Cardiovascular disease, 24-h movement behaviors and all-cause mortality: a compositional mediation analysis based on a prospective cohort

Abstract

Objectives

We aimed to investigate how 24-h movement behaviors mediated the association between cardiovascular disease (CVD) and mortality, and to determine 24-h time-use patterns across different mortality risk strata for CVD patients.

Methods

The study incorporated 90,858 UK Biobank adults (with a median age of 57 years, 56.2% female and 30.7% CVD patients) who undertook an accelerometer assessment. Cox compositional mediation models were used to determine the mediating effects of 24-h movement behaviors. The 24-h time-use patterns at varying risks were determined using risk stratification based on predicted mortality through isotemporal substitution models.

Results

During a median follow-up of 13.4 years, 3047 deaths were recorded. The total indirect effect of CVD on mortality through 24-h movement behaviors was statistically significant with the mediation proportion being 16.9% for moderate-to-vigorous physical activity (MVPA) and 1.1% for sedentary behavior (SB). The 24-h time-use pattern of CVD patients with the low mortality risk was predicted to comprise 433, 606, 310, 91 min/day on sleep, SB, light-intensity physical activity and MVPA, respectively. Physical activity levels progressively decreased with rising mortality risk. CVD patients at high mortality risk were expected to gain 1.8 years of life by reallocating daily time to match the 24-h time-use pattern of those at low risk.

Conclusion

The association between CVD and mortality is mediated by 24-h movement behaviors, particularly by MVPA and SB. For CVD patients, tailoring individual physical activity programs to 24-h time-use patterns at lower risk levels could serve as an effective behavioral intervention strategy for extending lifespan.

Graphical abstract

The top left shows the study timeline and main measurement. The top right shows the analytical workflow. In the bottom demonstrate the main results of the study. a. The mediating effect and effect proportion of 24-h movement behaviors between CVD and mortality. b. CVD patients were stratified into 4 groups by predictive ranking quartiles and the their 24-h movement behaviors were described, respectively. The years of life gained by adopting lower-risk patterns at age ≥45 were calculated for CVD patients with high risk. Abbreviations: CVD, cardiovascular disease; LPA, light-intensity physical activity; MACE, major adverse cardiovascular events. MVPA, moderate-to-vigorous intensity physical activity. SLP, sleep; SB, sedentary behavior.

Highlights

• •The 24-h movement behaviors were found to mediate 17.5% of the association between CVD and mortality, with a particular emphasis on MVPA and SB.
• •A pattern of 433, 606, 310, and 91 min/day spent on SLP, SB, LPA and MVPA was linked to low mortality risk for CVD patients.
• •Prolonging lifespan could be achievable by engagement in a preferable daily combination of 24 h for CVD patients.
• •Risk-based 24-h patterns may serve as progressive behaviors intervention targets in sequential physical activity program.

Abbreviations

CVD

Cardiovascular disease

LPA

Light-intensity physical activity

MACE

Major adverse cardiovascular events

MVPA

Moderate-to-vigorous intensity physical activity

SB

Sedentary behavior

SLP

Sleep

PA

Physical activity

1. Introduction

Cardiovascular disease (CVD) is the leading cause of death and accounts for nearly one third of deaths globally.¹ Physical activity (PA) is an effective cardiac intervention for reducing the mortality risk. Moreover, PA is significantly associated with biological aging indicators, such as telomere length, DNA methylation-predicted epigenetic clocks, which are all associated to the mortality.^2,3 However, prolonged sedentary time and reduced PA time are observed markedly in CVD patients.4, 5, 6 Given that behavioral changes after a CVD event are associated with all-cause mortality,^7,8 they may influence the association between CVD and mortality.

Traditional mediation studies focus on isolating single behavior in the relationships between chronic diseases and mortality.^9,10 The 24-h movement behaviors, including sleep (SLP), sedentary behavior (SB), light-intensity physical activity (LPA), and moderate-to-vigorous physical activity (MVPA), should be treated as a compositional unity, since they are mutually exclusive within 24-h cycle.¹¹ However, the compositional mediation of 24-h movement behaviors in the association between CVD and all-cause mortality remains unclear. Moreover, the effect of 24-h movement behaviors on mortality and life expectancy in CVD patients warrants further research, with an existing study in the heart failure population constrained by a small sample size.¹² Additionally, while existing clinical guidelines emphasize that CVD patients should engage in appropriate amounts of MVPA to derive benefits, there is a paucity of evidence to inform the development of progressive targets to optimize their daily behaviors.

To address these gaps, we aim to: (i) investigate the compositional mediating role of 24-h movement behaviors between CVD and mortality, (ii) explore the dose-response relationship between reallocated time across different behavior and mortality in both CVD and non-CVD groups; and (iii) determine 24-h time-use patterns across varying mortality risk levels in CVD patients and their impact on residual life expectancy.

2. Methods

2.1. Study population

Data were derived from UK Biobank. Briefly, UK Biobank was a large-scale population-based prospective cohort and recruited more than 500,000 adults aged from 40 to 69 years between 2006 and 2010.¹³ The UK Biobank project had obtained an ethical approval (REC reference: 21/NW/0157). Written informed consent was obtained from each participant before data collection. A subset of 103,669 participants accepted movement behaviors assessment through a wrist-worn accelerometer. After excluding poor-quality data and missing value on covariates, a total of 90,858 participants were included in the current study. The study design is presented in Graphical Abstract and the flowchart of participant selection is shown in Fig. S1.

2.2. Definition of cardiovascular disease

CVD at baseline was defined as: (i) presence of diseases within the circulatory system documented in hospital inpatient data prior to recruitment; (ii) having a history of CVD related operation procedure defined as valve replacement, coronary artery bypass graft and percutaneous transluminal coronary angioplasty; (iii) self-reported vascular or heart problems ascertained through verbal interviews. Considering that hypertension is the most common and modifiable subtype, while major adverse cardiovascular events (MACE) are the leading cause of cardiovascular death.^14,15 In addition to overall CVD population, we also defined the hypertension and MACE groups (see Table S1 for detailed description).

2.3. Assessment of 24-h movement behaviors

Accelerometry subsample participants were invited to wear a wrist accelerometer (AX3, Axivity, UK) to record daily movement behaviors for a week, which were completed between June 2013 and January 2016. The preliminary work on raw accelerometer data processing has been previously described.¹⁶ We defined compositional 24-h movement behaviors as the daily averaged time spent on SLP, SB, LPA and MVPA. Because accelerometer-derived cut-points cannot reliably distinguish SB from SLP, we adopted established “difference method" for defining the 24-h movement composition, consistent with previous studies.^17,18 The fraction where Euclidean Norm Minus One (ENMO) were in a range of ≤30 mg (excluding self-reported SLP), 31-125 mg and >125 mg were classified as SB, LPA or MVPA, respectively. SLP was obtained from touchscreen questionnaire, asking “About how many hours sleep do you get in every 24 h? (please include naps)". Log-ratio expectation-maximisation (lrEM) imputation was applied to replace zero values with extremely small but non-zero values.

2.4. All-cause mortality ascertainment

Follow-up was primarily conducted by linking to available national routine data from the UK. Mortality data were received from the National Health Service (NHS) England for participants in England and Wales and from the NHS Central Register (NHSCR) for participants in Scotland (more detailed information can found on https://biobank.ndph.ox.ac.uk/showcase/refer.cgi?id=115559). Data for survivors were censored on August 10, 2022, when the data was downloaded.

2.5. Covariates

Referring to previous population-based studies focusing on 24-h movement behaviors, this study adjusted for a set of key covariates to account for potential confounding.^19,20 At baseline recruitment, basic characteristics and health condition were collected. All analyses in this study adjusted for covariates including age, sex, ethnicity, residence location, body mass index (BMI) categories, Townsend deprivation index, smoking status, drinking status, occupational status, aspirin medication, cholesterol lowering medication, chronic kidney diseases, diabetes mellitus, depression, polygenic risk score for CVD. A directed acyclic graph (DAG) was used to visualize the assumed relationships of these variables (Fig. S2).

2.6. Statistical analysis

Baseline characteristics were described for the total sample and stratified by CVD status. Due to the compositional nature of the data, 24-h movement behaviors were reported as geometric means and percentages of the day. Given our large sample size, standardized mean differences (smd) were calculated to compare between-group characteristics, with differences larger than 0.1 considered meaningful.²¹

The Cox compositional mediation model was used to elucidate the mediation role of movement behaviors between CVD and mortality. The model was described elsewhere.^5,22 The proportional hazard assumption was confirmed by Schoenfeld residual test and no serious violations were found (Table S2). We employed bootstrap method with 1000 resamples to estimate hazard ratios (HRs) and their 95% confidence intervals. For each bootstrap replication, samples were drawn with replacement at the individual level, maintaining the full size of the original dataset. All analyses within each replicate were conducted using isometric log-ratio (ILR) transformations. Completed descriptions are provided in the Supplementary Methods.

To assess the dose-response relationship between 24-h movement behaviors and mortality, Cox isotemporal substitution models were employed. In these models, time was reallocated between each movement behavior and the residual time (all remaining time of other behaviors).²³ Substitution models were applied separately to the CVD and non-CVD groups with the mean 24-h movement behaviors of each group serving as the reference. The interaction effects were examined using a likelihood ratio test.

Subsequently, risk prediction analyses were conducted using Cox isotemporal substitution model within the CVD group. Risk levels were categorized into high, median high, median low and low based on the quartile distribution of predictive rankings. 24-hour time-use patterns were presented as compositional geometric means among populations at different mortality risk. Next, the Gompertz proportional hazards model was used to evaluate the differences in residual life expectancy associated with adherence to 24-h time-use patterns across different risk levels. Residual life expectancy was calculated as the area under the survival curve up to age 100, conditional on being ≥45 years (1-year interval).²⁴ The survival curve was re-estimated after substituting the 24-h movement behaviors pattern of high-risk level by that of other risk levels. The years of life gained or lost were calculated based on the changes in residual life expectancy (see Supplementary Methods).

All analyses were performed on overall, hypertension and MACE groups. We also conducted subgroup analyses stratified by sex. All analyses were conducted in SAS 9.4 (SAS Institute, Cary, NC, USA) and R 4.3.1 (R Foundation, Vienna, Austria). The threshold for statistical significance was set at 5%.

2.7. Sensitivity analyses

We conducted several sensitivity analyses to evaluate the robustness of our results. First, participants with self-reported poor health at baseline were excluded. Second, participants with extremely large values (>99th percentile) of movement behaviors were excluded. Third, to address missing data concerns, we conducted multiple imputations using chained equations on covariates, leveraging mice R package. Fourth, we substituted zero values in the movement behaviors dataset with a small non-zero value (0.01), instead of utilizing imputation techniques like lrEM. Fifth, we excluded CVD patients whose condition was ascertained solely by self-report (N=1330). Sixth, we excluded non-CVD participants who developed a CVD incidence prior to movement assessment (N = 6351).

3. Results

3.1. Descriptive characteristics

Table S3 presents the baseline characteristics and 24-h movement behaviors of 90,858 participants by the presence or absence of CVD at baseline. Participants had a median age of 57 (IQR: 50-62) years, with the majority being white (92.5%) and female (56.2%). Among them, 31,730 (30.7%) had a diagnosis of CVD. Compared with participants without CVD, those with CVD were more likely to be older, male, overweight or obese, retired, affected by type 2 diabetes, possessed a higher polygenic risk score (PRS) for CVD, and physically inactive (all smd>0.100). During a median follow-up of 13.4 (IQR: 12.7-14.1) years, encompassing a total of 1.21 million person-years, 3047 deaths were recorded. The characteristics of hypertension and MACE groups were described in Table S4.

3.2. The mediating effect of 24-h movement behaviors

As demonstrated in Fig. 1 and Table 1, in general, MVPA was negatively associated with mortality rate, while SB was positively associated with it. Furthermore, we observed that overall CVD patients tended to spend less time on MVPA (β: −0.055; 95% CI: −0.064 to −0.047) when compared with non-CVD participants, and this further increased mortality risk (indirect HR: 1.032; 95% CI: 1.026-1.039, mediation proportion: 16.9%). SB also mediated the association between CVD and mortality. For example, the increasing SB (β: 0.007; 95% CI: 0.004-0.009) in overall CVD patients accounted for 1.1% of the total effect in the association. LPA and SLP showed no indirect effect of CVD on mortality. On average, around 20% of the total effect of CVD on mortality was significantly mediated by compositional movement behaviors. It is worth mentioning that markedly stronger mediation through MVPA were detected in hypertension and MACE subgroup.

Fig. 1.

Associations between overall cardiovascular disease (CVD), hypertension, major adverse cardiovascular events (MACE) and mortality mediated by 24-h movement behaviors Shown are regression coefficients from Cox compositional mediation model. Bold means statistically significant. Abbreviations: LPA, light-intensity physical activity; MVPA, moderate-to-vigorous intensity physical activity. SLP, sleep; SB, sedentary behavior.

Table 1.

The effects of CVD, hypertension, MACE on all-cause mortality mediated by 24-h movement behaviors.

Exposure	Effects	HR (95% CI)	Proportion (%)
Overall CVD	Total effect	1.206(1.119,1.312)	100.0
	Direct effect	1.167(1.082,1.269)	82.5
	Total indirect effect	1.033(1.027,1.040)	17.5
	Indirect effect through SLP	1.000 (0.999, 1.000)	-0.1
	Indirect effect through SB	1.002(1.001,1.003)	1.1
	Indirect effect through LPA	0.999 (0.998, 1.000)	-0.4
	Indirect effect through MVPA	1.032(1.026,1.039)	16.9
Hypertension	Total effect	1.227(1.128,1.338)	100.0
	Direct effect	1.175(1.083,1.282)	78.8
	Total indirect effect	1.044(1.037,1.051)	21.0
	Indirect effect through SLP	0.999 (0.999, 1.000)	-0.5
	Indirect effect through SB	1.003(1.001,1.005)	1.5
	Indirect effect through LPA	0.999 (0.997, 1.001)	-0.5
	Indirect effect through MVPA	1.042(1.035,1.050)	20.1
MACE	Total effect	1.643(1.128,1.935)	100.0
	Direct effect	1.485(1.083,1.753)	79.6
	Total indirect effect	1.107(1.037,1.127)	20.5
	Indirect effect through SLP	1.001 (0.999, 1.003)	0.2
	Indirect effect through SB	1.006(1.001,1.011)	1.2
	Indirect effect through LPA	0.999 (0.997, 1.006)	-0.2
	Indirect effect through MVPA	1.100(1.035,1.121)	19.2

Abbreviations: CVD, cardiovascular disease; LPA, light-intensity physical activity; MACE, major adverse cardiovascular event; MVPA, moderate-to-vigorous intensity physical activity; SLP, sleep; SB, sedentary behavior.

3.3. Dose-response relationship between reallocated 24-h movement behaviors and mortality

The effects of reallocated time of each behavior within 24 h stratified by CVD status are shown in Fig. 2. Generally, when reallocation time was replaced by residual time, MVPA and LPA showed a reverse J-shape relationship to mortality, with MVPA showing a steeper curve. SB showed a roughly linear positive association with death, while SLP was not associated with mortality. The effect of reallocated MVPA significantly differed between the CVD and non-CVD groups (all P for interaction <0.05), with reduced MVPA in the CVD group being associated with a high risk of mortality.

Fig. 2.

Dose-response relationship between reallocated 24-h movement behaviors and all-cause mortality by CVD status a-d In overall CVD and non-CVD group. e-h In hypertension and non-CVD group. i-l In MACE and non-CVD group. The median line means HRs, while the shaded areas indicate 95%CI. Each curve represents an increase in the time spent on this behavior while the remaining behavior decreases accordingly. The reference composition for each group is the mean 24-h movement behaviors. Abbreviations: CVD, cardiovascular disease; LPA, light-intensity physical activity; MACE, major adverse cardiovascular events. MVPA, moderate-to-vigorous intensity physical activity. SLP, sleep; SB, sedentary behavior.

3.4. The 24-h time-use patterns across groups with different risk levels and the differences in residual expectancy

In CVD population, all participants were stratified into four groups according to predicted risk levels (Fig. 3). The mean 24-h time-use pattern for high-risk CVD patients was 437 min for SLP, 716 min for SB, 255 min for LPA, 31 min for MVPA per day. As mortality risk decreased, there was a progressive decline in SB and an increase in both LPA and MVPA, resulting in a 24-h time-use pattern of 433 min for SLP, 606 min for SB, 310 min for LPA, 91 min for MVPA per day for low-risk CVD patients. Similar patterns were observed across different risk levels in both the hypertension and MACE groups.

Fig. 3.

The 24-h time-use patterns under different risk levels and the disparity in residual life years by CVD status. a, c, e The 24-h time-use patterns under different risk levels in overall CVD, hypertension and MACE group. b, d, f The years of life gained by adhering patterns at lower risk levels for overall CVD, hypertension, MACE patients with high risk pattern. Abbreviations: CVD, cardiovascular disease; LPA, light-intensity physical activity; MACE, major adverse cardiovascular events. MVPA, moderate-to-vigorous intensity physical activity. SLP, sleep; SB, sedentary behavior.

When examining the differences in residual life years, we found that all combinations were associated with a longer lifespan compared to the high risk pattern in individuals with CVD at age ≥45 (Fig. 3). For all CVD patients with high risk of death, adhering to time-use patterns associated with median high, median low or low risk was linked to an additional 0.8, 1.2 or 1.8 years of life, respectively. The benefits of adopting lower-risk patterns were slightly greater for patients with MACE. To facilitate clinical operability, we also provided the results of relative risk reduction of all-cause mortality associated with replacing 10 to 60 min (at 10-min intervals) of remaining behaviors to increase MVPA gradually (Table S5). For CVD patients at high mortality risk, only a 10-min increase in MVPA corresponded to an approximately 16% lower mortality risk.

3.5. Subgroup analyses and sensitivity analyses

In the compositional mediation model, MVPA showed slightly greater indirect effect in the association between overall CVD and mortality for females than males (mediation proportions for males versus females: 18.3% and 15.7%, Figs. S3–S4), but no significant sex difference was observed (P for interaction = 0.800). The dose-response relationships for both sexes showed similar trends (Figs. S5–S6). Adopting 24-h time-use patterns with lower risks resulted in a greater gain in life years for males with hypertension, while females with MACE experienced a similar benefit (Fig. S7).

The robustness of our primary results was confirmed through various sensitivity analyses (see Fig. S8 and Table S6).The effect size and effect proportion of indirect effect were not largely changed. The years of life gained observed in these sensitivity analyses followed a consistent trend with the main analysis but were slightly higher when imputing missing covariate data, excluding self-reported CVD participants in CVD group and excluding CVD cases between baseline and movement assessment in non-CVD group (Fig. S9).

4. Discussion

In this cohort study, we observed that 24-h movement behaviors mediated the association between CVD and mortality, with a total indirect effect of 17.5%. MVPA was the strongest mediator, followed by SB. The modifying effects of CVD status on the mortality associated with 24-h movement behaviors were also found, highlighting the benefits of increasing MVPA and decreasing SB in CVD patients. Furthermore, the novelty of our study is that we predicted 24-h time-use combinations for CVD patients with varying mortality risks and evaluated the impact of their combinations on expected lifespan.

The effectiveness of exercise-based cardiac rehabilitation in reducing cardiovascular mortality has been consistently approved.²⁵ These findings are biologically plausible via metabolic and inflammatory regulation. Exercise improves multi-tissue metabolic adaptation (glucose homeostasis, insulin sensitivity, lipid metabolism and mitochondrial function) to boost cardiometabolic and overall health,^26,27 and exerts anti-inflammation effect by modulating IL-6, TNF-α, CRP, and IL-10.28, 29, 30 Epidemiological studies verify that these pathways mediated the association between MVPA and mortality, including in CVD patients.31, 32, 33 Conversely, prolonged SB links to dyslipidemia, hyperinsulinemia, and low-grade inflammation, thereby contributing to adverse health outcomes.34, 35, 36

Current guidelines jointly encourage stable CVD patients to undertake MVPA for 30-60 min/day, more than 5 days per week.37, 38, 39 However, we consistently observed that CVD patients often show lower levels of PA throughout the day. Possible explanations include inadequate illness perceptions, which may hinder the adoption of health promoting behaviors⁴⁰; the influence of psychophysiological factors, such as fear of falling, concern about disease recurrence, and lack of self-efficacy40, 41, 42; and restriction of physical condition.^43,44 In fact, CVD patients with limited physical capability are encouraged to gradually increase their level of PA as part of their functional rehabilitation. For example, outpatients recovering from acute coronary syndrome are advised to start low-to moderate-intensity recreational activities after 8-10 weeks following the cardiac event.³⁷ To improve the feasibility of exercise, the American Heart Association advocates for integrating PA into daily routine.³⁸ Therefore, in addition to raising the awareness about the risks of physical inactivity and encouraging PA among CVD patients, it is also essential to establish progressively increasing activity goals, considering their daily activity arrangements.

To address this challenge, we predicted the 24-h time use for patients at different risk levels from the perspective of behavioral substitution. Although modelling suggested the time use pattern observed under low risk of death is theoretically most effective for prolonging lifespan for CVD patients, immediately adopting it may not be achievable and realistic. In clinical practice, the pattern of the median-high risk can serve as an initial, achievable goal and gradually achieving the ultimate goal for long-term maintenance of low-risk pattern. Therefore, such a sequential PA program that considers patients' capability and health condition might improve adherence and effectiveness. To enhance clinical operability, clinicians can adopt a stepwise goal-setting approach after comprehensive risk and exercise capacity assessments for patients. For example, the intervention of time arrangement can commence by introducing short bouts of MVPA, as our data suggests even a 10-min increment in MVPA confers considerable relative risk reduction.

There are several strengths in our study. Existing research predominantly focused on the influences of single behavior. Beyond that, we treated 24-h movement behaviors as a whole and took into account for their intra-relationship. Furthermore, the use of device-measured PA helps to reduce subjective bias to some extent. Another strength of the study is that we used parametric survival analysis models and quantified the absolute effects rather than just the relative effect, which provides clearer and more actionable insights.

However, our study has some limitations. First, despite adjusting for several covariates in the models, there may still be potential confounders that we did not account for. Second, while we assumed that PA changed after the onset of CVD, we did not confirm this causal relationship. Third, CVD-related disease characteristics (e.g., severity, duration since the most recent event) and clinical management practices (e.g., secondary prevention interventions) may influence behavioral changes in patients with CVD. However, these factors were not accounted for in the present analysis and should be considered in future studies. Fourth, the relatively high proportion of censoring and good health condition of this population are likely attributable to their superior socioeconomic status. Our results need to be verified in developing countries. Fifth, the physical assessment was conducted only once, and changes in movement behaviors were not considered. Thus, it precluded a truly longitudinal examination of the association with CVD, despite the prospective nature of our analysis. Future studies should focus more on long-term behavioral trajectories affected by diseases and their relation to health outcomes. Sixth, self-reported SLP, which was used to derive SB via the difference method, is susceptible to overestimation due to recall bias.^45,46 This measurement error would propagate to SB, likely resulting in an underestimation of SB. However, no evidence of differential bias between the CVD and non-CVD groups was identified, suggesting that the group-specific associations were likely not substantially biased.

5. Conclusion

In conclusion, 24-h movement behaviors mediated the association between CVD and mortality, with MVPA and SB having the major mediating effect. CVD patients who replace other behaviors with additional MVPA experience greater reductions in mortality risk compared to non-CVD individuals. Furthermore, the 24-h time-use patterns associated with different mortality risks could serve as targets for progressive behaviors interventions in sequential PA programs for CVD patients.

Data statement

Data are available only to researchers who submitted an application and received approval to access the UK Biobank at https://www.ukbiobank.ac.uk/.

Declaration of Generative AI and AI-assisted technologies in the writing process

Nothing to disclose.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A. Supplementary data

The following are the Supplementary data to this article: