Sedentary Behavior and Cardiac Events and Mortality After Hospitalization for Acute Coronary Syndrome Symptoms: A Prospective Study.

Sedentary Behavior and Cardiac Events and Mortality After Hospitalization for Acute Coronary Syndrome Symptoms: A Prospective Study - PMC Skip to main content An official website of the United States government Here's how you know Here's how you know Search Log in Primary site navigation Search Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more: PMC Disclaimer | PMC Copyright Notice Circ Cardiovasc Qual Outcomes . Author manuscript; available in PMC: 2026 Jun 1. Published in final edited form as: Circ Cardiovasc Qual Outcomes. 2025 May 19;18(6):e011644. doi: 10.1161/CIRCOUTCOMES.124.011644 Sedentary Behavior and Cardiac Events and Mortality After Hospitalization for Acute Coronary Syndrome Symptoms: A Prospective Study Keith M Diaz 1 , Benjamin D Boudreaux 1 , Chang Xu 1 , Gabriel J Sanchez 1 , Margaret E Murdock 1 , Gaspar J Cruz 1 , Ammie Jurado 1 , Alvis Gonzalez 1 , Melinda J Chang 1 , Allie Scott 1 , Sung AJ Lee 1 , Emily K Romero 1 , Alexandra M Sullivan 1 , Andrea T Duran 1 , Joseph E Schwartz 1, 2 , Ian M Kronish 1 , Donald Edmondson 1 Author information Article notes Copyright and License information 1 Center for Behavioral Cardiovascular Health, Department of Medicine, Columbia University Medical Center, New York, NY 10032 2 Department of Psychiatry and Behavioral Health, Stony Brook Renaissance School of Medicine, Stony Brook, NY 11794 ✉ Address for Correspondence: Keith M. Diaz, Columbia University Medical Center, 622 West 168th Street, PH9-301, New York, NY 10032, kd2442@columbia.edu Issue date 2025 Jun. PMC Copyright notice PMCID: PMC12173790  NIHMSID: NIHMS2064839  PMID: 40384460 The publisher's version of this article is available at Circ Cardiovasc Qual Outcomes Abstract Background: Patients hospitalized with symptoms of acute coronary syndrome (ACS) remain at high risk for adverse events post-discharge, highlighting a need for modifiable therapeutic targets. The role of sedentary behavior in this risk and the potential benefits of replacing sedentary time with other activities remain unclear. This study examined the association between sedentary behavior and 1-year cardiac events/mortality among patients evaluated for ACS and estimated risk reductions from substituting alternative activities for sedentary time. Methods: Patients presenting to the emergency department of a New York City hospital with ACS symptoms were enrolled from 2016–2020. Sedentary behavior, light-intensity physical activity (LIPA), moderate-vigorous physical activity (MVPA), and sleep were measured via wrist-mounted accelerometer worn for 30-days post-discharge. Cardiac events and all-cause mortality were ascertained 1-year post-discharge via participant contact, electronic health records, and the Social Security Death Index. Participants were categorized into tertiles of sedentary time, with Tertile 1 representing the lowest sedentary time and Tertile 3 the highest. Cox proportional hazards regression models were used to evaluate associations. Results: Of 609 participants (mean age: 62 years; 52% male, 58% Hispanic), 8.2% experienced a cardiac event or died within one year. Mean sedentary time was 13.6 h/d (SD, 1.8). Sedentary time was associated with increased risk of cardiac events/mortality (Tertile 2: HR=0.95, 95% CI: 0.37–2.40; Tertile 3: HR= 2.58, 95% CI: 1.11–6.03; P-Trend=0.011). In isotemporal substitution analyses, replacing 30 minutes of sedentary time (referent) with sleep (HR=0.86, 95% CI: 0.78–0.95), LIPA (HR=0.49, 95% CI: 0.32–0.75), or MVPA (HR=0.39, 95% CI: 0.16–0.96) was associated with lower cardiac event/mortality risk. Conclusions: Sedentary behavior was associated with increased risk of 1-year cardiac events/mortality among patients evaluated for ACS. Replacing sedentary behavior with sleep, LIPA, or MVPA was associated with lower risk. These findings highlight reducing sedentary behavior as a potential strategy to improve post-hospitalization outcomes. Keywords: Sedentary behavior, cardiac events, acute coronary syndrome, isotemporal substitution, post-hospitalization outcomes INTRODUCTION Over 11 million patients annually present to U.S. emergency departments (ED) with chest pain due to symptoms suggestive of acute coronary syndrome (ACS). 1 An estimated 65% are subsequently admitted, comprising a quarter of all emergency admissions. 2 Patients with a coronary ischemic etiology (i.e., ACS-specific diagnosis) face substantial long-term morbidity and mortality risk. 3 Even in clinical trials where patients receive optimal medical treatment, disease burden and mortality risk remain high, suggestive that ACS carries residual risk that medication and revascularization cannot completely reverse. 4 – 6 Moreover, evidence suggests patients hospitalized with symptoms suggestive of ACS, but who ultimately rule out for ACS (i.e., non-specific chest pain, NSCP) do not have benign conditions and are also at risk of adverse outcomes including cardiovascular events. 7 – 10 As such, identification of novel modifiable targets to increase survival, reduce adverse events, and improve quality of life across the full spectrum of patients hospitalized for symptoms of ACS ranks among the highest priority evidence gaps. 11 – 13 Prolonged sedentary behavior is associated with an increased risk of cardiovascular disease (CVD) and mortality. 14 Experimental evidence suggests periods of prolonged sedentary behavior elicit detrimental cardiometabolic effects (inflammation, dyslipidemia, endothelial dysfunction, elevated procoagulant activity, impaired glucose tolerance) that are not offset by exercise. 14 Accordingly, physical activity recommendations for the general population have expanded beyond promoting moderate-vigorous physical activity (MVPA) and also advocate for reductions in sedentary time. 15 , 16 Patients with ACS are particularly prone to high volumes of sedentariness after hospitalization; accruing, on average, 12–13 hours/day. 17 .This raises the question as to whether reducing sedentary behavior may be an important therapeutic target for secondary prevention and rehabilitation of patients presenting with ACS symptoms. No existing secondary prevention guidelines for clinical populations hospitalized with acute chest pain mention sedentary behavior as a risk factor to be modified. Understanding the relationship between sedentary behavior and adverse outcomes across the full spectrum of patients presenting with ACS symptoms is necessary to inform potential modifications to secondary prevention guidelines. Existing evidence evaluating sedentary behavior as a prognostic risk factor in patients with ACS is sparse. 18 Previous studies have predominantly relied on self-reported measures of sedentary behavior, assessed sedentary behavior prior to the index event, and have reported mixed findings. 19 – 21 Thus, to rectify evidence gaps, address limitations of prior studies, and discern key information necessary for actionable secondary prevention guidelines, prospective studies are needed to 1) determine the association of device-measured sedentary behavior with adverse health outcomes after hospitalization, 2) determine which features of sedentary behavior (the total volume of sedentary behavior or its accrual in prolonged, uninterrupted bouts) confers adverse risk, and 3) identify the type(s) of behaviors within the 24-hour activity cycle paradigm (sleep, light-intensity physical activity [LIPA], and MVPA) that should be substituted for sedentary time to impart health benefit. The purpose of this study was to examine the association of device-measured sedentary time and prolonged sedentary bouts with risk of 1-year cardiac events and mortality among patients presenting with ACS symptoms. We furthermore modeled changes to predicted cardiac events/mortality risk in this population when replacing sedentary time with sleep, LIPA, and MVPA to identify potential beneficial time reallocations within the 24-hour activity cycle. METHODS The data that support the findings of this study are available from the corresponding author upon reasonable request. Study Population: Participants presenting to the emergency department (ED) at Columbia University Medical Center (CUMC) with symptoms suggestive of ACS were enrolled between September 2016 and March 2020. Research staff tracked the ED electronic status board for potential patients with ACS symptoms. If a patient was identified, staff confirmed the presentation with the attending physician and invited the patient to participate. Participants were enrolled during ED evaluation or following transfer to an inpatient unit. Participants were eligible if they were ≥18 years old, fluent in English or Spanish, and were evaluated in the ED for symptoms consistent with ACS. Participants were excluded if they were unable to complete study assessments and follow-up (e.g., prisoners, life expectancy <1 year), deemed unlikely to comply with protocol (e.g., cognitive impairment), or needed psychiatric intervention. While a confirmed ACS diagnosis was not required for enrollment, approximately 25.7% of participants ultimately received an ACS diagnosis according to the ESC/ACC/AHA/WHF criteria, which include ST-elevation myocardial infarction (STEMI), non-ST-elevation myocardial infarction (NSTEMI), and unstable angina. 22 The remaining participants either ruled out for ACS or had NSCP (see Supplemental Methods ). A total of 814 participants were enrolled. Upon enrollment, participants were instrumented with an accelerometer and completed a questionnaire battery in-hospital. After excluding participants who did not return the accelerometer, had insufficient accelerometer wear, or who had missing follow-up data, a total of 609 participants comprised the analytic sample ( Figure S1 ). Table S1 shows characteristics of included versus excluded participants. All participants provided informed consent. The study was approved by the institutional review board at CUMC. Accelerometer Data Collection: A wrist-worn GENEActiv accelerometer (Activinsights) was used to measure sedentary behavior, physical activity, and sleep. The GENEActiv device has been shown to be valid and reliable for measuring sedentary behavior, physical activity, and sleep across a number of populations. 23 – 27 Participants were provided the device during hospitalization and instructed to wear the device on their non-dominant wrist continuously for 24 hours while in-hospital and at least 30 days post-discharge. Participants were provided a reminder magnet that contains a picture of the GENEActiv device to place at home. Devices were returned via mail. A sampling rate of 10Hz was used and raw acceleration data were processed using the R-package GGIR (version 2.3.0). 28 The wrist wear location was chosen to maximize participant compliance, particularly given the 30-day wear protocol, which is longer than the conventional 7-day protocol used in most studies. Sedentary time and bouts, LIPA, MVPA, and sleep time were averaged across valid wear days (≥16 hours of wear) using only data collected after hospital discharge and prior to a hospital readmission (if it occurred during wear). Accelerometer data processing methods are provided in the Supplemental Methods . Outcome Ascertainment: The primary outcome was first occurrence of a cardiac event or all-cause mortality. Cardiac events included myocardial infarction (MI), urgent coronary revascularization, or hospitalization for unstable angina per AHA/ACC criteria. 22 Outcomes were assessed by a 12-month follow-up via phone and from electronic health records. Participant (or closest contact) report of a potential event triggered medical record retrieval followed by expert adjudication. Electronic health records were also searched for hospitalizations. Two board-certified cardiologists independently adjudicated suspected cardiac events, with a third cardiologist for consensus if needed. For participants who could not be contacted or were reported deceased, the Social Security Death Index was searched to verify vital status. Statistical Analyses: Participants were stratified into tertiles according to sedentary time and, separately, mean sedentary bout length (a measure of overall prolonged, uninterrupted sedentary behavior). Cox proportional hazards models were used to calculate the hazard ratio (HR) for 1-year cardiac events and all-cause mortality associated with tertiles of sedentary time and, separately, mean sedentary bout length. Crude HRs were initially calculated. Subsequent HRs were calculated after adjustment for age and sex (model 1), with further adjustment for race/ethnicity, education, partner status, health insurance, and ACS/non-ACS diagnosis (model 2). Models were additionally adjusted for Charlson comorbidity index, GRACE risk score, left ventricular ejection fraction, and length of hospital stay (model 3), and final adjustment for MVPA (model 4). Covariates were selected based on clinical and theoretical relevance to both sedentary behavior and outcomes of interest, as well as prior literature in this field. Details of covariate measures are provided in the Supplement . Proportional hazards assumptions were confirmed with a Kolmogorov-type supremum test. Because education violated the proportional hazards assumption, this variable was included as a cross-product with follow-up time in all models. To determine whether sedentary behavior was differentially associated with cardiac events/mortality risk in patients with a confirmed ACS diagnosis (versus those who ruled out), analyses were repeated in a fully-adjusted model, testing interactions for ACS diagnosis. As a secondary analysis, the continuous dose-response association of each sedentary characteristic with cardiac events/mortality risk was evaluated in a fully-adjusted model (model 4). We examined potential nonlinearity using restricted cubic splines with the median of the lowest tertile of each sedentary characteristic set as the reference. Restricted cubic splines were fitted using 3, 4, and 5 knots, and the Akaike Information Criterion (AIC) was used to determine the best-fitting model for each sedentary behavior variable. A 3-knot model (knots placed at 10 th , 50 th , and 90 th percentiles) and 4-knot model (knots placed at the 5th, 35th, 65th, and 95th percentiles) were selected for total sedentary time and mean sedentary bout duration, respectively. Tests for nonlinearity used the likelihood ratio test, comparing the model with only the linear term to that of the model with the linear and cubic spline terms. To examine individual and joint associations of sedentary time and prolonged, uninterrupted sedentary bouts with cardiac events/mortality, participants were classified into 4 categories: low sedentary time (<14 h/d) and low prolonged sedentary bout length (<10 min/bout), low sedentary time and high prolonged sedentary bout length (≥10 min/bout), high sedentary time (≥14 h/d) and low prolonged sedentary bout length, and high sedentary time and high prolonged sedentary bout length. HRs for cardiac events/mortality were calculated for each joint category in comparison with the low–low group in a fully-adjusted model (model 4). Thresholds for sedentary time (14 h/d) and mean sedentary bout length (10 min/bout) were selected using a maximum likelihood analysis of the log-rank test statistic for cardiac events/mortality. 29 The interaction of sedentary time and sedentary bouts was also examined by including an interaction term in a seperate regression model. To evaluate whether sleep, LIPA, and MVPA are healthier alternatives to sedentary behavior, isotemporal substitution models were used to estimate the theoretical effect of substituting sedentary time with another activity (sleep, LIPA, MVPA) for the same amount of time, keeping time in other activities fixed. Details of isotemporal substitution models are provided in the eMethods in the Supplement . Briefly, in the isotemporal model, sleep, LIPA, and MVPA were included in a single model (expressed in 30-minute units) that included covariate adjustment. Sedentary time was not included in this model, and the resulting HRs estimated the effect of replacing 30 minutes of sedentary time with an equal amount of time in another activity (sleep, LIPA, or MVPA). We also fitted models that represented the association of each activity category (sedentary time, sleep, LIPA, and MVPA) with cardiac events/mortality (1) without mutual adjustment for other activity categories (single-factor models) and (2) with adjustment for selected activity categories (2-factor models). To evaluate potential for reverse causality, a sensitivity analysis was conducted excluding participants who had a cardiac event or died in the first 30 days of follow-up. As the influence of behavior change may be more proximal than a 1-year endpoint, a sensitivity analysis examining risk of cardiac events/mortality at 6 months was conducted. Finally, as potential differences in baseline risk, treatment pathways, and recovery trajectories between participants with confirmed ACS and those ruled out for ACS may introduce unmeasured confounding, a frailty model treating ACS status as a random effect was additionally conducted as a sensitivity analysis. Analyses were conducted using SAS Version 9.4 (SAS Institute Inc). We used a significance threshold of P<0.05 for main effects and P<0.10 for interaction terms, consistent with conventions in assessing potential effect modification in clinical and epidemiological studies. RESULTS Participant Characteristics: Sedentary behavior accounted for 82.8% (SD, 9.0%) of the waking day, equivalent to 13.6 h/d (SD, 1.8). The distribution of sedentary time and sedentary bout length are shown in Figure S2 . Among the 609 enrolled patients, 25.7% were diagnosed with ACS. Participant characteristics stratified by tertile of sedentary time are presented in Table 1 . On average, participants with greater sedentary time were older, more likely to be non-Hispanic Black, had a higher Charlson comorbidity index, higher GRACE risk score, and lower left ventricular ejection fraction. They also had shorter sleep duration and fewer minutes of LIPA and MVPA. Participant characteristics stratified by tertiles of mean sedentary bout length are presented in Table S2 . Table 1. Participant characteristics by sedentary time tertiles. Characteristic Tertile 1 <12.8 h/d (N=202) Tertile 2 ≥12.8 to <14.3 h/d (N=203) Tertile 3 ≥14.3 h/d (N=204) P-Value Age, years 59.8 (11.9) 62.9 (12.3) 65.3 (12.3) <0.001 Male, % 52.0 51.7 52.5 0.986 Race/Ethnicity, % . . . <0.001 Non-Hispanic White 9.0 12.5 9.7 Non-Hispanic Black 15.1 21.9 33.2 Hispanic 69.2 57.8 46.6 Other 6.6 7.9 10.4 Education, % . . . 0.524 < High School Education 35.6 33.5 28.4 High School/GED 23.8 22.2 19.6 Trade or Vocational School/Some College 18.8 17.2 24.5 College/Graduate Degree 21.3 26.6 27.0 Partner, % 43.9 37.2 38.5 0.351 Health Insurance, % 92.6 92.6 92.6 0.886 ACS Diagnosis, % 24.1 25.4 28.2 0.624 Charlson Comorbidity Index * 1.0 (0.0–2.0) 1.0 (1.0–3.0) 2.0 (1.0–4.0) <0.001 GRACE Risk Score 90.2 (29.8) 99.1 (32.9) 108.5 (32.9) <0.001 Left Ventricular Ejection Fraction, % * 58.0 (50.0–63.0) 58.0 (50.0–63.0) 57.5 (45.3–61.2) 0.023 Length of Hospital Stay, days * 2.0 (1.0–3.0) 1.0 (1.0–3.0) 2.0 (1.0–4.0) <0.001 Accelerometer Data Valid Wear Days, days * 30.0 (22.0–35.0) 31.0 (25.0–35.0) 29.0 (21.0–34.0) 0.265 Sleep Time, h/d 8.4 (1.5) 7.8 (1.3) 6.6 (1.0) <0.001 Sedentary Time, h/d 11.7 (0.9) 13.5 (0.4) 15.6 (1.0) <0.001 Mean Sedentary Bout Length, min/bout * 4.5 (3.8–5.7) 6.2 (4.6–9.7) 8.1 (6.0–15.5) <0.001 LIPA, min/d 143.8 (52.7) 109.2 (44.8) 82.2 (34.0) <0.001 MVPA, min/d * 25.0 (9.9–47.3) 11.4 (3.2–28.5) 2.7 (0.3–8.5) <0.001 Open in a new tab Data presented as mean (SD), median (interquartile range), or percentage. * indicates data presented as median (interquartile range). P-values for differences across groups were calculated using Kruskal-Wallis tests for non-normally distributed variables and linear regression for normally distributed variables. ACS, acute coronary syndrome; LIPA, light intensity physical activity; MVPA, moderate to vigorous Physical intensity physical activity. Sedentary Time, Sedentary Bout Length, and Cardiac Events/Mortality: Over follow-up, 50 patients (8.2%) had a cardiac event or died. When expressed in tertiles, greater time spent in sedentary behavior and longer mean sedentary bout length were each associated with an increased risk of 1-year cardiac events/mortality in unadjusted and partially-adjusted models ( Table 2 ; Figure 1 ). Adjustment for MVPA attenuated associations, but results remained significant for sedentary time. Associations of sedentary time and mean sedentary bout length with risk of 1-year cardiac events/mortality did not vary by ACS diagnosis (p-interaction >0.10). Table 2. Hazard ratio (95% CI) for risk of 1-year cardiac events and all-cause mortality by sedentary time and mean sedentary bout length tertiles. Tertile 1 Tertile 2 Tertile 3 P-Trend Sedentary Time Events/N 9/202 10/203 31/204 Unadjusted 1.00 (Ref) 1.12 (0.45–2.75) 3.61 (1.72–7.58) <0.001 Model 1 1.00 (Ref) 1.13 (0.46–2.78) 3.62 (1.70–7.69) <0.001 Model 2 1.00 (Ref) 1.15 (0.46–2.85) 4.17 (1.94–8.96) <0.001 Model 3 1.00 (Ref) 1.13 (0.45–2.80) 3.46 (1.57–7.63) <0.001 Model 4 1.00 (Ref) 0.93 (0.36–2.37) 2.59 (1.10–6.08) 0.011 Sedentary Bout Length Events/N 10/208 15/201 25/200 Unadjusted 1.00 (Ref) 1.57 (0.70–3.49) 2.70 (1.30–5.63) 0.006 Model 1 1.00 (Ref) 1.59 (0.71–3.54) 2.76 (1.29–5.92) 0.007 Model 2 1.00 (Ref) 1.48 (0.65–3.36) 2.91 (1.36–6.22) 0.004 Model 3 1.00 (Ref) 1.32 (0.57–3.03) 2.65 (1.21–5.81) 0.018 Model 4 1.00 (Ref) 1.00 (0.42–2.39) 1.86 (0.79–4.36) 0.093 Open in a new tab Model 1: Adjusted for age and sex. Model 2: Adjusted for covariates in model 1 plus race/ethnicity, education (expressed as interaction with follow-up time), partner status, health insurance, and ACS status. Model 3: Adjusted for covariates in model 2 plus Charlson comorbidity index, GRACE risk score, left ventricular ejection fraction, and length of hospital stay. Model 4: Adjusted for covariates in model 3 plus MVPA. Tertile cutoff points were <12.8, ≥12.8 to <14.3, and ≥14.3 h/d for sedentary time and <4.9, ≥4.9 to <7.8, and ≥7.8 min/bout for sedentary bout length. Figure 1. Cumulative cardiac events and mortality by tertile of sedentary time (A) and mean sedentary bout length (B). Open in a new tab Figure S3 shows dose-response associations for risk of 1-year cardiac events/mortality expressing sedentary time and mean sedentary bout length continuously. Sedentary time and mean sedentary bout length were significantly associated with risk of 1-year cardiac events/mortality in a non-linear fashion (p for non-linear effect=0.001 and 0.008, respectively). Detailed data for Figure S3 are presented in Tables S3 and S4 . Joint Associations of Sedentary Time and Sedentary Bout Length with Cardiac Events/Mortality: Figure 2 illustrates the joint association of sedentary time and sedentary bout length (p-interaction=0.105). Participants classified as high for both sedentary characteristics had the highest risk for 1-year cardiac events/mortality. Participants classified into the high sedentary time and low sedentary bout length group also had a significantly increased risk for 1-year cardiac events/mortality relative to the low sedentary time and low sedentary bout length (reference) group. Those classified into the low sedentary time and high sedentary bout length group did not differ from the referent. Figure 2. Hazard risk of 1-year cardiac events and mortality according to joint associations of sedentary time and sedentary bout length. Open in a new tab Models were adjusted for age, sex, race/ethnicity, education (expressed as interaction with follow-up time), marital status, health insurance coverage, ACS diagnosis, Charlson Comorbidity Index, Grace risk score, left ventricular ejection fraction, length of stay in hospital, and MVPA. High/low thresholds were 14 h/d for sedentary time and 10 min/bout for mean sedentary bout length. Isotemporal Substitution: Table 3 presents single-factor, 2-factor, and isotemporal substitution models for the associations between activity categories (sleep, sedentary time, LIPA, and MVPA) and risk of 1-year cardiac events/mortality. Sedentary time was associated with greater risk of 1-year cardiac events/mortality in single-factor and 2-factor models, indicating independent associations from all activity categories. In isotemporal substitution models, replacing 30 minutes of sedentary time with 30 minutes of sleep, LIPA, or MVPA was associated with a 14% (HR: 0.86; 95% CI, 0.78–0.95), 50% (HR: 0.50; 95% CI: 0.33–0.75), and 61% (HR: 0.39; 95% CI: 0.16–0.96) lower risk of cardiac events/mortality, respectively. Table 3. Hazard ratios (95% CI) for risk of 1-year cardiac events and all-cause mortality by sedentary time, sleep, light intensity physical activity, and moderate-vigorous intensity physical activity (expressed in 30-minute units) with and without adjustment for each activity variable. Model * Sleep Sedentary time LIPA MVPA Single-factor † 0.90 (0.81–0.99) 1.18 (1.09–1.29) 0.78 (0.64–0.95) 0.46 (0.23–0.91) 2-Factor ‡ NA 1.22 (1.08–1.39) 0.70 (0.57–0.87) 0.43 (0.22–0.87) 2-Factor || 1.05 (0.91–1.22) NA 0.89 (0.71–1.13) 0.71 (0.35–1.44) 2-Factor # 0.86 (0.77–0.94) 1.16 (1.05–1.27) NA 0.59 (0.29–1.21) 2-Factor ** 0.89 (0.81–0.98) 1.16 (1.05–1.27) 0.85 (0.68–1.07) NA Isotemporal †† 0.86 (0.78–0.95) NA 0.50 (0.33–0.77) 0.38 (0.16–0.95) Open in a new tab LIPA, light intensity physical activity; MVPA, moderate-vigorous intensity physical activity; NA, not applicable. * All variables expressed in 30-minute units. All models adjusted for age, sex, race/ethnicity, education (expressed as interaction with follow-up time), partner status, health insurance, ACS diagnosis, Charlson comorbidity index, GRACE risk score, left ventricular ejection fraction, and length of hospital stay. † Results from separate models for each activity variable (sedentary time, sleep, LIPA, and MVPA), adjusted for covariates. ‡ Results from separate models for each activity variable, adjusted for covariates and sleep. || Results from separate models for each activity variable, adjusted for covariates and sedentary time. # Results from separate models for each activity variable, adjusted for covariates and LIPA. ** Results from separate models for each activity variable, adjusted for covariates and MVPA. †† Results from a single model wherein sedentary time is omitted from the model (but sleep, LIPA, and MVPA are included along with covariates); thus, resulting HRs estimate associations for replacing 30 minutes of sedentary time with an equal amount in a given type of activity (sleep, LIPA, or MVPA). Sensitivity Analyses: Results were similar excluding events in the first 30 days ( Table S5 ), at a 6-month endpoint ( Table S6 ), and when using a frailty model treating ACS status as a random effect ( Table S7 ). DISCUSSION In this prospective study of patients presenting to the ED with symptoms suggestive of ACS, both longer sedentary time and prolonged, uninterrupted sedentary bouts were associated with an increased risk of 1-year cardiac events and mortality. When the joint association of both sedentary characteristics was evaluated, the combination of high sedentary time and high sedentary bout length was associated with the highest risk for 1-year cardiac events/mortality. These findings highlight the importance of both total volume of sedentary time and its accumulation in prolonged bouts as health risk behaviors after hospitalization for ACS or equivocal symptoms. Using isotemporal substitution modeling, we observed that replacing sedentary time with sleep, LIPA, or MVPA was associated with reductions in 1-year cardiac events/mortality risk. These findings may be helpful to inform strategies for reducing the health risks incurred by sedentary behavior and suggest promoting more sleep or movement of any intensity can mitigate some of its risk. Little evidence exists evaluating sedentary behavior as a prognostic risk factor in cardiac populations. A 2021 systematic review identified only three studies that examined associations between sedentary behavior and clinical end-points in this population, with mixed results reported 18 . One study reported an association between self-reported sedentary time prior to event and risk of hospital readmission over a median follow-up of 2.6 years, 19 but others reported no associations between high levels of self-reported sedentary time prior to event and all-cause mortality or significant associations between change in self-reported sedentary time from pre- to post-MI and all-cause mortality risk only among patients with <8h/d of sedentary time pre-MI. 20 , 21 These studies were limited by use of self-report measures (data prone to measurement error and reporting bias), assessment of sedentary behavior before (not after) the index event, and lack of adjustment for comorbidities and disease severity indicators (which raise issues concerning reverse causality). Thus, it was determined that the current evidence-base could not inform whether sedentary behavior is a risk factor for clinical outcomes in cardiac populations 18 . Ours is the first study to examine device-measured sedentary behavior and estimate its prospective association with cardiac events/mortality in patients with ACS or equivocal symptoms. We accounted for multiple disease severity and comorbidity indicators and found that sedentary time was independently associated with risk of cardiac events/mortality. These findings suggest sedentary time is not an epiphenomenon of underlying disease, but rather, is an independent risk factor for secondary CVD events and mortality. The “prolonger” versus “breaker” hypothesis postulates that it is not only the amount of sedentary time that is important to cardiometabolic health, but also the manner in which it is accumulated. 30 Observational studies in general population samples have reported associations between prolonged, uninterrupted sedentary bout metrics and cardiometabolic biomarkers, CVD, and mortality. 31 – 34 Experimental studies have corroborated these findings. 35 , 36 Our findings extend those of previous studies by providing the first prospective evidence that prolonged, uninterrupted sedentary behavior is associated with greater risk for cardiac events/mortality in the 1-year period after hospitalization for ACS or equivocal symptoms, albeit this association was not independent of MVPA in primary analyses (results were significant in secondary analyses expressing mean sedentary bout length continuously). This finding suggests interrupting sedentary time may represent an opportunity to mitigate residual risk in this population. Our finding of a joint association between the volume and pattern of sedentary behavior with cardiac events/mortality risk furthermore underscores that future guidelines should recommend reductions in total sedentary time in conjunction with interruptions of prolonged sedentary bouts to maximize risk reduction. Future randomized controlled trials, however, are still needed. In the current study, isotemporal substitution modeling provided key information concerning healthful alternatives to sedentary behavior. We observed that replacing 30 minutes of sedentary time with LIPA or MVPA was associated with a 51% and 61% lower risk of cardiac events/mortality, respectively. These results provide data on the benefits of more modest levels of physical activity to improve outcomes post-hospitalization and underscore a public health message that any movement, irrespective of intensity, is beneficial. This may be pertinent for ACS and NSCP populations who are largely sedentary, older in age, and report fears of and/or aversion to intense activity for whom LIPA might be more practical. 17 , 37 – 39 Nonetheless, it should be acknowledged that MVPA provided the greatest benefit and, thus, should ultimately be the primary target for mitigating risk in these populations. Our finding that sleep also was associated with health benefit (14% reduction in cardiac event/mortality risk with 30-minute substitution) provides novel information concerning an additional healthful alternative to sedentary behavior. The majority of existing studies that have utilized isotemporal substitution modeling across general and clinic populations have not included sleep. 40 Thus, our findings provide further insights regarding beneficial time reallocations across the 24-hour movement cycle and align with emerging evidence that sleep is an important determinant of secondary events and longevity post-hospitalization. 41 – 43 Our study has several limitations. First, the definition of sedentary behavior was based only on intensity because the GGIR package used to process accelerometer data doesn’t distinguish between sitting and standing postures. Thus, time spent in sedentary behavior may be overestimated. Second, although a strength of our study is the longer accelerometer measurement period (30 days), change in the exposure may occur over time after the first month post-discharge. Thus, there may be some exposure misclassification. Third, while we adjusted for several variables related to social determinants of health (SDOH), including race/ethnicity, education, partner status, and health insurance, the lack of more comprehensive SDOH data (e.g., income, neighborhood characteristics) limits our ability to fully account for the broader social and environmental factors influencing risk of 1-year cardiac events and mortality. Fourth, comprehensive discharge disposition data (e.g., home, skilled nursing facilities, or with cardiac rehabilitation referrals) were not collected. This limits our ability to fully assess the potential impact of post-discharge care settings on study outcomes. However, we adjusted for key covariates such as comorbidity burden and device-measured MVPA, which may partially account for variations in post-discharge care. Fifth, our study sample entailed a heterogeneous group of patients who presented to the ED with ACS symptoms, with only 25% receiving an ACS diagnosis. This limits generalizability to the ACS population. Nonetheless, acute chest pain is the 2 nd leading cause of ED visits in the US. 1 Studies have documented that less than half of patients with ACS symptoms receive a confirmed diagnosis. 41 , 44 Thus, our findings are ultimately more generalizable, covering a larger patient group presenting to the ED. It should also be noted that patients presenting to the ED with acute chest pain still report similar somatic and psychological symptoms as patients with confirmed ACS and have increased rates of cardiovascular readmissions (primarily due to ACS) and seeking secondary medical care following evaluation for ACS. 8 , 10 , 45 , 46 Thus, risk factors for adverse outcomes in this patient group should still be evaluated and aggressively treated. Importantly, our results did not vary by whether patients received an ACS vs. non-ACS diagnosis. Finally, although our findings suggest that prolonged sedentary behavior is associated with 1-year risk of cardiac events and mortality, the small number of events and wide confidence intervals warrant caution when interpreting these results and should ultimately be considered as preliminary evidence. Larger studies and studies that evaluate cardiac events and mortality as separate outcomes are needed to confirm these initial findings. In conclusion, in a prospective study of patients presenting with ACS symptoms, both sedentary time and prolonged, uninterrupted sedentary bouts were associated with an increased risk of 1-year cardiac events and mortality. These findings show that sedentary behavior may constitute an independent risk factor and potential therapeutic target for intervention to improve prognosis post-hospitalization for ACS or equivocal symptoms. To mitigate risk in this population, our results suggest that replacing sedentary time with sleep, LIPA, or MVPA is associated with a lower cardiac event/mortality risk. These findings support the public health message that patients should sit less and move or sleep more to improve prognosis. Supplementary Material Supplemental Publication Material Supplemental Methods. Detailed Methods 47 – 61 Table S1. Characteristics of enrolled participants that were included vs excluded from the analytic sample. Table S2. Participant characteristics by mean sedentary bout length tertiles. Table S3. Hazard ratios for risk of 1-year cardiac events and all-cause mortality by sedentary time levels. Table S4. Hazard ratios for risk of 1-year cardiac events and all-cause mortality by mean sedentary bout length levels. Table S5. Association of sedentary time and mean sedentary bout length (expressed as tertiles) with risk of 1-year cardiac events and all-cause mortality excluding events in the first 30 days. Table S6. Association of sedentary time and mean sedentary bout length (expressed as tertiles) with risk of 6-month cardiac events and all-cause mortality. Table S7. Association of sedentary time and mean sedentary bout length (expressed as tertiles) with risk of 1-year cardiac events and all-cause mortality using a frailty model treating ACS status as a random effect. Figure S1. Consort diagram showing the inclusion/exclusion of enrolled participants for analyses examining the association of sedentary behavior with risk of 1-year cardiac events and mortality. Figure S2. Histogram and kernel density plots showing the distribution of (A) total sedentary time and (B) mean sedentary bout duration. Figure S3. Hazard ratio of 1-year cardiac events and mortality as a function of sedentary time (A) and sedentary bout length (B) expressed continuously. NIHMS2064839-supplement-Supplemental_Publication_Material.pdf (382.2KB, pdf) STROBE Checklist NIHMS2064839-supplement-STROBE_Checklist.pdf (206.4KB, pdf) What is Known: Patients hospitalized with symptoms of acute coronary syndrome (ACS) remain at high risk for cardiac events and mortality, even with optimal medical treatment. Sedentary behavior has been linked to adverse cardiovascular outcomes in the general population, but evidence in post-hospitalized ACS populations remains sparse and largely reliant on self-reported measures. What the Study Adds: In this prospective study of 609 patients evaluated for ACS symptoms, prolonged sedentary time measured via accelerometry post-discharge was independently associated with increased risk of 1-year cardiac events and mortality. Replacing sedentary behavior with sleep, light-intensity physical activity (LIPA), or moderate-to-vigorous physical activity (MVPA) was associated with substantial reductions in cardiac event/mortality risk. The study highlights the importance of addressing sedentary behavior as a therapeutic target to improve prognosis after hospitalization for ACS or equivocal symptoms and supports the public health message that patients should sit less and move or sleep more to mitigate risk. ACKNOWLEDGEMENTS Funding/Support: This work was supported by grants from the National Institutes of Health, National Heart, Lung, and Blood Institute: R01HL134985 (Diaz), R01HL128497 (Edmondson), and R01 HL123368 (Kronish). Role of the Funder/Sponsor: The funding organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. ABBREVIATIONS ACS Acute coronary syndrome AIC Akaike Information Criterion CVD Cardiovascular disease CUMC Columbia University Medical Center ED Emergency department HR Hazard ratio LIPA Light intensity physical activity MVPA Moderate vigorous intensity physical activity MI Myocardial infarction NSCP Non-specific chest pain NSTEMI Non-ST-elevation myocardial infarction SDOH Social determinants of health STEMI ST-elevation myocardial infarction Footnotes Conflicts of Interest: There are no conflicts of interest to disclose. Data Access, Responsibility, and Analysis: KM Diaz 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. Data Sharing: The data that support the findings of this study are available from the corresponding author, (KM Diaz), upon reasonable request. Researchers interested in obtaining the data should contact the corresponding author via email at kd2442@columbia.edu . 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Table S5. Association of sedentary time and mean sedentary bout length (expressed as tertiles) with risk of 1-year cardiac events and all-cause mortality excluding events in the first 30 days. Table S6. Association of sedentary time and mean sedentary bout length (expressed as tertiles) with risk of 6-month cardiac events and all-cause mortality. Table S7. Association of sedentary time and mean sedentary bout length (expressed as tertiles) with risk of 1-year cardiac events and all-cause mortality using a frailty model treating ACS status as a random effect. Figure S1. Consort diagram showing the inclusion/exclusion of enrolled participants for analyses examining the association of sedentary behavior with risk of 1-year cardiac events and mortality. Figure S2. Histogram and kernel density plots showing the distribution of (A) total sedentary time and (B) mean sedentary bout duration. Figure S3. Hazard ratio of 1-year cardiac events and mortality as a function of sedentary time (A) and sedentary bout length (B) expressed continuously. NIHMS2064839-supplement-Supplemental_Publication_Material.pdf (382.2KB, pdf) STROBE Checklist NIHMS2064839-supplement-STROBE_Checklist.pdf (206.4KB, pdf) ACTIONS View on publisher site PDF (339.3 KB) Cite Collections Permalink RESOURCES Similar articles Cited by other articles Links to NCBI Databases Follow NCBI NCBI on X (formerly known as Twitter) NCBI on Facebook NCBI on LinkedIn NCBI on GitHub NCBI RSS feed Connect with NLM NLM on X (formerly known as Twitter) NLM on Facebook NLM on YouTube National Library of Medicine 8600 Rockville Pike Bethesda, MD 20894 Web Policies FOIA HHS Vulnerability Disclosure Help Accessibility Careers NLM NIH HHS USA.gov Back to Top

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