Preoperative high respiratory quotient correlates with lower weight loss after bariatric surgery

  • Armando Rosales
  • Enrique Elli
  • Scott Lynch
  • Gretchen Ames
  • Mauricia Buchanan
  • Steven P. BowersEmail author
2019 SAGES Oral



The respiratory coefficient (RQ), as determined by indirect calorimetry (IC), classifies diet as being carbohydrate rich (RQ = 0.7–0.8), fat rich (RQ = 0.9–1.0), or overfeeding (RQ > 1). We hypothesized that preoperative RQ may be associated with weight-loss outcomes after bariatric surgery.


From 2016 to 2018, 137 obese patients were enrolled in a Bariatric Registry and underwent dietary and behavioral counseling, followed by preoperative IC. Resting energy expenditure (REE) and RQ of all patients was measured. Patients were classified as over-feeders (OF; 42, 31%) with RQ > 1 or non-over-feeders (NOF; 95, 69%) with RQ < 1. At baseline, there was no difference between groups in gender [female: 105 (76.6%), male: 32 (23.4%)], body mass index (BMI; OF: 46.8 ± 7.8 vs. NOF: 44.8 ± 7.4 kg/m2, p = 0.40), or baseline REE (OF: 1897 ± 622 vs. NOF: 1874 ± 579, p = 0.74), although OF were younger [mean age (OF: 47.1 ± 13.0 years vs. NOF: 43.1 ± 13.4; p = 0.009). At 6-month follow-up 94 patients [53.28%; OF: 35 (83%) vs. NOF: 59 (62%), p = 0.016] were seen and 48 [35.03%; OF: 23 (55%) vs. NOF: 25 (59%), p = 0.001] at 12-month follow-up. On preoperative psychological assessment, OF had a significantly higher rate of childhood neglect (OF: 28 (47.46%) vs. NOF: 40 (28.99%); p = 0.01).


At 1 year postoperatively, the OF had a significantly higher BMI (OF: 34.3 ± 6.5 vs. NOF: 29.3 ± 5.1 kg/m2, p = 0.009). Differences in weight were not significant at 6-month (OF: 36.0 ± 6.5 vs. NOF: 33.5 ± 5.9 kg/m2, p = 0.07). There was no difference between type of operation and RQ group (RYGB; OF: 55 (75%) vs. NOF: 18 (25%) and SG; OF: 40 (62%) vs. NOF: 24 (38%), p = 0.14), nor in BMI loss after operation.


Evidence of overfeeding in the preoperative period prior to bariatric surgery is associated with higher resultant BMI at 1 year. Calculation of the RQ with IC has prognostic significance in bariatric surgery, and calculation of REE based on assumed normal RQ potentiates error. It is unclear if overfeeding is purely behavioral or secondary to potentially reversible metabolic etiology.


Bariatric surgery Bypass Sleeve Respiratory quotient 


Compliance with ethical standards


Armando Rosales, Enrique Elli, Scott Lynch, Gretchen Ames, Mauricia Buchanan, and Steven P Bowers have no conflicts of interest or financial ties to disclose.


  1. 1.
    Shook RP, Hand GA, Paluch AE, Wang X, Moran R, Hebert JR, Jakicic JM, Blair SN (2016) High respiratory quotient is associated with increases in body weight and fat mass in young adults. Eur J Clin Nutr 70:1197–1202CrossRefGoogle Scholar
  2. 2.
    Rosales-Velderrain A, Goldberg RF, Ames GE, Stone RL, Lynch SA, Bowers SP (2014) Hypometabolizers: characteristics of obese patients with abnormally low resting energy expenditure. Am Surg 80:290–294Google Scholar
  3. 3.
    Ravussin E, Lillioja S, Knowler WC, Christin L, Freymond D, Abbott WG, Boyce V, Howard BV, Bogardus C (1988) Reduced rate of energy expenditure as a risk factor for body-weight gain. N Engl J Med 318:467–472CrossRefGoogle Scholar
  4. 4.
    Astrup A, Gotzsche PC, van de Werken K, Ranneries C, Toubro S, Raben A, Buemann B (1999) Meta-analysis of resting metabolic rate in formerly obese subjects. Am J Clin Nutr 69:1117–1122CrossRefGoogle Scholar
  5. 5.
    Leibel RL, Rosenbaum M, Hirsch J (1995) Changes in energy expenditure resulting from altered body weight. N Engl J Med 332:621–628CrossRefGoogle Scholar
  6. 6.
    Katzmarzyk PT, Perusse L, Tremblay A, Bouchard C (2000) No association between resting metabolic rate or respiratory exchange ratio and subsequent changes in body mass and fatness: 5-1/2 year follow-up of the Quebec family study. Eur J Clin Nutr 54:610–614CrossRefGoogle Scholar
  7. 7.
    Marra M, Scalfi L, Covino A, Esposito-Del Puente A, Contaldo F (1998) Fasting respiratory quotient as a predictor of weight changes in non-obese women. Int J Obes Relat Metab Disord 22:601–603CrossRefGoogle Scholar
  8. 8.
    Seidell JC, Muller DC, Sorkin JD, Andres R (1992) Fasting respiratory exchange ratio and resting metabolic rate as predictors of weight gain: the Baltimore Longitudinal Study on Aging. Int J Obes Relat Metab Disord 16:667–674Google Scholar
  9. 9.
    Roberts SB, Savage J, Coward WA, Chew B, Lucas A (1988) Energy expenditure and intake in infants born to lean and overweight mothers. N Engl J Med 318:461–466CrossRefGoogle Scholar
  10. 10.
    Zurlo F, Lillioja S, Esposito-Del Puente A, Nyomba BL, Raz I, Saad MF, Swinburn BA, Knowler WC, Bogardus C, Ravussin E (1990) Low ratio of fat to carbohydrate oxidation as predictor of weight gain: study of 24-h RQ. Am J Physiol 259:E650–657Google Scholar
  11. 11.
    Ravussin E, Swinburn BA (1993) Metabolic predictors of obesity: cross-sectional versus longitudinal data. Int J Obes Relat Metab Disord 17 Suppl 3:S28–31; discussion S41–22Google Scholar
  12. 12.
    Landsberg L (2012) Core temperature: a forgotten variable in energy expenditure and obesity? Obes Rev 13(Suppl 2):97–104CrossRefGoogle Scholar
  13. 13.
    Saltzman E, Roberts SB (1996) Effects of energy imbalance on energy expenditure and respiratory quotient in young and older men: a summary of data from two metabolic studies. Aging (Milan, Italy) 8:370–378Google Scholar
  14. 14.
    Valtuena S, Salas-Salvado J, Lorda PG (1997) The respiratory quotient as a prognostic factor in weight-loss rebound. Int J Obes Relat Metab Disord 21:811–817CrossRefGoogle Scholar
  15. 15.
    Astrup A, Buemann B, Western P, Toubro S, Raben A, Christensen NJ (1994) Obesity as an adaptation to a high-fat diet: evidence from a cross-sectional study. Am J Clin Nutr 59:350–355CrossRefGoogle Scholar
  16. 16.
    Nagy TR, Goran MI, Weinsier RL, Toth MJ, Schutz Y, Poehlman ET (1996) Determinants of basal fat oxidation in healthy Caucasians. J Appl Physiol (Bethesda, Md : 1985) 80:1743–1748CrossRefGoogle Scholar
  17. 17.
    Schutz Y, Tremblay A, Weinsier RL, Nelson KM (1992) Role of fat oxidation in the long-term stabilization of body weight in obese women. Am J Clin Nutr 55:670–674CrossRefGoogle Scholar
  18. 18.
    Schutz Y (1995) Abnormalities of fuel utilization as predisposing to the development of obesity in humans. Obes Res 3(Suppl 2):173S–178SCrossRefGoogle Scholar
  19. 19.
    Bassett DR Jr, Howley ET, Thompson DL, King GA, Strath SJ, McLaughlin JE, Parr BB (2001) Validity of inspiratory and expiratory methods of measuring gas exchange with a computerized system. J Appl Physiol (Bethesda, Md: 1985) 91:218–224CrossRefGoogle Scholar
  20. 20.
    Cooper JA, Watras AC, O’Brien MJ, Luke A, Dobratz JR, Earthman CP, Schoeller DA (2009) Assessing validity and reliability of resting metabolic rate in six gas analysis systems. J Am Diet Assoc 109:128–132CrossRefGoogle Scholar
  21. 21.
    Kroenke K, Spitzer RL, Williams JB (2001) The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med 16:606–613CrossRefGoogle Scholar
  22. 22.
    Kroenke K, Spitzer RL, Williams JB, Monahan PO, Lowe B (2007) Anxiety disorders in primary care: prevalence, impairment, comorbidity, and detection. Ann Intern Med 146:317–325CrossRefGoogle Scholar
  23. 23.
    Dube SR, Felitti VJ, Dong M, Chapman DP, Giles WH, Anda RF (2003) Childhood abuse, neglect, and household dysfunction and the risk of illicit drug use: the adverse childhood experiences study. Pediatrics 111:564–572CrossRefGoogle Scholar
  24. 24.
    Saunders JB, Aasland OG, Babor TF, de la Fuente JR, Grant M (1993) Development of the alcohol use disorders identification test (AUDIT): WHO collaborative project on early detection of persons with harmful alcohol consumption–II. Addiction 88:791–804CrossRefGoogle Scholar
  25. 25.
    Yanovski SZ, Marcus MD, Wadden TA, Walsh BT (2015) The questionnaire on eating and weight patterns-5: an updated screening instrument for binge eating disorder. Int J Eat Disord 48:259–261CrossRefGoogle Scholar
  26. 26.
    Belle SH, Berk PD, Chapman WH, Christian NJ, Courcoulas AP, Dakin GF, Flum DR, Horlick M, King WC, McCloskey CA, Mitchell JE, Patterson EJ, Pender JR, Steffen KJ, Thirlby RC, Wolfe BM, Yanovski SZ (2013) Baseline characteristics of participants in the Longitudinal Assessment of Bariatric Surgery-2 (LABS-2) study. Surg Obes Relat Dis 9:926–935CrossRefGoogle Scholar
  27. 27.
    Schulte EM, Gearhardt AN (2017) Development of the modified Yale food addiction scale version 2.0. Eur Eat Disord Rev 25:302–308CrossRefGoogle Scholar
  28. 28.
    Ames GE, Heckman MG, Diehl NN, Grothe KB, Clark MM (2015) Further statistical and clinical validity for the weight efficacy lifestyle questionnaire-short form. Eat Behav 18:115–119CrossRefGoogle Scholar
  29. 29.
    Werling M, Olbers T, Fandriks L, Bueter M, Lonroth H, Stenlof K, le Roux CW (2013) Increased postprandial energy expenditure may explain superior long term weight loss after Roux-en-Y gastric bypass compared to vertical banded gastroplasty. PLoS ONE 8:e60280CrossRefGoogle Scholar
  30. 30.
    Carrasco F, Papapietro K, Csendes A, Salazar G, Echenique C, Lisboa C, Diaz E, Rojas J (2007) Changes in resting energy expenditure and body composition after weight loss following Roux-en-Y gastric bypass. Obes Surg 17:608–616CrossRefGoogle Scholar
  31. 31.
    Das SK, Roberts SB, McCrory MA, Hsu LK, Shikora SA, Kehayias JJ, Dallal GE, Saltzman E (2003) Long-term changes in energy expenditure and body composition after massive weight loss induced by gastric bypass surgery. Am J Clin Nutr 78:22–30CrossRefGoogle Scholar
  32. 32.
    Flancbaum L, Choban PS, Bradley LR, Burge JC (1997) Changes in measured resting energy expenditure after Roux-en-Y gastric bypass for clinically severe obesity. Surgery 122:943–949CrossRefGoogle Scholar

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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of SurgeryMayo Clinic FloridaJacksonvilleUSA

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