Predictive equations for maximal respiratory pressures of children aged 7-10.

Braz J Phys Ther

Universidade do Estado de Santa Catarina (UDESC), Florianópolis, SC, Brazil. Electronic address:

Published: October 2017

Background: Measurements of respiratory muscle strength are widely used for assessment in children; however, clearly defined predictive equations for the Brazilian pediatric population have yet to be established.

Objective: To determine the prediction equations for maximal respiratory pressures in healthy children.

Method: Cross-sectional observational study with normal-weight students aged 7-10 years (n=399, 198 boys) with health attested by the (International Study of Asthma and Allergies in Childhood) questionnaire and medical history. Biometric data were evaluated (weight, height, and body mass index) as predictors. Spirometry and maximal expiratory pressure values were measured according to the recommendations of the American Thoracic Society. To verify data normality, the Shapiro-Wilk test was applied, and Pearson's test was used to verify the correlation between variables. The models were developed using simple linear regression and multivariate analyses. For all tests, the significance level was p<0.05.

Results: Boys showed higher values of maximal respiratory pressures than girls, both increasing with age. For boys, these values had moderate correlation with age, weight, and height and weak correlation with body mass index. For girls, maximum inspiratory pressure had a weak correlation with age and moderate correlation with biometric data. Maximum expiratory pressure had a moderate correlation with age and biometric measures. The best predictive models were found in boys: Log(MIP)=1.577+0.006×weight (kg) (R=14.1%) and Log(MEP)=1.282+0.409×height (m) (R=13.9%); and for girls: Log(MIP)=1.548+0.006×weight (kg) (R=15.0%) and Log(MEP)=1.524+0.012×age (years)+0.005×weight (kg) (R=21.6%).

Conclusion: Prediction equations for maximal respiratory pressures were developed for boys and girls. The biometric measurements were shown to have a weak influence on the results.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5537443PMC
http://dx.doi.org/10.1016/j.bjpt.2016.04.002DOI Listing

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