Dataset Information

Gait speed associated factors in elderly subjects undergoing exams to obtain the driver's license.

ABSTRACT: OBJECTIVE:to analyze the factors associated with gait speed in elderly subjects undergoing physical and mental fitness tests to obtain a driver's license. METHOD:a cross-sectional quantitative study conducted in transit agencies. The probabilistic sample included 421 elderly (≥ 60 years old). The study was developed through application of questionnaires and tests that assess the frailty phenotype. For evaluating gait speed, the time spent by each participant to walk a 4.6 meter distance at normal pace on a flat surface was timed. Data were analyzed by using multiple linear regression and the stepwise method. The R statistical program version 3.4.0 was adopted. RESULTS:there was a significant association between gait speed and paid work (<0.0000), body mass index (<0.0000), Mini-Mental State Examination (=0.0366), physical frailty (pre-frail =0.0063 and non-frail <0.0000), age (<0.0000), sex (=0.0255), and manual grip strength (<0.0000). CONCLUSION:elderly drivers who do not work, women of advanced age, high body mass index, low score in the Mini-Mental State Examination, low hand grip strength, and frail tend to decrease gait speed and should be a priority of interventions.

SUBMITTER: Binotto MA

PROVIDER: S-EPMC6528639 | biostudies-other | 2019 Apr

REPOSITORIES: biostudies-other

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Gait speed associated factors in elderly subjects undergoing exams to obtain the driver's license.

Binotto Maria Angélica MA Lenardt Maria Helena MH Carneiro Nathalia Hammerschmidt Kolb NHK Lourenço Tânia Maria TM Cechinel Clovis C Rodríguez-Martínez María Del Carmen MDC

Revista latino-americana de enfermagem 20190429

<h4>Objective</h4>to analyze the factors associated with gait speed in elderly subjects undergoing physical and mental fitness tests to obtain a driver's license.<h4>Method</h4>a cross-sectional quantitative study conducted in transit agencies. The probabilistic sample included 421 elderly (≥ 60 years old). The study was developed through application of questionnaires and tests that assess the frailty phenotype. For evaluating gait speed, the time spent by each participant to walk a 4.6 meter di ...[more]

PMID: 31038632

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Project description:Gait speed is a measure of general fitness. Changing from usual (UGS) to maximum (MGS) gait speed requires coordinated action of many body systems. Gait speed reserve (GSR) is defined as MGS-UGS. From a shortlist of 88 features across five categories including sociodemographic, cognitive, and physiological, we aimed to find and compare the sets of predictors that best describe UGS, MGS, and GSR. For this, we leveraged data from 3,925 adults aged 50+ from Wave 3 of The Irish Longitudinal Study on Ageing (TILDA). Features were selected by a histogram gradient boosting regression-based stepwise feature selection pipeline. Each model's feature importance and input-output relationships were explored using TreeExplainer from the Shapely Additive Explanations explainable machine learning package. The mean Radj2 (SD) from fivefold cross-validation on training data and the Radj2 score on test data were 0.38 (0.04) and 0.41 for UGS, 0.45 (0.04) and 0.46 for MGS, and 0.19 (0.02) and 0.21 for GSR. Each model selected features across all categories. Features common to all models were age, grip strength, chair stands time, mean motor reaction time, and height. Exclusive to UGS and MGS were educational attainment, fear of falling, Montreal cognitive assessment errors, and orthostatic intolerance. Exclusive to MGS and GSR were body mass index (BMI), and number of medications. No features were selected exclusively for UGS and GSR. Features unique to UGS were resting-state pulse interval, Center for Epidemiologic Studies Depression Scale (CESD) depression, sit-to-stand difference in diastolic blood pressure, and left visual acuity. Unique to MGS were standard deviation in sustained attention to response task times, resting-state heart rate, smoking status, total heartbeat power during paced breathing, and visual acuity. Unique to GSR were accuracy proportion in a sound-induced flash illusion test, Mini-mental State Examination errors, and number of cardiovascular conditions. No interactions were present in the GSR model. The four features that overall gave the most impactful interactions in the UGS and MGS models were age, chair stands time, grip strength, and BMI. These findings may help provide new insights into the multisystem predictors of gait speed and gait speed reserve in older adults and support a network physiology approach to their study.

Project description:The differences in kinetic mechanisms of decreased gait speed across brain lesion sides have not been elucidated, including the arrangement of motor modules reflected by kinetic interjoint coordination. The purpose of this study was to elucidate the differences in the kinetic factors of slow gait speed in patients with stroke on the lesion sides. A three-dimensional motion analysis system was employed to assess joint moment in the lower limb and representative gait parameters in 32 patients with right hemisphere brain damage (RHD) and 38 patients with left hemisphere brain damage (LHD) following stroke as well as 20 healthy controls. Motor module composition and timing were determined using principal component analysis based on the three joint moments in the lower limb in the stance phase, which were the variances accounted for principal components (PCs) and the peak timing in the time series of PCs. A stepwise multiple linear regression analysis was performed to identify the most significant joint moment and PC-associated parameter in explaining gait speed. A negligible difference was observed in age, weight, height, and gait speed among patients with RHD and LHD and controls. The following factors contributed to gait speed: in patients with RHD, larger ankle plantarflexion moment on the paretic (p = 0.001) and nonparetic (p = 0.002) sides and ankle dorsiflexion moment on the nonparetic side (p = 0.004); in patients with LHD, larger ankle plantarflexion moment (p < 0.001) and delayed peak timing of the first PC (p = 0.012) on the paretic side as well as ankle dorsiflexion moment on the nonparetic side (p < 0.001); in the controls, delayed peak timing of the first PC (p = 0.002) on the right side and larger ankle dorsiflexion moment (p = 0.001) as well as larger hip flexion moment on the left side (p = 0.023). The findings suggest that the kinetic mechanisms of gait speed may differ among patients with RHD following patients with stroke with LHD, and controls.

Dataset Information

Gait speed associated factors in elderly subjects undergoing exams to obtain the driver's license.

Publications

Gait speed associated factors in elderly subjects undergoing exams to obtain the driver's license.

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