Understanding the minimal dose of physical activity required to achieve improvement in physical functioning and reductions in disability risk is necessary to inform public health recommendations. To ...examine the effect of physical activity dose on changes in physical functioning and the onset of major mobility disability in The Lifestyle Interventions and Independence for Elders (LIFE) Study. We conducted a multicenter single masked randomized controlled trial that enrolled participants in 2010 and 2011 and followed them for an average of 2.6 years. 1,635 sedentary men and women aged 70-89 years who had functional limitations were randomized to a structured moderate intensity walking, resistance, and flexibility physical activity program or a health education program. Physical activity dose was assessed by 7-day accelerometry and self-report at baseline and 24 months. Outcomes included the 400 m walk gait speed, the Short Physical Performance Battery (SPPB), assessed at baseline, 6, 12, and 24 months, and onset of major mobility disability (objectively defined by loss of ability to walk 400 m in 15 min). When the physical activity arm or the entire sample were stratified by change in physical activity from baseline to 24 months, there was a dose-dependent increase in the change in gait speed and SPPB from baseline at 6, 12, and 24 months. In addition, the magnitude of change in physical activity over 24 months was related to the reduction in the onset of major mobility disability (overall P < 0.001) (highest versus the lowest quartile of physical activity change HR 0.23 ((95% CI:0.10-0.52) P = 0.001) in the physical activity arm. We observed a dose-dependent effect of objectively monitored physical activity on physical functioning and onset of major mobility disability. Relatively small increases (> 48 minutes per week) in regular physical activity participation had significant and clinically meaningful effects on these outcomes.
ClinicalsTrials.gov NCT00116194.
Weight loss (WL) and subsequent regain are complex physiologic processes, and our understanding of the hormonal changes associated with these processes continues to evolve. We aimed to examine the ...effects of behavioral WL on 6-month changes in ghrelin and GLP-1 and evaluate the effects of these changes in gut hormones on weight regain among older adults.
One hundred seventy-seven obese (BMI: 33.5 (3.5) kg/m
) older adults (66.9 ± 4.7 years, 71.2% female, 67.6% white) were randomized to WL (WL; n = 68), WL plus aerobic training (n = 79), or WL plus resistance training (n = 75) for 18 months. Ghrelin, GLP-1, power of food scale (PFS), and weight were measured at baseline, 6 months, and 18 months.
There was no differential treatment effect on change in either gut hormone, however, there was a significant time effect across all groups (p < 0.001), with increases in ghrelin (∆ = +106.77 pg/ml; 95% CI = + 84.82, +128.71) and decreases in GLP-1 (∆ = -4.90 pM; 95% CI = -6.27, -3.51) at 6-month. Ratings on the PFS decreased from baseline to 6-month and there was significant loss of weight from baseline to either 6- or 18-month, ∆ = -7.96 kg; 95% CI = -7.95, -8.78 and ∆ = -7.80 kg; 95% CI = -8.93, -6.65, respectively (p < 0.001). Changes in ghrelin and GLP-1 at 6-month did not predict weight regain from 6- to 18-month.
Among older adults with obesity and cardiometabolic disease, the intensive phase of dietary WL results in increasing levels of ghrelin and decreasing levels of GLP-1 that are unrelated to weight regain a year later. Registered with ClinicalTrials.gov (NCT01547182).
Clinical trials conventionally test aggregate mean differences and assume homogeneous variances across treatment groups. However, significant response heterogeneity may exist. The purpose of this ...study was to model treatment response variability using gait speed change among older adults participating in caloric restriction (CR) trials. Eight randomized controlled trials (RCTs) with five- or six-month assessments were pooled, including 749 participants randomized to CR and 594 participants randomized to non-CR (NoCR). Statistical models compared means and variances by CR assignment and exercise assignment or select subgroups, testing for treatment differences and interactions for mean changes and standard deviations. Continuous equivalents of dichotomized variables were also fit. Models used a Bayesian framework, and posterior estimates were presented as means and 95% Bayesian credible intervals (BCI). At baseline, participants were 67.7 (SD = 5.4) years, 69.8% female, and 79.2% white, with a BMI of 33.9 (4.4) kg/m2. CR participants reduced body mass CR: -7.7 (5.8) kg vs. NoCR: -0.9 (3.5) kg and increased gait speed CR: +0.10 (0.16) m/s vs. NoCR: +0.07 (0.15) m/s more than NoCR participants. There were no treatment differences in gait speed change standard deviations CR-NoCR: -0.002 m/s (95% BCI: -0.013, 0.009). Significant mean interactions between CR and exercise assignment 0.037 m/s (95% BCI: 0.004, 0.070), BMI 0.034 m/s (95% BCI: 0.003, 0.066), and IL-6 0.041 m/s (95% BCI: 0.009, 0.073) were observed, while variance interactions were observed between CR and exercise assignment -0.458 m/s (95% BCI: -0.783, -0.138), age -0.557 m/s (95% BCI: -0.900, -0.221), and gait speed -0.530 m/s (95% BCI: -1.018, -0.062) subgroups. Caloric restriction plus exercise yielded the greatest gait speed benefit among older adults with obesity. High BMI and IL-6 subgroups also improved gait speed in response to CR. Results provide a novel statistical framework for identifying treatment heterogeneity in RCTs.
To examine and compare changes in strength and physical function from pre- to post-diagnosis among men with prostate cancer (PC, cases) and matched non-cancer controls identified from the Health, ...Aging and Body Composition (Health ABC) study.
We conducted a longitudinal analysis of 2 strength and 3 physical function-based measures among both cases and controls, identified from a large cohort of community living older adults enrolled in the Health ABC study. We plotted trajectories for each measure and compared cases vs. controls from the point of diagnosis onwards using mixed-effects regression models. For cases only, we examined predictors of poor strength or physical function.
We identified 117 PC cases and 453 matched non-cancer controls (50% African Americans). At baseline, there were no differences between cases and controls in demographic factors, comorbidities or self-reported physical function; however, cases had slightly better grip strength (44.6 kg vs. 41.0 kg, p<0.01), quadriceps strength (360.5 Nm vs. 338.7 Nm, p = 0.02) and Health ABC physical performance battery scores (2.4 vs. 2.3, p = 0.01). All men experienced similar declines in strength and physical function over an equivalent amount of time. The loss of quad strength was most notable, with losses of nearly two-thirds of baseline strength over approximately 7 years of follow up.
Among both cases and controls, strength and physical function decline with increasing age. The largest declines were seen in lower body strength. Regular assessments should guide lifestyle interventions that can offset age- and treatment-related declines among men with PC.
IMPORTANCE: Clinical practice guidelines support home-based exercise for patients with peripheral artery disease (PAD), but no randomized trials have tested whether an exercise intervention without ...periodic medical center visits improves walking performance. OBJECTIVE: To determine whether a home-based exercise intervention consisting of a wearable activity monitor and telephone coaching improves walking ability over 9 months in patients with PAD. DESIGN, SETTING, AND PARTICIPANTS: Randomized clinical trial conducted at 3 US medical centers. Patients with PAD were randomized between June 18, 2015, and April 4, 2017, to home-based exercise vs usual care for 9 months. Final follow-up was on December 5, 2017. INTERVENTIONS: The exercise intervention group (n = 99) received 4 weekly medical center visits during the first month followed by 8 months of a wearable activity monitor and telephone coaching. The usual care group (n = 101) received no onsite sessions, active exercise, or coaching intervention. MAIN OUTCOMES AND MEASURES: The primary outcome was change in 6-minute walk distance at 9-month follow-up (minimal clinically important difference MCID, 20 m). Secondary outcomes included 9-month change in subcomponents of the Walking Impairment Questionnaire (WIQ) (0-100 score; 100, best), SF-36 physical functioning score, Patient-Reported Outcomes Measurement Information System (PROMIS) mobility questionnaire (higher = better; MCID, 2 points), PROMIS satisfaction with social roles questionnaire, PROMIS pain interference questionnaire (lower = better; MCID range, 3.5-4.5 points), and objectively measured physical activity. RESULTS: Among 200 randomized participants (mean SD age, 70.2 10.4 years; 105 52.5% women), 182 (91%) completed 9-month follow-up. The mean change from baseline to 9-month follow-up in the 6-minute walk distance was 5.5 m in the intervention group vs 14.4 m in the usual care group (difference, −8.9 m; 95% CI, −26.0 to 8.2 m; P = .31). The exercise intervention worsened the PROMIS pain interference score, mean change from baseline to 9 months was 0.7 in the intervention group vs −2.8 in the usual care group (difference, 3.5; 95% CI, 1.3 to 5.8; P = .002). There were no significant between-group differences in the WIQ score, the SF-36 physical functioning score, or the PROMIS mobility or satisfaction with social roles scores. CONCLUSIONS AND RELEVANCE: Among patients with PAD, a home-based exercise intervention consisting of a wearable activity monitor and telephone coaching, compared with usual care, did not improve walking performance at 9-month follow-up. These results do not support home-based exercise interventions of wearable devices and telephone counseling without periodic onsite visits to improve walking performance in patients with PAD. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT02462824
This trial investigated whether an intensive lifestyle intervention to produce weight loss and increased fitness would slow loss of mobility among obese patients with type 2 diabetes. Both weight ...loss and improved fitness were associated with a decline in the rate of mobility loss.
The growing prevalence of type 2 diabetes mellitus is an ominous health threat in the United States
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,
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and globally.
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Surveillance data from the Centers for Disease Control and Prevention cite type 2 diabetes as largely a disease of aging,
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and its prevalence may escalate as the population gets older.
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,
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An insidious consequence of aging in persons with type 2 diabetes is physical disability,
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particularly the loss of mobility.
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Reduced mobility puts patients at risk for loss of independence,
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leads to muscle loss (which compromises glucose storage and clearance),
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and compromises the quality of life.
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With increasing age in . . .
Older adults are a rapidly growing segment of the U.S. population. Mobility problems that lead to further disability can be addressed through physical activity interventions. Quality of life outcome ...results are reported from a large trial of physical activity for sedentary older adults at risk for mobility disability.
Data were from the Lifestyle Interventions and Independence for Elders study. This multisite RCT compared physical activity to health education among 1,635 randomly assigned sedentary older adults at risk for mobility disability in 2010–2011. Measures included demographics; comorbidity; a timed 400-meter walk; the Short Physical Performance Battery; and the Quality of Well-Being Scale (0–1.0 scale). Baseline and long-term follow-up (2.6 years) health-related quality of life data were collected as a secondary outcome. Multivariate linear regression modeling was used to examine covariates of health-related quality of life over time in 2017.
The sample had an overall mean Quality of Well-Being score of 0.613. Both groups declined in quality of life over time, but assignment to the physical activity intervention resulted in a slower decline in health-related quality of life scores (p=0.03). Intervention attendance was associated with higher health-related quality of life for both groups. Baseline characteristics including younger age, fewer comorbid conditions, non-white ethnicity, and faster 400-meter walk times were also associated with higher health-related quality of life over time.
Declining mobility measured by physical performance is associated with lower quality of life in sedentary older adults. Physical activity interventions can slow the decline in quality of life, and targeting specific subgroups may enhance the effects of such interventions.
Combined training in pain and weight management in overweight and obese OA patients resulted in improved pain and other outcomes compared to either training alone.
Overweight and obese patients with ...osteoarthritis (OA) experience more OA pain and disability than patients who are not overweight. This study examined the long-term efficacy of a combined pain coping skills training (PCST) and lifestyle behavioral weight management (BWM) intervention in overweight and obese OA patients. Patients (n=232) were randomized to a 6-month program of: 1) PCST+BWM; 2) PCST-only; 3) BWM-only; or 4) standard care control. Assessments of pain, physical disability (Arthritis Impact Measurement Scales AIMS physical disability, stiffness, activity, and gait), psychological disability (AIMS psychological disability, pain catastrophizing, arthritis self-efficacy, weight self-efficacy), and body weight were collected at 4 time points (pretreatment, posttreatment, and 6months and 12months after the completion of treatment). Patients randomized to PCST+BWM demonstrated significantly better treatment outcomes (average of all 3 posttreatment values) in terms of pain, physical disability, stiffness, activity, weight self-efficacy, and weight when compared to the other 3 conditions (Ps<0.05). PCST+BWM also did significantly better than at least one of the other conditions (ie, PCST-only, BWM-only, or standard care) in terms of psychological disability, pain catastrophizing, and arthritis self-efficacy. Interventions teaching overweight and obese OA patients pain coping skills and weight management simultaneously may provide the more comprehensive long-term benefits.
Abstract Background Acute decompensated heart failure (ADHF) is a leading cause of hospitalization in older persons in the United States. Reduced physical function and frailty are major determinants ...of adverse outcomes in older patients with hospitalized ADHF. However, these are not addressed by current heart failure (HF) management strategies and there has been little study of exercise training in older, frail HF patients with recent ADHF. Hypothesis Targeting physical frailty with a multi-domain structured physical rehabilitation intervention will improve physical function and reduce adverse outcomes among older patients experiencing a HF hospitalization. Study Design Rehabilitation Therapy in Older Acute Heart Failure Patients (REHAB-HF) is a multi-center clinical trial in which 360 patients ≥60 years hospitalized with ADHF will be randomized either to a novel 12-week multi-domain physical rehabilitation intervention or to attention control. The goal of the intervention is to improve balance, mobility, strength and endurance utilizing reproducible, targeted exercises administered by a multi-disciplinary team with specific milestones for progression. The primary study aim is to assess the efficacy of the REHAB-HF intervention on physical function measured by total Short Physical Performance Battery score. The secondary outcome is 6-month all-cause rehospitalization. Additional outcome measures include quality of life and costs. Conclusions REHAB-HF is the first randomized trial of a physical function intervention in older patients with hospitalized ADHF designed to determine if addressing deficits in balance, mobility, strength and endurance improves physical function and reduces rehospitalizations. It will address key evidence gaps concerning the role of physical rehabilitation in the care of older patients, those with ADHF, frailty, and multiple comorbidities.
Abstract
Background
Advances in computational algorithms and the availability of large datasets with clinically relevant characteristics provide an opportunity to develop machine learning prediction ...models to aid in diagnosis, prognosis, and treatment of older adults. Some studies have employed machine learning methods for prediction modeling, but skepticism of these methods remains due to lack of reproducibility and difficulty in understanding the complex algorithms that underlie models. We aim to provide an overview of two common machine learning methods: decision tree and random forest. We focus on these methods because they provide a high degree of interpretability.
Method
We discuss the underlying algorithms of decision tree and random forest methods and present a tutorial for developing prediction models for serious fall injury using data from the Lifestyle Interventions and Independence for Elders (LIFE) study.
Results
Decision tree is a machine learning method that produces a model resembling a flow chart. Random forest consists of a collection of many decision trees whose results are aggregated. In the tutorial example, we discuss evaluation metrics and interpretation for these models. Illustrated using data from the LIFE study, prediction models for serious fall injury were moderate at best (area under the receiver operating curve of 0.54 for decision tree and 0.66 for random forest).
Conclusions
Machine learning methods offer an alternative to traditional approaches for modeling outcomes in aging, but their use should be justified and output should be carefully described. Models should be assessed by clinical experts to ensure compatibility with clinical practice.
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