Spirometry centile charts for young Caucasian children: the Asthma UK Collaborative Initiative

Sanja Stanojevic, Angie Wade, Tim J. Cole, Sooky Lum, Adnan Custovic, Mike Silverman, Graham L. Hall, Liam Welsh, Jane Kirkby, Wenche Nystad, Monique Badier, Stephanie Davis, Steven Turner, Pavilio Piccioni, Daphna Vilzoni, Howard Eigen, Helen Vlachos-Mayer, Jinping Zheng, Waldemar Tomalak, Marcus JonesJohn L. Hankinson, Janet Stocks

Research output: Contribution to journalArticlepeer-review

174 Citations (Scopus)


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 yr), 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 to 7 years. Collaborators included researchers with access to pulmonary function test data in healthy preschool children. Spirometry centiles were created using the LMS (lambda, micro, sigma) method and extend previously published equations down to 3 years of age.

MEASUREMENTS AND MAIN RESULTS: The Asthma UK centile charts for spirometry are based on the largest sample of healthy young Caucasian children aged 3-7 years (n = 3,777) 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 data set 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 that will facilitate continued updating.
Original languageEnglish
Pages (from-to)547-552
Number of pages6
JournalAmerican Journal of Respiratory and Critical Care Medicine
Issue number6
Early online date2 Jul 2009
Publication statusPublished - 15 Sep 2009


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