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Challenges in collating spirometry reference data for South-Asian children: an observational study

Lum, S; Bountziouka, V; Quanjer, P; Sonnappa, S; Wade, A; Beardsmore, C; Chhabra, SK; Chudasama, RK; Cook, D; Harding, S; et al. Lum, S; Bountziouka, V; Quanjer, P; Sonnappa, S; Wade, A; Beardsmore, C; Chhabra, SK; Chudasama, RK; Cook, D; Harding, S; Kuehni, CE; Prasad, KVV; Whincup, P; Lee, S; Stocks, J (2016) Challenges in collating spirometry reference data for South-Asian children: an observational study. PLoS One, 11 (4). e0154336. ISSN 1932-6203 https://doi.org/10.1371/journal.pone.0154336
SGUL Authors: Cook, Derek Gordon Whincup, Peter Hynes

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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.

Item Type: Article
Additional Information: © 2016 Lum et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Keywords: General Science & Technology, MD Multidisciplinary
SGUL Research Institute / Research Centre: Academic Structure > Population Health Research Institute (INPH)
Journal or Publication Title: PLoS One
ISSN: 1932-6203
Dates:
DateEvent
27 April 2016Published
11 April 2016Accepted
Publisher License: Creative Commons: Attribution 4.0
Projects:
Project IDFunderFunder ID
WT094129MAWellcome Trusthttp://dx.doi.org/10.13039/100004440
068362/Z/02/ZWellcome Trusthttp://dx.doi.org/10.13039/100004440
10/013Asthma UKhttp://dx.doi.org/10.13039/501100000362
07/048Asthma UKhttp://dx.doi.org/10.13039/501100000362
32003B-122341Swiss National Science Foundationhttp://dx.doi.org/10.13039/501100001711
32003B_144068Swiss National Science Foundationhttp://dx.doi.org/10.13039/501100001711
PZ00P3_147987/1Swiss National Science Foundationhttp://dx.doi.org/10.13039/501100001711
PDFMP3-123162Swiss National Science Foundationhttp://dx.doi.org/10.13039/501100001711
MC_U130015185Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
MC_UU_12017/1Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
URI: https://openaccess.sgul.ac.uk/id/eprint/107831
Publisher's version: https://doi.org/10.1371/journal.pone.0154336

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