Lung Function Testing and Prediction Equations in Adult Population from Maputo, Mozambique.

ABSTRACT: Background: Local spirometric prediction equations are of great importance for interpreting lung function results and deciding on the management strategies for respiratory patients, yet available data from African countries are scarce. The aim of this study was to collect lung function data using spirometry in healthy adults living in Maputo, Mozambique and to derive first spirometric prediction equations for this population. Methods: We applied a cross-sectional study design. Participants, who met the inclusion criteria, underwent a short interview, anthropometric measurements, and lung function testing. Different modelling approaches were followed for generating new, Mozambican, prediction equations and for comparison with the Global Lung Initiative (GLI) and South African equations. The

SUBMITTER: Ivanova O 

PROVIDER: S-EPMC7344554 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature