Spatial Heterogeneity in Fatal Overdose Rate Trends in Mexican Cities: 2005-2021.

Objectives. To describe national and city-level fatal drug overdose trends between 2005 and 2021 in Mexico. Methods. We calculated fatal overdose rates at the city level in 3-year periods from 2005 to 2021 and annually at the national level for people aged 15 to 64 years in Mexico. We calculated rate differences and rate ratios for each city between periods. Results. The national fatal overdose rate was 0.53 overdose deaths per 100 000 population and was almost twice as high in urban than in nonurban areas. The national fatal overdose rate was stable over the period 2005 to 2014 and increased monotonically to a peak in 2021. Fatal overdose rates varied across cities. Cities with the 8 highest fatal overdose rates in the period were all in states along the US-Mexico border. Conclusions. Fatal overdoses have doubled over the past 15 years in Mexico. Overdose rates are particularly high and increasing in cities close to the US-Mexico border. Public Health Implications. There is a need for enhanced overdose surveillance data and coordinated harm reduction strategies, particularly in the northern border region of Mexico. (Am J Public Health. 2024;114(7):705-713. https://doi.org/10.2105/AJPH.2024.307650).

Participatory Systems Thinking to Elucidate Drivers of Food Access and Diet Disparities among Minoritized Urban Populations.

The purpose of this study was to use participatory systems thinking to develop a dynamic conceptual framework of racial/ethnic and other intersecting disparities (e.g., income) in food access and diet in Philadelphia and to identify policy levers to address these disparities. We conducted three group model building workshops, each consisting of a series of scripted activities. Key artifacts or outputs included qualitative system maps, or causal loop diagrams, identifying the variables, relationships, and feedback loops that drive diet disparities in Philadelphia, Pennsylvania. We used semi-structured methods informed by inductive thematic analysis and network measures to synthesize findings into a single causal loop diagram. There were twenty-nine participants with differing vantages and expertise in Philadelphia's food system, broadly representing the policy, community, and research domains. In the synthesis model, participants identified 14 reinforcing feedback loops and one balancing feedback loop that drive diet and food access disparities in Philadelphia. The most highly connected variables were upstream factors, including those related to racism (e.g., residential segregation) and community power (e.g., community land control). Consistent with existing frameworks, addressing disparities will require a focus on upstream social determinants. However, existing frameworks should be adapted to emphasize and disrupt the interdependent, reinforcing feedback loops that maintain and exacerbate disparities in fundamental social causes. Our findings suggest that promising policies include those that empower minoritized communities, address socioeconomic inequities, improve community land control, and increase access to affordable, healthy, and culturally meaningful foods.

Associated factors to non-medical and medical use of psychoactive medication among Mexican adolescents and adults in a national household survey.

BACKGROUND: Non-medical use of psychoactive medication is a public health problem. Studies in other contexts indicate that individual sociodemographic characteristics are associated with non-medical use, but these associations have not been assessed in the Mexican context. OBJECTIVES: To estimate the prevalence non-medical and medical use of psychoactive medication among Mexican adolescents and adults' medication users and to estimate the associations between sociodemographic characteristics and non-medical use of psychoactive medication, using data from a nationally representative sample. METHODS: Secondary analysis of data collected from the National Survey of Drug, Alcohol, and Tobacco Consumption (ENCODAT) 2016 to 2017. The analytical sample included people aged 12 to 65 years. The sample was stratified into two age categories: adolescents (12-17 years) and adults (18-65 years). Sub-analyses were performed to describe prevalence of use and non-medical use of psychoactive medication at the state-level. Descriptive statistics and multinomial logistic regression models were used to estimate associations between sociodemographic characteristics and medical, non-medical, and non-use of psychoactive medication in adolescents and adults. RESULTS: Among Mexican medication users in 2016, the national prevalence of non-medical use of psychoactive drugs was 19.6%; 22.2% among adolescents and 19.4% among adults. States adjacent to the US-Mexico border reported the highest levels of non-medical use of psychoactive medication. Illicit drug consumption was associated with non-medical use. Sociodemographic characteristics associated with non-medical use varied between adolescents and adults. CONCLUSIONS: There is a high proportion of non-medical use of psychoactive drugs among Mexican medication users, especially among young people. Understanding factors associated with the misuse of psychoactive medications in Mexico can inform policy for prevention and treatment.

Linking Data on Constituent Health with Elected Officials' Opinions: Associations Between Urban Health Disparities and Mayoral Officials' Beliefs About Health Disparities in Their Cities.

Policy Points Mayoral officials' opinions about the existence and fairness of health disparities in their city are positively associated with the magnitude of income-based life expectancy disparity in their city. Associations between mayoral officials' opinions about health disparities in their city and the magnitude of life expectancy disparity in their city are not moderated by the social or fiscal ideology of mayoral officials or the ideology of their constituents. Highly visible and publicized information about mortality disparities, such as that related to COVID-19 disparities, has potential to elevate elected officials' perceptions of the severity of health disparities and influence their opinions about the issue. CONTEXT: A substantive body of research has explored what factors influence elected officials' opinions about health issues. However, no studies have assessed the potential influence of the health of an elected official's constituents. We assessed whether the magnitude of income-based life expectancy disparity within a city was associated with the opinions of that city's mayoral official (i.e., mayor or deputy mayor) about health disparities in their city. METHODS: The independent variable was the magnitude of income-based life expectancy disparity in US cities. The magnitude was determined by linking 2010-2015 estimates of life expectancy and median household income for 8,434 census tracts in 224 cities. The dependent variables were mayoral officials' opinions from a 2016 survey about the existence and fairness of health disparities in their city (n = 224, response rate 30.3%). Multivariable logistic regression was used to adjust for characteristics of mayoral officials (e.g., ideology) and city characteristics. FINDINGS: In cities in the highest income-based life expectancy disparity quartile, 50.0% of mayoral officials "strongly agreed" that health disparities existed and 52.7% believed health disparities were "very unfair." In comparison, among mayoral officials in cities in the lowest disparity quartile 33.9% "strongly agreed" that health disparities existed and 22.2% believed the disparities were "very unfair." A 1-year-larger income-based life expectancy disparity in a city was associated with 25% higher odds that the city's mayoral official would "strongly agree" that health disparities existed (odds ratio [OR] = 1.25; P = .04) and twice the odds that the city's mayoral official would believe that such disparities were "very unfair" (OR = 2.24; P <.001). CONCLUSIONS: Mayoral officials' opinions about health disparities in their jurisdictions are generally aligned with, and potentially influenced by, information about the magnitude of income-based life expectancy disparities among their constituents.

Big City Health Officials' Conceptualizations of Health Equity.

CONTEXT: Senior health officials of local health departments are uniquely positioned to provide transformational leadership on health disparities and inequities. OBJECTIVE: This study aimed to understand how senior health officials in large US cities define health equity and its relationship with disparities and characterize these senior health officials' perceptions of using health equity and disparity language in local public health practice. DESIGN: In 2016, we used a general inductive qualitative design and conducted 23 semistructured interviews with leaders of large local health departments. Thematic content analysis was conducted using NVivo 11. PARTICIPANTS: A purposive sample of senior health officials from Big Cities Health Coalition cities. RESULTS: Health equity was conceptualized fairly consistently among senior health officials in big cities. Core elements of these conceptualizations include social and economic conditions, the input and redistribution of resources, equity in practice, values of justice and fairness, and equity as an outcome to be achieved. Senior health officials saw health disparity and health inequity as distinct but related concepts. Relationships between concepts included disparities data to identify and prioritize inequities, inequities creating health disparities, health equity to eliminate disparities, and disparities becoming inequities when their root causes are unjust. Some respondents critiqued health equity terminology for representing a superficial change, being inaccessible, and being politically loaded. CONCLUSIONS: Understanding how senior health officials conceptualize health equity and disparities can focus policy priorities, resources, and the scope of work undertaken by local health departments. Having a common language for health equity allows for policy and resource advocacy to promote the health of marginalized populations.

US Mayors' and Health Commissioners' Opinions About Health Disparities in Their Cities.

OBJECTIVES: To characterize US mayors' and health commissioners' opinions about health disparities in their cities and identify factors associated with these opinions. METHODS: We conducted a multimodal survey of mayors and health commissioners in fall-winter 2016 (n = 535; response rate = 45.2%). We conducted bivariate analyses and multivariable logistic regression. RESULTS: Forty-two percent of mayors and 61.1% of health commissioners strongly agreed that health disparities existed in their cities. Thirty percent of mayors and 8.0% of health commissioners believed that city policies could have little or no impact on disparities. Liberal respondents were more likely than were conservative respondents to strongly agree that disparities existed (mayors: odds ratio [OR] = 7.37; 95% confidence interval [CI] = 3.22, 16.84; health commissioners: OR = 5.09; 95% CI = 3.07, 8.46). In regression models, beliefs that disparities existed, were avoidable, and were unfair were independently associated with the belief that city policies could have a major impact on disparities. CONCLUSIONS: Many mayors, and some health commissioners, are unaware of the potential of city policies to reduce health disparities. Ideology is strongly associated with opinions about disparities among these city policymakers. Public Health Implications: Information about health disparities, and policy strategies to reduce them, needs to be more effectively communicated to city policymakers.

Methods and measures to evaluate the impact of participatory model building on public policymakers: a scoping review protocol.

INTRODUCTION: Public policymakers are increasingly engaged in participatory model building processes, such as group model building. Understanding the impacts of policymaker participation in these processes on policymakers is important given that their decisions often have significant influence on the dynamics of complex systems that affect health. Little is known about the extent to which the impacts of participatory model building on public policymakers have been evaluated or the methods and measures used to evaluate these impacts. METHODS AND ANALYSIS: A scoping review protocol was developed with the objectives of: (1) scoping studies that have evaluated the impacts of facilitated participatory model building processes on public policymakers who participated in these processes; and (2) describing methods and measures used to evaluate impacts and the main findings of these evaluations. The Joanna Briggs Institute's Population, Concept, Context framework was used to formulate the article identification process. Seven electronic databases-MEDLINE (Ovid), ProQuest Health and Medical, Scopus, Web of Science, Embase (Ovid), CINAHL Complete and PsycInfo-will be searched. Identified articles will be screened according to inclusion and exclusion criteria and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist for scoping reviews will be used and reported. A data extraction tool will collect information across three domains: study characteristics, methods and measures, and findings. The review will be conducted using Covidence, a systematic review data management platform. ETHICS AND DISSEMINATION: The scoping review produced will generate an overview of how public policymaker engagement in participatory model building processes has been evaluated. Findings will be disseminated through peer-reviewed publications and to communities of practice that convene policymakers in participatory model building processes. This review will not require ethics approval because it is not human subject research.

Use of qualitative systems mapping and causal loop diagrams to understand food environments, diet and obesity: a scoping review protocol.

INTRODUCTION: Food systems can shape dietary behaviour and obesity outcomes in complex ways. Qualitative systems mapping using causal loop diagrams (CLDs) can depict how people understand the complex dynamics, inter-relationships and feedback characteristic of food systems in ways that can support policy planning and action. To date, there has been no attempt to review this literature. The objectives of this review are to scope the extent and nature of studies using qualitative systems mapping to facilitate the development of CLDs by stakeholders to understand food environments, including settings and populations represented, key findings and the methodological processes employed. It also seeks to identify gaps in knowledge and implications for policy and practice. METHODS AND ANALYSIS: This protocol describes a scoping review guided by the Joanna Briggs Institute manual, the framework by Khalil and colleagues and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist reporting guidelines. A search strategy was iteratively developed with two academic librarians and the research team. This strategy will be used to search six databases, including Ovid MEDLINE, Embase, EmCare, Web of Science, Scopus and ProQuest Central. Identified citations will be screened by two independent reviewers; first, by title and abstract, and then full-text articles to identify papers eligible for inclusion. The reference lists of included studies and relevant systematic reviews will be searched to identify other papers eligible for inclusion. Two reviewers will extract information from all included studies and summarise the findings descriptively and numerically. ETHICS AND DISSEMINATION: The scoping review will provide an overview of how CLDs developed by stakeholders have been elicited to understand food environments, diet and obesity, the insights gained and how the CLDs have been used. It will also highlight gaps in knowledge and implications for policy and practice. The review will be disseminated through publication in an academic journal and conference presentations.

Urban scaling of opioid overdose deaths in the USA: a cross-sectional study in three periods between 2005 and 2017.

OBJECTIVES: To describe the association between population size, population growth and opioid overdose deaths-overall and by type of opioid-in US commuting zones (CZs) in three periods between 2005 and 2017. SETTINGS: 741 CZs covering the entirety of the US CZs are aggregations of counties based on commuting patterns that reflect local economies. PARTICIPANTS: We used mortality data at the county level from 2005 to 2017 from the National Center for Health Statistics. OUTCOME: Opioid overdose deaths were defined using underlying and contributory causes of death codes from the International Classification of Diseases, 10th revision (ICD-10). We used the underlying cause of death to identify all drug poisoning deaths. Contributory cause of death was used to classify opioid overdose deaths according to the three major types of opioid, that is, prescription opioids, heroin and synthetic opioids other than methadone. RESULTS: Opioid overdose deaths were disproportionally higher in largely populated CZs. A CZ with 1.0% larger population had 1.10%, 1.10%, and 1.16% higher opioid death count in 2005-2009, 2010-2014, and 2015-2017, respectively. This pattern was largely driven by a high number of deaths involving heroin and synthetic opioids, particularly in 2015-2017. Population growth over time was associated with lower age-adjusted opioid overdose mortality rate: a 1.0% increase in population over time was associated with 1.4% (95% CI: -2.8% to 0.1%), 4.5% (95% CI: -5.8% to -3.2%), and 1.2% (95% CI: -4.2% to 1.8%) lower opioid overdose mortality in 2005-2009, 2010-2014, and 2015-2017, respectively. The association between positive population growth and lower opioid mortality rates was stronger in larger CZs. CONCLUSIONS: Opioid overdose mortality in the USA was disproportionately higher in mid-sized and large CZs, particularly those affected by declines in population over time, regardless of the region where they are located.

Policy Makers' Priorities for Addressing Youth Substance Use and Factors That Influence Priorities.

OBJECTIVE: Understanding public policy makers' priorities for addressing youth substance use and the factors that influence these priorities can inform the dissemination and implementation of strategies that promote evidence-based decision making. This study characterized the priorities of policy makers in substance use agencies of U.S. states and counties for addressing youth substance use, the factors that influenced these priorities, and the differences in priorities and influences between state and county policy makers. METHODS: In 2020, a total of 122 substance use agency policy makers from 35 states completed a Web-based survey (response rate=22%). Respondents rated the priority of 14 issues related to youth substance use and the extent to which nine factors influenced these priorities. Data were analyzed as dichotomous and continuous variables and for state and county policy makers together and separately. RESULTS: The highest priorities for youth substance use were social determinants of substance use (87%), adverse childhood experiences and childhood trauma (85%), and increasing access to school-based substance use programs (82%). The lowest priorities were increasing access to naloxone for youths (49%), increasing access to medications for opioid use disorder among youths (49%), and deimplementing non-evidence-based youth substance use programs (41%). The factors that most influenced priorities were budget issues (80%) and state legislature (69%), federal (67%), and governor priorities (65%). Issues related to program implementation and deimplementation were significantly higher priorities for state than for county policy makers. CONCLUSIONS: These findings can inform the tailoring of dissemination and implementation strategies to account for the inner- and outer-setting contexts of substance use agencies.

Simulating the role of knowledge brokers in policy making in state agencies: An agent-based model.

OBJECTIVE: To model children's mental health policy making dynamics and simulate the impacts of knowledge broker interventions. DATA SOURCES: Primary data from surveys (n = 221) and interviews (n = 64) conducted in 2019-2021 with mental health agency (MHA) officials in state agencies. STUDY DESIGN: A prototype agent-based model (ABM) was developed using the PARTE (Properties, Actions, Rules, Time, Environment) framework and informed through primary data collection. In each simulation, a policy is randomly generated (salience weights: cost, contextual alignment, and strength of evidence) and discussed among agents. Agents are MHA officials and heterogenous in their properties (policy making power and network influence) and policy preferences (based on salience weights). Knowledge broker interventions add agents to the MHA social network who primarily focus on the policy's research evidence. DATA COLLECTION/EXTRACTION METHODS: A sequential explanatory mixed method approach was used. Descriptive and regression analyses were used for the survey data and directed content analysis was used to code interview data. Triangulated results informed ABM development. In the ABM, policy makers with various degrees of decision influence interact in a scale-free network before and after knowledge broker interventions. Over time, each decides to support or oppose a policy proposal based on policy salience weights and their own properties and interactions. The main outcome is an agency-level decision based on policy maker support. Each intervention and baseline simulation runs 250 times across 50 timesteps. PRINCIPAL FINDINGS: Surveys and interviews revealed that barriers to research use could be addressed by knowledge brokers. Simulations indicated that policy decision outcomes varied by policy making context within agencies. CONCLUSIONS: This is the first application of ABM to evidence-informed mental health policy making. Results suggest that the presence of knowledge brokers can: (1) influence consensus formation in MHAs, (2) accelerate policy decisions, and (3) increase the likelihood of evidence-informed policy adoption.

Evaluating the health effects of place-based slum upgrading physical environment interventions: A systematic review (2012-2018).

Rapid urbanization in low- and middle-income countries (LMIC) is associated with increasing population living in informal settlements. Inadequate infrastructure and disenfranchisement in settlements can create environments hazardous to health. Placed-based physical environment upgrading interventions have potential to improve environmental and economic conditions linked to health outcomes. Summarizing and assessing evidence of the impact of prior interventions is critical to motivating and selecting the most effective upgrading strategies moving forward. Scientific and grey literature were systematically reviewed to identify evaluations of physical environment slum upgrading interventions in LMICs published between 2012 and 2018. Thirteen evaluations that fulfilled inclusion criteria were reviewed. Quality of evaluations was assessed using an adapted Effective Public Health Practice Project Quality Assessment Tool for Quantitative Studies. Findings were then pooled with those published prior to 2012. Narrative analysis was performed. Of thirteen evaluations, eight used a longitudinal study design ("primary evaluations"). All primary evaluations were based in Latin America and included two housing, two transportation, and four comprehensive intervention evaluations. Three supporting evaluations assessed housing interventions in Argentina and South Africa; two assessed a comprehensive intervention in India. Effects by intervention-type included improvements in quality of life and communicable diseases after housing interventions, possible improvements in safety after transportation and comprehensive interventions, and possible non-statistically significant effects on social capital after comprehensive interventions. Effects due to interventions may vary by regional context and intervention scope. Limited strong evidence and the diffuse nature of comprehensive interventions suggests a need for attention to measurement of intervention exposure and analytic approaches to account for confounding and selection bias in evaluation. In addition to health improvements, evaluators should consider unintended health consequences and environmental impact. Understanding and isolating the effects of place-based interventions can inform necessary policy decisions to address inadequate living conditions as rapid urban growth continues across the globe.

The Role Of Nonprofit Hospitals In Identifying And Addressing Health Inequities In Cities.

For nonprofit hospitals to maintain their tax-exempt status, the Affordable Care Act requires them to conduct a community health needs assessment, in which they evaluate the health needs of the community they serve, and to create an implementation strategy, in which they propose ways to address these needs. We explored the extent to which nonprofit urban hospitals identified equity among the health needs of their communities and proposed health equity strategies to address this need. We conducted a content analysis of publicly available community health needs assessments and implementation strategies from 179 hospitals in twenty-eight US cities in the period August-December 2016. All of the needs assessments included at least one implicit health equity term (such as disparities, disadvantage, poor, or minorities), while 65 percent included at least one explicit health equity term (equity, health equity, inequity, or health inequity). Thirty-five percent of implementation strategies included one or more explicit health equity terms, but only 9 percent included an explicit activity to promote health equity. While needs assessment reporting requirements have the potential to encourage urban nonprofit hospitals to address health inequities in their communities, hospitals need incentives and additional capacity to invest in strategies that address the underlying structural social and economic conditions that cause health inequities.