Analysis of Physical Activity Using Wearable Health Technology in US Adults Enrolled in the All of Us Research Program: Multiyear Observational Study
BackgroundTo date, no studies have examined adherence to the 2018 Physical Activity Guidelines for Americans (PAGA) in real-world longitudinal settings using objectively measured activity monitoring data. This study addresses this gap by using commercial activity monitoring (...
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JMIR Publications
2024-12-01
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| Series: | Journal of Medical Internet Research |
| Online Access: | https://www.jmir.org/2024/1/e65095 |
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| author | Rujul Singh Macy K Tetrick James L Fisher Peter Washington Jane Yu Electra D Paskett Frank J Penedo Steven K Clinton Roberto M Benzo |
| author_facet | Rujul Singh Macy K Tetrick James L Fisher Peter Washington Jane Yu Electra D Paskett Frank J Penedo Steven K Clinton Roberto M Benzo |
| author_sort | Rujul Singh |
| collection | DOAJ |
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BackgroundTo date, no studies have examined adherence to the 2018 Physical Activity Guidelines for Americans (PAGA) in real-world longitudinal settings using objectively measured activity monitoring data. This study addresses this gap by using commercial activity monitoring (Fitbit) data from the All of Us dataset.
ObjectiveThe primary objectives were to describe the prevalence of adherence to the 2018 PAGA and identify associated sociodemographic determinants. Additionally, we compared 3 distinct methods of processing physical activity (PA) data to estimate adherence to the 2008 PAGA.
MethodsWe used the National Institutes of Health’s All of Us dataset, which contains minute-level Fitbit data for 13,947 US adults over a 7-year time span (2015-2022), to estimate adherence to PAGA. A published step-based method was used to estimate metabolic equivalents and assess adherence to the 2018 PAGA (ie, ≥150 minutes of moderate- to vigorous-intensity PA per week). We compared the step-based method, the heart rate–based method, and the proprietary Fitbit-developed algorithm to estimate adherence to the 2008 PAGA.
ResultsThe average overall adherence to the 2018 PAGA was 21.6% (3006/13,947; SE 0.4%). Factors associated with lower adherence in multivariate logistic regression analysis included female sex (relative to male sex; adjusted odds ratio [AOR] 0.66, 95% CI 0.60-0.72; P<.001); BMI of 25.0-29.9 kg/m2 (AOR 0.53, 95% CI 0.46-0.60; P<.001), 30-34.9 kg/m2 (AOR 0.30, 95% CI 0.25-0.36; P<.001), or ≥35 kg/m2 (AOR 0.13, 95% CI 0.10-0.16; P<.001; relative to a BMI of 18.5-24.9 kg/m2); being aged 30-39 years (AOR 0.66, 95% CI 0.56-0.77; P<.001), 40-49 years (AOR 0.79, 95% CI 0.68-0.93; P=.005), or ≥70 years (AOR 0.74, 95% CI 0.62-0.87; P<.001; relative to being 18-29 years); and non-Hispanic Black race or ethnicity (AOR 0.63, 95% CI 0.50-0.79; P<.001; relative to non-Hispanic White race or ethnicity). The Fitbit algorithm estimated that a larger percentage of the sample (10,307/13,947, 73.9%; 95% CI 71.2-76.6) adhered to the 2008 PAGA compared to the heart rate method estimate (4740/13,947, 34%; 95% CI 32.8-35.2) and the step-based method (1401/13,947, 10%; 95% CI 9.4-10.6).
ConclusionsOur results show significant sociodemographic differences in PAGA adherence and notably different estimates of adherence depending on the algorithm used. These findings warrant the need to account for these disparities when implementing PA interventions and the need to establish an accurate and reliable method of using commercial accelerometers to examine PA, particularly as health care systems begin integrating wearable device data into patient health records. |
| format | Article |
| id | doaj-art-0bb1ca991e68469ea745d9da286d8a54 |
| institution | Kabale University |
| issn | 1438-8871 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | Journal of Medical Internet Research |
| spelling | doaj-art-0bb1ca991e68469ea745d9da286d8a542024-12-10T21:46:37ZengJMIR PublicationsJournal of Medical Internet Research1438-88712024-12-0126e6509510.2196/65095Analysis of Physical Activity Using Wearable Health Technology in US Adults Enrolled in the All of Us Research Program: Multiyear Observational StudyRujul Singhhttps://orcid.org/0009-0009-8757-0658Macy K Tetrickhttps://orcid.org/0009-0004-2605-9614James L Fisherhttps://orcid.org/0000-0003-3211-2691Peter Washingtonhttps://orcid.org/0000-0003-3276-4411Jane Yuhttps://orcid.org/0000-0002-0527-4022Electra D Pasketthttps://orcid.org/0000-0002-8247-8299Frank J Penedohttps://orcid.org/0000-0002-2780-0417Steven K Clintonhttps://orcid.org/0000-0002-2840-5865Roberto M Benzohttps://orcid.org/0000-0001-8634-6472 BackgroundTo date, no studies have examined adherence to the 2018 Physical Activity Guidelines for Americans (PAGA) in real-world longitudinal settings using objectively measured activity monitoring data. This study addresses this gap by using commercial activity monitoring (Fitbit) data from the All of Us dataset. ObjectiveThe primary objectives were to describe the prevalence of adherence to the 2018 PAGA and identify associated sociodemographic determinants. Additionally, we compared 3 distinct methods of processing physical activity (PA) data to estimate adherence to the 2008 PAGA. MethodsWe used the National Institutes of Health’s All of Us dataset, which contains minute-level Fitbit data for 13,947 US adults over a 7-year time span (2015-2022), to estimate adherence to PAGA. A published step-based method was used to estimate metabolic equivalents and assess adherence to the 2018 PAGA (ie, ≥150 minutes of moderate- to vigorous-intensity PA per week). We compared the step-based method, the heart rate–based method, and the proprietary Fitbit-developed algorithm to estimate adherence to the 2008 PAGA. ResultsThe average overall adherence to the 2018 PAGA was 21.6% (3006/13,947; SE 0.4%). Factors associated with lower adherence in multivariate logistic regression analysis included female sex (relative to male sex; adjusted odds ratio [AOR] 0.66, 95% CI 0.60-0.72; P<.001); BMI of 25.0-29.9 kg/m2 (AOR 0.53, 95% CI 0.46-0.60; P<.001), 30-34.9 kg/m2 (AOR 0.30, 95% CI 0.25-0.36; P<.001), or ≥35 kg/m2 (AOR 0.13, 95% CI 0.10-0.16; P<.001; relative to a BMI of 18.5-24.9 kg/m2); being aged 30-39 years (AOR 0.66, 95% CI 0.56-0.77; P<.001), 40-49 years (AOR 0.79, 95% CI 0.68-0.93; P=.005), or ≥70 years (AOR 0.74, 95% CI 0.62-0.87; P<.001; relative to being 18-29 years); and non-Hispanic Black race or ethnicity (AOR 0.63, 95% CI 0.50-0.79; P<.001; relative to non-Hispanic White race or ethnicity). The Fitbit algorithm estimated that a larger percentage of the sample (10,307/13,947, 73.9%; 95% CI 71.2-76.6) adhered to the 2008 PAGA compared to the heart rate method estimate (4740/13,947, 34%; 95% CI 32.8-35.2) and the step-based method (1401/13,947, 10%; 95% CI 9.4-10.6). ConclusionsOur results show significant sociodemographic differences in PAGA adherence and notably different estimates of adherence depending on the algorithm used. These findings warrant the need to account for these disparities when implementing PA interventions and the need to establish an accurate and reliable method of using commercial accelerometers to examine PA, particularly as health care systems begin integrating wearable device data into patient health records.https://www.jmir.org/2024/1/e65095 |
| spellingShingle | Rujul Singh Macy K Tetrick James L Fisher Peter Washington Jane Yu Electra D Paskett Frank J Penedo Steven K Clinton Roberto M Benzo Analysis of Physical Activity Using Wearable Health Technology in US Adults Enrolled in the All of Us Research Program: Multiyear Observational Study Journal of Medical Internet Research |
| title | Analysis of Physical Activity Using Wearable Health Technology in US Adults Enrolled in the All of Us Research Program: Multiyear Observational Study |
| title_full | Analysis of Physical Activity Using Wearable Health Technology in US Adults Enrolled in the All of Us Research Program: Multiyear Observational Study |
| title_fullStr | Analysis of Physical Activity Using Wearable Health Technology in US Adults Enrolled in the All of Us Research Program: Multiyear Observational Study |
| title_full_unstemmed | Analysis of Physical Activity Using Wearable Health Technology in US Adults Enrolled in the All of Us Research Program: Multiyear Observational Study |
| title_short | Analysis of Physical Activity Using Wearable Health Technology in US Adults Enrolled in the All of Us Research Program: Multiyear Observational Study |
| title_sort | analysis of physical activity using wearable health technology in us adults enrolled in the all of us research program multiyear observational study |
| url | https://www.jmir.org/2024/1/e65095 |
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