Date Presented 03/26/20
This study explored the feasibility of using wearable activity monitors in people with mild cognitive impairment and correlations between the activity monitor data and self-reported physical activity and functional measures.
Primary Author and Speaker: John Rider
Contributing Authors: Haehyun Lee, Jason Longhurst, Merrill Landers
PURPOSE: Mild cognitive impairment (MCI) significantly impacts quality of life and is often a prelude to further cognitive decline. Currently, physical activity is the most promising treatment modality for slowing the progression of MCI and improving functional capacity for activities of daily living.
The quantification of physical activity is important to establish objective and reliable data for research and clinical utility. Physical activity levels can be assessed by self-report questionnaires, activity logs, or wearable activity monitors. Self-report questionnaires and activity logs are cost-effective and easy to administer; however, they rely on the participants’ recall ability, which is especially problematic in individuals with MCI.
Wearable activity monitors have the potential to provide more detailed and objective data for physical activity. However, participants must remember to wear the monitors correctly to collect accurate data. The potential benefit of reducing recall bias and collecting more accurate and detailed quantitative data justifies this investigation.
The purpose of this study was to assess the feasibility of using wearable activity monitors in people with MCI. Additionally, we aimed to assess the association between the International Physical Activity Questionnaire (IPAQ) and the activity monitor data and to determine if activity monitor data was more strongly associated with related variables (Caregiver burden, physical measures, and functional measures) than the IPAQ.
DESIGN: A secondary analysis of data obtained from a prospective cross-over design study. Twelve participants with neurologists diagnosed MCI and Montreal Cognitive Assesment scores between 25 and 19.
METHOD: Participants were instructed to wear the activity monitors during waking hours for one week. The percentage of participants who wore the activity monitors as instructed was calculated from activity monitor data. Additionally, Pearson’s correlational coefficients were used to explore the associations of the activity monitor data and related functional variables.
RESULTS: All participants wore the activity monitors for >75% of the time, with an average of 11.75 hours per day for at least six days of the week. There were strong positive correlations between the IPAQ question 1a (vigorous activity) and percent of total walking >1.3 m/sec and between IPAQ question 4 (sitting) and average length of sedentary breaks. There were no correlations between IPAQ 2a (moderate activity) or 3a (walking). There were also no negative correlations between IPAQ 1a and measures of sedentary or low-intensity activity, or between IPAQ 4 and measures of moderate to vigorous physical activity, as would be anticipated. Quality of life had a strong negative correlation with total walking <1 m/sec and strong positive correlations with percent of moderate to vigorous exercise per day.
CONCLUSION: The use of activity monitors with individuals who have MCI is feasible and provides additional data beyond self-report measures. Self-report measures may be inaccurate in individuals with MCI, based on the lack of correlation between the IPAQ and activity monitor data. None of the collected measures (cognition, physical measures, activity monitor data) correlated with caregiver burden; however, moderate to vigorous activity may be a significant factor in the quality of life for individuals with MCI.
IMPACT STATEMENT: This study provides support for the feasibility of using activity monitors with individuals who have MCI for a more accurate and objective measure of physical activity. Additionally, increasing physical activity within ADL/IADLs may have the potential to improve the quality of life for individuals with MCI.
References
Langa, K., & Levine, D. (2014). The Diagnosis and Management of Mild Cognitive Impairment: A Clinical Review. JAMA, 312(23), 2551-2561. DOI: 10.1001/jama.2014.13806
Ahlskog, J., Geda, Y., Graff-Radford, N., & Petersen, R. (2011). Physical Exercise as a Preventive or Disease-Modifying Treatment of Dementia and Brain Aging. Mayo Clinic Proceedings, 86(9), 876-884. DOI: 10.4065/mcp.2011.0252
Forbes, D., Thiessen, E., Blake, C., Forbes, S.C., & Forbes, S. (2013).Exercise programs for people with dementia. The Cochrane Database of Systematic Reviews, 2013(12), CD006489. DOI: 10.1002/14651858.CD006489.pub3
Butte, N. F., Ekelund, U. R., & Westerterp, K. (2012). Assessing Physical Activity Using Wearable Monitors: Measures of Physical Activity. Medicine & Science in Sports & Exercise, 44(1S Suppl 1), S5-S12. DOI: 10.1249/MSS.0b013e3182399c0e
