The Puerto Rico community engagement alliance (PR-CEAL) against COVID-19 disparities: outreach and research engagement efforts in disproportionately affected communities.

In September 2020, the National Institutes of Health acted in response to the COVID-19 pandemic, recognizing the critical need to combat misinformation, particularly in communities disproportionately affected by the crisis. The Community Engagement Alliance (CEAL) emerged as an initiative dedicated to fostering reliable, science-based information, diversity, and inclusion; aiming to implement effective strategies to mitigate the spread of COVID-19 nationwide. One of the teams participating in this initiative is Puerto Rico-CEAL (PR-CEAL). Our whose goal was to raise awareness about the coronavirus disease and advance research, mainly focusing on vulnerable and underserved populations. This concept paper seeks to outline PR-CEAL's infrastructure during its initial two cycles, providing insights into the research and community engagement activities designed to enhance prevention, counter misinformation, and foster awareness and uptake of COVID-19 vaccines. Ultimately, our objective is to reflect on the strengths and challenges encountered thus far as we endeavor to sustain this robust infrastructure, addressing ongoing public health issues with a forward-looking approach.

Mortality due to falls by county, age group, race, and ethnicity in the USA, 2000-19: a systematic analysis of health disparities.

BACKGROUND: Fall-related mortality has increased rapidly over the past two decades in the USA, but the extent to which mortality varies across racial and ethnic populations, counties, and age groups is not well understood. The aim of this study was to estimate age-standardised mortality rates due to falls by racial and ethnic population, county, and age group over a 20-year period. METHODS: Redistribution methods for insufficient cause of death codes and validated small-area estimation methods were applied to death registration data from the US National Vital Statistics System and population data from the US National Center for Health Statistics to estimate annual fall-related mortality. Estimates from 2000 to 2019 were stratified by county (n=3110) and five mutually exclusive racial and ethnic populations: American Indian or Alaska Native (AIAN), Asian or Pacific Islander (Asian), Black, Latino or Hispanic (Latino), and White. Estimates were corrected for misreporting of race and ethnicity on death certificates using published misclassification ratios. We masked (ie, did not display) estimates for county and racial and ethnic population combinations with a mean annual population of less than 1000. Age-standardised mortality is presented for all ages combined and for age groups 20-64 years (younger adults) and 65 years and older (older adults). FINDINGS: Nationally, in 2019, the overall age-standardised fall-related mortality rate for the total population was 13·4 deaths per 100 000 population (95% uncertainty interval 13·3-13·6), an increase of 65·3% (61·9-68·8) from 8·1 deaths per 100 000 (8·0-8·3) in 2000, with the largest increases observed in older adults. Fall-related mortality at the national level was highest across all years in the AIAN population (in 2019, 15·9 deaths per 100 000 population [95% uncertainty interval 14·0-18·2]) and White population (14·8 deaths per 100 000 [14·6-15·0]), and was about half as high among the Latino (8·7 deaths per 100 000 [8·3-9·0]), Black (8·1 deaths per 100 000 [7·9-8·4]), and Asian (7·5 deaths per 100 000 [7·1-7·9]) populations. The disparities between racial and ethnic populations varied widely by age group, with mortality among younger adults highest for the AIAN population and mortality among older adults highest for the White population. The national-level patterns were observed broadly at the county level, although there was considerable spatial variation across ages and racial and ethnic populations. For younger adults, among almost all counties with unmasked estimates, there was higher mortality in the AIAN population than in all other racial and ethnic populations, while there were pockets of high mortality in the Latino population, particularly in the Mountain West region. For older adults, mortality was particularly high in the White population within clusters of counties across states including Florida, Minnesota, and Wisconsin. INTERPRETATION: Age-standardised mortality due to falls increased over the study period for each racial and ethnic population and almost every county. Wide variation in mortality across geography, age, and race and ethnicity highlights areas and populations that might benefit most from efficacious fall prevention interventions as well as additional prevention research. FUNDING: US National Institutes of Health (Intramural Research Program, National Institute on Minority Health and Health Disparities; National Heart, Lung, and Blood Institute; Intramural Research Program, National Cancer Institute; National Institute on Aging; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Office of Disease Prevention; and Office of Behavioral and Social Sciences Research).

Risk factors underlying racial and ethnic disparities in tuberculosis diagnosis and treatment outcomes, 2011-19: a multiple mediation analysis of national surveillance data.

BACKGROUND: Despite an overall decline in tuberculosis incidence and mortality in the USA in the past two decades, racial and ethnic disparities in tuberculosis outcomes persist. We aimed to examine the extent to which inequalities in health and neighbourhood-level social vulnerability mediate these disparities. METHODS: We extracted data from the US National Tuberculosis Surveillance System on individuals with tuberculosis during 2011-19. Individuals with multidrug-resistant tuberculosis or missing data on race and ethnicity were excluded. We examined potential disparities in tuberculosis outcomes among US-born and non-US-born individuals and conducted a mediation analysis for groups with a higher risk of treatment incompletion (a summary outcome comprising diagnosis after death, treatment discontinuation, or death during treatment). We used sequential multiple mediation to evaluate eight potential mediators: three comorbid conditions (HIV, end-stage renal disease, and diabetes), homelessness, and four census tract-level measures (poverty, unemployment, insurance coverage, and racialised economic segregation [measured by Index of Concentration at the ExtremesRace-Income]). We estimated the marginal contribution of each mediator using Shapley values. FINDINGS: During 2011-19, 27 788 US-born individuals and 57 225 non-US-born individuals were diagnosed with active tuberculosis, of whom 27 605 and 56 253 individuals, respectively, met eligibility criteria for our analyses. We did not observe evidence of disparities in tuberculosis outcomes for non-US-born individuals by race and ethnicity. Therefore, subsequent analyses were restricted to US-born individuals. Relative to White individuals, Black and Hispanic individuals had a higher risk of not completing tuberculosis treatment (adjusted relative risk 1·27, 95% CI 1·19-1·35; 1·22, 1·11-1·33, respectively). In multiple mediator analysis, the eight measured mediators explained 67% of the disparity for Black individuals and 65% for Hispanic individuals. The biggest contributors to these disparities for Black individuals and Hispanic individuals were concomitant end-stage renal disease, concomitant HIV, census tract-level racialised economic segregation, and census tract-level poverty. INTERPRETATION: Our findings underscore the need for initiatives to reduce disparities in tuberculosis outcomes among US-born individuals, particularly in highly racially and economically polarised neighbourhoods. Mitigating the structural and environmental factors that lead to disparities in the prevalence of comorbidities and their case management should be a priority. FUNDING: US Centers for Disease Control and Prevention National Center for HIV, Viral Hepatitis, STD, and Tuberculosis Prevention Epidemiologic and Economic Modeling Agreement.

Assessing the extent and determinants of socioeconomic inequalities in epilepsy in the UK: a systematic review and meta-analysis of evidence.

BACKGROUND: Socioeconomic inequalities in epilepsy incidence and its adverse outcomes are documented internationally, yet the extent of inequalities and factors influencing the association can differ between countries. A UK public health response to epilepsy, which prevents epilepsy without widening inequalities, is required. However, the data on UK epilepsy inequalities have not been synthesised in a review and the underlying determinants are unknown. METHODS: In this systematic review and meta-analysis, we searched six bibliographic databases (MEDLINE, Embase, PsycINFO, CINAHL, Web of Science, and Scopus) and grey literature published between Jan 1, 1980, and Feb 21, 2024, to identify UK studies reporting epilepsy incidence or epilepsy-related adverse outcomes by socioeconomic factors (individual level or area level). We included longitudinal cohort studies, studies using routinely collected health-care data, cross-sectional studies, and matched cohort studies and excluded conference abstracts and studies not reporting empirical results in the review and meta-analysis. Multiple reviewers (KJB, EC, SER, WOP, and RHT) independently screened studies, KJB extracted data from included studies and a second reviewer (SM or EC) checked data extraction. We used Critical Appraisal Skills Programme checklists to assess quality. We used random-effects meta-analysis to pool incident rate ratios (IRRs) and synthesised results on adverse outcomes narratively. This study was registered on PROPSPERO (CRD42023394143). FINDINGS: We identified 2471 unique studies from database searches. We included 26 studies, ten of which reported epilepsy incidence and 16 reported epilepsy-related adverse outcomes according to socioeconomic factors. Misclassification, participation, and interpretive biases were identified as study quality limitations. Meta-analyses showed an association between socioeconomic deprivation and epilepsy incidence, with greater risks of epilepsy incidence in groups of high-deprivation (IRR 1·34 [95% CI 1·16-1·56]; I2=85%) and medium-deprivation (IRR 1·23 [95% CI 1·08-1·39]; I2=63%) compared with low-deprivation groups. This association persisted in the studies that only included children (high vs low: IRR 1·36 [95% CI 1·19-1·57]; I2=0%). Only two studies examined factors influencing epilepsy incidence. There is limited evidence regarding UK inequalities in adverse outcomes. INTERPRETATION: Socioeconomic inequalities in epilepsy incidence are evident in the UK. To develop an evidence-based public health response to epilepsy, further research is needed to understand the populations affected, factors determining the association, and the extent of inequalities in adverse outcomes. FUNDING: Epilepsy Research Institute UK.

Sex differences in the diagnostic algorithm of screening for heart failure by symptoms and NT-proBNP in patients with type 2 diabetes.

OBJECTIVES: This study aimed to assess the guideline recommended diagnostic tools NT-proBNP and NYHA classification, with a focus on sex-specific differences. BACKGROUND: Patients with Type 2 Diabetes (T2D) face a heart failure (HF) risk up to four times higher than those without T2D, particularly affecting women more than twice as much as men. Despite distinct pathophysiological differences between men and women, there are currently no sex-specific recommendations for the diagnostic algorithm of HF in diabetic patients. METHODS: A total of 2083 patients with T2D were enrolled, and the primary endpoint was heart failure during hospitalization within a 5-year timeframe. The secondary endpoint was all-cause death. RESULTS: In female patients, frequency of HF diagnosis prior to or during hospitalization and mortality did not differ significantly between NYHA II and III, in contrast to male patients. Additionally, there was no notable difference in mean NT-proBNP levels between NYHA stage II and III only in female patients. The multivariable regression analysis highlighted NYHA classification not to be a predictor of NT-proBNP levels in female but solely in male patients. On multivariable Cox regression NYHA score was also no significant risk factor for occurence of HF in female patients. Furthermore, there was no significant disparity in mortality between men with NT-proBNP levels between 125 and 400 pg/ml and those below 125 pg/ml, whereas in women mortality was significantly higher in the group with NT-proBNP levels between 125 and 400 pg/ml than below 125 pg/ml. CONCLUSION: These findings suggest that NYHA classification may not be the most suitable tool for assessing the diagnosis of HF in female patients with T2D. Moreover, the need for consideration of a more symptom-independent screening for HF in female patients with T2D and re-evaluation of current guidelines especially regarding sex-specific aspects is highlighted.

Decomposition analysis to assess intervention strategies for reducing health-related exposure disparities in Michigan public drinking water systems.

OBJECTIVE: Contamination in U.S. public drinking water systems (PWS) is estimated to cause millions of illnesses and billions of dollars in medical expenditures annually. Few prior studies have explored intervention strategies, including environmental enforcement, to reduce estimated health-related exposure disparities (exposure disparity) in PWS, which are driven partially by socioeconomic status (SES), racism, and PWS characteristics. METHOD: This study used a longitudinal measurement method to estimate the annual health-related exposure level (health level) of each PWS in Michigan, based on data from the Enforcement and Compliance Online (ECHO) and U.S. Census Bureau databases. Using a decomposition model with four strategies, we analyzed how eliminating disparities in SES, proportion minority, environmental enforcement, and PWS characteristics across communities would affect adjusted exposure disparities. RESULTS: This study found that adjusted race- and poverty-based exposure disparities have existed since the 1980s but might have decreased in the last one or two decades. PWS characteristics strongly impacted the crude and adjusted exposure disparity. Environmental enforcement, although less effective in minority-concentrated communities, reduced the adjusted race-based exposure disparity by 10%-20% in the 1980s, 8% in the 1990s, and 0.012% in the 2010s. Equalizing the poverty rate distribution reduced the adjusted race-based exposure disparity by 0.72% in the 1980s and 6.8% in the 2010s. However, equalizing racial and ethnic composition distribution increased the adjusted poverty-based exposure disparity in the 2000s. CONCLUSION: These findings indicate that economically disadvantaged or minority-concentrated communities in Michigan disproportionately suffer from poorer PWS quality. Enhanced environmental enforcement, increased household income, PWS investment, and other actions are needed to address these exposure disparities effectively.

Measuring spatial inequalities in maternal and child mortalities in Pakistan: evidence from geographically weighted regression.

BACKGROUND: In developing countries, the death probability of a child and mother is more significant than in developed countries; these inequalities in health outcomes are unfair. The present study encompasses a spatial analysis of maternal and child mortalities in Pakistan. The study aims to estimate the District Mortality Index (DMI), measure the inequality ratio and slope, and ascertain the spatial impact of numerous factors on DMI scores across Pakistani districts. METHOD: This study used micro-level household datasets from multiple indicator cluster surveys (MICS) to estimate the DMI. To find out how different the DMI scores were, the inequality ratio and slope were used. This study further utilized spatial autocorrelation tests to determine the magnitude and location of the spatial dependence of the clusters with high and low mortality rates. The Geographically Weighted Regression (GWR) model was also applied to examine the spatial impact of socioeconomic, environmental, health, and housing attributes on DMI. RESULTS: The inequality ratio for DMI showed that the upper decile districts are 16 times more prone to mortalities than districts in the lower decile, and the districts of Baluchistan depicted extreme spatial heterogeneity in terms of DMI. The findings of the Local Indicator of Spatial Association (LISA) and Moran's test confirmed spatial homogeneity in all mortalities among the districts in Pakistan. The H-H clusters of maternal mortality and DMI were in Baluchistan, and the H-H clusters of child mortality were seen in Punjab. The results of GWR showed that the wealth index quintile has a significant spatial impact on DMI; however, improved sanitation, handwashing practices, and antenatal care adversely influenced DMI scores. CONCLUSION: The findings reveal a significant disparity in DMI and spatial relationships among all mortalities in Pakistan's districts. Additionally, socioeconomic, environmental, health, and housing variables have an impact on DMI. Notably, spatial proximity among individuals who are at risk of death occurs in areas with elevated mortality rates. Policymakers may mitigate these mortalities by focusing on vulnerable zones and implementing measures such as raising public awareness, enhancing healthcare services, and improving access to clean drinking water and sanitation facilities.

Indicators of social inequalities associated with cancer mortality in Brazilian adults: scoping review. / Indicadores de desigualdades sociais associados à mortalidade por neoplasias nos adultos brasileiros: revisão de escopo.

The objective of this study was to identify indicators of social inequalities associated with mortality from neoplasms in the Brazilian adult population. A scoping review method was used, establishing the guiding question: What is the effect of social inequalities on mortality from neoplasms in the Brazilian adult population? A total of 567 papers were identified, 22 of which were considered eligible. A variety of indicators were identified, such as the Human Development Index and the Gini Index, which primarily assessed differences in income, schooling, human development and vulnerability. A single pattern of association between the indicators and the different neoplasms was not established, nor was a single indicator capable of explaining the effect of social inequality at all levels of territorial area and by deaths from all types of neoplasms identified. It is known that mortality is influenced by social inequalities and that the study of indicators provides an opportunity to define which best explains deaths. This review highlights important gaps regarding the use of non-modifiable social indicators, analysis of small geographical areas, and limited use of multidimensional indicators.

O objetivo deste estudo foi identificar indicadores de desigualdades sociais associados à mortalidade por neoplasias na população adulta brasileira. Utilizou-se como método a revisão de escopo, estabelecendo-se a pergunta norteadora: qual o efeito das desigualdades sociais na mortalidade por neoplasias na população adulta brasileira? Foram identificados 567 trabalhos, sendo 22 considerados elegíveis. Identificou-se uma diversidade de indicadores, como o Índice de Desenvolvimento Humano e o Índice de Gini, entre outros, que avaliaram primordialmente diferenças de renda, escolarização, desenvolvimento humano e vulnerabilidade. Não foi estabelecido um único padrão de associação entre os indicadores e as diferentes neoplasias, assim como não se identificou um indicador único capaz de explicar o efeito da desigualdade social em todos os níveis de área e por óbitos por todos os tipos de neoplasias, mas identificou-se que a mortalidade é influenciada pelas desigualdades sociais e que o estudo dos indicadores proporciona definir qual melhor explica os óbitos. Essa revisão destaca importantes lacunas referentes ao uso de indicadores sociais não modificáveis, à análise de pequenas áreas e ao uso limitado de indicadores multidimensionais.

Benefits and challenges of geographic information systems (GIS) for data-driven outreach in black communities experiencing overdose disparities: results of a stakeholder focus group.

BACKGROUND: Black individuals in the U.S. face increasing racial disparities in drug overdose related to social determinants of health, including place-based features. Mobile outreach efforts work to mitigate social determinants by servicing geographic areas with low drug treatment and overdose prevention access but are often limited by convenience-based targets. Geographic information systems (GIS) are often used to characterize and visualize the overdose crisis and could be translated to community to guide mobile outreach services. The current study examines the initial acceptability and appropriateness of GIS to facilitate data-driven outreach for reducing overdose inequities facing Black individuals. METHODS: We convened a focus group of stakeholders (N = 8) in leadership roles at organizations conducting mobile outreach in predominantly Black neighborhoods of St. Louis, MO. Organizations represented provided adult mental health and substance use treatment or harm reduction services. Participants were prompted to discuss current outreach strategies and provided feedback on preliminary GIS-derived maps displaying regional overdose epidemiology. A reflexive approach to thematic analysis was used to extract themes. RESULTS: Four themes were identified that contextualize the acceptability and utility of an overdose visualization tool to mobile service providers in Black communities. They were: 1) importance of considering broader community context; 2) potential for awareness, engagement, and community collaboration; 3) ensuring data relevance to the affected community; and 4) data manipulation and validity concerns. CONCLUSIONS: There are several perceived benefits of using GIS to map overdose among mobile providers serving Black communities that are overburdened by the overdose crisis but under resourced. Perceived potential benefits included informing location-based targets for services as well as improving awareness of the overdose crisis and facilitating collaboration, advocacy, and resource allocation. However, as GIS-enabled visualization of drug overdose grows in science, public health, and community settings, stakeholders must consider concerns undermining community trust and benefits, particularly for Black communities facing historical inequities and ongoing disparities.

Aiming for transformations in power: lessons from intersectoral CBPR with public housing tenants (Québec, Canada).

Intersectoral collaborations are recommended as effective strategies to reduce health inequalities. People most affected by health inequalities, as are people living in poverty, remain generally absent from such intersectoral collaborations. Community-based participatory research (CBPR) projects can be leveraged to better understand how to involve people with lived experience to support both individual and community empowerment. In this paper, we offer a critical reflection on a CBPR project conducted in public housing in Québec, Canada, that aimed to develop intersectoral collaboration between tenants and senior executives from four sectors (housing, health, city and community organizations). This single qualitative case study design consisted of fieldwork documents, observations and semi-structured interviews. Using the Emancipatory Power Framework (EPF) and the Limiting Power Framework (LPF), we describe examples of types of power and resistance shown by the tenants, the intersectoral partners and the research team. The discussion presents lessons learned through the study, including the importance for research teams to reflect on their own power, especially when aiming to reduce health inequalities. The paper concludes by describing the limitations of the analyses conducted through the EPF-LPF frameworks and suggestions to increase the transformative power of future studies.

Age- and deprivation-related inequalities in identification of people at high risk of type 2 diabetes in England.

BACKGROUND: Early detection of intermediate hyperglycaemia, otherwise known as non-diabetic hyperglycaemia (NDH) is crucial to identify people at high risk of developing type 2 diabetes mellitus (T2DM) who could benefit from preventative interventions. Failure to identify NDH may also increase the risks of T2DM-related complications at the time of T2DM diagnosis. We investigate sociodemographic inequalities in identification of NDH in England. METHODS: We used nationwide data from the English National Health Service (NHS) National Diabetes Audit, which includes all people who were newly identified with NDH (N = 469,910) or diagnosed with T2DM (N = 222,795) between 1st April 2019 and 31st March 2020. We used regression models to explore inequalities in the under identification of NDH by area-level deprivation and age group. RESULTS: Of those with a new T2DM diagnosis, 67.3% had no previous record of NDH. The odds of no previous NDH being recorded were higher amongst people living in more deprived areas (Odds ratio (OR) 1.15 (95% confidence intervals (CI) [1.12, 1.19]) most deprived (Q1) compared to least deprived (Q5) quintile) and younger individuals (OR 4.02 (95% CI [3.79, 4.27] under 35s compared to age 75-84)). Deprivation-related inequalities persisted after stratification by age group, with the largest inequalities amongst middle and older age groups. People living in more deprived areas and younger people also had shorter recorded NDH duration before progression to T2DM, and higher T2DM severity at the time of diagnosis. CONCLUSIONS: There is under identification of NDH relative to diagnosis of T2DM amongst people living in more deprived areas and particularly amongst younger people, resulting in missed opportunities for targeted T2DM prevention efforts and potentially contributing to inequalities in T2DM prevalence and severity. More active NDH case-finding amongst these groups may be an important first step in helping to reduce inequalities in T2DM.

How can health systems approach reducing health inequalities? An in-depth qualitative case study in the UK.

BACKGROUND: Addressing socioeconomic inequalities in health and healthcare, and reducing avoidable hospital admissions requires integrated strategy and complex intervention across health systems. However, the understanding of how to create effective systems to reduce socio-economic inequalities in health and healthcare is limited. The aim was to explore and develop a system's level understanding of how local areas address health inequalities with a focus on avoidable emergency admissions. METHODS: In-depth case study using qualitative investigation (documentary analysis and key informant interviews) in an urban UK local authority. Interviewees were identified using snowball sampling. Documents were retrieved via key informants and web searches of relevant organisations. Interviews and documents were analysed independently based on a thematic analysis approach. RESULTS: Interviews (n = 14) with wide representation from local authority (n = 8), NHS (n = 5) and voluntary, community and social enterprise (VCSE) sector (n = 1) with 75 documents (including from NHS, local authority, VCSE) were included. Cross-referenced themes were understanding the local context, facilitators of how to tackle health inequalities: the assets, and emerging risks and concerns. Addressing health inequalities in avoidable admissions per se was not often explicitly linked by either the interviews or documents and is not yet embedded into practice. However, a strong coherent strategic integrated population health management plan with a system's approach to reducing health inequalities was evident as was collective action and involving people, with links to a "strong third sector". Challenges reported include structural barriers and threats, the analysis and accessibility of data as well as ongoing pressures on the health and care system. CONCLUSION: We provide an in-depth exploration of how a local area is working to address health and care inequalities. Key elements of this system's working include fostering strategic coherence, cross-agency working, and community-asset based approaches. Areas requiring action included data sharing challenges across organisations and analytical capacity to assist endeavours to reduce health and care inequalities. Other areas were around the resilience of the system including the recruitment and retention of the workforce. More action is required to embed reducing health inequalities in avoidable admissions explicitly in local areas with inaction risking widening the health gap.

Disparities in perioperative mortality outcomes between First Nations and non-First Nations peoples in Australia: protocol for a systematic review and planned meta-analysis.

BACKGROUND: Health inequities persist among First Nations people living in developed countries. Surgical care is pivotal in addressing a significant portion of the global disease burden. Evidence regarding surgical outcomes among First Nations people in Australia is limited. The perioperative mortality rate (POMR) indicates timely access to safe surgery and predicts long-term survival after major surgery. This systematic review will examine POMR among First Nations and non-First Nations peoples in Australia. METHODS: A systematic search strategy using MEDLINE, Embase, Emcare, Global Health, and Scopus will identify studies that include First Nations people and non-First Nations people who underwent a surgical intervention under anaesthesia in Australia. The primary focus will be on documenting perioperative mortality outcomes. Title and abstract screening and full-text review will be conducted by independent reviewers, followed by data extraction and bias assessment using the ROBINS-E tool. Meta-analysis will be considered if there is sufficient homogeneity between studies. The quality of cumulative evidence will be evaluated following the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) criteria. DISCUSSION: This protocol describes the comprehensive methodology for the proposed systematic review. Evaluating disparities in perioperative mortality rates between First Nations and non-First Nations people remains essential in shaping the discourse surrounding health equity, particularly in addressing the surgical burden of disease. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42021258970.

Spatial patterns and sociodemographic predictors of chronic obstructive pulmonary disease in Florida.

Background: Chronic obstructive pulmonary disease (COPD) is a chronic, inflammatory respiratory disease that obstructs airflow and decreases lung function and is a leading cause death globally. In the United States (US), the prevalence among adults is 6.2%, but increases with age to 12.8% among those 65 years or older. Florida has one of the largest populations of older adults in the US, accounting for 4.5 million adults 65 years or older. This makes Florida an ideal geographic location for investigating COPD as disease prevalence increases with age. Understanding the geographic disparities in COPD and potential associations between its disparities and environmental factors as well as population characteristics is useful in guiding intervention strategies. Thus, the objectives of this study are to investigate county-level geographic disparities of COPD prevalence in Florida and identify county-level socio-demographic predictors of COPD prevalence. Methods: This ecological study was performed in Florida using data obtained from the US Census Bureau, Florida Health CHARTS, and County Health Rankings and Roadmaps. County-level COPD prevalence for 2019 was age-standardized using the direct method and 2020 US population as the standard population. High-prevalence spatial clusters of COPD were identified using Tango's flexible spatial scan statistics. Predictors of county-level COPD prevalence were investigated using multivariable ordinary least squares model built using backwards elimination approach. Multicollinearity of regression coefficients was assessed using variance inflation factor. Shapiro-Wilks, Breusch Pagan, and robust Lagrange Multiplier tests were used to assess for normality, homoskedasticity, and spatial autocorrelation of model residuals, respectively. Results: County-level age-adjusted COPD prevalence ranged from 4.7% (Miami-Dade) to 16.9% (Baker and Bradford) with a median prevalence of 9.6%. A total of 6 high-prevalence clusters with prevalence ratios >1.2 were identified. The primary cluster, which was also the largest geographic cluster that included 13 counties, stretched from Nassau County in north-central Florida to Charlotte County in south-central Florida. However, cluster 2 had the highest prevalence ratio (1.68) and included 10 counties in north-central Florida. Together, the primary cluster and cluster 2 covered most of the counties in north-central Florida. Significant predictors of county-level COPD prevalence were county-level percentage of residents with asthma and the percentage of current smokers. Conclusions: There is evidence of spatial clusters of COPD prevalence in Florida. These patterns are explained, in part, by differences in distribution of some health behaviors (smoking) and co-morbidities (asthma). This information is important for guiding intervention efforts to address the condition, reduce health disparities, and improve population health.

Inequalities in lifespan and mortality risk in the US, 2015-2019: a cross-sectional analysis of subpopulations by social determinants of health.

OBJECTIVE: To quantify inequalities in lifespan across multiple social determinants of health, how they act in tandem with one another, and to create a scoring system that can accurately identify subgroups of the population at high risk of mortality. DESIGN: Comparison of life tables across 54 subpopulations defined by combinations of four social determinants of health: sex, marital status, education and race, using data from the Multiple Cause of Death dataset and the American Community Survey. SETTING: United States, 2015-2019. MAIN OUTCOME MEASURES: We compared the partial life expectancies (PLEs) between age 30 and 90 years of all subpopulations. We also developed a scoring system to identify subgroups at high risk of mortality. RESULTS: There is an 18.0-year difference between the subpopulations with the lowest and highest PLE. Differences in PLE between subpopulations are not significant in most pairwise comparisons. We visually illustrate how the PLE changes across social determinants of health. There is a complex interaction among social determinants of health, with no single determinant fully explaining the observed variation in lifespan. The proposed scoring system adds clarification to this interaction by yielding a single score that can be used to identify subgroups that might be at high risk of mortality. A similar scoring system by cause of death was also created to identify which subgroups could be considered at high risk of mortality from specific causes. Even if subgroups have similar mortality levels, they are often subject to different cause-specific mortality risks. CONCLUSIONS: Having one characteristic associated with higher mortality is often not sufficient to be considered at high risk of mortality, but the risk increases with the number of such characteristics. Reducing inequalities is vital for societies, and better identifying individuals and subgroups at high risk of mortality is necessary for public health policy.

Description of census-tract-level social determinants of health in cancer surveillance data.

BACKGROUND: Disparities in cancer incidence, stage at diagnosis, and mortality persist by race, ethnicity, and many other social determinants, such as census-tract-level socioeconomic status (SES), poverty, and rurality. Census-tract-level measures of these determinants are useful for analyzing trends in cancer disparities. METHODS: The purpose of this paper was to demonstrate the availability of the Surveillance, Epidemiology, and End Results Program's specialized census-tract-level dataset and provide basic descriptive cancer incidence, stage at diagnosis, and survival for 8 cancer sites, which can be screened regularly or associated with infectious agents. We present these analyses according to several census-tract-level measures, including the newly available persistent poverty as well as SES quintile, rurality, and race and ethnicity. RESULTS: Census tracts with persistent poverty and low SES had higher cancer incidence rates (except for breast and prostate cancer), higher percentages of cases diagnosed with regional or distant-stage disease, and lower survival than non-persistent-poverty and higher-SES tracts. Outcomes varied by cancer site when analyzing based on rurality as well as race and ethnicity. Analyses stratified by multiple determinants showed unique patterns of outcomes, which bear further investigation. CONCLUSIONS: This article introduces the Surveillance, Epidemiology, and End Results specialized dataset, which contains census-tract-level social determinants measures, including persistent poverty, rurality, SES quintile, and race and ethnicity. We demonstrate the capacity of these variables for use in producing trends and analyses focusing on cancer health disparities. Analyses may inform interventions and policy changes that improve cancer outcomes among populations living in disadvantaged areas, such as persistent-poverty tracts.