Factors influencing gait speed in community-dwelling older women: A Bayesian approach

Júnior, Eduardo Lima Souza; Oliveira, Alinne Alves; Schettino, Ludmila; Mascarenhas, Claudio Henrique Meira; Araújo, Claudinéia Matos de; Fernandes, Marcos Henrique; Pereira, Rafael

doi:10.1016/j.gaitpost.2021.12.022

Cited by 4 publications

(5 citation statements)

References 31 publications

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“…It is well documented that aging leads to a decline in ability to generate propulsive force rapidly. 14,15 In addition, research suggests that the ability to generate propulsive force rapidly in the lower limbs significantly affects mobility (ie, gait speed), 29,30 which is a crucial health indicator during aging. [1][2][3][4][5][6] Therefore, our study contributes significantly by demonstrating that the reduction in the ability to generate propulsive force during gait may start during the menopausal transition.…”

Section: Discussionmentioning

confidence: 99%

Propulsive forces and muscle activation during gait: comparisons between premenopausal and postmenopausal midlife women

Tomaz,

Souza,

Carneiro

et al. 2024

Menopause

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Objective The aim of this study was to investigate whether there is a reduction in propulsive force during gait in postmenopausal women compared with premenopausal women. Methods Forty-four women (21 premenopausal and 23 postmenopausal women) aged 40 to 55 years were selected. The ability to reach peak propulsive forces was assessed during the step execution test. The test was performed at the usual speed on 2 nonconsecutive days, with two attempts per day, using a force platform. Four temporal parameters were defined and calculated: initiation phase, preparation phase, swing phase, and total time. Peak force (anteroposterior and vertical) and time to reach peak force were obtained in both preparation and swing phases. The rate of force development was defined as peak force divided by time to reach peak force. Results The postmenopausal women group presented a longer time in the preparation phase (540.6 ± 77 ms vs 482.5 ± 93 ms, P = 0.024) and consequently a longer total time in the step execution test (1,191 ± 106.4 ms vs 1,129 ± 114.3 ms, P = 0.045). There were differences between the groups for the rate of force development in the anteroposterior (postmenopausal women, 142.5 ± 38.1 N/s vs premenopausal women, 174.7 ± 70.5 N/s; P = 0.022) and vertical directions in the preparation phase (postmenopausal women, 102.7 ± 62.3 N/s vs premenopausal women, 145.3 ± 71 N/s; P = 0.012). No significant differences (P > 0.05) were found in force, time to peak force, and rate of force development during the swing phase. In addition, there were no observed differences in surface electromyography of the medial and lateral gastrocnemius muscles during the preparation phase and swing phase of the step execution test between the two groups. Conclusions Postmenopausal women exhibited lower ability to generate propulsive force rapidly (rates of force development) in both the anteroposterior and vertical directions during the preparation phase of gait compared with premenopausal women. This indicates that postmenopausal women experience a reduction in propulsive force during gait.

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Section: Discussionmentioning

confidence: 99%

Propulsive forces and muscle activation during gait: comparisons between premenopausal and postmenopausal midlife women

Tomaz,

Souza,

Carneiro

et al. 2024

Menopause

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“…Descriptive (17). These statistical procedures were carried out using SPSS (SPSS Inc., Chicago, IL) and the critical alpha was set at 0.05.…”

Section: Discussionmentioning

confidence: 99%

Upper and Lower Limb Muscle Thickness Measurements in Older Women: Analysis of Variability and Development of Prediction Equations

Araujo¹,

Pereira²,

Carneiro³

et al. 2023

Muscle Ligaments and Tendons J

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Purpose. The present study aimed to describe the variability of muscle thickness measures (MT) of arm and thigh muscles, obtained by ultrasound (USD) from community-dwelling healthy older women; and to obtain a predictive equation model for arm, thigh and leg MT based on upper and lower limb circumference measures using a frequentist and Bayesian approach. Methods. Sixty-two older women (74.5 ± 8.5 years) volunteered and were submitted to MT measures. Assessments of the Brachial (Br), Biceps Brachii (BB), Vastus Lateralis (VL), Rectus Femoris (RF) were obtained and grouped to infer elbow flexors (EF), and knee extensors (KE) muscles. Thigh (TC) and arm (AC) circumference were also measured. Variability of MT and circumference measures were inferred by the coefficient of variation (CV) and Huber's M-estimator. Age-adjusted linear regression models were generated to predict MT. The magnitude of evidence was obtained using Bayesian inference, determining posterior probabilities based on our data. Results. The MT measure of the EF presented lower CV (15.9%). The CV of limb circumference measures was 10.8% (TC) and 12.5% (AC) and Huber's M-estimator varied 0.18 cm (AC). Circumference measurements were significantly associated with MT with age-adjusted coefficients of determination (R 2 ) of 0.268 and 0.173 (p < 0.05), and standard error of the estimate of 0.36 cm and 0.56 cm for EF and KE, respectively. Bayesian inference confirmed the good posterior probability of the model. Conclusions. Measure of MT of the EF presented lower between-subject variability, and a better predictive equation model for MT based on AC.

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“…Gait is a complex task requiring the interaction of sensory perception, muscle output, and sensory–motor integration 5 . Previous studies have reported that factors such as age, balance, leg muscle strength, and skeletal muscle mass affect gait speed in older adults 5–10 .…”

Section: Introductionmentioning

confidence: 99%

“…Gait is a complex task requiring the interaction of sensory perception, muscle output, and sensory-motor integration. 5 Previous studies have reported that factors such as age, balance, leg muscle strength, and skeletal muscle mass affect gait speed in older adults. [5][6][7][8][9][10] Furthermore, asymmetry in skeletal muscle mass has been reported to affect gait speed; 11 however, in this report on the association between the asymmetry index of leg skeletal muscle mass and gait speed, a cutoff value for leg skeletal muscle mass asymmetry that might affect gait speed was not identified, as an association was found with multivariate analysis but not with univariate analysis.…”

Section: Introductionmentioning

confidence: 99%

“…5 Previous studies have reported that factors such as age, balance, leg muscle strength, and skeletal muscle mass affect gait speed in older adults. [5][6][7][8][9][10] Furthermore, asymmetry in skeletal muscle mass has been reported to affect gait speed; 11 however, in this report on the association between the asymmetry index of leg skeletal muscle mass and gait speed, a cutoff value for leg skeletal muscle mass asymmetry that might affect gait speed was not identified, as an association was found with multivariate analysis but not with univariate analysis. Because reduced gait speed is a predictor of further deterioration in level of care for older adults requiring long-term care, 12 it is important to assess and intervene in the gait of older adults requiring long-term care who are walking more slowly than the general community of older adults.…”

Section: Introductionmentioning

confidence: 99%

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Leg skeletal muscle mass asymmetry is independently associated with gait speed in older adults requiring long‐term care

Sato

Sawaya

Ishizaka

et al. 2023

Geriatrics Gerontology Int

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Decreased gait speed in older adults has been associated with incident disability, cognitive impairment, institutionalization, falls, deterioration in level of care, and mortality. Gait speed has been reported to be related to leg asymmetry. However, the relationship between gait speed and leg skeletal muscle mass asymmetry in older adults requiring longterm care has not been clarified. In this study, we examined the association between gait speed and leg skeletal muscle mass asymmetry and the cutoff values of leg skeletal muscle mass asymmetry that may affect gait speed. Methods:The asymmetry index of leg skeletal muscle mass was measured in 230 older adults under the Japanese long-term care insurance system using bioelectrical impedance analysis. This cross-sectional study used multiple regression analysis and receiver operating characteristic (ROC) curve analysis to determine the relationship between gait speed and the asymmetry index of leg skeletal muscle mass.Results: Multiple regression analysis revealed that the asymmetry index of leg skeletal muscle mass (β = À0.19, P = 0.002, R 2 = 0.261) was independently and significantly associated with gait speed. Furthermore, ROC analysis showed that the cutoff value of the asymmetry index of leg skeletal muscle mass that identified reduced gait speed (<1.0 m/s) was 3.02% (Area under the curve = 0.62, sensitivity 47.3%, specificity 81.0%, P = 0.014). Conclusions:The asymmetry index of leg skeletal muscle mass was associated with gait speed in older adults requiring long-term care. Future assessment and interventions directed towards symmetry of leg skeletal muscle mass may help to improve gait speed in older adults.

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Factors influencing gait speed in community-dwelling older women: A Bayesian approach

Cited by 4 publications

References 31 publications

Propulsive forces and muscle activation during gait: comparisons between premenopausal and postmenopausal midlife women

Propulsive forces and muscle activation during gait: comparisons between premenopausal and postmenopausal midlife women

Upper and Lower Limb Muscle Thickness Measurements in Older Women: Analysis of Variability and Development of Prediction Equations

Leg skeletal muscle mass asymmetry is independently associated with gait speed in older adults requiring long‐term care

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