Paediatric and Adult African Spirometry II: A Determination of Reference Equation in South African Children and Adults

Brief Summary

Detailed Description

Pulmonary function testing is the most widely used tool for the diagnosis, severity assessment, management, risk factor categorization and follow-up of individuals with chronic lung disease. Africa has a high burden of infectious respiratory diseases which include tuberculosis and human immunodeficiency virus-related lung disease.Coupled with this is an increasing burden of non-communicable respiratory diseases; which include chronic obstructive pulmonary disease, emphysema, bronchiectasis and asthma \[1,2\]. The management of these colliding epidemics requires correct diagnosis and management in order to ensure adequate resource allocation and avoidance of unnecessary costs. A proviso to the use of lung function testing is the determination of "normal" values; which are determined for age, gender, height and ethnicity for the relevant population \[3\]. These "normal' values should also take into account the normal lung function decline associated and the aging process. It is well recognised that the comparison of an individual patients' results to an ethnically inappropriate population may lead to the under or -over diagnosis of disease, inappropriate treatments and result in increased burden on individuals, their families and the healthcare system \[4-6\]. There are numerous published reference equations, but the recently published Global Lung Initiative multi-ethnic reference equations published in 2012(GLI2012) collated the largest spirometry data set from individuals aged 2.5 to 95 years \[7\]. The innovation in GLI2012 was that it allowed for the smooth transitioning of data from childhood adulthood using sophisticated statistical modelling. The investigators have previously collated data in phase 1 of this study using the GLI methodology on published African spirometry data from 26 594 individuals, and found a wide variation in predicted z-scores when fitting the African data to GLI2012, with a fairly good match between the black African males and African-Americans \[15\]. This dataset was skewed as due to the large number of African males and with a disproportionally larger contribution of data from North Africa and therefore requires confirmation. The investigators therefore propose to conduct a prospective well-designed study to include a representative sample of both adults and children (4000); to verify the validity of the retrospective pilot data, in a South African population.

Primary Outcomes