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  Table of Contents    
ORIGINAL ARTICLE
Year : 2015  |  Volume : 32  |  Issue : 4  |  Page : 353-358  

Pulmonary function of adolescents from Tripura, a North-eastern state of India


Department of Human Physiology, Tripura University (A Central University), Agartala, Tripura, India

Date of Web Publication30-Jun-2015

Correspondence Address:
Dipayan Choudhuri
Department of Human Physiology, Tripura University (A Central University), Suryamaninagar, Agartala - 799 022, Tripura
India
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Source of Support: This work is supported by Indian Council of Medical Research, New Delhi, through an ad hoc project sanctioned to the corresponding author., Conflict of Interest: None


DOI: 10.4103/0970-2113.159568

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   Abstract 

Objective: Spirometric evaluation of pulmonary function has been evolved as clinical tool in diagnosis, management, and follow-up of respiratory disorders. There are very few studies on normative reference values of pulmonary function parameters for adolescents from Tripura, a North-eastern state of India. The present study was aimed to evaluate pulmonary function and their predictors in male and female adolescents of Tripura. Materials and Methods: A total of 640 (320 from tribal and 320 non-tribal) healthy, non-smoking male and female school children (age 10-14 years) from four different districts of Tripura were randomly sampled for the study. The pulmonary function parameters analysed included forced vital capacity (FVC), forced expiratory volume in 1 second (FEV 1 ), peak expiratory flow rate (PEFR), forced expiratory flow between 25% and 75% expired volume (FEF 25-75% ), ratio of FEV 1 /FVC and maximum voluntary ventilation (MVV). Results: The results revealed that body weight, body mass index (BMI), PEFR, FEF 25-75% and MVV are significantly high among male tribal children in comparison to non-tribal children. Height, weight, waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), PEFR and MVV were found to be significantly more in tribal girls. In case of adolescents from Tripura, most of the pulmonary function parameters correlated with anthropometric parameters of the subject like height, weight, BMI, WHR, and WHtR. Conclusion: From the present study, it can be concluded that both anthropometric and pulmonary function status of tribal and non-tribal adolescents from Tripura are comparable. The computed regression norms may be used to predict pulmonary function of adolescents from Tripura by using anthropometric indices.

Keywords: Anthropometric indices, correlation, prediction equation, pulmonary function, tribal and nontribal adolescents


How to cite this article:
Choudhuri D, Sutradhar B. Pulmonary function of adolescents from Tripura, a North-eastern state of India. Lung India 2015;32:353-8

How to cite this URL:
Choudhuri D, Sutradhar B. Pulmonary function of adolescents from Tripura, a North-eastern state of India. Lung India [serial online] 2015 [cited 2019 Feb 19];32:353-8. Available from: http://www.lungindia.com/text.asp?2015/32/4/353/159568


   Introduction Top


Spirometric evaluation of pulmonary function is the most important tool for clinical assessment of respiratory functions in individuals. [1],[2] Population specific reference values are necessary for maintaining the reliability of pulmonary function evaluation. [3],[4] Till now, several studies have reported reference values for pulmonary function from different corners of the world, including India. [5],[6],[7],[8] There is significant difference in these values owing to genetic, environmental and ethnic differences of the population studied. [9],[10]

The normal standards for pulmonary function measurements among the tribal adolescents of Tripura, a North eastern state of India is not reported yet. Moreover, the difference between tribal and nontribal adolescents residing in Tripura is also not reported. Since, ethnicity and environment plays important role in influencing pulmonary function, and in view of paucity of pertinent data, evaluation of pulmonary function of adolescents from Tripura seemed important.

The present study was, therefore, aimed to evaluate pulmonary functions of both tribal and non tribal adolescents from Tripura. The study also aimed to evaluate association of pulmonary function parameters with various physical and anthropometric parameters of the subject from both the groups.


   Materials and Methods Top


This cross sectional study was conducted among adolescents from eight schools covering four different districts of Tripura. From each district one rural and one urban school was included for the study. The study was conducted between February to June 2013. Total number of subjects included in the study were six hundred and forty (640). Out of which 320 were from tribal and another 320 were from nontribal community of the state. In each group equal number of male (160) and female (160) were included for the study. The sample size was calculated according to World Health Organisation method for sample size calculation in health studies taking 95% confidance. [11]

All the students with in the age group of 10-14 years were requested to participate in the study, irrespective of their sex, ethnicity or socioeconomic status. A pre validated questionnaire that was used in INSEARCH studies across India was administered to the parents to identify children with any respiratory symptoms. [12] One hundred and eighty seven (187) subjects having the history or existing pulmonary disorders were excluded from the study. Informed consent to participate in the study was obtained from the parents of each children. The study protocol was approved by the Human Ethical Committee of the University.

Demographic information of the subject including age, sex, and ethnicity were recorded. [13] Anthropometric parameters like weight, height, chest circumference, hip and waist circumference were recorded using standardized procedure. [14] Height was measured with subject standing barefoot on a stadiometer (Bio + Plus R. Sl. No. 51392) and rounded to the nearest 10 th of a centimetre. Weight was recorded with the subjects wearing school uniforms to an accuracy of ± 0.1 kg by using a standard spring balance (Libra, India). Waist circumference was measured at the level of umbilicus and hip circumference was measured across the greater trochanter with legs and feet together by using a tailors measuring tape. The body mass index and waist hip ratio were calculated. [10]

A complete spirogram was performed according to American Thoracic Society (ATS) guidelines [15] by using an expirograph (Helios 702, RMS, India). The test was carried out in a private and quiet room in a standing position with the nose clip held in position on the nose. Data from two hundred and fifty three (253) subjects were not included for analysis as they could not perform spirometry according to ATS standard. The flow, volume/timed graph were taken out in accordance to the criteria based on the ATS. The subject was instructed to take a deep breath until the lung were full and then blow out through mouth as forcibly and as fast and as long as possible till the maximum capacity, sealing the lips tightly around a clean mouth piece. Best of the three acceptable curves was selected as the recording.

Spirometric parameters recorded for analysis were forced expiratory volume in 1 second (FEV 1 ), forced vital capacity (FVC), FEV 1 /FVC ratio, peak expiratory flow rate (PEFR), forced expiratory flow FEF 25- 75% . The maximum voluntary ventilation (MVV) was determined by fast, deep breathing for a 10 second period and reported as liters/minute.

Statistical analysis was performed using SPSS 16.0 (statistical Program for the Social Sciences) for Windows. Continues variables (e.g. age) were reported as mean ± standard deviation (SD). The mean for age, height, weight, BMI, WHR, FVC, FEV 1 , PEFR, FEF 25-75% and MVV were stratified by gender and ethnicity. The t-test was used to test for the difference in measurements between various groups at the level of significance P < 0.05. Pearson's correlation coefficients between spirometric parameters (FVC, FEV 1 , FEV 1 /FVC, PEFR, FEF 25-75% and MVV) and age, height, weight, BMI and WHR were calculated. Linear regression analysis was performed to establish the relationship between pulmonary function parameter and physical parameters.


   Results Top


[Table 1] shows the comparison of mean values for anthropometric and pulmonary function characteristics between tribal and non tribal male subjects. Among different anthropometric and pulmonary function parameters mean values for weight, BMI, PEFR, FEF 25-75% and MVV were found to be significantly higher in tribal male than their non-tribal counterpart.
Table 1: Recording of anthropometric and pulmonary function parameter of tribal and nontribal male subject

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[Table 2] represents anthropometric and pulmonary function parameters in female subjects. Mean values for WHtR, WHR, PEFR, and MVV of the subjects were significantly higher in tribal female and mean values height and weight were found to be higher in non tribal female subjects.
Table 2: Recording of anthropometric and pulmonary function parameter of tribal and nontribal female subject

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[Table 3] represents comparison of various pulmonary function parameters recorded in different groups of Indian children recently. [16],[17],[18],[19],[20] It shows that various parameters recorded in our study is comparable with that from other groups of children. The variations in values may be due variation in age group included and method and sensitivity of study protocol employed.
Table 3: Recent reports on pulmonary function measurements by different authors

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In male subjects PEFR and FEF 25-75% is correlated positively with age of the subject. Height of the subject correlated positively with FEV 1 /FVC % , PEFR, FEF 25-75%, and negatively with FVC. Weight of the subjects shows significant positive correlation with PEFR, FEF 25-75%, and negative correlation with FVC of the subject. BMI of the subjects positively correlated with FVC, PEFR, and MVV and negative correlation was found between BMI and FEV 1 /FVC % of the subjets. WHtR of the subject correlated negatively with FEV 1 /FVC % , and positively with FVC, and MVV of the subjects. WHR of the subjects exhibited significant positive correlation with FVC, MVV and negative correlation with FEV 1 /FVC % of the male subjects [Table 4].
Table 4: Pearson's correlation coefficient between different anthropometric and pulmonary function parameter of male subject

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In female, age of the subject shows significant positive correlation with FVC, FEV 1 , FEV 1 /FVC%, PEFR and significant negative correlation with MVV of the subjects. Height of the subjects correlated positively with FEV1, FEF 25-75% and negatively with MVV of the subjects. Weight of the female subjects exhibits significant positive correlation with FVC, FEV 1 , FEV 1 /FVC % and PEFR of the subjects but here is no significant negative correlation between weight and pulmonary function parameters of the subjects. BMI shows significant positive correlation with PEFR and significant negative correlation with FEV 1 , FEV 1 /FVC % , and FEF 25-75% of the subjects. WHtR of the subjects' exhibit significant positive correlation with FVC and MVV of the subjects and negative correlation with FEV 1 , FEV 1 /FVC, FEF 25-75% of the subjects. WHR of the subjects positively correlated with FVC and MVV and negatively correlated with FEV 1 , FEV 1 /FVC % of the subjects [Table 5].
Table 5: Pearson's correlation coefficient between different anthropometric and pulmonary function parameter of female subject

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The regression equation for FVC, FEV 1 , FEV 1 /FVC % , PEFR, FEF 25-75% and MVV based on weight, BMI, WHtR, and WHR are presented in [Table 6] for male subjects and [Table 7] for female subjects. A comparison of recently reported regression equations among Indian children is represented in [Table 8]. [17],[18],[19],[20],[21],[22] Most of these equations used age, height, weight of the subject as predictors of pulmonary function. Pulmonary function in our subjects showed positive correlation with markers of obesity like BMI, WHtR, and WHR, for this reason, we utilized these parameters in regression equation.
Table 6: Multiple regression norms for the prediction of pulmonary function measurements in male adolescent of Tripura

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Table 7: Multiple regression norms for the prediction of pulmonary function measurements in female adolescent of Tripura

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Table 8: Predictive equation derived from different recent studies

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   Discussion Top


In the present study we evaluated pulmonary function and their anthropometric predictors in school children 10-14 years of age from Tripura, a North eastern state of India. The pulmonary function and anthropometric parameters of ethnic tribal children and non-ethnic Bengali children residing in the state of Tripura, evaluated in our study, are found to be comparable. The bodyweight and BMI of tribal children were significantly higher. Both height and weight of non-tribal female were found to be higher. The waist to hip ratio (WHR) and waist to height ratio (WHtR) of tribal female were significantly higher.

The tribal population of the country is generally at risk of under nutrition owing to different factors affecting their health status. [23] Most of the earlier studies have reported poor health condition of tribal children. [24] Comparable nutritional status of tribal children from Tripura indicates improved health status of the children owing to improved health care and other facilities. [25]

The lung function parameters like PEFR, PEF50%, and MVV were found to be significantly higher in tribal children than the non-tribal Bengal children. Other lung function parameters like FVC, FEV 1 , FEV 1 /FVC% were found to be comparable between the children of both the groups. Singha and Nag also reported a higher value of FVC, FEV 1 , among the urban male tribal children of Tripura than the non-tribal children. [26] PEFR recorded by them was less in tribal male than non-tribal male children. Gupta et al. reported a better peak expiratory flow rate for children living at high altitude than the low landers. [27]

However, Kasyap et al. did not find any difference in PEFR values between highlander tribal children and children from West or lowlanders urban North Indian children. [28] Comparable nutritional status of tribal children might contribute to better pulmonary function status among the tribal children from Tripura. [29]

Variables like ethnicity, age, weight, and height, are reported to be the prime predictors of lung function in different groups of population. [30],[31] In our study, parameters like height, weight, BMI, WHR and WHtR correlated positively in different groups of subjects. Meng-chiao Tasi, et al. observed that standing height was the factor with highest correlation with the pulmonary function parameters in growing children aged 6-11 years in Tiawn city. [32] Ya-Nan Ma, et al. recently developed predictive equation of lung function for 9-15 years old children from North east china following ATS/ERS Task force guidelines and using predictor variable like age, height, and weight. [33] Doctor et al. in their study with Gujarati school children of 8-14 years of age found, for FVC and FEV highest correlation was presented with age in girls and height in boys. For FEV1% significant negative correlation was present with age and height in both sexes, but positive correlation was found with surface area. Similarly, PEFR showed highest correlation with surface area in boys and girls. [18] Various earlier studies on children from India mostly used age, height and weight as predictor for pulmonary function. [34],[35],[36]

Number of recent studies have observed that pulmonary function shows an inverse relationship with various markers of obesity and fat distribution in children and adolescent. [37],[38],[39] Markers of both general and visceral obesity like BMI, WC, WHR are reported to influence pulmonary function in children and adolescent. [40],[41] Some of the recent studies showed that respiratory mechanics can be affected by fat distribution pattern and central obesity, estimated by WC and WHR, independent of BMI. In view of these findings and depending on results of correlation analysis we utilized marker of obesity like weight, BMI, WHR, and WHtR in multiple regression analysis for prediction of pulmonary function measurements in both male and female adolescents from Tripura.

The study included both ethnic and non ethnic population of the state for comparison. This provides overall picture of pulmonary function of different groups of children in the state. However cross sectional nature of the study is a limitation. Longitudinal studies are needed to investigate the effect of various anthropometric predictors on pulmonary function of the studied subjects.


   Conclusion Top


In conclusion, our study determined the normative values for pulmonary function parameters in children from Tripura and proposed predictive equation with anthropometric markers like BMI, WHR, WHtR. These normative reference values can be utilized for evaluating pulmonary function of children living in Tripura.


   Acknowledgement Top


Financial assistance for the project by Indian Council of Medical Research (ICMR), New Delhi, is acknowledged.

 
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  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7], [Table 8]



 

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