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BACKGROUND/OBJECTIVES The number of older adults with complex health needs is growing, and this population experiences disproportionate morbidity and mortality. Interventions led by community health workers (CHWs) can improve clinical outcomes in the general adult population with multimorbidity, but few studies have investigated CHW-delivered interventions in older adults. DESIGN We systematically reviewed the impact of CHW interventions on health outcomes among older adults with complex health needs. We searched for English-language articles from database inception through April 2020 using seven databases. PROSPERO protocol registration CRD42019118761. SETTING Any U.S. or international setting, including clinical and community-based settings. PARTICIPANTS Adults aged 60 years or older with complex health needs, defined in this review as multimorbidity, frailty, disability, or high-utilization. INTERVENTIONS Interventions led by a CHW or similar role consistent with the American Public Health Association's definition of CHWs. MEASUREMENTS Pre-defined health outcomes (chronic disease measures, general health measures, treatment adherence, quality of life, or functional measures) as well as qualitative findings. RESULTS Of 5671 unique records, nine studies met eligibility criteria, including four randomized controlled trials, three quasi-experimental studies, and two qualitative studies. Target population and intervention characteristics were variable, and studies were generally of low-to-moderate methodological quality. Outcomes included mood, functional status and disability, social support, well-being and quality of life, medication knowledge, and certain health conditions (e.g., falls, cognition). Results were mixed with several studies demonstrating significant effects on mood and function, including one high-quality RCT, while others noted no significant intervention effects on outcomes. CONCLUSION CHW-led interventions may have benefit for older adults with complex health needs, but additional high-quality studies are needed to definitively determine the effectiveness of CHW interventions in this population. Integration of CHWs into geriatric clinical settings may be a strategy to deliver evidence-based interventions and improve clinical outcomes in complex older adults.

Objective: A 5% change in weight is a significant predictor for frailty and obesity. We ascertained how self-reported weight change over the lifespan impacts rates of frailty in older adults. Methods: We identified 4,984 subjects ≥60 years with body composition measures from the National Health and Nutrition Examination Survey. An adapted version of Fried’s frailty criteria was used as the primary outcome. Self-reported weight was assessed at time current,1 and 10 years earlier and at age 25. Weight changes between each time point were categorized as ≥ 5%, ≤5% or neutral. Logistic regression assessed the impact of weight change on the outcome of frailty. Results: Among 4,984 participants, 56.5% were female, mean age was 71.1 years, and mean BMI was 28.2kg/m2. A weight loss of ≥ 5% had a higher association with frailty compared to current weight, age 25 (OR 2.94 [1.72,5.02]), 10 years ago (OR 1.68 [1.05,2.69]), and 1 year ago (OR 1.55 [1.02,2.36]). Weight gain in the last year was associated with increased rate of frailty (1.59 [1.09,2.32]). Conclusion: There is an association between frailty and reported weight loss over time while only weight gain in the last year has an association with frailty.

OBJECTIVE: Body composition changes with aging can increase rates of obesity, frailty and impact function. Measuring adiposity using body fat (%BF) or central adiposity using waist circumference (WC) have greater diagnostic accuracy than traditional measures such as body mass index (BMI). DESIGN: This is an observational study SETTING: This study focused on older community-dwelling participants PARTICIPANTS: We identified individuals age ≥ 60 years old using the 1999–2004 cross-sectional National Health and Nutrition Survey (NHANES). INTERVENTION: The primary analysis evaluated the association between frailty and %BF or WC. Frailty was the primary predictor (robust=referent) and %BF and WC were considered continuous outcomes. Multiple imputation analyses accounted for missing characteristics. MEASUREMENT: Dual energy x-ray absorptiometry was used to assess %BF and WC was objectively measured. Frailty was defined using an adapted version of Fried’s criteria that was self-reported: (low BMI

Background: Obesity in combination with sarcopenia (age-related loss of muscle mass, strength or function) is increasing in adults aged ≥65 years which places individuals at risk for functional decline and worse health. We ascertained the relationship between sarcopenic obesity and self-reported health in a representative US population. Methods: We identified participants ≥65 years with grip strength and body mass index (BMI) measures from the baseline wave of the National Health and Aging Trends Survey. Sarcopenia was defined using the Sarcopenia Definitions and Outcomes Consortium grip strength cut-points (males

BACKGROUND: Self-reported weight change may lead to adverse outcomes. We evaluated weight change with cutpoints of low lean mass (LLM) in older adults. METHODS: Of 4,984 subjects ≥60 years from NHANES 1999-2004, we applied LLM cutoffs of appendicular lean mass (ALM):body mass index (BMI) males

Objectives To compare the ability of frailty status to predict fall risk with that of community fall risk screening tools. Design Analysis of cross‐sectional and longitudinal data from NHATS. Setting National Health and Aging Trend Study (NHATS) 2011‐2015. Participants Individuals aged 65 and older (N = 7,392). Measurements Fall risk was defined according to the Stopping Elderly Accidents, Deaths and Injuries (STEADI) initiative. Frailty was defined as exhaustion, weight loss, low activity, slow gait speed, and weak grip strength. Robust was defined as meeting 0 criteria, prefrailty as 1 or 2 criteria, and frailty as 3 or more criteria. Falls were self‐reported and ascertained using NHATS subsequent rounds (2012–2015). We compared the ability of frailty to predict future falls with that of STEADI score, adjusting for age, race, sex, education, comorbidities, hearing and vision impairment, and disability. Results Of the 7,392 participants (58.5% female), there 3,545 (48.0%) were classified as being at low risk of falling, 2,966 (40.1%) as being at moderate risk, and 881 (11.9%) as being at high risk. The adjusted risk of falling over the 4 subsequent years was 2.5 times as great for the moderate‐risk group (hazard ratio (HR) = 2.50, 95% confidence interval (CI) = 2.16–2.89) and almost 4 times as great (HR = 3.79, 95% CI = 2.76–5.21) for the high‐risk group as for the low‐risk group. Risk of falling was greater for those who were prefrail (HR = 1.34, 95% CI 1.16–1.55) and frail (HR = 1.20, 95% CI = 0.94–1.54) than for those who were robust. Conclusion STEADI score is a strong predictor of future falls. Addition of frailty status does not improve the ability of the STEADI measure to predict future falls.

Objectives To determine the relationship between frailty and overall and cardiovascular mortality. Design Longitudinal mortality analysis. Setting National Health and Nutrition Examination Survey (NHANES) 1999–2004. Participants Community‐dwelling older adults aged 60 and older (N = 4,984; mean age 71.1 ± 0.19, 56% female). Measurements We used data from 1999–2004 cross‐sectional NHANES and mortality data from the National Death Index, updated through December 2011. An adapted version of Fried's frailty criteria was used (low body mass index, slow walking speed, weakness, exhaustion, low physical activity). Frailty was defined as persons meeting 3 or more criteria, prefrailty as meeting 1 or 2 criteria, and robust (reference) as not meeting any criteria. The primary outcome was to evaluate the association between frailty and overall and cardiovascular mortality. Cox proportional hazard models were used to evaluate the association between risk of death and frailty category adjusted for age, sex, race, smoking, education, coronary artery disease, heart failure, nonskin cancer, diabetes, and arthritis. Results Half (50.4%) of participants were classified as robust, 40.3% as prefrail, and 9.2% as frail. Fully adjusted models demonstrated that prefrail (hazard ratio (HR) = 1.64, 95% confidence interval (CI) = 1.45–1.85) and frail (HR = 2.79, 95% CI = 2.35–3.30) participants had a greater risk of death and of cardiovascular death (prefrail: HR = 1.84, 95% CI = 1.45–2.34; frail: HR = 3.39, 95% CI = 2.45–4.70). Conclusion Frailty and prefrailty are associated with increased risk of death. Demonstrating the association between prefrail status and mortality is the first step to identifying potential targets of intervention in future studies.

Background Preventing falls and fall-related injuries among older adults is a public health priority. The Stopping Elderly Accidents, Deaths, and Injuries (STEADI) tool was developed to promote fall risk screening and encourage coordination between clinical and community-based fall prevention resources; however, little is known about the tool’s predictive validity or adaptability to survey data. Methods Data from five annual rounds (2011–2015) of the National Health and Aging Trends Study (NHATS), a representative cohort of adults age 65 years and older in the USA. Analytic sample respondents (n=7392) were categorised at baseline as having low, moderate or high fall risk according to the STEADI algorithm adapted for use with NHATS data. Logistic mixed-effects regression was used to estimate the association between baseline fall risk and subsequent falls and mortality. Analyses incorporated complex sampling and weighting elements to permit inferences at a national level. Results Participants classified as having moderate and high fall risk had 2.62 (95% CI 2.29 to 2.99) and 4.76 (95% CI 3.51 to 6.47) times greater odds of falling during follow-up compared with those with low risk, respectively, controlling for sociodemographic and health-related risk factors for falls. High fall risk was also associated with greater likelihood of falling multiple times annually but not with greater risk of mortality. Conclusion The adapted STEADI clinical fall risk screening tool is a valid measure for predicting future fall risk using survey cohort data. Further efforts to standardise screening for fall risk and to coordinate between clinical and community-based fall prevention initiatives are warranted.

Body composition changes with aging can impact function in older adults leading to frailty. Measuring adiposity using body fat or central adiposity using waist circumference (WC) have greater diagnostic accuracy than traditional measures such as body mass index (BMI).