Citations

ABSTRACT Aim To systematically review and meta‐analyze cohort studies evaluating associations of gingival inflammation, periodontitis, and tooth loss with cognitive decline and incident mild cognitive impairment or dementia. Methods PROSPERO‐registered searches of MEDLINE, Embase, Scopus, Web of Science, and the Cochrane Library identified cohort studies from inception through October 10, 2025, with a PubMed update on June 24, 2026. Random‐effects meta‐analyses pooled adjusted hazard ratios (HRs) for dementia/MCI; cognitive function outcomes were summarized qualitatively. Risk of bias (RoB) was assessed using the Newcastle–Ottawa Scale. Results Fifty‐nine studies met inclusion criteria; 28 contributed to dementia/MCI meta‐analyses. Severe periodontitis (HR: 1.16; 95% CI: 1.06–1.27; I 2 = 0%; Q ‐test p = 0.49), periodontitis of unspecified severity (HR: 1.45; 95% CI: 1.21–1.73; I 2 = 98%; Q ‐test p < 0.001), edentulism (HR: 1.26; 95% CI: 1.19–1.33), and low tooth count (HR: 1.27; 95% CI: 1.14–1.42; I 2 = 94%; Q ‐test p < 0.001) were associated with elevated dementia/MCI risk. RoB was low in 31 studies (53%), moderate in 25 (42%), and high in 3 (5%); inadequate confounder adjustment was common. Meta‐regression showed stronger estimates for ICD‐code periodontitis definitions (fold change (FC) = 1.44 95% CI: 1.04–2.01), older cohorts (FC per year = 1.02 95% CI: 1.00, 1.05), and weaker estimates with lower RoB (FC per NOS star = 0.81 95% CI: 0.73–0.92). Follow‐up duration, cohort age, and RoB were not associated with tooth‐count estimates. Conclusion Periodontitis and tooth loss are associated with modestly higher dementia/MCI risk and poorer cognitive function, but heterogeneity, residual confounding, and bias temper causal interpretation. Longitudinal studies with rigorous baseline cognition assessment and intervention studies are needed.

ABSTRACT Purpose This study assesses the association between colorectal cancer (CRC) screening and a validated, housing-based measure of individual-level socioeconomic status (SES, called HOUSES hereafter) within rural communities and determines whether HOUSES-integrated geospatial analysis can be used to tailor interventions. Methods We used CRC screening data from a subset of Mayo Clinic Midwest patients living in cities without ready access to routine care in the Mayo Clinic Health System in 2019 to represent rural communities. At the individual level, we assessed the association between CRC screening rates and the HOUSES index, adjusting for age, sex, race/ethnicity, comorbidity, distance from home address to clinic, and area deprivation index, using a multilevel mixed-effects logistic regression model. Additionally, we conducted geospatial analysis to examine the correlation between hotspots of 1) lower CRC screening rates and 2) lower SES of the subject population (HOUSES quartile 1). Findings Among 34,489 individuals (median age 64.0 years, 52.4% female), those with the lowest SES (HOUSES Q1) had 37% lower odds of being CRC screening adherent than those with the highest SES (HOUSES Q4) (adj. OR [95% CI]: 0.63 [0.58-0.69]). In the 14 identified HOUSES Q1 hotspots, there was a significant correlation in counts of HOUSES Q1 and low CRC screening (correlation coefficient=0.81). Conclusion Lower SES was significantly associated with lower CRC screening among rural populations. HOUSES-enabled geospatial analysis identified geographic hotspots with lower CRC screening rates for targeted interventions to address disparities in CRC screening in rural communities. HOUSES may be a useful digital tool for cancer preventive care and research.

Racial and ethnic survival disparities exist in pediatric and young adult acute lymphoblastic leukemia (ALL), with differential treatment toxicity and setting of care as possible drivers. Whether treatment cost and utilization disparities exist, or how they may contribute to differences in ALL survival, is unknown. Patients with ALL diagnosed between 2000 and 2019 at ages 1 to 24 years were identified using ICD-9/10 codes in the administrative claims data from the OptumLabs Data Warehouse and the Surveillance, Epidemiology, and End Results program. Sex, race and ethnicity, age, year, and subtype of ALL diagnosis were collected. Reimbursed treatment cost and utilization (number of inpatient and outpatient days) were computed over the initial 8 months of treatment. Regression models assessed associations with demographic and clinical characteristics. Survival analyses assessed associations between race and ethnicity and overall survival. Among 374 individuals with ALL, treatment costs were 57% lower for Black patients than for White patients (estimate 0.43, 95% CI: 0.19-0.96; P =0.04). Utilization was similar across groups, though Black patients had 24% fewer outpatient visits (estimate 0.76, 95% CI: 0.58-0.99; P =0.04). No significant differences in survival were detected, but observations are consistent with previous reports. Despite a small sample size, the statistically significantly lower cost and utilization among Black relative to White ALL patients are concerning and warrant further research.

Introduction Women residing in rural areas or belonging to lower socioeconomic status (SES) strata experience disproportionately low rates of breast cancer screening, contributing to delayed diagnoses and poorer prognoses. In addition, their participation in clinical trials remains markedly limited, reducing opportunities to access preventive and screening interventions. Promoting research preparedness among women before disease onset may empower them to make informed decisions regarding their health and willingness to participate in clinical research with fewer emotional and logistical barriers. Methods and analysis This project applies a community-based participatory research approach to develop and refine the WeCARE (Women’s Engagement for Cancer Awareness, Resources and Education) intervention for women aged 50–74 years who have either never undergone breast cancer screening or have not received screening in the past 5 years and who reside in rural areas or belong to low SES groups. The intervention consists of two components. Component 1 is a single-day, in-person community forum that includes (a) an educational seminar led by an oncologist to address breast cancer risk and screening guidelines, (b) survivor storytelling to enhance emotional engagement and cultural resonance and (c) facilitated navigation to breast cancer screening and future research participation. Component 2 involves structured post-forum follow-up through multiple touchpoints (phone calls and mailed boosters) to reinforce knowledge, address barriers and support screening completion and research enrolment. Quantitative data (eg, screening completion, satisfaction and follow-up engagement) will be summarised using descriptive statistics to assess feasibility and reach on 50 participants. Qualitative feedback from participants will undergo thematic analysis to identify barriers, facilitators and perceived cultural relevance. Integrated mixed-method interpretation will inform iterative refinement of the WeCARE intervention and guide design of subsequent larger trials. Ethics and dissemination Approved by the Mayo Clinic Institutional Review Board (IRB #25–008934). All participants will provide informed consent. Procedures ensure confidentiality, cultural sensitivity and participant safety. Data will be stored in REDCap and disseminated through publications, conferences, local town halls and community reports.

ABSTRACT Importance Rural-urban disparities in chronic disease prevalence are well established; however, the extent to which individual-level socioeconomic status (SES) contributes to these disparities remains unclear. Objective To examine the associations of rurality and SES with the prevalence of five most burdensome chronic diseases among adults. Design We conducted a retrospective cross-sectional study of adults across 27 Upper Midwest counties using the Expanded Rochester Epidemiology Project (E-REP) medical record data linkage system to evaluate associations between rurality, SES and chronic disease prevalence. Prevalence of clinically diagnosed asthma, diabetes, hypertension, coronary heart disease, and mood disorders was identified from International Classification of Diseases ICD9/10 codes over a five-year period (2014-2019). Setting Population based Participants Adults over 18 years residing in the 27 E-REP counties, excluding those missing rural-urban residence status. Exposure HOUSES index, an individual-level measure of SES, served as the primary measure, while rurality based on Rural Urban Commuting Area (RUCA) codes 4-10 was the secondary measure. Main Outcome Prevalence of the five clinically diagnosed chronic diseases was identified using ICD9/10 codes from 2014–2019. Mixed effect logistic regression models were used and adjusted for demographics and general medical examination receipt, to assess rural-urban and SES differences for prevalence of each chronic disease. Results Among 455,802 adults with available HOUSES index, 42.8% lived in rural areas, 53.8% were female and 87.4% were non-Hispanic White. In the unadjusted analysis, rural and urban populations showed comparable asthma and CHD prevalence, while mood disorders, hypertension, and diabetes were more common in urban areas. After adjusting for demographic factors and healthcare utilization, rural-urban differences were no longer statistically significant, whereas SES remained strongly associated with all diseases in a dose response manner (e.g., adjusted Odds Ratio for hypertension (ref: HOUSES index Q4): 1.14, 1.27, and 1.42 for HOUSES index Q3, Q2, and Q1, respectively). Conclusions and Relevance Individual-level SES measured by the HOUSES index, was more strongly associated with chronic disease prevalence than rurality, supporting its integration into population health assessment and risk stratification.

Abstract Introduction: The National Cancer Institute estimated almost 317,000 new breast cancer and over 13,000 new cervical cancer cases in 2025. While the National Breast and Cervical Cancer Early Detection Program has served millions of women over the past two decades, inequities in cancer screening, subsequently delayed diagnosis, and timely and appropriate treatment remain a public health challenge in the United States. Despite the substantial impact of social determinants of health (SDOH) on cancer screening, few studies have accounted for SDOH at the individual level when assessing breast and cervical cancer screening adherence. The primary objective of this study is to examine whether the individual-level SDOH, measured using HOUsing-based SocioEconomic Status (HOUSES) index, is associated with breast and cervical cancer screening non-adherence (not current on respective USPSTF recommendations for age and frequency). Methods: In this retrospective study, patients were identified as those receiving primary care in the Mayo Clinic Health System and Mayo Clinic (Rochester, MN). The Midwest Quality Metrics panel was then used to assess patients due for screening for breast or cervical cancer in July 2023. The HOUSES, using home address and publicly available data on the residence which measures and categorizes housing status into quartiles, was obtained using the electronic health records (EHRs)-linkable patient-level information. Logistic regression analyses were conducted, controlling for Census block group-level adverse social exposome from the Area Deprivation Index, age, and comorbidities. Results are presented as odds ratios (OR) with corresponding 95% confidence intervals (CI). Results: For breast cancer, among 128,462 eligible patients, 20.1% (n= 25,857) were non-adherent. Compared to the highest HOUSES quartile (Q4), lower HOUSES groups showed significantly higher odds of non-adherence: Q3 OR=1.20 (95% CI=1.15, 1.25), Q2 OR=1.45; (95% CI=1.40, 1.53), and Q1 OR=1.90 (95% CI=1.81, 1.99). For cervical cancer, among 175,712 eligible patients, 29.9% (n=52,533) were non-adherent. Compared to the highest HOUSES quartile (Q4), lower HOUSES groups showed significantly higher odds of non-adherence: Q3 OR=1.07 (95% CI=1.03, 1.10), Q2 OR=1.16; (95% CI=1.12, 1.20), and Q1 OR=1.36 (95% CI=1.31, 1.41). Conclusions: A clinically meaningful association between the HOUSES index and cancer screening adherence was observed. A lower HOUSES index was associated with higher odds of non-adherence for both breast and cervical cancer screening, even after accounting for neighborhood-level risk, age, and comorbidities. Incorporating HOUSES into EHRs can be a practical “screening-for-screening” tool that enables close monitoring of higher-risk patients without additional burden of surveys. Citation Format: Eunice Y. Park, Madison Beenken, Dave Watson, Chung Il Wi, Tufia Haddad, Gladys Asiedu, Karla BALLMAN, James R. Cerhan, Carolyn Flock, Brian Lynch, Folakemi T. Odedina, Scott H. Okuno, Young J Juhn, . HOUSES as a screening tool for cancer screening: Patient-level housing-based socioeconomic status and breast and cervical cancer screening adherence [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 7599.

Background Mortality in adults with congenital heart disease (CHD) is strongly driven by disease complexity. Social determinants of health (SDOH) influence adult CHD (ACHD) health outcomes but their impact on mortality is unclear. This study examined the influence of clinical factors and SDOH on all‐cause mortality in patients with ACHD. Methods Single‐center retrospective cohort study of patients with ACHD in the Mayo ACHD Registry who had a verifiable residential address between January 1, 2004 and December 31, 2023. Clinical and SDOH indicators were extracted, including insurance type, language, rural–urban commuting area code, and a housing‐based socioeconomic index, an individual‐level measure of socioeconomic status derived from 4 objective housing characteristics and categorized into quartiles (Q1–Q4). Cox proportional‐hazards models were fitted to evaluate associations with mortality, incorporating CHD severity, arrhythmias, SDOH indicators, and other comorbidities. County of residence was included as a random effect, and model discrimination was assessed using the concordance statistic. Results Among 6134 patients with ACHD, the mean age was 38±16 years; 51% were male; 78.7% were White and 44.9% had rural residence. Independent predictors of mortality included cyanotic CHD (adjusted hazard ratio [aHR], 5.70 [95% CI, 2.90–11.23]), Fontan palliation (aHR, 4.98 [95% CI, 2.56–9.70]), ventricular tachycardia (aHR, 1.71 [95% CI, 1.16–2.52]), older age at first visit (aHR, 1.05 per year [95% CI, 1.04–1.05]), male sex (aHR, 1.19 [95% CI, 1.03–1.39]), public insurance (aHR, 1.60 [95% CI, 1.35–1.90]), rural residence (aHR, 1.25 [95%, CI 1.06–1.47]), and non‐English language (aHR 1.75 [95% CI 1.38–2.23]). The housing‐based socioeconomic index quartile was not associated with mortality. The final model achieved a concordance statistic of 0.77. Conclusions Mortality in patients with ACHD is strongly influenced by both clinical factors and SDOH, independent of socioeconomic status. Addressing barriers to care such as language, insurance, and geography is essential for improving ACHD survival particularly in those at increased mortality risk.

Abstract Background Coagulation markers are used to guide clinical anticoagulation decisions. We aimed to identify circulating metabolites that are associated with coagulation markers in children with congenital heart disease (CHD). Methods Plasma samples were separated from whole blood under consistent conditions. Untargeted metabolomic data were measured in plasma from up to 203 young patients (age range: 0 days-24 years) with CHD before cardiac surgery. Coagulation markers included activated partial thromboplastin time (aPTT), prothrombin time (PT), and activated clotting time (ACT). Weighted Gene Co-expression Network Analysis (WGCNA) was performed to explore metabolite modules (clusters). Associations of metabolites with the coagulation markers were assessed cross-sectionally with regression models, with false discovery rate (FDR) correction for multiple comparison. Associations between coagulation markers and ‘eigenmetabolites’ from WGCNA modules were assessed by correlation analysis. Results A total of 776 metabolites were included in the final analysis. Among these, 20 metabolites were associated with PT and one (valine) with ACT (FDR q value < 0.05). Among the metabolites associated with PT, the top three were retinol, 1-palmitoyl-GPI (16:0), and X-25371 (identity unknown). One module from WGCNA with metabolites from the lipid super pathway was correlated with PT (P = 0.004). Conclusion In this first attempt to identify novel metabolites for coagulation markers, we report 21 metabolites associated with PT or ACT in children with CHD. Future studies are needed to replicate these findings in independent cohorts and to elucidate the biological mechanisms linking these metabolites to hemostatic regulation.

OBJECTIVES The 2-bag intravenous (IV) fluid system for diabetic ketoacidosis (DKA) has been associated with shorter duration of insulin and faster resolution of acidosis. Our aims were to increase the use of 2-bag IV fluids among children with medium- or high-risk DKA treated at 2 tertiary care pediatric hospitals and to increase the proportion of children who receive timely administration of fluid and insulin treatments. METHODS We conducted a quality improvement initiative using data from January 1, 2014, to December 31, 2021, among patients 21 years or younger with medium- or high-risk DKA. The study spanned pre- and post-initiative periods and a stability period. Our interventions included development of a clinical practice guideline, education, and electronic medical record updates. Statistical process control methods were used to evaluate outcome changes. RESULTS We identified 876 eligible encounters. Age, sex, and the proportion of children with medium- or high-risk DKA were similar across study periods. A higher proportion of non-Hispanic Black children was observed in the stability period (26.3%) than the pre- (17.7%) and post-initiative (18.2%) periods. We observed an increase in 2-bag IV fluid use from an average of 41.3% to 77.7%. We did not observe changes in time to isotonic fluid bolus, continuous insulin, or 2-bag IV fluids. There was no change in hypoglycemic events. CONCLUSION We increased the proportion of children with medium- or high-risk DKA treated with 2-bag IV fluids through a combination of interventions, including implementation and refinement of a clinical guideline, creation of a nurse algorithm, and nursing education.