Age-Related Imbalance Is Associated With Slower Walking Speed: An Analysis From the National Health and Nutrition Examination Survey

Abstract

Background and purpose Walking speed is an important dimension of gait function and is known to decline with age. Gait function is a process of dynamic balance and motor control that relies on multiple sensory inputs (e.g. visual, proprioceptive and vestibular) and motor outputs. These sensory and motor physiologic systems also play a role in static postural control, which has been shown to decline with age. In this study, we evaluated whether imbalance that occurs as part of healthy aging is associated with slower walking speed in a nationally-representative sample of older adults. Methods We performed a cross-sectional analysis of the previously collected1999–2002 National Health and Nutrition Examination Survey (NHANES) data to evaluate whether age-related imbalance is associated with slower walking speed in older adults aged 50 to 85 (n=2,116). Balance was assessed on a pass/fail basis during a challenging postural task—Condition 4 of the modified Romberg test, and walking speed was determined using a 20-feet (6.10 m) timed walk. Multivariable linear regression was used to evaluate the association between imbalance and walking speed, adjusting for demographic and health-related covariates. A structural equation model was developed to estimate the extent to which imbalance mediates the association between age and slower walking speed. Results In the unadjusted regression model, inability to perform the NHANES balance task was significantly associated with 0.10 m/s slower walking speed (95% confidence interval [CI]: −0.13, −0.07; p<0.01). In the multivariable regression analysis, inability to perform the balance task was significantly associated with 0.06 m/s slower walking speed (95% CI: −0.09, −0.03; p<0.01), an effect size equivalent to 12 years of age. The structural equation model estimated that age-related imbalance mediates 12.2% of the association between age and slower walking speed in older adults. Conclusion In a nationally-representative sample, age-related balance limitation was associated with slower walking speed. Balance impairment may lead to walking speed declines. Additionally, reduced static postural control and dynamic walking speed that occur with aging may share common etiologic origins, including the decline in visual, proprioceptive, and vestibular sensory and motor functions.

Using a Deep Learning Method and Data from Two-Dimensional (2D) Marker-Less Video-Based Images for Walking Speed Classification

“…Walking speed is a simple, rapid, and easily obtained assessment tool [ 3 ], but significantly affects all gait parameters, such as cadence, stride length, stance, and swing durations [ 4 , 5 ]. For a long time, walking speed has been used as an independent screening indicator of demographic characteristics (e.g., age and sex), functional activities (e.g., kinematic and kinetic patterns and spatiotemporal parameters), and various physical outcomes (e.g., activity-related fear of falling) in normal controlled individuals (e.g., healthy) and patients (e.g., Parkinson’s disease and osteoarthritis) [ 6 , 7 , 8 , 9 , 10 ]. Additionally, the functional movement performance of individuals with neuromuscular conditions, such as post-stroke and cerebral palsy, can be assessed based on their walking speed, which might have an impact on gait [ 9 , 10 ].…”

The Relationship between Locomotive Syndrome Risk, Gait Pattern, and Standing Posture in Young Japanese Women: A Cross-Sectional Study

“…In addition, walking stride length generally reduces the locomotive syndrome risk [ 26 ]. This is suggested to maintain lower limb strength, balance, and hip flexibility [ 27 , 28 ]. Although it was the maximum walking in our study, we confirmed that the locomotive syndrome risk in young people was associated with walking speed.…”

Walking balance is mediated by muscle strength and bone mineral density in postmenopausal women: an observational study

“…Multiple linear regression analysis was conducted to assess the effect of the six explanatory variables (HGS,, %BFM, FFM, BMI, FM and T-score of the right big toe(T-scorert) on WB, in postmenopausal women, after adjustment for age [ 33 ], smoking status [ 34 ], level of physical activity [ 35 ], alcohol intake, [ 36 , 37 ] vitamin K intake, [ 38 ] comorbid conditions (e.g. chronic heart failure, renal failure and cancer) [ 25 – 27 ] and drug interactions (e.g.…”