Managing Bleeding Risk in Older Adults

Low handgrip strength (HGS) and abdominal obesity (AO) have been reported to be linked to an increased all-cause mortality risk in older adults. However, the combined impact of AO with low HGS and/or HGS asymmetry on mortality risk remains unclear. Therefore, this study aimed to investigate the synergistic effects of AO and abnormal HGS on mortality risk among Chinese older adults. Baseline data of the China Health and Retirement Longitudinal Study in 2011, along with mortality outcomes obtained in 2018 were used for the analysis. Low HGS was identified as HGS <18 kg in women or <28 kg in men, while HGS asymmetry is defined as an HGS of either hand > 10% stronger than the other. AO was characterized by a waist circumference ≥90 cm in men and ≥85 cm in women. Logistic regression analysis was used to evaluate the relationship between AO, abnormal HGS and mortality risk. A total of 5186 subjects aged 60 years or older were enrolled, 50.6% of whom were male. The proportions of participants with only AO, only low HGS, only HGS asymmetry, low HGS with asymmetry, both AO and low HGS, both AO and asymmetric HGS, and AO with both low HGS and asymmetry were 20.0%, 6.1%, 16.6%, 8.3%, 3.2%, 13.4%, and 3.9%, respectively. Over the course of a 7-year follow-up interval, 970 of these individuals died, with 13.4%, 12.4%, 13.6%, 15.5%, 4.1%, 10.1% and 6.9% of deaths in the above groups, respectively. The adjusted logistic regression analysis model confirmed that only low HGS (OR = 1.897, 95%CI: 1.386-2.596, p<0.001), low HGS with asymmetry (OR = 1.680, 95%CI: 1.265-2.231, p<0.001), and AO combined with both low HGS and asymmetry (OR = 2.029, 95%CI: 1.381-2.981, p<0.001) were associated with a higher risk of mortality. Low HGS, with or without asymmetry, is associated with increased mortality risk in older Chinese adults without AO, and the combination of low HGS and HGS asymmetry further elevates mortality risk in those with AO.

Research has shown the importance of Electronic Health Records (EHR) and in-home sensor data for continuous health tracking and health risk predictions. With the increased computational capabilities and advances in machine learning techniques, we have new opportunities to use multi-modal health big data to develop accurate health tracking models. This dissertation describes the development, evaluation, and testing of systems for predicting functional health and fall risks in community-dwelling older adults using health data and machine learning techniques. In an initial study, we focused on organizing and de-identifying EHR data for analysis using HIPAA regulations. The dataset contained nine years of structured and unstructured EHR data obtained from TigerPlace, a senior living facility at Columbia, MO. The de-identification of this data was done using custom automated algorithms. The de-identified EHR data was used in several studies described in this dissertation. We then developed personalized functional health tracking models using geriatric assessments in the EHR data. Studies show that higher levels of functional health in older adults lead to a higher quality of life and improves the ability to age-in-place. Even though several geriatric assessments capture several aspects of functional health, there is limited research in longitudinally tracking the personalized functional health of older adults using a combination of these assessments. In this study, data from 150 older adult residents were used to develop a composite functional health prediction model using Activities of Daily Living (ADL), Instrumental Activities of Daily Living (IADL), Mini-Mental State Examination (MMSE), Geriatric Depression Scale (GDS), and Short Form 12 (SF12). Tracking functional health objectively could help clinicians to make decisions for interventions in case of functional health deterioration. We next constructed models for fall risk prediction in older adults using geriatric assessments, demographic data, and GAITRite assessment data. A 6-month fall risk prediction model was developed with data from 93 older adult residents. Explainable AI techniques were used to provide explanations to the model predictions, such as which specific features increased the risk of fall in a particular model prediction. Such explanations to model predictions provide valuable insights for targeted interventions. In another study, we developed deep neural network models to predict fall risk from de-identified nursing notes data from 162 older adult residents from TigerPlace. Clinical nursing notes have been shown to contain valuable information related to fall risk factors. This analysis provides the groundwork for future experiments to predict fall risk in older adults using clinical notes. In addition to using EHR data to predict functional health and fall risk in older adults, two studies were conducted to predict fall and functional health from in-home sensor data. Models for in-home fall prediction using depth sensor imagery have been successfully used at TigerPlace. However, the model is prone to false fall alarms in several scenarios, such as pillows thrown on the floor and pets jumping from couches. A secondary fall analysis was performed by analyzing fall alert videos to further identify and remove false alarms. In the final study, we used in-home sensor data streaming from depth sensors and bed sensors to predict functional health and absolute geriatric assessment values. These prediction models can be used to predict the functional health of residents in absence of sparse and infrequent geriatric assessments. This can also provide continuous tracking of functional health in older adults using the streaming in-home sensor data.

Objectives This cross-sectional study examined whether age moderates the relation between sleep problems and suicide risk and investigated whether sleep problems are differentially associated with suicide risk in younger (18–40) and older (60+) adults. Methods MTurk workers (N = 733) completed the Pittsburgh Sleep Quality Index, Suicidal Behavior Questionnaire–Revised, Patient Health Questionnaire, and demographic questions. Analysis of variance and linear regressions were utilized. Results Older adults scored lower on four PSQI components, symptoms of depression, and suicide risk than younger adults. Age significantly moderated the relation between sleep problems and suicide risk after controlling for gender and depressive symptoms, F(5, 635) = 72.38, p < .001. Sleep problems significantly related to suicide risk in younger adults (t = 6.47, p < .001) but not in older adults (t = 0.57, p = .57). Sleep medication use was related to suicide risk in both groups, whereas daytime dysfunction was related to suicide risk in older adults and sleep disturbances were related to suicide risk in younger adults. Conclusions The relation between sleep problems and suicide risk differs between younger and older adults. This study adds to the literature suggesting that sleep medications may not be appropriate for older adults. Clinical Implications Sleep problems are significantly related to suicide risk in younger adults but not older adults. Sleep medication use is associated with suicide risk regardless of age.

ABSTRACTBackgroundSarcopenic obesity (SO) is characterized by the presence of both obesity and sarcopenia and is related to disability and loss of independence in older adults. The extent to which time spent in light physical activity (LPA), or moderate‐to‐vigorous physical activity (MVPA) is associated with SO risk in older adults remains unclear. The aim of this study was (a) to examine the association between the level of adherence to recommended amounts of MVPA and the risk of SO in older adults and (b) to determine whether time spent in LPA is associated with SO risk independently of time spent in MVPA.MethodsThis cross‐sectional study involved 862 community‐dwelling older adults (58% women; aged 65–79 years) from four European countries. Accelerometer‐determined time in MVPA was categorized as follows: inactive (< 75 min/week), moderately active (75–149 min/week), active (150–299 min/week) and highly active (≥ 300 min/week). Time in LPA was expressed in tertiles. The outcome measure SO risk was determined based on appendicular lean mass, waist circumference, handgrip strength and the 5‐times sit‐to‐stand test. Odds ratios (OR) with a 95% confidence interval (95% CI) of high SO risk across levels of MVPA and LPA were determined by binary logistic regression adjusted for the level of systemic inflammation (high‐sensitivity C‐reactive protein) and dietary protein intake.ResultsCompared to the inactive group, ORs of having a high SO risk were about 50%–80% lower, depending on the MVPA level, with the largest risk reduction in the highly active group (OR: 0.23, 95% CI: 0.13–0.39; p < 0.05). The likelihood of having a high SO risk was significantly lower among the highly active group compared to the active group (OR: 0.50; 95% CI: 0.33–0.77; p < 0.05). More time in LPA was associated with a significantly lower likelihood of having high SO risk (highest vs. lowest tertile: OR: 0.52, 95% CI: 0.30–0.89; p < 0.05) only in participants with low amounts of MVPA. In contrast, LPA was not associated with SO risk among participants meeting the MVPA recommendation.ConclusionsMVPA is strongly associated with a lower likelihood of having a high SO risk in older adults, independently of the level of systemic inflammation and intakes of dietary proteins. LPA is related to SO risk in sedentary older adults, which supports the promotion of physical activity regardless of intensity for mitigating SO.

As the population and longevity of older adults’ increases, the prevalence of falls is becoming an ever-growing issue. Falls in older adults may lead to sedentary behavior, decreased independence, and lower quality of life. Evidence has shown that traditional exercise programs emphasizing strength and balance can decrease the fall risk in older adults, but may be difficult to sustain over time. Emerging evidence suggests that exercises that are integrated into daily life, as seen in the Lifestyle-integrated Functional Exercise (LiFE) program, may have a more lasting effect in reducing fall risk in older adults. This study explored the effectiveness of a 26-week modified-LiFE program in decreasing fall risk in community-dwelling older adults. Purposive sampling of men and women 65 years and older, with or without a history of falls, living at two retirement communities yielded 16 participants. Participants were assessed three times using a battery of six fall risk assessments. Results demonstrated a significant reduction in fall risk, and increase in strength and balance. Additionally, results showed a trend toward sustainability of exercise. Therefore, integrating exercises into daily life may offer occupational therapists an effective occupation-based intervention that promotes safety, independence, and quality of life for older adults.

Dietary screening tool identifies nutritional risk in older adults

We performed a meta-analysis on the relationship between positive affect (PA) and mortality risk in older adults (55 years and older) and reviewed evidence on the Main Effect Model and the Stress-buffering Model of PA. Four databases (ISI Web of Knowledge, APA PsycNET, PubMed, and Embase) were used to identify potential studies. Three types of effect sizes (ESs), odds ratio, relative risk, and hazard ratio (OR, RR, and HR), were calculated and analyzed within a random effects model. The analysis of the studies in which the effects of other variables were not controlled indicated that older adults with higher levels of positive affect had lower mortality risk (75%, HR = 0.75, 95% confidence interval [CI] = 0.66-0.85) than those with lower positive affect. In studies in which the effects of covariates were controlled, this rate was 85% (HR = 0.85, 95% CI = 0.81-0.89), which was still significant. These results suggest that higher positive affect is associated with lower mortality risk in community-dwelling older adults, even after controlling for medical, psychological, and social factors. The results point to potential methods of improving longevity, and to achieving healthy aging in older adults.

This secondary analysis explored the association between the sarcopenia index (SI), calculated using serum creatinine and cystatin C values, and fall risk in middle aged and older adults with impaired renal function (estimated glomerular filtration rate < 90 mL/min/1.73 m²). Data from the 2011 baseline and 2015 follow-up cohorts of the China Health and Retirement Longitudinal Study were analyzed. Impaired renal function was defined using estimated glomerular filtration rate values, and the SI was derived as the product of serum creatinine and cystatin C-based estimated glomerular filtration rate. Falls were assessed using self-reported questionnaires during follow-up. Multivariate logistic regression and restricted cubic spline models were used to evaluate the SI-fall relationship, and subgroup analyses identified high-risk populations. Among 3461 participants, 20.8% reported falls. Higher SIs were associated with fewer falls, with adjusted odds ratios (95% confidence interval) for Q2, Q3, and Q4 of 0.75 (0.57–0.99), 0.66 (0.46–0.93), and 0.54 (0.31–0.93) versus Q1, respectively. The restricted cubic spline analysis indicated no dose–response relationship (P, overall = .312). Stratified analyses revealed a pronounced protective effect in individuals with obesity (odds ratio: 0.57, 95% confidence interval: 0.36–0.92; P, interaction = .039). SI was inversely associated with fall risk in older adults with impaired renal function, particularly in those with obesity. These findings support the use of SI as a practical biomarker for identifying high-risk individuals and developing targeted fall prevention strategies.

To test the hypothesis that methylphenidate modifies markers of fall risk in older adults. Randomized, double-blind, placebo-controlled, single-dose cross-over study. Outpatient movement disorders clinic. Twenty-six community-living older adults without dementia (mean age 73.8) with subjective complaints of "memory problems." The study examined the effects of a single dose of 20 mg of methylphenidate (MPH) on cognitive function and gait. Participants were evaluated before and 2 hours after taking MPH or a placebo in sessions 1 to 2 weeks apart. The Timed Up and Go and gait variability quantified mobility and fall risk. A computerized neuropsychology battery quantified memory and executive function (EF). Timed Up and Go times, stride time variability, and measures of EF significantly improved in response to MPH but not in response to the placebo. In contrast, MPH did not significantly affect memory or finger tapping abilities. In older adults, MPH appears to improve certain aspects of EF, mobility, and gait stability. Although additional studies are required to assess clinical utility and efficacy, the present findings suggest that methylphenidate and other drugs that are designed to enhance attention may have a role as a therapeutic option for reducing fall risk in older adults.

Introduction: In middle-aged adults, time spent being sedentary is associated with cardiovascular (CV) health risks independent of structured physical activity (PA). However, data are sparse regarding the impact of sedentary behavior on CV risk in older adults. The extent to which the absolute duration or intensity of daily PA reduces CV risk in older adults is also unknown. Objectives: Our objective was to examine the cross-sectional association between objectively-measured sedentary behavior and predicted CV risk among older adults in the Lifestyle Interventions and Independence for Elders (LIFE) study. The secondary objective was to evaluate associations between the duration/intensity of daily PA and predicted CV risk. Methods: LIFE is a randomized clinical trial to determine if regular PA prevents mobility disability among mobility-limited older adults. Activity data were collected by hip-worn accelerometer at baseline prior to participation in study interventions. Only participants with at least three days of accelerometry data (≥ 10 hrs wear time) were included. Unadjusted and adjusted linear regression was used to model the relationship between accelerometry measures and predicted 10-year Framingham risk of Hard Coronary Heart Disease (HCHD; i.e. myocardial infarction or coronary death). Adjusted models included demographic confounders (e.g. education, race, income) and health parameters (e.g. depression, cognition, arthritis) not in the risk score. Accelerometry cut-points were (in counts/min): sedentary behavior: &lt; 100; low-intensity activity: 100-499; higher intensity activity: &gt; 500. Results: Participants (n = 1170; 78.7 ± [SD] 5.3 years; 66.1% female) had a median HCHD risk of 10.3% (25 th -75 th %: 5.7-18.6). Over a mean accelerometer wear time of 8.1 ± 3.2 days, participants spent 77.0 ± 8.2% of their time sedentary. They also spent 16.6 ± 5.0% of their time in low-intensity PA and 6.4 ± 4.4% in higher-intensity PA. For all PA performed (&gt; 100 counts/min), participants achieved a median of 393.4 (337.8-473.5) counts/min. In the unadjusted model, time spent sedentary (β = 2.41; 95% CI : 1.94, 2.89), in low-intensity PA (-2.56; -3.03, -2.08), and in higher-intensity PA (-1.60; -2.09, -1.11) were all associated with HCHD risk (all p’s &lt; 0.001). These associations remained significant after adjustment. The mean intensity of daily PA was not significantly associated with HCHD risk in any model (p &gt; 0.05). Conclusions: Daily time spent being sedentary is positively associated with predicted 10-year HCHD risk among mobility-limited older adults. Duration, but not mean intensity, of daily PA is inversely associated with HCHD risk score in this population.

BackgroundNon-alcoholic fatty liver disease (NAFLD) is a common chronic liver condition that affects a quarter of the global adult population. To date, only a few NAFLD risk prediction models have been developed for Chinese older adults aged ≥ 60 years. This study presented the development of a risk prediction model for NAFLD in Chinese individuals aged ≥ 60 years and proposed personalised health interventions based on key risk factors to reduce NAFLD incidence among the population.MethodsA cross-sectional survey was carried out among 9,041 community residents in Shanghai. Three NAFLD risk prediction models (I, II, and III) were constructed using multivariate logistic regression analysis based on the least absolute shrinkage and selection operator regression analysis, and random forest model to select individual characteristics, respectively. To determine the optimal model, the three models’ discrimination, calibration, clinical application, and prediction capability were evaluated using the receiver operating characteristic (ROC) curve, calibration plot, decision curve analysis, and net reclassification index (NRI), respectively. To evaluate the optimal model’s effectiveness, the previously published NAFLD risk prediction models (Hepatic steatosis index [HSI] and ZJU index) were evaluated using the following five indicators: accuracy, precision, recall, F1-score, and balanced accuracy. A dynamic nomogram was constructed for the optimal model, and a Bayesian network model for predicting NAFLD risk in older adults was visually displayed using Netica software.ResultsThe area under the ROC curve of Models I, II, and III in the training dataset was 0.810, 0.826, and 0.825, respectively, and that of the testing data was 0.777, 0.797, and 0.790, respectively. No significant difference was found in the accuracy or NRI between the models; therefore, Model III with the fewest variables was determined as the optimal model. Compared with the HSI and ZJU index, Model III had the highest accuracy (0.716), precision (0.808), recall (0.605), F1 score (0.692), and balanced accuracy (0.723). The risk threshold for Model III was 20%–80%. Model III included body mass index, alanine aminotransferase level, triglyceride level, and lymphocyte count.ConclusionsA dynamic nomogram and Bayesian network model were developed to identify NAFLD risk in older Chinese adults, providing personalized health management strategies and reducing NAFLD incidence.

Advanced glycation end-products (AGEs) are irreversibly and heterogeneously formed compounds during the non-enzymatic modification of macromolecules, such as proteins. Aging and lifestyle habits, such as high-fat and high-protein diets, and smoking, promote AGEs accumulation. This study aimed to investigate the relationship between fall risk and AGEs in community-dwelling older adults. This cross-sectional study included patients from the 2022 Yakumo Study who were evaluated for fall risk index 5-items version, locomotive syndrome stage and AGEs. AGEs were evaluated using Skin autofluorescence (SAF) measured by the AGE reader (DiagnOptics Technologies BV, Groningen, the Netherlands). We divided the participants into two groups according to the presence or absence of fall risk (fall risk index 5-items version ≥6 or not), and investigated the factors associated with fall risk. The fall risk group had a higher age and SAF, and a higher proportion of locomotive syndrome stage >2 than the without fall risk group in patients aged ≥65 years (P < 0.01). The multivariate logistic regression analysis after adjustment of age, sex and body mass index showed that locomotive syndrome stage ≥2 and SAF were independent associators of fall risk in older adults (odds ratio 3.26, P < 0.01, odds ratio 2.96, P < 0.05, respectively). The optimal cutoff value of the SAF for fall risk was 2.4 (area under the curve 0.631; 95% CI 0.53-0.733; sensitivity 0.415; specificity 0.814; P < 0.05). The accumulation of AGEs in skin tissues can be used to screen for fall risk comprehensively. Geriatr Gerontol Int 2024; 24: 517-522.

Association of daily step volume and intensity with cardiometabolic risk in older adults

APTA-Geriatrics, an Academy of the American Physical Therapy Association, appointed a guideline development group (GDG) to develop a clinical practice guideline (CPG) synthesizing the evidence for physical therapy management of fall risk in community-dwelling older adults. The GDG consisted of five physical therapists with clinical expertise in the management of fall risk in older adults and methodological expertise in evidence-based document development. The CPG includes a systematic review of existing literature, and stringent methodology developed by the American Physical Therapy Association to form the evidence-based recommendations. The CPG content, including methodology, recommendations and algorithm were externally reviewed by clinical providers and academicians with expertise in fall risk management for older adults. These recommendations are intended to assist physical therapists and physical therapist assistants who are engaged in fall risk management for community-dwelling older adults.

Backward walking is increasingly recognized as an alternative task for detecting balance deficits and fall risk in older adults. However, its utility as a functional indicator in healthy populations remains underexplored. This study aimed to investigate the potential associations between the backward walking speed (BWS), physical balance, and fall risk in community-dwelling older adults. In this cross-sectional study, 90 community-dwelling older adults were recruited. Self-selected backward walking speed (SBWS) was assessed together with the Berg Balance Scale (BBS), the Performance-Oriented Mobility Assessment (POMA), and the Fall Risk Index (FRI). Grip strength and cognitive function, evaluated using the Montreal Cognitive Assessment (MoCA), were also measured as covariates. Fear of backward walking (FoBW) was investigated using a self-administered questionnaire prior to the walking tests. Pearson correlation and multiple regression analyses were performed to examine the associations between SBWS, physical balance, and fall risk. The data of 84 participants (mean ± SD age 75.7 ± 5.0years) were analyzed. Their mean forward and backward walking speeds were 1.36 ± 0.23m/s and 0.73 ± 0.24m/s, respectively. The SBWS showed moderate correlations with the Timed Up and Go (TUG) test (r = -0.52), forward speed (r = 0.49), and grip strength (r = 0.41), and weaker correlations with the BBS (r = 0.38), MoCA (r = 0.23)andFES-I (r = -0.34) . No statistically significant correlations were found between SBWS and POMA-Total (r = 0.20), FRI (r = 0.09). In adjusted regression models, SBWS was significantly associated with higher BBS scores (β = 3.744, p = 0.023) and lower TUG times (β = -1.488, p = 0.029) but not with the POMA-Total (β = 1.052, p = 0.344) or FRI (β = 3.001, p = 0.096). BWS may serve as a multidimensional indicator of physical and psychological vulnerability in older adults. Longitudinal studies with dynamic or dual-task assessments are necessary to validate its predictive value for fall risk screening.