Physical Activity as a Long-Term Predictor of Peak Oxygen Uptake

Aspenes, Stian Thoresen; Nauman, Javaid; Nilsen, Tom Ivar Lund; Vatten, Lars J.; Wisløff, Ulrik

doi:10.1249/mss.0b013e318216ea50

Cited by 33 publications

(34 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…This may have attenuated the parent-offspring associations in the physical activity analyses. However, validation studies have shown that questionnaires may be useful for classifying people into broad categorisations of physical activity,33 and a recent study showed that the questions used in this study were a good long-term predictor of cardiorespiratory fitness 34…”

Section: Discussionmentioning

confidence: 77%

Tracking of cardiovascular risk factors across generations: family linkage within the population-based HUNT study, Norway

Vik

Romundstad

Nilsen

2013

J Epidemiol Community Health

View full text Add to dashboard Cite

show abstract

Section: Discussionmentioning

confidence: 77%

Tracking of cardiovascular risk factors across generations: family linkage within the population-based HUNT study, Norway

Vik

Romundstad

Nilsen

2013

J Epidemiol Community Health

View full text Add to dashboard Cite

show abstract

“…Most research examining the relationship between PA and CRF, has used PA as an independent variable and CRF as a dependent variable. In this tradition, Aspenes et al (Aspenes, Nauman, Nilsen, Vatten, & Wisloff, 2011) found that self-reported PA level at baseline was positively associated with CRF 23 years later, while Loe et al (Loe, Rognmo, Saltin, & Wisloff, 2013) found a poor overall correlation (r=0.24) between self-reported PA level and oxygen uptake. In contrast to these studies we used CRF as an independent variable in our statistical analysis.…”

Section: Discussionmentioning

confidence: 99%

“…Moreover, the strongest single correlate of overall PA, CRF, was measured by direct ergospirometry instead of using estimated CRF values or substitute measures of CRF, which is more common in large population-based public health studies (Aspenes et al, 2011). …”

Section: Discussionmentioning

confidence: 99%

Correlates of Objectively Measured Physical Activity Among Norwegian Older Adults: The Generation 100 Study

Viken

Aspvik²,

Ingebrigtsen³

et al. 2016

Journal of Aging and Physical Activity

Self Cite

View full text Add to dashboard Cite

The aim of this study was to identify how demographics, physical activity (PA) history, and environmental and biological correlates are associated with objectively measured PA among older adults. PA was assessed objectively in 850 older adults (70–77 years, 48% females) using the ActiGraph GT3X+ activity monitor. Hierarchical multiple regression analysis was used to identify important PA correlates. The included correlates explained 27.0% of the variance in older adult’s PA. Cardiorespiratory fitness (CRF), gender, and season were the most important correlates, explaining 10.1%, 3.9%, and 2.7% of the variance, respectively. PA was positively associated with CRF, females were more physically active than males, and PA increased in warmer months compared with colder months. This is, to our knowledge, the largest study of PA correlates in older adults that has combined objectively measured PA and CRF. Our findings provide new knowledge about how different correlates are associated with PA.

show abstract

“…Earlier studies have suggested that non-exercise models can be valid predictors of VO 2 peak for heterogeneous samples [11] and can give relatively accurate results conveniently [5]. Recently, Aspenes et al (2011) [3] have further suggested that "valid and reliable physical activity questionnaires that predict cardiorespiratory fitness may be valuable instruments for monitoring physical fitness in a population, when more costly and time-consuming techniques are not feasible".…”

Section: Discussionmentioning

confidence: 99%

Estimation of aerobic fitness among young men without exercise test

Tanskanen

Kyröläinen

Santtila

et al. 2015

Biomedical Human Kinetics

View full text Add to dashboard Cite

SummaryStudy aim: to develop and estimate the validity of non-exercise methods to predict VO 2 max among young male conscripts entering military service in order to divide them into the different physical training groups. Material and methods: fifty males (age 19.7 ± 0.3 years) reported their physical activity before military service by IPAQ and SIVAQ questionnaires. Furthermore, Jackson's non-exercise method was used to estimate VO 2 max. Body mass and height were measured, body mass index calculated and VO 2 max measured directly in a maximal treadmill test. Subjects were randomly divided into two groups. The results of the Group 1 (N = 25) were used to develop a regression equation to estimate VO 2 max. The results of the Group 2 (N = 25) were used to evaluate the validity of the developed non-exercise methods and Jackson's non-exercise methods to estimate VO 2 max by Bland and Altman plot. The validity was further evaluated by comparing the results to 12-minute running test performed by 877 male conscripts (age 19.6 ± 0.2 years). Results: the developed models explained 68-74% of the variation in VO 2 max. Mean difference between directly measured and estimated VO 2 max was not significant, while Jackson's method overestimated VO 2 max (p < 0.001). Both developed models were equally valid to divide conscripts into tertile group of fitness. However, 5% of the conscripts were classified into the highest fitness group based on both methods, but they were actually in the lowest fitness group based on a running test. Conclusion: in practice, these findings suggest that developed methods can be used as a tool to divide conscripts into different fitness groups in the very beginning of their military service.

show abstract

Physical Activity as a Long-Term Predictor of Peak Oxygen Uptake

Cited by 33 publications

References 33 publications

Tracking of cardiovascular risk factors across generations: family linkage within the population-based HUNT study, Norway

Tracking of cardiovascular risk factors across generations: family linkage within the population-based HUNT study, Norway

Correlates of Objectively Measured Physical Activity Among Norwegian Older Adults: The Generation 100 Study

Estimation of aerobic fitness among young men without exercise test

Contact Info

Product

Resources

About