Long-term Resting Metabolic Rate Analysis in Pregnancy and Weight Loss Interventions

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Published Aug 24, 2021
shayok Teresa Wu Erica Forzani Corrie Whisner David Jackemeyer

Abstract

In this paper, we first studied the change in resting metabolic rate (RMR) of 4 women during their pregnancy period. We retrospectively analyzed published data, which lacked rigorous statistical analysis. We introduced new data that helps to define RMR baseline variabilities and further compare the RMR fluctuations in steady physiological conditions (no pregnancy, no weight/diet/exercise regime change) to assess “true” RMR changes that can guide healthy weight management in pregnancy and other conditions. For each subject, the change in the RMR values were computed as the difference between the values during the metabolic rate inspection period and the baseline values. This difference was compared against the difference values of a reference subject, using a two-sided paired t-test at the significance level of 5%. Our results indicated that some subjects exhibit a statistically significant increase, some exhibit a decrease while others show no significant statistical variation in RMR values during pregnancy.
These are important findings that demystify the old idea that the RMR of a pregnant woman “always” increases since she is generating a new life; rather, individualized physiological processes can produce metabolic changes that cannot be generalized and need individual RMR measurements throughout pregnancy. The insights gained from this study were then applied to retrospectively analyze the RMR of 20 subjects during a 6-month pilot weight loss intervention with 89% efficiency in weight loss. Our analysis revealed that there was no significant decrease in metabolic activities at the end of the program. Although this contradicts the belief that weight loss is associated with a decrease in metabolic activities, our results can be explained by the fact that subjects adhered to a healthy nutritional diet and regular exercise during the pro- gram; thus, the effect of weight loss on decreasing the RMR was counter-balanced by the effect of healthier diet and exercise on increasing the RMR, which helped in maintaining a steady and healthy metabolic rate. Both studies, pregnancy and weight loss interventions indicated that changes in the metabolic rate of pregnant women and individuals undergoing weight loss interventions are unpredictable, therefore there is an urgent need to implement personalized practices of weight management by periodically measuring RMR and adjusting food caloric intakes based on the individual’s metabolic rate.

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Keywords

Resting metabolic rate, Pregnancy, Weight Loss Interventions

References
Bray, G. (2004). Medical consequences of obesity. Journal Of Clinical Endocrinology and Metabolism, 89(6), 2583-2589.
Campos, P., Saguy, A., Ernsberger, P., Oliver, E., & Gaesser, G. (2006). The epidemiology of overweight and obesity: public health crisis or moral panic? International Journal Of Epidemiology, 35(1), 55-60.
Criscione, L., & Durr-Gross, M. (Eds.). (2010). Eating healthy and dying obese. Vitasanas GmbH.
Criscione, L., Durr-Gross, M., & Stebler, K. (2013). Calogenetic balance, an educational program for lifelong weight control on measured resting metabolic rate and intake of favorite foods, promotes adherence and success rate. In European congress on obesity.
Elliot, D., Goldberg, L., Kuehl, K., & Bennett, W. (1987). Sustained decrement in resting metabolic-rate following weight loss. Clinical Research, 35(3), A365-A365.
Elliot, D., Goldberg, L., Kuehl, K., & Bennett, W. (1989). Sustained depression of the resting metabolic-rate after massive weight loss. American Journal Of Clinical Nutrition, 49(1), 93-96.
Finkelstein, E., Trogdon, J., Cohen, J., & Dietz, W. (2009). Annual medical spending attributable to obesity: Payer- and service-specific estimates. Health Affairs, 28(5), W822-W831.
Flegal, K., Carroll, M., Ogden, C., & Johnson, C. (2002). Prevalence and trends in obesity among u.s. adults, 1999-2000. Journal of the American Medical Association, 288(14), 1723-1727.
Hales, C., Carroll, M., Fryar, C., & Ogden, C. (2017). Prevalence of obesity among adults and youth: United states, 2015-2016. In Nchs data brief, no 288.
Heshka, S., Yang, M., Wang, J., Burt, P., & Pisunyer, F. (1990). Weight-loss and change in resting metabolic rate. American Journal Of Clinical Nutrition, 52(6), 981-986.
Jackemeyer, D., Forzani, E., & Whisner, C. (2017). Study of resting energy expenditure and weight changes during pregnancy. Global Journal of Obesity, Diabetes and Metabolic Syndrome, 4(1), 16-23.
Jones, V. (2006). Resting metabolic rate: A critical, primary care screening test. MedGenMed, 8(2).
Kinney, J., & Tucker, H. (Eds.). (1992). Energy metabolism, tissue determinants and cellular corollaries. Raven Press.
Manore, M., Meyer, N., & Thompson, J. (Eds.). (2009). Human kinetics (ed.). Sport Nutrition for Health and Performance.
McArdle, W., Katch, F., & Katch, V. (Eds.). (2010). Exercise physiology: nutrition, energy, and human performance. Lippincott Williams and Wilkins.
McDoniel, S., Nelson, H., & Thomson, C. (2008). Employing rmr technology in a 90-day weight control program. Obesity Facts, 1(6), 298-304.
Nestle, M., & Nesheim, M. (Eds.). (2012). Why calories count: from science to politics. University of California Press.
Orsi, C., Hale, D., & Lynch, J. (2011). Pediatric obesity epidemiology. Current Opinion in Endocrinology Diabetes and Obesity, 18(1), 14-22.
Seagle, H., Strain, G., Makris, A., & Reeves, R. (2009). Position of the american dietetic association: Weight management. Journal of the American Dietetic Association, 109, 330-346.
Spring, B., Pellegrini, C., Pfammatter, A., Duncan, J., Pictor, A., McFadden, H., . . . Hedeker, D. (2017). Effects of an abbreviated obesity intervention supported by mobile technology: The engaged randomized clinical trial. Obesity, 25(7), 1191-1198.
Stump, C., Jackemeyer, D., Abidov, Y., Herbst, K., Tao, N., & Forzani, E. (2017). Study of the effect of mobile indirect calorimeter on weight management. Global Journal of Obesity, Diabetes and Metabolic Syndrome, 4(2), 44-50.
Wahrlich, V., Anjos, L., Going, S., & Lohman, T. (2006). Validation of the vo2000 calorimeter for measuring resting metabolic rate. Clinical Nutrition, 25(4), 687-692.
Weir, J. (1949). New methods for calculating metabolic rate with special reference to protein metabolism. Journal of Physiology, 109(1-2), 1-9.
Weir, J. (1990). Nutrition metabolism classic - new methods for calculating metabolic-rate with special reference to protein-metabolism. Journal of Nutrition, 6, 213-221.
Wolf, A., & Colditz, G. (1998). Current estimates of the economic cost of obesity in the united states. Obesity Research, 6(2), 97-106.
Xian, X., Quach, A., Bridgeman, D., Tsow, F., Forzani, E., & Tao, N. (2015). Personalized indirect calorimeter for energy expenditure (ee) measurement. Global Journal of Obesity, Diabetes and Metabolic Syndrome, 2(1), 004-008.
Section
Technical Papers