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

Olena Ivanova, Celso Khosa, Abhishek Bakuli, Nilesh Bhatt, Isabel Massango, Ilesh Jani, Elmar Saathoff, Michael Hoelscher and Andrea Rachow
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Olena Ivanova: Division of Infectious Diseases and Tropical Medicine, Medical Centre of the University of Munich (LMU), 80802 Munich, Germany
Celso Khosa: Instituto Nacional de Saúde (INS), 3943 Maputo, Mozambique
Abhishek Bakuli: Division of Infectious Diseases and Tropical Medicine, Medical Centre of the University of Munich (LMU), 80802 Munich, Germany
Nilesh Bhatt: Instituto Nacional de Saúde (INS), 3943 Maputo, Mozambique
Isabel Massango: Instituto Nacional de Saúde (INS), 3943 Maputo, Mozambique
Ilesh Jani: Instituto Nacional de Saúde (INS), 3943 Maputo, Mozambique
Elmar Saathoff: Division of Infectious Diseases and Tropical Medicine, Medical Centre of the University of Munich (LMU), 80802 Munich, Germany
Michael Hoelscher: Division of Infectious Diseases and Tropical Medicine, Medical Centre of the University of Munich (LMU), 80802 Munich, Germany
Andrea Rachow: Division of Infectious Diseases and Tropical Medicine, Medical Centre of the University of Munich (LMU), 80802 Munich, Germany

IJERPH, 2020, vol. 17, issue 12, 1-11

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 pulmonary function performance of participants was assessed against the different reference standards. Results: A total of 212 males and females were recruited, from whom 155 usable spirometry results were obtained. The mean age of participants was 35.20 years (SD 10.99) and 93 of 155 (59.35%) were females. The predicted values for forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1) and the FEV1/FVC ratio based on the Mozambican equations were lower than the South African—and the GLI-based predictions. Conclusions: This study provides first data on pulmonary function in healthy Mozambican adults and describes how they compare to GLI and South African reference values for spirometry.

Keywords: lung function; spirometry; prediction equation; adult; Mozambique; Africa (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
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