You are here

Article Text

Article menu
Systematic review
Relationship between objectively measured physical activity and subclinical cardiovascular disease: a systematic review
  1. Aparna Narendrula1,
  2. Ellen Brinza2,
  3. Christine Horvat Davey3,
  4. Chris T Longenecker4,
  5. Allison R Webel5
  1. 1Internal Medicine, NYU Grossman School of Medicine, New York, New York, USA
  2. 2Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
  3. 3Case Western Reserve University Frances Payne Bolton School of Nursing, Cleveland, Ohio, USA
  4. 4Division of Cardiology, University of Washington School of Medicine, Seattle, Washington, USA
  5. 5University of Washington School of Nursing, Seattle, Washington, USA
  1. Correspondence to Dr Allison R Webel; awebel{at}uw.edu

Abstract

Introduction The association of physical activity (PA) with subclinical cardiovascular disease (CVD) is unclear. Clarifying this relationship may inform cardiovascular prevention strategies.

Methods We performed a systematic review (CRD42021226089) using Medline, Embase, CINAHL and Cochrane (1 January 2000 to 1 September 2023). Studies published with adult populations exploring the relationship between objectively measured PA and subclinical CVD were included. Subclinical CVD was assessed using: ankle-brachial index (ABI); arterial stiffness; carotid artery disease; coronary artery atherosclerosis; endothelial function; and measures of cardiac structure and function. The Risk Of Bias In Non-randomised Studies - of Interventions (ROBINS-I) and Cochrane Risk of Bias tools were used for quality review.

Results Of 68 included studies, most supported an inverse relationship between PA and subclinical CVD. Arterial stiffness was the most common outcome (n=40), and 33 studies suggested that less sedentary behaviour (SB), increased PA and/or higher intensity PA was associated with less arterial stiffness. Ten studies of carotid artery disease (total n=18), six of endothelial function (n=10), two of coronary artery disease (n=3) and all of ABI (n=6) suggested that PA or less SB is associated with less subclinical disease. Five studies assessing cardiac structure/function (n=6) suggested alterations in structure/function with PA.

Conclusions PA reduces the risk of CVD events, and this systematic review demonstrates that some of the benefits may be mediated by an inverse association between PA and subclinical CVD. Interventions to increase PA are important for CVD prevention, so we provide a comprehensive overview of which surrogate outcome measures may be most useful to assess future CVD prevention interventions.

PROSPERO registration number CRD42021226089.

  • Physical activity
  • Review
  • Accelerometer
  • Cardiology prevention

Data availability statement

Data included in this systematic review were gathered from previously peer-reviewed, published literature and are available through their respective journals.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi.org/10.1136/bmjsem-2023-001596

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    WHAT IS ALREADY KNOWN ON THIS TOPIC

    • Higher levels of objectively-measured physical activity are associated with reduced risk of cardiovascular events.

    • Individual studies have assessed the relationship between objectively measured physical activity and a variety of different measures of subclinical cardiovascular disease or dysfunction.

    WHAT THIS STUDY ADDS

    • This systematic review synthesises the breadth of individual studies and the directional nature of associations between physical activity and six measures of subclinical disease: coronary artery disease, arterial stiffness, endothelial function, peripheral artery atherosclerosis, carotid artery atherosclerosis and cardiac structure and function.

    Introduction

    Cardiovascular disease (CVD) continues to be a leading cause of morbidity and mortality globally, and its prevalence has been rising in recent decades.1 Between 1990 and 2019, the global prevalence of CVD nearly doubled from 271 million to 523 million.1 Based on data from 2018, CVD was estimated to affect 9.3% of the US population (26.1 million individuals), with prevalence increasing with older age.2 3 Despite its significant contribution to disease burden and health expenditures, CVD and its adverse health consequences may be largely preventable through targeted interventions for modifiable risk factors such as physical inactivity.

    The inverse relationship between higher levels or longer duration of physical activity (PA) and risk of CVD events is well established.4 What is less clear is whether this relationship is primarily mediated by changes in subclinical CVD (eg, vascular dysfunction, atherosclerotic plaque or abnormal cardiac structure and function) or other potential mediators of risk, such as inflammation, sympathetic tone and thrombogenesis (figure 1). While there is evidence describing the relationship between intentional exercise and subclinical vascular disease, the impact of daily PA on subclinical disease is less established.5 6

    Figure 1
    Figure 1

    Directed acyclic graph of potential mediators of the relationship between physical activity and clinical cardiovascular events. This systematic review focuses on subclinical disease.

    Subclinical CVD is a powerful predictor of future development of clinical CVD, and the prevalence of subclinical CVD increases with age.7 Identification of subclinical CVD and its associated risk factors may help decrease the progression to clinical CVD events and CVD-related disability and mortality.8

    Much of the published literature focuses on self-reported PA, which is subject to bias.9 Wearable activity monitors are tools that objectively measure activity levels.10 Accelerometers are the gold-standard measurement of PA and are often used in research due to their increased accuracy, reliability and validity compared with simpler options, such as pedometers, self-reported activity and direct observation.9–11 Accelerometers are able to quantify the magnitude and duration of acceleration by using piezoelectric transducers and microprocessors, and just several days of wear have been shown to be a reliable measure of 2–3 years of activity.12

    We aimed to describe the association between objectively-measured PA and markers of subclinical CVD, defined as vascular dysfunction, atherosclerotic plaque or abnormal cardiac structure and function, by performing a systematic review of the literature. A better understanding of this relationship may inform the use of subclinical CVD measures as surrogate outcomes for CVD prevention interventions that aim to promote PA and decrease sedentary time among populations.

    Methods

    This prospectively registered (PROSPERO CRD42021226089, registered 14 January 2021) systematic review follows the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols 2020 guidelines, and institutional review board approval was not needed for this review.13 The study protocol is available on request.

    Equity, diversity and inclusion statement

    The investigator team included members of two genders, junior and senior researchers, career researchers, physicians at different stages of training and researchers trained in nursing. With non-restrictive exclusion criteria, we include manuscripts that analysed data for different genders, ages, races, ethnicities, socioeconomic statuses, countries and geographies. Thus, we include studies of diverse participant samples. We present overall trends in this analysis and do not draw conclusions about subgroups of populations. We encourage future interpreters of this systematic review to use our analysis to guide their review of the literature that focuses on their population of interest.

    Search strategy

    A comprehensive list of search terms was developed by a main reviewer (EB) under the direct supervision of CVD and PA experts (CTL and ARW). Searches were performed in Medline, Embase, CINAHL and Cochrane for publications from 1 January 2000 through 1 September 2023 (online supplemental table 1).

    Supplemental material

    No restrictions or filters involving date, language, article type, text availability, duplication or other limitations were applied to the original search. Next, search results were narrowed to English language, peer-reviewed full-text articles and human studies. Excluded publications included research letters, letters to the editor, editorials, commentaries, systematic reviews/meta-analyses, case reports, case series and meeting abstracts. Study designs included in this systematic review were longitudinal observation studies, randomised/non-randomised controlled/uncontrolled trials, cohort studies and cross-sectional studies. There was no geographic limitation to the included studies. Additionally, the reference lists for all included studies and related systematic reviews/meta-analyses were searched for additional sources meeting the inclusion criteria.

    Data management

    Search results were imported into Covidence, a systematic review management software (Veritas Health Innovation, Melbourne, Australia).14 Title and abstract screening was performed independently by two reviewers (AN and EB) using Covidence, according to the inclusion criteria outlined in box 1. These included: subjects 18 years or older without pre-existing CVD (studies that included adolescents and young adults in which the majority of patients were 18 years of age or older were not excluded), a primary exposure variable of objectively measured PA using the validated tool of actigraphy/accelerometry and outcomes of subclinical CVD. After initial abstract screening and adjudication of discrepancies between the two reviewers, full-text papers were reviewed independently by the two reviewers (AN and EB). Disputes were resolved during adjudication meetings with experts (ARW, CTL and CHD). Once all disputes had been settled, the two reviewers verified the list of studies included.

    Box 1

    Inclusion criteria for primary studies

    • Study published between 1 January 2000 and 1 September 2023.

    • Subjects were at least 18 years of age.

    • Subjects had no known pre-existing vascular disease.

    • Outcome measures include one or more of the following: (1) ankle-brachial index, (2) carotid or popliteal artery plaque/stenosis and intima-media thickness, (3) aortic stiffness, (4) measures of cardiac structure and function (echocardiography, CT, MRI), (5) endothelial function and (6) coronary artery atherosclerosis (coronary calcium and coronary CT angiography).

    • Accelerometry/actigraphy data are available for included subjects.

    • The direct relationship between objectively measured physical activity (PA) and subclinical cardiovascular disease (CVD) is reported.

    • The study is peer reviewed.

    In conjunction with the criteria listed in box 1, reasons for exclusion included duplicates identified manually or by Covidence, studies with the wrong exposure, wrong outcome, wrong intervention, wrong study design, wrong comparator, wrong patient population or data not reported. Meeting abstracts and manuscripts not written in English were also excluded (figure 2).

    Figure 2
    Figure 2

    Flow diagram of study selection.

    Exposures

    The primary exposure was objectively measured PA using the validated tool of actigraphy/accelerometry. Studies that reported actigraphy/accelerometry data as an independent predictor of subclinical CVD were included. Studies that measured PA using self-reported measures or pedometer data without accelerometer data were excluded.

    Outcomes

    Subclinical CVD was the primary outcome and was derived from definitions proposed by the Cardiovascular Health Study7: (1) abnormal ankle-brachial index (ABI), (2) carotid or popliteal artery plaque/stenosis or intima-media thickness (IMT) of the internal or common carotid artery (CCA), (3) abnormalities noted on measures of cardiac structure and function (echocardiography, CT, MRI), (4) arterial stiffness, (5) endothelial dysfunction and (6) coronary artery atherosclerosis (coronary calcium and coronary CT angiography).

    Data extraction

    Data were extracted from included papers separately by AN and EB using a data extraction spreadsheet. Discrepancies were adjudicated between the reviewers (AN and EB). The following data were extracted for each included study: publication details (title, author(s), journal, publication date, publication location, publication type and funding source), methods (including study design, type of accelerometer, PA outcome measure(s) reported and subclinical CVD outcome), participant details (number, pertinent characteristics of the population and demographics), outcomes and limitations (including types of bias present).

    Quality assessment

    Quality assessment was performed by two reviewers (AN and EB). The included studies were assessed using the Cochrane Risk of Bias tool for randomised controlled trials and the Risk Of Bias In Non-randomised Studies - of Interventions (ROBINS-I) tool for non-randomised controlled trials.15 16

    Data synthesis

    A narrative synthesis of the existing literature was performed without meta-analysis due to the heterogeneity of exposure and outcome measures. We reported findings according to outcome measure, including the following a priori categories: arterial stiffness, endothelial function, carotid artery disease, coronary artery atherosclerosis, peripheral artery atherosclerosis and cardiac structure and function (online supplemental table 2).

    Supplemental material

    Results

    Study selection

    Our search yielded an initial 9161 records for title and abstract screening, of which 162 studies underwent full-text review; 68 studies met the inclusion criteria (figure 2).

    Study characteristics

    Of the included studies, study samples ranged from 22 to 7,688 subjects, and there was marked variability with regard to characteristics of study participants; for example, some studies focused on specific populations (eg, individuals with diabetes or pregnancy). Study characteristics are described in online supplemental table 3. The majority of studies included were observational studies and therefore subject to bias and/or residual confounding.

    Accelerometry wear time ranged from 1 day to 1 year. PA was classified as sedentary behaviour (SB), habitual PA (HPA), light PA (LPA), moderate PA (MPA), moderate to vigorous physical activity (MVPA) and vigorous PA (VPA), as defined by counts per minute on accelerometry. Studies assessed duration in each category of PA.

    As a wide range of outcome measures were assessed, a descriptive systematic review was performed. Most studies examined a single outcome (n=57), while other studies included two or more outcomes (n=11). Figure 3A–C graphically demonstrate the number of studies assessing each measure of subclinical CVD and further indicates the proportion of these studies that suggested an association between PA or SB and disease.

    Figure 3
    Figure 3

    (A) Association between subclinical cardiovascular disease (CVD) and sedentary behaviour (SB), by marker of disease. Included in the figure are 37 analyses assessing the relationship between subclinical CVD and SB. Indication of the presence of an association includes all studies with a positive association between SB and subclinical CVD, regardless of strength of the association, significance or controlling for confounders. (B) Association between subclinical CVD and habitual or low-intensity physical activity, by marker of disease. Included in the figure are 46 analyses assessing the relationship between subclinical CVD and physical activity. Indication of the presence of an association includes all studies with an inverse association between physical activity and subclinical CVD, regardless of strength of the association, significance or controlling for confounders. (C) Association between subclinical CVD and higher intensity physical activity, by marker of disease. Included in the figure are 47 analyses assessing the relationship between subclinical CVD and higher intensity physical activity. Indication of the presence of an association includes all studies with an inverse association between higher intensity physical activity and subclinical CVD, regardless of strength of the association, significance or controlling for confounders.

    Arterial stiffness (n=40)

    The relationship between arterial stiffness and objectively measured PA was reported in 40 studies. Most studies measured arterial stiffness using pulse-wave velocity (PWV), some in addition to tonometry (eg, augmentation index or AIx) and only three studies assessed tonometry but not PWV.

    Cruickshank et al and Funck et al suggested that time in PA of non-specific intensity was related to decreased arterial stiffness as measured by PWV.17 18 However, higher intensity of PA did not further decrease carotid-femoral PWV (cfPWV) in Funck’s analysis, which was not designed to investigate intensity of PA.18 Several other studies also suggested an inverse dose–response relationship between time in PA and arterial stiffness,19–26 although this was not always statistically significant.27 In a smaller cross-sectional study, O’Donovan et al found significant inverse associations between HPA and PA of different intensities with AIx and PWV.28 Additionally, some studies found an inverse association between LPA and arterial stiffness,25 29 while others did not.30 31

    Many studies suggested that higher intensities of PA, including MPA, MVPA or VPA, were inversely associated with arterial stiffness.21 23 32–41 Several studies that found a significant inverse relationship between higher intensity PA and arterial stiffness found no significant relationship with lower intensities of PA and/or total PA.21 23 32 36 38 41 42 In contrast, Gando et al suggested no relationship between arterial stiffness with VPA, while there was an inverse relationship for MPA and LPA in older subjects.43 Several studies found no relationship between higher intensity PA with arterial stiffness.23 44–49 Some studies investigated specific patient populations, with differing results for subsets of patients.50 51 For example, Fernberg et al suggested a strong inverse association between AIx and MVPA in women and the total population, but not in men.51

    Several studies also found a significant positive association between SB and arterial stiffness.21 26 28 29 32 35 36 40 52 Gomez-Sanchez et al investigated SB and showed a positive correlation with vascular ageing, a term that included arterial stiffness.53 While the small (n=47) analysis by Morillas-de-Laguno (2018) suggested inverse associations between total PA and PA of all intensities with arterial stiffness, as well as a positive association between SB and arterial stiffness, these reports were not significant, potentially due to underpowering of the study.54 Other analyses did not find an association between SB and arterial stiffness.31 40 44 51 55

    Endothelial function (n=10)

    Ten studies explored the relationship between PA and endothelial function. Studies used change in flow-mediated dilation (FMD) or reactive hyperaemic flow as markers for endothelial function.

    Of studies assessing change in FMD, Kohlbrenner et al found an inverse relationship between daily PA and FMD in a cohort of patients with chronic obstructive pulmonary disease (COPD).56 Reyes et al also found a higher FMD response in active versus inactive pregnant women, defined by time in MVPA.57 Suboc et al found a similar correlation in participants with ≥20 min/day of MPA in bouts, which was not statistically significant, perhaps due to underpowering of the study (n=96).46 Suboc et al also found that MPA in bouts, rather than overall time in MPA, was associated with change in FMD.47 Similarly, Shivgulam et al noted MPA, habitual prolonged sedentary bouts and sedentary breaks, but not total sedentary time, were associated with change in popliteal FMD.58 On the other hand, Lane-Cordova et al reported no relationship between change in FMD with PA; however, their reporting of results was limited.59

    Four studies investigated reactive hyperaemic flow velocity as a measure of endothelial function. While Duran et al did not see worsened hyperaemic flow velocity with SB, Wipfli et al found a non-significant correlation.60 61 Baier et al found that daily PA is associated with improved hyperaemic flow velocity in patients with diabetes and control patients.62 Andersson et al measured both change in FMD and reactive hyperaemia and found no consistent relationship between SB or MVPA and endothelial function.55

    Peripheral artery atherosclerosis (n=6)

    A low ABI (≤0.90) is a gold-standard screening tool for peripheral artery disease.63 64 Five studies demonstrated the inverse relationship between exercise and peripheral artery atherosclerosis, as defined by a low ABI. Parsons et al showed that the total amount of time spent in MVPA is associated with decreased peripheral artery atherosclerotic risk, while increased LPA and decreased SB are also associated with decreased risk of peripheral artery atherosclerosis.65 Similarly, two large cross-sectional studies demonstrated that increased time in SB is associated with low ABI, while one of them also indicated that increased time in PA is less suggestive of peripheral artery atherosclerosis.53 66 67 Another study suggested that those with low ABI spent more time in SB and less time in LPA or MVPA, although these relationships are not statistically significant.68 Finally, Chiu et al found that a lower daily volume of PAs was associated with lower ABI scores.69

    Carotid artery atherosclerosis (n=18)

    Eighteen studies assessed subclinical carotid artery atherosclerosis through measures of carotid IMT (cIMT) and/or beta index. Kozàkovà et al found that SB was related to worsened CCA but not internal carotid artery IMT, while all intensities of PA, particularly VPA, were associated with lower CCA IMT.70 Five other studies showed that increased time spent in PA, of non-specific or light intensity, was related to reduced risk of carotid artery atherosclerosis.26 27 34 71 72 Parsons et al found an association between increased SB and worse cIMT, while an inverse relationship was found between LPA and MVPA with cIMT, although MVPA did not have a stronger association than LPA.65 Several studies (n=5) found no relationship between cIMT and PA.20 49 73–75 Other studies (n=4) found a negative association between cIMT and PA and/or a positive association between cIMT and SB, but not after adjusting for confounders.19 21 76 77 MVPA was found to improve Young’s elastic modulus of the carotid artery in one study, while another study found no association between cIMT and LPA, MVPA or SB, but did find decreased popliteal IMT with MVPA.78 79

    Coronary artery atherosclerosis (n=3)

    Three papers explored coronary artery calcification (CAC) as measured by CT as a marker of subclinical CVD. Gabriel et al showed that women without detectable CAC were statistically significantly more likely to spend more time per day in MVPA than those with prevalent CAC, while increased LPA and decreased SB showed non-significant associations with decreased CAC.80 Hamer et al showed a weak inverse relationship between MVPA and CAC that did not persist after adjustment for confounders and a weak non-significant positive association between SB and CAC.81 Webel et al found no association between objectively measured PA and CAC.82

    Cardiac structure and function (n=6)

    Five studies evaluated cardiac structure and function using echocardiography, while one assessed cardiac MRI (CMR).27 55 83–86 Most studies suggested better myocardial function with increased PA. Thangada et al demonstrated that MVPA was associated with increased stroke volume and left ventricular (LV) end diastolic volume (EDV), and VPA was associated with larger LV mass (LVM) on CMR.83 They did not observe an association between PA and left atrial (LA) size, while Heitmann et al found increased LA volume index (LAVI) with higher levels of PA in participants <70 years with normal diastolic function.83 84 Berdy et al85 found that higher levels of both LPA and MVPA were associated with increased LAVI. SB was associated with worsening LV myocardial mechanics, worsening LA pressure and right ventricular function.85 Andersson et al showed the Third Generation Framingham Heart Study indicated that more time spent in LPA or MVPA is associated with greater LVM, largely due to increased LV wall thickness, while SB was associated with lower LV wall thickness and LVM.55 In a smaller study, subjects with increased MVPA demonstrated higher LVM.27 Suboc et al found that engagement in MVPA after a 12-week intervention in healthy adults had no impact on cardiac function, including septal wall thickness, LV EDV, LV end systolic volume, or diastolic or systolic function.86

    Quality assessment results

    The results from the quality assessment scoring are depicted in online supplemental table 4. Of the six randomised controlled trials, three were classified as having low risk for bias, one was classified as having some concern for risk of bias and two were classified as having high concern for risk of bias. Reasons for lower ratings were due to concern for risk of bias arising randomisation or deviation from the intended intervention group, which often occurred in insufficient reporting of (1) randomisation procedures, (2) baseline characteristics from each randomisation group and (3) adherence to intended intervention, as well as a high percentage of the study population with missing data. Of the 62 non-randomised experimental or observational studies, 4 were classified as having low risk of bias, 39 moderate risk of bias, 18 serious risk of bias and 1 as having a critical risk of bias. The primary reasons for worse quality scores among the non-randomised studies were potential for confounding, classification bias and missing data.

    Discussion

    Substantial data have established that increasing PA through intentional exercise or daily activities may prevent and mitigate cardiovascular morbidity and mortality.87 However, the mediators of this effect on clinical outcomes were not previously elucidated. Notably, no prior systematic review to our knowledge has previously investigated the relationship between objectively measured PA and a comprehensive list of markers of subclinical CVD. This study demonstrated that the majority of the published literature describes an inverse relationship between increased PA and risk of subclinical CVD and a positive relationship between sedentary time and risk of various types of subclinical CVD.

    These findings are similar to those published by Germano-Soares et al, whose meta-analysis demonstrated a negative association between time spent in PA and cfPWV, and a positive association between time spent in SB and cfPWV.88 Our study expands on this review by including a comprehensive array of measures of subclinical CVD, beyond arterial stiffness to include measures of carotid artery plaque/stenosis and IMT, endothelial function, cardiac structure and function, ABI and coronary artery atherosclerosis.

    While the majority of studies described an inverse relationship between increased PA and risk of subclinical CVD, there was heterogeneity in the strength and direction of these associations. Notably, some studies found no association between risk of subclinical CVD and engagement in PA or SB. The discrepancy in findings may be explained by several factors. The heterogeneity of populations studied (eg, sex, age, comorbidities, geography), study design (eg, accelerometry wear time and location, presence of an exercise intervention, blinding of investigators) and low power in some studies are potential reasons for the lack of associations between measures of PA or SB and subclinical CVD measures. Subpopulation analyses suggest that this heterogeneity may be a reason for varying strength of results among different study groups.29 43 Therefore, it is difficult to quantitatively assess whether one type of PA or reducing SB is universally more effective at reducing subclinical CVD. Additionally, we cannot rule out the possibility that publication bias may have contributed to a higher volume of literature describing positive associations.

    Subclinical CVD is a powerful predictor of future development of clinical CVD, and the prevalence of subclinical CVD increases with age.7 Identification of subclinical CVD and its associated risk factors may help decrease the progression to clinical CVD events and CVD-related disability and mortality.8 The findings in this review are noteworthy, as they support the notion that the inverse relationship between time or intensity of PA and risk of CVD may be mediated by changes in subclinical CVD, as opposed to inflammation, thrombosis or other proposed mechanisms. As such, enhanced public health efforts towards promoting engagement in PA at an early age may have significant impacts on reducing risk of various types of CVD in adulthood.29 43 88

    Limitations

    While the breadth of our systematic review protocol provides the opportunity to consolidate a narrative of the current literature on this topic, the heterogeneity of both measures of PA, as well as included outcome measures, rendered it impossible to do a meaningful meta-analysis of all included studies. The included studies represent a range of different populations and sample sizes; however, the lack of participant-level characteristics prevents us from making conclusions about the relationship between PA or SB and subclinical CVD in any specific subgroup.

    Conclusion

    In conclusion, this systematic review consolidates contemporary research describing the relationship between objectively measured PA, including time spent in PA and different intensities of PA, or SB and subclinical CVD. Despite a wide array of study designs and populations, most studies suggested that decreased SB, increased PA and higher intensity PA were associated with less subclinical CVD. No studies suggested a positive association between PA and increased subclinical disease. We hope that by summarising existing data, our study can inform the choice of outcome measures in the design of future research and interventions assessing CVD prevention.

    Data availability statement

    Data included in this systematic review were gathered from previously peer-reviewed, published literature and are available through their respective journals.

    Ethics statements

    Patient consent for publication

    Ethics approval

    This is a systematic review of the published literature. The articles included in this study obtained ethics committee approval as appropriate.

    Acknowledgments

    We acknowledge the medical librarian of the Cleveland Clinic Floyd D Loop Alumni Library, Mary Schleicher, RN, BSN, MLIS, for her help in the design and implementation of the search strategy.

    References

    1. ↵
      1. Roth GA,
      2. Mensah GA,
      3. Johnson CO, et al
      . Global Burden of Cardiovascular Diseases and Risk Factors, 1990-2019: Update From the GBD 2019 Study. J Am Coll Cardiol 2020;76:2982–3021. doi:10.1016/j.jacc.2020.11.010
      OpenUrlCrossRefPubMed
    2. ↵
      1. Go AS,
      2. Mozaffarian D,
      3. Roger VL, et al
      . Heart disease and stroke statistics - 2014 update: a report from the american heart association. Circulation 2014;129. Available: https://www.ahajournals.org/doi/10.1161/01.cir.0000441139.02102.80
    3. ↵
      1. Newman AB,
      2. Arnold AM,
      3. Naydeck BL, et al
      . Successful aging:’ effect of subclinical cardiovascular disease. Arch Intern Med 2003;163:2315–22. doi:10.1001/archinte.163.19.2315
      OpenUrlCrossRefPubMedWeb of Science
    4. ↵
      1. Oguma Y,
      2. Shinoda-Tagawa T
      . Physical activity decreases cardiovascular disease risk in women: review and meta-analysis. Am J Prev Med 2004;26:407–18. doi:10.1016/j.amepre.2004.02.007
      OpenUrlCrossRefPubMedWeb of Science
    5. ↵
      1. Di Francescomarino S,
      2. Sciartilli A,
      3. Di Valerio V, et al
      . The effect of physical exercise on endothelial function[Internet]. Sports Med 2009;39:797–812. doi:10.2165/11317750-000000000-00000
      OpenUrlCrossRefPubMedWeb of Science
    6. ↵
      1. Bertoni AG,
      2. Whitt-Glover MC,
      3. Chung H, et al
      . The association between physical activity and subclinical atherosclerosis: the multi-ethnic study of atherosclerosis. Am J Epidemiol 2009;169:444–54. doi:10.1093/aje/kwn350
      OpenUrlCrossRefPubMedWeb of Science
    7. ↵
      1. Kuller LH,
      2. Arnold AM,
      3. Psaty BM, et al
      . 10-year follow-up of subclinical cardiovascular disease and risk of coronary heart disease in the cardiovascular health study. Arch Intern Med 2006;166:71–8. doi:10.1001/archinte.166.1.71
      OpenUrlCrossRefPubMedWeb of Science
    8. ↵
      1. Devereux RB,
      2. Alderman MH
      . Role of preclinical cardiovascular disease in the evolution from risk factor exposure to development of morbid events. Circulation 1993;88:1444–55. doi:10.1161/01.cir.88.4.1444
      OpenUrlAbstract/FREE Full Text
    9. ↵
      1. Fukuoka Y,
      2. Haskell W,
      3. Vittinghoff E
      . New insights into discrepancies between self-reported and accelerometer-measured moderate to vigorous physical activity among women - the mPED trial. BMC Public Health 2016;16:761. doi:10.1186/s12889-016-3348-7
      OpenUrl
    10. ↵
      1. Pevnick JM,
      2. Birkeland K,
      3. Zimmer R, et al
      . Wearable technology for cardiology: an update and framework for the future. Trends Cardiovasc Med 2018;28:144–50. doi:10.1016/j.tcm.2017.08.003
      OpenUrlPubMed
    11. ↵
      1. Skender S,
      2. Ose J,
      3. Chang-Claude J, et al
      . Accelerometry and physical activity questionnaires - a systematic review. BMC Public Health 2016;16:515. doi:10.1186/s12889-016-3172-0
      OpenUrlCrossRefPubMed
    12. ↵
      1. Herrmann SD,
      2. Barreira TV,
      3. Kang M, et al
      . How many hours are enough? Accelerometer wear time may provide bias in daily activity estimates. J Phys Act Health 2013;10:742–9. doi:10.1123/jpah.10.5.742
      OpenUrlPubMed
    13. ↵
      1. Ardern CL,
      2. Büttner F,
      3. Andrade R, et al
      . Implementing the 27 PRISMA 2020 statement items for systematic reviews in the sport and exercise medicine, musculoskeletal rehabilitation and sports science fields: the PERSiST (implementing PRISMA in exercise, rehabilitation, sport medicine and sports science) guidance. Br J Sports Med 2022;56:175–95. doi:10.1136/bjsports-2021-103987
      OpenUrlAbstract/FREE Full Text
    14. ↵
      Covidence -Better systematic review management [Internet]. 2021. Available: https://www.covidence.org/
    15. ↵
      1. Sterne JAC,
      2. Savović J,
      3. Page MJ, et al
      . RoB 2: A revised tool for assessing risk of bias in randomised trials. BMJ 2019;366. doi:10.1136/bmj.l4898
    16. ↵
      1. Sterne JA,
      2. Hernán MA,
      3. Reeves BC, et al
      . ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. BMJ 2016;355. doi:10.1136/bmj.i4919
    17. ↵
      1. Cruickshank JK,
      2. Silva MJ,
      3. Molaodi OR, et al
      . Ethnic differences in and childhood influences on early adult pulse wave velocity: the determinants of adolescent, now young adult, social wellbeing, and health longitudinal study. Hypertension 2016;67:1133–41. doi:10.1161/HYPERTENSIONAHA.115.07079
      OpenUrlCrossRef
    18. ↵
      1. Funck KL,
      2. Laugesen E,
      3. Høyem P, et al
      . Low physical activity is associated with increased arterial stiffness in patients recently diagnosed with type 2 diabetes. Am J Hypertens 2016;29:882–8. doi:10.1093/ajh/hpv197
      OpenUrlCrossRefPubMed
    19. ↵
      1. Ranadive SM,
      2. Yan H,
      3. Weikert M, et al
      . Vascular dysfunction and physical activity in multiple sclerosis. Med Sci Sports Exerc 2012;44:238–43. doi:10.1249/MSS.0b013e31822d7997
      OpenUrlCrossRefPubMed
    20. ↵
      1. Kozakova M,
      2. Palombo C,
      3. Mhamdi L, et al
      . Habitual physical activity and vascular aging in a young to middle-age population at low cardiovascular risk. Stroke 2007;38:2549–55. doi:10.1161/STROKEAHA.107.484949
      OpenUrlAbstract/FREE Full Text
    21. ↵
      1. Gomez-Marcos MA,
      2. Recio-Rodríguez JI,
      3. Patino-Alonso MC, et al
      . Relationship between objectively measured physical activity and vascular structure and function in adults. Atherosclerosis 2014;234:366–72. doi:10.1016/j.atherosclerosis.2014.02.028
      OpenUrlCrossRefPubMed
    22. ↵
      1. Ayabe M,
      2. Park S,
      3. Shephard RJ, et al
      . Associations of activity monitor output and an estimate of aerobic fitness with pulse wave velocities: the Nakanojo study. J Phys Act Health 2015;12:139–44. doi:10.1123/jpah.2012-0374
      OpenUrlCrossRefPubMed
    23. ↵
      1. Hawkins M,
      2. Gabriel KP,
      3. Cooper J, et al
      . The impact of change in physical activity on change in arterial stiffness in overweight or obese sedentary young adults. Vasc Med 2014;19:257–63. doi:10.1177/1358863X14536630
      OpenUrlCrossRefPubMed
    24. ↵
      1. Jung JY,
      2. Min KW,
      3. Ahn HJ, et al
      . Arterial stiffness by aerobic exercise is related with aerobic capacity, physical activity energy expenditure and total fat but not with insulin sensitivity in obese female patients with type 2 diabetes. Diabetes Metab J 2014;38:439–48. doi:10.4093/dmj.2014.38.6.439
      OpenUrl
    25. ↵
      1. Lopes S,
      2. Mesquita-Bastos J,
      3. Garcia C, et al
      . Physical activity is associated with lower arterial stiffness in patients with resistant hypertension. Heart Lung Circ 2021;30:1762–8. doi:10.1016/j.hlc.2021.06.532
      OpenUrl
    26. ↵
      1. Parsons TJ,
      2. Sartini C,
      3. Ellins EA, et al
      . Objectively measured physical activity, sedentary time and subclinical vascular disease: cross-sectional study in older british men. Prev Med 2016;89:194–9. doi:10.1016/j.ypmed.2016.05.031
      OpenUrl
    27. ↵
      1. Kozakova M,
      2. Balkau B,
      3. Morizzo C, et al
      . Physical activity, adiponectin, and cardiovascular structure and function. Heart Vessels 2013;28:91–100. doi:10.1007/s00380-011-0215-4
      OpenUrl
    28. ↵
      1. O’Donovan C,
      2. Lithander FE,
      3. Raftery T, et al
      . Inverse relationship between physical activity and arterial stiffness in adults with hypertension. J Phys Act Health 2014;11:272–7. doi:10.1123/jpah.2012-0075
      OpenUrlCrossRefPubMed
    29. ↵
      1. Cooke AB,
      2. Daskalopoulou SS,
      3. Dasgupta K
      . The impact of accelerometer wear location on the relationship between step counts and arterial stiffness in adults treated for hypertension and diabetes. J Sci Med Sport 2018;21:398–403. doi:10.1016/j.jsams.2017.08.011
      OpenUrl
    30. ↵
      1. Königstein K,
      2. Infanger D,
      3. Klenk C, et al
      . Physical activity is favorably associated with arterial stiffness in patients with obesity and elevated metabolic risk. Int J Clin Pract 2020;74:1–7.:e13563. doi:10.1111/ijcp.13563
      OpenUrlPubMed
    31. ↵
      1. Gerage AM,
      2. Benedetti TRB,
      3. Farah BQ, et al
      . Sedentary behavior and light physical activity are associated with brachial and central blood pressure in hypertensive patients. PLoS One 2015;10:e0146078. doi:10.1371/journal.pone.0146078
    32. ↵
      1. Bohn L,
      2. Ramoa A,
      3. Silva G, et al
      . Sedentary behavior and arterial stiffness in adults with and without metabolic syndrome. Int J Sports Med 2017;38:396–401. doi:10.1055/s-0043-101676
      OpenUrl
    33. ↵
      1. Aoyagi Y,
      2. Park H,
      3. Kakiyama T, et al
      . Yearlong physical activity and regional stiffness of arteries in older adults: the nakanojo study. Eur J Appl Physiol 2010;109:455–64. doi:10.1007/s00421-010-1357-2
      OpenUrlCrossRefPubMed
    34. ↵
      1. Hörnberg K,
      2. Pomeroy J,
      3. Sandberg C, et al
      . Physical activity in rheumatoid arthritis: relationship to cardiovascular risk factors, subclinical atherosclerosis, and disease activity. Scand J Rheumatol 2020;49:112–21. doi:10.1080/03009742.2019.1657491
      OpenUrl
    35. ↵
      1. Horta BL,
      2. Schaan BD,
      3. Bielemann RM, et al
      . Objectively measured physical activity and sedentary-time are associated with arterial stiffness in brazilian young adults. Atherosclerosis 2015;243:148–54. doi:10.1016/j.atherosclerosis.2015.09.005
      OpenUrl
    36. ↵
      1. Mac Ananey O,
      2. McLoughlin B,
      3. Leonard A, et al
      . Inverse Relationship Between Physical Activity, Adiposity, and Arterial Stiffness in Healthy Middle-Aged Subjects. J Phys Act Health 2015;12:1576–81. doi:10.1123/jpah.2014-0395
      OpenUrl
    37. ↵
      1. Vandercappellen EJ,
      2. Henry RMA,
      3. Savelberg HHCM, et al
      . Association of the amount and pattern of physical activity with arterial stiffness: the maastricht study. J Am Heart Assoc 2020;9:e017502. doi:10.1161/JAHA.120.017502
    38. ↵
      1. García-Ortiz L,
      2. Recio-Rodríguez JI,
      3. Schmidt-Trucksäss A, et al
      . Relationship between objectively measured physical activity and cardiovascular aging in the general population--the EVIDENT trial. Atherosclerosis 2014;233:434–40. doi:10.1016/j.atherosclerosis.2014.01.021
      OpenUrlCrossRefPubMedWeb of Science
    39. ↵
      1. Matenchuk BA,
      2. Fujii K,
      3. Skow RJ, et al
      . The effects of physical activity on arterial stiffness during pregnancy: an observational study. Appl Physiol Nutr Metab 2022;47:234–42. doi:10.1139/apnm-2021-0121
      OpenUrl
    40. ↵
      1. Brantley B,
      2. Sydni C,
      3. Norman G, et al
      . Physical activity and arterial stiffness: is body fat a mediator? Eur J Appl Physiol 2023.
    41. ↵
      1. Cobos-Palacios L,
      2. Ruiz-Moreno MI,
      3. Muñoz-Ubeda M, et al
      . A healthy lifestyle is associated with lower arterial stiffness in a metabolically healthy elderly population with overweight or obesity. J Hypertens 2022;40:1808–14. doi:10.1097/HJH.0000000000003227
      OpenUrl
    42. ↵
      1. Sugawara J,
      2. Otsuki T,
      3. Tanabe T, et al
      . Physical activity duration, intensity, and arterial stiffening in postmenopausal women. Am J Hypertens 2006;19:1032–6. doi:10.1016/j.amjhyper.2006.03.008
      OpenUrlCrossRefPubMed
    43. ↵
      1. Gando Y,
      2. Yamamoto K,
      3. Murakami H, et al
      . Longer time spent in light physical activity is associated with reduced arterial stiffness in older adults. Hypertension 2010;56:540–6. doi:10.1161/HYPERTENSIONAHA.110.156331
      OpenUrlCrossRefPubMed
    44. ↵
      1. Laursen ASD,
      2. Hansen A-LS,
      3. Wiinberg N, et al
      . Higher physical activity is associated with lower aortic stiffness but not with central blood pressure. Medicine 2015;94:e485. doi:10.1097/MD.0000000000000485
    45. ↵
      1. Hamaguchi K,
      2. Kurihara T,
      3. Fujimoto M, et al
      . Associations among bone mineral density, physical activity and nutritional intake in middle-aged women with high levels of arterial stiffness: a pilot study. Int J Environ Res Public Health 2020;17:1620. doi:10.3390/ijerph17051620
    46. ↵
      1. Suboc TB,
      2. Knabel D,
      3. Strath SJ, et al
      . Associations of reducing sedentary time with vascular function and insulin sensitivity in older sedentary adults. Am J Hypertens 2016;29:46–53. doi:10.1093/ajh/hpv063
      OpenUrlCrossRefPubMed
    47. ↵
      1. Suboc TB,
      2. Strath SJ,
      3. Dharmashankar K, et al
      . Relative importance of step count, intensity, and duration on physical activity’s impact on vascular structure and function in previously sedentary older adults. J Am Heart Assoc 2014;3:e000702. doi:10.1161/JAHA.113.000702
    48. ↵
      1. Dasgupta K,
      2. Rosenberg E,
      3. Joseph L, et al
      . Carotid femoral pulse wave velocity in type 2 diabetes and hypertension: capturing arterial health effects of step counts. J Hypertens 2017;35:1061–9. doi:10.1097/HJH.0000000000001277
      OpenUrl
    49. ↵
      1. de Sousa MKF,
      2. Silva R de M,
      3. Freire YA, et al
      . Associations between physical activity and cardiorespiratory fitness with vascular health phenotypes in older adults: a cross-sectional study. Front Physiol 2023;14:1096139. doi:10.3389/fphys.2023.1096139
      OpenUrl
    50. ↵
      1. Hayashi K,
      2. Maeda S,
      3. Iemitsu M, et al
      . Estrogen receptor-alpha genotype affects exercise-related reduction of arterial stiffness. Med Sci Sports Exerc 2008;40:252–7. doi:10.1249/mss.0b013e31815c04cf
      OpenUrlPubMedWeb of Science
    51. ↵
      1. Fernberg U,
      2. Fernström M,
      3. Hurtig-Wennlöf A
      . Higher total physical activity is associated with lower arterial stiffness in swedish, young adults: the cross-sectional lifestyle, biomarkers, and atherosclerosis study. Vasc Health Risk Manag 2021;17:175–85. doi:10.2147/VHRM.S283211
      OpenUrl
    52. ↵
      1. Cabral LLP,
      2. Freire YA,
      3. Browne RAV, et al
      . Associations of steps per day and peak cadence with arterial stiffness in older adults. Exp Gerontol 2022;157:111628. doi:10.1016/j.exger.2021.111628
      OpenUrl
    53. ↵
      1. Gomez-Sanchez M,
      2. Gomez-Sanchez L,
      3. Patino-Alonso MC, et al
      . Vascular aging and its relationship with lifestyles and other risk factors in the general Spanish population: early vascular ageing study. J Hypertens 2020;38:1110–22. doi:10.1097/HJH.0000000000002373
      OpenUrlCrossRef
    54. ↵
      1. Morillas-de-Laguno P,
      2. Vargas-Hitos JA,
      3. Rosales-Castillo A, et al
      . Association of objectively measured physical activity and sedentary time with arterial stiffness in women with systemic lupus erythematosus with mild disease activity. PloS One 2018;13:e0196111. doi:10.1371/journal.pone.0196111
    55. ↵
      1. Andersson C,
      2. Lyass A,
      3. Larson MG, et al
      . Physical activity measured by accelerometry and its associations with cardiac structure and vascular function in young and middle-aged adults. J Am Heart Assoc 2015;4:e001528. doi:10.1161/JAHA.114.001528
    56. ↵
      1. Kohlbrenner D,
      2. Clarenbach CF,
      3. Thiel S, et al
      . A few more steps lead to improvements in endothelial function in severe and very severe COPD. Respiratory Medicine 2021;176:106246. doi:10.1016/j.rmed.2020.106246
      OpenUrl
    57. ↵
      1. Reyes LM,
      2. Farooq SM,
      3. Skow RJ, et al
      . Physical activity in pregnancy is associated with increased flow-mediated dilation. Med Sci Sports Exerc 2020;52:801–9. doi:10.1249/MSS.0000000000002201
      OpenUrl
    58. ↵
      1. Shivgulam ME,
      2. Liu H,
      3. Schwartz BD, et al
      . Impact of exercise training interventions on flow-mediated dilation in adults: an umbrella review. Sports Med 2023;53:1161–74. doi:10.1007/s40279-023-01837-w
      OpenUrl
    59. ↵
      1. Lane-Cordova AD,
      2. Phillips SA,
      3. Baynard T, et al
      . Effects of ageing and physical activity on blood pressure and endothelial function during acute inflammation. Exp Physiol 2016;101:962–71. doi:10.1113/EP085551
      OpenUrl
    60. ↵
      1. Wipfli B,
      2. Wild S,
      3. Donovan C, et al
      . Sedentary work and physiological markers of health. Int J Environ Res Public Health 2021;18:1–12.:3230. doi:10.3390/ijerph18063230
      OpenUrlCrossRefPubMed
    61. ↵
      1. Duran AT,
      2. Garber CE,
      3. Ensari I, et al
      . Associations between habitual sedentary behavior and endothelial cell health. Transl J Am Coll Sports Med 2020;5:e000138. doi:10.1249/tjx.0000000000000138
    62. ↵
      1. Baier JM,
      2. Funck KL,
      3. Vernstrøm L, et al
      . Low physical activity is associated with impaired endothelial function in patients with type 2 diabetes and controls after 5 years of follow-up. BMC Endocr Disord 2021;21:189. doi:10.1186/s12902-021-00857-9
      OpenUrl
    63. ↵
      1. O’Hare AM,
      2. Katz R,
      3. Shlipak MG, et al
      . Mortality and cardiovascular risk across the ankle-arm index spectrum. Circulation 2006;113:388–93. doi:10.1161/CIRCULATIONAHA.105.570903
      OpenUrlAbstract/FREE Full Text
    64. ↵
      1. Allison MA,
      2. Hiatt WR,
      3. Hirsch AT, et al
      . A high ankle-brachial index is associated with increased cardiovascular disease morbidity and lower quality of life. J Am Coll Cardiol 2008;51:1292–8. doi:10.1016/j.jacc.2007.11.064
      OpenUrlFREE Full Text
    65. ↵
      1. Parsons TJ,
      2. Sartini C,
      3. Ellins EA, et al
      . Objectively measured physical activity and sedentary behaviour and ankle brachial index: cross-sectional and longitudinal associations in older men. Atherosclerosis 2016;247:28–34. doi:10.1016/j.atherosclerosis.2016.01.038
      OpenUrl
    66. ↵
      1. Unkart JT,
      2. Allison MA,
      3. Parada H, et al
      . Sedentary time and peripheral artery disease: the hispanic community health study/study of latinos. Am Heart J 2020;222:208–19. doi:10.1016/j.ahj.2020.02.005
      OpenUrl
    67. ↵
      1. Kulinski JP,
      2. Sanghavi M,
      3. Ayers CR, et al
      . Association between low ankle-brachial index and accelerometer-derived sedentary and exercise time in the asymptomatic general population. Vasc Med 2015;20:332–8. doi:10.1177/1358863X15573837
      OpenUrlCrossRefPubMed
    68. ↵
      1. Hawkins MS,
      2. Gabriel KP,
      3. Conroy MB, et al
      . Physical activity intensity and cardiovascular risk by ankle-brachial index. Vasc Med 2013;18:79–84. doi:10.1177/1358863X13480552
      OpenUrlCrossRefPubMed
    69. ↵
      1. Chiu V,
      2. Urbanek JK,
      3. Wanigatunga AA, et al
      . The association between ankle-brachial index and daily patterns of physical activity: results from the hispanic community health study/study of latinos (HCHS/SOL). J Gerontol A Biol Sci Med Sci 2023. doi:10.1093/gerona/glad200
    70. ↵
      1. Kozàkovà M,
      2. Palombo C,
      3. Morizzo C, et al
      . Effect of sedentary behaviour and vigorous physical activity on segment-specific carotid wall thickness and its progression in a healthy population. Eur Heart J 2010;31:1511–9. doi:10.1093/eurheartj/ehq092
      OpenUrlCrossRefPubMedWeb of Science
    71. ↵
      1. Veldsman T,
      2. Swanepoel M,
      3. Monyeki MA, et al
      . Relationship between physical activity and carotid intima-media thickness among teachers in South Africa: the SABPA study. Cardiovasc J Afr 2020;31:304–13. doi:10.5830/CVJA-2020-024
      OpenUrl
    72. ↵
      1. Pae BJ,
      2. Lee SK,
      3. Kim S, et al
      . Effect of physical activity on the change in carotid intima-media thickness: an 8-year prospective cohort study. PLoS One 2023;18:e0287685. doi:10.1371/journal.pone.0287685
    73. ↵
      1. Hamer M,
      2. Malan L,
      3. Schutte AE, et al
      . Conventional and behavioral risk factors explain differences in sub-clinical vascular disease between black and Caucasian South Africans: the SABPA study. Atherosclerosis 2011;215:237–42. doi:10.1016/j.atherosclerosis.2010.12.015
      OpenUrlCrossRefPubMedWeb of Science
    74. ↵
      1. Kadoya M,
      2. Koyama H,
      3. Kurajoh M, et al
      . Sleep, cardiac autonomic function, and carotid atherosclerosis in patients with cardiovascular risks: HSCAA study. Atherosclerosis 2015;238:409–14. doi:10.1016/j.atherosclerosis.2014.12.032
      OpenUrlCrossRefPubMed
    75. ↵
      1. Veldsman T,
      2. Swanepoel M,
      3. Monyeki MA, et al
      . The role of physical activity status in the relationship between obesity and carotid intima-media thickness (CIMT) in Urban South African Teachers: the SABPA study. Int J Environ Res Public Health 2022;19:10. doi:10.3390/ijerph19106348
      OpenUrl
    76. ↵
      1. Gastaldelli A,
      2. Kozakova M,
      3. Højlund K, et al
      . Fatty liver is associated with insulin resistance, risk of coronary heart disease, and early atherosclerosis in a large European population. Hepatology 2009;49:1537–44. doi:10.1002/hep.22845
      OpenUrlCrossRefPubMedWeb of Science
    77. ↵
      1. García-Hermoso A,
      2. Martínez-Vizcaíno V,
      3. Recio-Rodríguez JI, et al
      . Sedentary behaviour patterns and carotid intima-media thickness in Spanish healthy adult population. Atherosclerosis 2015;239:571–6. doi:10.1016/j.atherosclerosis.2015.02.028
      OpenUrl
    78. ↵
      1. Ried-Larsen M,
      2. Grøntved A,
      3. Kristensen PL, et al
      . Moderate-and-vigorous physical activity from adolescence to adulthood and subclinical atherosclerosis in adulthood: prospective observations from the European youth heart study. Br J Sports Med 2015;49:107–12. doi:10.1136/bjsports-2013-092409
      OpenUrlAbstract/FREE Full Text
    79. ↵
      1. Ryan DJ,
      2. Wullems JA,
      3. Stebbings GK, et al
      . Segregating the distinct effects of sedentary behavior and physical activity on older adults’ cardiovascular profile: part 2-isotemporal substitution approach. J Phys Act Health 2018;15:537–42. doi:10.1123/jpah.2017-0326
      OpenUrl
    80. ↵
      1. Gabriel KP,
      2. Matthews KA,
      3. Pérez A, et al
      . Self-reported and accelerometer-derived physical activity levels and coronary artery calcification progression in older women: results from the healthy women study. Menopause 2013;20:152–61. doi:10.1097/gme.0b013e31826115af
      OpenUrl
    81. ↵
      1. Hamer M,
      2. Venuraju SM,
      3. Lahiri A, et al
      . Objectively assessed physical activity, sedentary time, and coronary artery calcification in healthy older adults. Arterioscler Thromb Vasc Biol 2012;32:500–5. doi:10.1161/ATVBAHA.111.236877
      OpenUrlAbstract/FREE Full Text
    82. ↵
      1. Webel AR,
      2. Perazzo J,
      3. Longenecker CT, et al
      . The Influence of exercise on cardiovascular health in sedentary adults with human immunodeficiency virus. J Cardiovasc Nurs 2018;33:239–47. doi:10.1097/JCN.0000000000000450
      OpenUrl
    83. ↵
      1. Thangada ND,
      2. Patel KV,
      3. Peden B, et al
      . Cross-sectional associations of objectively measured sedentary time, physical activity, and fitness with cardiac structure and function: findings from the dallas heart study. J Am Heart Assoc 2021;10:e015601. doi:10.1161/JAHA.119.015601
    84. ↵
      1. Heitmann KA,
      2. Løchen M-L,
      3. Hopstock LA, et al
      . Cross-sectional associations between accelerometry-measured physical activity, left atrial size, and indices of left ventricular diastolic dysfunction: the tromsø study. Prev Med Rep 2021;21:101290. doi:10.1016/j.pmedr.2020.101290
      OpenUrl
    85. ↵
      1. Berdy AE,
      2. Upadhya B,
      3. Ponce S, et al
      . Associations between physical activity, sedentary behaviour and left ventricular structure and function from the echocardiographic study of latinos (ECHO-SOL). Open Heart 2021;8:1–9.:e001647. doi:10.1136/openhrt-2021-001647
      OpenUrlCrossRef
    86. ↵
      1. Suboc TB,
      2. Strath SJ,
      3. Dharmashankar K, et al
      . The impact of moderate intensity physical activity on cardiac structure and performance in older sedentary adults. Int J Cardiol Heart Vessel 2014;4:19–24. doi:10.1016/j.ijchv.2014.08.007
      OpenUrl
    87. ↵
      1. Swift DL,
      2. Lavie CJ,
      3. Johannsen NM, et al
      . Physical activity, cardiorespiratory fitness, and exercise training in primary and secondary coronary prevention. Circ J 2013;77:281–92. doi:10.1253/circj.cj-13-0007
      OpenUrlCrossRefPubMedWeb of Science
    88. ↵
      1. Germano-Soares AH,
      2. Andrade-Lima A,
      3. Menêses AL, et al
      . Association of time spent in physical activities and sedentary behaviors with carotid-femoral pulse wave velocity: a systematic review and meta-analysis. Atherosclerosis 2018;269:211–8. doi:10.1016/j.atherosclerosis.2018.01.009
      OpenUrl

    Supplementary materials

    Footnotes

    • Twitter @a_narendrula

    • AN and EB contributed equally.

    • Contributors AN and EB contributed equally to this paper. The guarantor is CTL. All authors designed the study, acquired PROSPERO approval and edited this manuscript. AN and EB conducted abstract and full-text reviews, data extraction and quality review. All authors read and approved the final manuscript.

    • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

    • Competing interests None declared.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.