ALL-AGE EQUATIONS UPDATED WITH PRE-SCHOOL DATA (2009)

Stanojevic, S., Wade, A., Cole, T.J., Lum, S., Custovic, A., Silverman, M., Hall, G.L., Welsh, L., Kirkby, J., Nystad, W., Badier, M., Davis, S., Tuner, S., Piccioni, P., Vilozni, D., Eigen, H., Vlachos-Mayer, H., Zheng, J., Tomalak, W., Jones, M., Hankinson, J., and Stocks, J. 2009. Spirometry Centile Charts for Young Caucasian Children: The Asthma UK Collaborative Initiative. American Journal of Respiratory and Critical Care Medicine. 180(6); 547-522

ABSTRACT:

RATIONALE:

Advances in spirometry measurement techniques have made it possible to obtain measurements in children as young as 3 years of age; however, in practice, application remains limited by the lack of appropriate reference data for young children, which are often based on limited population-specific samples.

OBJECTIVES:

We aimed to build on previous models by collating existing reference data in young children (aged 3-7 years), to produce updated prediction equations that span the preschool years and that are also linked to established reference equations for older children and adults.

METHODS:

The Asthma UK Collaborative initiative was established to collate lung function data from healthy young children aged 3-7 years. Collaborators included researchers with access to pulmonary function test data in healthy preschool children. Spirometry centiles were created using the LMS (Lambda-Mu-Sigma) method and extend previously published equations down to 3 years of age.

MAIN RESULTS:

The Asthma UK centiles charts for spirometry are based on the largest sample of healthy young Caucasian children aged 3-7 years (n=3777) from 15 centers across 11 countries and provide a continuous reference with a smooth transition into adolescence and adulthood. These equations improve existing pediatric equations by considering the between-subject variability to define a more appropriate age-dependent lower limit of normal. The collated dataset reflects a variety of equipment, measurement protocols and population characteristics and may be generalizable across different populations.

CONCLUSIONS:

We present prediction equations for spirometry for preschool children and provide a foundation which will facilitate continued updating.

ADDITIONAL PARAMETERS

FEV0.5

Due to limited data, we were unable to create reference equations for FEV0.5; however until more data are available, unpublished reference equations for FEV0.5 can be found here (PDF, 28 KB). Please note these are based on a much smaller sample of children, compared to equations for other outcomes, and should be used with caution.

PEF

Similarly, due to limited data, we were unable to create reference equations for PEF; however until more data are available, unpublished reference equations for PEF can be found here (PDF, 28 KB). Please note these are based on a much smaller sample of children, compared to equations for other outcomes, and should be used with caution.