Background
Spirometry is a clinical tool used to measure and monitor lung function. There are well-defined spirometric variables that inform about patterns of lung function abnormalities and aid in the diagnosis of different types of lung disease that may manifest with obstructive and restricted lung function patterns [
1]. Lung function results obtained from a patient after a spirometry manoeuvre are compared to appropriate spirometric reference equations (SRE) derived from healthy individuals of the same ethnicity, height, age, and sex [
2]. SRE have traditionally been generated using different methods and populations, resulting in significant variability, and rarely including data from sub-Saharan Africa [
3‐
6]. There is also increasing concern over the use of fixed percentage predicted cut-offs in SRE in clinical settings to define abnormalities as it can lead to incorrect interpretation of spirometry results [
2,
7].
To address this, the European Respiratory Society (ERS), through the Global Lung Function Initiative (GLI), developed global SRE for healthy individuals aged 3–95 years in 2012. The data used to generate the GLI
2012 SRE were collected from Europe, Australia, Latin America, East Asia, India, North America and North Africa [
8]. The GLI
2012 provide ethnic-specific equations for Caucasians, African-Americans, South East Asians and North East Asians. The GLI
2012 provide age-, height-, sex- and ethnic-specific SRE [
9]. These equations provide lower-limit-of-normal (LLN) values, which can be defined as the 5th percentile values (z-score < − 1.64) of the healthy, non-smoking population [
2]. The z-score reflects the number of standard deviations a measurement is positioned from its predicted/reference value, centered at zero [
10]. It is a function of a normally distributed population and is thought to be a more valid measure to define the LLN as compared to traditional fixed cut-offs (i.e., 0.8 for forced vital capacity [FVC] and forced expiratory volume in 1 s [FEV
1], and 0.7 for the FEV
1/FVC ratio) used to help define airflow limitation and obstruction [
2,
11,
12]. Use of the GLI
2012 SRE is endorsed by the American Thoracic Society (ATS) and the ERS, and many manufacturers now install the module in their devices [
8,
13,
14].
Studies validating the GLI
2012 SRE have made varying conclusions, with some indicating a poor fit for local populations [
10,
15]. However, the FEV
1/FVC ratio has consistently demonstrated a better fit across populations than other lung function measurements [
10,
15‐
17]. Potential reasons for poor fit of SRE include sampling which is unrepresentative of the population, potential mis-specification of the prediction equations, and environmental factors such as exposure to indoor and/or ambient air pollution, malnutrition, and low socioeconomic status (SES), which may result in lower lung volumes on a population level, leading to erroneous estimations [
18‐
23]. Like many SRE, the GLI
2012 SRE lack contribution of lung function data from sub-Saharan African populations, and use of the African-American GLI
2012 SRE is generally recommended for African populations [
8].
As such, an ERS task force recommended additional studies to validate the GLI
2012 SRE in non-Caucasian populations [
8]. A cross-sectional observational study was performed to evaluate the performance of the GLI
2012 SRE among urban and peri-urban Zimbabwean children aged 7–13 years. The GLI
2012 SRE were also compared against the Polgar equations because they are currently used in clinical practice.
Discussion
This study is the first to evaluate the use of the African-American GLI2012 SRE in Zimbabwean children aged 7–13 years attending primary school. Our findings demonstrate that lung function parameters for Zimbabwean children are comparable to those of African-American children as indicated by the overall fit of African-American GLI2012 SRE. Thus, the African-American GLI2012 SRE is applicable for use in Zimbabwean children.
These findings are consistent with other findings in children [
15] and adults [
40] from sub-Saharan Africa. The similarities in spirometric variables between Zimbabwean and African-American children highlight the influence of ethnic background on lung development in healthy individuals, regardless of healthcare access, exposure to air pollution and SES [
15,
41,
42]. Indeed, we detected no difference in lung function patterns between schools belonging to areas characterised by a different SES in this study. We identified anthropometry differences in this population consistent with studies that have also highlighted sex-related differences in anthropometry and lung function indices in children of the same age [
36,
37].
Z-scores for spirometry variables are dimensionless values that show the number of SDs the measurement is positioned from the GLI
2012 SRE population values [
2,
15]. The GLI
2012 SRE predict standardised z-score values that are adjusted for ethnicity and anthropometric variables. Mean African-American GLI
2012 z-scores for all the spirometry variables were within 0.5 z-scores from zero, which is within the acceptable range of the GLI
2012 perfect fit prediction [
15,
32]. However, the z-score SD for the FEV
1/FVC ratio was ≥1, indicating more variability than the reference population, thus affecting the performance of the African-American GLI
2012 LLN in this population [
15,
43,
44]. By definition, the LLN allows 5% of healthy people to be misclassified and higher variability in FEV
1/FVC may increase misclassification of airway obstruction [
2,
44]. Conversely, however, as the overall population is slightly shifted down away from the predicted mean, this may reflect an actual reduction of FEV
1/FVC in our population. The FEV
1/FVC is sensitive to early life exposures and maybe an early indicator of decline in lung function later in life [
45].
In this study, all the spirometry z-scores had a negative offset, indicating that the African-American GLI2012 SRE generates values which are slightly above those of Zimbabwean children regardless of sex. Mean predicted values for all spirometry values were lower than 100% (perfect fit), and the observed differences were lower in girls than boys.
With a perfect fit, the z-scores developed from the GLI
2012 SRE should show a lack of association with ethnicity and anthropometric variables since they are independent variables for generating the LLN [
8,
16]. We identified weak correlations between anthropometric and spirometry z-scores with no consistent direction. Furthermore, the scatterplots for these associations showed no particular pattern indicating a lack of any physiological correlations. Similar results indicating weak correlations were also reported in other studies from Tunisian, Swedish and Asian populations [
10,
15,
16]. Analysis of the scatterplots and multivariable analysis stratified by school-income level showed inconsistent influence of SES in explaining the variability in lung function z-scores. However, the associations detected between FEV
1/FVC and BMI z-scores may be contributing to the high variability in this measure, resulting in less goodness of fit by the African-American GLI
2012 SRE. Furthermore, this finding highlights the possibility of more variability in the body frames of Zimbabwean as compared to African American children, and this may influence the association of anthropometric and spirometric measurements in our population.
Most physicians in Zimbabwe use the Polgar SRE for diagnosis of lung disease, which were developed from North America, Europe and Japan and compiled by Polgar & Promadaht (1971) for the 6–18-year age group [
2,
34]. In contrast, the GLI
2012 produced SRE from 74,117 healthy individuals worldwide. Mean comparisons of percent predicted GLI
2012 SRE-derived values against the Polgar values in this population showed substantially higher lung function prediction for the African-American GLI
2012 SRE (5.6, 9.1 and 3.6% in FVC, FEV
1 and FEV
1/FVC, respectively) [
8,
46]. Results showing lower Polgar predicted values as compared to the GLI
2012 values have also been identified in other populations [
15,
46].
Our results suggest that the use of the African-American GLI
2012 SRE in Zimbabwean children can improve identification of a tendency towards a restrictive and obstructive lung function pattern. Diagnosis of associated lung diseases can be enhanced by using LLN to identify impaired lung function rather than fixed-cut offs, as this approach mitigates the anthropometric and ethnic group related biases that can result in misclassification of borderline lung function [
8,
47]. The LLN values were developed from a large sample using z-scores adjusted for ethnic groups, height, age and sex. The LLN values can help define lung function abnormality: airflow obstruction is defined as FEV
1/FVC < LLN, whilst FEV
1/FVC > LLN in combination with FVC < LLN can represent a tendency towards a restrictive pattern. Thus, it is possible that changing SRE from Polgar to African-American GLI
2012 can alter the interpretation of spirometry results which will, in turn, affect the overall classification of patients as having a tendency towards an obstructive or restricted lung pattern, thereby, modifying the prevalence and subtypes of lung disorders [
46,
48]. The negative mean spirometry z-scores for all the variables implies the LLN should be cautiously interpreted by practitioners, to avoid over-classifying children with low lung function.
This study represents a response to the call of the ERS to validate the GLI
2012 SRE in ethnic groups that are not included in the sample used to derive these SRE [
8]. Strengths of our study include a randomly selected sample, and high quality lung function variables collected in a standardised manner based on ATS/ERS guidelines. We used the same spirometer that was regularly calibrated to minimise variability, and the failure rate for valid measurements was low. We acknowledge several limitations. We had a 20% refusal rate but the overall sample size was sufficient to validate the GLI
2012 SRE. The z-score calculations may have been subject to measurement error because they are adjusted for height which was measured only to the nearest centimetre; for instance, a one cm difference in height for a 12-year-old male child can relate to a difference of 0.08 and 0.1 in the predicted FEV
1 and FVC z-scores, respectively. Our results may not be generalisable to other Zimbabwean settings where exposure to indoor and outdoor air pollution may differ from Harare; we did not measure air pollution so were unable to assess its effects. The study did not capture birthweight and preterm status which is associated with the general lung development in children.
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