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Original Article

Indian Pediatrics 2003; 40:705-711 

Study on Lung Function Tests and Prediction Equations in Indian Male Children


 

P. Sitarama Raju, K.V.V. Prasad, Y. Venkata Ramana*, Syed Kabir Ahmed+,
K. J.R. Murthy

From the Department of Physiology, Vemana Yoga Research Institute, Hyderabad, *National Institute of Nutrition, ICMR, Hyderabad, and +Gandhi Medical College, Hyderabad, India.

Correspondence to: Dr. Y. Venkata Ramana, Senior Research Officer, Department of Work Physiology, National Institute of Nutrition, ICMR, Jamai-Osmania, Hyderabad 500 007, India. E-mail: [email protected]

Manuscript received: May 7, 2002, Initial review completed: July 20, 2002; Revision accepted: February 14, 2003.

Abstract:

Objectives: The present study was carried out to evaluate lung functions and develop prediction equations in Indian boys. Subjects: 1555 normal healthy schoolboys from Hyderabad city who were in the age group of 5 to 15 years were selected for the present study. Design: The anthropometric parameters such as height, sitting height, weight, and chest circumference were measured and body surface area (BSA) and percent body fat (%Fat) were derived. The lung functions studied were FEV1 , FVC, FEV1% and PEFR. Results: The height, sitting height, weight, BSA, chest circumference, body fat as well as FEV1 , FVC, FEV1% and PEFR were comparable with Indian boys. The height for age, weight for age and weight for height were found to be lower than 50th percentile of NCHS standards in the subjects studied. Similarly the lung function values of the study population were found to be lower than the values of corresponding western population. Conclusion: Regression equations were derived to predict FEV1, FVC and PEFR using physical characteristics. Height, chest circumference and fat free mass were the best predictors for FEV1, FVC, and PEFR. Age, height, sitting height, weight, chest circumference and fat free mass showed significant association with lung functions.

Key words: Adolescents boys, Lung functions.

Several studies on lung functions were carried out in children of different age groups in different parts of India(1-6). Studies carried out in children had projected the equations for predicting different lung functions using height, age and weight as independent variables(1,4). Two other studies reported regression equations using age, height as independent variables(2,5).

Studies carried out on western, Afro-Caribbean and Indian children published prediction equations for FVC, FEV1, and PEFR using height(7), sitting height(8) as independent variables, and they have clearly established that there was a large variance among lung functions in these populations. On the other hand a study carried out in UK reported the ethnic variations in lung functions among children of European, Afro-Caribbean and Indian origin(9). Another study has reported that body fat has to be corrected for to achieve better prediction of lung functions using height as an indicator(10).

The present study was aimed to elucidate which of the anthropometric indices have an influence on prediction of lung functions in Indian population. Apart from this, the regression equations were developed and presented.

Subjects and Methods

The present study was conducted on all available 1555 normal, healthy boys aged between 5 and 15 years, selected from three different schools in Hyderabad. The purpose and objectives of the study were explained to the subjects, parents and the school management and their consent was obtained. The ethical committee of the Institute approved the design and study protocol. The study excluded the boys suffering from any respiratory diseases or had a recent history of respiratory infections.

The anthropometric indices recorded were height, sitting height, weight, and chest circumference (expired and inspired). The height and weight was measured by using height and weight scale (Libra, India). The heights were measured to nearest mm. Weight was measured with minimal clothing to the nearest 100 g. Fat fold thickness were measured at biceps, triceps, sub scapular and suprailiac regions nearest to 0.2 mm by using skin fold callipers (Holtain, UK). Body surface area (BSA) was derived using the height and weight of the boys(11). Body fat was estimated from fat fold thickness using the sex-matched equations of Slaughter et. al.(12) and fat free mass (FFM) was derived.

Each boy was explained and demonstrated the technique of the lung function test and was given three trials prior to the actual measurement. Then the subjects were asked to perform the test three times and best of the three results were taken into consideration. The measurements such as FEV1, FVC were made by using spirometer (Vitalograph, UK) and PEFR was measured by Wright’s peak flow meter and these values were measured at BTPS. The FEV1 and FVC ratio was then calculated. The spirometer was calibrated everyday with one liter standardized syringe before measurement.

The correlation coefficients of anthro-pometric measurements with lung functions were estimated. It was observed that the height, weight, sitting height, chest circum-ference, BSA and FFM had shown signi-ficantly high correlation with FEV1, FVC and PEFR. The correlation co-efficient of chest circumference, inspired and expired, with lung functions was found to be highly significant. Hence, only expired chest circumference values were used in the present study. In the present study, the age factor was removed in the step-down regression analysis and hence it was not used in prediction of lung functions.

The analysis of the data was carried out using SPSS statistical package (Version 10). The values were indicated as mean ± SD and the significance were noted at 0.01 levels. The correlation co-efficient and regression equations were derived from anthropometric measurements and lung function tests. Preliminary analyses were carried out to study the distributions and associations of the variables involved in the development of the predictive models. Several models, linear, quadratic, cubic or logarithmic were tried for the prediction of FEV1, FVC and PEFR. Then comparing the model’s R2 values, checking for violation of assumptions, and analysing the model residuals selected the best models. Separate linear regression equations were computed using the best-fitted predictors, i.e., height, chest circumference and FFM.

Results

The age wise physical characteristics are given in Table I. The boys were compared with NCHS standards and were found to be lower than 50th percentile considering their height for age, weight for age and weight for height. The information pertaining to lung functions are given in Table II.

TABLE I

Anthropometry and Body Composition Profile of Boys
Age
Yrs (n)
Height
(cm)
Standard
height (cm)
Weight
(kg)
Standard
weight
Sitting
height (cm)
Surface
area (m2)
Body fat
(%)
Fat free
mass (Kg)
Fat
(Kg)
Chest
(Cm)
5
(138)

105.28 ± 5.90 

104.00 

15.80 ± 2.21

16.00

55.19 ± 3.36

0.63 ±  0.09 

15.74 ± 1.85

13.29 ± 1.69 

2.51 ± 0.60 

50.28 ± 2.55
6
(134)

112.20 ± 5.67

109.90

17.42 ± 1.87 

17.70

59.11 ± 2.89 

0.70 ± 0.08

14.47 ± 1.41

14.89 ± 1.52 

2.53 ± 0.44 

51.05 ± 2.31
7
(128) 

116.39 ± 6.00

115.20 

19.03 ± 3.05 

19.50 

60.67 ± 3.78 

0.75 ± 0.10 

14.88 ± 3.65 

16.15 ± 2.27 

2.88 ± 1.23 

52.28 ± 3.12
8
(138) 

120.40 ± 5.91 

120.10

20.54 ± 3.38

21.30 

60.41 ± 3.20 

0.80 ± 0.10 

15.36 ± 3.81 

17.31 ± 2.40 

3.23 ± 1.41 

53.64 ± 3.19
9
(131)

127.40 ± 5.99 

124.90 

23.28 ± 3.28

23.30

65.86 ± 2.98 

0.90 ± 0.10 

15.01± 4.51

19.70 ± 2.26 

3.58 ± 1.73 

55.73 ± 2.80
10
(151)

133.22 ± 5.89

129.70 

26.12 ± 4.23 

25.50 

68.33 ± 3.15 

0.99 ± 0.11 

16.53 ± 5.49 

21.67 ± 2.89 

4.45 ± 2.41 

57.90 ± 3.65
11
(147) 

138.19 ± 6.20 

134.70 

28.32 ± 4.60 

28.10 

70.75 ± 3.46 

1.06 ± 0.12 

14.91 ± 4.22 

23.99 ± 3.24 

4.34 ± 2.02 

59.70 ± 3.44
12
(151)

143.40± 6.26 

140.00 

31.90 ± 5.89 

31.50 

72.81± 3.81 

1.17 ± 0.17 

16.34 ± 6.46 

26.47 ± 4.01 

5.43 ± 3.28 

61.48 ± 4.25
13
(144)

146.55 ±7.25 

145.90 

32.43 ± 6.49 

35.60 

74.73 ± 3.74 

1.23 ± 0.20 

15.90 ± 5.84 

27.91 ± 4.47 

5.53 ± 3.57 

62.48 ± 4.31
14
(153) 

157.38 ± 8.23 

152.10 

40.80 ± 7.45 

40.60 

80.06 ± 4.42 

1.46 ± 0.29 

13.85 ± 5.35 

34.95 ± 5.51 

5.85 ± 3.34 

67.20 ± 5.30   
15
(140)

162.60 ± 6.87 

158.70 

45.80 ± 7.50 

46.00 

82.67 ± 3.96 

1.59 ± 0.27 

16.12 ± 7.11 

38.08 ± 4.78 

7.72 ± 4.69 

70.80 ± 5.18
All values expressed as Mean ± SD. Standard weight and height refer to NCHC 10th centile.
TABLE II

Lung Function Parameters Of The Total Subjects (n=1555)

Age (Yrs)
(n)
FVC
(L/sec)
FEV1
(L/Sec)
FEV1/FVC%
PEFR
(L/sec)
5
(138)

0.78 ± 0.24 

0.76  ± 0.23 

98.40 ±  4.97 

155.31 ± 38.66
6
(134) 

0.98 ± 0.22 

0.94 ± 0.20 

96.62 ± 5.18 

191.78 ± 36.01

(128)

1.14 ± 0.27 
1.09  ± 0.24 
96.43 ±  5.69 
210.53 ± 45.66
(138) 
1.24 ± 0.24 
1.17 ± 0.21 
94.25 ± 5.21 
223.56 ± 41.50
(131) 
1.49 ± 0.25 
1.37 ± 0.22 
91.87 ± 5.64 
261.31± 44.83
(151) 
1.68 ± 0.29 
1.54 ± 0.26 
92.21 ± 5.88 
283.39 ± 49.42
(147) 
1.92 ± 0.31 
1.75 ± 0.30 
90.98 ± 4.41 
307.11 ± 50.61
(151) 
2.07 ± 0.37 
1.89 ± 0.34 
91.07 ± 6.11 
334.21± 52.25
(144) 
2.19 ± 0.41 
1.99 ± 0.38 
90.82 ± 5.98 
338.44 ± 56.60
(153) 
2.69 ± 0.48 
2.50 ± 0.45 
92.78 ± 5.16 
421.45 ± 62.02
(140) 
3.03 ± 0.56 
2.82 ± 0.53 
93.11 ± 5.16 
465.59 ± 62.76
All values expressed as Mean ± SD
 

The prediction equations were derived based upon the correlation coefficients of physical characteristics with lung functions. It was observed that the age, height, sitting height, weight, chest circumference (expired), fat free mass and BSA were highly correlated with that of the lung functions. In view of this age, height, weight, chest circumference and FFM were used as the independent variables in the prediction equations. Significantly high R2 values were found only when height, chest circumference and FFM were used as independent variables in regression analysis. Therefore, the data pertaining to these regression equations are presented in Table III.

 

Table III

Regression Equations for Lung Functions with Height, Chest and Fat Free Mass (n=1555)
Dependent variable
Regression equations
R
R2
SE of estimate 
 
FEV1 
 
FEV1 = –2.916 + (0.03409*Height) 
0.922* 
0.851 
0.2687
FEV1 = –3.286 + (0.08401*Chest) 
0.894* 
0.799 
0.3120 
FEV1 = –0.134 + (0.07583*FFM) 
0.924*
0.855 
0.2650
 
FVC 
 
FVC = –3.272 + (0.03773*Height) 
0.929*
0.864 
0.2819 
FVC = –3.672 + (0.09282*Chest) 
0.899*
0.808 
0.3346
FVC = –0.177 + (0.08330*FFM) 
0.925*
0.855 
0.2908
 
PEFR 
 
PEFR = –370.050 + (4.963*Height) 
0.897*
0.804 
46.0680 
PEFR = –405.601 + (11.920*Chest) 
0.847*
0.717 
55.3918
PEFR = 38.125 + (10.912*FFM) 
0.888*
0.789 
47.7753
* Significant at p <0.001

Discussion

Lung functions in children were largely overlooked because of the difficulties in measuring them at clinical set-ups. They are also not taken-up due to expensive equipment required and lack trained technicians to carryout these tests. For the diagnosis and follow-up of respiratory diseases in children, lung function tests are essential and where the facilities are available for direct measure-ments of lung functions, the prediction equations can be used as referral standards for comparison.

In India, several studies were carried out on school children to predict the lung func-tions using anthropometric variables(1-6). Most of these studies included local boys and the number of volunteers was comparatively low. In order to overcome the ethnic bias in the prediction equations, emphasis was made in the selection of the subjects by recruiting the participants who were settled in Hyderabad and having 11 out of the 15 official Indian languages as their mother tongue.

The studies conducted on boys at Bombay(1), Chandigarh(2), Delhi(4), Kerala(5) have projected different types of regression equations for lung functions. Some of them had used age, height and weight(1,4,5), age and height(1,2), age and BSA(2) and height alone(3) as independent variables for prediction of lung functions. These studies have showed that there were differences in the lung function values due to difference in ethnicity among these subjects.

Studies conducted in western countries reported that the ventilatory function values were significantly different between Mexican-American, white and black children population and presented the regression equations, separately for each race, to predict these ventilatory function values using height as a dependant variable(7). The same group also reported that the racial differences were greatly reduced when sitting height was used as a predictor for ventilatory function values(8). In a UK study, it was reported that the difference in lung functions between boys and girls is smaller when the function is related to stature than to sitting height. They further stated that the difference was further reduced when fat free mass/stature2 and percentage body fat are included in the prediction equations(10).

A study conducted in Chinese children and adolescents in Hong Kong demonstrated that FVC in boys were 8-10% lower in their study as compared to studies carried out on whites. They have presented the regression equations for lung functions with standing height as dependant variable. They concluded that the exogenous factors might contribute signifi-cantly to the differences in lung function values among ethnic groups(13). In another study Polynesian children showed that Polynesian and European children generally showed different slope and intercept relationship for the prediction of lung volume from height. They stated that this could be explained based on lung growth and maturation(14).

In two separate studies carried out in European, Indian and Afro-Caribbean children at Nottingham, UK reported a large difference in FVC and FEV1 between the groups studied. This difference was attributed to constitutional rather than environmental influences(9).

The studies conducted on Indian children have projected the regression equations, for estimating lung function variables, using age, height, weight and BSA as the independent variables(1-6). On the contrary, studies conducted on western populations have used height(7), sitting height(8), stature, FFM/stature2 and % BF(10) as independent variables to predict the ventilatory functions. However in the present study no significant predictability of lung functions were found using age and weight as an independent variables and hence were not considered in the prediction model. On the other hand it was found that significantly high correlation existed between lung functions with sitting height, chest circumference and FFM apart from height. Since the measurement of sitting height is likely to give erroneous results at rural set-ups, the regression equations were presented by using height, chest circum-ference and FFM as the independent variables for predicting the lung functions. Of these three parameters height and chest circum-ference can be measured accurately with the help of simple measuring tape.

In view of the large sample size in the age range of 5-15 years the equations of the present study can be used largely to calculate the lung functions in children anywhere in India in both urban and rural populations for epidemiological surveys etc. and also as referral standards against measured values. The age specific(5-15 years) regression models developed in the present study would facilitate in measuring lung functions of Indian children delimiting the ethnic differences.

Acknowledgements

The authors express their sincere gratitude to Mrs. Subharty for her help in data collection and preparation. The authors express their sincere appreciation and gratitude to the students, their parents and the school managements who had encouraged the students to participate in this study. The authors acknowledge the support extended by M. Venkata Reddy, Director, Vemana Yoga Research Institute and Gowrinath Shastry, Deputy Director, National Institute of Nutrition, Hyderabad. The authors are grateful to M/S Vitalograph, UK for providing lung function graph cards.

Contributors: PSR, KVVP, SKA and KJRM were involved in concept, design, analysis, interpretation of data, drafting the article and final approval of the version. YVR was involved in the concept, design, analysis and interpretation of data, revising for intellectual content and final approval of the draft.

Funding: Institutional grants.

Competing interests: None stated.

Key Messages

  • The values of present study can be used as referral standards against measured values for Indian male children.

  • The age specific regression models would facilitate in measuring lung functions of Indian children delimiting the ethnic differences.

  • The equations of the present study can be used largely to calculate the lung functions in Indian children.

 

 References


 

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