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      Accelerometer Metrics: Healthy Adult Reference Values, Associations with Cardiorespiratory Fitness, and Clinical Implications

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          ABSTRACT

          Purpose

          Accelerometer-assessed physical activity (PA) can be summarized using cut-point–free or population-specific cut-point–based outcomes. We aimed to 1) examine the interrelationship between cut-point–free (intensity gradient (IG) and average acceleration (AvAcc)) and cut-point–based accelerometer metrics, 2) compare the association between cardiorespiratory fitness (CRF) and cut-point–free metrics to that with cut-point–based metrics in healthy adults aged 20 to 89 yr and patients with heart failure, and 3) provide age-, sex-, and CRF-related reference values for healthy adults.

          Methods

          In the COmPLETE study, 463 healthy adults and 67 patients with heart failure wore GENEActiv accelerometers on their nondominant wrist and underwent cardiopulmonary exercise testing. Cut-point–free (IG: distribution of intensity of activity across the day; AvAcc: proxy of volume of activity) and traditional (moderate-to-vigorous and vigorous activity) metrics were generated. The “interpretablePA” R-package was developed to translate findings into clinical practice.

          Results

          IG and AvAcc yield complementary information on PA with both IG ( P = 0.009) and AvAcc ( P < 0.001) independently associated with CRF in healthy individuals (adjusted R 2 = 73.9%). Only IG was independently associated with CRF in patients with heart failure ( P = 0.043, adjusted R 2 = 38.4%). The best cut-point–free and cut-point–based model had similar predictive value for CRF in both cohorts. We produced age- and sex-specific reference values and percentile curves for IG, AvAcc, moderate-to-vigorous PA, and vigorous PA for healthy adults.

          Conclusions

          IG and AvAcc are strongly associated with CRF and thus indirectly with the risk of noncommunicable diseases and mortality, in healthy adults and patients with heart failure. However, unlike cut-point–based metrics, IG and AvAcc are comparable across populations. Our reference values provide a healthy age- and sex-specific comparison that may enhance the translation and utility of cut-point–free metrics in clinical practice.

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          Most cited references50

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          World Health Organization 2020 guidelines on physical activity and sedentary behaviour

          Objectives To describe new WHO 2020 guidelines on physical activity and sedentary behaviour. Methods The guidelines were developed in accordance with WHO protocols. An expert Guideline Development Group reviewed evidence to assess associations between physical activity and sedentary behaviour for an agreed set of health outcomes and population groups. The assessment used and systematically updated recent relevant systematic reviews; new primary reviews addressed additional health outcomes or subpopulations. Results The new guidelines address children, adolescents, adults, older adults and include new specific recommendations for pregnant and postpartum women and people living with chronic conditions or disability. All adults should undertake 150–300 min of moderate-intensity, or 75–150 min of vigorous-intensity physical activity, or some equivalent combination of moderate-intensity and vigorous-intensity aerobic physical activity, per week. Among children and adolescents, an average of 60 min/day of moderate-to-vigorous intensity aerobic physical activity across the week provides health benefits. The guidelines recommend regular muscle-strengthening activity for all age groups. Additionally, reducing sedentary behaviours is recommended across all age groups and abilities, although evidence was insufficient to quantify a sedentary behaviour threshold. Conclusion These 2020 WHO guidelines update previous WHO recommendations released in 2010. They reaffirm messages that some physical activity is better than none, that more physical activity is better for optimal health outcomes and provide a new recommendation on reducing sedentary behaviours. These guidelines highlight the importance of regularly undertaking both aerobic and muscle strengthening activities and for the first time, there are specific recommendations for specific populations including for pregnant and postpartum women and people living with chronic conditions or disability. These guidelines should be used to inform national health policies aligned with the WHO Global Action Plan on Physical Activity 2018–2030 and to strengthen surveillance systems that track progress towards national and global targets.
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            Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses

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              Cardiorespiratory fitness as a quantitative predictor of all-cause mortality and cardiovascular events in healthy men and women: a meta-analysis.

              Epidemiological studies have indicated an inverse association between cardiorespiratory fitness (CRF) and coronary heart disease (CHD) or all-cause mortality in healthy participants. To define quantitative relationships between CRF and CHD events, cardiovascular disease (CVD) events, or all-cause mortality in healthy men and women. A systematic literature search was conducted for observational cohort studies using MEDLINE (1966 to December 31, 2008) and EMBASE (1980 to December 31, 2008). The Medical Subject Headings search terms used included exercise tolerance, exercise test, exercise/physiology, physical fitness, oxygen consumption, cardiovascular diseases, myocardial ischemia, mortality, mortalities, death, fatality, fatal, incidence, or morbidity. Studies reporting associations of baseline CRF with CHD events, CVD events, or all-cause mortality in healthy participants were included. Two authors independently extracted relevant data. CRF was estimated as maximal aerobic capacity (MAC) expressed in metabolic equivalent (MET) units. Participants were categorized as low CRF ( or = 10.9 METs). CHD and CVD were combined into 1 outcome (CHD/CVD). Risk ratios (RRs) for a 1-MET higher level of MAC and for participants with lower vs higher CRF were calculated with a random-effects model. Data were obtained from 33 eligible studies (all-cause mortality, 102 980 participants and 6910 cases; CHD/CVD, 84 323 participants and 4485 cases). Pooled RRs of all-cause mortality and CHD/CVD events per 1-MET higher level of MAC (corresponding to 1-km/h higher running/jogging speed) were 0.87 (95% confidence interval [CI], 0.84-0.90) and 0.85 (95% CI, 0.82-0.88), respectively. Compared with participants with high CRF, those with low CRF had an RR for all-cause mortality of 1.70 (95% CI, 1.51-1.92; P < .001) and for CHD/CVD events of 1.56 (95% CI, 1.39-1.75; P < .001), adjusting for heterogeneity of study design. Compared with participants with intermediate CRF, those with low CRF had an RR for all-cause mortality of 1.40 (95% CI, 1.32-1.48; P < .001) and for CHD/CVD events of 1.47 (95% CI, 1.35-1.61; P < .001), adjusting for heterogeneity of study design. Better CRF was associated with lower risk of all-cause mortality and CHD/CVD. Participants with a MAC of 7.9 METs or more had substantially lower rates of all-cause mortality and CHD/CVD events compared with those with a MAC of less 7.9 METs.
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                Author and article information

                Contributors
                Journal
                Med Sci Sports Exerc
                Med Sci Sports Exerc
                MSSE
                Medicine and Science in Sports and Exercise
                Lippincott Williams & Wilkins
                0195-9131
                1530-0315
                February 2024
                12 September 2023
                : 56
                : 2
                : 170-180
                Affiliations
                [1 ]Division of Sports and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Basel, SWITZERLAND
                [2 ]Assessment of Movement Behaviours Group (AMBer), Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, UNITED KINGDOM
                [3 ]National Institute for Health Research (NIHR) Leicester Biomedical Research Centre (BRC), University Hospitals of Leicester NHS Trust and the University of Leicester, Leicester, UNITED KINGDOM
                [4 ]Alliance for Research in Exercise, Nutrition and Activity (ARENA), Sansom Institute for Health Research, Division of Health Sciences, University of South Australia, Adelaide, AUSTRALIA
                Author notes
                [*]Address for correspondence: Arno Schmidt-Trucksäss, M.D., M.A., Head of Sports and Exercise Medicine, University of Basel, Birsstrasse 320 B, St. Jakob Turm, Basel 4052, Switzerland; E-mail: arno.schmidt-trucksaess@ 123456unibas.ch .
                Article
                MSSE_230721 00002
                10.1249/MSS.0000000000003299
                11882184
                37703330
                cde5db0b-52a1-4fee-b1f7-71284ea3a1ea
                Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American College of Sports Medicine.

                This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

                History
                : May 2023
                : August 2023
                Categories
                Clinical Sciences
                Custom metadata
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                T

                accelerometry,physical activity,normative data,cardiorespiratory fitness,ggir,activity monitors

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