Background
Obesity is one of the biggest public health problems worldwide. It currently affects all age groups, including children and adolescents. The World Health Organization (WHO) characterizes the fight against obesity as one of the primary challenges for healthcare professionals in the 21st century. In Brazil, the prevalence of obesity is greater than 30% among children between 5 and 9 years of age and is almost 20% in children between 10 and 19 years of age [
1‐
4].
Body mass is modulated from birth to adulthood by physiological mechanisms such as balancing intake, caloric expenditure and energy reserves. Hypercaloric diets and sedentary lifestyle have resulted in the development of obesity in younger populations. The development of obesity triggers a vicious cycle in which subjects become obese, and the systemic repercussions of their disease process make them intolerant to exercise; therefore, they become more sedentary, which promotes additional weight gain. Multisystem dysfunction, an entity previously observed only in adults, has become more common among children and adolescents, resulting in physical exercise intolerance and increasing the prevalence of obesity, which affects the cardiorespiratory system [
2,
5].
In adults, obesity’s effects on lung function are well known. According to the Brazilian Pulmonary Function Guidelines, changes in spirometry occur only in the setting of morbid obesity, wherein low vital capacity (VC) and expiratory reserve volume (ERV) may be observed. Among children and adolescents, there is no literature consensus regarding common spirometric findings. Additionally, it is not clear when obesity begins to damage lung function, nor is it clear when patients’ physical performances become inadequate [
6,
7].
Physical activity reduces the harm caused by obesity, which improves patients’ metabolic profiles and prevents obesity’s deleterious structural and psychosocial effects. Additionally, daily exercise improves quality of life [
8].
In this study, lung function was assessed by spirometry, which measures inspired and expiratory air volumes and respiratory flow. It also helps in the prevention of ventilator disturbances, diagnosis and quantification [
7]. The six-minute walk test (6MWT) was used to evaluate physical conditioning. The test demonstrates good reproducibility in children and adolescents; its application is inexpensive and simple and provides information about the global and integrated responses of each body system during exercise [
9,
10].
Therefore, the principal aim of the present study was to evaluate obesity’s influence on physical conditioning and lung function in children and adolescents to determine if any correlation among these variables exists and to compare said values with those of a control group. Another point of investigation involved the relationship among height, weight and body mass index (BMI) with lung function variables, as well as the relationship among height, weight and BMI with 6MWT variables.
Methods
Study design and inclusion criteria
This was a cross-sectional study that included 38 obese children and adolescents of both sexes between 5 and 17 years of age, as well as a control group paired by sex and age. Obese subjects were followed at the Multidisciplinary Ambulatory Service for Obese Children and Adolescents at University Hospital.
The CDC (Center for Disease Control and Prevention) standards for individuals between 2 and 19 years of age were used to define obesity: a subject is considered obese if his BMI is above the 95th percentile.
The control group was composed of healthy subjects of the same age groups. Control individuals had previously registered with the Pulmonary Physiology Laboratory database. The spirometry (n = 39) and 6MWT (n = 56) control groups consisted of distinct individuals, so they cannot be considered a single group.
Exclusion criteria
Patients with acute or chronic diseases, neurological or physical limitations, or any respiratory diseases that may have interfered with their ability to perform spirometry or to complete the 6MWT were excluded from this study.
Procedures
The study was approved by the Ethics Committee of the Medical Sciences College of Unicamp (#1165/2009). The parents and guardians of each of the participants provided written informed consent prior to the evaluations.
Each subject performed spirometry to assess pulmonary function. They were subsequently scheduled to complete a 6MWT on another date in order to prevent the use of bronchodilators (BDs), spirometry or fatigue from interfering with their performances during the walking test. Of the 38 patients who underwent spirometry, 29 completed the 6MWT.
Spirometry
Spirometry was performed using the CPFS/D model spirometer (MedGraphics, Saint Paul, Minnesota, USA, software BREEZE PF 3.8 B version for Windows 95/98/NT), and the results were assessed using the American Thoracic Society (ATS) and European Respiratory Society (ERS) standards.
Subjects who performed spirometry were allowed to rest for 10 min before beginning testing. The mouthpiece was properly positioned on the tongue, and it was ensured that the lips were tightly sealed around the mouthpiece to avoid air leakage. During the evaluation, subjects remained standing and performed slow and forced maneuvers. Following the first measurement, the obese group underwent salbutamol inhalation and repeated the test after 20 min. Acceptance criteria included the generation of at least three acceptable and two reproducible curves. Percentages of predicted values were used for statistical analysis.
The variables analyzed included the following: forced vital capacity (FVC), forced expiratory volume in the first second (FEV1), FEV1/FVC index, forced expiratory flow at 25%, 50% and 75% of FVC (FEF25%, FEF50%, FEF75%), forced expiratory flow between 25% and 75% of FVC (FEF25–75%), maximal forced expiratory flow (FEFmax), and expiratory reserve volume (ERV).
The 6 minute walk test (6MWT)
The 6MWT was performed according to ATS guidelines. Walking distance (WD), work index (W = body weight X WD), respiratory rate (RR), heart rate (HR), saturation of peripheral oxygen (SpO2), physiological cost index (PC = HR6minutes - HRrest/average speed) and dyspnea perception (BorgD) based on the Borg scale were evaluated. Arterial blood pressure (BP) and legs effort perception (BorgL) were also recorded in the obese group. Measurements were performed at rest, immediately following the 6MWT and following three min of rest.
Statistical analysis
Our statistical analysis compared height, weight and BMI with lung function variables (FVC, FEV1, FEV1/FVC index, FEF25%, FEF50%, FEF75%, FEF25–75%, FEFmax and ERV): height, weight and BMI were also compared with 6MWT variables (WD, W, RR, HR, SpO2, PC, BorgD, BP and BorgL). Correlation tests were performed using the following variables: (i) height, weight, BMI and lung function; (ii) height, weight, BMI and 6MWT; and (iii) lung function and 6MWT.
SPSS 21.0 (SPSS Inc., Chicago, IL, EUA) was used to tabulate data. The Mann–Whitney test was used to compare two numeric variables, and the Kruskal-Wallis test evaluated three or more groups. The χ2 test was used for categorical variables analysis. The Spearman correlation was used to determine relationships between variables. The Wilcoxon test compared pulmonary function before and after BD use. α (alpha) was equal to 0.05, and the Bonferroni correction was used for multiple tests.
The non-parametric test was performed to determine sample distribution. The data demonstrated a non-parametric distribution following an analysis using the Kolmogorov-Smirnov test of normality and the Shapiro-Wilk test of normality, which accounted for the graphic analysis for the distribution of data.
The sample size was calculated using G*Power 3.1.9.2. After taking into account the number of subjects enrolled (38 obese and 56 healthy controls) for all tests performed, the power was greater than 0.80. For the Mann–Whitney test, given an α = 0.05 and an effect size, d = 0.80, a power, β, equal to 0.96 was achieved. For the Kruskal-Wallis test, given an α = 0.05, a number of groups = 4, an effect size, f = 0.40, a power, β, equal to 0.90 was achieved. For the Wilcoxon test, given an α = 0.05, an effect size, dz = 0.50, a power, β, equal to 0.99 was achieved. For the Spearman Regression, given an α = 0.05, a correlation, ρH1 = 0.3, and a correlation, ρH0 = 0, a power, β, equal 0.84 was achieved.
Discussion
Physiological pulmonary capacity is dependent on body size and system efficiency. Therefore, exercise adaptation is influenced by body growth and pubertal development. Obesity is related to sedentary lifestyle, which effects performance, and also to increased fat mass relative to muscle mass per unit of weight. Being overweight makes any physical activity uncomfortable and reduces physical activity interest, which fosters the development of a vicious cycle [
15].
Maximal oxygen uptake (VO
2max) is the best fitness evaluation tool, and it increases with pubertal development. However, obese children must exert themselves more in order to perform their daily activities; therefore, they reach their VO
2max earlier than eutrophics (percentile ≥ 25 and < 95) do. This may be related to anticipation of effort adaptive mechanisms, mechanisms that initiate earlier pubertal development in obese children. They have been described in the literature, but no consensus regarding the mechanisms has been reached [
15‐
18].
Lower values of FEV1/FVC were observed in the obese group in the present study. There were no differences in FEV1 between the groups, and obese subjects demonstrated higher FVC values, but these values became statistically non-significant following Bonferroni correction. However, these results demonstrate that the lower FEV1/FVC values observed in the obese group were determined by higher FVC values as opposed to lower values of FEV1, which may be related to these patients’ increased need for oxygen due to greater oxygen consumption.
The literature diverges regarding spirometric findings in obese children and adolescents. There were no significant differences in FVC between the obese group and the healthy group in this study, whereas a study performed by another author found no relationship between body composition and FVC [
19]. However, other studies noted higher values of FVC in obese children and adults [
20‐
22], whereas additional studies noted lower FVC values in obese children [
23,
24].
The same authors disagree regarding the relationship between FEV
1 and obesity. The present study did not find differences in FEV
1 between the groups, which was consistent with a finding in the literature [
19]. Some studies noted lower values of FEV
1 in the setting of obesity [
23,
24], although others noted higher FEV
1 values [
20,
21].
Greater consistency has been noted in the literature regarding FEV
1/FVC ratios. Other authors found that this variable was reduced in obese patients, a finding consistent with that of our study [
20,
24,
25].
Another study observed a negative correlation between sagittal abdominal diameter and FEV
1/FVC [
22], which may be related to sex differences, as a similar finding was observed in the present study. Boys experience android obesity; therefore, fat distribution occurs primarily in abdominal and chest areas, and they develop larger sagittal abdominal diameters than girls, who experience gynoid fat distribution, which is characterized by the distribution of adipose tissue at the hips and in the thighs. Another study noted lower FEV
1/FVC values only in obese boys, a finding that supports this hypothesis [
26].
Forced expiratory flow reduction among obese subjects may be explained primarily by compromised lung mechanics as a result of the extra load that adipose tissue imposes upon the ribcage, a phenomenon supported by other literature articles [
23,
25,
27]. However, a study involving 64 obese subjects with an average age of 12 years noted only three individuals with obstruction abnormalities [
28], and another study that included 22 obese subjects between two and 20 years of age noted only one child with flow obstruction [
29]. Low prevalences of obstruction disorders were also observed in other studies [
19,
21].
In both the obese and healthy groups, it was observed that forced expiratory flow volumes were lower in males than in females, a finding that may be related to lung growth and structural differences between the sexes. Male lungs are larger than female lungs of the same age. Therefore, they have longer but narrower airways, which limits expiratory flow [
30].
The 6MWT results are due to physiological changes described previously. The obese group walked a shorter distance than the control group due to extra load, weak musculature, sedentary lifestyle, and reduced glycolytic capacity. Nevertheless, these subjects did more work while walking, as they have higher cardiorespiratory requirements. There is a study in which a group of authors found that 6MWT performances were 26% worse in obese subjects between eight and 16 years old compared with eutrophics of same age. They concluded that the 6MWT is a reproducible test among obese children and adolescents and is useful in clinical practice, although it did not demonstrate a strong correlation with VO
2max[
10].
Some studies suggest that poor performance on the 6MWT, as observed in the present study, persists into adulthood. They also found that obese individuals walk shorter distances than eutrophics and that obese subjects also perform more work [
25,
31].
PC was originally proposed by McGregor [
32] and may represent an alternative means of analyzing the 6MWT. The relationship between ∆HR and average speed estimates energetic expenditure, and studies have used this parameter to evaluate healthy subjects and individuals with diseases. Its applicability is still debated, however, because there are many variations among the studies that have utilized it [
32‐
37]. No studies comparing PC in obese and healthy individuals have been found.
The obese group demonstrated lower PC values among subjects between five and 11 years of age, walked shorter distances and exhibited lower HR6min than eutrophics, demonstrating lower values in ∆HR and average speed. With growth, lower values in HR and increases in walking speed are expected in healthy individuals due to increasing leg lengths and expected improvements in cardiorespiratory fitness. Therefore, obese subjects, who demonstrated reduced average speeds due to excessive load, demonstrate lower PC values upon reaching adulthood.
Analyzing normal parameters of the 6MWT has resulted in disagreements regarding the test’s criteria due to anthropometric variations in each ethnic group, age differences, and the importance of each variable in normality equation determination, each of which hampers the homogeneity of this particular evaluation.
Both Brazilian studies included similar samples based on subjects’ nationality, and also included subtractive body mass related variables accounting for body weight influences on performance. However, Li et al. [12] utilized criteria based on Chinese children and adolescents in their study, characteristics different from those of the Brazilian population, and observed that all obese subjects and almost all eutrophics performed below normal values. Therefore, these criteria were not suitable for the evaluations of obese and eutrophic differences in our sample. An equation developed by Geiger et al. [
13] evaluated a population with different ethnic characteristics than those of Brazilians: they observed differences between the obese and healthy groups’ performances. However, the authors did not take into account the influence of body mass on performance when developing their normality equation [
11‐
14].
Limitations of the study
It is necessary to develop more accurate methods of defining obesity and to evaluate body composition more precisely. For example, researchers must define percentages of body fat and lean mass so that they will select better populations for study. Moreover, the control groups for spirometry and the 6MWT were composed of different individuals. Therefore, we could not establish a correlation among these variables in our healthy subjects. Finally, as sample numbers conform to sample calculations, a larger population may allow for the detection of significant differences among groups.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
MSF, RTM, FALM, MPZ, IAP, AADCT, SDS, MAGOR, JDR each made substantial contributions to the conception and design of this study, as well to the acquisition of data and its analysis and interpretation: each was involved in drafting the manuscript and critically revising it for important intellectual content and has given final approval of the version of the manuscript that will be published.