The sit-to-stand (STS) test has been deployed as surrogate measures of strength or physical performance in sarcopenia diagnosis. This study examines the relationship of two common STS variants - Five ...Times Sit-to-Stand Test (5TSTS) and 30 s Chair Stand Test (30CST) - with grip strength, muscle mass and functional measures, and their impact on sarcopenia prevalence in community-dwelling older adults.
This is a cross-sectional analysis of 887 community-dwelling adults aged ≥50 years. Participants completed a battery of physical fitness tests - 5TSTS, 30CST, grip strength, gait speed, Timed-Up-and-Go (TUG) for dynamic balance and six-minute walk test (6MWT) for cardiorespiratory endurance. Muscle mass was measured using multi-frequency segmental bioelectrical impedance analysis (BIA). We performed correlation analysis between STS performance and other fitness measures and muscle mass, followed by multiple linear regression for the independent determinants of STS performance.
Mean participant age was 67.3±7 years, with female predominance (72.9%). STS tests exhibited weak correlations with grip strength (30CST, r = 0.290; 5TSTS, r = - 0.242; both p< 0.01), and stronger correlations with gait speed (30CST, r = 0.517; 5TSTS, r = - 0.533; both p< 0.01), endurance (30CST, r = 0.558; 5TSTS, r = - 0.531; both p < 0.01) and dynamic balance (30CST, r = - 0.501; 5TSTS, r = 0.646; both p< 0.01). Muscle mass correlated with grip strength but not STS. In multiple regression analysis, all fitness measures were independently associated with 30CST performance. Performance in both STS tests remained independent of muscle mass. There was no significant difference in prevalence of possible sarcopenia diagnosis using grip strength or STS (30CST, 25.0%; 5TSTS, 22.1%; grip strength, 22.3%; p = 0.276). When both measures are used, prevalence is significantly higher (42.0%; p = 0.276). Prevalence of confirmed sarcopenia with inclusion of muscle mass was significantly lower using STS compared with grip strength (30CST, 4.6%; 5TSTS, 4.1% vs. grip strength, 7.1%; p< 0.05).
In the sarcopenia construct, STS tests better represents muscle physical performance rather than muscle strength. Different subsets of population with possible sarcopenia are identified depending on the test used. The lack of association of STS performance with muscle mass results in a lower prevalence of confirmed sarcopenia compared with grip strength, but may better reflect changes in muscle quality.
Aim
In order to account for the variability in gait speed due to demographic factors, an observed gait speed value can be compared with its predicted value based on age, sex, and body height ...(observed gait speed divided by predicted gait speed, termed “GS%predicted” henceforth). This study aimed to examine the screening accuracy of an optimal GS%predicted threshold for prefrailty/frailty.
Methods
This cross‐sectional study included 998 community‐dwelling ambulant participants aged >50 years (mean age = 68 years). Participants completed a multi‐domain geriatric screen and a physical fitness assessment, from which the 10‐m habitual gait speed, GS%predicted, Physical Frailty Phenotype (PFP) index, and 36‐item Frailty Index (FI) were computed.
Results
Based on the FI, ~49% of participants had pre‐frailty or frailty. The optimal threshold of GS%predicted (0.93) had greater screening accuracy than the 1.0 m/s fixed threshold for gait speed (AUC, 0.65 vs. 0.60; DeLong's P < 0.001). Replacing gait speed with GS%predicted in the PFP improved its overall discrimination (AUC, 0.70 vs. 0.67 of original PFP; DeLong's P < 0.001).
Conclusions
Defining a “slow” gait speed by a GS%predicted value of <0.93 provided greater screening accuracy than the traditional 1.0 m/s threshold for gait speed. Our results also support the use of GS%predicted‐derived PFP to identify older adults at risk of prefrailty/frailty. Geriatr Gerontol Int 2022; 22: 575–580.
To account for the variability in habitual gait speed due to demographic factors, an observed gait speed value can be compared with its predicted value based on age, sex, and body height (observed gait speed divided by predicted gait speed, termed “GS%predicted” henceforth). In a large sample of 998 community‐dwelling older adults, we found that defining a “slow” gait speed by a GS%predicted value of <0.93 provided greater prefrailty/frailty screening accuracy than the traditional 1.0 m/s threshold for gait speed.
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Although the frailty index (FI) is designed as a continuous measure of frailty, thresholds are often needed to guide its interpretation. This study aimed to introduce and demonstrate the utility of ...an item response theory (IRT) method in estimating FI interpretation thresholds in community-dwelling adults and to compare them with cutoffs estimated using the receiver operating characteristics (ROC) method.
A sample of 1,149 community-dwelling adults (meanSD, 687 years) participated in this cross-sectional study. Participants completed a multi-domain geriatric screen from which the 40-item FI and 3 clinical anchors were computed - namely, (i)self-reported mobility limitations (SRML), (ii)"fair" or "poor" self-rated health (SRH), and (iii) restricted life-space mobility (RLSM). Participants were classified as having SRML-1 if they responded "Yes" to either of the 2 questions regarding walking and stair climbing difficulty and SRML-2 if they reported having walking and stair climbing difficulty. Participants with a Life Space Assessment score <60 points were classified as having RLSM. Threshold values for all anchor questions were estimated using the IRT method and ROC analysis with Youden criterion.
The proportions of participants with SRML-1, SRML-2, Fair/Poor SRH, and RLSM were 21 %, 8 %, 22 %, and 9 %, respectively. The IRT-based thresholds for SRML-2 (0.26), fair/poor SRH (0.29), and RLSM (0.32) were significantly higher than those for SRML-1 (0.18). ROC-based FI cutoffs were significantly lower than IRT-based values for SRML-2, SRH, and RLSM (0.12 to 0.17), and they varied minimally and non-systematically across the anchors.
The IRT method identifies biologically plausible FI thresholds that could meaningfully complement and contextualize existing thresholds for defining frailty.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
•The adjusted predictive modeling (APM) method estimates interpretational thresholds.•The APM method generates biologically plausible cutpoints for mobility difficulty.•The APM-based cutpoints are ...more precise than ROC-based cutpoints.•The APM method uses common regression methods and can be easily applied.
Clinical interpretability of the gait speed and 5-times sit-to-stand (5-STS) tests is commonly established by comparing older adults with and without self-reported mobility limitations (SRML) on gait speed and 5-STS performance, and estimating clinical cutpoints for SRML using the receiver operating characteristics (ROC) method. Accumulating evidence, however, suggests that the adjusted predictive modeling (APM) method may be more appropriate to estimate these interpretational cutpoints. Thus, we aimed to compare, in community-dwelling older adults, gait speed and 5-STS cutpoints estimated using the ROC and APM methods.
Cross-sectional study.
This study analyzed data from 955 community-dwelling independently walking older adults (73%women) aged ≥60 years (mean, 68; range, 60–88).
Participants completed the 10-metre gait speed and 5-STS tests. Participants were classified as having SRML if they responded "Yes" to either of the 2 questions regarding walking and stair climbing difficulty. Cutpoints for SRML and its component questions were estimated using ROC analysis with Youden criterion and the APM method.
The proportions of participants with self-reported walking difficulty, self-reported stair climbing difficulty, and SRML were 10%, 19%, and 22%, respectively. Gait speed and 5-STS time were moderately correlated with each other (r=-0.56) and with the self-reported measures (absolute r-values, 0.39–0.44). ROC-based gait speed cutpoints were 0.14 to 0.16 m/s greater than APM-based cutpoints (P < 0.05) whilst ROC-based 5-STS time cutpoints were 0.8 to 3.3 s lower than APM-based cutpoints (P < 0.05 for walking difficulty). Compared with ROC-based cutpoints, APM-based cutptoints were more precise and they varied monotonically with self-reported walking difficulty, self-reported stair climbing difficulty, and SRML.
In a sample of 955 older adults, our findings of precise and biologically plausible gait speed and 5-STS cutpoints for SRML estimated using the APM method indicate that this promising method could potentially complement or even replace traditional ROC methods.
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Frailty begins in middle life and manifests as a decline in functional fitness. We described a model for community frailty screening and factors associated with prefrailty and frailty and fitness ...measures to distinguish prefrail/frail from robust older adults. We also compared the Fatigue, Resistance, Ambulation, Illnesses and Loss of weight (FRAIL) scale against Fried frailty phenotype and Frailty Index (FI).
Community-dwelling adults ≥55 years old were designated robust, prefrail or frail using FRAIL. The multidomain geriatric screen included social profiling and cognitive, psychological and nutritional assessments. Physical fitness assessments included flexibility, grip strength, upper limb dexterity, lower body strength and power, tandem and dynamic balance and cardiorespiratory endurance.
In 135 subjects, 99 (73.3%) were robust, 34 (25.2%) were prefrail and 2 (1.5%) were frail. After adjusting for age and sex, depression (odds ratio OR, 2.90; 95% confidence interval CI, 1.05-7.90;
= 0.040) and malnutrition (OR, 6.07; 95% CI, 2.52-14.64;
<0.001) were independently associated with prefrailty/frailty. Prefrail/frail participants had significantly poorer performance in upper limb dexterity (
= 0.030), lower limb power (
= 0.003), tandem and dynamic balance (
= 0.031) and endurance (
= 0.006). Except for balance and flexibility, all fitness measures differentiated prefrail/frail from robust women. In men, only lower body strength was significantly associated with frailty. Area under receiver operating characteristic curves for FRAIL against FI and Fried were 0.808 (0.688-0.927,
<0.001) and 0.645 (0.546-0.744,
= 0.005), respectively.
Mood and nutrition are targets in frailty prevention. Physical fitness declines early in frailty and manifests differentially in both genders.
Background
The differential risk profiles associated with prefrailty may be attributable to underlying intrinsic capacity (IC).
Objectives
We examine (i) effect of a multi-domain physical exercise ...and nutrition intervention on pre-frailty reversal in community-dwelling older adults at 1-year, and (ii) whether IC contributes to pre-frailty reversal.
Methods
Prefrail participants in this non-randomized study were invited to attend a 4-month exercise and nutritional intervention following a frailty screen in the community. Prefrailty was operationalized as (i) FRAIL score 1–2 or (ii) 0 positive response on FRAIL but with weak grip strength or slow gait speed based on the Asian Working Group for Sarcopenia cut-offs. Participants who fulfilled operational criteria for prefrailty but declined enrolment in the intervention programme served as the control group. All participants completed baseline IC assessment: locomotion (Short Physical Performance Battery, 6-minute walk test), vitality (nutritional status, muscle mass), sensory (self-reported hearing and vision), cognition (self-reported memory, age- and education adjusted cognitive performance), psychological (Geriatric Depression Scale-15, self-reported anxiety/ depression). Reversal of prefrailty was defined as achieving a FRAIL score of 0, with unimpaired grip strength and gait speed at 1-year follow-up.
Results
Of 81 participants (70.0 ± 6.6 years, 79.0% female), 52 participants (64.2%) were enrolled in the multi-domain intervention, and 29 participants (35.8%) who declined intervention constituted the control group. There was no difference in age, gender and baseline composite IC between groups. Reversal to robustness at 1-year was similar between intervention and control groups (30.8% vs. 44.8% respectively,
p
= 0.206). Reduced prevalence of depression was observed among participants in the intervention group at 1-year relative to baseline (7.8% vs. 23.1%,
p
= 0.022). In multiple logistic regression, intervention had no effect on prefrailty reversal, while higher composite IC exhibited reduced likelihood of remaining prefrail at 1-year (OR = 0.67, 95% CI 0.45–1.00,
p
= 0.049).
Conclusion
Focusing only on the locomotion and vitality domains through a combined exercise and nutritional intervention may not adequately address component domain losses to optimize prefrailty reversal. Future studies should examine whether an IC-guided approach to target identified domain declines may be more effective in preventing frailty progression.
Handgrip strength is commonly normalized or stratified by body size to define subgroup-specific cut-points and reference limits values. However, it remains unclear which anthropometric variable is ...most strongly associated with handgrip strength. We aimed to, in older adults with no self-reported mobility limitations, determine whether height, weight, and body mass index (BMI) were meaningfully associated with handgrip strength.
This cross-sectional study included community-dwelling ambulant participants, and we identified 775 older adults who reported no difficulty walking 100 m, climbing stairs, and rising from the chair. Handgrip strength was measured with a digital dynamometer. Bayesian linear regression was used to estimate the probabilities that the positive associations of height, weight, and BMI with handgrip strength exceeded 0 kg (the null value) and 2.5 kg (the clinically meaningful threshold value).
Mean handgrip strength was 22.1 kg (SD, 4) for women and 32.9 kg (SD, 6) for men. Body height, weight, and BMI had >99.9% probabilities of a positive association with handgrip strength; however, the associations of per interquartile increase in body weight and BMI with handgrip strength had low probabilities (<5%) of exceeding the clinically meaningful threshold of 2.5 kg. In contrast, body height had the highest probability (99.6%) of a clinically meaningful association with handgrip strength: adjusting for age and gender, handgrip strength was 3.2 kg (95% CrI, 2.7 to 3.8) greater in older adults 1.61 m tall than in older adults 1.51 m tall.
In a large sample of mobile-intact older adults, handgrip strength differed meaningfully by body height. Although requiring validation, our findings suggest that future efforts should be directed at normalizing handgrip strength by body height to better define subgroup-specific handgrip weakness. A web-based application (https://sghpt.shinyapps.io/ippts/) was created to allow interactive exploration of predicted values and reference limits of age-, gender-, and height-subgroups.
•Handgrip strength differed by body height, body weight, and body mass index (BMI) in community-dwelling older adults.•Only the association between body height and handgrip strength had a high probability of clinical significance.•Future studies should normalize handgrip strength by body height to better define subgroup-specific handgrip weakness.•Encouraging future work to evaluate clinical significance could facilitate practice standardization and harmonization.
Summary: In 775 community-dwelling older adults with no self-reported mobility limitations, we found that the association between body height and handgrip strength had a high probability of clinical significance, thereby shedding light on the important but previously unaddressed question of which anthropometric variables – namely, body height, weight, and BMI – were meaningfully associated with handgrip strength.
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The conventional count-based physical frailty phenotype (PFP) dichotomizes its criterion predictors-an approach that creates information loss and depends on the availability of population-derived ...cut-points. This study proposes an alternative approach to computing the PFP by developing and validating a model that uses PFP components to predict the frailty index (FI) in community-dwelling older adults, without the need for predictor dichotomization.
A sample of 998 community-dwelling older adults (mean SD, 68 7 years) participated in this prospective cohort study. Participants completed a multi-domain geriatric screen and a physical fitness assessment from which the count-based PFP and the 36-item FI were computed. One-year prospective falls and hospitalization rates were also measured. Bayesian beta regression analysis, allowing for nonlinear effects of the non-dichotomized PFP criterion predictors, was used to develop a model for FI ("model-based PFP"). Approximate leave-one-out (LOO) cross-validation was used to examine model overfitting.
The model-based PFP showed good calibration with the FI, and it had better out-of-sample predictive performance than the count-based PFP (LOO-R
, 0.35 vs 0.22). In clinical terms, the improvement in prediction (i) translated to improved classification agreement with the FI (Cohen's k
, 0.47 vs 0.36) and (ii) resulted primarily in a 23% (95%CI, 18-28%) net increase in FI-defined "prefrail/frail" participants correctly classified. The model-based PFP showed stronger prognostic performance for predicting falls and hospitalization than did the count-based PFP.
The developed model-based PFP predicted FI and clinical outcomes more strongly than did the count-based PFP in community-dwelling older adults. By not requiring predictor cut-points, the model-based PFP potentially facilitates usage and feasibility. Future validation studies should aim to obtain clear evidence on the benefits of this approach.
Digital technology (DT) has a significant role to play in modern education. This study examined motivational goals of student teachers in initial teacher education in Singapore and the influences of ...goals on their use of DT personally and in the classroom. The participants (N=312) responded to a survey about their motivational goals (learning versus performance) and DT application (personal versus classroom application). Results showed that personal use of DT, especially for younger teachers, was clearly more than classroom application. Females were found to have higher performance goals. Structural equation modelling found that learning goals were positively related to both personal use and classroom application, but performance goals were not positively related to either outcome. As performance goals were found to be unrelated to classroom application of DT, teacher education should focus more on the development of learning goals so as to encourage teachers, especially females, to use DT for teaching. Author abstract, ed
AimThis study aimed to investigate the association between intrinsic capacity (IC) and frailty in community‐dwelling older adults. Specifically, we examined the utility of the World Health ...Organization's Integrated Care for Older People Step 1 screen for identifying frail older persons in the community.MethodsThis is a cross‐sectional analysis of a community frailty screening initiative. IC loss was ascertained using the World Health Organization's Integrated Care for Older People Step 1 questions. The Clinical Frailty Scale was used to categorize participants as robust (Clinical Frailty Scale S1‐3) or frail (Clinical Frailty Scale ≥4). Logistic regression was used to analyze the association of individual and cumulative IC losses with frailty, adjusting for confounders. Additionally, the diagnostic performance of using cumulative IC losses to identify frailty was assessed.ResultsThis study included 1164 participants (28.2% frail). Loss in locomotion (adjusted odds ratio AOR 1.47, 95% CI 1.07–2.02), vitality (AOR 1.58, 95% CI 1.04–2.39), sensory (AOR 1.99, 95% CI 1.51–2.64) and psychological capacities (AOR 1.92, 95% CI 1.45–2.56) were significantly associated with frailty. Loss in more than three IC domains was associated with frailty. Using loss in at least three ICs identifies frailty, with sensitivity of 38.6%, specificity of 83.5% and positive predictive value of 47.4%. Using loss in at least four ICs improved specificity to 96.9%, and is associated with the highest positive predictive value of 57.6% and highest positive likelihood ratio of 3.55 for frailty among all cut‐off values. The area under the receiver operating characteristic curve was 0.64 (95% CI 0.61–0.68).ConclusionsIC loss as identified through World Health Organization's Integrated Care for Older People Step 1 is associated with frailty community‐dwelling older adults. Geriatr Gerontol Int 2024; 24: 457–463.
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