Abstract
ObjectivesLittle is known about the severity and long-term health and economic consequences of sarcopenia. We developed a sarcopenia index to measure severity in older Americans and estimated the long-term societal benefits generated by effective interventions to mitigate severity.DesignUsing a micro-simulation model, we quantified the potential societal value generated in the US in 2010–2040 by reductions in sarcopenia severity in older adults. All analyses were performed in Stata and SAS. Setting & Participants: Secondary data from the National Health and Nutrition Examination Survey (NHANES) (N = 1634) and Health and Retirement Study (HRS) (N = 952) were used to develop a sarcopenia severity index in older adults.MeasurementsMultitrait multi-method and factor analyses were used to validate and calibrate the sarcopenia severity index, which was modeled as a function of gait speed, walking without an assistive device, and moderate physical activity.ResultsIn representative elderly populations, reducing sarcopenia severity by improving gait speed by 0.1 m/s in those with gait speed under 0.8 m/s generated a cumulative benefit of $65B by 2040 (2015 dollars). Improving walking ability in those with walking difficulty generated cumulative social benefit of $787B by 2040.ConclusionsReducing sarcopenia severity would generate significant health and economic benefits to society— almost $800B in the most optimistic scenarios.
Highlights
Sarcopenia, an age-related loss of muscle mass and strength [1, 2], contributes to disability and increases the risk of morbidity and mortality [3,4,5,6,7,8]
While BMI and appendicular lean mass adjusted for BMI performed the latter was not available in Health and Retirement Study (HRS); the models using BMI were preferred because they allowed for validation and comparison with principal factor analysis using a HRS individual sample
Based on the model diagnostic statistics, we preferred the four-method model with gait speed as the performance measure of the sarcopenia trait, moderate physical activity as the self-reported trait measure, use of an assistive device in the timed walk as the self-reported physical trait measure, and BMI as the physical measure
Summary
Sarcopenia, an age-related loss of muscle mass and strength [1, 2], contributes to disability and increases the risk of morbidity and mortality [3,4,5,6,7,8]. One in four older adults (individuals over the age of 65) in the US has mobility impairment that may be the result of, or worsened by, sarcopenia. In 2000, the direct healthcare costs attributable to sarcopenia alone reached an estimated $18.5 billion [9, 10]. Despite these risks, identifying patients for treatment remains challenging [11], in part because no uniform or generally accepted diagnostic criteria exist [12]. A significant amount of variation in severity and appropriateness for intervention likely exists among individuals who meet the typical binary diagnostic criteria for a sarcopenia. A natural question is whether one can create a continuous measure of sarcopenia severity with an index
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