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Year : 2015  |  Volume : 9  |  Issue : 1  |  Page : 20-25

Relationship between anthropometric variables and lung function parameters among primary school children

1 Department of Physiotherapy, Bayero University Kano, Kano, Nigeria; Department of Rehabilitation Sciences and Physiotherapy, Ghent University, Ghent, Belgium
2 Department of Physiotherapy, Bayero University Kano, Kano, Nigeria

Date of Web Publication21-Aug-2015

Correspondence Address:
Jibril Mohammed
Department of Physiotherapy, Bayero University Kano, Kano, Nigeria

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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/0331-3131.163331

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Background: Anthropometric measurements in children are known to change with increasing age and other factors. This study investigated the relationship between anthropometric variables and lung functions (LF) of children.
Materials and Methods: Two hundred and fifty apparently healthy school children aged between 6 and 12 years (male: 9.3 ± 2; female: 9.4 ± 1.9) participated in this study. They were recruited using multi-stage sampling technique from five purposively selected primary schools in Kano, Nigeria. Their LF such as forced expiratory volume in 1 s (FEV 1 ), forced vital capacity (FVC) and peak expiratory flow rate (PEF) were assessed using a micro computerized spirometer. Additionally, anthropometric variables, including height, weight, chest circumference (CC), waist circumference (WC) and hip circumference (HC) were measured. Data were analyzed using descriptive and inferential statistics on SPSS. Alpha probability level of 0.05 indicated point of significance.
Results: The results showed gender similarities for age (P = 0.502; 95% confidence-interval [CI] = 0.07-0.15), height (P = 0.142; 95% CI = 0.003-0.04), weight (P = 0.511; 95% CI = −2.34-6.68), WC (P = 0.556; 95% CI = −2.23-6.53), HC (P = 0.084; 95% CI = −1.67-8.13), CC (P = 0.133; 95% CI = −0.11-0.02), FEV 1 (P = 0.452; 95% CI = −0.81-0.69), FVC (P = 0.158; 95% CI = −0.15-0.8) and PEF (P = 0.181; 95% CI = −0.009-0.07). All anthropometric variables showed significant relationship with LF parameters (0.289> r <0.581). In the male children, underweight and normal weight body mass index (BMI) groups had lower values for FEV 1 (P = 0.003) and FVC (P = 0.001) compared the higher BMI groups. In the female children, only the underweight BMI group showed lower values for FEV 1 (P = 0.042) and FVC (0.05) compared to other groups (P < 0.05). Conversely, the PEF was similar across all the BMI groups among both males (P = 0.104) and female (P = 0.296) children.
Conclusion: Anthropometric variables are strong determinants of LF among the children. Besides higher BMI had a positive influence on FEV 1 and FVC values.

Keywords: Anthropometry, lung function, obesity, relationship

How to cite this article:
Mohammed J, Maiwada SA, Sumaila FG. Relationship between anthropometric variables and lung function parameters among primary school children. Ann Nigerian Med 2015;9:20-5

How to cite this URL:
Mohammed J, Maiwada SA, Sumaila FG. Relationship between anthropometric variables and lung function parameters among primary school children. Ann Nigerian Med [serial online] 2015 [cited 2021 Apr 18];9:20-5. Available from: https://www.anmjournal.com/text.asp?2015/9/1/20/163331

   Introduction Top

Lung function tests (LFT)/spirometry are techniques use to evaluate how well the lungs work, by determining how much air the lung can hold and how quickly air moves in and out of the lungs. It is also the measures of the rate of changing lung volumes during forced breathing. [1],[2],[3] The measurement of lung function (LF) is helpful in the diagnoses and management of diseases, monitoring of rehabilitation outcomes as well as in epidemiological surveys. [3],[4],[5]

Children have a dynamic developmental phase during which lung volume and airway sizes change with increasing age. During this period, LF parameters are also influenced by factors like weight, height, sex, environmental factors, body composition, ethnicity and prematurity. [3],[6],[7],[8],[9],[10] The current global increase in the prevalence of obesity in children, especially in the urban areas, which has been associated with negative consequences on the LF of these children. [10],[11],[12]

Anthropometric measurements are an important, widely applicable, noninvasive, and inexpensive technique for assessing body size, proportions, and composition. [13] Differences in LF parameters (forced expiratory volume in 1 s [FEV 1 ] and forced vital capacity [FVC]) are due in part to differences in body proportions as well as several other factors. Some evidence also suggest that psychosocial factors, and family problems, may influence truncal length and height in childhood. [10] Presently, the specific effect of environmental factors on LF are not clearly defined in literature. However, significant differences have been reported in the results of LF studies carried out in different parts of the world. Moreover, ethnic group differences are largely due to the differences in anthropometric parameters. [14]

In developing countries, enormous environmental problems such as air pollution problems resulting from automobile exhaust, in addition to inadequate environmental planning and monitoring still exist. Like any other city of the world, Kano metropolis has developed steadily over the years, resulting in a steady progress in industrialization, increase in population, and traffic density. [15]

Additionally, since habitat is one of the multifarious factors, which may influence both anthropometric measures and LFTs. Reporting reliable correlates pulmonary function measurements from specific areas is necessary, especially in view of the paucity of pertinent data. To the best of our knowledge, no such study has been carried out in Kano. This study was therefore designed to investigate the relationship between LF indices and selected anthropometric variables among primary school children.

   Materials and Methods Top

Ethical approval to conduct the study was obtained from the Ethical Committee of Aminu Kano Teaching Hospital, Kano prior to commencement of the study. All the parents/guardians gave their written consent before their child/ward was allowed to participate. In addition, all the children were also given a choice whether to participate or not, and they were also allowed to decline participation at any point during the study protocols.

A total of three hundred and eighty (380) primary school children between the ages of 6 and 12 years where initially recruited to participate in the study from a population of primary school children from five primary schools (two public and three private) in Nassarawa local government area (LGA) of Kano municipality, Nigeria. The study area is most populous and cosmopolitan LGA in Kano State. The LGA has an area of 34 km΂ spread across 26 wards. The schools that participated in the study were selected purposively one each from five randomly selected wards. Purposive sampling was utilized to select the schools with high enrolment rate that can provide diverse strata of participants because most of the schools had very low enrollment.

The initial study sample was arrived at using the sample size estimation table that is based on the formula; n = X 2 × N × P × (1 − P)/(ME 2 × [N − 1]) + (X 2 × P × [1 − P]), were n = sample size, X 2 = Chi-square at the specified confidence level at 1° of freedom, N = population size, P = population proportion (0.50) and the ME = desired margin of error. The estimated population from the school in the LGA was estimated to be about 75,000. Using the sample size estimation table, the calculated sample based on 95% confidence level and a 5% margin of error is 380. [16] Hence, 380 children were sampled (76 from each of the five schools).

The Public Schools are Race Course Primary School and Gwagwarwa Primary School, while the Private Schools are Yan-dutse primary school, Kano Capital Primary School and Crescent International School. A multistage sampling technique was used in selecting the study participants from each of the five selected schools. And this was done using the classroom register (sampling frames) from randomly selected classrooms after separating the list of the male and female children. The sampling was done systematically until the required number of male and female participants for each school was reached. We excluded children who could not complete the LF tests. Subsequently, only 250 pupils completed the study comprising of 119 boys and 131 girls.

Lung function measurements

The LF was assessed with the aid of the micro computerized spirometer (micro plus spirometer MSO4; made in USA). The technique of the procedure was explained to all the participants carefully and practical trials were conducted prior to actual measurements. Each participant started the procedure only after it was fully understood. The measurement was done in sitting position on a stool for all participants. They were then asked to take the deepest breath possible (total lung capacity), put the mouth piece (disposable) of the spirometer into their mouth. Thereafter, in one continuous breath they were instructed to blow into the mouth piece of the spirometer as hard and as quickly as possible using the maximum effort possible till they emptied all the air in their lungs. The reading indicated on the spirometer for three LF parameters (FVC, FEV 1 and peak expiratory flow [PEF]) was recorded for analysis. The readings for the FEV 1 and FVC were expressed in liters (l), while the PEF was expressed in liters per second (l/s). The procedure was repeated three times for each participant and the best of the three results with <5% deviation from another was taken into consideration for analysis. [17]

Anthropometric measurements

The weight for each participant was measured using a standard bathroom weighing scale. The participants were asked to remove all objects that are heavy on them (only light clothing) and they were barefoot before the weight reading was recorded in kilograms (kg) to the nearest 0.5 kg. For the height measurement they were also barefooted. Their feet were placed together on a level floor and their upper back, buttocks and heels touching the wall, while their head was held erect, then with the aid of a ruler, the point of greatest height perpendicular to the height meter reading was taken in meters (m) to two decimal places. The body mass index (BMI) was calculated by dividing the body weight by the square of the height in BMI = weight (kg)/height 2 (m 2 ) after BMI was calculated, the BMI number was plotted on the chart provided by center for disease control BMI-for-age growth charts (for either girls or boys) to obtain the BMI percentile ranking. BMI percentile allows for a comparison with normal values of children of the same sex and age on the chart. The percentile indicates the relative position of the child's BMI number among children of the same sex and age. The growth charts was used to categorize the participants based on weight status categories: Underweight (<5 th percentile), healthy weight (5-<85 th percentile), overweight (85-<95 th percentile) and obese ≥95 th percentile. [18]

Other anthropometric measurements were: (i) chest circumference (CC), which was measured during the inspiratory phase of breathing in a comfortable seating position, using an anthropometry tape rule at the level of the fourth intercostals space; [16] (ii) waist circumference (WC), which was done in standing position with the arms folded across the thorax, the measurement was taken midway between the lower rib margin and the iliac crest, that is, the narrowest point between the lower costal rib (10 th rib) border and the iliac crest; with the researcher standing in front of the subject and allowing the tape to pass around the abdomen; [16] and (iii) hip circumference (HC), whereby the same position was used as for the WC, however, the participant's feet were kept together and the gluteal muscles relaxed. The girth was taken at the level of the greatest posterior protuberance of the buttocks, which corresponds anteriorly about the level of the pubis symphysis.

The data were analyzed using descriptive and inferential statistics. Descriptive statistics of mean, standard deviation and percentage was used to summarize the physical characteristics of the subjects. Independent t-test was used to compare male and female children's LF and anthropometric variables. Pearson moment correlation method was used to explore the relationship of weight, height, BMI, WC, HC and waist to hip ratio and LF values (FVC, FEV 1 and PEF). One-way analysis of variance (ANOVA) was used to compare across the BMI groups and point of significant difference (P = 0.05) was determined using Fischer's least significant difference post-hoc. The data were analyzed using the IBM Statistical Package for the Social Sciences version 16.0 on windows software (PC).

   Results Top

The mean ages of the male and female children were 9.3 (±1.97) and 9.40 (±1.87) years respectively. While the mean height, weight, WC, HC and CC were 1.33 m ± 0.19 m, 29.90 kg ± 9 kg, 59.6 cm ± 7 cm, 65.4 cm ± 7 cm and 60.30 cm ± 6 cm respectively. The mean FEV 1 , FVC and PEF values of the participants were 2.04 ± 0.9l, 3.14 ± 1.6 l and 2.57 ± 0.6 l/s, respectively. There were no gender differences in all the anthropometric parameters of age (P = 0.502; mean difference of female to male ratio [MD] = 0.11; 95% confidence-interval [CI] = 0.07-0.15), height (P = 0.142; MD = 0.01; 95% CI = 0.003-0.04), weight (P = 0.511; MD = 2.84; 95% CI = −2.34-6.68), WC (P = 0.556; MD = 2.53; 95% CI = −2.23-6.53), HC (P = 0.084; MD = 3.43; 95% CI = −1.67-8.13) and CC (P =.133; MD = −0.07; 95% CI = −0.11-0.02) as well as in the LF parameters of FEV 1 (P = 0.452; MD = 0.26; 95% CI = −0.81-0.69), FVC (P = 0.158; MD = −0.11; 95% CI = −0.15-0.8) and PEF (P = 0.181; MD = 0.03; 95% CI = −0.009-0.07) of the children as presented in [Table 1].
Table 1: Physical characteristics and lung function variables

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[Table 2] shows the correlation matrix between the anthropometric variables and LF parameters. The results showed that there were significant relationships between all the anthropometric variables and LF parameters. All anthropometric variables showed significant relationship with the three LF parameters (0.289> r <0.581 for all).
Table 2: Correlation matrix

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According to the BMI percentile classification, of the 119 male children, 29 were underweight, 46 were normal weight, 25 were overweight and 19 were obese. Whereas among the 131 female children, 23 were underweight, 63 were normal weight 28 overweight and 17 were obese. The results of the ANOVA analysis comparing within group differences of the four BMI groups for the male and female participants showed that the FEV 1 and FVC values among the males participants was significantly lower in the underweight and normal weight groups when compared with the higher BMI categories. Specifically, the participants in the overweight BMI group had significantly higher FEV 1 (male = 0.003; female = 0.042) and FVC (male = 0.001 female = 0.05) scores in relation to all other groups. The results also showed that the PEF did not differ across all the four BMI groups in both (P = 0.104) and female (P = 0.296) children. The underweight BMI group of the female children had a significantly lower FEV 1 (P = 0.042) and FVC (P = 0.05) scores compared with all other BMI groups as presented in [Table 3].
Table 3: Summary of ANOVA and least significant difference across the different BMI groups

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   Discussion Top

The main objective of this study was to investigate the relationship between the LF parameters (FEV 1 , FVC and PEF) and selected anthropometric variables, which included WC, HC, CC and also to determine the BMI percentiles groups among primary school children in Kano. The participants were sampled from both private and public schools so as to enable account for diverse socioeconomic strata in a typical cosmopolitan environment. Moreover, previous studies have highlighted the importance and influence population specific variables on LF. [7],[19] This study also reported the effect of different BMI percentile grouping on LF among the male and female children, since prediction based on anthropometric measures including height, weight, CC, HC and WC often result in under or overestimated spirometry. [19]

The results of this study showed similar baseline characteristics in all variables (anthropometric and LF) between the male and female children. Although, this finding is different with results of some previous studies, [20],[21],[22] similar findings have also been reported by Barcala et al. [19] This might be in part due to differences in study populations, as LF and anthropometry can be affected by several factors such as race, geographical location and social circumstances. The children that participated in our study had a lower mean age compared with these studies, and that might have accounted for the similarity Between the male and female children anthropometric variables. Furthermore, puberty is an important factor that can cause changes in the physical and physiological characteristics of children within this age category.

The results of this study showed that there were significant differences across the different BMI groups for LF indices, and the differences existed mainly for FEV 1 and FVC values across the different BMI groups. The children in the underweight BMI group had the lowest FEV 1 and FVC values when compared to the other groups. This finding could be attributed to the effect of poor nutritional status, which is also known to directly cause conditions like low birth weight and disproportionate body composition who in turn have negative consequences on the LF. [7],[19] In the same vein, the results revealed that the obese BMI group had significantly lower values for FEV 1 and FVC compared with the overweight BMI group. Although, similar findings have been previously reported among Canadian [17] and Indian children. [20] The main explanation for this outcome in our study may be due to the possibility of a reduction in diffusing capacity, lower ventilatory muscle endurance and airway narrowing that is more prevalent among obese compared to overweight and normal weight children. [23],[24]

Furthermore, this study revealed that there was a significant relationship between all the anthropometric variables and LF parameters the children in this study. Previous studies have reported similar findings among children and even adults. [8],[19],[25],[26],[27],[28],[29] And this is generally attributed to the of the normal physiological development and growth pattern (spurt) that is common to children of this age group. [30] In general, height is known to be a strong indicator of high LF values. Moreover, it is the most reliable factor used in prediction equations. The height of individuals is also known to be a factor of their trunk length. However, the significant relationship that was seen between CC, HC and WC with the LF indices could be because of the influence of these parameters on the thoracic cage capacity. In the case of CC, larger CC have a higher mechanical advantage because of the enhancement in the descending of the diaphragm during respiration, hence a higher volume of air can be breathed in. And the higher the volume of air inspired the higher LF indices. Our study also reported a significant relationship between WC and LF values. This is understandable in view of the LF in terms of the age (growth) and WC relationship as corroborated by a past study among young adults. [31]

The results of this study are important because of the increasing prevalence of overweight, obesity and respiratory diseases in our society. The increased awareness of the relationship between BMI and other anthropometric measures on LF will result in better interpretation of LF test. Therefore, BMI and WC could be suggested for use in the prediction equations of LF, thereby improving the accuracy of the equations. The main limitations of this study is that the participants were not matched for their physical activity or physical fitness level, which are both known to also influence LF. However, the effect of these factors on the study results are likely to be limited, due to the diversity of the participants.

   Conclusion Top

Gender did not have any influence on the anthropometric and LF of the children in this study. However, the height, weight WC, HC and CC were all strong determinants of LF. It was also concluded that the lower BMI groups had lower FEV 1 and FVC compared to the over-weight BMI group in both male and female children. Conversely, BMI group did not have any effect on PEF of the children.

   References Top

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  [Table 1], [Table 2], [Table 3]

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[Pubmed] | [DOI]


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