Edinburgh Research Explorer

Development of spirometry predictive values for Indian population

Dataset

  • Sanjay Jukevar (Creator)
  • Dhiraj Agarwal (Creator)
  • Hilary Pinnock (Creator)
  • Sudipto Roy (Creator)
  • Richard Parker (Creator)
  • Parag Khatavkar (Creator)
  • Sundeep Salvi (Creator)
  • Deesha Ghorpade (Creator)
  • Moni Choudhury (Data Manager)

Related Edinburgh Organisations

PublisherEdinburgh DataVault
Temporal coverage2008 - 2012
Date made available2020
Geographical coverageVadu, India

Description

Single CSV (comma-separated values) file.

Abstract

Interpretation of spirometry involves comparing lung function parameters with predicted values to determine the presence/severity of the disease. The Global Lung Function Initiative (GLI) derived reference equations for healthy individuals aged 3–95 years from multiple populations but highlighted India as a ‘particular group’ in whom further data are needed. We aimed to derive predictive equations for spirometry in a rural Western Indian adult population. We used spirometry data previously collected (2008-2012) from 1,258 healthy adults (aged 18 years and over) by the Vadu Health and Demographic Surveillance System. We constructed sex-stratified prediction equations for FEV1, FVC, and FEV1/FVC using the Generalised Additive Model for Location, Scale and Shape (GAMLSS) method to derive the best fitting model of each outcome as a function of age and height. When compared with GLI Ethnicity Codes 1 (White Caucasian) and 5 (Other/Mixed), the Western Indian adult population appears to have lower lung volumes on average, though the FEV1/FVC ratio is comparable. Both age and height were predictive of mean FEV1 and FVC; and for females, the variability of response was also dependent on age. FEV1/FVC appears to have a very strong age effect, highlighting the limitations of using a fixed 0.7 cut-off value. The use of GLI normal values may result in overdiagnosis of lung disease in this population. We recommend that the values and equations generated from this study should be used by physicians in their routine practice for diagnosing disease and its severity in adults from the Western Indian population.

Data Citation

Juvekar, Sanjay; Agarwal, Dhiraj; Pinnock, Hilary; Roy, Sudipto; Parker, Richard; Khatavkar, Parag; Salvi, Sundeep; Ghorpade, Deesha. (2020). Development of spirometry predictive values for Indian population, 2008-2012 [dataset]. KEM Hospital Research Centre, Pune and UoE Usher Institute/RESPIRE group.

Contact person

Reason for data restriction and conditions for release

This dataset is held in the Edinburgh DataVault, directly accessible only to authorised University of Edinburgh users. Academic researchers may request access, and will be required to sign a data sharing agreement.

ID: 164599295