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

Open access
Master, Hiral, Annis, Jeffrey, Huang, Shi, Beckman, Joshua A., Ratsimbazafy, Francis, Marginean, Kayla, Carroll, Robert, Natarajan, Karthik +4 more·2022·Nature Medicine
DOI 10.1038/s41591-022-02012-wPMC PMC9671804
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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.

AI snapshot

Written from the paper’s full text.

TL;DR

In 6,042 All of Us Research Program participants who linked their own Fitbit and EHR data, higher daily step counts over a median 4.0 years were associated with lower incidence of several chronic diseases. The relationships were inverse and linear for obesity, sleep apnea, GERD and major depressive disorder, while diabetes and hypertension showed nonlinear risk reduction that plateaued around 8,000–9,000 steps per day.

Key findings

  • Among 6,042 participants (median age 56.7 years, 73% female, 84% white, 71% college degree), median daily steps were 7,731.3 (IQR 5,866.8–9,826.8) over a median 4.0 years (IQR 2.2–5.6), totaling 5.9 million person-days.
  • Incident disease risk was inverse and linear for obesity (n = 368), sleep apnea (n = 348), GERD (n = 432) and major depressive disorder (n = 467), with values above 8,200 daily steps associated with protection from incident disease.
  • Diabetes (n = 156) and hypertension (n = 482) had nonlinear relationships, with no further risk reduction above 8,000–9,000 steps.
  • Comparing the 75th versus 25th percentile of daily steps in Model 1, hazard ratios were 0.44 for diabetes, 0.71 for hypertension, 0.64 for GERD, 0.63 for MDD, 0.52 for obesity and 0.53 for sleep apnea. In a high-risk obesity analysis, increasing from the 25th to 75th step percentile reduced obesity risk by 36% (95% CI 20–49%) and lowered 5-year cumulative obesity incidence from 16% to 8%.

Methods

  • Used All of Us Research Program Registered Tier Dataset version 5 (R2021Q3R2), including adults ≥18 years who linked their own Fitbit device, had valid Fitbit data for at least 6 months, and shared EHR data; participants were enrolled from May 30, 2018 to April 1, 2021.
  • First conducted exploratory logistic regression across 1,711 phecodes, adjusted for age, sex and race, reporting odds ratios per 1,000-step increase; then focused on conditions meeting Bonferroni significance and plausible biological link to activity.
  • Used time-varying Cox proportional hazards models with monthly averaged steps, restricted cubic splines to assess linearity/nonlinearity, and adjustment for age, sex, race, CAD, cancer, BMI, systolic blood pressure, education, smoking and alcohol use; also examined step intensity via bout cadence and performed falsification analyses for carpal tunnel syndrome and actinic keratosis.

Limitations

  • The paper states that it could not account for daily step variations between Fitbit models, seasonal differences, or the COVID-19 pandemic because device data were unavailable and dates were shifted for privacy.
  • The sample was mostly young, female, white, college-educated and Fitbit-owning, and participants were more active than average US adults over 60, limiting generalizability; further studies in historically under-represented and more sedentary populations are needed.
  • The study was observational, so causation should not be inferred; reverse causation and unmeasured confounding are possible, though the authors focused on incident conditions and excluded diagnoses in the first 6 months.
  • The paper also notes that it did not capture nonstepping activity such as swimming or cycling, excluded 15.4–16.0% of months due to fewer than 15 valid days in Cox models, and relied on EHR diagnostic codes, which may lack specificity or be miscoded.
  • Evident from the text: BMI had substantial missingness among included participants (2,644, 43.8%), and missing covariate data were handled by multiple imputation.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1038/s41591-022-02012-w

Cites

36 of 36 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

35 of 41 cited sources checked · 15 supported · 2 flagged · accuracy not yet measured

  • Premisecitation

    Prior studies have focused on a relatively targeted set of outcomes limited to mortality, diabetes and cardiovascular disease.

    “Second, prior studies have focused on a relatively targeted set of outcomes limited to mortality, diabetes and cardiovascular disease.”
    Quote in the paperSubstantial claim6 of 6 sources checked
    • cites [1] Saint-Maurice, P. F. et al. Association of daily step count and step intensity with mortality among US adults. JAMA 323, 1151–1160 (2020). source

      The Discussion describes prior step-count studies focused on mortality, and the paper examines cardiovascular-disease mortality. But the paper does not identify diabetes as an outcome of those prior studies; its Statistical Analysis lists diabetes as a covariate. It therefore supports the mortality focus, not the full list of outcomes or the claim that prior studies were limited to them. (LLM, conf=0.82)

      Experimental — accuracy not yet measured
    • cites [2] Lee, I.-M. et al. Association of step volume and intensity with all-cause mortality in older women. JAMA Intern Med. 179, 1105–1112 (2019). source

      The Discussion and the passage following the dose-response figure (page not provided) describe prior step-count studies of mortality, diabetes, and cardiovascular events. But the latter also reports analyses of metabolic syndrome risk score and glucose, so the claim that outcomes were limited to the three named categories is too narrow. (LLM, conf=0.86)

      Experimental — accuracy not yet measured
    • cites [3] Piercy, K. L. et al. The physical activity guidelines for Americans. JAMA 320, 2020–2028 (2018). source

      The Discussion (page unavailable) says evidence has expanded beyond the primary prevention of chronic disease, supporting the general contrast with an earlier, narrower focus. It does not say prior studies were limited to mortality, diabetes, and cardiovascular disease. (LLM, conf=0.82)

      Experimental — accuracy not yet measured
    • cites [4] Tudor-Locke, C. et al. How many steps/day are enough? For older adults and special populations. Int J. Behav. Nutr. Phys. Act. 8, 79 (2011). source

      The Results section (“Steps/day associated with various health outcomes”; page unavailable) discusses prior studies of depression, BMI, body composition and obesity. Those outcomes fall outside mortality, diabetes and cardiovascular disease, contrary to the claim that prior studies were limited to those three. (LLM, conf=0.88)

      Checked by a reasoning model — may be wrong.

      Experimental — accuracy not yet measured
    • cites [5] Paluch, A. E. et al. Steps per day and all-cause mortality in middle-aged adults in the coronary artery risk development in young adults study. JAMA Netw. Open 4, e2124516–e2124516 (2021). source

      The Methods (Primary Outcome: All-Cause Mortality; page unavailable) establish that this study examined mortality. The Methods (Covariates; page unavailable) treat diabetes and cardiovascular disease as covariates, not outcomes. The paper therefore supports mortality as one focus of prior research but does not establish that prior studies’ outcomes were limited to mortality, diabetes, and cardiovascular disease. (LLM, conf=0.84)

      Experimental — accuracy not yet measured
    • cites [6] Bassett, D. R. Jr., Toth, L. P., LaMunion, S. R. & Crouter, S. E. Step counting: a review of measurement considerations and health-related applications. Sports Med. 47, 1303–1315 (2017). source

      The review’s Steps/Day and Health > Longitudinal Intervention Studies section reports prior step-counting studies that measured weight change, including a meta-analysis of nine studies. Weight change falls outside the claimed list, so the paper does not support describing prior outcomes as limited to mortality, diabetes, and cardiovascular disease. Page numbers were not available in our copy. (LLM, conf=0.85)

      Checked by a reasoning model — may be wrong.

      Experimental — accuracy not yet measured
  • Premisecitation

    Prior studies consistently show that taking fewer steps per day is associated with higher risk of all-cause mortality and cardiovascular disease.

    “Prior studies consistently show that taking fewer steps per day1–6 is associated with higher risk of all-cause mortality and cardiovascular disease.”
    Quote in the paperSubstantial claim6 of 6 sources checked
    • cites [1] Saint-Maurice, P. F. et al. Association of daily step count and step intensity with mortality among US adults. JAMA 323, 1151–1160 (2020). source

      The Discussion reports that greater daily step counts were associated with lower all-cause and cardiovascular disease (CVD) mortality in US adults aged 40 or older. The Cardiovascular Disease and Cancer Mortality section likewise reports lower CVD mortality at 8000 versus 4000 steps per day. The paper measures deaths from CVD, not the risk of developing cardiovascular disease, so it does not support that part of the claim as written. (LLM, conf=0.86)

      Experimental — accuracy not yet measured
    • cites [2] Lee, I.-M. et al. Association of step volume and intensity with all-cause mortality in older women. JAMA Intern Med. 179, 1105–1112 (2019). source
    • cites [3] Piercy, K. L. et al. The physical activity guidelines for Americans. JAMA 320, 2020–2028 (2018). source

      The Discussion (page unavailable) links sitting time and moderate-to-vigorous physical activity with all-cause and cardiovascular disease mortality. It does not establish the claim’s specific association between fewer steps per day and higher risk, or say that prior step-count studies consistently found it. (LLM, conf=0.83)

      Experimental — accuracy not yet measured
    • cites [4] Tudor-Locke, C. et al. How many steps/day are enough? For older adults and special populations. Int J. Behav. Nutr. Phys. Act. 8, 79 (2011). source

      The Results section (‘Steps/day associated with various health outcomes’; page unavailable) reports more adverse cardiometabolic risk factors among adults taking fewer than 5,000 steps/day. That supports an association with risk factors, but not the claimed higher risk of all-cause mortality or cardiovascular disease. The mortality reference listed in the paper concerns sitting time, not daily steps. (LLM, conf=0.84)

      Experimental — accuracy not yet measured
    • cites [5] Paluch, A. E. et al. Steps per day and all-cause mortality in middle-aged adults in the coronary artery risk development in young adults study. JAMA Netw. Open 4, e2124516–e2124516 (2021). source

      The Discussion reports that fewer daily steps were associated with higher all-cause mortality and says this agrees with previous studies. The paper does not establish the claimed association between daily step count and cardiovascular disease risk: the Introduction discusses physical activity broadly, while the Limitations section notes only that the lowest-step group had the highest baseline rates of cardiovascular disease. Page numbers are unavailable in our copy. (LLM, conf=0.87)

      Experimental — accuracy not yet measured
    • cites [6] Bassett, D. R. Jr., Toth, L. P., LaMunion, S. R. & Crouter, S. E. Step counting: a review of measurement considerations and health-related applications. Sports Med. 47, 1303–1315 (2017). source

      The Cross-Sectional Studies section reports that fewer daily steps are associated with less favorable cardiometabolic risk factors, including hypertension. It does not report an association with all-cause mortality or cardiovascular disease outcomes; the Prospective Observational Studies section lists studies examining disease endpoints but gives no such results. No page numbers are available in our copy. (LLM, conf=0.82)

      Experimental — accuracy not yet measured
  • Premisecitation

    Prior studies report no information about activity levels between the baseline period and when outcomes are assessed at follow-up, often many years later.

    “Moreover, no information is reported about activity levels between the baseline period and when outcomes are assessed at follow-up, often many years later.”
    Quote in the paperSubstantial claim4 of 4 sources checked
    • cites [1] Saint-Maurice, P. F. et al. Association of daily step count and step intensity with mortality among US adults. JAMA 323, 1151–1160 (2020). source
    • cites [2] Lee, I.-M. et al. Association of step volume and intensity with all-cause mortality in older women. JAMA Intern Med. 179, 1105–1112 (2019). source

      The Limitations section says this study used a single assessment of steps, supporting the concern that activity was not routinely measured throughout follow-up. But it also reports repeated assessments in a subgroup over 2–3 years, and the discussion describes another study measuring steps at baseline and 12 months. The blanket claim that prior studies report no intervening activity information is therefore too broad. (LLM, conf=0.82)

      Experimental — accuracy not yet measured
    • cites [3] Piercy, K. L. et al. The physical activity guidelines for Americans. JAMA 320, 2020–2028 (2018). source

      The Key Guidelines discuss health benefits that accrue over months or years, but do not describe how prior studies measured activity between baseline and follow-up. Searches for baseline, follow-up, and longitudinal study limitations found no passage addressing the claimed gap in activity data. (LLM, conf=0.73)

      Experimental — accuracy not yet measured
    • cites [4] Tudor-Locke, C. et al. How many steps/day are enough? For older adults and special populations. Int J. Behav. Nutr. Phys. Act. 8, 79 (2011). source

      The Results sections on normative data and interventions discuss step counts and activity goals, but do not say whether prior studies measured activity between baseline and follow-up. Searches for baseline, follow-up, and longitudinal activity measurements found no passage addressing that claimed reporting gap. (LLM, conf=0.72)

      Experimental — accuracy not yet measured
  • Premisecitation

    Prior studies assessed physical activity either by self-reported questionnaires or by having participants wear a research-grade device for a brief monitoring period, most often 7 days.

    “First, prior studies assessed physical activity either by self-reported questionnaires or by having participants wear a research-grade device for a brief monitoring period (most often 7 days)1–4.”
    Quote in the paperSubstantial claim4 of 4 sources checked
    • cites [1] Saint-Maurice, P. F. et al. Association of daily step count and step intensity with mortality among US adults. JAMA 323, 1151–1160 (2020). source
    • cites [2] Lee, I.-M. et al. Association of step volume and intensity with all-cause mortality in older women. JAMA Intern Med. 179, 1105–1112 (2019). source
    • cites [3] Piercy, K. L. et al. The physical activity guidelines for Americans. JAMA 320, 2020–2028 (2018). source

      The References mention a self-reported physical-activity questionnaire, and Promoting Physical Activity discusses wearable devices as tools for feedback. Neither passage describes how prior studies measured activity or says that research-grade devices were typically worn for 7 days (searched: questionnaires, accelerometers, and 7 days). (LLM, conf=0.73)

      Experimental — accuracy not yet measured
    • cites [4] Tudor-Locke, C. et al. How many steps/day are enough? For older adults and special populations. Int J. Behav. Nutr. Phys. Act. 8, 79 (2011). source
  • Premisecitation

    The rich EHR data within All of Us can be used to identify the incidence of chronic conditions across the human phenome.

    “The rich EHR data within AoURP can be used to identify the incidence of chronic conditions across the human phenome9.”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [9] Pendergrass, S. A. & Crawford, D. C. Using electronic health records to generate phenotypes for research. Curr. Protoc. Hum. Genet. 100, e80–e80 (2019). source

      The Commentary’s “Phenotype Algorithm Development” section describes using EHR data to classify disease status across a data warehouse, including phenome-wide studies. It does not establish that All of Us EHR data can identify the incidence of chronic conditions; identifying case status is not the same as measuring new cases over time. No page number was provided for these passages. (LLM, conf=0.84)

      Experimental — accuracy not yet measured
  • Classified as probably not a substantial claim. 36
  • May combine two claims. 25
  • The quote only partly states this claim. 1

  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    The All of Us Research Program is accumulating multiple streams of health-related information in 1,000,000 or more Americans and includes a focus on populations usually under-represented in biomedical research.

    “The All of Us Research Program (AoURP) is an initiative that is accumulating multiple streams of health-related information (for example, electronic health records (EHRs), genomics, physical measures, participant surveys and wearables such as Fitbit) in 1,000,000 or more Americans and includes a focus on populations usually under-represented in biomedical research to date8.”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [8] Investigators AoURP. The ‘All of Us’ research program. N. Engl. J. Med. 381, 668–676 (2019). source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationcitation

    Our findings are consistent with previous literature describing associations between step counts and adverse events.

    “Our findings are consistent with previous literature describing associations between step counts and adverse events10,11.”
    Quote in the paperNot a substantial claim2 of 2 sources checked
    • cites [10] Hall, K. S. et al. Systematic review of the prospective association of daily step counts with risk of mortality, cardiovascular disease, and dysglycemia. Int J. Behav. Nutr. Phys. Act. 17, 78 (2020). source
    • cites [11] Paluch, A. E. et al. Daily steps and all-cause mortality: a meta-analysis of 15 international cohorts. Lancet Public Health 7, e219–e228 (2022). source

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    A systematic review by Hall et al. found that taking more steps per day was related to lower risk of all-cause mortality, cardiovascular events and incident diabetes.

    “A systematic review by Hall et al.10 found that taking more steps per day was related to lower risk of all-cause mortality, cardiovascular events and incident diabetes.”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [10] Hall, K. S. et al. Systematic review of the prospective association of daily step counts with risk of mortality, cardiovascular disease, and dysglycemia. Int J. Behav. Nutr. Phys. Act. 17, 78 (2020). source

      The Discussion (page not provided) reports that more daily steps were associated with lower all-cause mortality and CVD morbidity or mortality. It says the evidence for incident diabetes was limited and the review could not definitively characterize that association, although some large cohorts suggested a benefit. (LLM, conf=0.90)

      Experimental — accuracy not yet measured

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    The National Health and Nutrition Examination Survey study found a 51% lower mortality at 8,000 steps per day compared with 4,000 steps per day.

    “The National Health and Nutrition Examination Survey study, which quantified steps over a 7-day monitoring period and assessed mortality over an average of 10.1 years, found a 51% lower mortality at 8,000 steps per day compared with 4,000 steps per day1.”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [1] Saint-Maurice, P. F. et al. Association of daily step count and step intensity with mortality among US adults. JAMA 323, 1151–1160 (2020). source

  • May combine two claims.

    Study design and conductreasoning

    The study was unable to account for daily step variations between different types of Fitbit models, seasonal differences, and the COVID-19 pandemic because device data were not available at the time of analyses and data were date-shifted to protect participant privacy.

    “We were not able to account for daily step variations between different types of Fitbit models14 and seasonal differences15 as well as the occurrence of the COVID-19 pandemic because device data were not available at the time of analyses and data were date-shifted to protect privacy of participants.”
    Quote in the paperNot a substantial claim2 of 2 sources checked
    • cites [14] Fuller, D. et al. Reliability and validity of commercially available wearable devices for measuring steps, energy expenditure, and heart rate: systematic review. JMIR Mhealth Uhealth 8, e18694 (2020). source
    • cites [15] Garriga, A., Sempere-Rubio, N., Molina-Prados, M. J. & Faubel, R. Impact of seasonality on physical activity: a systematic review. Int J. Environ. Res Public Health 19, 2 (2021). source

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    Self-reported physical activity or exercise interventions may have potential beneficial effects to lower the incidence of depression and lower the severity of obstructive sleep apnea and associated comorbidities.

    “Finally, self-reported physical activity or exercise interventions may have potential beneficial effects to lower the incidence of depression20 and lower the severity of obstructive sleep apnea and associated comorbidities21.”
    Quote in the paperNot a substantial claim2 of 2 sources checked
    • cites [20] Schuch, F. B. et al. Physical activity and incident depression: a meta-analysis of prospective cohort studies. Am. J. Psychiatry 175, 631–648 (2018). source

      The Abstract and Conclusions report that higher physical activity is associated with lower odds of incident depression, supporting the depression portion attributed to this source. But the paper analyzes prospective cohorts, not exercise interventions; its Conclusions say randomized trials are needed to determine whether increasing physical activity prevents depression. The sleep-apnea portion is attached to a different citation and is not assessed here. (LLM, conf=0.86)

      Experimental — accuracy not yet measured
    • cites [21] Mendelson, M. et al. Obstructive sleep apnea syndrome, objectively measured physical activity and exercise training interventions: a systematic review and meta-analysis. Front Neurol. 9, 73 (2018). source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductcitation

    All missing data for covariates were imputed using multiple imputation with predictive mean matching.

    “All missing data for covariates were imputed using multiple imputation with predictive mean matching32.”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [32] Morris, T. P., White, I. R. & Royston, P. Tuning multiple imputation by predictive mean matching and local residual draws. BMC Med. Res. Methodol. 14, 75 (2014). source

  • May combine two claims.

    Findingown data

    The relationship between steps per day and incident disease was inverse and linear for obesity, sleep apnea, gastroesophageal reflux disease and major depressive disorder, with values above 8,200 daily steps associated with protection from incident disease.

    “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.”
    • Also stated in: § Time-varying analysis of daily step counts and disease risk · plain
      “The relationship between steps and incident disease was inverse (all P < 0.001) and linear for obesity, sleep apnea, GERD and MDD (chunk tests for nonlinearity were nonsignificant for those conditions) with a lower risk of each diagnosis at higher step counts.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    The analytical cohort was predominantly female (73%), white (84%) and college-educated (71%).

    “Of the 6,042 participants included in the study, 73% were female, 84% were white and 71% had a college degree”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The analytical cohort included 6,042 participants with a median age of 56.7 years and median BMI of 28.1 kg/m2 at baseline.

    “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.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The relationships between steps per day and incident diabetes and hypertension were nonlinear, with no further risk reduction above 8,000-9,000 steps.

    “The relationships with incident diabetes (n = 156) and hypertension (n = 482) were nonlinear with no further risk reduction above 8,000–9,000 steps.”
    • Also stated in: § Time-varying analysis of daily step counts and disease risk · boosted
      “In contrast, incident diabetes and hypertension had a nonlinear relationship (chunk tests for nonlinearity P < 0.05 for both) with step counts demonstrating inflections points at approximately 9,000 and 8,000 steps, respectively, where risk plateaued at higher step counts.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Participants walked a median of 7,731.3 steps per day over a median activity monitoring period of 4.0 years, totaling 5.9 million person-days.

    “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.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Incident risk for all years is higher at lower step counts and increases over time when a given step count is maintained.

    “In general, incident risk for all the years is higher at lower step counts and increases over time when a given step count is maintained.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    In a phenome-wide logistic regression adjusted for age, sex and race, higher average daily step counts (per 1,000 steps) were associated with lower odds of obstructive sleep apnea, obesity, type 2 diabetes with neurological manifestations, hypertension, GERD and MDD.

    “Incident chronic conditions with the largest effect sizes that met the adjusted statistical significance threshold across the human phenome after a minimum of 6 months of monitoring were obstructive sleep apnea (n/N = 342/5,518, OR (95% confidence intervals (CI)) = 0.88 (0.84, 0.92)), obesity (n/N = 380/5,267, OR (95% CI) = 0.89 (0.86, 0.93))”
    • Also stated in: § Daily steps and chronic diseases across human phenome · plain
      “type 2 diabetes with neurological manifestations (n/N = 37/5,976, OR (95% CI) = 0.69 (0.60, 0.79)), hypertension (n/N = 498/4,897, OR (95% CI) = 0.92 (0.89, 0.95)), gastroesophageal reflux disease (GERD) (n/N = 451/5,091, OR (95% CI)= 0.92 (0.89, 0.95)) and major depressive disorder (MDD) (n/N = 483/5,370, OR (95% CI) = 0.92 (0.89, 0.95))”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    Of the 329,070 All of Us participants at the time of analysis, 214,206 had consented to share EHR data.

    “Of the 329,070 AoURP participants at the time of our analysis, 214,206 participants had consented to share EHR data.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    Median daily average steps ranged from 8,160 to 8,290 steps per day across the different analytical cohorts.

    “The median values ranged from 8,160 to 8,290 steps per day across the different analytical cohorts created to investigate each incident diagnosis.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Participants with Fitbit and EHR data were more likely to be white, female and to have a lower burden of medical comorbidities compared with those sharing EHR data alone.

    “Participants with Fitbit and EHR data were more likely to be white, female and to have a lower burden of medical comorbidities compared with those sharing EHR data alone (Table 1).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Of those sharing EHR data, 6,042 participants linked their own Fitbit device, had valid Fitbit data over at least 6 months of total monitoring and were aged at least 18 years at any time during the monitoring period.

    “Of those sharing EHR data, 6,042 participants linked their own Fitbit device, had valid Fitbit data over at least 6 months of total monitoring and were aged at least 18 years at any time during the monitoring period (Extended Data Fig. 1).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    In the All of Us Research Program cohort, higher daily step counts were associated with reduced risk of several common chronic diseases, including diabetes, hypertension, GERD, MDD, obesity, and sleep apnea.

    “In summary, using the data from AoURP, higher daily step counts were associated with reduced risk of several common, chronic diseases, including diabetes, hypertension, GERD, MDD, obesity and sleep apnea.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    When defined using a moderate to vigorous intensity, bout cadence remained significantly associated with obesity, sleep apnea and GERD (all chunk tests P < 0.05).

    “When defined using a moderate to vigorous intensity, bout cadence remained significantly associated with obesity, sleep apnea and GERD (all chunk tests P < 0.05; Supplementary Table 5).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingnone given

    The majority of the cohort was relatively young, female, white, and college-educated, and only included participants who owned Fitbit devices.

    “The majority of our cohort was relatively young, female, white and college-educated, and only included participants who owned Fitbit devices.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Step intensity was significantly associated with incident diabetes, hypertension, GERD, MDD, obesity, and sleep apnea, although the relationships were less consistent than with step counts.

    “Step intensity was also significantly associated with these incident diseases, although the relationships were less consistent than with step counts.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

    Interpretationown data

    Although validation in a more diverse sample is needed, the findings provide a real-world evidence-base for clinical guidance regarding activity levels necessary to reduce disease risk.

    “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.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: The observed associations between step counts and disease risk are not substantially due to unmeasured confounding.

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning

    The All of Us dataset provides a unique opportunity to directly examine the effects of physical activity over time on health outcomes using wearables and clinical data.

    “Thus, the AoURP dataset provides a unique opportunity to directly examine the effects of physical activity over time on health outcomes using wearables and clinical data.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    Only 0.02% and 0.44% of total days were excluded because they had fewer than 100 steps and less than 6 months of monitoring, respectively.

    “Only 0.02% and 0.44% of total days were excluded given they had fewer than 100 steps and <6 months of monitoring, respectively.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    The analysis of obesity as a function of baseline BMI, daily step counts and BMI*steps interaction was designed to address potential concerns regarding incidence estimates confounded by conditions that were prevalent but undiagnosed at baseline.

    “This analysis was designed to address potential concerns regarding incidence estimates confounded by conditions that were prevalent but undiagnosed at baseline.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    In Cox models, 15.4-16.0% of months (4.7-4.9% of days) were excluded due to fewer than 15 valid days of data.

    “In the Cox models, 15.4–16.0% of months (that is, 4.7–4.9% of days) were excluded due to fewer than 15 valid days of data.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    Short monitoring periods are prone to an observer effect and may not accurately reflect true short- and long-term activity behavior.

    “Short monitoring periods are prone to an observer effect and may not accurately reflect true short- and long-term activity behavior13.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [13] Clemes, S. A., Matchett, N. & Wane, S. L. Reactivity: an issue for short-term pedometer studies? Br. J. Sports Med. 42, 68–70 (2008). source

  • Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

    Interpretationown data

    These data provide new, empiric evidence of activity levels associated with chronic disease risk and suggest that integration of commercial wearables data into the EHR may be valuable to support clinical care.

    “These data provide new, empiric evidence of activity levels associated with chronic disease risk and suggest that integration of commercial wearables data into the EHR may be valuable to support clinical care.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: The observed associations between step counts and disease risk are not substantially due to unmeasured confounding.

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    The findings from exploratory logistic regression that did not find an association between steps per day and cardiovascular diseases should be viewed with caution because the analytical sample was relatively young, reported fewer outcomes, and had limited follow-up.

    “Additionally, findings from exploratory logistic regression that did not find an association between steps per day and other outcomes such as cardiovascular diseases should be viewed with caution given that the analytical sample was relatively young, reported fewer outcomes and had limited follow-up.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

    Interpretationreasoning

    The sources of data for the study are unique and offer an example of the potential clinical value of linking wearables data to the EHR.

    “Despite these limitations, the sources of data for our study are unique and offer an example of the potential clinical value of linking wearables data to the EHR.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductnone given

    It is possible that conditions are coded improperly, not coded at all, or not recognized in the clinic.

    “It is possible that conditions are coded improperly, not coded at all or not recognized in the clinic.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationown data

    Such data provide a necessary first step toward the development of personalized activity prescriptions.

    “Although validation of these results is important, such data provide a necessary first step toward the development of personalized activity prescriptions.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Interpretationreasoning

    Causation should not be inferred from this study.

    “Further, this study was observational in nature; therefore, causation should not be inferred.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    This study was observational in nature.

    “Further, this study was observational in nature; therefore, causation should not be inferred.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationnone given

    Data from commercially available devices are highly generalizable to a large portion of the public who own such devices.

    “Although some fidelity is lost between research-grade and commercial devices, data from the latter are highly generalizable to a large portion of the public who own such devices.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationown data

    These results provide support for the need for further research to examine the effect of real-world, unstructured physical activity to prevent or mitigate the effects of such conditions, including some previously unidentified activity-disease associations (for example, GERD).

    “Therefore, these results provide support for the need for further research to examine the effect of real-world, unstructured physical activity to prevent or mitigate the effects of such conditions, including some previously unidentified activity-disease associations (for example, GERD).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    There is a potential for reverse causation in which the existence of a condition leads to taking fewer steps rather than the reverse.

    “We acknowledge the potential for reverse causation in which the existence of a condition leads to taking fewer steps rather than the reverse.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    The study excluded 15.4-16.0% of months (varies by outcome) due to fewer than 15 valid days of data in the Cox models.

    “We excluded 15.4–16.0% (varies based on the outcome) of months due to fewer than 15 valid days of data in the Cox models.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationnone given

    The results reflect use of diagnostic codes in clinical practice across various medical systems, including large regional medical centers and federally qualified health centers.

    “Nonetheless, our results reflect use of diagnostic codes in clinical practice across various medical systems, including large regional medical centers and federally qualified health centers.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductnone given

    The study acknowledges limitations of using EHR data for outcomes ascertainment and the potential lack of specificity of diagnostic codes.

    “Lastly, we also acknowledge the limitations of using EHR data for outcomes ascertainment and the potential lack of specificity of diagnostic codes.”
    Quote in the paperNot a substantial claim

  • The quote only partly states this claim.

    Interpretationown data

    The analytical cohort in this study was more active than the general population.

    “Further, participants engaged in more steps per day (median 7,731 steps per day) than the average steps per day values reported for adults in the USA aged over 60 years16, suggesting that the analytical cohort in this study was more active.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductcitation

    This missingness seems acceptable in comparison with prior studies which considered data valid if activity was captured on at least 3 out of 7 days (up to 57% missing data).

    “This missingness seems acceptable in comparison with prior studies which considered data to be valid if activity was captured on at least 3 out of 7 days (that is, up to 57% missing data)18.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [18] Tudor-Locke, C. et al. How many days of pedometer monitoring predict weekly physical activity in adults? Prev. Med. 40, 293–298 (2005). source

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    The study attempted to mitigate reverse causation by focusing only on incident conditions and excluding any incident disease that emerged in the first 6 months of the monitoring period.

    “We attempted to mitigate this concern by focusing only on incident conditions and excluding any incident disease that emerged in the first 6 months of the monitoring period.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationown data

    These findings provide a new, robust source of evidence in support of the physical activity guidelines to prevent the risk of developing chronic diseases.

    “These findings provide a new, robust source of evidence in support of the physical activity guidelines to prevent the risk of developing chronic diseases.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    This study provides an example of the potential clinical value of linking data from commercially available wearables to the EHR.

    “This study also provides an example of the potential clinical value of linking data from commercially available wearables to the EHR.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    This study provides important new evidence that integration of these data sources is feasible and may provide valuable and actionable information for clinicians.

    “Therefore, this study provides important new evidence that integration of these data sources is feasible and may provide valuable and actionable information for clinicians.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

    Interpretationreasoning

    The ability to detect robust associations between steps and incident disease in this active sample suggests even stronger associations may exist in a more sedentary population.

    “The fact that we were able to detect robust associations between steps and incident disease in this active sample suggests even stronger associations may exist in a more sedentary population.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    The study excluded any new diagnoses coded during the first 6 months of monitoring.

    “We excluded any new diagnoses coded during the first 6 months of monitoring, assuming that such conditions were likely prevalent but not yet recognized clinically.”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: New diagnoses coded during the first 6 months of monitoring were likely prevalent but not yet recognized clinically.

  • Classified as probably not a substantial claim.

    Study design and conductown data

    All Cox models were adjusted for a priori covariates: age, sex, race, coronary artery disease, cancer, BMI, systolic blood pressure, education level, smoking, and alcohol use.

    “All Cox models were adjusted for a priori covariates: age, sex (male, female), race (Black or African American, white, other), coronary artery disease (CAD) (yes, no), cancer (yes, no), BMI, systolic blood pressure, education level (no college, some college, college degree), all time smoking (<100 cigarettes, ≥100 cigarettes) and alcohol use (alcohol participant, not an alcohol participant).”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    The study accounted for baseline daily steps averaged over the first 3 and 6 months in separate Cox models in addition to a priori covariates to mitigate potential reverse causation.

    “We then accounted for baseline daily steps averaged over the first 3 and 6 months, in separate Cox models in addition to a priori covariates, in an attempt to mitigate the potential for reverse causation.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    The study ran a separate Cox model accounting for wear time as a time-varying covariate.

    “In addition to accounting for a priori covariates, we ran a separate Cox model accounting for wear time, which was considered to be a time-varying covariate.”
    Quote in the paperNot a substantial claim
52 of 52

  • The paper relies on this without support.

    Step counts captured by participants' own Fitbit devices accurately reflect physical activity levels.

    “step count volumes as captured by participants’ own Fitbit devices”
    “Physical activity can be quantified and tracked by wearables that are used widely by the public.”

  • The paper relies on this without support.

    The observed associations between step counts and disease risk are not substantially due to unmeasured confounding.

    “These data provide new, empiric evidence of activity levels associated with chronic disease risk and suggest that integration of commercial wearables data into the EHR may be valuable to support clinical care.”

  • The paper relies on this without support.

    Nonstepping movement is better captured via waveform or raw accelerometry.

    “such nonstepping movement is better captured via waveform or raw accelerometry”

  • The paper relies on this without support.

    Fitbit devices have reduced fidelity compared with research-grade actigraphs.

    “We acknowledge that Fitbit devices have reduced fidelity compared with research-grade actigraphs”

  • The authors state this as an assumption.

    New diagnoses coded during the first 6 months of monitoring were likely prevalent but not yet recognized clinically.

    “assuming that such conditions were likely prevalent but not yet recognized clinically”

  • The paper relies on this without support.

    Published activity studies almost exclusively used research-grade actigraphs to measure steps and/or activity counts.

    “Published activity studies almost exclusively used research-grade actigraphs to measure steps and/or activity counts.”
6 of 6

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Conflicting obesity risk reductions for the same step-count comparison

    Major

    For a person starting at BMI 28, the Results say increasing steps from the 25th to the 75th percentile reduces obesity risk by 36%, whereas the Discussion gives a 64% reduction for approximately the same increase (6,000 to 11,000 steps). The reported confidence intervals also differ.

  • Figure 1 calls post-monitoring diagnoses prevalent

    Minor

    The figure caption describes prevalent disease, but the same caption states that all plotted phecodes occurred after six months of monitoring and not before.

  • Conflicting descriptions of activity data in prior studies

    Minor

    The Main section says prior studies reported no activity information between baseline and follow-up, while the Discussion says those studies had activity data during that interval.

3 of 3

Cites

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Cited by

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Related

Authors
Master, H., Annis, J., Huang, S., Beckman, J. A., Ratsimbazafy, F., Marginean, K., Carroll, R., Natarajan, K., Harrell, F. E., Roden, D. M., Harris, P., & Brittain, E. L.
Affiliations
  • Vanderbilt University (US)
  • Vanderbilt University Medical Center (US)
  • Columbia University (US)
Corresponding author
Brittain, Evan L.
ORCID
Venue
Nature Medicine
Publisher
Springer Science and Business Media LLC
Published
2022-10-10
Volume
28
Issue
11
Pages
2301-2308
ISSN
  • 1078-8956 (ISSN-L)
  • 1546-170X
DOI
10.1038/s41591-022-02012-w
PMC
PMC9671804
OpenAlex
W4304080209
Semantic Scholar
ab705b91765484562d3f4d2d1fffb0e9e7bbecdd
Cited by
221
References
36
Citations by year
2026: 58 · 2025: 68 · 2024: 56 · 2023: 36 · 2022: 3
FWCI
20.99
Type
journal article
Language
en
Update notices
correction (2023-04-12)
Open access
Licence
Locations
  • Nature Medicine (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (submittedVersion, cc-by)
Funders
  • National Institutes of Health (AOD 16037, 1z01od022003-10, HHSN263201600085U, AOD21041, 5U2COD0231 96, 1r61hl158941-01a1, IAA: AOD21037, 263201600085U, OT2 OD026554, OT2 OD025315, OT2OD025276, 1 OT2OD026550, U2C OD023196, OT2 OD025337, U24OD023176, 1 OT2 OD026555, OT2OD026553, OT2 OD026551, 3OT2 OD023205, OT2OD026557, 1 OT2 OD026548, 1 U24 OD023121, OT2 OD023205, OT2 OD026552, 1 U24 OD023163, U24OD023163, OT2OD026555, 3OT2 OD025315, 1 OT2 OD026556, OT2 OD026548, U24 OD023121, 1 OT2OD026557, 1OT2 OD026551, 1 OT2 OD025277, OT2 OD026556, 1 OT2 OD026549, 1 OT2 OD025276, 1 OT2 OD026554, 1 OT2 OD025337, 1 OT2 OD026553, 3 OT2 OD023206, OD 026553, OT2 OD026549, 1 OT2OD026552, OT2 OD023206, OT2 OD026550, OT2OD025277)
  • National Heart, Lung, and Blood Institute (R01 HL 146588, R61 HL158941)
Topics
  • Health Sciences › Medicine › Physiology › Physical Activity and Health
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
Keywords
step count, physical activity, chronic disease risk, Fitbit, wearable activity trackers, obesity, sleep apnea, gastroesophageal reflux disease, major depressive disorder, diabetes mellitus, hypertension, electronic health records, All of Us, disease prevention
MeSH terms
Fitness Trackers, Population Health, Adult, Aged, Chronic Disease, Depressive Disorder, Major, Major Depressive Disorder, Female, Humans, Male, Middle Aged, Walking

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-09.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-09.

Cited sources are checked by gpt-6-sol.

Statistics and arithmetic are recomputed, not judged.

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