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Modern Assessment of Body Composition and the Obesity Epidemic

 Modern Assessment of Body Composition and the Obesity Epidemic

INTRODUCTION

According to the American College of Sports Medicine, “approximately 70% of the U.S. population are classified as either overweight or obese (BMI ≥25 kg/m-2), with approximately 40% classified as obese (BMI ≥30kg/m-2), including 7% with severe obesity (BMI ≥40kg/m-2)” (Liguori & American College of Sports Medicine, 2020, p. 296). Additionally, some statistics report up to 32% of children and adolescents are overweight or obese, with roughly 18% of children aged 6-11 yo, and roughly 21% of adolescents aged 12-19 yo being categorized as obese. Categories of BMI include:

            Underweight: <18.5 kg/m-2

            Normal: 18.5-24.9 kg/m-2

                Overweight: 25.0-29.9 kg/m-2

                Obese:

                        Class I: 30.0-34.9 kg/m-2

                        Class II: 35.0-39.9 kg/m-2

                        Class III: ≥40.0 kg/m-2

(Liguori & American College of Sports Medicine, 2020, p. 63-64)

Obesity comes with significant health risks, increasing with each tier of obesity. Aronne (2002) compares the portion of disease risk attributable to obesity as the following:

            DM2: 61%

            Uterine Cancer: 34%

            Gallbladder Disease: 30%

            Osteoarthritis: 24%

            Hypertension: 17%

            Coronary Heart Disease: 17%

            Breast/Colon Cancer: 11%

(Aronne, 2002, p. 106S)

Additionally, the higher the BMI, the higher the risk category for disease, starting at overweight providing an increased risk in men and high risk in women, obesity I rising to a high risk for men and a very high risk for women, obesity II rising to very high for men and very high for women, and finally, obesity III raising both to extremely high risk (Aronne, 2002, p. 107S).

PROBLEM      

As mentioned, obesity can be associated with an increased risk for various diseases. Obesity has been directly linked to chronic conditions such as cancer [2] [11], cardiovascular disease [10], depression [7] [9], type 2 diabetes [3] [4], among others. This not only shortens the potential lifespan, and reduces the quality of life for the individual, but on the scale, it is at, it puts a significant strain on the healthcare system. In addition to the health concerns, societal changes have increased the cost of programs encouraging healthy lifestyles, and modifications to buildings and public spaces to accommodate the heavier person. Finally, the increase in obesity has disqualified a lot of people from military service, and public service (i.e., police and fire fighting), and has reduced the number of children participating in sports at any level.

METHODS OF MEASUREMENT

BMI (body mass index) is a measurement of body composition using height (in meters) and weight (in kilograms) (BMI=kg/m-2) and is largely considered, among the health and fitness community, as a flawed measurement due to the lack of other considerations of weight (i.e., fluids, bone/muscle density, etc.), and known deviations based on gender and ethnicity. One study by Romero-Corral et al. (2008) performed a cross-sectional analysis of 13,601 subjects using both BMI and bioelectrical impedance (to measure BF%), finding

“BMI has a limited diagnostic performance to correctly identify individuals with excess in body fatness, particularly for those with BMI between 25 to 30 kg/m2, for men, and for the elderly. Body mass index has a good general correlation with BF %, but it fails to discriminate between BF % and lean mass. In addition, the sensitivity of BMI ≥ 30 kg/m2 to diagnose obesity is relatively low, missing more than half of people with BF %defined obesity, while the specificity and positive predictive value are good. Furthermore, for a given BMI value there is significant inter-subject variability in BF %: (p. 5).

            In addition to BMI, the waist-to-hip circumference can be used as a measure of assessing health. Circumference measurements are clinically performed at the waist and hip (waist (cm)/hips (cm)), measuring the pattern of body fat distribution. Where the body stores fat is a helpful indicator of health and disease risk. Common types of obesity include android (abdominal fat), increasing risk of hypertension, metabolic syndrome, DM2, dyslipidemia, CVS, and premature death, when compared to gynoid/gynecoid (hip and thigh fat), Visceral fat (fat within surrounding thoracic and abdominal cavities) also increases the risk of metabolic syndrome (Liguori & American College of Sports Medicine, 2020, p. 64-65).

            More reliable measures of body composition include skinfold measurements, densitometry, DXA, and bioelectrical impedance. Skinfold measurements can be performed as a 3-site test or a 7-site test, with the 7-site being more precise. Skinfold involves the measuring of thickness at various sites on the body, through the pinching of subcutaneous fat and tissue. Densitometry involves the measurement of the density of the body, through a ratio of body mass to body volume. The most common method is hydrodensitometry, which measures the displacement of water in the presence of the individual. Basically, how much the water rises when the subject is immersed. This works due to the higher density of bone and muscle tissue, and lower density of fat tissue. If two subjects were being measured, with the same body mass, the person with more fat-free mass would weigh more in the water than the other person with a higher fat percentage (Liguori & American College of Sports Medicine, 2020, p. 67-70). DXA uses x-ray in order to measure bone mineral density, as well as soft tissue mass. DXA is not commonly used outside of schools, laboratories, or hospitals, due to its specialized and expensive nature. Other methods include bioelectrical impedance and ultrasound which utilize either electrical current or ultrasound to measure interference and associate the interference with BF%.

DISCUSSION

            Although the standard tool for measuring body composition is the BMI, there is still a significant percentage of the population that is obese. This obesity epidemic stems from an increasingly sedentary lifestyle with the increase in desk jobs, and the reduction of trade jobs. Children are participating in sports less at all levels, adults are not engaging in enough physical activity throughout the week, and these changes are burdening society both fiscally and socially. A more obese society is sicker, with more chronic illnesses, higher rates of mental health disorders such as depression and anxiety, and less work or defense capability required. This is a scary trend to watch since the fast-food industry is not slowing down, and health education/recess is being reduced in schools, we are putting ourselves on track to continue seeing an increase in societal obesity.

            Big is not beautiful, big is sick. Our bodies are not meant to carry around excess weight. That is why obese people are at a higher risk of chronic diseases, musculoskeletal disorders, and mental health disorders. Fat shaming should, of course, be discouraged however, obesity awareness is extremely important right now and needs to be pushed more than it is. Society cannot function without capable people, and currently, a large number of people are not capable. Obese people need to be encouraged to seek help through registered dietitians and qualified personal trainers that know how to work with obese clients.

CONCLUSION

            Obesity is a significant problem facing America right now. There are various thoughts behind the rise in obesity however, acceptance of obesity should not be encouraged. Obesity affects society in many ways including financial strain (especially on the healthcare system), and infrastructure modifications to accommodate heavier people. There are various methods used to measure body composition and body fat percentage with the current practice being BMI, which is an unreliable measure. Other tools of measurement include skinfold, densitometry, and circumference tapings, among others. Obesity needs to be reversed and should start with encouraging obese people to seek help from registered dietitians and qualified personal trainers to learn healthy habits and get their lives back on track.

 

 

References

1. Aronne, L. J. (2002). Classification of Obesity and Assessment of Obesity-Related Health Risks. Obesity Research10(2), 105S-115S.

2. Calle, E. E., & Thun, M. J. (2004). Obesity and cancer. Oncogene23(38), 6365–6378. https://doi.org/10.1038/sj.onc.1207751

3. Golay, A., & Ybarra, J. (2006). Link between obesity and type 2 diabetes. Best Practice & Research: Clinical Endocrinology & Metabolism19(4), 649–663. https://doi.org/10.1016/j.beem.2005.07.010

4. Hannon, T. S., Rao, G., & Arslanian, S. A. (2005). Childhood obesity and type 2 diabetes mellitus. Pediatrics116(2), 473-480. https://doi.org/10.1542/peds.2004-2536

5. Kuriyan, R. (2018). Body composition techniques. Indian Journal of Medical Research148(5), 648-658. https://doi.org/10.4103/ijmr.IJMR_1777_18

6. Liguori, G., & American College of Sports Medicine. (2020). ACSM's guidelines for exercise testing and prescription (11th ed.). Lippincott Williams & Wilkins.

7. Markowitz, S., Friedman, M. A., & Arent, S. M. (2008). Understanding the relation between obesity and depression: Causal mechanisms and implications for treatment. Clinical Psychology: Science and Practice15(1), 1-20. https://doi.org/10.1111/j.1468-2850.2008.00106.x

8. Romero-Corral, A., Somers, V. K., Sierra-Johnson, J., Thomas, R. J., Collazo-Clavell, M. L., Korinek, J., Allison, T. G., Batsis, J. A., Sert-Kuniyoshi, F. H., & Lopez-Jimenez, F. (2008). Accuracy of body mass index in diagnosing obesity in the adult general population. International Journal of Obesity32(6), 959-966. https://doi.org/10.1038/ijo.2008.11

9. Simon, G. E., Ludman, E. J., Linde, J. A., Operskalski, B. H., Ichikawa, L., Rohde, P., Finch, E. A., & Jeffery, R. W. (2008). Association between obesity and depression in middle-aged women. General Hospital Psychiatry30(1), 32-39. https://doi.org/10.1016/j.genhosppsych.2007.09.001

10. Van Gaal, L. F., Mertens, I. L., & De Block, C. E. (2006). Mechanisms linking obesity with cardiovascular disease. Nature444(7121), 875-880. https://doi.org/10.1038/nature05487

11. Wollen, K. Y., Carson, K., & Colditz, G. A. (2010). Obesity and Cancer. Oncologist15(6), 556–565. https://doi.org/10.1634/theoncologist.2009-0285

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