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ORIGINAL ARTICLE
Year : 2021  |  Volume : 14  |  Issue : 4  |  Page : 415-423  

Relative influence of overall and central body adiposity on lung function and development of lung function predictive model for adolescents in Tripura


1 Department of Human Physiology, Guest Faculty, Tripura University (A Central University), Agartala, Tripura, India
2 Department of Human Physiology, Tripura University (A Central University), Agartala, Tripura, India
3 Department of Statistics, Tripura University (A Central University), Agartala, Tripura, India

Date of Submission05-Nov-2019
Date of Decision25-Jun-2020
Date of Acceptance29-Jul-2020
Date of Web Publication17-Jun-2021

Correspondence Address:
Balaram Sutradhar
Department of Human Physiology, Guest Faculty, Tripura University (A Central University), Suryamani Nagar, Agartala - 799 022, Tripura
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/mjdrdypu.mjdrdypu_303_19

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  Abstract 


Background: Population-specific reference values are necessary for maintaining the reliability of pulmonary function evaluation. There are very few studies that have included body adiposity markers as the predictors of lung function, instead of age and height. Objectives: A gender-specific lung function predictive model of adolescents was developed using overall and central adiposity markers. The relative influences of both markers on pulmonary functions were also evaluated. Methods: Anthropometric and pulmonary function parameters of the subjects were recorded. The percentage body fat, fat mass (FM), fat-free mass (FFM), and body density were calculated. Statistical analysis was done using SPSS 16.0. Results: Significant differences between sexes for anthropometric measures were observed. The mean values of waist circumference (71.94 ± 2.33 mm for female vs. 71.37 ± 2.25 mm for male; P < 0.0005), body composition (5.83 ± 1.27 mm for female vs. 4.71 ± 0.83 mm for male; P < 0.0005), and sum of skinfolds (35.71 ± 4.48 mm for female vs. 34.66 ± 3.01 mm for male; P < 0.0005) were higher in female in comparison to male. Males had significantly higher subscapular skinfold thickness (9.39 ± 1.05 mm, compared with 9.17 ± 1.05 mm for females; P = 0.003). Mean values of central adiposity markers such as waist-hip-ratio (0.88 ± 0.01 for female vs. 0.87 ± 0.01, for male; P < 0.0005) and waist-to-height ratio (0.47 ± 0.004 for female vs. 0.47 ± 0.01, for male; P = 0.002) as well as overall adiposity markers such as percentage body fat (23.81 ± 1.11 for female vs. 18.98 ± 1.20, for male; P = 0.001) and FM (11.27 ± 1.83 kg for female vs. 8.94 ± 1.16, kg for male; P < 0.0005) were significantly higher in female compared to male. Mean FFM (38.17 ± 4.38 mm for male vs. 35.81 ± 3.93 mm for female; P < 0.0005) was significantly higher in male. All the pulmonary function parameters were significantly higher in male compared to female. Results showed the existence of significant mean differences in pulmonary function measures across the three body fat percentage groups in both sexes, with linear decrease of mean values of lung function with the increase of body fat percentage. Post hoc pair-wise multiple comparisons were done to compare the lung function between groups. Conclusion: Overall adiposity marker would explain variation in the pulmonary function parameters better than central adiposity markers in adolescents of both sexes.

Keywords: Adiposity, adolescent, lung function, prediction equation, Tripura


How to cite this article:
Sutradhar B, Choudhuri D, Hore S. Relative influence of overall and central body adiposity on lung function and development of lung function predictive model for adolescents in Tripura. Med J DY Patil Vidyapeeth 2021;14:415-23

How to cite this URL:
Sutradhar B, Choudhuri D, Hore S. Relative influence of overall and central body adiposity on lung function and development of lung function predictive model for adolescents in Tripura. Med J DY Patil Vidyapeeth [serial online] 2021 [cited 2021 Aug 4];14:415-23. Available from: https://www.mjdrdypv.org/text.asp?2021/14/4/415/318690




  Introduction Top


Obesity is the growing health problem worldwide.[1] Recently, India has emerged as the third largest obese country in the world.[2] Obesity has detrimental effects on pulmonary functions.[3] Studies reported that severe clinical obesity has a significant association with lung function impairment.[4] Most of the association study between obesity and lung function used body mass index (BMI) as a measure of overall adiposity and found a weak or nonsignificant association with diminished lung function at both extremes of BMI distribution.[5],[6] However, BMI does not take into account the pattern of fat distribution and body composition (BC); it cannot properly distinguish between fat mass (FM) and fat-free mass (FFM). Therefore, the frequently used BMI is currently less preferred as a reliable method to evaluate the association between obesity and associated diseases.

During the past few years, several studies reported the associations between BC such as FM and FFM and lung function.[6],[7],[8],[9],[10] These studies showed a positive association between the amount of FFM and respiratory function in human and an inverse relationship between FM and respiratory function of individual. FFM is mainly composed of muscles and is associated with several physical activities and therefore lung function.[8] A significant positive correlation between physical activity and lung function was confirmed by a large-scale association study between hand grip strength and forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1). This indicates that regardless of physical activities, FFM can independently affect respiratory muscles. Relatively, few previous studies have addressed the comparative relationship between central and overall obesity and ventilatory function separately in adolescents.

Till now, several studies have reported the reference values for pulmonary function worldwide including India.[10],[11]

Most studies used age and height as the predictors of lung function. There are very few studies that have included body adiposity markers as the predictors of lung function. In the present study, a gender-specific best lung function predictive model of adolescent boys and girls was developed using two independent adiposity markers.


  Methods Top


Schoolchildren from different urban and rural areas of the state of Tripura were included for the study through a stratified random sampling method. After obtaining permission from the school authority, verbal consent was taken from the students to participate in the study. This was followed by obtaining written consent from parents of each willing student. All the volunteer subjects (n = 1020 initial; 823 final) were healthy, without any cardiorespiratory symptom. They were evaluated as per the standard pro forma, which included a questionnaire to evaluate health and sociodemographic status of the subjects. Subjects (n = 197) were excluded due to improper spirometric performance and application of different exclusion criteria. The study protocol was approved by the Institutional Human Ethical Committee of Tripura University (No. TU/IHEC/01/2011 dated March 2, 2011). The sample size of the present study was calculated according to the World Health Organization method for sample size calculation in health studies taking 95% confidence.[12]

Subjects doing regular physical exercise, heaving obstructive or restrictive type of pulmonary disorder and taking treatment for the same, or heaving metabolic disorders related to obesity were excluded from the studies. A prevalidated questionnaire that was used in INSEARCH studies across India was administered to the parents to identify children with any respiratory symptoms.[13] Anthropometric measurements taken and instruments used to the study were described in our previous study.[11]

The percentage body fat was estimated using the method of Durnin and Rahaman.[14] Skinfold measurements were made by Harpenden skinfold caliper at four different sites on the left side of the body.[15] Extremity skinfolds were measured at the triceps and biceps, while trunk skinfolds were measured in the suprailiac and subscapular areas. The skinfold was picked up between the thumb and the forefinger, and the readings were taken 5 s after the caliper was applied. Three consecutive readings were taken and were recorded at each site. The difference among the readings was <2 mm. The average of the three readings at each site was calculated, and the sum of these values was entered into the table given by Durnin and Rahaman.[14] FM, FFM, and body density of the each subject were calculated separately. Methods for pulmonary function variable measured were reported earlier.[15] Spirometric parameters recorded for analysis were FVC (L), in FEV1, FEV1/FVC% ratio, and peak expiratory flow rate (PEFR in L/s).

Statistical analysis

Statistical analysis was performed using SPSS 16.0 (SPSS Inc., Chicago, IL, USA). Descriptive statistics were performed, and data were presented as a mean ± standard deviation (SD). The mean values of anthropometric and pulmonary function measures were stratified by gender. Pulmonary function measurements of male and female subjects were stratified by body fat percentage.[16] An independent unpaired Student's t-test for the continuous variable was used to compare the data between the sexes. Analysis of variance (ANOVA) was used to compare three or more groups followed by post hoc (Tukey's comparison) test. Differences were considered to be statistically significant at P < 0.05. Pearson's correlation coefficient between pulmonary function parameters (FVC [L], FEV1 [L], FEV1/FVC%, and PEFR [L/s]) and adiposity markers of both sexes was performed. Simple and linear multiple linear regression analyses were applied to develop the prediction models for each pulmonary function parameter (dependent variable) with the overall and central adiposity markers (independent variable). The goodness of fit of a model was assessed by the coefficient of determination (R2) and adjusted R2. The error of our estimate was determined from the standard error of estimate (SEE).


  Results Top


The physio-metric parameters, biceps skin fold thickness (BC), and pulmonary function parameters of subjects were stratified by gender and presented in [Table 1]. Values are presented as mean ± SD, range, and 95% of confidence interval. The present study shows significant mean differences between males and females for anthropometric measures (such as waist circumference [WC], subscapular skinfold thickness [SSFT], biceps skin fold thickness [BC], triceps skin fold thickness [TC], and Σ of the skin fold), central and overall adiposity markers, and pulmonary function measures.
Table 1: Physiometric, body composition, and pulmonary function parameters of the study group

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Males had significantly higher SSFT (9.39 ± 1.05 mm, compared with 9.17 ± 1.05 mm for females; P = 0.003). The female had significantly higher WC (71.94 ± 2.33 mm for female vs. 71.37 ± 2.25 mm for male; P < 0.0005); BC (5.83 ± 1.27 mm for female vs. 4.71 ± 0.83 mm for male; P < 0.0005); sum of skinfolds (35.71 ± 4.48 for female vs. 34.66 ± 3.01 for male ; P < 0.0005); central adiposity marker (0.88 ± 0.01 vs. 0.87 ± 0.01, P < 0.0005 for waist-to-hip ratio [WHR]; 0.47 ± 0.004 vs. 0.47 ± 0.01, P = 0.002 for waist-to-height ratio [WHtR]); overall adiposity marker (23.81 ± 1.11 vs. 18.98 ± 1.20, P = 0.001 for body fat percentage; 11.27 ± 1.83 vs. 8.94 ± 1.16, P < 0.0005 for FM). However, males had significantly higher FFM (38.17 ± 4.38 mm compared with 35.81 ± 3.93 mm for female; P < 0.0005). All the pulmonary function parameters (FVC, FEV1, FEV1/FVC%, and PEFR) were also significantly higher in male subjects than for female subjects at P < 0.05 level.

Pulmonary function measures stratified by body fat percentage are presented in [Table 2]. ANOVA showed the existence of significant mean difference of pulmonary function measurement across the three groups in both male and female at 0.05 level of significance [Table 2]. Post hoc pair-wise multiple comparisons (Tukey's test) between Groups I and II and Groups I and III showed a significantly different group mean for all the pulmonary function character, at an alpha level of 0.05. Results showed a significant inverse relation in the trends of the pulmonary function status to body fat percentage category in male and female. There was a linear decrease of pulmonary function values in females in relation to body fat percentage, which did not show any linear trends in the male.
Table 2: Details of pulmonary function status of male and female stratified by different body adiposity markers

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In males, overall adiposity markers such as percentage body fat and FM showed significant negative linear correlation with all the pulmonary function parameters; FFM showed significant positive correlation with all the pulmonary function characteristics, except FEV1/FVC% [Table 3].
Table 3: Initial Linear regression analysis for overall and central adiposity measures and associated with lung function measures in male and female

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Central adiposity marker such as WC, WHR, and WHtR showed significant negative correlation with all the pulmonary function characters. Hip circumference did not show any significant relationship [Table 3].

In female, overall adiposity markers such as percentage body fat and FM showed significant negative correlation with FVC, FEV1, and PEFR, whereas FFM showed nonsignificant positive correlation with FEV1/FVC% and significant negative correlation with all other lung function parameters [Table 3].

Central adiposity markers such as WC, HC, WHR, and WHtR in female showed significant negative correlation with FVC and FEV1, whereas PEFR and FEV1/FVC% showed nonsignificant correlation with central adiposity markers in female subjects [Table 3].

Most significant and strong predictors found in the initial regression model were used for the development final prediction model [Table 4]. In the final stage of our study, we had developed sex and adiposity specific final prediction model for lung function [Table 4]. The final prediction model suggested that there was a strong relation between observed and model-predicted values of the dependent variable. The final prediction equation based on overall adiposity markers for all lung function variables had a significantly higher cumulative correlation coefficient compared with prediction equation based on central adiposity markers of both sexes (R = 0.925 vs. 0.737; 0.919 vs. 0.726; 0.382 vs. 0.261; 0.886 vs. 0.759 for male group; R = 0.892 vs. 0.755; 0.877 vs. 0.749; 0.107 vs. 0.114; 0.867 vs. 0.759 for female).
Table 4: Final prediction equation based on overall adiposity marker and central adiposity marker as independent variable for pulmonary function parameters of the male and female study participants

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R2, the coefficient of determination, showed that in most of the cases, about half or more of the variations in pulmonary function values were explained by our model. The analysis of simulation carried out using the prediction equation based on overall adiposity marker (independent variable) for lung function observed values showed that the SEE of prediction was significantly lower than that based on central adiposity markers for both the sex group of our study. It was also found that it is comparable with female group.

The adjusted R2 that describes the variations explained by overall adiposity marker was significantly higher from central adiposity marker for both sex groups in our study. Therefore, the first model is the best fit to explain the dependent variable in our study.


  Discussion Top


The present study revealed that the mean values of FM and percentage fat were significantly higher in girls than in boys, while body FFM was significantly higher in boys. This observation is in agreement with the earlier findings on an analysis of BC of children and adolescents – a study of the Polish population – and comparison of body fat measurement methods done by Golec et al.[17] Earlier findings also confirmed that gender discrepancy in the pattern of fat distribution was one of the important mechanisms for the sex difference in lung function deterioration due to weight gain.[18] Even when males and females are matched for height, weight males have larger lungs than females. In addition to anatomical and physiological differences, sex hormones, sex hormone receptors, or intracellular signaling mechanism may also be answerable for the gender difference in lung function values.[19] Gender variation in the lung function parameters in the Indian adolescents was observed by Berad et al. in their study.[20] Higher pulmonary function test (PFT) values in males in comparison to females were also observed by Wang et al.[21] Both the studies revealed that body muscularity was the major contributing factor for higher values PFT in male than the girl. In agreement with these findings, in our study, boys who showed better muscularity than the girls were also found to have better pulmonary function characteristics.

Lung function status stratified by percentile value of the body fat percentage of male and female subjects revealed that all the pulmonary function parameters of both sex groups showed a significantly different group mean (P < 0.05) with significantly higher mean value in normal body fat category in comparison to moderate and elevated body fat category. Trends also suggested that there was a significant linear decrease in lung function value of females with the increase of body fat percentage, which is not linear in the case of male subjects.

PFT is a vital diagnostic device for prognosis and evaluation of pulmonary dysfunction, respiratory disease, and treatment results. Normal lung function predictive values are calculated via regression equation reflecting gender, age, height, and body weight due to significant correlation with PFT values.[22] Since other important body measures have also been reported to have a correlation with the outcomes of PFT, studies to develop a regression equation of pulmonary function values according to different body measures continued.[23] Since fat distribution in the body is rarely considered in body weight and BMI studies on the correlation between pulmonary function and fat distribution, in recent times, studies are being conducted to evaluate such relationship.[24]

In the present study, overall adiposity markers such as percentage body fat and FM, evaluated using age- and sex-specific equations based on skinfold thicknesses, showed significant negative linear correlation with all the pulmonary function parameters in male and female. Santana et al. reported that body fat percentage and FVC are significantly negatively correlated.[7] Lazarus et al.,[6] in a sample of 1235 nonobese subjects aged 18–78 years, showed a decrease in lung function with increasing FM and central body fat distribution. The amount of body fat might be related to lung function via several mechanisms, such as mechanical effects on the diaphragm (impeding descent into the abdominal cavity) and on the chest wall (changes in compliance and in the work of breathing and elastic recoil).[25] This shrinkage in lung capacity may impact on breathlessness due to the requirement of an elevated respiratory rate and greater work output from the respiratory muscles.[26] Therefore, such an increase may influence physical achievements and quality of life.[27]

FFM, in this study, showed significant positive association with all the pulmonary function characteristics (except FEV1/FVC%) in male subjects, whereas association was significantly negative in females except a nonsignificant positive correlation with FEV1/FVC%. Several researchers working on pulmonary function in relation to FFM reported a significant positive association for FEV1 and FVC in both sexes.[6],[7],[28] However, our observation of a significant negative association between respiratory function and FFM in the female is supported by a study of Sutherland et al.[29]

The multitude of factors potentially influencing lung function is responsible for some of the difficulties in establishing adequate and reliable prediction equations for lung function measures. Taking into account many of these factors, we were able to establish regression models showing a good correlation between predicted and measured lung function values. In our study, the major influencing factor for lung function predicted value was identified by initial regression model separately for male and female using both overall and central adiposity markers for every individual dependent variable. The initial regression model suggested that the percentage body fat of overall adiposity markers is the leading influencing factor for lung function predicted value followed by FM and FFM of both sexes. However, in the case of central adiposity marker, the maximum variance of lung function predicted values was explained by WHtR followed by WHR, WC, and HC in the male. In female, the maximum variance of lung function predicted values was explained by WC followed by HC, WHR, and WHtR. The ratio of FEV1 to FVC, in our regression models, could explain only a very small part of the variability. A similar effect of the ratio of FEV1 to FVC was observed by Schnable et al.[30] in their study.

Most significant and strong predictors found in the initial regression model were used in final prediction model. Final prediction suggested that there was a strong relation between observed and model predicted values of the dependent variable. The final prediction equation based on overall adiposity marker for all lung function variables had a significantly higher cumulative correlation coefficient compared with prediction equation based on central adiposity marker of both the sex group. In most of the cases, about half or more of the variations in the pulmonary function values were explained by our model. The SEE based on overall adiposity marker for lung function observed values was significantly lower than that based on central adiposity marker for both the sex groups of our study. The variations explained by overall adiposity marker were significantly higher from central adiposity markers for both sex groups in our study. Therefore, the first model is the best fit to explain the dependent variable in our study.


  Conclusion Top


Overall adiposity markers would explain variation in pulmonary function parameters better than central adiposity markers in adolescents of both sexes.

Limitation

Cross-sectional nature of the study is a major limitation, and the study does not include subjects with impaired lung function for comparison.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]



 

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