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Challenges in Collating Spirometry Reference Data for South-Asian Children: An Observational Study.

Sooky Lum1, Vassiliki Bountziouka1, Philip Quanjer2

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This summary is machine-generated.

South-Asian children exhibit lower lung function (FEV1, FVC) compared to White Europeans. Current GLI equations require refinement for accurate spirometry interpretation in this population.

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Area of Science:

  • Pulmonary Medicine
  • Pediatric Respiratory Health
  • Global Health Disparities

Background:

  • Spirometry is crucial for diagnosing pediatric respiratory conditions.
  • Existing Global Lung Initiative (GLI) equations are primarily based on European populations.
  • Accurate lung function prediction is essential for appropriate clinical management of children worldwide.

Purpose of the Study:

  • To evaluate the suitability of current GLI spirometry prediction equations for South-Asian children.
  • To identify potential ethnic and socio-economic variations in lung function among South-Asian children.
  • To inform the development of more accurate spirometry reference values for this demographic.

Main Methods:

  • Collated spirometry datasets from South-Asian children across multiple centers in India and the UK.
  • Excluded records with errors, missing data, or implausible values.
  • Compared lung function parameters (FEV1, FVC, FEV1/FVC ratio) against GLI-predicted values for White Europeans.

Main Results:

  • South-Asian children showed significantly lower forced expired volume in 1s (FEV1) and forced vital capacity (FVC) by an average of 15% compared to White European predictions.
  • The FEV1/FVC ratio remained largely independent of ethnicity, indicating proportional declines in FEV1 and FVC.
  • GLI-Black equations provided a better fit for South-Asian data than GLI-White, while GLI-Other was suitable for North Indian data; however, significant inter-center variations precluded a single South-Asian adjustment.
  • Socio-economic conditions influenced lung function z-scores, highlighting the complexity of deriving universal equations.

Conclusions:

  • The 'GLI-Black' equation is recommended for interpreting most South-Asian spirometry data, with 'GLI-Other' potentially better for North Indian data, pending improved equations.
  • Urgent need for prospective data collection with standardized protocols to address variations due to socio-economic factors, secular trends, and intra-South Asian ethnic diversity.
  • Standardized data collection is critical for developing robust, ethnicity-specific GLI spirometry prediction equations for South-Asian children.