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Figure 1.  Distribution of Moderate to Vigorous Physical Activity (MVPA) on Top 2 Days vs Remaining 5 Days Among Active Individuals Using Guideline-Based Activity Threshold of 150 Minutes or More of MVPA Per Week
Distribution of Moderate to Vigorous Physical Activity (MVPA) on Top 2 Days vs Remaining 5 Days Among Active Individuals Using Guideline-Based Activity Threshold of 150 Minutes or More of MVPA Per Week

Depicted is the distribution of daily MVPA on the 2 most active days of the week (blue), vs the remaining 5 days (yellow), among individuals with activity above the guideline-based threshold (ie, ≥150 minutes MVPA over the week,1-3 n = 59 345). A, Individuals meeting criteria for weekend warrior activity (ie, ≥50% of total MVPA achieved in 1-2 days) are shown. B, Active individuals not meeting criteria for weekend warrior activity (regular) are shown. A total of 431 individuals in the weekend warrior group (1.1%) with a value of zero for the remaining 5 days were attributed 1 minute of MVPA to accommodate logarithmic x-axis scale.

Figure 2.  Associations Between Physical Activity Pattern and Incident Cardiovascular Disease
Associations Between Physical Activity Pattern and Incident Cardiovascular Disease

Depicted are plots of multivariable-adjusted associations between activity pattern and incident atrial fibrillation, myocardial infarction, heart failure, and stroke. Three activity groups are compared: active weekend warrior (active WW), active regular, and inactive (reference). Each plot depicts a different activity threshold used to define the inactive group (see title above each plot). Bars depict 95% CIs.

Table.  Sample Characteristics of Participants in an Accelerometer-Derived Physical Activity Study
Sample Characteristics of Participants in an Accelerometer-Derived Physical Activity Study
Supplement 1.

eMethods. Supplemental methods

eTable 1. Disease Definitions

eTable 2. Covariate Definitions

eTable 3. Sample Characteristics Stratified at Activity Threshold of ≥230.4 Minutes of MVPA Per Week (Sample Median)

eTable 4. Sample Characteristics of Individuals in Primary Analysis Sample Versus Individuals Excluded for Incomplete Accelerometer Data

eTable 5. Associations Between Physical Activity Pattern and Incident Cardiovascular Disease Across Varying MVPA Thresholds

eTable 6. Associations Between Physical Activity Pattern and Incident Cardiovascular Disease Using Activity Threshold of ≥150 Minutes of MVPA Per Week (Guideline-Based)

eTable 7. Associations Between Physical Activity Pattern and Incident Cardiovascular Disease Using Activity Threshold of ≥230.4 Minutes of MVPA Per Week (Sample Median)

eTable 8. Associations Between Physical Activity Pattern and Incident Cardiovascular Disease With 2-Year Blanking Period After Accelerometer

eTable 9. Associations Between Physical Activity Pattern and Incident Cardiovascular Disease In Models Additionally Adjusted For Body Mass Index, Blood Pressure, Anti-hypertensive Use, and Diabetes

eTable 10. Associations Between Physical Activity Pattern and Incident Cardiovascular Disease With Individuals With Incomplete Accelerometer Data Assumed to be Inactive

eTable 11. Associations Between Physical Activity Pattern and Incident Cardiovascular Disease Among Individuals With Complete Wear Time (No Imputed Values)

eTable 12. Associations Between Physical Activity Pattern and Incident Musculoskeletal Disease

eFigure 1. Study Flow

eFigure 2. Distribution of Moderate-to-Vigorous Physical Activity on Top Two Days Versus Remaining Five Days Among Active Individuals Based on Guideline-Based Threshold of ≥230.4 Minutes of MVPA Per Week (Sample Median)

eFigure 3. Cumulative Risk of Incident Cardiovascular Events Stratified by Activity Pattern Using an Activity Threshold of ≥150 Minutes of MVPA Per Week (Guideline-Based)

eFigure 4. Cumulative Risk of Incident Cardiovascular Events Stratified by Activity Pattern Using an Activity Threshold of ≥230.4 Minutes of MVPA Per Week (Sample Median)

eFigure 5. Associations Between Physical Activity Pattern and Incident Cardiovascular Disease Utilizing Alternative Definitions of Weekend Warrior Activity

eFigure 6. Cumulative Risk of Incident Musculoskeletal Conditions Stratified by Activity Pattern

eReferences

1.
Arnett  DK, Blumenthal  RS, Albert  MA,  et al.  2019 ACC/AHA guideline on the primary prevention of cardiovascular disease: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines.   Circulation. 2019;140(11):e596-e646. doi:10.1161/CIR.0000000000000678PubMedGoogle ScholarCrossref
2.
World Health Organization.  Global Recommendations on Physical Activity for Health. World Health Organization; 2010.
3.
National Health Service. Physical activity guidelines for adults aged 19 to 64. Accessed May 31, 2023. https://www.nhs.uk/live-well/exercise/exercise-guidelines/physical-activity-guidelines-for-adults-aged-19-to-64/
4.
Kunutsor  SK, Jae  SY, Laukkanen  JA.  ‘Weekend warrior’ and regularly active physical activity patterns confer similar cardiovascular and mortality benefits: a systematic meta-analysis.   Eur J Prev Cardiol. 2023;30(3):e7-e10. doi:10.1093/eurjpc/zwac246PubMedGoogle ScholarCrossref
5.
Inoue  K, Tsugawa  Y, Mayeda  ER, Ritz  B.  Association of daily step patterns with mortality in US adults.   JAMA Netw Open. 2023;6(3):e235174. doi:10.1001/jamanetworkopen.2023.5174PubMedGoogle ScholarCrossref
6.
Littlejohns  TJ, Sudlow  C, Allen  NE, Collins  R.  UK Biobank: opportunities for cardiovascular research.   Eur Heart J. 2019;40(14):1158-1166. doi:10.1093/eurheartj/ehx254PubMedGoogle ScholarCrossref
7.
Doherty  A, Jackson  D, Hammerla  N,  et al.  Large scale population assessment of physical activity using wrist worn accelerometers: the UK Biobank Study.   PLoS One. 2017;12(2):e0169649. doi:10.1371/journal.pone.0169649PubMedGoogle ScholarCrossref
8.
Walmsley  R, Chan  S, Smith-Byrne  K,  et al.  Reallocation of time between device-measured movement behaviours and risk of incident cardiovascular disease.   Br J Sports Med. 2021;56(18):1008-1017. doi:10.1136/bjsports-2021-104050PubMedGoogle ScholarCrossref
9.
Thompson  D, Batterham  AM, Peacock  OJ, Western  MJ, Booso  R.  Feedback from physical activity monitors is not compatible with current recommendations: a recalibration study.   Prev Med. 2016;91:389-394. doi:10.1016/j.ypmed.2016.06.017PubMedGoogle ScholarCrossref
11.
R Core Team. The R Project for Statistical Computing. Accessed March 5, 2023. https://www.R-project.org/.
12.
Plummer  M.  Improved estimates of floating absolute risk.   Stat Med. 2004;23(1):93-104. doi:10.1002/sim.1485PubMedGoogle ScholarCrossref
13.
Stamatakis  E, Ahmadi  MN, Gill  JMR,  et al.  Association of wearable device-measured vigorous intermittent lifestyle physical activity with mortality.   Nat Med. 2022;28(12):2521-2529. doi:10.1038/s41591-022-02100-xPubMedGoogle ScholarCrossref
14.
Dempsey  PC, Rowlands  AV, Strain  T,  et al.  Physical activity volume, intensity, and incident cardiovascular disease.   Eur Heart J. 2022;43(46):4789-4800. doi:10.1093/eurheartj/ehac613PubMedGoogle ScholarCrossref
15.
Hartnett  DA, Milner  JD, DeFroda  SF.  The weekend warrior: common shoulder and elbow injuries in the recreational athlete.   Am J Med. 2022;135(3):297-301. doi:10.1016/j.amjmed.2021.08.015PubMedGoogle ScholarCrossref
Original Investigation
July 18, 2023

Accelerometer-Derived “Weekend Warrior” Physical Activity and Incident Cardiovascular Disease

Author Affiliations
  • 1Cardiovascular Research Center, Massachusetts General Hospital, Boston
  • 2Demoulas Center for Cardiac Arrhythmias, Cardiology Division, Massachusetts General Hospital, Boston
  • 3Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
  • 4Cardiology Division, Massachusetts General Hospital, Boston
  • 5Cardiovascular Performance Program, Cardiology Division, Massachusetts General Hospital, Boston
JAMA. 2023;330(3):247-252. doi:10.1001/jama.2023.10875
Key Points

Question  Does engagement in moderate to vigorous physical activity, with most activity concentrated within 1 to 2 days of the week (ie, a “weekend warrior” pattern), confer similar cardiovascular benefits to more evenly distributed physical activity?

Findings  In an analysis of 89 573 individuals providing a week of accelerometer-based physical activity data, a weekend warrior pattern of physical activity was associated with similarly lower risks of incident atrial fibrillation, myocardial infarction, heart failure, and stroke compared with more evenly distributed physical activity.

Meaning  Increased activity, even when concentrated within 1 to 2 days each week, may be effective for improving cardiovascular risk profiles.

Abstract

Importance  Guidelines recommend 150 minutes or more of moderate to vigorous physical activity (MVPA) per week for overall health benefit, but the relative effects of concentrated vs more evenly distributed activity are unclear.

Objective  To examine associations between an accelerometer-derived “weekend warrior” pattern (ie, most MVPA achieved over 1-2 days) vs MVPA spread more evenly with risk of incident cardiovascular events.

Design, Setting, and Participants  Retrospective analysis of UK Biobank cohort study participants providing a full week of accelerometer-based physical activity data between June 8, 2013, and December 30, 2015.

Exposures  Three MVPA patterns were compared: active weekend warrior (active WW, ≥150 minutes with ≥50% of total MVPA achieved in 1-2 days), active regular (≥150 minutes and not meeting active WW status), and inactive (<150 minutes). The same patterns were assessed using the sample median threshold of 230.4 minutes or more of MVPA per week.

Main Outcomes and Measures  Associations between activity pattern and incident atrial fibrillation, myocardial infarction, heart failure, and stroke were assessed using Cox proportional hazards regression, adjusted for age, sex, racial and ethnic background, tobacco use, alcohol intake, Townsend Deprivation Index, employment status, self-reported health, and diet quality.

Results  A total of 89 573 individuals (mean [SD] age, 62 [7.8] years; 56% women) who underwent accelerometry were included. When stratified at the threshold of 150 minutes or more of MVPA per week, a total of 37 872 were in the active WW group (42.2%), 21 473 were in the active regular group (24.0%), and 30 228 were in the inactive group (33.7%). In multivariable-adjusted models, both activity patterns were associated with similarly lower risks of incident atrial fibrillation (active WW: hazard ratio [HR], 0.78 [95% CI, 0.74-0.83]; active regular: 0.81 [95% CI, 0.74-0.88; inactive: HR, 1.00 [95% CI, 0.94-1.07]), myocardial infarction (active WW: 0.73 [95% CI, 0.67-0.80]; active regular: 0.65 [95% CI, 0.57-0.74]; and inactive: 1.00 [95% CI, 0.91-1.10]), heart failure (active WW: 0.62 [95% CI, 0.56-0.68]; active regular: 0.64 [95% CI, 0.56-0.73]; and inactive: 1.00 [95% CI, 0.92-1.09]), and stroke (active WW: 0.79 [95% CI, 0.71-0.88]; active regular: 0.83 [95% CI, 0.72-0.97]; and inactive: 1.00 [95% CI, 0.90-1.11]). Findings were consistent at the median threshold of 230.4 minutes or more of MVPA per week, although associations with stroke were no longer significant (active WW: 0.89 [95% CI, 0.79-1.02]; active regular: 0.87 [95% CI, 0.74-1.02]; and inactive: 1.00 [95% CI, 0.90-1.11]).

Conclusions and Relevance  Physical activity concentrated within 1 to 2 days was associated with similarly lower risk of cardiovascular outcomes to more evenly distributed activity.

Introduction

Physical activity is regarded as favorable for health and is consistently associated with lower risks of death and cardiovascular disease.1 World Health Organization and American Heart Association guidelines recommend 150 minutes or more of moderate to vigorous physical activity (MVPA) per week, without specifying an optimal MVPA pattern.1,2 The UK National Health Service recommends MVPA be spread “evenly over 4-5 days per week, or every day.”3 However, it remains unclear whether MVPA concentrated within 1 to 2 days per week (“weekend warrior” pattern4) confers similar benefits compared with more evenly distributed activity. Prior studies were limited by self-reported activity,4 modest sample sizes,5 and a limited set of outcomes (eg, mortality).4,5

Here, associations between physical activity patterns, defined using wrist-based accelerometers, and incident cardiovascular events were assessed among nearly 90 000 participants of the UK Biobank prospective cohort study.

Methods

The UK Biobank is a prospective cohort of 502 629 participants enrolled between 2006 and 2010.6 Briefly, 9.2 million individuals aged 40 to 69 years living within 25 miles of 22 assessment centers in the UK were invited, and 5.4% participated in the baseline assessment (Table). Information on race and ethnicity were included given prior associations with physical activity and cardiovascular events and was determined by self-report based on fixed categories.

Within the accelerometer substudy, 103 695 participants submitted data from an Axivity AX3 wrist-based triaxial accelerometer worn for 1 week.7 The sensor captured continuous acceleration at 100 Hz with dynamic range ±8g. As described previously, acceleration signals were calibrated to gravity.7 Sample data were combined into 5-second epochs, each representing mean vector magnitude. Non–wear time was identified as consecutive stationary episodes of 60 minutes or more in which all 3 axes had an SD less than 13.0 mg.7 Epochs representing non–wear time were imputed based on the mean of similar time-of-day vector magnitude and intensity distribution data points on different days. We excluded individuals whose wear time was insufficient to support imputation (no wear data in each 1-hour period of the 24-hour cycle), whose signals were insufficient for calibration or MVPA estimation, and whose mean acceleration values were nonphysiologic (eFigure 1 in Supplement 1).8

MVPA was then classified using a published machine-learning–based method developed to classify a broad range of activities (eg, walking, jogging, stationary cycling, elliptical, and others) and validated in a UK-based sample.8 Because optimal MVPA levels using wrist-based accelerometers are unclear,9 we assessed multiple thresholds. For our primary analyses, we assessed the guideline-based threshold (≥150 minutes/week1-3) and the sample median (≥230.4 minutes) based on UK national health surveys reporting approximately half of individuals are physically active.10 We tested additional thresholds in secondary analyses. Quiz Ref IDIndividuals were classified as active weekend warrior (active WW, at or above the MVPA threshold and ≥50% of total MVPA over 1-2 days4), active regular (at or above MVPA threshold but not active WW), and inactive (below MVPA threshold).

We assessed associations between activity pattern and incident atrial fibrillation (AF), myocardial infarction (MI), heart failure (HF), and stroke using Cox proportional hazards models adjusted for age, sex, racial and ethnic background, tobacco use, Townsend Deprivation Index, alcohol intake, educational attainment, employment status, self-reported health, and diet quality. We used a complete case analysis (eFigure 1 in Supplement 1). To compare activity patterns without thresholding, we fit analogous models comparing active WW vs regular patterns with MVPA decile as a stratification variable. Exposure and outcome definitions are described in eTables 1 and 2 in Supplement 1. We plotted the Kaplan-Meier cumulative incidence of each outcome stratified by activity pattern and calculated E-values. We performed multiple secondary analyses (eMethods in Supplement 1).

Participants provided written informed consent. The UK Biobank was approved by the UK Biobank Research Ethics Committee (reference No. 11/NW/0382). UK Biobank data were used under application 17488. Analyses were performed using R version 4.0.11 Hazard ratios and 95% CIs are presented using floating absolute risks.12

Results

Our analyses included 89 573 individuals who underwent activity measurement between June 8, 2013, and December 30, 2015 (Table; eTables 3 and 4 and eFigure 1 in Supplement 1). The median follow-up time was 6.3 years (quartile 1: 5.7, quartile 3: 6.8). Stratified at the guideline-based threshold of 150 minutes or more of MVPA per week, a total of 37 872 participants were in the active WW group (42.2%), 21 473 were in the active regular group (24.0%), and 30 228 were in the inactive group (33.7%). Individuals in the active WW group had substantially more MVPA on their 2 most active days vs the remaining 5 days, while those in the active regular group had more consistent MVPA (Figure 1; eFigure 2 in Supplement 1).

Quiz Ref IDIn multivariable-adjusted models, both activity patterns were associated with similarly lower risks of incident AF, MI, and HF at both the guideline-based (≥150 minutes) and median (≥230.4 minutes) thresholds (Figure 2). Stroke associations were also similar, although significant only at the guideline-based threshold (Figure 2). Event rates were comparable between the active WW and active regular groups (eFigures 3 and 4 in Supplement 1). In multivariable models stratified by MVPA decile, there were no differences in risk with the WW pattern (AF: hazard ratio [HR], 0.98 [95% CI, 0.89-1.09]; MI: HR, 1.12 [95% CI, 0.95-1.30]; HF: HR, 0.92 [95% CI, 0.79-1.08]; stroke: HR, 0.92 [95% CI, 0.77-1.11]). Findings were generally consistent across other activity thresholds (Figure 2; eTable 5 in Supplement 1), alternative WW definitions (eTables 6 and 7 and eFigure 5 in Supplement 1), a 2-year blanking period (eTable 8 in Supplement 1), additional covariate adjustment (eTable 9 in Supplement 1), individuals with incomplete accelerometer data included as inactive (eTable 10 in Supplement 1), and excluding imputed wear time (eTable 11 in Supplement 1). Both activity patterns were associated with similarly lower risks of incident musculoskeletal conditions (eTable 12 and eFigure 6 in Supplement 1).

Discussion

These study results have implications for efforts leveraging physical activity to reduce cardiovascular morbidity. First, when quantified using accelerometry, a weekend warrior pattern appears common. Across multiple activity thresholds, more than half of active individuals accrued most of their MVPA in 1 to 2 days. Second, varying activity patterns were observed, in only 5 years’ time, to have similar associations with lower risk of AF, MI, HF, and stroke. These observations thereby extend prior work reporting improved cardiovascular outcomes with increasing moderate and vigorous activity,8,13,14 as well as reports suggesting that concentrated physical activity is associated with similar reductions in mortality to more regular activity.4,5Quiz Ref ID Specifically, these findings suggest that engagement in physical activity, regardless of pattern, may optimize risk across a broad spectrum of cardiovascular diseases. Third, efforts to increase physical activity for cardiovascular health may be effective even when such efforts are concentrated into 1 to 2 days per week. Because weekend warrior patterns may be more feasible for certain schedules, targeted interventions delivered over shorter timeframes may be more accessible. Despite concern that weekend warrior activity may be associated with musculoskeletal injury,15 similarly lower risk of musculoskeletal conditions with both activity patterns was observed. Future research is warranted to better define potential negative effects of concentrated activity.

Limitations

This study had some limitations. First, activity was measured over 1 week, and individuals may have modified their behavior during observation. Second, a validated MVPA classification method developed using a broad range of activities (eg, walking, jogging, stationary cycling, elliptical, and others) was used,8 but MVPA classification accuracy may vary by activity type. Third, optimal MVPA thresholds using wrist-based accelerometers remain unclear.9 However, findings were consistent across multiple thresholds, including the 25th percentile or 115.2 minutes or more (ie, below guideline recommendations1-3). Fourth, analysis of a single UK-based sample comprising predominantly White individuals may limit generalizability. Fifth, most covariates were ascertained several years prior to accelerometry and are subject to misclassification. Sixth, the weekend warrior pattern is less well-defined using accelerometers, but findings were consistent across multiple definitions.

Conclusions

Within nearly 90 000 individuals providing wrist-based activity quantification, physical activity concentrated within 1 to 2 days was associated with similarly lower risk of cardiovascular outcomes to more regular activity. Future prospective studies are warranted to assess whether interventions to increase physical activity, even when concentrated within a day or 2 each week, improve cardiovascular outcomes.

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Article Information

Accepted for Publication: June 2, 2023.

Corresponding Author: Patrick T. Ellinor, MD, PhD, Cardiac Arrhythmia Service and Cardiovascular Research Center, Massachusetts General Hospital, 55 Fruit St, GRB 109, Boston, MA 02114 (ellinor@mgh.harvard.edu).

Author Contributions: Dr Khurshid had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Khurshid.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Khurshid, Guseh, Ellinor.

Critical revision of the manuscript for important intellectual content: Al-Alusi, Churchill, Guseh, Ellinor.

Statistical analysis: Khurshid.

Obtained funding: Ellinor.

Administrative, technical, or material support: Ellinor.

Supervision: Guseh, Ellinor.

Conflict of Interest Disclosures: Dr Al-Alusi has received grants from the National Institutes of Health (NIH) (T32-HL007208). Dr Churchill reported receiving grants from the NIH. Dr Guseh reported receiving grants from the American Heart Association (19AMFDP34990046) and the President and Fellows of Harvard College (5KL2 TR002542-04). Dr Ellinor reported receiving grants from the NIH (1RO1HL092577, 1R01HL157635, and 5R01HL139731), the American Heart Association Strategically Focused Research Networks (18SFRN34110082), the European Union (MAESTRIA 965286), Bayer AG (to the Broad Institute), IBM Health (to the Broad Institute), Bristol Myers Squibb (to Massachusetts General Hospital), and Pfizer (to Massachusetts General Hospital) and personal fees from Bayer AG, Novartis, and MyoKardia. No other disclosures were reported.

Data Sharing Statement: See Supplement 2.

References
1.
Arnett  DK, Blumenthal  RS, Albert  MA,  et al.  2019 ACC/AHA guideline on the primary prevention of cardiovascular disease: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines.   Circulation. 2019;140(11):e596-e646. doi:10.1161/CIR.0000000000000678PubMedGoogle ScholarCrossref
2.
World Health Organization.  Global Recommendations on Physical Activity for Health. World Health Organization; 2010.
3.
National Health Service. Physical activity guidelines for adults aged 19 to 64. Accessed May 31, 2023. https://www.nhs.uk/live-well/exercise/exercise-guidelines/physical-activity-guidelines-for-adults-aged-19-to-64/
4.
Kunutsor  SK, Jae  SY, Laukkanen  JA.  ‘Weekend warrior’ and regularly active physical activity patterns confer similar cardiovascular and mortality benefits: a systematic meta-analysis.   Eur J Prev Cardiol. 2023;30(3):e7-e10. doi:10.1093/eurjpc/zwac246PubMedGoogle ScholarCrossref
5.
Inoue  K, Tsugawa  Y, Mayeda  ER, Ritz  B.  Association of daily step patterns with mortality in US adults.   JAMA Netw Open. 2023;6(3):e235174. doi:10.1001/jamanetworkopen.2023.5174PubMedGoogle ScholarCrossref
6.
Littlejohns  TJ, Sudlow  C, Allen  NE, Collins  R.  UK Biobank: opportunities for cardiovascular research.   Eur Heart J. 2019;40(14):1158-1166. doi:10.1093/eurheartj/ehx254PubMedGoogle ScholarCrossref
7.
Doherty  A, Jackson  D, Hammerla  N,  et al.  Large scale population assessment of physical activity using wrist worn accelerometers: the UK Biobank Study.   PLoS One. 2017;12(2):e0169649. doi:10.1371/journal.pone.0169649PubMedGoogle ScholarCrossref
8.
Walmsley  R, Chan  S, Smith-Byrne  K,  et al.  Reallocation of time between device-measured movement behaviours and risk of incident cardiovascular disease.   Br J Sports Med. 2021;56(18):1008-1017. doi:10.1136/bjsports-2021-104050PubMedGoogle ScholarCrossref
9.
Thompson  D, Batterham  AM, Peacock  OJ, Western  MJ, Booso  R.  Feedback from physical activity monitors is not compatible with current recommendations: a recalibration study.   Prev Med. 2016;91:389-394. doi:10.1016/j.ypmed.2016.06.017PubMedGoogle ScholarCrossref
11.
R Core Team. The R Project for Statistical Computing. Accessed March 5, 2023. https://www.R-project.org/.
12.
Plummer  M.  Improved estimates of floating absolute risk.   Stat Med. 2004;23(1):93-104. doi:10.1002/sim.1485PubMedGoogle ScholarCrossref
13.
Stamatakis  E, Ahmadi  MN, Gill  JMR,  et al.  Association of wearable device-measured vigorous intermittent lifestyle physical activity with mortality.   Nat Med. 2022;28(12):2521-2529. doi:10.1038/s41591-022-02100-xPubMedGoogle ScholarCrossref
14.
Dempsey  PC, Rowlands  AV, Strain  T,  et al.  Physical activity volume, intensity, and incident cardiovascular disease.   Eur Heart J. 2022;43(46):4789-4800. doi:10.1093/eurheartj/ehac613PubMedGoogle ScholarCrossref
15.
Hartnett  DA, Milner  JD, DeFroda  SF.  The weekend warrior: common shoulder and elbow injuries in the recreational athlete.   Am J Med. 2022;135(3):297-301. doi:10.1016/j.amjmed.2021.08.015PubMedGoogle ScholarCrossref
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