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

. 2022 Nov;28(11):2301-2308.

doi: 10.1038/s41591-022-02012-w. Epub 2022 Oct 10.

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

Hiral Master et al. Nat Med. 2022 Nov.

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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.

© 2022. The Author(s).

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Conflict of interest statement

The authors declare no competing interests. The sponsor, All of Us Research Program, as well as Fitbit, had no involvement in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Figures

Fig. 1
Fig. 1. Hypothesis-generating analysis to explore relation between daily steps and prevalent chronic disease across human phenome.

a, Negative log base-10 P values for each phecode are plotted as a function of the OR from the corresponding logistic regression with average daily step count. EF, ejection fraction; NOS, not otherwise specified. OR is reported per 1,000 step count increase, as adjusted for age, race and sex. All phecodes occurred after 6 months of Fitbit monitoring and not before. Horizontal red line indicates the Bonferroni corrected α level of 3.1856 × 10–5, accounting for all phecodes used. Vertical line is OR = 1. b, OR and 95% CI to quantify the association of increasing daily step counts with selected outcomes, that is type 2 diabetes mellitus (T2DM) with (w/) neurological manifestation (manif.) (sample size, N = 5,976), sleep apnea (N = 5,699), obstructive sleep apnea (N = 5,518), obesity (N = 5,267), major depressive disorder (N = 5,370), GERD (N = 5,091) and essential hypertension (N = 4,897). The points represent OR and error bars represent 95% CI. The values toward the right of the figure represent OR (95% CI) values in text format. All models were adjusted for age, race and sex.

Fig. 2
Fig. 2. Relation between daily steps over time and incident chronic disease.

a, Cox models were used to compute HRs as a function of average daily step count. Median step counts of 8,160 (diabetes), 8,290 (essential hypertension), 8,260 (GERD), 8,210 (major depressive disorder), 8,280 (obesity) and 8,220 (sleep apnea) were used as reference. b, Cumulative incidence by year for each outcome as a function of average daily step count. Shaded area represents 95% CI. All the Cox models were adjusted for age, race, sex, CAD, cancer, BMI, systolic blood pressure, education level, smoking and alcohol use.

Fig. 3
Fig. 3. Relation between daily step counts and incident risk of obesity.

a, Cox models were used to compute HR for obesity (outcome) as a function of average daily step count as stratified by BMI of 25–29 kg m–2. A median step count of 8,594 steps was used as reference. b, Cumulative incidence by year as a function of average daily step count and as stratified by BMI of 25–29 kg m–2. The model is identical to models previously described except BMI was allowed to interact linearly with the average daily step count.

Extended Data Fig. 1
Extended Data Fig. 1. Consort diagram showing inclusion/exclusion criteria.

The flow diagram graphically depicts the steps that were utilized to derive the analytical sample that met the inclusion and exclusion criteria. EHR, electronic health records.

Extended Data Fig. 2
Extended Data Fig. 2. Frequency of multiple conditions by number.

The bar chart depicts number of participants who reported having multimorbidity among 6 conditions, i.e. diabetes, hypertension, gastroesophageal reflux disease, major depressive disorder, obesity and sleep apnea.

Extended Data Fig. 3
Extended Data Fig. 3. Relation between daily steps counts and incident risk of chronic diseases.

Relation between daily steps counts and incident risk of chronic diseases. a: Adjusted Hazard ratio on log-transformed scale as a function average daily steps for each select outcome. b: Log relative hazard as a function of average steps for each selected outcome. All the models were adjusted for age, race, sex, coronary artery disease, cancer, body mass index, systolic blood pressure, education level, smoking, and alcohol use. Shaded area represents 95%confidence interval.

Extended Data Fig. 4
Extended Data Fig. 4. Trajectory of average daily step counts (mean and 95% confidence interval) among participants who did (status = True) and did not (status = False) develop each of the conditions, that is, diabetes (Sample Size (N) = 5124), essential hypertension (N = 4437), GERD (N = 4613), major depressive disorders (N = 4884), obesity (N = 4774) and sleep apnea (N = 4922) that were examined in Cox Models.

Trajectory of average daily step counts (mean and 95% confidence interval) among participants who did (status = True) and did not (status = False) develop each of the conditions, that is, diabetes (Sample Size (N) = 5124), essential hypertension (N = 4437), GERD (N = 4613), major depressive disorders (N = 4884), obesity (N = 4774) and sleep apnea (N = 4922) that were examined in Cox Models. Indentation (>) represents the break in y-axis.

Extended Data Fig. 5
Extended Data Fig. 5. Relation between daily step counts and incident risk of actinic keratosis and carpal tunnel syndrome.

Relation between daily step counts and incident risk of actinic keratosis and carpal tunnel syndrome. a: Adjusted Hazard ratios as a function of average daily step count. All the models were adjusted for age, race, sex, coronary artery disease, cancer, body mass index, systolic blood pressure, education level, smoking, and alcohol use. Reference for steps was the median steps count at 8,064 steps. b: Cumulative incidence by year as a function of average daily step count for each selected outcome. Shaded area represents 95%confidence interval.

Extended Data Fig. 6
Extended Data Fig. 6. Incidence rates (number of events shown in brackets) for each diagnosis as a function of step counts and bout cadence (step intensity) quartiles.

Incidence rates (number of events shown in brackets) for each diagnosis as a function of step counts and bout cadence (step intensity) quartiles. Incidence rates is number of cases per 1000 people for each diagnosis as a function of step and bout cadence quartiles. Bout cadence referred to steps per minute computed by averaging the steps over the time when participant engaged in ≥2 consecutive minutes at ≥60 steps/minute across all the valid days. Step quartile intervals (thous.) are as follows: 1: [549,5.87]; 2: [5.87,7.73]; 3: [7.73,9.83]; 4: [9.83,33.6]. Bout cadence quartiles are as follows: 1: [68.1,83.6]; 2: [83.6,88.7]; 3: [88.7,94.3]; 4: [94.3,158].

Extended Data Fig. 7
Extended Data Fig. 7. Probability density plot examining the relation between step counts and bout cadence (step intensity) on continuous spectrum in participants who developed (represented as TRUE) vs. did not develop the condition (represented as FALSE).

Probability density plot examining the relation between step counts and bout cadence (step intensity) on continuous spectrum in participants who developed (represented as TRUE) vs. did not develop the condition (represented as FALSE). Bout cadence referred to steps per minute computed by averaging the steps over the time when participant engaged in ≥2 consecutive minutes at ≥60 steps/minute across all the valid days.

Extended Data Fig. 8
Extended Data Fig. 8. Incidence rates (number of events shown in brackets) for each diagnosis as a function of step counts and bout cadence (step intensity) quartiles.

Incidence rates (number of events shown in brackets) for each diagnosis as a function of step counts and bout cadence (step intensity) quartiles. Incidence rates is number of cases per 1000 people for each diagnosis as a function of step and bout cadence quartiles. Bout cadence referred to steps per minute computed by averaging the steps over the time when participant engaged in ≥2 consecutive minutes at ≥100 steps/minute across all the valid days. Step quartile intervals (thous.) are as follows: 1: [549,5.87]; 2: [5.87,7.73]; 3: [7.73,9.83]; 4: [9.83,33.6]. Bout cadence quartiles are as follows: 1: [102,109]; 2: [109,111]; 3: [111,114]; 4: [113,207].

Extended Data Fig. 9
Extended Data Fig. 9. Relation between daily steps counts and incident risk of chronic diseases.

Relation between daily steps counts and incident risk of chronic diseases. A: Hazard ratio as a function of average daily steps in thousands for each outcome. B: Cumulative incidence as a function of average daily steps for each selected outcome by year. Results of Cox model with average daily bout cadence (step intensity) as covariate, in addition to other covariates: age, race, sex, coronary artery disease, cancer, body mass index, systolic blood pressure, education level, smoking, and alcohol use. Bout cadence referred to steps per minute computed by averaging the steps over the time when participant engaged in ≥2 consecutive minutes at ≥60 steps/minute across all the valid days. Shaded area represents 95%confidence interval.

Extended Data Fig. 10
Extended Data Fig. 10. Relation between daily bout cadence (step intensity) and incident risk of chronic diseases.

Relation between daily bout cadence (step intensity) and incident risk of chronic diseases. a: Hazard ratio as a function of average daily bout cadence (step intensity) for each outcome. b: Cumulative incidence as a function of average daily bout cadence for each selected outcome by year. Results of Cox model with average daily steps, average daily bout cadence addition to other covariates: age, race, sex, coronary artery disease, cancer, body mass index, systolic blood pressure, education level, smoking, and alcohol use. Bout cadence referred to steps per minute computed by averaging the steps over the time when participant engaged in ≥2 consecutive minutes at ≥60 steps/minute across all the valid days. Shaded area represents 95%confidence interval.

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