Abstract
Background
Although weekend warrior (WW) physical activity may confer health benefits comparable with more evenly distributed activity, whether this pattern is associated with venous thromboembolism (VTE) incidence and death remains unclear. This study aimed to investigate the associations of accelerometer‐derived physical activity patterns with incident VTE and all‐cause death in individuals with prevalent VTE.
Methods
In this prospective cohort study, we analyzed 92 392 participants free of VTE for incidence analysis and 3019 participants with prevalent VTE for mortality analysis. Physical activity was measured using wrist‐worn accelerometers. Participants were classified as inactive (<150 min/wk of moderate‐to‐vigorous physical activity [MVPA]), regularly active (≥150 min/wk of MVPA with <50% of total MVPA accumulated over 1–2 days), or WW (≥150 min/wk of MVPA with ≥50% of total MVPA accumulated over 1–2 days). The primary outcome was incident VTE, analyzed using Cox models.
Results
Over a median follow‐up of 11.1 years, 1955 incident VTE cases were recorded. In comparison with the inactive group, the WW pattern lowered the risk of incident VTE (hazard ratio [HR], 0.813 [95% CI, 0.733–0.902]) and reduced all‐cause death among those with preexisting VTE (HR, 0.567 [95% CI, 0.438–0.734]). When compared with the regularly active group, the inactive group showed an increased risk, whereas the WW pattern showed no statistically significant difference.
Conclusions
Our findings indicate that the WW pattern was associated with lower risks of incident VTE and all‐cause death, with associations comparable with those observed for activity distributed more evenly across the week, suggesting that it may be a practical strategy for VTE prevention and management.
Keywords: deep vein thrombosis, physical activity, pulmonary embolism, venous thromboembolism, weekend warrior
Subject Categories: Cardiovascular Disease, Lifestyle
Nonstandard Abbreviations and Acronyms
- CAPTURE‐24
A Large Dataset of Wrist‐Worn Activity Tracker Data Collected in the Wild for Human Activity Recognition
- MVPA
moderate‐to‐vigorous physical activity
- PA
physical activity
- WW
weekend warrior
Research Perspective.
What Is New?
This is the first large‐scale prospective study using accelerometer‐derived data to investigate the association between the weekend warrior physical activity pattern and venous thromboembolism incidence and death.
The weekend warrior pattern provides comparable benefits in lowering venous thromboembolism risk and improving survival in population with venous thromboembolism. Compared with the regularly active group, it showed no statistically significant difference in these outcomes.
What Question Should Be Addressed Next?
Future research should determine whether these associations are causal, clarify the biological mechanisms linking concentrated physical activity patterns to venous thromboembolism prevention and prognosis, and evaluate whether promoting the weekend warrior pattern may offer a practical strategy for individuals who face barriers to regular daily exercise.
Venous thromboembolism (VTE) is a prevalent vascular disease marked by blood clots in veins. 1 As the third most common cardiovascular condition worldwide, it affects up to 5% of the population and has a case fatality rate of up to 10%. 1 , 2 , 3 VTE has become a major global health issue, making the identification of modifiable lifestyle factors essential for its prevention and improved outcomes.
Physical activity (PA) is commonly viewed as a protective factor for cardiovascular health. 4 , 5 Previous guidelines advise at least 150 minutes of moderate‐to‐vigorous physical activity (MVPA) throughout the week, but many adults find this difficult due to time constraints. 6 , 7 Thus, a new exercise pattern has emerged known as the weekend warrior (WW), in which weekly MVPA is concentrated into 1 to 2 days. 8 Recent studies indicate that the WW pattern might offer benefits similar to regular exercise in lowering hypertension, diabetes, and death, but systematic evidence on its link to VTE risk remains lacking. 9 Furthermore, the relationship between PA and the development of VTE appears complex and inconclusive.
Existing epidemiological studies indicate that regular PA generally lowers the risk of VTE. 10 , 11 However, findings remain inconsistent. The Norwegian Tromsø Study reported no association between regular moderate‐intensity exercise and VTE risk. 12 Findings from the VEINS (Venous thromboEmbolism In Northern Sweden) study also indicate a lack of significant association between PA and incident VTE in men. 13 Conversely, a Swedish cohort study found that men with the highest level of PA faced a 222% increased risk of VTE. 14 These contradictory results suggest that temporal distribution and intensity of exercise may be critical determinants of VTE risk. Moreover, most prior studies used self‐reported PA data, which may be limited by recall bias and may fail to capture the nuances of the WW pattern.
Using comprehensive accelerometer‐derived PA data, this study sought to evaluate the impact of 3 distinct activity patterns (WWs, regularly active, and inactive) on the risk of developing VTE in a population initially free of VTE. Additionally, the study aimed to examine the relationship between these activity patterns and the risk of all‐cause death among patients diagnosed with VTE.
METHODS
Data Availability
Data are available in a public, open‐access repository. This research was conducted using the UK Biobank Resource under Application Number 1210686. The UK Biobank data are available on application to the UK Biobank (www.ukbiobank.ac.uk/).
Ethics Approval and Consent to Participate
All participants in the UK Biobank provided written informed consent. The UK Biobank study received ethical approval from the multicenter Research Ethics Committee, the National Information Governance Board for Health and Social Care in England and Wales, and the Community Health Index Advisory Group in Scotland.
Study Design and Participants
Participants in this study were included from the UK Biobank, a prospective cohort study designed to investigate diverse health‐related results. A detailed description of the study rationale and design is available in previous literature. 15 In summary, the baseline survey conducted between 2006 and 2010 involved more than half a million UK residents aged 40 to 69 years.
The current analysis was restricted to participants in the accelerometer substudy (n=103 567). 16 In this study, we excluded participants without valid accelerometer data (n=8 143) and those lost to follow‐up (n=13). Consequently, the final analytic sample comprised 95 411 participants, divided into 2 groups: 92 392 participants free of VTE at baseline for the analysis of incident VTE and 3019 participants with prevalent VTE for the analysis of mortality risk of patients with VTE. A detailed flowchart of participant selection is provided in Figure S1.
Assessment of PA Pattern
From June 2013 through December 2015, PA levels were objectively measured using Axivity AX3 triaxial accelerometers. Participants were instructed to wear the device on their primary wrist for a continuous 1‐week period. After retrieving the device, we calibrated raw acceleration signals to local gravity and excluded nonwear time. Movement behaviors were classified using a previously validated machine‐learning algorithm that has been applied in prior studies to identify behaviors such as light‐intensity physical activity, sedentary behavior, sleep, and MVPA. 17 This approach was based on the CAPTURE‐24 (A Large Dataset of Wrist‐Worn Activity Tracker Data Collected in the Wild for Human Activity Recognition) study containing a large free‐living data set. Compared with traditional “vector magnitude” methods, the machine‐learning approach leverages multiple data features to classify behaviors with greater accuracy. Based on these objective measurements, participants were stratified into 3 distinct PA patterns: (1) inactive (achieving <150 minutes of MVPA per week); (2) regularly active (achieving at least 150 minutes of MVPA weekly, where less than half of the total activity occurred within any 2 days); and (3) WW (achieving at least 150 minutes of weekly MVPA, but with ≥50% of that volume concentrated on 1 or 2 days.).
Ascertainment of Outcome
The primary study outcome was incident VTE, which includes both deep vein thrombosis and pulmonary embolism (PE); all‐cause death in participants with VTE were also examined as secondary outcomes. VTE cases were defined according to the International Classification of Diseases, Tenth Revision (ICD‐10), using codes I80 to I82 (for deep vein thrombosis) and I26 (for PE) 18 ; a comprehensive list of these codes is available in Table S1. Follow‐up for each participant began at the date of accelerometer assessment and continued until the first occurrence of VTE, death, or the censoring date (December 31, 2024). For mortality analysis in participants with existing VTE, follow‐up started after accelerometer wear ended and continued until all‐cause death occurred.
Assessment of Covariates
The covariates for this study included sociodemographic factors (age, sex, race and ethnicity, education level, Townsend Deprivation Index, 19 and employment status), lifestyle characteristics (body mass index, smoking status, alcohol consumption, and healthy diet 20 ) and medical history covariates (diabetes, hypertension, cancer, hyperlipidemia, and aspirin use). 21 , 22 , 23 To maximize data use, missing values were imputed with multiple imputations with chained equations. 24 , 25 Detailed definitions for covariates are provided in Supplemental Methods.
Statistical Analysis
Cumulative VTE incidence across the distinct PA patterns was estimated and compared using Kaplan–Meier survival curves. We investigated the relationship between PA pattern and VTE incidence by using the multivariable Cox proportional hazards models. Three adjusted models were constructed: Model 1 included age, sex, and ethnicity. Model 2 further incorporated socioeconomic indicators, including Townsend Deprivation Index, education, and employment status. Model 3 was the fully adjusted model, adding body mass index, smoking status, alcohol consumption, healthy diet score, aspirin use, and comorbidities (diabetes, hypertension, hyperlipidemia, and malignancy). The validity of the proportional hazard assumption was verified through the inspection of Schoenfeld residuals, which revealed no significant violations (all P>0.05).
To evaluate the robustness of our findings, we conducted a series of sensitivity and subgroup analyses. These analyses included (1) the exclusion of incident VTE cases occurring within the first 2 years of follow‐up to reduce the potential for reverse causation; (2) a complete‐case analysis by omitting individuals with missing covariate data; (3) the redefinition of PA patterns using the 25th, 50th, and 75th percentiles of total MVPA volume as alternative, population‐specific thresholds. This analysis was performed to assess whether the observed associations were robust to different definitions of activity patterns and were not solely dependent on the guideline‐based threshold of 150 min/wk used in the primary analysis. The cut points were 115.2, 230.4, and 403.2 min/wk for the VTE incidence study, and 72.0, 187.2, and 345.6 min/wk for the mortality study, respectively; and (4) additional adjustment for metabolic biomarkers, including glycated hemoglobin, low‐density lipoprotein cholesterol, high‐density lipoprotein cholesterol, total cholesterol, and triglycerides. Additionally, to explore potential effect modifications, subgroup analyses were performed across various strata: age (split at 65 years), sex, socioeconomic status (using a Townsend Deprivation Index threshold of 0), employment status (employed versus retired/unemployed), body mass index (<25 versus ≥25 kg/m2) and smoking history (never versus ever/current).
Statistical analyses were conducted using SAS version 9.4 (SAS Institute, Cary, NC) and R version 4.4.1 (R Foundation for Statistical Computing, Vienna, Austria). A 2‐sided P value of <0.05 was considered indicative of statistical significance.
RESULTS
Study Participants
Among 92 392 participants (mean age, 56.1±7.8 years; 56.3% women) included in the VTE incidence analysis, 33.6% were inactive, 43.1% were WW, and 23.3% were regularly active. Compared with both active groups, inactive participants were characterized by a higher prevalence of obesity and current smoking. Additionally, the inactive group exhibited a higher prevalence of hypertension and diabetes, whereas the WW and regularly active groups displayed broadly comparable clinical and socioeconomic characteristics (Table 1). Details about the baseline characteristics of the participants involved in the mortality analysis are provided in Table S2.
Table 1.
Baseline Characteristics of Participants in the VTE Incidence Study According to Physical Activity Pattern
| Overall | Inactive | Weekend warrior | Regularly active | |
|---|---|---|---|---|
| (n=92 392) | (n=31 024) | (n=39 844) | (n=21 524) | |
| Age, y, mean±SD | 56.1±7.8 | 57.0±7.8 | 56.0±7.7 | 54.9±7.9 |
| Sex, n (%) | ||||
| Female | 51 999 (56.3) | 20 695 (66.7) | 20 408 (51.2) | 10 896 (50.6) |
| Male | 40 393 (43.7) | 10 329 (33.3) | 19 436 (48.8) | 10 628 (49.4) |
| Race and ethnicity, n (%) | ||||
| White | 89 451 (96.8) | 29 897 (96.4) | 38 795 (97.4) | 20 759 (96.4) |
| Others * | 2941 (3.2) | 1127 (3.6) | 1049 (2.6) | 765 (3.6) |
| Body mass index, kg/m2, n (%) | ||||
| <25 kg/m2 | 36 672 (39.7) | 9517 (30.7) | 16 986 (42.6) | 10 169 (47.2) |
| 25–29.9 kg/m2 | 38 071 (41.2) | 12 557 (40.5) | 17 022 (42.7) | 8492 (39.5) |
| ≥30 kg/m2 | 17 649 (19.1) | 8950 (28.8) | 5836 (14.6) | 2863 (13.3) |
| Drinking, n (%) | ||||
| Daily or almost daily | 21 124 (22.9) | 6159 (19.9) | 9646 (24.2) | 5319 (24.7) |
| 3 or 3 times/wk | 24 090 (26.1) | 6915 (22.3) | 11 246 (28.2) | 5929 (27.5) |
| Once or twice/wk | 23 249 (25.2) | 7840 (25.3) | 10 224 (25.7) | 5185 (24.1) |
| 1–3 times/mo | 10 027 (10.9) | 3967 (12.8) | 3915 (9.8) | 2145 (10) |
| Special occasions only | 8712 (9.4) | 3884 (12.5) | 3027 (7.6) | 1801 (8.4) |
| Never | 5190 (5.6) | 2259 (7.3) | 1786 (4.5) | 1145 (5.3) |
| Smoking, n (%) | ||||
| Never smoker | 52 911 (57.3) | 17 011 (54.8) | 23 471 (58.9) | 12 429 (57.7) |
| Former smoker | 33 086 (35.8) | 11 256 (36.3) | 14 079 (35.3) | 7751 (36.1) |
| Current smoker | 6395 (6.9) | 2757 (8.9) | 2294 (5.8) | 1344 (6.2) |
| Healthy diet score, mean±SD | 3.9±1.3 | 3.9±1.3 | 3.9±1.3 | 4.0±1.3 |
| Townsend Deprivation Index, mean±SD | −1.7±2.8 | −1.8±2.8 | −1.9±2.7 | −1.3±3.0 |
| Education, n (%) | ||||
| ≥College | 40 337 (43.7) | 10 784 (34.8) | 18 730 (47.0) | 10 823 (50.3) |
| College | 52 055 (56.3) | 20 240 (65.2) | 21 114 (53.0) | 10 701 (49.7) |
| Employment status, n (%) | ||||
| Employed | 56 942 (61.6) | 17 515 (56.5) | 24 961 (62.6) | 14 466 (67.2) |
| Unemployed | 35 450 (38.4) | 13 509 (43.5) | 14 883 (37.4) | 7058 (32.8) |
| History of aspirin use, n (%) | 10 683 (11.6) | 4280 (13.8) | 4240 (10.6) | 2163 (10.0) |
| History of hypertension, n (%) | 21 051 (22.8) | 8742 (28.2) | 8151 (20.5) | 4158 (19.3) |
| History of diabetes, n (%) | 3156 (3.4) | 1647 (5.3) | 959 (2.4) | 550 (2.6) |
| History of hyperlipidemia, n (%) | 9447 (10.2) | 3943 (12.7) | 3715 (9.3) | 1789 (8.3) |
| History of malignant tumor, n (%) | 6639 (7.2) | 2584 (8.3) | 2692 (6.8) | 1363 (6.3) |
*Includes Mixed, Asian or Asian British, Black or Black British, Chinese, and other ethnic groups.
Associations Between PA and Risk of VTE
Over a median follow‐up period of 11.1 years, a total of 1955 incident VTE cases were recorded within the study cohort. As illustrated in Figures 1A through 1C, the inactive group had consistently exhibited the greatest cumulative probability of developing VTE, deep vein thrombosis, and PE. In contrast, both WW and regularly active groups demonstrated significantly lower risks (log‐rank P<0.001). In terms of crude incidence rates per 1000 person‐years, the values stood at 2.46 for the inactive group, 1.76 for the WW group, and 1.68 for the regularly active group (Table 2). In multivariable‐adjusted Cox models, we observed that both WW and regularly active patterns correlated with a decreased likelihood of incident VTE (hazard ratio [HR], 0.813 [95% CI, 0.733–0.903]; and HR, 0.829 [95% CI, 0.731–0.940], respectively) relative to the inactive group (Table 2). Specifically, the WW pattern conferred a protective benefit against deep vein thrombosis (HR, 0.845 [95% CI, 0.733–0.974]) as well as PE (HR, 0.791 [95% CI, 0.690–0.907]). Notably, no appreciable difference in VTE risk was detected between the WW and regularly active patterns (HR, 0.986 [95% CI, 0.872–1.114]). Conversely, the inactive group had a 22.1% elevated risk of VTE (HR, 1.221 [95% CI, 1.078–1.385]) when compared with the regularly active group (Table 3).
Figure 1. Cumulative risk of VTE incidence and mortality stratified by different physical activity pattern.
A through C, Incidence of VTE in the VTE‐free population stratified by different physical activity patterns; (D) Overall survival of patients with VTE stratified by different physical activity patterns. DVT indicates deep vein thrombosis; PE, pulmonary embolism; and VTE, venous thromboembolism.
Table 2.
Association Between Physical Activity Pattern and VTE Incidence and Death
| Outcome | Physical activity pattern | No. of cases/no. of population | Incidence rate per 1000 person‐year | HR (95% CI) | ||
|---|---|---|---|---|---|---|
| Model 1 | Model 2 | Model 3 | ||||
| VTE risk in the VTE‐free population | ||||||
| VTE | Inactive | 808/31 024 | 2.46 | Reference | Reference | Reference |
| Weekend warrior | 756/39 844 | 1.76 | 0.702 (0.635–0.777) | 0.710 (0.642–0.785) | 0.813 (0.733–0.902) | |
| Regularly active | 391/21 524 | 1.68 | 0.706 (0.624–0.797) | 0.703 (0.621–0.794) | 0.829 (0.731–0.940) | |
| Deep vein thrombosis | Inactive | 407/31 024 | 1.23 | Reference | Reference | Reference |
| Weekend warrior | 417/39 844 | 0.97 | 0.750 (0.653–0.861) | 0.759 (0.661–0.872) | 0.845 (0.733–0.974) | |
| Regularly active | 225/21 524 | 0.96 | 0.773 (0.656–0.912) | 0.774 (0.656–0.914) | 0.883 (0.745–1.046) | |
| Pulmonary embolism | Inactive | 486/31 024 | 1.47 | Reference | Reference | Reference |
| Weekend warrior | 420/39 844 | 0.97 | 0.664 (0.581–0.758) | 0.670 (0.586–0.765) | 0.791 (0.690– 0.907) | |
| Regularly active | 205/21 524 | 0.88 | 0.638 (0.541–0.753) | 0.633 (0.537–0.748) | 0.776 (0.655–0.919) | |
| Mortality risk in the VTE population | ||||||
| All‐cause death | Inactive | 203/1312 | 15.08 | Reference | Reference | Reference |
| Weekend warrior | 95/1133 | 7.86 | 0.518 (0.406–0.661) | 0.474 (0.370–0.607) | 0.567 (0.438–0.734) | |
| Regularly active | 40/574 | 6.46 | 0.427 (0.304–0.600) | 0.426 (0.303–0.600) | 0.494 (0.348–0.703) | |
The weekend warrior pattern was defined as MVPA ≥150 min/wk (guideline‐based) with ≥50% concentrated on 1–2 d/wk; regularly active pattern was defined as MVPA ≥150 min/wk (guideline‐based) with ≥50% distributed on >2 d/wk; inactive group was defined as <150 min/wk (guideline‐based) of MVPA. Model 1 was adjusted for age, sex, and race and ethnicity. Model 2 was adjusted for age, sex, race and ethnicity, Townsend Deprivation Index, education level, and employment status. Model 3 was adjusted for age, sex, race and ethnicity, Townsend Deprivation Index, education level, employment status, body mass index, smoking status, alcohol drinking, healthy diet score, history of aspirin use, diabetes, hypertension, hyperlipidemia, and malignancy. HR indicates hazard ratio; MVPA, moderate‐to‐vigorous intensity physical activity; and VTE, venous thromboembolism.
Table 3.
HRs for VTE Incidence and Death Comparing Weekend Warrior With Regularly Active Pattern
| Outcome | Physical activity pattern | HR (95% CI) | ||
|---|---|---|---|---|
| Model 1 | Model 2 | Model 3 | ||
| VTE risk in the VTE‐free population | ||||
| VTE | Regularly active | Reference | Reference | Reference |
| Weekend warrior | 0.995 (0.881–1.125) | 1.011 (0.894–1.142) | 0.986 (0.872–1.114) | |
| Inactive | 1.417 (1.254–1.602) | 1.424 (1.260–1.610) | 1.221 (1.078–1.385) | |
| Deep vein thrombosis | Regularly active | Reference | Reference | Reference |
| Weekend warrior | 0.970 (0.824–1.141) | 0.981 (0.834–1.155) | 0.962 (0.817–1.132) | |
| Inactive | 1.293 (1.096–1.525) | 1.293 (1.096–1.526) | 1.140 (0.963–1.351) | |
| Pulmonary embolism | Regularly active | Reference | Reference | Reference |
| Weekend warrior | 1.041 (0.880–1.230) | 1.057 (0.894–1.250) | 1.024 (0.866–1.211) | |
| Inactive | 1.568 (1.329–1.850) | 1.579 (1.338–1.864) | 1.313 (1.109–1.555) | |
| Mortality risk in the VTE population | ||||
| All‐cause death | Regularly active | Reference | Reference | Reference |
| Weekend warrior | 1.213 (0.838–1.755) | 1.112 (0.768–1.609) | 1.148 (0.792–1.663) | |
| Inactive | 2.340 (1.667–3.285) | 2.346 (1.666–3.304) | 2.023 (1.423–2.877) | |
The weekend warrior pattern was defined as MVPA ≥150 min/wk (guideline‐based) with ≥50% concentrated on 1–2 d/wk; regularly active pattern was defined as MVPA ≥150 min/wk (guideline‐based) with ≥50% distributed on >2 d/wk; inactive group was defined as <150 min/wk (guideline‐based) of MVPA. Model 1 was adjusted for age, sex, and race and ethnicity. Model 2 was adjusted for age, sex, race and ethnicity, Townsend Deprivation Index, education level, and employment status. Model 3 was adjusted for age, sex, race and ethnicity, Townsend Deprivation Index, education level, employment status, body mass index, smoking status, alcohol drinking, healthy diet score, history of aspirin use, diabetes, hypertension, hyperlipidemia, and malignancy. HR indicates hazard ratio; MVPA, moderate‐to‐vigorous intensity physical activity; and VTE, venous thromboembolism.
Associations Between PA and Mortality Risk in the VTE Population
Among 3019 participants with established VTE, 338 deaths occurred during follow‐up. Figure 1D showed the inactive group had the highest cumulative mortality risk, with rates of 15.08 per 1000 person‐years, compared with 7.86 for the WW group and 6.46 for the regularly active group (Table 2). Multivariable‐adjusted analysis revealed that both active PA groups were independently linked to a substantial decrease in all‐cause death relative to the inactive group (WW: HR, 0.567 [95% CI, 0.438–0.734]; regularly active: HR, 0.494 [95% CI, 0.348–0.703]). Furthermore, when using the regularly active group as the reference, the WW pattern displayed a statistically comparable mortality risk (HR, 1.148 [95% CI, 0.792–1.663]; Table 3).
Sensitivity Analyses
Subgroup analyses demonstrated that the protective effects of WW and regularly active patterns were largely consistent across age, Townsend Deprivation Index, employment, body mass index, and smoking status (Table S3). Significant effect modification by sex was observed for the risk of VTE and PE. The WW pattern was showing stronger protective effects in women than men (Figure 2). We further substantiated the validity of these results via a series of sensitivity assessments (Tables S4 through S9). Specifically, the associations with VTE incidence and death remained consistent after excluding cases occurring within the first 2 years of follow‐up, performing a complete‐case analysis, redefining PA patterns on the basis of alternative MVPA volume thresholds (25th, 50th, and 75th percentiles), or additionally adjusting for metabolic biomarkers.
Figure 2. Associations between different physical active patterns and VTE incidence and death stratified by age and sex.
Data are presented as hazard ratios (95% CIs). Models were adjusted for age, sex, race and ethnicity, Townsend Deprivation Index, education level, employment status, body mass index, smoking status, alcohol drinking, healthy diet score, history of aspirin use, diabetes, hypertension, hyperlipidemia, and malignancy. DVT indicates deep vein thrombosis; PE, pulmonary embolism; and VTE, venous thromboembolism.
DISCUSSION
In this prospective cohort, we found that, in comparison with inactive individuals, the WW pattern is linked to a lower risk of VTE. Moreover, we demonstrated that the WW pattern not only offers protection against the onset of VTE but also exerts a significant protective effect against death among patients with VTE. Importantly, this beneficial correlation was more pronounced in women. The findings of this study suggest that engaging in MVPA 1 to 2 times per week can effectively reduce VTE risk and enhance survival outcomes, particularly among female populations.
Our findings align with and extend the recent studies supporting PA as a protective factor against VTE. 26 A previous meta‐analysis of 14 prospective cohort studies with 1 286 295 participants identified that, relative to the least active group, individuals with the highest PA levels demonstrated a 13% reduction in VTE (relative risk, 0.87 [95% CI, 0.79–0.95]). 11 Our findings extend these observations by demonstrating that concentrated activity patterns can achieve similar protective effects on VTE incidence and death across diverse demographic subgroups. Multiple studies on the WW pattern in cardiovascular outcomes support this. Previous studies have shown that accumulating MVPA over a condensed period of 1 to 2 days can significantly reduce the risks of atrial fibrillation, myocardial infarction, heart failure, and stroke. 8
Notably, there remains a paucity of research specifically examining the association between PA and mortality outcomes among patients with VTE. Preliminary evidence was provided by a recent population‐based cohort study, which observed that PA correlated with a 28% decrease in mortality risk over a decade‐long follow‐up period among those with VTE. 27 However, the reliance on self‐reported PA may lead to overestimation and consequent misclassification. 28 Additionally, the research did not account for the distribution of MVPA throughout the week. Similar to this study, our study identified a beneficial association between regular PA and diminished mortality risk in patients with VTE. More importantly, we discovered that the WW pattern also exerts a protective effect against death in patients with VTE, with an efficacy comparable with that of regular PA. Consequently, these findings suggest that accumulating the recommended volume of activity in fewer, more intense sessions is a viable strategy, providing clinicians with greater flexibility when prescribing exercise to patients who face time constraints during the workweek.
The specific biological pathways explaining the correlation between the WW pattern and VTE are not fully understood. Several pathways may be involved. First, intensive exercise significantly activates the skeletal muscle pump, improving blood flow back to the heart and preventing venous obstruction. These circulatory improvements may persist throughout the week. 7 Second, such concentrated activity may also promote endothelial function by increasing nitric oxide bioavailability and upregulating antithrombotic mediators like tissue plasminogen activator and prostacyclin, thereby mitigating prothrombotic risk factors. 29 Furthermore, the WW pattern might exert systemic anti‐inflammatory effects by suppressing proinflammatory cytokines, including interleukin‐6 and tumor necrosis factor‐α, which are recognized to facilitate platelet activation and endothelial cell activation. 30
The demonstrated equivalence of the WW pattern in preventing VTE carries profound public health implications. These findings support providing flexible exercise recommendations for time‐constrained individuals, aligning with the European Association of Preventive Cardiology principles for individualized exercise prescription. 31 Furthermore, given its significant reduction in VTE mortality risk and a mechanistic benefit profile similar to high‐intensity interval training, 32 clinicians should encourage VTE survivors to adopt this concentrated activity pattern to improve clinical outcomes. Considering the pattern's pronounced efficacy in women and its inherent cost effectiveness, the WW model holds significant strategic value in the realm of cardiovascular prevention.
This study has notable strengths, including the use of wrist‐worn accelerometers to objectively measure PA, reducing recall bias and misclassification common in self‐reported questionnaires. Additionally, the large‐scale prospective design with >11 years of follow‐up provides strong statistical power to evaluate the effects of activity patterns on VTE incidence and postdiagnosis death, while accounting for various confounding factors. Several limitations must be acknowledged. First, the observational nature of the research design limits the determination to establish causal inferences. Second, our analysis was restricted to participants in the accelerometer substudy, which may have introduced additional selection bias. In addition, the low response rate of UK Biobank and the predominantly White composition of the study population may further limit generalizability. Participants included in the primary analyses generally had a more favorable socioeconomic and health profile, potentially reflecting a healthy volunteer effect. Therefore, caution is warranted when generalizing these findings to broader populations. Third, since PA was assessed at only 1 time point, the study was unable to capture behavioral changes during the follow‐up period.
CONCLUSIONS
Our study suggests that the WW pattern is associated with lower risks of VTE incidence and all‐cause death, with associations comparable with those observed for more evenly distributed activity patterns. These findings support the potential value of flexible PA accumulation strategies for individuals with time constraints or other barriers to being active on most days of the week. Future research should aim to refine exercise guidelines, understand biological mechanisms, and assess clinical application and cost effectiveness in various health care systems.
Sources of Funding
None.
Disclosure
None.
Supporting information
Tables S1–S9
Figure S1
Data S1. Supplemental Methods
STROBE Statement—Checklist
Acknowledgments
This research has been conducted using the UK Biobank Resource under Application Number 1210686.
Author contributions: Dr He: conceptualization, investigation, formal analysis, data curation, writing—original draft, supervision, writing—review and editing. Dr Sun: methodology, validation, writing—original draft, writing—review and editing. Dr Yao: resources, investigation, writing—review and editing. Dr Han: conceptualization, supervision, writing—review and editing.
This manuscript was sent to Charalambous C. Charalambous, PhD, Assistant Editor, for review by expert referees, editorial decision, and final disposition.
Supplemental Material is available at https://www.ahajournals.org/doi/suppl/10.1161/JAHA.126.050774
For Sources of Funding and Disclosures, see page 9.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Tables S1–S9
Figure S1
Data S1. Supplemental Methods
STROBE Statement—Checklist
Data Availability Statement
Data are available in a public, open‐access repository. This research was conducted using the UK Biobank Resource under Application Number 1210686. The UK Biobank data are available on application to the UK Biobank (www.ukbiobank.ac.uk/).