|Year : 2018 | Volume
| Issue : 1 | Page : 6-10
Basic anthropometric parameters and ventilatory function indices among current cigarette smokers
Muhammad D Isah1, Muhammad A Makusidi1, Anas A Sabir1, Juliana U Okpapi2, Chibueze H Njoku3, Abdullahi A Abba2
1 Department of Medicine, UDUTH, Sokoto, Nigeria
2 Department of Medicine, ABUTH, Zaria, Nigeria
3 Department of Medicine, UCTH, Calabar, Nigeria
|Date of Web Publication||29-May-2018|
Dr. Muhammad D Isah
Department of Medicine, Usmanu Danfodiyo University Teaching Hospital, P.M.B. 2370, Sokoto
Source of Support: None, Conflict of Interest: None
Background: Ventilatory function indices [forced vital capacity (FVC), expiratory volume in 1 (FEV1), and FEV1/FVC] are a function of the basic anthropometric parameters (weight and height). Cigarette smoking is an important confounder in the relationship between ventilatory function indices and basic anthropometric parameters.
Aim: To determine the relationship between anthropometric parameters and ventilatory function among male adult cigarette smokers.
Materials and Methods: This is a community-based cross-sectional study incorporating 200 male participants (150 cigarette smokers and 50 non-smokers) who met inclusion criteria using stratified random sampling technique. Participants were drawn from local governments that constituted Sokoto metropolis. Subsequently, participants had a questionnaire adapted from European Community Respiratory Health Survey administered to collect demographic, clinical and cigarette smoking data. Ventilatory function test was performed using Clement Clarke One Flow Spirometer, version 1.3 Revision 0 (Clement Clarke International, Edinburgh, UK). The highest value of each ventilatory function indices (FEV1, FVC, FEV1/FVC) was chosen for analysis. Data were summarized, and statistical tests were applied using the software Statistical Package for Social Sciences, version 19 (IBM SPSS Inc., Chicago, IL, USA).
Result: The majority of study participants among cigarette smokers and control were young, single and had a form of formal education. There was no significant difference in the mean of anthropometric indices [weight, height, body mass index (BMI)] of participants (cigarette smokers) and control (non-cigarette smokers). Twenty-nine (58%) non-cigarette smokers were overweight/obese as against 35 (23.3%) participants among cigarette smokers observed to be equally overweight/obese. Mean values of the ventilatory function indices except FVC were low among study participants as compared with control. Furthermore, the mean FEV1/FVC between participants (75.60 ± 7.53) and control (82.48 ± 6.11) was statistically significant (P = 0.001). A significant correlation between anthropometric parameters (height and BMI) and ventilatory function indices (FEV1 and FVC) was observed among study participants and control.
Conclusion: Ventilatory function indices are associated with anthropometric parameters among cigarette smokers. Although, BMI did not significantly affect decline in ventilatory function indices among cigarette smokers, an inverse relationship was observed between them.
Keywords: Anthropometry, association, spirometry, tobacco use
|How to cite this article:|
Isah MD, Makusidi MA, Sabir AA, Okpapi JU, Njoku CH, Abba AA. Basic anthropometric parameters and ventilatory function indices among current cigarette smokers. J Med Trop 2018;20:6-10
|How to cite this URL:|
Isah MD, Makusidi MA, Sabir AA, Okpapi JU, Njoku CH, Abba AA. Basic anthropometric parameters and ventilatory function indices among current cigarette smokers. J Med Trop [serial online] 2018 [cited 2019 May 23];20:6-10. Available from: http://www.jmedtropics.org/text.asp?2018/20/1/6/233420
| Introduction|| |
Changes in the basic anthropometric parameters (weight and height) can substantially affect the ventilatory function of individuals. While this is true for the general population, cigarette smoking poses an additional confounding factor coupled with the intricate relationship between anthropometric indices and ventilatory function among cigarette smokers., Similarly, there is lack of consensus on effect of cigarette smoking on body weight., This observation is without prejudice to the fact that nicotine (a major component of cigarette smoke) is known to increase energy expenditure and reduce appetite. Worthy of mention is the need to clarify whether the association between cigarette smoking, and obesity merely reflects differences in other lifestyle factors (physical activity, poor diet, and alcohol consumption).
Obesity is a public health challenge that is assuming an epidemic proportion in Nigeria., This may not be unrelated with the report that obesity appears to be generally acceptable and misconstrued as signs of affluence, good living, and esteem in Nigeria. Obesity is not only a harbinger for ventilatory dysfunction but also a well-recognized risk factor for cardiovascular and metabolic diseases. These multi-systemic effects of obesity may have been underpinned by the strong correlation between obesity and body fat percentage.,
The natural course of ventilatory function in healthy individuals is marked by increase, plateau and decline at various points in human life. These changes in ventilatory function at any given time are largely determined by the maximally attained level of lung function during early adulthood, onset of decline, and the rate of decline. Studies have reported a detrimental effect of obesity on lung function, which is reflected by a decline in ventilatory function indices.,, The ventilatory dysfunction among obese individual is thought to be due to a decrease in diaphragmatic excursion or increased weight on the chest wall, thereby, increasing airway resistance and the work of breathing.,
There is paucity of studies examining the relationship between ventilatory function and body weight among cigarette smokers in Nigeria. Similarly, there is the challenge of establishing the anthropometric determinants of ventilatory function among cigarette smokers and agreeing if it concurs with that of never cigarette smokers. Furthermore, there is need to determine whether there is an association between basic anthropometric parameters and ventilatory function indices among cigarette smokers. It is against this backdrop that we set to assess the relationship between anthropometric parameters and ventilatory function among male adult cigarette smokers in our environment. This study would form a basis for future reference in establishing anthropometric determinants of ventilatory function indices among current cigarette smokers.
| Materials and methods|| |
Approval from Health Research and Ethics Committee of Usmanu Danfodiyo University Teaching Hospital, Sokoto was obtained. The data for this study were collected from September 1, 2013 to February 28, 2014. Similarly, study participants gave informed consent.
This is a community-based cross-sectional study among male adult who at the time of the index study either indulge in cigarette smoking (study participants) or are never cigarette smokers (matched control). A stratified random sampling technique was used to select participants and controls from residents of Sokoto metropolis (constituted by Sokoto North (SN) Local Government Area (LGA), Sokoto South (SS) LGA and Wamakko (WK) LGA with a population of 232,846, 194,914 and 179,619, respectively). Two cigarette selling points from each LGA (a total of six study sites) were randomly selected for recruitment of study participants. The sample size was determined by using a formula for sample size calculation for the comparison between two groups [2SD2 (Zα/2 + Zβ)2/d2] when endpoint is quantitative data. On the basis of study power of 80% and values of mean weight from study by Alkali et al., [standard deviation (SD) of 2, Zα/2 of 1.96 (from Z table), Zβ of 0.84 (from Z table), d (effect size) of 0.1] the estimated sample size is 100. The sample size was scaled up and subject to control ratio of 3:1 was chosen to arrive at 150 participants and 50 controls. The study participants were adult, male, current cigarette smokers (participants) and a healthy, never smoking, sex- and age-group matched adults (controls). All participants in the index study met inclusion criteria (without chest deformity, illness(es) or previous cardiothoracic surgery that would hinder the performance of spirometry).
Information which include participants’ socio-demographic characteristics (age, area of residence, education level, occupation, marital status) and cigarette smoking history (duration of cigarette smoking and pack years of cigarette smoking) was obtained. Furthermore, participants weight [using Hana Mechanical Weighing Scale (Precision Hana Scales Private Limited, Ramdaspeth, Nagpur, India), model BR9012] and height [using Seca Freestanding Mobile Stadiometer (Precision Hana Scales Private Limited, Ramdaspeth, Nagpur, India)] were measured to the nearest 0.1 kg and 0.1 m, respectively with participants wearing light clothing and without shoes. Body mass index (BMI) was calculated [weight (kg) divided by the square of height (m)]. Subsequently, spirometry [using Clement Clarke One Flow Spirometer, version 1.3 (UK)] was conducted according to the American Thoracic Society guideline while ensuring cigarette smoking abstinence of at least 1 h prior to the procedure. The largest ventilatory function indices [forced vital capacity (FVC), expiratory volume in 1 (FEV1), and FEV1/FVC] taken 5 min apart from at least three attempt (spirometry procedure) was recorded. Consequently, a post-bronchodilator spirometry was performed on participants with ventilatory function defect (obstructive and/or restrictive defect) to quantify the degree of reversibility. The instruments and equipment used in this study were properly checked, calibrated and verified before use. The age of participants was subcategorized into <19 years, 20–29 years, 30–39 years, 40–49 years, and 50–60 years. Conventional BMI cut off points were applied [underweight (BMI <18.5 kg/m2), normal weight (BMI >18.5 to <25.0 kg/m2), and overweight (BMI ≥25.0 kg/m2)]. Spirometry was conducted between 07:00 AM and 12:00 PM [Table 1].
|Table 1: Socio-demographic characteristics of study participants and control|
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Statistical Package for Social Sciences, version 19 (IBM SPSS Inc., Chicago, IL, USA) was used for statistical analysis. Descriptive statistics of respondents’ continuous variables was reported as mean ± SD while categorical variables was presented as frequencies and percentages. Chi-square analyses and independent t-tests were used to examine the bivariate association of means and percentages of variables (anthropometric measurements, socio-demographic parameter and ventilatory function indices) between participants and control. Partial correlation analyses were used to assess relationships between lung function and anthropometric variables. Level of significance was set at 0.05.
| Results|| |
The study included 200 participants (150 current cigarette smokers and 50 never smokers) who met the inclusion criteria set for the study. The age group ≤29 years and 30–39 years were the predominantly represented. Conversely, subject ≥50 years are least represented among both current cigarette smokers and non-cigarette smokers.
From [Table 2], majority of cigarette smokers had normal weight (69.3%) while majority of non-cigarette smokers were obese (58%). Obesity is common among study participants aged 30–39 (22 current cigarette smokers and 12 non-cigarette smokers).
Current cigarette smokers and non-cigarette smokers did not differ in means of age, height, weight, and BMI [Table 3].
|Table 3: Clinical parameters and ventilatory function indices of study participants and controls|
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Comparison of mean values of ventilatory function test indices showed all except FVC to be reduced in cigarette smokers compared non-cigarette smokers. From [Table 3], the mean FEV1/FVC of participants (75.60 ± 7.53) and control (82.48 ± 6.11) was statistically significant with P = 0.001.
There could be a significant positive correlation between anthropometric parameters (height and BMI) and ventilatory function indices. The correlation coefficient was most significant between height and FVC (r = 0.801) [Table 4].
|Table 4: Correlation matrix of anthropometric parameters and ventilatory function indices|
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| Discussion|| |
In the index study, we aimed to explore the relationship between anthropometric parameters and ventilatory function indices. Majority of the cigarette smokers are young from our study, and this is in tandem with results from previous studies.,, This observation may not be unconnected with early debut of cigarette smoking habit, heedless of its related ills.
The basic anthropometric parameters were similar among cigarette smokers and control in the current study. This finding may be attributed to the predominant large number of the young study participants and probably in the early phase of cigarette smoking habit. Our finding on anthropometric parameters contrasts with Anil et al., who reported a significant difference in the weight of cigarette smokers and non-smokers. In addition, the difference in sampling technique may have also contributed to the contrasting basic anthropometric findings in our study and that of Anil et al.
There was no significant difference in the BMI of study participants which concur with the study by Alkali et al. The low mean pack years in our study may explain the uniformity in BMI among cigarette smokers and non-smokers. In contrast, Finer and Flegal et al. reported lower BMI among cigarette smokers as compared with apparently healthy control which was attributed to the decrease in appetite and high-energy expenditure associated with nicotine use., Furthermore, without controlling for eating habits and physical activities among study participants, significant proportion of cigarette smokers had normal weight while the converse was observed among controls. This finding contradicts that by Alkali et al.
Ventilatory function test indices were observed to be lower among the cigarette smokers in comparison with control. Our finding is in keeping with that of Jaya et al., and the probable explanation is the effect of cigarette smoking on the airway through inflammation and remodeling.,, Furthermore, there were significant associations between anthropometric parameters and ventilatory function indices in our study. This association was consistently significant for height among both cigarette smokers and control which may be explained by the fact that this anthropometric parameter is an independent variable that determines ventilatory function test that is not subject to intra-individual variability.,A weak negative correlation was observed between BMI and some ventilatory function indices (FEV1, FVC, FEV1/FVC) among cigarette smokers and control. However, only the correlation of BMI with ventilatory function indices of control was statistically significant. The inverse relationship between weight gain and decline in indices of ventilatory function has been corroborated in earlier studies.,,,, This association has been attributed to airway obstruction and mechanical disadvantage of the diaphragm owing to regional deposition and accumulation of fat.
The cross-sectional nature of the current study does not confer it with the strength of establishing a causal relation between cigarette smoking and BMI changes. Furthermore, we have not adjusted for effect of physical activity and caloric intake among study participants which may confound the study results. However, the matching of participants in the index study and the diversity of participants could mitigate for confounders.
In conclusion, height is consistent in its association with ventilatory function indices among cigarette smokers and non-smokers. Furthermore, BMI did not significantly affect decline in ventilatory function indices among cigarette smokers although there is an inverse relationship between them. This is may be a reflection of the early metabolic effect of cigarette smoking.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Arnaud C, David F, Fred P, Jacques C. Consequences of smoking for body weight, body fat distribution, and insulin resistance. Am J Clin Nutr 2008;87:801-9.
Shadrach D, Daniel FM, Jill PP. Relationship between smoking and obesity: A cross-sectional study of 499,504 middle-aged adults in the UK general population. PLoS One 2015;10:e0123579.
World Health Organization. Obesity: Preventing and Managing the Global Epidemic: Report of a WHO Consultation. Geneva; 2002. Available from: www.who.int/topics/obesity/en
. [Last accessed on 2016 Jan 23].
Innocent IC, Abali C, Collins J, Kenneth AO, Miracle EI, Samson EI et al.
Prevalence of overweight and obesity in adult Nigerians − A systematic review. Diabetes Metab Syndr Obes 2013;6:43-7.
Alkali MB, Bilkisu M, Denue AB, Bandele EO. Correlation of BMI, and pulmonary function in Nigerian firefighters. Donnish J Med Med Sci 2015;2:67-71.
Chathuranga R, Prasanna G, Prasad K, Nalinda A, Sithira T, Praveen T. Relationship between body mass index (BMI) and body fat percentage, estimated by bioelectrical impedance, in a group of Sri Lankan adults: A cross sectional study. BMC Public Health 2013;13:797.
Madhur V, Meena R, Soumya SS, Navjot K, Ravi R. Correlation between the percentage of body fat and surrogate indices of obesity among adult population in rural block of Haryana. J Family Med Prim Care 2016;5:154-9.
Yue C, Donna R, Yvon FC, James D. Waist circumference is associated with pulmonary function in normal-weight, over-weight, and obese subjects. Am J Clin Nutr 2007;85:35-9.
Arkanshu A, Sanjay A. Relationship between certain pulmonary function tests and anthropometric measures in normal male M.B.B.S. students. Int J Health Inf Med Res 2014;1:21-4.
Finer N. Obesity. Clin Med 2003;3:23-7.
Jaykaran C, Tamoghna B. How to calculate sample size for different study designs in medical research. Indian J Psychol Med 2013;35:121-6.
American Thoracic Society. Lung function testing: Selection of reference values and interpretative strategies. Am Rev Respir Dis 1991;144:1202-18.
Hammad AQ, Jamil AS, Tahira KS, Fahmida AS, Fahira R, Anjum H. Spirometric screening of chronic obstructive pulmonary disease in smokers presenting to tertiary health care. J Med 2009;10:40-4.
Isah MD, Makusidi MA, Abbas A, Okpapi JU, Njoku CH, Abba AA. Spirometric evaluation of ventilatory function in adult male cigarette smokers in Sokoto metropolis. Niger Postgrad Med J 2017;24:1-7.
] [Full text]
Anil CM, Royce K, Akshaya KM, Karthikeyan S, Thomas VC. Association between smoking and body mass index among males aged 20 years and above: A study in rural Tamil Nadu, South India. South East Asia J Public Health 2014;4:53-8.
Flegal KM, Troiano RP, Pamuk ER, Kuczmarski RJ, Campbell SM. The influence of smoking cessation on the prevalence of overweight in the United States. N Engl J Med 1995;333:1165-70.
Lee J, Taneja V, Vassallo R. Cigarette smoking and inflammation cellular and molecular mechanisms. J Dent Res 2012;91:142-9.
Jaya MG, Kalyani S, Raveendran C. Evaluation of the effect of smoking on pulmonary function in young healthy adults. IJBR 2014;5:359-63.
Iyawe VI, Ebomoyi MI. Current developments in the physiology and management of asthma. Niger J Physiol Sci 2005;20:1929.
Oloyede IP, Ekrikpo UE, Ekanem EE. Normative values and anthropometric determinants of lung function indices in rural Nigerian children: A pilot survey. Niger J Paediatr 2013;40:406-11.
Mohammed J, Maiwada SA, Sumaila FG. Relationship between anthropometric variables and lung function parameters among primary school children. Ann Niger Med 2015;9:20-5.
Canoy D, Luben R, Welch A, Bingham S, Wareham N, Day N et al.
Abdominal obesity and respiratory function in men and women in the EPIC-Norfolk study, United Kingdom. Am J Epidemiol 2004;159:1140-9.
Fimognari FL, Pasqualetti P, Moro L, Franco A, Piccirillo G, Pastorelli R et al.
The association between metabolic syndrome and restrictive ventilatory dysfunction in older persons. J Gerontol A Biol Sci Med Sci 2007;62:760-5.
Beitollah A, Seyyedeh ZH, Akbar S, Khalil A. Influence of anthropometric measurements in lung function in patients with asthma. Int J Prev Med 2015;6:50.
Mar SA, Francisco ML, Gemma FM, Cristina JP, Estefania AL, Josep BG et al.
Adiposity markers and lung function in smokers: A cross-sectional study in a Mediterranean population. BMC Pulm Med 2016;16:178.
[Table 1], [Table 2], [Table 3], [Table 4]