|Year : 2018 | Volume
| Issue : 2 | Page : 133-136
Conicity index and a body shape index as predictor variable for cardiorespiratory fitness in healthy young adults
Himel Mondal1, Shaikat Mondal2, Chayan Baidya3
1 Department of Physiology, MKCG Medical College, Ganjam, Odisha, India
2 Department of Physiology, Medical College and Hospital, Kolkata, West Bengal, India
3 JB Roy State Ayurvedic Medical College, Kolkata, West Bengal, India
|Date of Web Publication||9-Apr-2018|
Department of Physiology, MKCG Medical College, Ganjam, Odisha
Source of Support: None, Conflict of Interest: None
Background: Central obesity has been established to be linked with increased cardiometabolic health risks. Waist circumference (WC), conicity index (CI), and A Body Shape Index (ABSI) are anthropometric proxy for central obesity. Maximal aerobic capacity (V̇O2max) provides an estimation of cardiorespiratory fitness of an individual. Decrease in V̇O2maxhas also been established to be associated with increased health risk. Aim: The aim of the study was to find out correlation between central obesity parameters and V̇O2max. Materials and Methods: A cross-sectional study was conducted with 154 young adults (male = 90 and female = 64) who were in daily exercise. WC, height, and weight were measured to calculate CI and ABSI according to formulae. V̇O2maxwas estimated by submaximal exercise test – 1.5 mile run test. Pearson's correlation coefficient was used to find out correlation between central obesity parameters and V̇O2max. Results: Mean age of male and female was 21.89 ± 3.65 years and 21.06 ± 2.92 years, respectively. Correlation coefficient between WC and V̇O2maxwas r = −0.61 (P < 0.001), ABSI and V̇O2maxwas r = −0.46 (P < 0.001), and CI and V̇O2maxwas r = −0.59 (P < 0.001). Conclusion: Central obesity anthropometric parameters were negatively associated with V̇O2max. WC showed higher negative correlation with V̇O2maxthan CI and ABSI. Hence, CI and ABSI are not better predictor variable in comparison with simple WC for V̇O2max. Further studies are needed to explore this association for general population.
Keywords: 1.5 mile run test, A Body Shape Index, conicity index, oxygen consumption, submaximal exercise
|How to cite this article:|
Mondal H, Mondal S, Baidya C. Conicity index and a body shape index as predictor variable for cardiorespiratory fitness in healthy young adults. CHRISMED J Health Res 2018;5:133-6
|How to cite this URL:|
Mondal H, Mondal S, Baidya C. Conicity index and a body shape index as predictor variable for cardiorespiratory fitness in healthy young adults. CHRISMED J Health Res [serial online] 2018 [cited 2020 Jul 8];5:133-6. Available from: http://www.cjhr.org/text.asp?2018/5/2/133/229592
| Introduction|| |
Central obesity rather than whole body obesity is being considered to have a greater association with metabolic health risks., Laboratory-based methods for measurement of central obesity involves higher cost, expensive instruments, and expert operator. However, for measurement of central obesity in clinical settings, simple anthropometric parameters may be used as a proxy of laboratory methods. Along with waist circumference (WC), conicity index (CI), and A Body Shape Index (ABSI) have been established to be associated with risk of cardiovascular diseases.,, These central obesity indices can be calculated from WC, weight, and height of the patients.
Maximal aerobic capacity (V̇O2max) of an individual is considered as cardiorespiratory fitness (CRF) and it can be measured by graded maximal exercise test with gas analysis. However, due to the involvement of exhaustive exercise and requirement of well-equipped laboratory, submaximal exercise performance is taken as reference for calculation of CRF in a person. V̇O2max can be calculated from the heart rate response obtained in different levels of exercise intensity during a submaximal exercise test. A lower level of V̇O2max has been established to be associated with increased cardiovascular disease risk.
With this background, the aim of this study was to find if any correlation exists between WC, CI, and ABSI with V̇O2max obtained from a submaximal exercise test.
| Materials and Methods|| |
After obtaining permission from Institutional Ethics Committee, this cross-sectional study was conducted during the time span from December 2016 to June 2017.
Sample and recruitment procedure
For minimum required sample size calculation, we used the correlation coefficient between WC and V̇O2max reported in a previously published literature. In that study, reported correlation coefficient between WC and V̇O2max in male was r = −0.745 and in female was r = −0.663. With these data, and α = 0.05 and β = 0.05, minimum sample size was calculated as male = 17 and female = 23. However, this sample size was considered as minimum sample size and it was decided to include more number of subjects according to available logistics. Inclusion criteria for the “convenience sample” were age above 18 years, having regular exercise, capabilities to jog at least 15 min, and provided written consent. Exclusion criteria were any acute or chronic illness or deformity, subjects with any addiction of tobacco, smoking, and alcoholism, and subjects with any chronic medication. Subjects were briefed about the aim of the study and only willing subjects were requested to fill the informed consent form. After providing consent, subjects were interviewed about the presence of any exclusion criteria in them. Presence of any one or more exclusion criteria in a subject was considered unfit for the study.
Age and anthropometric parameters recording
Age of the subjects was recorded as a discrete variable in completed years. Standing height was measured by portable stadiometer in centimeter to nearest 0.1 cm, while subject was on erect posture without shoes or socks. WC was measured in erect posture with light clothing at the end of normal expiration at the midpoint between lower costal margin and iliac crest with Fiberglass Measuring Tape Hi-Plastika 15 M (GK FML, Freemans Measurers, India) to nearest 0.1 cm. Weight was measured by digital weighing scale (Omron Body Composition Monitor HBF-701) with 0.1 kg sensitivity with light clothing and without any accessories.
Calculation of obesity indices
BMI was calculated according to Quetelet's formula:
CI was calculated from the formula:
ABSI was calculated from the formula:
Submaximal exercise protocol
For submaximal exercise protocol, fixed distance test was used. The 1.5 mile run test was conducted on an open ground with track marking for 1.5 mile distance. Subjects were briefed about the aim of the study and requested to finish the distance in possible shortest time. A warm-up for 2 min was practiced before the 1.5 mile run test to ensure aerobic energy utilization. Continuous verbal motivation was done wherever possible. Time required for completion of the track of 1.5 mile was recorded by a digital stopwatch. Then, the time is converted into minute for using it in calculation. V̇O2max was calculated by the formula: V̇O2max(mL/kg/min) = 3.5 + 483/1.5 mile run time in minutes. The procedure of submaximal exercise test is depicted in [Figure 1].
|Figure 1: Steps followed for maximal aerobic capacity estimation by 1.5 mile run submaximal exercise test (Formula for calculation: VO2max(mL/kg/min) =3.5 + 483/1.5 mile run time in minutes)|
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Data were entered in Spreadsheet and analyzed statistically in Microsoft Excel and GraphPad Prism version 6.01 (GraphPad Software, Inc., CA, USA). For all the analyses, chances of type I error was set at 0.05. Data were expressed in mean and standard deviation to compare the variables between male and female subjects by unpaired t-test. Anthropometric parameters and V̇O2max were taken as continuous variable, and the correlation between two continuous variables was determined by Pearson's correlation coefficient (r).
| Results|| |
A total of 154 subjects participated in the study where males were 90 (58.44%) and females were 64 (41.56%) in number. Age, central obesity parameters (namely, WC, ABSI, and CI), and V̇O2max in study sample according to sex is shown in [Table 1].
|Table 1: Age, central obesity parameters, and V̇O2max in study subjects expressed in mean and standard deviation|
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Pearson's correlation coefficient between V̇O2max and central obesity parameters is shown in [Table 2]. Scatterplot with trend line for relationship between WC and V̇O2max is shown in [Figure 2].
|Table 2: Correlation of maximal aerobic capacity with central obesity parameters tested by Pearson's correlation coefficient|
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|Figure 2: Relationship between waist circumference and VO2maxexpressed in a scatterplot with trend line (r = −0.61, P < 0.001)|
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| Discussion|| |
This study was conducted to find out correlation between indirectly measured central obesity parameters and predicted maximal aerobic capacity in young adult who was in regular exercise.
For measurement of central obesity, we used circumference-based measurement as it is readily available and can be measured in any settings with minimal instruments. WC has been established to be a better index of visceral adipose tissue, and an increase in visceral adipose tissue is associated with increased cardiovascular mortality. This study revealed that WC is negatively correlated with V̇O2max[Table 2] in subjects who are regularly exercising. Hence, an increase in central obesity may be an indicator of less endurance capacity. The person with higher WC would have less capability to run for a long distance. Study on physically active middle-aged population as well as on sedentary young adults also showed WC to be negatively correlated with V̇O2max in previous studies., Hence, exercise protocols should be aimed to reduce central obesity. This may help in the improvement of maximal aerobic capacity. However, the level of improvement in aerobic capacity along with decrease in central obesity was beyond the scope of this study. Further studies with a cohort may help to establish the level of improvement in V̇O2max with decrease in WC.
The advantage of CI for assessment of central obesity lays in the fact that it includes adjustment of WC for height and weight., ABSI is derived from WC, and it is independent of BMI., Hence, theoretically, these are considered better parameters for central obesity. From this study, we found a significant negative correlation between these two parameters and V̇O2max[Table 2]. However, WC showed stronger negative correlation with V̇O2max in comparison with CI and ABSI. If we compare the correlation coefficient with V̇O2max between ABSI and CI; CI showed higher negative correlation coefficient [Table 2]. Hence, applicability of CI as a determinant of poor CRF is better than ABSI.
WC can be measured by simple instrument, and it does not involve any calculation. However, for obtaining CI and ABSI, weight and height measurements and complex calculation are needed. Hence, WC is simply measured parameters which can be used to compare endurance capacity of individuals.
This study has several limitations. According to the available logistics for the study, we recruited sample from a narrow range of age. Further study with wide age range may provide accurate result for different age groups. CI and ABSI are indirectly measured and calculated indices of central obesity. These are not gold standard test for the measurement of central obesity.
| Conclusion|| |
CI and ABSI both are negatively correlated with V̇O2max. WC showed a higher negative correlation with V̇O2max than that of with CI and ABSI which suggests that WC is better predictor variable for V̇O2max. Hence, WC may be considered to be more informative for the status of CRF in young adults. Further studies with subjects of wide age range and different physical fitness level would provide us more generalized result.
We thank all the participants for their active participation in the study. We also thank the fitness trainers who helped a lot during recruitment of sample.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Després JP, Lemieux I, Bergeron J, Pibarot P, Mathieu P, Larose E, et al.
Abdominal obesity and the metabolic syndrome: Contribution to global cardiometabolic risk. Arterioscler Thromb Vasc Biol 2008;28:1039-49.
von Eyben FE, Mouritsen E, Holm J, Montvilas P, Dimcevski G, Suciu G, et al.
Intra-abdominal obesity and metabolic risk factors: A study of young adults. Int J Obes Relat Metab Disord 2003;27:941-9.
Shuster A, Patlas M, Pinthus JH, Mourtzakis M. The clinical importance of visceral adiposity: A critical review of methods for visceral adipose tissue analysis. Br J Radiol 2012;85:1-0.
Onat A, Avci GS, Barlan MM, Uyarel H, Uzunlar B, Sansoy V, et al.
Measures of abdominal obesity assessed for visceral adiposity and relation to coronary risk. Int J Obes Relat Metab Disord 2004;28:1018-25.
Motamed N, Perumal D, Zamani F, Ashrafi H, Haghjoo M, Saeedian FS, et al.
Conicity index and waist-to-hip ratio are superior obesity indices in predicting 10-year cardiovascular risk among men and women. Clin Cardiol 2015;38:527-34.
Krakauer NY, Krakauer JC. A new body shape index predicts mortality hazard independently of body mass index. PLoS One 2012;7:e39504.
Malara M, Kęska A, Tkaczyk J, Lutosławska G. Body shape index versus body mass index as correlates of health risk in young healthy sedentary men. J Transl Med 2015;13:75.
Beltz NM, Gibson AL, Janot JM, Kravitz L, Mermier CM, Dalleck LC, et al.
Graded exercise testing protocols for the determination of VO2max: Historical perspectives, progress, and future considerations. J Sports Med (Hindawi Publ Corp) 2016;2016:3968393.
Katch VL, McArdle WD, Katch FI. Measuring and evaluating human energy-generating capacities during exercise. In: Essentials of Exercise Physiology. 4th
ed. USA: Lippincott Williams & Wilkins; 2011. p. 229-32.
Fernström M, Fernberg U, Eliason G, Hurtig-Wennlöf A. Aerobic fitness is associated with low cardiovascular disease risk: The impact of lifestyle on early risk factors for atherosclerosis in young healthy Swedish individuals – The Lifestyle, Biomarker, and Atherosclerosis study. Vasc Health Risk Manag 2017;13:91-9.
Mondal H, Mishra SP. Correlation of waist circumference and waist-to-height ratio with maximal aerobic capacity in young adults. J Health Res Rev 2017;4:62-5. [Full text]
Mondal H, Mondal S. Sample size calculation to data analysis of a correlation study in Microsoft Excel®: A hands-on guide with example. Int J Clin Exp Physiol 2016;3:180-9. [Full text]
The International Society for the Advancement of Kinanthropometry. International Standards for Anthropometric Assessment. Australia: International Society for the Advancement of Kinanthropometry; 2011.
Pitanga FJ, Lessa I. Anthropometric indexes of obesity as an instrument of screening for high coronary risk in adults in the city of Salvador – Bahia. Arq Bras Cardiol 2005;85:26-31.
Bouchi R, Asakawa M, Ohara N, Nakano Y, Takeuchi T, Murakami M, et al.
Indirect measure of visceral adiposity 'A Body Shape Index' (ABSI) is associated with arterial stiffness in patients with type 2 diabetes. BMJ Open Diabetes Res Care 2016;4:e000188.
Kaminsky LA. Cardiorespiratory fitness: Estimation from field and submaximal exercise tests. In: ACSM's Health-Related Physical Fitness Assessment Manual. 3rd
ed. USA: Wolters Kluwer Health, Lippincott Williams & Wilkins; 2010. p. 110-37.
Heymsfield SB, Hu HH, Wang Z, Shen W, Jin Y. Measurement of total adiposity, regional fat depots, and ectopic fat. In: Bray GA, Bouchard C, editors. Handbook of Obesity Epidemiology, Etiology, and Physiopathology. 3rd
ed. Boca Raton: Taylor & Francis Group, LLC; 2014. p. 19-35.
Dagan SS, Segev S, Novikov I, Dankner R. Waist circumference vs. body mass index in association with cardiorespiratory fitness in healthy men and women: A cross sectional analysis of 403 subjects. Nutr J 2013;12:12.
Valdez R, Seidell JC, Ahn YI, Weiss KM. A new index of abdominal adiposity as an indicator of risk for cardiovascular disease. A cross-population study. Int J Obes Relat Metab Disord 1993;17:77-82.
Kim KS, Owen WL, Williams D, Adams-Campbell LL. A comparison between BMI and conicity index on predicting coronary heart disease: The Framingham heart study. Ann Epidemiol 2000;10:424-31.
Sowmya S, Thomas T, Bharathi AV, Sucharita S. A body shape index and heart rate variability in healthy Indians with low body mass index. J Nutr Metab 2014;2014:865313.
[Figure 1], [Figure 2]
[Table 1], [Table 2]