Physical performance analysis: A new approach to assessing free-living physical activity in musculoskeletal pain and mobility-limited populations

Abstract

BackgroundAccurate measurement of physical performance in individuals with musculoskeletal pain is essential. Accelerometry is a powerful tool for this purpose, yet the current methods designed to evaluate energy expenditure are not optimized for this population. The goal of this study is to empirically derive a method of accelerometry analysis specifically for musculoskeletal pain populations.MethodsWe extracted data from 6,796 participants in the 2003–4 National Health and Nutrition Examination Survey (NHANES) including: 7-day accelerometry, health and pain questionnaires, and anthropomorphics. Custom macros were used for data processing, complex survey regression analyses, model selection, and statistical adjustment. After controlling for a multitude of variables that influence physical activity, we investigated whether distinct accelerometry profiles accompany pain in different locations of the body; and we identified the intensity intervals that best characterized these profiles.ResultsUnique accelerometry profiles were observed for pain in different body regions, logically clustering together based on proximity. Based on this, the following novel intervals (counts/minute) were identified and defined: Performance Sedentary (PSE) = 1–100, Performance Light 1 (PL1) = 101–350, Performance Light 2 (PL2) = 351–800, Performance Light 3 (PL3) = 801–2500, and Performance Moderate/Vigorous (PMV) = 2501–30000. The refinement of accelerometry signals into these new intervals, including 3 distinct ranges that fit inside the established light activity range, best captures alterations in real-life physical performance as a result of regional pain.Discussion and conclusionsThese new accelerometry intervals provide a model for objective measurement of real-life physical performance in people with pain and musculoskeletal disorders, with many potential uses. They may be used to better evaluate the relationship between pain and daily physical function, monitor musculoskeletal disease progression, gauge disease severity, inform exercise prescription, and quantify the functional impact of treatments. Based on these findings, we recommend that future studies of pain and musculoskeletal disorders analyze accelerometry output based on these new “physical performance” intervals.

<p>Psychosocial Correlates of Objective, Performance-Based, and Patient-Reported Physical Function Among Patients with Heterogeneous Chronic Pain</p>

“…Consistently, the Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials (IMMPACT) 8,9 and the International Classification of Functioning, Disability and Health (ICF) 10 recommend comprehensively assessing physical function, with PROs, performance-based (which capture functional capacity during a time-limited standard test), and objective assessments (ambulatory measurement of daily step-count via accelerometers across a specified time period). 11 Studies evaluating the relationship between the different aspects of physical function in chronic pain have generally found conflicting results on the association between PROs and accelerometer-measured physical function. [12][13][14] They found a small to moderate association between PROs and performanced based physical function, [15][16][17][18] as well as between accelerometer-measured physical function and PROs.…”

Does the physical activity profile change in patients with hip dysplasia from before to 1 year after periacetabular osteotomy?

“…However, it is important to recognize that self-reported physical activity captures the capability to complete a given task, while the ability to measure the actual performance is limited (Smuck et al. 2017). Accelerometer-based measures of physical activity allow us to evaluate if patients with hip dysplasia change objectively measured physical activity profile, alongside with subjective measured levels of improved pain, physical function, and quality of life after PAO.…”

Subjective and Objective Measures of Daytime Activity and Sleep Disturbance in Retinitis Pigmentosa

“…55 For future studies, it has been suggested that it is possible to modify and analyze novel intervals for accelerometer data to detect varying activity levels of real-life physical performance. 56 The wrist is the preferred location for sleep measures and, while the waist has been reported as the optimal location for recording a wide range of physical activity, 57 a previous study found much lower compliance rates for waist sensors compared to wrist sensors (i.e., 65% versus 99% wear time). 58 This finding prompted the NHANES program to switch placement from the waist to the wrist, which did result in improved compliance rates.…”