Contribution of Biological, Physiological and Gait Mechanisms to High Metabolic Cost of Walking in Older Adults

Johns Hopkins University, Baltimore MD

Investigators

Abstract

PROJECT SUMMARY Age-related decline in mobility is strongly associated with loss of independence and increased risk of frailty and mortality in older adults. Mobility decline is typically preceded by a slowing of gait speed, which is closely reflected by a decrease in peak energetic capacity (VO2 peak) and an increase in the energetic cost of walking. Although age-related declines in peak capacity and fitness are well-established, mechanisms contributing to a higher energetic cost of walking are under-studied. In response to RFA–AG-25-030, this application proposes to investigate bioenergetic and physiological mechanisms underlying slow gait speed and high energetic cost of walking. We will use clinical, laboratory, and sensor-based free-living assessments to detect changes in health and mobility consistent with the onset and progression of energetic inefficiencies in a population of 100 diverse older participants aged ≥70 years from the Johns Hopkins Older Americans Independence Center (OAIC) registry who vary in demographics, health, and function. We will conduct baseline and two-year assessments of muscle quantity and metabolic quality, gait mechanics, free-living physical activity and sedentary behaviors, and biological (blood biomarkers) and physiological (heart rate and variability, glucose control) indicators of health in older adults to compare their relative importance to preserving gait speed and energetic efficiency. Our overarching hypothesis is that deficits in energy production and utilization induced by aging-related changes across multiple aspects of energy metabolism, gait mechanics, physical activity, and clinical/subclinical disease burden contribute to slowed gait and poor mobility and to their progression with advancing age. Specifically, as older adults move along the gait speed continuum, heterogeneity in muscle quality and metabolism, gait mechanics and characteristics, physical activity and sedentary behavior, and disease burden contribute to energetic (in)efficiency and trajectory of gait speed decline. Individuals who maintain high energetic efficiency are more likely to maintain gait speed, with minimal decline over time. Our specific aims are to: (1) determine the cross-sectional and longitudinal associations of muscle quantity and metabolic quality, and gait mechanics, with gait speed and the energetic cost of walking; (2) establish the cross-sectional and longitudinal associations of novel sensor-based measures of free-living physical activity and sedentary behaviors, heart rate and variability, and glucose control with gait speed and the energetic cost of walking; and (3) quantify the relative predictive performance -and interactions between- the laboratory and free-living measures from Aims 1 and 2, as well as traditional blood biomarkers, as contributors to high energetic cost of walking and slow gait speed using machine learning methods. Conducting these rigorous assessments in an older at-risk population where interventions may still be impactful is especially timely, given the population-wide proliferation of metabolic- associated diseases in older adults.