Impact of Social Vulnerability and Demographics on Ischemic Heart Disease Mortality in the United States.

Background: Cardiovascular disease is a leading cause of morbidity and mortality, largely dominated by ischemic heart diseases (IHDs). Social determinants of health, including geographic, psychosocial, and socioeconomic factors, influence the development of IHD. Objectives: This study aimed to evaluate yearly trends and disparities in IHD mortality and to assess the impact of social vulnerability. Methods: We performed cross-sectional analyses using United States county-level mortality data and social vulnerability index (SVI) obtained from the Centers for Disease Control and Prevention databases. Age-adjusted mortality rates (AAMRs) per 100,000 population were compared between aggregated U.S. county groups, stratified by demographic information and SVI quartiles. Log-linear regression models were used to identify mortality trends from 1999 to 2020, with inflection points determined through the Monte-Carlo permutation test. Results: We identified a total of 9,108,644 deaths related to IHD between 1999 and 2020. Overall AAMR decreased from 194.6 in 1999 to 91.8 in 2020. Males (AAMR: 161.51) and Black (AAMR: 141.49) populations exhibited higher AAMR compared to females (AAMR: 93.16) and White (AAMR: 123.34) populations, respectively. Disproportionate AAMRs were observed among nonmetropolitan (AAMR: 136.17) and Northeastern (AAMR: 132.96) regions. Counties with a higher SVI experienced a greater AAMR, with a cumulative excess of 20.91 deaths per 100,000 person-years associated with increased social vulnerability. Conclusions: Despite a decline in IHD mortality from 1999 to 2020, disparities persisted among racial, gender, and geographic subgroups. A higher SVI was linked to increased IHD mortality. Policy interventions should prioritize integrating the SVI into health care delivery systems to effectively address these disparities.

The association between cognition and dual-tasking among older adults: the effect of motor function type and cognition task difficulty.

BACKGROUND: Dual-task actions challenge cognitive processing. The usefulness of objective methods based on dual-task actions to identify the cognitive status of older adults has been previously demonstrated. However, the properties of select motor and cognitive tasks are still debatable. We investigated the effect of cognitive task difficulty and motor task type (walking versus an upper-extremity function [UEF]) in identifying cognitive impairment in older adults. METHODS: Older adults (≥65 years) were recruited, and cognitive ability was measured using the Montreal Cognitive Assessment (MoCA). Participants performed repetitive elbow flexion under three conditions: 1) at maximum pace alone (Single-task); and 2) while counting backward by ones (Dual-task 1); and 3) threes (Dual-task 2). Similar single- and dual-task gait were performed at normal speed. Three-dimensional kinematics were measured for both motor functions using wearable sensors. RESULTS: One-hundred older adults participated in this study. Based on MoCA score <20, 21 (21%) of the participants were considered cognitively impaired (mean age =86±10 and 85±5 for cognitively impaired and intact participants, respectively). Within ANOVA models adjusted with demographic information, UEF dual-task parameters, including speed and range-of-motion variability were significantly higher by 52% on average, among cognitively impaired participant (p<0.01). Logistic models with these UEF parameters plus age predicted cognitive status with sensitivity, specificity, and area under curve (AUC) of 71%, 81% and 0.77 for Dual-task 1. The corresponding values for UEF Dual-task 2 were 91%, 73% and 0.81, respectively. ANOVA results were non-significant for gait parameters within both dual-task conditions (p>0.26). CONCLUSION: This study demonstrated that counting backward by threes within a UEF dual-task experiment was a pertinent and challenging enough task to detect cognitive impairment in older adults. Additionally, UEF was superior to gait as the motor task component of the dual-task. The UEF dual-task could be applied as a quick memory screen in a clinical setting.

Frailty Assessment Predicts Acute Outcomes in Patients Undergoing Screening Colonoscopy.

BACKGROUND: Colonoscopy is associated with multiple adverse outcomes. With an aging population undergoing colorectal cancer screening, few modalities exist to assess the patient risk prior to colonoscopy. Frailty, the age-related decline in reserve and function across multiple organ systems, predicts poor surgical outcomes, but its role in endoscopy is unclear. AIMS: This prospective cohort study assesses the efficacy of frailty in predicting acute colonoscopy outcomes. METHODS: Participants aged ≥ 50 years undergoing screening colonoscopy at a tertiary care center were recruited over 2 months ending in July 2017. Frailty was assessed using a validated 20-s upper-extremity frailty test, which measures the capacity of muscle performance. Demographic data, American Society of Anesthesiologists (ASA) status, and Charlson comorbidity index (CCI) were evaluated. Procedure-related adverse events and cardiopulmonary changes during and in the immediate post-procedure period were recorded. Adverse events were stratified into minor and major events. Chi-square and ANCOVA models were used in the analysis. RESULTS: Ninety-nine adults (mean age 62.8 years) were enrolled, among which 49 were non-frail and 50 were pre-frail/frail; 50 were female. Overall, 55 participants experienced a total of 87 adverse events. Frailty and ASA status were significantly associated with colonoscopy adverse events (p = 0.01 and p = 0.02, respectively). Age and CCI did not predict colonoscopy outcomes. CONCLUSIONS: Compared to age and CCI, frailty status better predicts colonoscopy outcomes in older adults. Among adults undergoing colonoscopy, routine frailty screening should be considered for risk stratification. Additional prospective studies evaluating frailty measurements in endoscopy will further clarify its role in forecasting adverse events.