Literature DB >> 36216933

Association of step counts over time with the risk of chronic disease in the All of Us Research Program.

Hiral Master1, Jeffrey Annis1, Shi Huang2, Joshua A Beckman3, Francis Ratsimbazafy1, Kayla Marginean1, Robert Carroll4, Karthik Natarajan5, Frank E Harrell2, Dan M Roden6, Paul Harris7, Evan L Brittain8.   

Abstract

The association between physical activity and human disease has not been examined using commercial devices linked to electronic health records. Using the electronic health records data from the All of Us Research Program, we show that step count volumes as captured by participants' own Fitbit devices were associated with risk of chronic disease across the entire human phenome. Of the 6,042 participants included in the study, 73% were female, 84% were white and 71% had a college degree, and participants had a median age of 56.7 (interquartile range 41.5-67.6) years and body mass index of 28.1 (24.3-32.9) kg m-2. Participants walked a median of 7,731.3 (5,866.8-9,826.8) steps per day over the median activity monitoring period of 4.0 (2.2-5.6) years with a total of 5.9 million person-days of monitoring. The relationship between steps per day and incident disease was inverse and linear for obesity (n = 368), sleep apnea (n = 348), gastroesophageal reflux disease (n = 432) and major depressive disorder (n = 467), with values above 8,200 daily steps associated with protection from incident disease. The relationships with incident diabetes (n = 156) and hypertension (n = 482) were nonlinear with no further risk reduction above 8,000-9,000 steps. Although validation in a more diverse sample is needed, these findings provide a real-world evidence-base for clinical guidance regarding activity levels that are necessary to reduce disease risk.
© 2022. The Author(s).

Entities:  

Year:  2022        PMID: 36216933     DOI: 10.1038/s41591-022-02012-w

Source DB:  PubMed          Journal:  Nat Med        ISSN: 1078-8956            Impact factor:   87.241


  1 in total

1.  Using Electronic Health Records To Generate Phenotypes For Research.

Authors:  Sarah A Pendergrass; Dana C Crawford
Journal:  Curr Protoc Hum Genet       Date:  2018-12-05
  1 in total

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