Prediction of Cardiorespiratory Fitness Level of Young Healthy Women Using Non-Exercise Variables

Prediction of Cardiorespiratory Fitness Level of Young Healthy Women Using Non-Exercise Variables

Cardiorespiratory fitness (CRF) is considered an important indicator of health in children and adults. The main contribution of this paper is an analysis of cardiorespiratory fitness predictive models among a population of healthy and young women, using the non-exercise variables. The study was cond...

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Bibliographic Details
Published in:Applied sciences Vol. 13; no. 24; p. 13251
Main Authors: Zadarko, Emilian, Przednowek, Karolina H, Barabasz, Zbigniew, Zadarko-Domaradzka, Maria, Nizioł-Babiarz, Edyta, Hulewicz, Tomasz, Niewczas-Czarna, Klaudia, Huzarski, Maciej, Iskra, Janusz, Gouveia, Élvio Rúbio, Przednowek, Krzysztof
Format: Journal Article
Language:English
Published: Basel MDPI AG 01-12-2023
Subjects:
Age
Body composition
Body fat
Body mass index
cardiorespiratory fitness
Exercise
Females
Gender
Health aspects
Heart rate
Hypertension
Insulin resistance
Leisure
maximal oxygen uptake
non-exercise variables
Physical fitness
predictive models
Questionnaires
Variables
Women
Womens health
Poland
Minnesota
United States > US
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Summary:Cardiorespiratory fitness (CRF) is considered an important indicator of health in children and adults. The main contribution of this paper is an analysis of cardiorespiratory fitness predictive models among a population of healthy and young women, using the non-exercise variables. The study was conducted on a group of 154 healthy women (aged 20.3 ± 1.2) from selected academic centers in Poland. The VO2max was measured using a Cosmed K4b2 portable analyzer during a 20 m shuttle test. In addition, selected anthropomotor parameters including body composition components were measured for each subject. The participants’ leisure-time physical activity was assessed using the Minnesota Leisure-Time Physical Activity Questionnaire. The Ridge regression was the most accurate model for estimating VO2max from anthropometric parameters. The most accurate model based on the level of leisure-time physical activity was calculated using stepwise regression for which the prediction error was at the level of 6.68 (mL·kg−1·min−1). The best model calculated from all non-exercise variables (age, anthropometric parameters, and leisure-time physical activity) had only two predictors: waist circumference and total physical activity, and had a prediction error equal to 6.20 (mL·kg−1·min−1).
ISSN:2076-3417
2076-3417
DOI:10.3390/app132413251