clinic to complete a cognitive interview about a 4-item screening questionnaire for tobacco, alcohol, illicit drugs, and misuse of prescription drugs. Detailed field notes were analyzed for overall comprehension of the screening items on illicit drug use and prescription drug misuse, the accuracy with which participants classified drugs into these categories, and whether the screening response correctly captured the participant's substance use behavior. RESULTS: Based on initial responses to the screening items, 6 (22%) participants screened positive for past-year prescription drug misuse, and 8 (30%) for illicit drug use. The majority (26/27) of participants correctly interpreted the item on illicit drug use, and appropriately classified drugs in this category. Eleven (41%) participants had errors in their understanding of the prescription drug misuse item. The most common error was classifying use of medications without abuse potential as nonmedical use. All cases of misunderstanding the prescription drug misuse item occurred among participants who screened negative for illicit drug use. CONCLUSIONS: The results suggest that terminology used to describe misuse of prescription medications may be misunderstood by many primary care patients, particularly those who do not use illicit drugs. Failure to improve upon the language used to describe prescription drug misuse in screening questionnaires intended for use in medical settings could potentially lead to high rates of false-positive results.

Health and Equity Data to Teach the Next Generation of Public Health Leaders.

The COVID-19 pandemic restructured university learning environments while also underscoring the need for granular local health data. We describe how the University of Memphis School of Public Health used the City Health Dashboard, an online resource providing data at the city and neighborhood level for more than 35 measures of health outcomes, health drivers, and health equity for all US cities with populations >50 000, to enrich students' learning of applying data to community health policy. By facilitating students' engagement with population needs, assets, and capacities that affect communities' health-key components of the master of public health accreditation process-the Dashboard supports in-person and virtual learning at undergraduate and graduate levels and is recommended as a novel and rigorous data source for public health trainees.

Life Expectancy and Built Environments in the U.S.: A Multilevel Analysis.

INTRODUCTION: The purpose of this study is to examine the associations between built environments and life expectancy across a gradient of urbanicity in the U.S. METHODS: Census tract‒level estimates of life expectancy between 2010 and 2015, except for Maine and Wisconsin, from the U.S. Small-Area Life Expectancy Estimates Project were analyzed in 2022. Tract-level measures of the built environment included: food, alcohol, and tobacco outlets; walkability; park and green space; housing characteristics; and air pollution. Multilevel linear models for each of the 4 urbanicity types were fitted to evaluate the associations, adjusting for population and social characteristics. RESULTS: Old housing (built before 1979) and air pollution were important built environment predictors of life expectancy disparities across all gradients of urbanicity. Convenience stores were negatively associated with life expectancy in all urbanicity types. Healthy food options were a positive predictor of life expectancy only in high-density urban areas. Park accessibility was associated with increased life expectancy in all areas, except rural areas. Green space in neighborhoods was positively associated with life expectancy in urban areas but showed an opposite association in rural areas. CONCLUSIONS: After adjusting for key social characteristics, several built environment characteristics were salient risk factors for decreased life expectancy in the U.S., with some measures showing differential effects by urbanicity. Planning and policy efforts should be tailored to local contexts.

Validation of a geospatial aggregation method for congressional districts and other US administrative geographies.

Stakeholders need data on health and drivers of health parsed to the boundaries of essential policy-relevant geographies. US Congressional Districts are an example of a policy-relevant geography which generally lack health data. One strategy to generate Congressional District heath data metric estimates is to aggregate estimates from other geographies, for example, from counties or census tracts to Congressional Districts. Doing so requires several methodological decisions. We refine a method to aggregate health metric estimates from one geography to another, using a population weighted approach. The method's accuracy is evaluated by comparing three aggregated metric estimates to metric estimates from the US Census American Community Survey for the same years: Broadband Access, High School Completion, and Unemployment. We then conducted four sensitivity analyses testing: the effect of aggregating counts vs. percentages; impacts of component geography size and data missingness; and extent of population overlap between component and target geographies. Aggregated estimates were very similar to estimates for identical metrics drawn directly from the data source. Sensitivity analyses suggest the following best practices for Congressional district-based metrics: utilizing smaller, more plentiful geographies like census tracts as opposed to larger, less plentiful geographies like counties, despite potential for less stable estimates in smaller geographies; favoring geographies with higher percentage population overlap.

The challenge of attribution: responsibility for population health in the context of accountable care.

One of the 3 goals for accountable care organizations is to improve population health. This will require that accountable care organizations bridge the schism between clinical care and public health. But do health care delivery organizations and public health agencies share a concept of "population"? We think not: whereas delivery systems define populations in terms of persons receiving care, public health agencies typically measure health on the basis of geography. This creates an attribution problem, particularly in large urban centers, where multiple health care providers often serve any given neighborhood. We suggest potential innovations that could allow urban accountable care organizations to accept accountability, and rewards, for measurably improving population health.