Dataset Information

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 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.

SUBMITTER: Ivanova O

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

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Ivanova Olena O Khosa Celso C Bakuli Abhishek A Bhatt Nilesh N Massango Isabel I Jani Ilesh I Saathoff Elmar E Hoelscher Michael M Rachow Andrea A

International journal of environmental research and public health 20200624 12

<b>Background:</b> 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. <b>Methods:</b> We applied a cross-sectional study design. Part ...[more]

PMID: 32599726

Similar Datasets

Project description:Rationale: African American individuals have worse outcomes in chronic obstructive pulmonary disease (COPD). Objectives: To assess whether race-specific approaches for estimating lung function contribute to racial inequities by failing to recognize pathological decrements and considering them normal. Methods: In a cohort with and at risk for COPD, we assessed whether lung function prediction equations applied in a race-specific versus universal manner better modeled the relationship between FEV1, FVC, and other COPD outcomes, including the COPD Assessment Test, St. George's Respiratory Questionnaire, computed tomography percent emphysema, airway wall thickness, and 6-minute-walk test. We related these outcomes to differences in FEV1 using multiple linear regression and compared predictive performance between fitted models using root mean squared error and Alpaydin's paired F test. Measurements and Main Results: Using race-specific equations, African American individuals were calculated to have better lung function than non-Hispanic White individuals (FEV1, 76.8% vs. 71.8% predicted; P = 0.02). Using universally applied equations, African American individuals were calculated to have worse lung function. Using Hankinson's Non-Hispanic White equation, FEV1 was 64.7% versus 71.8% (P < 0.001). Using the Global Lung Initiative's Other race equation, FEV1 was 70.0% versus 77.9% (P < 0.001). Prediction errors from linear regression were less for universally applied equations compared with race-specific equations when examining FEV1% predicted with the COPD Assessment Test (P < 0.01), St. George's Respiratory Questionnaire (P < 0.01), and airway wall thickness (P < 0.01). Although African American participants had greater adversity (P < 0.001), less adversity was only associated with better FEV1 in non-Hispanic White participants (P for interaction = 0.041). Conclusions: Race-specific equations may underestimate COPD severity in African American individuals.Clinical trial registered with www.clinicaltrials.gov (NCT01969344).

Project description:BackgroundIrrational use of antibiotics is a major driver of antimicrobial resistance (AMR) worldwide. Sub-Saharan Africa, where the risk of spread of AMR is highest, lacks data on the knowledge, attitudes and practices regarding antibiotic prescription and use. This is the first study in Mozambique to address this gap.MethodsA cross-sectional study was conducted in 2016 in 1091 adults (age ≥18 years) living in five districts in peri-urban areas of Maputo City. Three stage cluster sampling was used to select the households. A semi-structured questionnaire was used to collect information on the knowledge, attitudes and practices regarding antibiotics and their use and socio-demographic data.ResultsOf the 1091 participants, 20.9% (228/1091) had used non-prescribed antibiotics. Most of the non-prescribed antibiotics were purchased in pharmacies (199/228; 87.3%). The proportion of use of non-prescribed antibiotics was higher in those who purchased from informal markets (82.6%; 14/17) and home stores (66.7%; 12/18), compared to pharmacies (24.6%; 199/810) (p = 0.000). Variables significantly associated with use of non-prescribed antibiotics were male gender (p = 0.004), living in the Central A (p<0.001), Aeroporto B (p<0.001) or 25 de Junho (p<0.001) neighborhoods, purchase of antibiotics in informal markets (p<0.002) or obtaining from home stores (p = 0.026), not completing the course (p<0.001) and having poor knowledge on the use of antibiotics (p<0.001). Main reasons for use of non-prescribed antibiotics were a perception that there was no need to attend a health facility (26.8%), followed by someone else's advice (7.7%), symptoms similar to a previous episode (6.2%) and poor quality of care in health facilities (6.7%).ConclusionsOur study shows for the first time that knowledge regarding antibiotics is poor in Maputo City. Purchase of non-prescribed antibiotics is a common practice and most are sold in pharmacies, indicating deficient inspection. Interventions to reinforce adherence by pharmacies to current legislation for dispensing antibiotics, combined with community education are urgently needed.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets