Spirometric Prediction Equations for Hispanic Children and Adults in New Mexico

Abstract

We conducted a population-based survey of respiratory diseases and lung function in a New Mexico Hispanic community, and developed spirometric prediction equations based on data from 576 children and adults. Spirometric test procedures were followed as recommended by the American Thoracic Society. For children 6 through 18 yr of age, we used a logarithmic model to predict spirometric parameters. We used simple linear regression for adults 25 through 80 yr of age. On the basis of exploratory analyses, we excluded adult subjects who were obese, defined as a body mass index of 30 kg/m2 or greater. This report describes these regressions. We did not perform regression analysis for those subjects between 19 and 24 yr of age because of small numbers and the inappropriateness of grouping these subjects with older adults for regression analysis. As an alternative to a regression equation for this age group specifically, we propose linear interpolation between values obtained using prediction equations developed for children and for adults. Finally, we compared the percent predicted values obtained from our internal prediction equations with equations from other populations of white children and adults. In general, the comparison equations underestimated the percent predicted values in our population.

Defining race/ethnicity and explaining difference in research studies on lung function

“…[17] Technical factors 1988 USA ''With the sample sizes typically available for developing prediction equations, sampling variation will remain an explanation for all but extreme differences.'' [18] Other 1993 Israel ''Anthropometric measurements could not explain interethnic variability in spirometric values;…could be due to ethnic differences in growth velocity.'' [19] Mixed explanations 1927 China ''It may prove that there is a larger variability in nationals of one country, caused by climate, activity and bodily build than is found between nations or races.''…”

The necessity of building population specific prediction equations for clinical assessment of pulmonary function tests

“…The main independent variables used for spirometric prediction equations are anthropometric measurements such as height, weight and body mass index [2]. Many researchers [1,2,4,10] have developed univariate spirometric prediction equations based on height or the natural logarithm of height.…”

“…Many researchers [1,2,4,10] have developed univariate spirometric prediction equations based on height or the natural logarithm of height. Similarly to Marcus et al [5] we found that height is the main predictor of PFT parameters.…”

IL10 gene polymorphisms are associated with asthma phenotypes in children

“…The bronchodilator albuterol was administered by metered dose inhaler with a spacer and at least 15 min elapsed before post-bronchodilator measurements were obtained. The FEV 1 measured after bronchodilator administration as a percent of predicted FEV 1 (FEV 1 PP) was the phenotype used to assess lung function [Knudson et al, 1983;Coultas et al, 1988;Wang et al, 1993;Weiss et al, 2000]. The bronchodilator responsiveness phenotypes analyzed were absolute change in FEV 1 before and after bronchodilator in mLs (ABS BD ), the absolute change as a percent of predicted FEV 1 (Pred BD ), and the absolute change as a percent of baseline FEV 1 (FEV BD ).…”