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Sagelv EH, Casolo A, Eggen AE, Heitmann KA, Johansen KR, Løchen ML, Mathiesen EB, Morseth B, Njølstad I, Osborne JO, Hagerupsen K, Pedersen S, Wilsgaard T. Females Display Lower Risk of Myocardial Infarction From Higher Estimated Cardiorespiratory Fitness Than Males: The Tromsø Study 1994-2014. Mayo Clin Proc Innov Qual Outcomes 2024; 8:62-73. [PMID: 38268988 PMCID: PMC10806283 DOI: 10.1016/j.mayocpiqo.2023.12.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2024] Open
Abstract
Objective To examine the dose-response association between estimated cardiorespiratory fitness (eCRF) and risk of myocardial infarction (MI). Patients and Methods Adults who attended Tromsø Study surveys 4-6 (Janurary 1,1994-December 20, 2008) with no previous cardiovascular disease were followed up through December 31, 2014 for incident MI. Associations were examined using restricted cubic splines Fine and Gray regressions, adjusted for education, smoking, alcohol, diet, sex, adiposity, physical activity, study survey, and age (timescale) in the total cohort and subsamples with hyperlipidemia (n=2956), hypertension (n=8290), obesity (n=5784), metabolic syndrome (n=1410), smokers (n=3823), and poor diet (n=3463) and in those who were physically inactive (n=6255). Results Of 14,285 participants (mean age ± SD, 53.7±11.4 years), 979 (6.9%) experienced MI during follow-up (median, 7.2 years; 25th-75th, 5.3-14.6 years). Females with median eCRF (32 mL/kg/min) had 43% lower MI risk (subdistributed hazard ratio [SHR], 0.57; 95% CI, 0.48-0.68) than those at the 10th percentile (25 mL/kg/min) as reference. The lowest MI risk was observed at 47 mL/kg/min (SHR, 0.02; 95% CI, 0.01-0.11). Males had 26% lower MI risk at median eCRF (40 mL/kg/min; SHR, 0.74; 95% CI, 0.63-0.86) than those at the 10th percentile (32 mL/kg/min), and the lowest risk was 69% (SHR, 0.31; 95% CI, 0.14-0.71) at 60 mL/kg/min. The associations were similar in subsamples with cardiovascular disease risk factors. Conclusion Higher eCRF associated with lower MI risk in females and males, but associations were more pronounced among females than those in males. This suggest eCRF as a vital estimate to implement in medical care to identify individuals at high risk of future MI, especially for females.
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Affiliation(s)
- Edvard H. Sagelv
- School of Sport Sciences, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway
| | - Andrea Casolo
- Department of Biomedical Sciences, University of Padua, Padua, Italy
| | - Anne Elise Eggen
- Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway
| | - Kim Arne Heitmann
- School of Sport Sciences, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway
| | - Kristoffer R. Johansen
- School of Sport Sciences, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway
| | - Maja-Lisa Løchen
- Department of Clinical Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway
| | - Ellisiv B. Mathiesen
- Department of Clinical Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway
- Department of Neurology, University Hospital of North Norway, Tromsø, Norway
| | - Bente Morseth
- School of Sport Sciences, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway
| | - Inger Njølstad
- Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway
| | - John O. Osborne
- School of Sport Sciences, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway
| | - Karianne Hagerupsen
- School of Sport Sciences, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway
| | - Sigurd Pedersen
- School of Sport Sciences, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway
| | - Tom Wilsgaard
- Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway
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Wang Z, Zhang Q, Lan K, Yang Z, Gao X, Wu A, Xin Y, Zhang Z. Enhancing instantaneous oxygen uptake estimation by non-linear model using cardio-pulmonary physiological and motion signals. Front Physiol 2022; 13:897412. [PMID: 36105296 PMCID: PMC9465676 DOI: 10.3389/fphys.2022.897412] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Accepted: 07/29/2022] [Indexed: 11/30/2022] Open
Abstract
Oxygen uptake (VO2) is an important parameter in sports medicine, health assessment and clinical treatment. At present, more and more wearable devices are used in daily life, clinical treatment and health care. The parameters obtained by wearables have great research potential and application prospect. In this paper, an instantaneous VO2 estimation model based on XGBoost was proposed and verified by using data obtained from a medical-grade wearable device (Beijing SensEcho) at different posture and activity levels. Furthermore, physiological characteristics extracted from single-lead electrocardiogram, thoracic and abdominal respiration signal and tri-axial acceleration signal were studied to optimize the model. There were 29 healthy volunteers recruited for the study to collect data while stationary (lying, sitting, standing), walking, Bruce treadmill test and recuperating with SensEcho and the gas analyzer (Metalyzer 3B). The results show that the VO2 values estimated by the proposed model are in good agreement with the true values measured by the gas analyzer (R2 = 0.94 ± 0.03, n = 72,235), and the mean absolute error (MAE) is 1.83 ± 0.59 ml/kg/min. Compared with the estimation method using a separate heart rate as input, our method reduced MAE by 54.70%. At the same time, other factors affecting the performance of the model were studied, including the influence of different input signals, gender and movement intensity, which provided more enlightenment for the estimation of VO2. The results show that the proposed model based on cardio-pulmonary physiological signals as inputs can effectively improve the accuracy of instantaneous VO2 estimation in various scenarios of activities and was robust between different motion modes and state. The VO2 estimation method proposed in this paper has the potential to be used in daily life covering the scenario of stationary, walking and maximal exercise.
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Affiliation(s)
- Zhao Wang
- Medical School of Chinese PLA, Beijing, China
| | - Qiang Zhang
- School of Life Science, Beijing Institute of Technology, Beijing, China
| | - Ke Lan
- Beijing SensEcho Science and Technology Co Ltd, Beijing, China
| | - Zhicheng Yang
- PAII Inc., Palo Alto, Santa Clara, CA, United States
| | - Xiaolin Gao
- Institute of Sports Science, General Administration of Sport of China, Beijing, China
| | - Anshuo Wu
- The Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, United States
| | - Yi Xin
- School of Life Science, Beijing Institute of Technology, Beijing, China
- *Correspondence: Yi Xin, ; Zhengbo Zhang,
| | - Zhengbo Zhang
- Center for Artificial Intelligence in Medicine, Chinese PLA General Hospital, Beijing, China
- *Correspondence: Yi Xin, ; Zhengbo Zhang,
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Nevill AM, DE Menezes-Junior FJ, DE Jesus ÍC, DE Fatima Aguiar Lopes M, Corazza PRP, Tadiotto MC, Mota J, Leite N. Predicting Cardiorespiratory Fitness Using the 20-m Shuttle Run Test: New Insights Using Nonlinear Allometry. Med Sci Sports Exerc 2021; 53:1624-1629. [PMID: 33587552 DOI: 10.1249/mss.0000000000002637] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
PURPOSE Recently, doubts have been raised concerning the validity of the 20-m shuttle run test (20mSRT) to predict cardiorespiratory fitness (CRF) in youth. Despite these doubts, authors continue to provide powerful evidence that CRF can be predicted reliably using the 20mSRT albeit using contrasting models. Therefore, we aimed to compare a new linear model with an alternative allometric model to predict CRF (peak oxygen uptake, V˙O2peak) using the 20mSRT. METHODS The study included 148 adolescents (43% girls) age 13.37 ± 1.84 yr. Adolescents were randomly assigned to validation (n = 91) and cross-validation (n = 57) groups. V˙O2peak was measured using a gas analyzer in both maximal exercise tests in the laboratory and the 20mSRT. Multiple linear regression methods were applied to develop the linear models using the 20mSRT (laps), body mass index, and body fat percentage. Alternative allometric models were also proposed/fitted using the 20mSRT (laps), height, and body mass. RESULTS The criterion validity values of both the linear and the allomeric models were found to be acceptable, with R2 = 82.5% and 82.7% respectively, providing reassuring evidence that the 20mSRT can be used with confidence to predict CRF. However, the allometric model identified a height-to-mass ratio, not dissimilar to the inverse body mass index (known to be a measure of leanness), to be associated with CRF. The allometric model also revealed that the rise in energy cost (V˙O2peak) with increasing laps was exponential. This will more accurately reflect the nonlinear rise in energy demand of shuttle running as the test progresses to exhaustion. CONCLUSIONS These observations provided powerful evidence that allometric models are more than satisfactory in terms of both criterion and construct validity when predicting CRF (V˙O2peak) using the 20mSRT.
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Affiliation(s)
- Alan M Nevill
- Faculty of Education, Health and Wellbeing, University of Wolverhampton, Walsall Campus, Walsall, UNITED KINGDOM
| | | | | | | | | | | | - Jorge Mota
- Department of Centro de Investigação em Actividade Fìsica, Saúde e Lazer (CIAFEL), University of Porto, Porto, PORTUGAL
| | - Neiva Leite
- Department of Physical Education, Federal University of Paraná, Curitiba, BRAZIL
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Nevill AM, Myers J, Kaminsky LA, Arena R, Myers TD. Comparing individual and population differences in minute ventilation/carbon dioxide production slopes using centile growth curves and log-linear allometry. ERJ Open Res 2021; 7:00088-2021. [PMID: 34322548 PMCID: PMC8311134 DOI: 10.1183/23120541.00088-2021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 05/20/2021] [Indexed: 11/28/2022] Open
Abstract
Identifying vulnerable groups and/or individuals’ cardiorespiratory fitness (CRF) is an important challenge for clinicians/researchers alike. To quantify CRF accurately, the assessment of several variables is now standard practice including maximal oxygen uptake (VʹCO2) and ventilatory efficiency, the latter assessed using the minute ventilation/carbon dioxide production (VʹE/VʹCO2) slope. Recently, reference values (centiles) for VʹE/VʹCO2 slopes for males and females aged 20 to 80 have been published, using cardiopulmonary exercise testing (CPX) data (treadmill protocol) from the Fitness Registry and the Importance of Exercise National Database (FRIEND Registry). In the current observational study we provide centile curves for the FRIEND Registry VʹE/VʹCO2 slopes, fitted using the generalised additive model for location, scale and shape (GAMLSS), to provide individuals with a more precise estimate of where their VʹE/VʹCO2 slopes fall within the population. We also confirm that by adopting allometric models (incorporating a log transformation), the resulting ANCOVAs provided more normal and homoscedastic residuals, with superior goodness-of-fit using the Akaike information criterion (AIC)=14 671 (compared with traditional ANCOVA's AIC=15 008) that confirms allometric models are vastly superior to traditional ANCOVA models. In conclusion, providing sex-by-age centile curves rather than referring to reference tables for ventilatory efficiency (VʹE/VʹCO2 slopes) will provide more accurate estimates of where an individual's particular VʹE/VʹCO2 slope falls within the population. Also, by adopting allometric models researchers are more likely to identify real and valid inferences when analysing population/group differences in VʹE/VʹCO2 slopes. This article provides centile curves of VʹE/VʹCO2slopes and demonstrates that by adopting log-linear models, more trustworthy inferences with group differences will also be foundhttps://bit.ly/3uitACS
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Affiliation(s)
- Alan M Nevill
- Faculty of Education, Health and Wellbeing, University of Wolverhampton, Walsall, UK
| | - Jonathan Myers
- Division of Cardiology, VA Palo Alto Healthcare System, Palo Alto, CA, USA.,Stanford University, Stanford, CA, USA
| | - Leonard A Kaminsky
- Fisher Institute of Health and Well-Being and Clinical Exercise Physiology Laboratory, Ball State University, Muncie, IN, USA
| | - Ross Arena
- Dept of Physical Therapy, College of Applied Sciences, University of Illinois at Chicago, Chicago, IL, USA
| | - Tony D Myers
- Sport and Health, Newman University, Birmingham, UK
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Response to the Comment by Armstrong and Welsman on 'Developing a New Curvilinear Allometric Model to Improve the Fit and Validity of the 20-m Shuttle Run Test as a Predictor of Cardiorespiratory Fitness in Adults and Youth'. Sports Med 2021; 51:1595-1597. [PMID: 34014501 DOI: 10.1007/s40279-021-01464-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/29/2021] [Indexed: 10/21/2022]
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Nevill AM, Myers J, Kaminsky LA, Arena R. Comments on “validation of equations to estimate the peak oxygen uptake in adolescents from 20 metres shuttle run test”. J Sports Sci 2020; 39:900-902. [DOI: 10.1080/02640414.2020.1850985] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Affiliation(s)
- Alan M. Nevill
- Faculty of Education, Health and Wellbeing, University of Wolverhampton, Walsall Campus, Walsall, UK
| | - Jonathan Myers
- Division of Cardiology, VA Palo Alto Healthcare System, Palo Alto, CA, USA
- Stanford University, Stanford, CA, USA
| | | | - Ross Arena
- Department of Physical Therapy, College of Applied Sciences, University of Illinois at Chicago, Chicago, IL, USA
- Healthy Living for Pandemic Event Protection (HL – PIVOT) Network, Chicago, IL, USA
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Giuriato M, Nevill A, Kawczynski A, Lovecchio N. Body size and shape characteristics for Cooper's 12 minutes run test in 11-13 years old Caucasian children: an allometric approach. J Sports Med Phys Fitness 2020; 60:417-421. [DOI: 10.23736/s0022-4707.19.10282-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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8
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Nevill AM, Myers J, Kaminsky LA, Arena R. Improving reference equations for cardiorespiratory fitness using multiplicative allometric rather than additive linear models: Data from the Fitness Registry and the Importance of Exercise National Database Registry. Prog Cardiovasc Dis 2019; 62:515-521. [PMID: 31759954 DOI: 10.1016/j.pcad.2019.11.011] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2019] [Accepted: 11/17/2019] [Indexed: 11/29/2022]
Abstract
New improved reference equations for cardiorespiratory fitness have recently been published, using Data from the Fitness Registry and the Importance of Exercise National Database (FRIEND Registry). The new linear equation for VO2max (ml.kg-1.min-1) was additive, derived using multiple-linear regression. An alternative multiplicative allometric model has also been published recently, thought to improve further the quality of fit. The purpose of the current study was to compare the accuracy and quality/goodness-of-fit of the linear, additive model with the multiplicative allometric model using the FRIEND database. The results identified that the allometric model out performs the linear model based on all model-comparison criteria. The allometric model demonstrates; 1) greater explained variance (R2 = 0.645; R = 0.803) vs. (R2 = 0.62; R = 0.79), 2) residuals that were more normally distributed, 3) residuals that yielded less evidence of curvature, 4) superior goodness-of-fit statistics i.e., greater maximum log-likelihood (MLL) and smaller Akaike Information Criterion (AIC) statistics, 5) less systematic bias together with smaller unexplained standard error of estimates. The Bland and Altman plots also confirmed little or no evidence of curvature with the allometric model, but systematic curvature (lack-of-fit) in the linear model. The multiplicative allometric model to predict VO2max was; VO2max (ml.kg-1.min-1) = M-0.854 · H1.44 · exp. (0.424-0.346 · (sex) -0.011.age), where M = body mass and H = height (R2 = 0.645; R = 0.803) and sex is entered as a [0,1] indicator variable (male = 0 and female = 1). Another new insight obtained from the allometric model (providing construct validity) is that the height-to-body-mass ratio is similar to inverse body mass index or the lean body mass index, both associated with leanness when predicting VO2max. In conclusion adopting allometric models will provide more accurate predictions of VO2max (ml.kg-1.min-1) using more plausible, biologically sound and interpretable models.
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Affiliation(s)
- Alan M Nevill
- Faculty of Education, Health and Wellbeing, University of Wolverhampton, Walsall Campus, Walsall WS1 3BD, UK.
| | - Jonathan Myers
- Division of Cardiology, VA Palo Alto Healthcare System, Palo Alto, CA, United States of America; Stanford University, Stanford, CA, United States of America
| | - Leonard A Kaminsky
- Fisher Institute of Health and Well-Being and Clinical Exercise Physiology Laboratory, Ball State University, Muncie, IN, United States of America
| | - Ross Arena
- Department of Physical Therapy, College of Applied Sciences, University of Illinois at Chicago, Chicago, IL, United States of America
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9
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Mylius CF, Krijnen WP, van der Schans CP, Takken T. Peak oxygen uptake reference values for cycle ergometry for the healthy Dutch population: data from the LowLands Fitness Registry. ERJ Open Res 2019; 5:00056-2018. [PMID: 30949491 PMCID: PMC6441675 DOI: 10.1183/23120541.00056-2018] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2018] [Accepted: 02/06/2019] [Indexed: 11/05/2022] Open
Abstract
Peak oxygen uptake (V′O2peak) is recognised as the best expression of aerobic fitness. Therefore, it is essential that V′O2peak reference values are accurate for interpreting a cardiopulmonary exercise test (CPET). These values are country specific and influenced by underlying biological ageing processes. They are normally stratified per paediatric and adult population, resulting in a discontinuity at the transition point between prediction equations. There are currently no age-related reference values available for the lifespan of individuals in the Dutch population. The aim of this study is to determine the best-fitting regression model for V′O2peak in the healthy Dutch paediatric and adult populations in relation to age. In this retrospective study, CPET cycle ergometry results of 4477 subjects without reported somatic diseases were included (907 females, age 7.9–65.0 years). Generalised additive models were employed to determine the best-fitting regression model. Cross-validation was performed against an independent dataset consisting of 3518 subjects (170 females, age 6.8–59.0 years). An additive model was the best fitting with the largest predictive accuracy in both the primary (adjusted R2=0.57, standard error of the estimate (see)=556.50 mL·min−1) and cross-validation (adjusted R2=0.57, see=473.15 mL·min−1) dataset. This study provides a robust additive regression model for V′O2peak in the Dutch population. Peak oxygen uptake has a nonlinear dependence on years of age in the paediatric and adult Dutch populationshttp://ow.ly/H3fH30nIjRy
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Affiliation(s)
- Caspar Frederik Mylius
- Hanze University of Applied Sciences, Research Group Healthy Ageing, Allied Health Care and Nursing, Groningen, The Netherlands.,Centre of Expertise Primary Care Groningen (ECEZG), Groningen, The Netherlands
| | - Wilhelmus Petrus Krijnen
- Hanze University of Applied Sciences, Research Group Healthy Ageing, Allied Health Care and Nursing, Groningen, The Netherlands.,Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, Groningen, The Netherlands
| | - Cornelis Peter van der Schans
- Hanze University of Applied Sciences, Research Group Healthy Ageing, Allied Health Care and Nursing, Groningen, The Netherlands.,University of Groningen, University Medical Center Groningen, Dept of Rehabilitation Medicine, Groningen, The Netherlands.,University of Groningen, University Medical Center Groningen, Health Psychology Research, Groningen, The Netherlands
| | - Tim Takken
- University Medical Center Utrecht, Utrecht, The Netherlands
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Predicting oxygen uptake responses during cycling at varied intensities using an artificial neural network. BIOMEDICAL HUMAN KINETICS 2019. [DOI: 10.2478/bhk-2019-0008] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
Summary
Study aim: Oxygen Uptake (VO2) is avaluable metric for the prescription of exercise intensity and the monitoring of training progress. However, VO2 is difficult to assess in anon-laboratory setting. Recently, an artificial neural network (ANN) was used to predict VO2 responses during aset walking protocol on the treadmill [9]. The purpose of the present study was to test the ability of an ANN to predict VO2 responses during cycling at self-selected intensities using Heart Rate (HR), time derivative of HR, power output, cadence, and body mass data.
Material and methods: 12 moderately-active adult males (age: 21.1 ± 2.5 years) performed a50-minute bout of cycling at a variety of exercise intensities. VO2, HR, power output, and cadence were recorded throughout the test. An ANN was trained, validated and tested using the following inputs: HR, time derivative of HR, power output, cadence, and body mass. A twelve-fold hold-out cross validation was conducted to determine the accuracy of the model.
Results: The ANN accurately predicted the experimental VO2 values throughout the test (R2 = 0.91 ± 0.04, SEE = 3.34 ± 1.07 mL/kg/min).
Discussion: This preliminary study demonstrates the potential for using an ANN to predict VO2 responses during cycling at varied intensities using easily accessible inputs. The predictive accuracy is promising, especially considering the large range of intensities and long duration of exercise. Expansion of these methods could allow ageneral algorithm to be developed for a more diverse population, improving the feasibility of oxygen uptake assessment.
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