IJLSSR,VOLUME 3, ISSUE 1, JANUARY 2017 : 856-862

    
Research Article (Open Access)

Associations of Obesity Indices with Cardiorespiratory Fitness in Bengali School Going Boys in India

Supriya Kumar Misra1, Kunal Dutta2, Parimal Dua1, Chandradipa Ghosh3*
1Research Scholar, Department of Human Physiology and Community Health, Vidyasagar University, Midnapore, West Bengal, India
2Scientist- B, Department of Human Physiology and Community Health, Vidyasagar University, Midnapore, West Bengal, India
3Professor and Head, Department of Human Physiology and Community Health, Vidyasagar University, Midnapore, West Bengal, India

*Address for Correspondence: Dr. Chandradipa Ghosh, Professor and Head, Department of Human Physiology and Community Health, Vidyasagar University, Midnapore, West Bengal, India
Received: 15 November 2016/Revised: 14 December 2016/Accepted: 30 December 2016

ABSTRACT- This study determined the relationship between obesity parameters (Body Mass Index, Waist Hip Ratio, Waist Thigh Ratio and Body Fat Percentage) and cardio respiratory fitness in terms of physical fitness index (PFI) and also were compared the selected physiological parameters (resting pulse rate, respiratory rate and blood pressure) among three body weight categories of selected boys. The present study was carried out in 233 healthy school going Bengali boys aged 11 to <13 years from India. On the basis of BMI-age-boys Z-scores, boys were categorised in three subdivisions such Normal weight, Overweight and Obese. The Scheffe’s multiple comparison post hoc analyses showed (p<0.05) significant difference of selected physiological parameters in each pairs of categories. The lowest (5th) to highest (95th) percentiles values of PFI were higher in normal weight categories than those in over weight and obese categories. Anthropometric obesity parameters were found to have significant (p < 0.001) and negative correlation with physical fitness index (PFI). However, multiple regression analysis found that only body mass index and waist hip circumference (WHR) were independently and significantly associated with the physical fitness index (PFI). The present study reveals that higher values of BMI, body fat% and WHR may be responsible for lower score of PFI which indicates low cardiorespiratory fitness in Bengali overweight and obese children.
Key-Words- Obesity, BMI, WHR, PFI, Cardiorespiratory fitness, Boys

INTRODUCTION- Physical fitness index (PFI) is considered as an important and valuable parameter in the field of sports and exercise physiology and is very important aspect for an individual life. Body mass index (BMI), body fat% and waist to hip ratio (WHR) are useful tools for determining obesity. Health related physical fitness of children is dependent on lifestyle related factors such as daily physical activity levels.
It was believed that the low physical fitness level of an individual is associated with higher mortality rate [1]. Determination of Physical Fitness Index (PFI) is one of the important criteria to assess the cardiopulmonary efficiency of a subject. Physical fitness level of an individual depends on the amount of oxygen which can be transported by the body to working muscles, and the efficiency of muscles to use that oxygen [2]. Distribution of fat centrally, with increases waist circumference thought to reflect increases in visceral fat with age [3]. The relationship between obesity indices and physical fitness index are well documented in other populations by several previous studies [4-6] which show the importance of physical fitness index in obesity management in children. Another study on the subjects of Kolkata of West Bengal in India documented similar findings [7]. BMI, body fat% and waist to hip ratio, waist to thigh ratio have been used to evaluate health risks associated with overweight and obesity. The objectives of this study were to evaluate the relationship of PFI score with different anthropometric obesity parameters (i.e., BMI, body fat%, WHR and WTR) and comparison of PFI score among three body weight categories of boys aged 11 to < 13years in West Bengal.

MATERIALS AND METHODS-
The present study was carried-out in 233 healthy school going Bengali boys aged 11 to <13years. The subjects were drawn by simple random sampling from different urban private schools of mainly three districts (Bankura, Paschim Medinipur and Purba Medinipur) of West Bengal in India. On the basis of BMI- age-boys Z-scores (normal weight: -2SD > BMI Z score < + 1SD, overweight: BMI Z-score = +2SD, obese: BMI Z-score > +2SD), boys were categorised in three subdivisions such Normal weight, Overweight and Obese [8]. The age of the boys were determined from their date of birth as recorded in their school registered. Ethical approval and prior permission were obtained from the Institutional Ethical Committee before commencement of the study and the experiment was performed in accordance with the ethical standard of the committee. For this study, the parents of the participating boys and also head school were asked to give written approval for their boys to be involved in this research programme.

Measurement of obesity parameters-
Body mass index (kg.m-2)- Body mass index (BMI) was calculated as the body weight in kilogram divided by height in square meters (kg.m-2). For the purpose of identification of overweight and obesity of the boys the cut off values of BMI set by the World Health Organization [8] was used.

Measurement of circumferences (cm)- All the selected circumferences in the present study were measured according to the recommendation of WHO [9]. Waist circumference was measured midway between the lower rib margin and the iliac crest. Hip circumference was measured horizontally at the level of gluteal muscle (at maximum circumference). Thigh circumference was measured as the horizontal girth at the level of the gluteal fold on the right thigh.

Computation of Body fat percentage- The skinfold thickness were measured at the right side on the triceps and subscapula with the boys standing in the proper erect posture according to the methods proposed by Johnson & Nelson [10], using Holtain skinfold callipers. For the computation of body fat% of boys were done using triceps and subscapular equation that is developed by Slaughter et al. [11].The equation is as follows:

Body Fat % for boys = 783*(Triceps + Subscapular) _ 1.7

Determination of physiological parameters- Blood pressure was determined using a mercury sphygmomanometer as per the recommendations of American Heart Association [12]. The measurements were taken in a quiet room in the sitting posture with the arm resting on the table. The average of three consecutive readings was taken as the blood pressure of the child. Resting heart rate was measured after a complete rest of 3 minutes by taking the radial pulse. Three successive readings were taken in the resting state for 60 seconds each with an interval of one minute while the person was sitting. Resting respiratory rate was determined by the method mentioned by the William et al. [13].

Physical fitness index (PFI)- PFI was determined by Modified Harvard Step Test (HST – III). This test was done according to the method developed by Brouha & Ball [14], applicable to elimentary school children. The method is as follows:
Every boy studied was advised to step up on the modified Harvard steps on 14 inches height (bench) once in every two seconds (i.e. 30 times per minute) for 3 minutes, a total of 90 steps. Post exercise recovery pulse was recorded as:
a) Pulse rate 1 – 2 minutes after exercise
b) Pulse rate 2 – 3 minutes after exercise
c) Pulse rate 3 – 4 minutes after exercise

PFI = [Duration of exercise in seconds X 100] / 2×(Recovery pulse rate 1st + 2nd + 3rd Minutes)

STATISTICAL ANALYSIS- All the values of anthropometric and physiological variables were expressed as Mean ± SD (standard deviation). Analysis of variance (ANOVA) followed by Scheffe’s multiple comparisons test was performed to find out the mean difference of different anthropometric and physiological variable of different categorised. In each cases significant level were chosen at 0.05 levels. Pearson product moment correlation coefficient (r) was used to examine the co-relationship of anthropometric obesity indices with the physical fitness index. Multiple regressions were used to study the association of anthropometric obesity marker (ie, BMI, body fat percentage, WHR and WTR) with physical fitness index (PFI). The analyses were performed using the Statistical Package for Social Sciences (SPSS, version 20.0; SPSS Inc., Chicago, Illinois, USA), and the level of significance was set to p<0.05.

RESULTS AND DISCUSSION
Comparison of selected anthropometric obesity parameters among three body weight categories- Comparison of selected anthropometric obesity parameters among three body weight categories of boys are presented in Table 1. One way ANOVA was performed to make an overall comparison of the selected anthropometric obesity parameters among three body weight categories. Further, Scheffe’s multiple comparison tests were performed to identify significant difference in each pair of categories. It is observed from Table 1that there existed no significant difference in height among three body weight categories. On the other hand, weight, BMI, WHR, and body fat% differed significantly (p<0.001) among three body weight categories. Moreover, in post hoc multiple comparison tests all pairs of body weight categories showed significant difference (p<0.01) among three body weight categories.

Table 1. Comparison of selected anthropometric obesity parameters among three body weight categories of boys (Normal weight boys = 125, Overweight boys = 68, Obese boys = 40)
Categories Height (cm) Weight (kg.) BMI (kg.m-2) WHR WTR Body fat%
Normal weight (a) 147.34 ± 3.31 36.08 ± 2.75 16.59 ± 0.79 0.858 ± 0.026 1.549 ± 0.080 14.13 ± 2.48
Overweight (b) 146.85 ± 3.23 46 .93 ±3.57 21.72 ± 0.90 0.955 ± 0.024 1.647 ± 0.059 21.83 ± 0.87
obese (c) 147.01 ± 3.01 53.69 ± 5.59 24.78 ± 1.69 0.980 ± 0.022 1.753 ± 0.063 24.97 ± 1.66
Level of significance ns ***(ab)(ac)(bc) ***(ab)(ac)(bc) ***(ab)(ac)(bc) **(ab)(ac)(bc) ***(ab)(ac)(bc)
F values 0.18 437.58 1177.29 528.13 151.57 696.34
Note: Values are Mean ± SD
One way ANOVA (expressed by F value and level of significance) was performed to show the overall differences of the selected anthropometric obesity parameters among three body weight categories in 11 - < 13 years age group (** p < 0.01, *** p < 0.001, ns = not significant). Sceffe’s multiple comparison tests were performed in every pair of three body weight categories a, b and c, where (ab) indicates ‘a’ significantly (p < 0.05) differed from ‘b’, (ac) indicates ‘a’ significantly (p < 0.05) differed from ‘c’, (bc) indicates ‘b’ significantly (p < 0.05) differed from ‘c’. BMI = body mass index, WHR = waist to hip ratio, WTR = waist to thigh ratio.


Comparison of selected physiological parameters among three body weight categories Comparison of selected physiological parameters of three body weight categories has been presented in Table 2. The results from the Table 2 showa significant variation (p<0.01) of PFI and SBP among three body weight categories. The Scheffe’s multiple comparisons post hoc analysis showed (p<0.05) significant difference of selected physiological parameters in each pairs of categories. The mean values of SBP, DBP, pulse rate and respiratory rate significantly higher in obese boys than in normal weight boys. On the other hand, mean values of PFI significantly (p<0.01) higher in normal weight boys than in overweight and obese boys. Earlier, Indian studies have also found PFI score of normal weight boys to be higher than in over weight and obese boys [15].
Blood pressure and adiposity in children and adolescents were assessed by Paradis et al. [16], and showed that resting heart (RHT) rate was increased, which suggests some degree of increased sympathetic activity, body mass index (BMI) was consistently associated with increase in SBP and DBP in all age-gender groups. The mean resting pulse rate was significantly higher in obese boys than in normal weight and overweight categories due to activation of the sympathetic nervous system occurs early in the course of obesity and the autonomic nervous system is an important contributor to the regulation of both the cardiovascular system and energy expenditure [17-18].
On the other hand, the probable reason of high respiratory rate in obese boys due to the increased adiposity around ribs, diaphragm and abdomen leading to limited movement of ribs, decreased total thoracic and pulmonary volume causes reduction in chest wall compliance and preventing full excursion of the diaphragm [19-20].

Table 2. Comparison of selected physiological parameters among three body weight categories of boys (Normal weight boys = 125, Overweight boys = 68, Obese boys = 40)
Categories PFI score Resting SBP (mmHg) Resting DBP (mmHg) Resting pulse rate (bpm) Resting respiratory rate (cpm)
Normal weight (a) 50.61 ± 8.06 104.02 ± 7.32 62.07 ± 7.18 86.68 ± 15.39 18.29 ± 3.46
Overweight (b) 40.58 ± 5.49 110.45 ± 6.64 66.30 ± 7.82 90.52 ± 15.41 19.01 ± 3.50
Obese (c) 36.87 ± 3.32 114.42 ± 9.24 72.45 ± 8.60 93.9 ± 14.58 20.35 ± 3.97
Level of significance **(ab)(ac) (bc) **(ab)(ac) (bc) *(ab)(ac) (bc) *(ab)(ac) (bc) *(ab)(ac) (bc)
F values 86.01 37.14 29.25 3.83 5.84
Note: Values are Mean ± SD
One way ANOVA (expressed by F value and level of significance) was performed to show the overall differences of the selected physiological parameters among three body weight categories in 11 - < 13 years age group (* p < 0.05, ** p < 0.01, ns = not significant). Sceffe’s multiple comparison tests were performed in every pair of three body weight categories a, b and c, where (ab) indicates ‘a’ significantly (p < 0.05) differed from ‘b’, (ac) indicates ‘a’ significantly (p < 0.05) differed from ‘c’, (bc) indicates ‘b’ significantly (p < 0.05) differed from ‘c’. SBP = systolic blood pressure, DBP = diastolic blood pressure, PFI = physical fitness index.


Range of PFI score among three body weight categories- Table 3 shows that the mean PFI of normal weight categories was 50.61 (range 38.29 to 64.74). On the other hand, mean PFI of overweight categories was 40.58 (range 34 to 58.44). In contrary, mean PFI of obese categories was 36.87 (range 32.49 to 42.58).

Table 3. Mean, standard deviation (SD), median and range of PFI scores of three body weights categories
Categories Parameter Mean SD Median Minimum Maximum
Normal weight
PFI
50.61 8.06 50.27 38.29 64.74
Overweight 40.58 5.49 39.48 34.0 58.44
Obese 36.87 3.32 36.66 32.49 42.58

Comparison of percentile values of PFI score among three body weight categories- Comparison of 5th, 10th, 25th, 50th, 75th, 90th and 95th percentiles of PFI scores among three body weight categories are presented in Table 4. It is observed from the Table 4 that the 5th, 10th, 25th, 75th, 90th and 95th percentile values of PFI were higher in normal weight categories than in over weight and obese categories. In contrary, the lowest (5th) to highest (95th) percentiles values of PFI were higher in overweight categories than in obese categories.

Table 4. Comparison of selected percentiles values of PFI among three body weight categories
Categories Mean SD
Percentile
5th 10th 25th 50th 75th 90th 95th
Normal weight 50.61 8.06 40 40.54 42.85 50.27 55.90 62.5 63.38
Overweight 40.58 5.49 34.61 35.15 36.29 39.48 43.17 47.61 52.63
Obese 36.87 3.32 32.66 32.96 33.51 36.66 39.73 41.66 42.35

Determination of association BMI and body fat% with physical fitness index (PFI)- Pearson’s product-moment correlation coefficients of BMI and body fat% with physical fitness index (PFI) were presented in Table 5. Correlation analysis showed that BMI had significant (p<0.001) and negative correlation with physical fitness index (PFI). In contrary, result also showed (Table 5) that body fat% had significant negative correlation (p<0.001) with physical fitness index (PFI). The findings of the present research confirmed the finding of these earlier studies in the present Bengali children where PFI was significantly and negatively correlated with BMI and body fat percentage [21-22]. The observed negative association between body fat percent and physical fitness index (PFI) score concur with previous studies where sophisticated techniques to measure body composition were used [23-26]. On the other hand, Gutin et al. [24] assessed body fat by dual energy x-ray absorptiometry (DXA) in youth and showed a negative association between body fat% and cardiorespiratory fitness in terms of PFI.

Table 5. Pearson’s product moment correlation coefficient of BMI and % of Fat with PFI (No of cases: 233)
BMI(kg/m2) Body fat%
Variable r values 95% CI Level of significance (p) r values 95% CI Level of significance (p)
PFI - 0.632 - 0.704, - 0.548 < 0.001 - 0.599 - 0.675 , - 0.51 < 0.001
Note: 2-tailed of significance was used, ns = not significance, 95 % CI = 95% confidence intervals, BMI = body mass index, PFI = physical fitness index

Determination of association of WHR and body WTR with physical fitness index (PFI)- Pearson’s product-moment correlation coefficients of WHR and WTR with physical fitness index (PFI) were presented in Table 6. Pearson’s product-moment correlation coefficient analysis demonstrated that WHR had significant (p<0.001) and negative correlation with physical fitness index. On the other hand, result (Table 6) also showed that WTR had significant (p<0.001) and negative correlation with physical fitness index (PFI). Our present finding also corroborate with the findings of Ortega et al. [27-28], they observed that physical fitness index was negatively associated with waist circumference in Swedish and Spanish youth. On the other hand, Winsley et al. [23] showed that visceral obesity assessed by MRI was negatively associated with cardiorespiratory fitness in children.

Table 6. Pearson’s product moment correlation coefficient of WHR and WTR with PFI (no of cases: 233)
WHR WTR
Variable r values 95% CI Level of significance (p) r values 95% CI Level of significance (p)
PFI - 0.621 - 0.694, - 0.535 < 0.001 - 0.411 - 0.512, - 0.298 < 0.001
Note: 2-tailed of significance was used, ns = not significance, 95 % CI = 95% confidence intervals, WHR = waist to hip ratio, WTR = waist to thigh ratio

Multiple linear regression analysis- Multiple linear regression analysis was performed to see whether there were independent relationships of anthropometric obesity parameters (i.e., BMI, body fat%, WHR and WTR) with PFI and standard partial regression coefficients (ß) are presented in support of that (Table 7). Multiple regression analysis demonstrated that waist to hip ratio (WHR) had independent significant (p<0.001) negative impact on physical fitness index (PFI) when body mass index (BMI), body fat % and waist to thigh ratio were controlled.

Table 7. In multiple regression analysis PFI is dependent variable and BMI, body fat%, WHR and WTR are independent variables
Physical fitness index (PFI) is dependent variable
Independent Variable Constant (A) Unstandarzied coefficient Standardized coefficient
Beta (ß)
t Level of significance (p) F Level of significance (p) R2
B Std. Error
BMI 98.85 -1.32 0.48 - 0.53 -2.79 p<0.006 43.96 p<0.001 0.43
Body fat% 0.09 0.23 0.13 0.75 ns
WHR -57.52 15.70 - 0.38 -3.66 p<0.001
WTR -13.25 6.30 0.15 -2.10 0.036
Note: BMI = body mass index, WHR = waist hip ratio, WTR = waist to thigh ratio

Hence, it appears from the present study that waist to hip ratio (WHR) is partly good detector for variability of physical fitness index (PFI) in these children. Our findings well support with previous finding in Bengali children and adolescent by Mukherjee and Dhara [21]. It is also observed from the Table 7 that even after controlling the effects of body fat %, waist to hip ratio (WHR) and waist to thigh ratio (WTR), BMI had independent significant (p<0.006) and negative association with the physical fitness index (PFI) , this finding similar as the earlier finding of Das and Dhundasi [29]. Increased central adiposity may lower utilization of oxygen per unit of body mass or respiratory trouble may occur due to higher amount fat deposition in the abdomen and chest cavity. This may restrict proper functioning of heart especially during physical activities or exercises [30]. Thus on the basis of the present study it may be said that higher values of BMI, body fat percent and WHR may be responsible for lower score of PFI. Increased cardio respiratory fitness had been found to lower BMI, body fat% and WHR [30].In light of these earlier studies and results of the present study it may be said that obesity indices has a negative effect on cardio-respiratory fitness in terms of physical fitness index (PFI).

CONCLUSION- The mean value of physical fitness index (PFI) was found to be higher in normal weight boys than in overweight and obese boys. Resting heart rate, respiratory rate and blood pressure were higher in overweight and obese children compared to normal children. The findings documented herein found significant negative association of obesity parameters (i.e., BMI, Body Fat%, WHR and WTR) with PFI. This indicates a lower level of cardiovascular efficiency in overweight and obese boys compared to normal weight boys. The results of this study emphasizes the need for early identification of the risk factors leading to exces sive BMI, body fat% and initiation of preventive measures in order to prevent the deterioration of cardiovascular performance in 11 to <13 years old school going Bengali boys.

ACKNOWLEDGMENT- The authors would like to thank all boys, their parents, the teachers and also non teaching staff of the participating schools for their kind helps in collecting the data.

REFERENCES
  1. Takken T, Vander NJ, Kuis W, and Helders PJM. Physical activity and health related physical fitness in children with juvenile idiopathicarthritis, Ann Rheum Dis, 2003; 62:885-889.
  2. Choudhuri D, Choudhuri S, and Kulkarni S. Physical fitness: A comparive study between students of residential (Sainik) and non-residential schools children aged 12- 14 years. Indian J Physiol Pharmacol, 2002; 46(3): 328-332.
  3. Harris TB. Invited Commentary: Body Composition in Studies of Aging: New Opportunities to Better Understand Health Risks Associated with Weight. Am J Epidemiol, 2002; 156:122-124.
  4. Berkey CS, Rockett HRH, Gillman MW, and Colditz GA. One year changes in activity and in inactivity among 10- to 15-year-old boys and girls: relationship to change in body mass index. Pediatrics, 2003; 111:836-43.
  5. Mayo M J, Grantham JR, and Balasekaran G. Exercise Induced Weight Loss Preferentially Reduces Abdominal Fat. Med Sci Sports Exerc, 2003; 35(2):207-13.
  6. Shaikh WA, Patel MC, and Singh SK. Association of physical activity and physical fitness with blood pressure profile in Gujarati Indian adolescents. Indian J Physiol Pharmacol, 2011; 55 (4):322-328.
  7. Mukhopadhyay A, Bhadra M, and Bose K. Physical exercise, body mass index, subcutaneous adiposity and body composition among Bengalee boys aged 10-17 years of Kolkata, India. AnthropolAnz, 2005; 63(1):93-101.
  8. WHO Child Growth Standards: Length/height-for-age, Weight-for-age, Weight-for-length, Weight-for height and Body Mass Index-for-Age: Methods and Development. World Health Organization: Geneva, ActaPaediatr 2007; 450: 76-85.
  9. World Health Organization Expert Commitee. Measuring obesity- classification and description of anthropometric data. EUR/ICP/NUT 125. Copenhagen, Regional office for Europe: World Health Organization, 1989.
  10. Johnson BL and Nelson JK. Practical measurements for evaluation in physical education, London; Macmillan Publishing Co: 1996
  11. Slaughter MH, Lahman TG, and Boileau RA. Skinfold equation for estimation of body fat in children and youth. Human Biol, 1988; 60:709-723.
  12. Kirkendall WM, Feinleib M, Freis ED, Mark AL. American Heart Association. Recommendations for human blood pressure determination by sphygmomanometer. Hypertension, 1981; 3: 509-519.
  13. William D, Mc Ardle, Frank IK, and Victor LK. Exercise Physiology: Energy, Nutrition and Human Physiology, Lippincott Williams & Wilkins: 2006: pp. 270.
  14. Brouha L and Ball MV. Canadian Red Cross Society’s School Meal Study. Toronto, Canada; University of Toronto Press: 1952.
  15. Chatterjee S, Catterjee P, and Bandyopadhyay A. Cardiorespiratory fitness of obese boys. Indian journal of Physiology and Pharmacology, 2005; 49: 1-5.
  16. Paradis G, Lambert M, O'Loughlin J, Lavallee C, Aubin J, and Delvin E. Blood pressure and adiposity in children and adolescents. Circulation, 2004; 110:1832-3.
  17. Benjamin EJ, and Levy D. Why is left ventricular hypertrophy so predictive of morbidity and mortality? Am J Med Sci, 1999; 317:168-175.
  18. Scherrer U, Randin D, Tappy L, Vollenweider P, Jequier E, and Nicod P. Body fat and sympathetic nerve activity in healthy subjects. Circulation, 1994; 89: 2634-2640.
  19. Kumar D. Spirometric evaluation of lung functions in obese and non obese subjects. Journal of Advance Researches in Biological Sciences, 2013; 5(3):229-233
  20. Behera AA, Behera BB, Dash S, and Mishra S. Effect of body mass index on gender difference in lung functions in Indian population. International Journal of Clinical and Experimental Physiology 2014;1:229-31.
  21. Mukherjee R, and Dhara PC. Effects of Daily Life Physical Activity on Obesity Indices, Cardiorespiratory Fitness and Association of the Latter Two with Academic Performance in Bengali Adolescents of India. American Journal of Sports Science and Medicine, 2014; 2(1): 48-55.
  22. Banerjee I, Ghia N, Bandopadhyay S, Sayed HN, and Mukherjee D. Body mass index in Bengali adolescents, Indian Pediatr, 2005, 42:262-267.
  23. Winsley RJ, Armstrong N, and Middlebrooke AR. Aerobic fitness and visceral adipose tissue in children. ActaPaediatr, 2006; 95:1435–1440.
  24. Gutin B, Yin Z, and Humphries MC. Relations of fatness and fitness to fasting insulin in black and white adolescents. J Pediatr, 2004; 145:737–43.
  25. Lee SJ and Arslanian SA. Cardiorespiratory fitness and abdominal adiposity in youth. Eur J ClinNutr, 2007; 61:561–5.
  26. Wong SL, Katzmarzyk P and Nichaman MZ. Cardiorespiratory fitness is associated with lower abdominal fat independent of body mass index. Med Sci Sports Exerc, 2004; 36:286–91.
  27. Ortega FB, Ruiz JR, and Hurtig-Wennlöf A. Cardiovascular fi tness modifies the associations between physical activity and abdominal adiposity in children and adolescents. The European Youth Heart Study. Br J Sports Med, 2010; 44:256–62.
  28. Ortega FB, Tresaco B, and Ruiz JR. AVENA Study Group: Cardiorespiratory fitness and sedentary activities are associated with adiposity in adolescents. Obesity (Silver Spring), 2007; 15:1589–9.
  29. Das KK, Dhundasi SA. Physical Fitness: A longitudinal study among Muslim children of Bijapur (Karnataka). Indian J PhysiolPharmacal, 2001; 45(4) in press.
  30. Bandyopadhya A. Cardiorespiratory fitness in obese girls. Indian J PhysiolPharmacol, 2012; 56(4): 393-395.
       
International Journal of Life-Sciences Scientific Research (IJLSSR) Open Access Policy
Authors/Contributors are responsible for originality, contents, correct references, and ethical issues.
IJLSSR publishes all articles under Creative Commons Attribution- Non-Commercial 4.0 International License (CC BY-NC).
https://creativecommons.org/licenses/by-nc/4.0/legalcode
      
How to cite this article:
Misra SK, Dutta K, Dua P, Ghosh C: Associations of Obesity Indices with Cardiorespiratory Fitness in Bengali School Going Boys in India. Int. J. Life. Sci. Scienti. Res., 2017; 3(1): 856-862. DOI:10.21276/ijlssr.2017.3.1.18
Source of Financial Support: Nil, Conflict of interest: Nil