ArticleInternational journal of sports medicine2016
The Role of Body Habitus in Predicting Cardiorespiratory Fitness: The FRIEND Registry.
Article in International journal of sports medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Prediction of maximum oxygen uptake over time in adults: analysis from the FRIEND registry.Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologicas · 2025Article
- Association of Step Count with Cardiorespiratory Fitness: Results from the Virtual 2-Minute Step Test.Archives of rehabilitation research and clinical translation · 2024Article
- Associations of Relative Intensity of Physical Activity With Incident Cardiovascular Events and All-Cause Mortality.The journals of gerontology. Series A, Biological sciences and medical sciences · 2024Article
- Predicting Maximum Oxygen Uptake from Non-Exercise and Submaximal Exercise Tests in Paraplegic Men with Spinal Cord Injury.Healthcare (Basel, Switzerland) · 2023Article
- Estimating Cardiorespiratory Fitness Without Exercise Testing or Physical Activity Status in Healthy Adults: Regression Model Development and Validation.JMIR public health and surveillance · 2022Article
- Accuracy of Non-Exercise Estimated Cardiorespiratory Fitness in Japanese Adults.International journal of environmental research and public health · 2021Article
- Accuracy of Nonexercise Prediction Equations for Assessing Longitudinal Changes to Cardiorespiratory Fitness in Apparently Healthy Adults: BALL ST Cohort.Journal of the American Heart Association · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
This study aimed to validate and cross-validate a non-exercise prediction model from a large and apparently healthy US cohort of individuals who underwent an analysis of body habitus (waist circumference (WC) and body mass index (BMI)) with measured CRF. The large cohort (5 030 individuals) was split into validation (4 030) and cross-validation (1 000) groups, whereby waist circumference and maximal aerobic capacity (VO2max) were assessed by rigorously approved laboratories. VO2max was estimated in 2 multiple regression equations using age, sex and either WC (r=0.77; standard error of the estimate (SEE) 6.70 mLO2∙kg(-1)∙min(-1)) or BMI (r=0.76; SEE 6.89 mLO2∙kg(-1)∙min(-1)).Cross-validation yielded similar results. However, as VO2max increased, there was increased bias, suggesting VO2max may be underestimated at higher values. Both WC and BMI prediction models yielded similar findings, with WC having a slightly smaller SEE. These measures of body habitus appear to be adequate in predicting CRF using non-exercise parameters, even without a measure of physical activity. Caution should be taken when using these equations in more fit individuals.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.