Lum, S; Bountziouka, V; Quanjer, P; Sonnappa, S; Wade, A; Beardsmore, C; Chhabra, S; ... Stocks, J; + view all Lum, S; Bountziouka, V; Quanjer, P; Sonnappa, S; Wade, A; Beardsmore, C; Chhabra, S; Chudasama, RK; Cook, DG; Harding, S; Kuehni, CE; Prasad, KVV; Whincup, PH; Lee, S; Stocks, J; - view fewer (2016) Challenges in collating spirometry reference data for South-Asian children: an observational study. PLoS One , 11 (4) , Article e0154336. 10.1371/journal.pone.0154336.

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Abstract

Availability of sophisticated statistical modelling for developing robust reference equations has improved interpretation of lung function results. In 2012, the Global Lung function Initiative(GLI) published the first global all-age, multi-ethnic reference equations for spirometry but these lacked equations for those originating from the Indian subcontinent (South-Asians). The aims of this study were to assess the extent to which existing GLI-ethnic adjustments might fit South-Asian paediatric spirometry data, assess any similarities and discrepancies between South-Asian datasets and explore the feasibility of deriving a suitable South-Asian GLI-adjustment. Methods: Spirometry datasets from South-Asian children were collated from four centres in India and five within the UK. Records with transcription errors, missing values for height or spirometry, and implausible values were excluded(n=110). Results: Following exclusions, cross-sectional data were available from 8,124 children (56.3% male; 5-17 years). When compared with GLI-predicted values from White Europeans, forced expired volume in 1s (FEV1) and forced vital capacity (FVC) in South-Asian children were on average 15% lower, ranging from 4-19% between centres. By contrast, proportional reductions in FEV1 and FVC within all but two datasets meant that the FEV1/FVC ratio remained independent of ethnicity. The ‘GLI-Other’ equation fitted data from North India reasonably well while ‘GLI-Black’ equations provided a better approximation for South-Asian data than the ‘GLI-White’ equation. However, marked discrepancies in the mean lung function z-scores between centres especially when examined according to socio-economic conditions precluded derivation of a single South-Asian GLI-adjustment. Conclusion: Until improved and more robust prediction equations can be derived, we recommend the use of ‘GLI-Black’ equations for interpreting most South-Asian data, although ‘GLI-Other’ may be more appropriate for North Indian data. Prospective data collection using standardised protocols to explore potential sources of variation due to socio-economic circumstances, secular changes in growth/predictors of lung function and ethnicities within the South-Asian classification are urgently required.

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