|Year : 2017 | Volume
| Issue : 2 | Page : 82-85
Correlation of anthropometric indices with rate pressure product in healthy young adults
Sunil Kumar Jena1, Kanhu Charan Purohit1, Biswabhusan Mohanty2
1 Department of Physiology, Veer Surendra Sai Institute of Medical Sciences and Researches, Burla, Sambalpur, Odisha, India
2 Department of Anatomy, IMS and SUM Hospital, Bhubaneswar, Odisha, India
|Date of Web Publication||7-Aug-2017|
Sunil Kumar Jena
Department of Physiology, Veer Surendra Sai Institute of Medical Sciences and Researches, Burla, Sambalpur - 768 017, Odisha
Source of Support: None, Conflict of Interest: None
Background: Generalized and abdominal obesity is associated with increased incidence of adverse cardiovascular events. Rate pressure product (RPP) is an indicator of myocardial oxygen consumption, and higher value of RPP indicates myocardial work stress or cardiovascular risk. Thus, RPP can be correlated with anthropometric indices such as body mass index (BMI), waist circumference (WC), and waist–hip ratio (WHR) to evaluate the risk of adiposity on myocardial work stress. Materials and Methods: In this study, 104 young male college students were recruited as subjects. Height, weight, WC, and hip circumference were measured whereas BMI and WHR were derived by specific formula. Heart rate (HR) and blood pressure (BP) were recorded after allowing for 10 min rest and RPP was derived by specific formula. Subjects were distributed into different groups considering BMI, WC, and WHR. The analysis of parameters, i.e., systolic BP, HR, and RPP was done by one-way ANOVA, unpaired t-test, and Pearson correlation. Results: The major findings of this study suggested that obese and overweight subject RPP was more than normal participants. The subjects of WC >90 cm had higher RPP than the subjects of WC ≤90 cm. The subjects of WHR ≥0.90 had higher RPP than WHR <0.90. There was a significant positive correlation (P < 0.05) between RPP and anthropometric indices, i.e., BMI, WC, and WHR. Conclusion: Vital parameters of adiposity or obesity such as BMI, WC, and WHR may be used to evaluate the risk of myocardial work stress or cardiovascular events in correlation with RPP.
Keywords: Adiposity, myocardial work stress, rate pressure product
|How to cite this article:|
Jena SK, Purohit KC, Mohanty B. Correlation of anthropometric indices with rate pressure product in healthy young adults. Muller J Med Sci Res 2017;8:82-5
|How to cite this URL:|
Jena SK, Purohit KC, Mohanty B. Correlation of anthropometric indices with rate pressure product in healthy young adults. Muller J Med Sci Res [serial online] 2017 [cited 2018 Oct 19];8:82-5. Available from: http://www.mjmsr.net/text.asp?2017/8/2/82/212407
| Introduction|| |
Anthropometric indices such as weight, height, circumferences, ratios, and body mass index (BMI) are used in clinical settings and research work. These indices estimate the degree of adiposity or obesity and its relation to different diseases., Obesity nowadays is considered as a major health hazard worldwide. Overweight and obesity are associated with a number of diseases such as hypertension, cardiovascular diseases (CVDs), diabetes, raised cholesterol level, arthritis, anesthesia risk, respiratory problem, breast cancer, menstrual abnormalities, ovarian dysfunction, and many more. The prevalence of obesity is increasing in both developed and developing countries nowadays. Genetic predisposition, sedentary lifestyle, intake of inappropriate caloric rich junk food and stress has made the environment favorable for human being to be overweight and obese. It generates as well as potentiates a large number of health problems, either independently or in association with other factors. Obesity or adiposity is an independent risk factor for CVDs. There is an increased prevalence of heart failure in obesity. “Obesity cardiomyopathy” is the important clinical entity having left ventricular remodeling, reduced efficiency, and left ventricular diastolic dysfunction. Rate pressure product (RPP) is a product of heart rate (HR), and systolic blood pressure (SBP) is a major determinant of myocardial oxygen consumption (MVO2). It is an indirect and easy noninvasive method of measuring MVO2. RPP reflects the internal myocardial work performed by the beating heart whereas the performance of the external myocardial work is represented by the stages of exercise., Heart, being a muscular organ, its regular functioning needs steady supply of oxygen and nutrients; if these supply are deficient, there is all chances of heart failure to occur. Increased RPP, an index of myocardial work stress, has been documented to be an indicator of cardiovascular risk. This study was proposed to evaluate the correlation between various anthropometric indices with RPP so that myocardial work stress or myocardial workload can be correlated with adiposity or obesity.
| Materials and Methods|| |
This cross-sectional study was conducted in the Department of Physiology, in a Medical College of Odisha, after getting approval by Institutional Ethical Committee and Institutional Review Board of the institution. This study was completed between January 2016 and December 2016. In this study, researchers hypothesized to evaluate the correlation between anthropometric indices, i.e., BMI, waist circumference (WC), and waist–hip ratio (WHR) with RPP. For this study, 104 young male adults of age between 20 and 25 years were selected from various local educational institutions. For a selection of subjects, face-to-face interview and general examination were done. Face-to-face examination included name, age, history of any systemic disease, current medication, smoking, and alcohol history. Both face-to-face interview and general examination were done by the researchers. Subjects selected for this study were all apparently healthy young adults. Those were suffering from any CVD, respiratory disease, endocrine disease, renal disease, neural disease, hypertension, family history of diabetes mellitus, smokers, alcoholics, and on current medication were excluded from the study. After selection of subjects, they were explained properly about the purpose and output of the study. An informed written consent was taken from each subject. Recording of height, weight, WC, hip circumference (HC), HR and BP was done by standard methods. The weight of the subjects was recorded by a standard analogue weighing machine (VIRGO Model No 9811 B). Height, WC, and HC were measured by a standard measuring tape. Body weight was measured without shoes in light clothing to the nearest 0.5 kg, with the subject standing motionless on an analog weighing machine in such a way that body weight should be distributed equally on each leg. Weighing machine was standardized every day with a weight of 20 kg. Height was measured without shoes with the subject standing in erect posture, shoulders in relaxed position and arms hanging freely using a measuring tape. WC was measured as per the recommendation of WHO STEPS for surveillance (2008) protocol at the approximate midpoint between the lower margin of last palpable rib and the top of the iliac crest by a measuring tape. HC was measured around the widest portion of the buttocks, with the measuring tape parallel to the floor. For measurement of waist and HC, the subjects were instructed to stand with close feet, arms at the side and body weight evenly distributed across the feet, and with light clothing. WC and HC measurement was nearest to 0.1 cm. BMI was calculated as weight in kg divided by height in m2 (BMI = kg/m2). WHR was calculated as waist WC divided by HC (WHR = WC/HC).
Recording of HR and BP was done between 8 and 9 a.m. after 5–10 min rest. HR was calculated by palpating radial pulsation for 1 min, thrice at an interval of 1 min and the average of three was taken the average HR. BP was recorded by auscultatory method using Elkometer sphygmomanometer. Recording of BP was done in the right arm sitting position. RPP was calculated by following formula.
RPP = (SBP × HR) × 10−2
For analysis, the data subjects were classified into different groups using anthropometric indices such as BMI, WC, and WHR. On the basis of BMI, subjects were classified into 3 groups, i.e., normal (BMI = 18.5–24.99 kg/m2), overweight (BMI = 25–29.99 kg/m2), and obese (BMI >30 kg/m2). On the basis of WC, subjects were classified into two groups, i.e., WC ≤90 cm and WC >90 cm (International Diabetes Federation cut-off points for South Asians). On the basis of WHR, subjects were classified into two groups, i.e., WHR <0.90 and WHR ≥0.90 (WHO cutoff points).
The analysis of data was done by statistical software SPSS (Statistical Package for the Social Sciences, IBM Corporation, Armonk, New York, USA) version 16. Various statistical tests implemented were one-way ANOVA test, unpaired t-test, and Pearson correlation. P < 0.05 was considered to be statistically significant. Generation of tables and graphs was done by Microsoft Word and Excel.
| Results|| |
[Table 1] depicts the effect of BMI on RPP, SBP, and HR. Data analysis was done by one-way ANOVA. There was a significant difference in RPP (P = 0.000) between different group of subjects. Overweight and obese subjects had higher RPP than normal participants. Post hoc analysis suggested that the significant variation was found between obese and normal, obese and overweight subjects. There was a significant difference in SBP (P = 0.000) between different group of subjects. Obese subjects had higher SBP than normal participants, but overweight subjects had lower SBP than normal subjects. Post hoc analysis suggested that the significant variation was found between obese and normal and overweight and obese subjects. There was a significant difference in HR (P = 0.010) between different group of subjects. Overweight and obese subjects had higher HR than normal participants. Post hoc analysis suggested that the significant variation was found between obese and normal participants.
|Table 1: Comparison of hemodynamic variables between normal, overweight and obese subjects|
Click here to view
[Table 2] depicts the effect of WC on RPP, SBP, and HR. Data analysis was done by unpaired t-test. RPP of subjects WC >90 cm was significantly (P = 0.025) more than the WC ≤90 cm. SBP of subjects WC >90 cm was significantly (P = 0.040) more than the WC ≤90 cm. HR of subjects WC >90 cm was significantly (P = 0.034) more than the WC ≤90 cm.
|Table 2: Comparison of hemodynamic variables based on waist circumference|
Click here to view
[Table 3] depicts the effect of WHR on RPP, SBP, and DBP. Data analysis was done by unpaired t-test. RPP of subjects WHR ≥0.90 was significantly (P = 0.001) more than the WHR <0.90. SBP of subjects WHR ≥0.90 was significantly (P = 0.009) more than the WHR <0.90. HR of subjects WHR ≥0.90 was significantly (P = 0.000) more than the WHR <0.90.
[Table 4] depicts the correlation of RPP with anthropometric indices, i.e., BMI, WC, and WHR. Data analysis was done by Pearson correlation. Significant positive correlation (P = 0.000) was found between RPP and anthropometric indices.
|Table 4: Correlation between rate pressure product and hemodynamic variables|
Click here to view
| Discussion|| |
This prospective study was done in young healthy adults to establish the relationship between anthropometric indices and RPP. Age and sex variation was excluded by selecting subjects of narrow range between 20 and 25 years, and all were male. The major findings of this study suggested that obese subjects SBP, HR, and RPP were more than normal and overweight subjects. The subjects of WC >90 cm had higher SBP, HR, and RPP than the subjects of WC ≤90 cm. The subjects of WHR ≥0.90 had higher SBP, HR, and RPP than WHR <0.90. There was a significant positive correlation (P < 0.05) between RPP and anthropometric indices, i.e., BMI, WC, and WHR.
The understanding of the development of overweight and obesity is incomplete; however, it may be due to a no of factors such as social, behavioral, cultural, physiological, metabolic, and genetic factors. Several studies proposed; both generalized and abdominal obesity are associated with increased risk of morbidity and mortality. The main cause of obesity-related deaths is CVD, for which abdominal obesity is a predisposing factor. BMI is an indicator which measures body size and composition; therefore, diagnose underweight, overweight, and obese. However, there are several alternative measures that reflect abdominal adiposity, such as WC, WHR, and waist–height ratio, have been suggested as being superior to BMI in predicting CVD risk. This study suggested that in overweight, obese as well as subjects of abdominal obesity, hemodynamic variables such as SBP, HR, and RPP increased may be due to increased sympathetic activity. Obesity is associated with insulin resistance; hyperinsulinemia is associated with sympathetic overactivity which explains the increase in parameters of hemodynamic variables.,,,
RPP is an index of MVO2 as well as a vital indicator of ventricular functional status. The determination of MVO2 is important in monitoring the level of exercise to be done by various groups of persons like obese persons, patients of CVD, diabetic patients, and also in normal persons who are health conscious as well as in athletes. While doing exercise it must be done in limits otherwise, it may put an adverse effect on the health. Various researches suggested overwork of cardiac muscle beyond limit may lead to the development of angina. That limit can be determined by calculating RPP. Under resting conditions, the safer RPP varies between 70 and 90 in an apparently healthy adult. The value of RPP more than 100 is a clear indicator of cardiovascular risk., The positive correlation between RPP with BMI, WC, and WHR suggested that cardiovascular risk increases with increase in anthropometric indices. Persons whose BMI, WC, and WHR cross the normal limit may be at risk to develop adverse cardiac events.
Young adults of this era are gaining more weight and are showing increasing tendency toward overweight and obese due to less physical activity, sedentary lifestyle, and change in dietary habit. Thus, this study suggested the young adults to modify their lifestyle to remain healthy and fit.
| Conclusion|| |
This study concluded that anthropometric indices such as BMI, WC, and WHR, which are the vital indicators of adiposity or obesity, may be utilized in productive way to evaluate the cardiovascular risk of generalized as well as in abdominal obesity.
We are very much thankful to the subjects involved in this study without whom this study could not be completed.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Lichtash CT, Cui J, Guo X, Chen YD, Hsueh WA, Rotter JI, et al
. Body adiposity index versus body mass index and other anthropometric traits as correlates of cardiometabolic risk factors. PLoS One 2013;8:e65954.
Kesavachandran CN, Bihari V, Mathur N. The normal range of body mass index with high body fat percentage among male residents of Lucknow city in North India. Indian J Med Res 2012;135:72-7.
] [Full text]
Akhter MN, Pappas G. Health, Pakistan, and globalization. Am J Public Health 2001;91:13-4.
World Health Organization. Reducing Risks, Promoting Healthy Life: The World Health Report. Geneva: World Health Organization; 2002.
Saxena Y, Saxena V, Dvivedi J, Sharma RK. Evaluation of dynamic function tests in normal obese individuals. Indian J Physiol Pharmacol 2008;52:375-82.
Kopelman P. Health risks associated with overweight and obesity. Obes Rev 2007;8 Suppl 1:13-7.
Lin CH, Kurup S, Herrero P, Schechtman KB, Eagon JC, Klein S, et al
. Myocardial oxygen consumption change predicts left ventricular relaxation improvement in obese humans after weight loss. Obesity (Silver Spring) 2011;19:1804-12.
Selwyn AP, Braunwald E. Ischemic heart disease. In: Isselbacher KJ, Braunwald E, Wilson JD, Martin JB, Fauci AS, Kasper DL, editors. Harrison's Principles of Internal Medicine. 13th
ed. New York: McGraw-Hill, Inc.; 1994. p. 1081-2.
Kasper DL, Braunwald E, Fauci AS, Hauser SL, Longo DL, Jameson JL, editors. Harrison's Principles of Internal Medicine. 15th
ed. New York: McGraw Hill; 2001. p. 1402.
Jena SK, Sahoo SK, Mohanty B. Correlation of lactate dehydrogenase to cardiovascular risk in preeclampsia. Int J Clin Exp Physiol 2015;2:224-7. [Full text]
National Research Council, Committee on Diet and Health. Implications for Reducing Chronic Disease Risk. Washington, DC: National Academy Press; 1989.
Huxley R, Mendis S, Zheleznyakov E, Reddy S, Chan J. Body mass index, waist circumference and waist:hip ratio as predictors of cardiovascular risk – A review of the literature. Eur J Clin Nutr 2010;64:16-22.
Rahmouni K, Correia ML, Haynes WG, Mark AL. Obesity-associated hypertension: New insights into mechanisms. Hypertension 2005;45:9-14.
Falkner B, Daniels SR. Summary of the fourth report on the diagnosis, evaluation, and treatment of high blood pressure in children and adolescents. Hypertension 2004;44:387-8.
Grundy SM, Benjamin IJ, Burke GL, Chait A, Eckel RH, Howard BV, et al
. Diabetes and cardiovascular disease: A statement for healthcare professionals from the American Heart Association. Circulation 1999;100:1134-46.
Rumantir MS, Vaz M, Jennings GL, Collier G, Kaye DM, Seals DR, et al
. Neural mechanisms in human obesity-related hypertension. J Hypertens 1999;17:1125-33.
Understanding Exercise Intensity and Rate Pressure Product (RPP) By NCSF on: 17 February, 2011. Available from: http://www.ncsf.org/
. [Last accessed on 2012 Aug 02, 8:45 am].
Robinson BF. Relation of heart rate and systolic blood pressure to the onset of pain in angina pectoris. Circulation 1967;35:1073-83.
Sarnoff SJ, Braunwald E, Welch GH Jr., Case RB, Stainsby WN, Macruz R. Hemodynamic determinants of oxygen consumption of the heart with special reference to the tension-time index. Am J Physiol 1958;192:148-56.
Fletcher GF, Cantwell JD, Watt EW. Oxygen consumption and hemodynamic response of exercises used in training of patients with recent myocardial infarction. Circulation 1979;60:140-4.
[Table 1], [Table 2], [Table 3], [Table 4]