Implementing and monitoring high-quality community health worker care in adult primary care at New York City Health + Hospitals.

BACKGROUND: This study describes how New York City (NYC) Health + Hospitals implemented a large-scale Community Health Worker (CHW) program in adult primary care clinics between January 2022 and December 2023 and established metrics to monitor program implementation. This study is timely as healthcare systems consider how to scale high-quality CHW programs. METHODS: We collected metrics in the following areas: (1) Workforce demographics, team structure, and training; (2) Enrolled patient demographics; (3) Patient-centered metrics, such as patient counts (e.g. patients outreached and enrolled) and engagement (e.g. median time in program, caseloads per CHW), and goals (e.g. median number of goals identified and completed). Metrics are based on standard data elements captured through CHW documentation in the electronic health record collected during program implementation. Data cleaning is completed using SQL queries and R scripts. RESULTS: In June 2023, there were a total of 97 CHW and 22 CHW Supervisor staff lines in adult primary care across 17 healthcare sites. There were 4.6 CHWs to 1 CHW supervisor on average though this ranged by facility from 1:1 to 1:6. Compared to the population that receives primary care at NYC H + H, CHWs served more African American/Black patients (40% vs. 32%) and an older patient population (35% older than 65 vs. 21% older than 65). From January 2022 to December 2023, 13,812 patients were outreached by CHWs. Of these, 9,069 (66%) were referred by clinicians, 7,331 (53%) were enrolled, and 5,044 (37%) successfully graduated. The median number of goals identified by patients was four, and the median number of goals completed with a CHW per patient was three. The top three goals were primary care engagement (47%), specialty care engagement (46%), and food insecurity (45%). CONCLUSION: Establishing clear implementation and process metrics helps to ensure that CHWs embedded in health systems can meaningfully engage adult patients in health care, address patient-centered goals, and connect patients to community and government services.

Social Vulnerability and National Diabetes Prevention Program Recognition Status.

INTRODUCTION: The CDC National Diabetes Prevention Program (National DPP) aims to reduce the incidence of diabetes in the U.S. Organizations delivering the National DPP receive pending, preliminary, full, or full-plus recognition status based on specific program criteria and outcomes. Achieving full/full-plus recognition is critical for organizations to sustain the program and receive reimbursements to cover costs, but organizations in disadvantaged areas may face barriers to obtaining this level of recognition. This study examined the association between county-level social vulnerability and full/full-plus recognition status within the National DPP. METHODS: Using the 2022 National DPP registry and the 2018 CDC Social Vulnerability Index (SVI), a three-level categorical dependent variable was created (n=843): counties without organizations having full/full-plus recognition, counties with at least one organization not having full/full-plus recognition, and counties with all organizations having full/full-plus recognition. A multinomial logit model was analyzed in 2023 to examine the association between SVI and in-person full/full-plus recognition organizations at the county level, adjusting for confounders. RESULTS: Compared to counties with low social vulnerability, counties with higher social vulnerability had significantly higher odds of having no organizations with full/full-plus recognition. For example, counties with high SVI had 2.63 (95% CI: 1.55-4.47) times higher odds of having no organizations with full/full-plus recognition compared to having all organizations with full/full-plus CDC recognition. CONCLUSIONS: The findings suggest disparities in the National DPP recognition status among organizations in vulnerable communities. Developing strategies to ensure organizations in high social vulnerability areas achieve at least full recognition status is critical for program sustainability and reducing diabetes-related health disparities.

Mapping Public Health Nursing competencies: A comparative document analysis of competency frameworks and practice standards in the USA and Ireland.

The Public Health Nursing discipline plays a crucial role in promoting sustainable health services. The establishment of competency frameworks and practice standards pertaining to Public Health Nursing has emerged as a cornerstone for guiding practice, education, and research. This study aimed to identify contemporary Public Health Nursing competency frameworks and practice standards and establish a robust list of competency domains. This will inform a subsequent phase of this project that will conduct a review of recent scholarly literature to discern prevailing research trends and delineate strategic directives and research priorities for the discipline. A systematic search of three databases and a grey literature search was undertaken by incorporating keywords to identify existing Public Health Nursing-specific competency frameworks and practice standards. Through screening and selection based on our inclusion criteria, three documents were analyzed. A comprehensive document analysis was conducted to generate a unified domain list and associated descriptors. Three competency-based frameworks and practice standards emanating from two countries, the United States of America and the Republic of Ireland met the inclusion criteria. The document analysis identified 16 individual domains. There was consistent evidence of similarity across the three documents. There were minimal divergences featured within the frameworks which are discussed and compelling justifications for inclusion as universal domains are provided. This document analysis has generated a list of 16 common Public Health Nursing competency domains which will be utilized in phase two of this project as a foundational framework for the purpose of analyzing research trends, influencing research priorities, and enhancing the focal areas for future research agendas within the discipline.

Pharmacist Use of a Population Management Dashboard for Safe Anticoagulant Prescribing: Evaluation of a Nationwide Implementation Effort.

BACKGROUND: Direct oral anticoagulants (DOACs) have complex dosing regimens and are often incorrectly prescribed. We evaluated a nationwide DOAC population management dashboard rollout whose purpose includes pharmacist review and correction of off-label dosing prescriptions. METHODS AND RESULTS: Using data from Veterans Health Affairs, we identified all patients prescribed DOACs for atrial fibrillation or venous thromboembolism between August 2015 and December 2019. Sites were grouped on the basis of the timing of moderate-high usage of the DOAC population management tool dashboard. Effectiveness was defined as the monthly rate of off-label DOAC prescribing and the rate of clinical adverse events (bleeding, composite of stroke or venous thromboembolism). Implementation was evaluated as the percentage of off-label DOAC prescriptions changed within 7 days. Among the 128 652 patients receiving DOAC therapy at 123 centers, between 6.9% and 8.6% had off-label DOAC prescriptions. Adoption of the DOAC population management tool dashboard before July 2018 was associated with a decline in off-label dosing prescriptions (8.7%-7.6%). Only 1 group demonstrated a significant reduction in monthly rates of bleeding following implementation. All sites experienced a reduction in the composite of venous thromboembolism or stroke following dashboard adoption. There was no difference in the implementation outcome of DOAC prescription change within 7 days in any of the adoption groups. CONCLUSIONS: Early adoption of the DOAC population management tool dashboard was associated with decreased rates of off-label DOAC dosing prescription and reduced bleeding. Following adoption of the DOAC population management tool dashboard, all sites experienced reductions in venous thromboembolism and stroke events.

Predictive Modelling of Diabetes Risk in Population Groups Defined by Socioeconomic and Lifestyle Factors in Canada: A Cross-Sectional Study.

Objectives: This study modelled diabetes risk for population groups in Canada defined by socioeconomic and lifestyle characteristics and investigated inequities in diabetes risk using a validated population risk prediction algorithm. Methods: We defined population groups, informed by determinants of health frameworks. We applied the Diabetes Population Risk Tool (DPoRT) to 2017/2018 Canadian Community Health Survey data to predict 10-year diabetes risk and cases across population groups. We modelled a preventive intervention scenario to estimate reductions in diabetes for population groups and impacts on the inequity in diabetes risk across income and education. Results: The population group with at least one lifestyle and at least one socioeconomic/structural risk factor had the highest estimated 10-year diabetes risk and number of new cases. When an intervention with a 5% relative risk reduction was modelled for this population group, diabetes risk decreased by 0.5% (females) and 0.7% (males) and the inequity in diabetes risk across income and education levels was reduced. Conclusion: Preventative interventions that address socioeconomic and structural risk factors have potential to reduce inequities in diabetes risk and overall diabetes burden.

Assessing the Strengths and Weaknesses for Implementing a Place-Based Model of Care for Older People on the Central Coast, Australia: Results of a Pilot Project Using the Population Health Management Maturity Index (PHM-MI) Tool.

Introduction: Population health management is increasingly being used to support place-based models of care. This case study provides an account of the use of the Population Health Management - Maturity Index (PHM-MI) tool to inform the future development of a neighbourhood model of care for older people in the Central Coast region of Australia. Description: The PHM-MI tool comprises a set of six evidence-informed elements known to be important in enabling PHM in practice. As part of a joint strategic needs assessment, 17 selected stakeholders from key regional organizations were invited to undertake the PHM-MI tool survey. Three follow-up workshops were held to interpret the results and determine priority actions. Discussion: The PHM-MI scores revealed that the overall maturity of the Central Coast to successfully deliver PHM was low across all six elements, findings that were corroborated through participant workshops. Systemic fragmentations, most pertinently of funding and regulation, incentivised silo-based working. The need to formalise and strengthen regional collaborations, enable data integration, find creative ways to use existing funding streams, and promote community engagement were highlighted as core priorities. Conclusion: Using the PHM-MI tool was enabled by it being embedded within a pre-existing regional strategic process. The results were used to inform future regional priorities. The PHM-MI tool has the potential for use across regional or national contexts.

Development of a three-dimensional scoring model for the assessment of continuous glucose monitoring data in type 1 diabetes.

INTRODUCTION: Despite the improvements in diabetes management by continuous glucose monitoring (CGM) it is difficult to capture the complexity of CGM data in one metric. We aimed to develop a clinically relevant multidimensional scoring model with the capacity to identify the most alarming CGM episodes and/or patients from a large cohort. RESEARCH DESIGN AND METHODS: Retrospective CGM data from 2017 to 2020 available in electronic medical records were collected from n=613 individuals with type 1 diabetes (total 82 114 days). A scoring model was developed based on three metrics; glycemic variability percentage, low blood glucose index and high blood glucose index. Values for each dimension were normalized to a numeric score between 0-100. To identify the most representative score for an extended time period, multiple ways to combine the mean score of each dimension were evaluated. Correlations of the scoring model with CGM metrics were computed. The scoring model was compared with interpretations of a clinical expert board (CEB). RESULTS: The dimension of hypoglycemia must be weighted to be representative, whereas the other two can be represented by their overall mean. The scoring model correlated well with established CGM metrics. Applying a score of ≥80 as the cut-off for identifying time periods with a 'true' target fulfillment (ie, reaching all targets for CGM metrics) resulted in an accuracy of 93.4% and a specificity of 97.1%. The accuracy of the scoring model when compared with the CEB was high for identifying the most alarming CGM curves within each dimension of glucose control (overall 86.5%). CONCLUSIONS: Our scoring model captures the complexity of CGM data and can identify both the most alarming dimension of glycemia and the individuals in most urgent need of assistance. This could become a valuable tool for population management at diabetes clinics to enable healthcare providers to stratify care to the patients in greatest need of clinical attention.

Innovation in Healthcare Education: Using "Shark Tank" Approaches to Educate Teams of Interprofessional Students in Health Equity.

Inspired by the television show Shark Tank, we developed a summer research program that brought together students from the Colleges of Medicine, Pharmacy, Business, and Communications, to collaborate, find creative solutions, and spark innovations in population health. Under the guidance of faculty, student teams conducted literature reviews and data-thon exercises to examine trends to identify health equity gaps. Students then worked collaboratively to develop and pitch innovative solutions in front of a panel of expert "sharks" for feedback and to gain financial support to advance their ideas.

¿No Hay Racismo?: application of the levels of racism framework to Latinx perspectives on barriers to health and wellbeing.

BACKGROUND: The purpose of this study is to increase understanding of the forms of systemic racism experienced by Latinx communities in North Carolina during the COVID-19 pandemic as identified by Latinx community health workers (CHWs) and community-based organization (CBO) leaders. METHODS: We held three focus groups in July 2022 (N = 16) with CHWs and CBO leaders in Spanish to discuss policy and community interventions that improved access to resources during the COVID-19 pandemic; policy or community interventions needed to improve care of Latinx communities; and lessons learned to improve the health of Latinx communities in the future. We performed directed and summative qualitative content analysis of the data in the original language using the Levels of Racism Framework by Dr. Camara Jones to identify examples of implicitly and explicitly discussed forms of systemic racism. RESULTS: Latinx CHWs and CBO leaders implicitly discussed numerous examples of all levels of racism when seeking and receiving health services, such as lack of resources for undocumented individuals and negative interactions with non-Latinx individuals, but did not explicitly name racism. Themes related to institutionalized racism included: differential access to resources due to language barriers; uninsured or undocumented status; exclusionary policies not accounting for cultural or socioeconomic differences; lack of action despite need; and difficulties obtaining sustainable funding. Themes related to personally-mediated racism included: lack of cultural awareness or humility; fear-inciting misinformation targeting Latinx populations; and negative interactions with non-Latinx individuals, organizations, or institutions. Themes related to internalized racism included: fear of seeking information or medical care; resignation or hopelessness; and competition among Latinx CBOs. Similarly, CHWs and CBO leaders discussed several interventions with systems-level impact without explicitly mentioning policy or policy change. CONCLUSION: Our research demonstrates community-identified examples of racism and confirms that Latinx populations often do not name racism explicitly. Such language gaps limit the ability of CHWs and CBOs to highlight injustices and limit the ability of communities to advocate for themselves. Although generally COVID-19 focused, themes identified represent long-standing, systemic barriers affecting Latinx communities. It is therefore critical that public and private policymakers consider these language gaps and engage with Latinx communities to develop community-informed anti-racist policies to sustainably reduce forms of racism experienced by this unique population.

Physician Follow-Up of Pediatric and Young Adult Emergency Department Visits for Substance Use in Ontario, Canada.

PURPOSE: To study the proportion and predictors of outpatient physician follow-up within 60 days of substance-related emergency department (ED) visits for Ontario youth. METHODS: We examined administrative data on substance-related ED visits before and during the COVID-19 pandemic among youths aged 10-24 years in Ontario, Canada. Substance-related visits were identified using International Classification of Diseases-10-CA codes. We described demographic characteristics, receipt of mental health services in the year before the ED visit, disposition from the ED, and follow-up services within 60 days of the ED visit. RESULTS: Between April 1, 2017, and May 31, 2021, 64,236 youth had at least one ED visit for substance use. Visits for alcohol were the most common (49%), followed by cannabis (32.3%). ED visits for all substances were more prevalent during the pandemic than prepandemic, except visits for alcohol. The receipt of follow-up physician care for substance use was low (33.2% prepandemic) but increased during the pandemic (41.7%; adjusted odds ratio 1.34, 95% CI 1.28, 1.39) and varied between substances. Mental health service history in the year before the substance-related ED visit had the strongest association with receipt of follow-up physician care within 60 days (adjusted odds ratio 6.86, 95% CI 6.57, 7.17). DISCUSSION: Youth frequently do not receive physician follow-ups within two months of the substance-related ED visit, although higher follow-up proportions were seen during the pandemic after the implementation of virtual care. Further research is required to understand why follow-up is low and to examine interventions that can increase connection to care.

Towards Regional Population Health Management: A Prospective Analysis Using the Adjusted Clinical Groups Classification.

This research seeks to assess the potential of regionally integrated health management for specific sub-populations, including the incorporation of self-management initiatives. It will achieve this by conducting a thorough stratification analysis of hospital data, utilizing the Adjusted Clinical Groups (ACG) classification system. The approach involves a retrospective review of healthcare data spanning five years, which includes patient demographics, health outcomes, and healthcare utilization metrics. We intend to use the ACG method to classify the patient population into pertinent groups that mirror their health requirements and resource use. The insights obtained from this analysis will be used to create a localized adaptation of the Kaiser Permanente Pyramid Model of Care. This adaptation aims to identify the distribution of costs among patients treated in the Rivierenland Hospital. We anticipate that stratifying data with the ACG method will identify distinct multimorbid subgroups. These subgroups will have unique healthcare requirements. Early interventions and customized health management strategies, based on these insights, could enhance health outcomes and resource efficiency for high-risk patients. This analysis will serve as a foundation for constructive discussions with hospital management and clinical staff, fostering a deeper comprehension of the patients' burden of disease. It might also foster multidisciplinary collaboration opportunities between medical specialties as with regional healthcare partners such as general practitioners (GPs), mental health and other long-term care organizations. Moreover, we anticipate that self-care initiatives, supported by customized health information, will encourage increased patient engagement and strategies for enhancing lifestyle improvements. This strategy is expected to enable the personalization of advanced care planning based on individual needs profiles, thereby improving the management of complex and chronic conditions, and encouraging self-care practices. Our anticipated findings highlight the potential benefits of a data-informed approach to advancing healthcare outcomes and present opportunities for future investigations to refine and implement such integrated care models across the region.

Climate-related health impact indicators for public health surveillance in a changing climate: a systematic review and local suitability analysis.

Climate change challenges public health. Effective management of climate-related health risks relies on robust public health surveillance (PHS) and population health indicators. Despite existing global and country-specific indicators, their integration into local PHS systems is limited, impacting decision-making. We conducted a systematic review examining population health indicators relevant to climate change impacts and their suitability for national PHS systems. Guided by a registered protocol, we searched multiple databases and included 41 articles. Of these, 35 reported morbidity indicators, and 39 reported mortality indicators. Using Chile as a case study, we identified three sets of indicators for the Chilean PHS. The high-priority set included vector-, food-, and water-borne diseases, as well as temperature-related health outcomes indicators due to their easy integration into existing PHS systems. This review highlights the importance of population health indicators in monitoring climate-related health impacts, emphasising the need for local contextual factors to guide indicator selection. Funding: This research project was partly funded by ANID Chile and University College London. None of these sources had any involvement in the research conceptualisation, design, or interpretation of the results.

Addressing cost barriers to healthy eating with Eat Well, a prescription produce subsidy, for patients with diabetes and at risk for food insecurity: Study protocol for a type 1 hybrid effectiveness-implementation pragmatic randomized controlled trial.

BACKGROUND: Patients with diabetes at risk of food insecurity face cost barriers to healthy eating and, as a result, poor health outcomes. Population health management strategies are needed to improve food security in real-world health system settings. We seek to test the effect of a prescription produce program, 'Eat Well' on cardiometabolic health and healthcare utilization. We will also assess the implementation of an automated, affirmative outreach strategy. METHODS: We will recruit approximately 2400 patients from an integrated academic health system in the southeastern United States as part of a two-arm parallel hybrid type 1 pragmatic randomized controlled trial. Patients with diabetes, at risk for food insecurity, and a recent hemoglobin A1c reading will be eligible to participate. The intervention arm receives, 'Eat Well', which provides a debit card with $80 (added monthly) for 12 months valid for fresh, frozen, or canned fruits and vegetables across grocery retailers. The control arm does not. Both arms receive educational resources with diabetes nutrition and self-management materials, and information on existing care management resources. Using an intent-to-treat analysis, primary outcomes include hemoglobin A1C levels and emergency department visits in the 12 months following enrollment. Reach and fidelity data will be collected to assess implementation. DISCUSSION: Addressing food insecurity, particularly among those at heightened cardiometabolic risk, is critical to equitable and effective population health management. Pragmatic trials provide important insights into the effectiveness and implementation of 'Eat Well' and approaches like it in real-world settings. REGISTRATION: ClinicalTrials.gov Identifier: NCT05896644; Clinical Trial Registration Date: 2023-06-09.

Inequality in Physical Activity in Organized Group Settings for Children: A Cross-Sectional Study.

BACKGROUND: Adult-led organized settings for children (eg, classrooms) provide opportunities for physical activity (PA). The structure of setting time may influence inequalities (ie, unequalness) in the distribution of PA. This study examined differences in PA inequality by setting and time-segment purpose in time-segmented organized group settings for children. METHODS: PA and setting meetings were assessed using accelerometer and video observation data from school, before-/after-school, and youth club groups (n = 30) for third- through sixth-grade children (n = 699) in 2 rural US communities. Meetings (n = 130) were time-segmented into smaller units (sessions; n = 835). Each session was assigned a purpose code (eg, PA). Accelerometer data were paired with the meetings and sessions, and the Gini coefficient quantified inequality in activity counts and moderate to vigorous PA minutes for each segment. Beta generalized estimating equations examined differences in PA inequality by setting and session purpose. RESULTS: Activity count inequality was lowest (P < .05) during youth club meetings (Gini = 0.17, 95% CI, 0.14-0.20), and inequality in moderate to vigorous PA minutes was greatest (P < .01) during school (Gini = 0.34, 95% CI, 0.30-0.38). Organized PA sessions (Gini = 0.20, 95% CI, 0.17-0.23) had lower activity count inequality (P < .0001) than academic (Gini = 0.30, 95% CI, 0.27-0.34), enrichment (Gini = 0.31, 95% CI, 0.27-0.36), and nonactive recreation (Gini = 0.30, 95% CI, 0.25-0.34) sessions. Inequality in moderate to vigorous PA minutes was lower (P < .05) in organized PA (Gini = 0.26, 95% CI, 0.20-0.32) and free play (Gini = 0.28, 95% CI, 0.19-0.39) than other sessions. CONCLUSIONS: PA inequality differed by setting time structure, with lower inequality during organized PA sessions. The Gini coefficient can illuminate PA inequalities in organized settings and may inform population PA improvement efforts in rural communities.

The relationship between neighborhood economic deprivation and community-acquired pneumonia related admissions in Maryland.

Introduction: Community-acquired pneumonia (CAP) is a major health concern in the United States (US), with its incidence, severity, and outcomes influenced by social determinants of health, including socioeconomic status. The impact of neighborhood socioeconomic status, as measured by the Distressed Communities Index (DCI), on CAP-related admissions remains understudied in the literature. Objective: To determine the independent association between DCI and CAP-related admissions in Maryland. Methods: We conducted a retrospective study using the Maryland State Inpatient Database (SID) to collate data on CAP-related admissions from January 2018 to December 2020. The study included adults aged 18-85 years. We explored the independent association between community-level economic deprivation based on DCI quintiles and CAP-related admissions, adjusting for significant covariates. Results: In the study period, 61,467 cases of CAP-related admissions were identified. The patients were predominantly White (49.7%) and female (52.4%), with 48.6% being over 65 years old. A substantive association was found between the DCI and CAP-related admissions. Compared to prosperous neighborhoods, patients living in economically deprived communities had 43% increased odds of CAP-related admissions. Conclusion: Residents of the poorest neighborhoods in Maryland have the highest risk of CAP-related admissions, emphasizing the need to develop effective public health strategies beneficial to the at-risk patient population.

Higher ultraviolet light exposure is associated with lower mortality: An analysis of data from the UK biobank cohort study.

We aimed to examine associations between ultraviolet (UV) exposure and mortality among older adults in the United Kingdom (UK). We used data from UK Biobank participants with two UV exposures, validated with measured vitamin D levels: solarium use and annual average residential shortwave radiation. Associations between the UV exposures, all-cause and cause-specific mortality were examined as adjusted hazard ratios. The UV exposures were inversely associated with all-cause, cardiovascular disease (CVD) and cancer mortality. Solarium users were also at a lower risk of non-CVD/non-cancer mortality. The benefits of UV exposure may outweigh the risks in low-sunlight countries.

Improving uptake of population health management through scalable analysis of linked electronic health data.

Population Health Management - often abbreviated to PHM - is a relatively new approach for healthcare planning, requiring the application of analytical techniques to linked patient level data. Despite expectations for greater uptake of PHM, there is a deficit of available solutions to help health services embed it into routine use. This paper concerns the development, application and use of an interactive tool which can be linked to a healthcare system's data warehouse and employed to readily perform key PHM tasks such as population segmentation, risk stratification, and deriving various performance metrics and descriptive summaries. Developed through open-source code in a large healthcare system in South West England, and used by others around the country, this paper demonstrates the importance of a scalable, purpose-built solution for improving the uptake of PHM in health services.

Analysis of the microbial community diversity in various regions of the healthy oral cavity.

BACKGROUND: Microbiomics offers new methods for conducting epidemiological surveys of oral microbiota in large populations. Compared to curette sampling, swab sampling is more convenient and less technically sensitive, making it more suitable for such surveys. To verify the feasibility of using swabs for buccal mucosa sampling in large-scale studies, we collected samples from the buccal mucosa and tooth surfaces of healthy individuals using both swabs and curettes. Microbiomics was employed to analyze and compare microbial abundance and diversity between these two methods. METHODS: Four sites were assessed: the buccal mucosa on both sides and the buccal surfaces of the left and right mandibular first molars. Two sampling methods, swab and curette, were used to collect bacterial communities from healthy individuals. Specifically, buccal mucosa samples (n = 10) and tooth surface samples (n = 20) were analyzed using 16 S rDNA gene sequencing. Bacterial signals were detected through fluorescence in situ hybridization (FISH), targeting the bacterial 16 S rDNA gene. Metastats analysis and Wilcoxon test were used. RESULTS: A total of 383 OTUs were detected in the 30 samples, which belonged to 1 kingdom (bacteria), 11 phyla, 23 classes, 40 orders, 75 families, 143 genus, and 312 species. Among them, 223 OTUs were found on both the buccal mucosa and tooth surfaces. The statistics suggest that although there were no significant differences in colony composition, there were differences in the abundance and distribution of colonies on the dental and buccal mucosal surfaces. When detecting oral disease-causing pathogens such as Enterococcus faecalis and Porphyromonas gingivalis, the efficiency of detection is higher when using curette sampling. Compared to right tooth sampling with a curette, the swab sampling group had higher levels of Firmicutes, while Fusobacteria and Bacteroidetes were more prevalent in the curette tissues. CONCLUSIONS: In oral health individuals, there is no difference in the bacterial composition of the oral buccal mucosa and the dental surface, differing only in abundance. Thus, the buccal mucosa can act as a substitute for the teeth in epidemiological investigations exploring the bacterial composition of the oral cavity.

Rising incidence of obesity-related cancers among younger adults in China: A population-based analysis (2007-2021).

BACKGROUND: Developing countries face an "obesity epidemic," particularly affecting children and younger adults. While obesity is a known risk factor for 12 types of cancer, primarily affecting older populations, its impact on younger generations is understudied. METHODS: This study analyzed data from a population-based cancer registry covering 14.14 million individuals in China (2007-2021). We compared the incidence of obesity- and non-obesity-related cancers and applied an age-period-cohort model to estimate their impacts. FINDINGS: Among 651,342 cancer cases, 48.47% were obesity related. The age-standardized incidence rates (ASRs) of the 12 obesity-related cancers increased annually by 3.6% (p < 0.001), while ASRs for non-obesity-related cancers remained stable. Obesity-related cancers surged among younger adults, with rates rising across successive generations. The annual percentage of change decreased with age, from 15.28% for ages 25-29 years to 1.55% for ages 60-64 years. The incidence rate ratio for obesity-related cancer was higher in younger generations compared to those born in 1962-1966. We predict that the ASR for obesity-related cancers will nearly double in the next decade. CONCLUSIONS: The rising incidence of obesity-related cancers among young adults poses a significant public health concern. The increasing cancer burden underscores the need for targeted interventions to address the obesity epidemic. FUNDING: This work was supported by the National Natural Science Foundation of China (81930019, 82341076) to J.-K.Y.

Spatial and spatio-temporal statistical implications for measuring structural racism: A review of three widely used residential segregation measures.

Social determinants of health are the conditions in the environments where people are born, live, learn, work, play, worship, and age that affect a wide range of health, functioning and quality of life outcomes and risks - these social determinants of health often aid in explaining the racial and ethnic health inequities present in the United States (US). The root cause of these social determinants of health has been tied to structural racism, and residential segregation is one such domain of structural racism that allows for the operationalization of the geography of structural racism. This review focuses on three residential segregation measures that are often utilized to capture segregation as a function of race/ethnicity, income, and simultaneously race/ethnicity and income. Empirical findings related to the spatial and spatio-temporal heterogeneity of these residential segregation measures are presented. We also discuss some of the implications of utilizing these three residential segregation measures.