Derive continuous prediction equations and their lower limits of normal for spirometric indices, which are applicable globally.
Over 160,000 data points from 72 centres in 33 countries were shared with the European Respiratory Society Global Lung Function Initiative. Eliminating data that could not be used (mostly missing ethnic group, some outliers) left 97,759 records of healthy nonsmokers (55.3% females) aged 2.5–95 years.
Lung function data were collated, and prediction equations derived using the LMS (λ, µ, σ) method, which allows simultaneous modelling of the mean (mu), the coefficient of variation (sigma) and skewness (lambda) of a distribution family.
After discarding 23,572 records, mostly because they could not be combined with other ethnic or geographic groups, reference equations were derived for healthy individuals from 3–95 years for Caucasians (N=57,395), African Americans (N=3,545), and North (N=4,992) and South East Asians (N=8,255). FEV1 and FVC between ethnic groups differed proportionally from that in Caucasians, such that FEV1/FVC remained virtually independent of ethnic group. For individuals not represented by these four groups, or of mixed ethnic origins, a composite equation taken as the average of the above equations is provided to facilitate interpretation until a more appropriate solution is developed.
Spirometric prediction equations for the 3–95 age range are now available that include appropriate age-dependent lower limits of normal. They can be applied globally to different ethnic groups. Additional data from the Indian subcontinent, Arab, Polynesian, Latin American countries, and Africa will further improve these equations in the future.