Negative effects of obesity analyzed through bioimpedance, indirect calorimetry, the sympathovagal index and the orthoclinostatic test

• Main Authors: Cadena, M., Azpiroz, J., Martinez, F., Borja, G., Ramos, N., Velazquez, C., Rodriguez, M., Diaz, R.
• Format: Conference Proceeding
• Language: English
• Subjects: Biochemistry; Energy measurement; Heart rate variability; Lead; Physiology; Robustness; Weight measurement
• ISSN: 1094-687X; 1558-4615; 2694-0604
• DOI: 10.1109/EMBC.2012.6346351

Early analysis of the negative effects of obesity is important to prevent the development of chronic diseases related to this condition. There is a need to monitor these effects through simple instrumentation that measures fat-free mass (FFM) catabolism. Obesity leads to a decrease in the FFM energy expenditure and to an increase in the autonomic nervous system (ANS) activity. Thus, the measurement of FFM dynamic catabolism can provide information regarding the effects of obesity. The hypothesis is that this increased ANS activity produces an increase of energy expenditure of carbohydrates and fats when the subjects are under stress; in this case after an 8-hour fast and while they are undergoing an orthoclinostatic test. A pilot study was conducted on 29 volunteers, 16 women and 13 men. The results show significant statistical differences (p0.1) in fat and carbohydrate utilization during the orthoclinostatic tests: A move from the clinostatic to the orthostatic positions produced the following: Fat metabolism varied from 97.2 to 105.9 gr/day of fat for women and 24.9 to 35.7 gr/day of fat for men; carbohydrate metabolism changed from 38 to 39 gr/day for women and 239 to 277 gr/day for men; FFM averages were 47 Kg for women and 57.6 Kg for men; changes in the sympathovagal index (SVI) averages were 0.4 to 1.8 for women and 0.8 to 2.7 for men. The conclusions show that the methodology's sensitivity is such that gender differences can be used as a model to prove FFM metabolic differences. We believe that further studies will lead to the development of a robust methodology for the early detection of the negative effects of obesity.