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Wrist Accelerometer Estimates of Physical Activity Intensity During Walking in Older Adults and People Living With Complex Health Conditions: Retrospective Observational Data Analysis Study
Accurate measurement of daily physical activity (PA) is important as PA is linked to health outcomes in older adults and people living with complex health conditions. Wrist-worn accelerometers are widely used to estimate PA intensity, including walking, which composes much of daily PA. However, ther...
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Published in: | JMIR formative research 2023-03, Vol.7, p.e41685-e41685 |
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description | Accurate measurement of daily physical activity (PA) is important as PA is linked to health outcomes in older adults and people living with complex health conditions. Wrist-worn accelerometers are widely used to estimate PA intensity, including walking, which composes much of daily PA. However, there is concern that wrist-derived PA data in these cohorts is unreliable due to slow gait speed, mobility aid use, disease-related symptoms that impact arm movement, and transient activities of daily living. Despite the potential for error in wrist-derived PA intensity estimates, their use has become ubiquitous in research and clinical application.
The goals of this work were to (1) determine the accuracy of wrist-based estimates of PA intensity during known walking periods in older adults and people living with cerebrovascular disease (CVD) or neurodegenerative disease (NDD) and (2) explore factors that influence wrist-derived intensity estimates.
A total of 35 older adults (n=23 with CVD or NDD) wore an accelerometer on the dominant wrist and ankle for 7 to 10 days of continuous monitoring. Stepping was detected using the ankle accelerometer. Analyses were restricted to gait bouts ≥60 seconds long with a cadence ≥80 steps per minute (LONG walks) to identify periods of purposeful, continuous walking likely to reflect moderate-intensity activity. Wrist accelerometer data were analyzed within LONG walks using 15-second epochs, and published intensity thresholds were applied to classify epochs as sedentary, light, or moderate-to-vigorous physical activity (MVPA). Participants were stratified into quartiles based on the percent of walking epochs classified as sedentary, and the data were examined for differences in behavioral or demographic traits between the top and bottom quartiles. A case series was performed to illustrate factors and behaviors that can affect wrist-derived intensity estimates during walking.
Participants averaged 107.7 (SD 55.8) LONG walks with a median cadence of 107.3 (SD 10.8) steps per minute. Across participants, wrist-derived intensity classification was 22.9% (SD 15.8) sedentary, 27.7% (SD 14.6) light, and 49.3% (SD 25.5) MVPA during LONG walks. All participants measured a statistically lower proportion of wrist-derived activity during LONG walks than expected (all P |
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The goals of this work were to (1) determine the accuracy of wrist-based estimates of PA intensity during known walking periods in older adults and people living with cerebrovascular disease (CVD) or neurodegenerative disease (NDD) and (2) explore factors that influence wrist-derived intensity estimates.
A total of 35 older adults (n=23 with CVD or NDD) wore an accelerometer on the dominant wrist and ankle for 7 to 10 days of continuous monitoring. Stepping was detected using the ankle accelerometer. Analyses were restricted to gait bouts ≥60 seconds long with a cadence ≥80 steps per minute (LONG walks) to identify periods of purposeful, continuous walking likely to reflect moderate-intensity activity. Wrist accelerometer data were analyzed within LONG walks using 15-second epochs, and published intensity thresholds were applied to classify epochs as sedentary, light, or moderate-to-vigorous physical activity (MVPA). Participants were stratified into quartiles based on the percent of walking epochs classified as sedentary, and the data were examined for differences in behavioral or demographic traits between the top and bottom quartiles. A case series was performed to illustrate factors and behaviors that can affect wrist-derived intensity estimates during walking.
Participants averaged 107.7 (SD 55.8) LONG walks with a median cadence of 107.3 (SD 10.8) steps per minute. Across participants, wrist-derived intensity classification was 22.9% (SD 15.8) sedentary, 27.7% (SD 14.6) light, and 49.3% (SD 25.5) MVPA during LONG walks. All participants measured a statistically lower proportion of wrist-derived activity during LONG walks than expected (all P<.001), and 80% (n=28) of participants had at least 20 minutes of LONG walking time misclassified as sedentary based on wrist-derived intensity estimates. Participants in the highest quartile of wrist-derived sedentary classification during LONG walks were significantly older (t
=4.24, P<.001) and had more variable wrist movement (t
=2.13, P=.049) compared to those in the lowest quartile.
The current best practice wrist accelerometer method is prone to misclassifying activity intensity during walking in older adults and people living with complex health conditions. A multidevice approach may be warranted to advance methods for accurately assessing PA in these groups.</description><identifier>ISSN: 2561-326X</identifier><identifier>EISSN: 2561-326X</identifier><identifier>DOI: 10.2196/41685</identifier><identifier>PMID: 36920452</identifier><language>eng</language><publisher>Canada: JMIR Publications</publisher><subject>Accelerometers ; Amyotrophic lateral sclerosis ; Ankle ; Data collection ; Data processing ; Disease ; Exercise ; Gait ; Metabolism ; Older people ; Original Paper ; Parkinson's disease ; Sedentary behavior ; Self report ; Walking ; Wearable computers ; Wrist</subject><ispartof>JMIR formative research, 2023-03, Vol.7, p.e41685-e41685</ispartof><rights>Kyle S Weber, F Elizabeth Godkin, Benjamin F Cornish, William E McIlroy, Karen Van Ooteghem. Originally published in JMIR Formative Research (https://formative.jmir.org), 15.03.2023.</rights><rights>2023. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Kyle S Weber, F Elizabeth Godkin, Benjamin F Cornish, William E McIlroy, Karen Van Ooteghem. Originally published in JMIR Formative Research (https://formative.jmir.org), 15.03.2023. 2023</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c458t-b703b97fc978642a7aac6e10bbb7368142e1864233c90528b600870d39e5278f3</citedby><cites>FETCH-LOGICAL-c458t-b703b97fc978642a7aac6e10bbb7368142e1864233c90528b600870d39e5278f3</cites><orcidid>0000-0003-2319-1746 ; 0000-0002-0367-0654 ; 0000-0002-8470-2805 ; 0000-0002-6743-3332 ; 0000-0002-9667-2666</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2918526184/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2918526184?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36920452$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Weber, Kyle S</creatorcontrib><creatorcontrib>Godkin, F Elizabeth</creatorcontrib><creatorcontrib>Cornish, Benjamin F</creatorcontrib><creatorcontrib>McIlroy, William E</creatorcontrib><creatorcontrib>Van Ooteghem, Karen</creatorcontrib><title>Wrist Accelerometer Estimates of Physical Activity Intensity During Walking in Older Adults and People Living With Complex Health Conditions: Retrospective Observational Data Analysis Study</title><title>JMIR formative research</title><addtitle>JMIR Form Res</addtitle><description>Accurate measurement of daily physical activity (PA) is important as PA is linked to health outcomes in older adults and people living with complex health conditions. Wrist-worn accelerometers are widely used to estimate PA intensity, including walking, which composes much of daily PA. However, there is concern that wrist-derived PA data in these cohorts is unreliable due to slow gait speed, mobility aid use, disease-related symptoms that impact arm movement, and transient activities of daily living. Despite the potential for error in wrist-derived PA intensity estimates, their use has become ubiquitous in research and clinical application.
The goals of this work were to (1) determine the accuracy of wrist-based estimates of PA intensity during known walking periods in older adults and people living with cerebrovascular disease (CVD) or neurodegenerative disease (NDD) and (2) explore factors that influence wrist-derived intensity estimates.
A total of 35 older adults (n=23 with CVD or NDD) wore an accelerometer on the dominant wrist and ankle for 7 to 10 days of continuous monitoring. Stepping was detected using the ankle accelerometer. Analyses were restricted to gait bouts ≥60 seconds long with a cadence ≥80 steps per minute (LONG walks) to identify periods of purposeful, continuous walking likely to reflect moderate-intensity activity. Wrist accelerometer data were analyzed within LONG walks using 15-second epochs, and published intensity thresholds were applied to classify epochs as sedentary, light, or moderate-to-vigorous physical activity (MVPA). Participants were stratified into quartiles based on the percent of walking epochs classified as sedentary, and the data were examined for differences in behavioral or demographic traits between the top and bottom quartiles. A case series was performed to illustrate factors and behaviors that can affect wrist-derived intensity estimates during walking.
Participants averaged 107.7 (SD 55.8) LONG walks with a median cadence of 107.3 (SD 10.8) steps per minute. Across participants, wrist-derived intensity classification was 22.9% (SD 15.8) sedentary, 27.7% (SD 14.6) light, and 49.3% (SD 25.5) MVPA during LONG walks. All participants measured a statistically lower proportion of wrist-derived activity during LONG walks than expected (all P<.001), and 80% (n=28) of participants had at least 20 minutes of LONG walking time misclassified as sedentary based on wrist-derived intensity estimates. Participants in the highest quartile of wrist-derived sedentary classification during LONG walks were significantly older (t
=4.24, P<.001) and had more variable wrist movement (t
=2.13, P=.049) compared to those in the lowest quartile.
The current best practice wrist accelerometer method is prone to misclassifying activity intensity during walking in older adults and people living with complex health conditions. A multidevice approach may be warranted to advance methods for accurately assessing PA in these groups.</description><subject>Accelerometers</subject><subject>Amyotrophic lateral sclerosis</subject><subject>Ankle</subject><subject>Data collection</subject><subject>Data processing</subject><subject>Disease</subject><subject>Exercise</subject><subject>Gait</subject><subject>Metabolism</subject><subject>Older people</subject><subject>Original Paper</subject><subject>Parkinson's disease</subject><subject>Sedentary behavior</subject><subject>Self report</subject><subject>Walking</subject><subject>Wearable computers</subject><subject>Wrist</subject><issn>2561-326X</issn><issn>2561-326X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpdkttuEzEQhlcIRKuSV0CWEBI3AR92vV5uUJQWGilSKg4qd5bXO5s4eNep7Y3Iw_FueJNStVx5PPP5n1_jybIJwe8pqfiHnHBRPMvOacHJlFH-8_mj-CybhLDFGFNCeFmxl9kZ4xXFeUHPsz-33oSIZlqDBe86iODRVYimUxECci262RyC0comJpq9iQe06CP0YYwuB2_6NbpV9td4mh6tbJMEZs1gY0Cqb9ANuJ0FtExPR9LEDZq7LqV-o2tQ9njtGxON68NH9BWid2EHYytAqzqA36uxlvpfqqjQLEXJT0Df4tAcXmUvWmUDTO7Pi-zH56vv8-vpcvVlMZ8tpzovRJzWJWZ1Vba6KgXPqSqV0hwIruu6ZFyQnAIZC4zpChdU1BxjUeKGVVDQUrTsIlucdBuntnLn03T8QTpl5DHh_FoqH422IDVvkn7LVKMgB1qrmjKRK920QLiGMml9OmnthrqDRkMfvbJPRJ9WerORa7eXBBNGeCGSwrt7Be_uBghRdiak_7OqBzcEmSyXlNCS4YS--Q_dusGnGSaqIqKgnIg8UW9PlE7DDx7aBzcEy3HB5HHBEvf6sfUH6t86sb-LDM5K</recordid><startdate>20230315</startdate><enddate>20230315</enddate><creator>Weber, Kyle S</creator><creator>Godkin, F Elizabeth</creator><creator>Cornish, Benjamin F</creator><creator>McIlroy, William E</creator><creator>Van Ooteghem, Karen</creator><general>JMIR Publications</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>NAPCQ</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-2319-1746</orcidid><orcidid>https://orcid.org/0000-0002-0367-0654</orcidid><orcidid>https://orcid.org/0000-0002-8470-2805</orcidid><orcidid>https://orcid.org/0000-0002-6743-3332</orcidid><orcidid>https://orcid.org/0000-0002-9667-2666</orcidid></search><sort><creationdate>20230315</creationdate><title>Wrist Accelerometer Estimates of Physical Activity Intensity During Walking in Older Adults and People Living With Complex Health Conditions: Retrospective Observational Data Analysis Study</title><author>Weber, Kyle S ; Godkin, F Elizabeth ; Cornish, Benjamin F ; McIlroy, William E ; Van Ooteghem, Karen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c458t-b703b97fc978642a7aac6e10bbb7368142e1864233c90528b600870d39e5278f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Accelerometers</topic><topic>Amyotrophic lateral sclerosis</topic><topic>Ankle</topic><topic>Data collection</topic><topic>Data processing</topic><topic>Disease</topic><topic>Exercise</topic><topic>Gait</topic><topic>Metabolism</topic><topic>Older people</topic><topic>Original Paper</topic><topic>Parkinson's disease</topic><topic>Sedentary behavior</topic><topic>Self report</topic><topic>Walking</topic><topic>Wearable computers</topic><topic>Wrist</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Weber, Kyle S</creatorcontrib><creatorcontrib>Godkin, F Elizabeth</creatorcontrib><creatorcontrib>Cornish, Benjamin F</creatorcontrib><creatorcontrib>McIlroy, William E</creatorcontrib><creatorcontrib>Van Ooteghem, Karen</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing & Allied Health Database</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Nursing & Allied Health Premium</collection><collection>Access via ProQuest (Open Access)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>JMIR formative research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Weber, Kyle S</au><au>Godkin, F Elizabeth</au><au>Cornish, Benjamin F</au><au>McIlroy, William E</au><au>Van Ooteghem, Karen</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Wrist Accelerometer Estimates of Physical Activity Intensity During Walking in Older Adults and People Living With Complex Health Conditions: Retrospective Observational Data Analysis Study</atitle><jtitle>JMIR formative research</jtitle><addtitle>JMIR Form Res</addtitle><date>2023-03-15</date><risdate>2023</risdate><volume>7</volume><spage>e41685</spage><epage>e41685</epage><pages>e41685-e41685</pages><issn>2561-326X</issn><eissn>2561-326X</eissn><abstract>Accurate measurement of daily physical activity (PA) is important as PA is linked to health outcomes in older adults and people living with complex health conditions. Wrist-worn accelerometers are widely used to estimate PA intensity, including walking, which composes much of daily PA. However, there is concern that wrist-derived PA data in these cohorts is unreliable due to slow gait speed, mobility aid use, disease-related symptoms that impact arm movement, and transient activities of daily living. Despite the potential for error in wrist-derived PA intensity estimates, their use has become ubiquitous in research and clinical application.
The goals of this work were to (1) determine the accuracy of wrist-based estimates of PA intensity during known walking periods in older adults and people living with cerebrovascular disease (CVD) or neurodegenerative disease (NDD) and (2) explore factors that influence wrist-derived intensity estimates.
A total of 35 older adults (n=23 with CVD or NDD) wore an accelerometer on the dominant wrist and ankle for 7 to 10 days of continuous monitoring. Stepping was detected using the ankle accelerometer. Analyses were restricted to gait bouts ≥60 seconds long with a cadence ≥80 steps per minute (LONG walks) to identify periods of purposeful, continuous walking likely to reflect moderate-intensity activity. Wrist accelerometer data were analyzed within LONG walks using 15-second epochs, and published intensity thresholds were applied to classify epochs as sedentary, light, or moderate-to-vigorous physical activity (MVPA). Participants were stratified into quartiles based on the percent of walking epochs classified as sedentary, and the data were examined for differences in behavioral or demographic traits between the top and bottom quartiles. A case series was performed to illustrate factors and behaviors that can affect wrist-derived intensity estimates during walking.
Participants averaged 107.7 (SD 55.8) LONG walks with a median cadence of 107.3 (SD 10.8) steps per minute. Across participants, wrist-derived intensity classification was 22.9% (SD 15.8) sedentary, 27.7% (SD 14.6) light, and 49.3% (SD 25.5) MVPA during LONG walks. All participants measured a statistically lower proportion of wrist-derived activity during LONG walks than expected (all P<.001), and 80% (n=28) of participants had at least 20 minutes of LONG walking time misclassified as sedentary based on wrist-derived intensity estimates. Participants in the highest quartile of wrist-derived sedentary classification during LONG walks were significantly older (t
=4.24, P<.001) and had more variable wrist movement (t
=2.13, P=.049) compared to those in the lowest quartile.
The current best practice wrist accelerometer method is prone to misclassifying activity intensity during walking in older adults and people living with complex health conditions. A multidevice approach may be warranted to advance methods for accurately assessing PA in these groups.</abstract><cop>Canada</cop><pub>JMIR Publications</pub><pmid>36920452</pmid><doi>10.2196/41685</doi><orcidid>https://orcid.org/0000-0003-2319-1746</orcidid><orcidid>https://orcid.org/0000-0002-0367-0654</orcidid><orcidid>https://orcid.org/0000-0002-8470-2805</orcidid><orcidid>https://orcid.org/0000-0002-6743-3332</orcidid><orcidid>https://orcid.org/0000-0002-9667-2666</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Accelerometers Amyotrophic lateral sclerosis Ankle Data collection Data processing Disease Exercise Gait Metabolism Older people Original Paper Parkinson's disease Sedentary behavior Self report Walking Wearable computers Wrist |
title | Wrist Accelerometer Estimates of Physical Activity Intensity During Walking in Older Adults and People Living With Complex Health Conditions: Retrospective Observational Data Analysis Study |
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