Predictors of Post-Exercise Energy Intake in Adolescents Ranging in Weight Status from Overweight to Severe Obesity

Nicole Fearnbach, Amanda E Staiano, Neil M Johannsen, Daniel S Hsia, Robbie A Beyl, Owen T Carmichael, Corby K Martin, Nicole Fearnbach, Amanda E Staiano, Neil M Johannsen, Daniel S Hsia, Robbie A Beyl, Owen T Carmichael, Corby K Martin

Abstract

Exercise may sensitize individuals with overweight and obesity to appetitive signals (e.g., hunger and fullness cues), overriding trait eating behaviors that contribute to overeating and obesity, such as uncontrolled eating. The objective of the current study was to measure predictors of objective ad libitum energy intake at a laboratory-based, post-exercise test-meal in adolescents ranging in weight status from overweight to severe obesity. We hypothesized that appetitive states, rather than appetitive traits, would be the strongest predictors of energy intake at a post-exercise test-meal, after controlling for body size. At Baseline, 30 adolescents (ages 10-16 years, 50% female (F), 43% non-Hispanic white (NHW), 83% with obesity (OB)) completed state and trait appetite measures and an ad libitum dinner meal following intensive exercise. Nineteen of those participants (47% F, 32% NHW, 79% OB) completed identical assessments two years later (Year 2). Energy intake (kcal) at each time point was adjusted for fat-free mass index (i.e., body size). Adjusted energy intake was reliable from Baseline to Year 2 (ICC = 0.84). Multiple pre-meal appetite ratings were associated with test-meal energy intake. In stepwise linear regression models, pre-meal prospective food consumption was the strongest and only significant predictor of test-meal energy intake at both Baseline (R2 = 0.25, p = 0.005) and Year 2 (R2 = 0.41, p = 0.003). Baseline post-exercise energy intake was associated with weight change over two years (R2 = 0.24, p = 0.04), but not with change in fat mass (p = 0.11). Appetitive traits were not associated with weight or body composition change (p > 0.22). State appetite cues were the strongest predictors of post-exercise energy intake, independent of body size. Future studies should examine whether long-term exercise programs enhance responsiveness to homeostatic appetite signals in youth with overweight and obesity, with a goal to reduce excess energy intake and risk for weight gain over time.

Keywords: appetite; childhood obesity; prospective food consumption; uncontrolled eating; weight gain.

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Timeline of study assessments. Visit procedures were identical at Baseline and Year 2. Abbreviations: visual analog scales, VAS; Three-Factor Eating Questionnaire, TFEQ.
Figure 2
Figure 2
Association between energy intake (adj. for FFMI) at Baseline and Year 2 (ICC = 0.84), depicted against a line of identity (solid line). Abbreviations: energy intake, EI; fat-free mass index, FFMI; intra-class correlation, ICC; baseline, Y0; year 2, Y2.
Figure 3
Figure 3
Association between energy intake (adj. for FFMI) at Baseline and weight change (kg) from Baseline to Year 2 (r = 0.49, p = 0.04). Abbreviations: energy intake, EI; fat-free mass index, FFMI; baseline, Y0.

References

    1. Keller K.L., Kling S.M.R., Fuchs B., Pearce A.L., Reigh N.A., Masterson T., Hickok K. A Biopsychosocial Model of Sex Differences in Children’s Eating Behaviors. Nutrients. 2019;11:682. doi: 10.3390/nu11030682.
    1. Russell C.G., Russell A. A biopsychosocial approach to processes and pathways in the development of overweight and obesity in childhood: Insights from developmental theory and research. Obes. Rev. 2019;20:725–749. doi: 10.1111/obr.12838.
    1. Kininmonth A., Smith A., Carnell S., Steinsbekk S., Fildes A., Llewellyn C. The association between childhood adiposity and appetite assessed using the Child Eating Behavior Questionnaire and Baby Eating Behavior Questionnaire: A systematic review and meta-analysis. Obes. Rev. 2021;22:13169. doi: 10.1111/obr.13169.
    1. Batterink L., Yokum S., Stice E. Body mass correlates inversely with inhibitory control in response to food among ad-olescent girls: An fMRI study. Neuroimage. 2010;52:1696–1703. doi: 10.1016/j.neuroimage.2010.05.059.
    1. Price M., Lee M., Higgs S. Food-specific response inhibition, dietary restraint and snack intake in lean and over-weight/obese adults: A moderated-mediation model. Int. J. Obes. 2016;40:877–882. doi: 10.1038/ijo.2015.235.
    1. Vainik U., Garcia I.G., Dagher A. Uncontrolled eating: A unifying heritable trait linked with obesity, overeating, personality and the brain. Eur. J. Neurosci. 2019;50:2430–2445. doi: 10.1111/ejn.14352.
    1. Brunner E.J., Maruyama K., Shipley M., Cable N., Iso H., Hiyoshi A., Stallone D., Kumari M., Tabak A., Singh-Manoux A., et al. Appetite disinhibition rather than hunger explains genetic effects on adult BMI trajectory. Int. J. Obes. 2021;45:758–765. doi: 10.1038/s41366-020-00735-9.
    1. Garcia-Garcia I., Neseliler S., Morys F., Dadar M., Yau Y.H.C., Scala S.G., Zeighami Y., Sun N., Collins D.L., Vainik U., et al. Relationship between impulsivity, uncontrolled eating and body mass index: A hierarchical model. Int. J. Obes. 2021;46:129–136. doi: 10.1038/s41366-021-00966-4.
    1. de Lauzon-Guillain B., Basdevant A., Romon M., Karlsson J., Borys J.M., Charles M.A. FLVS Study Group Is restrained eating a risk factor for weight gain in a general population? Am. J. Clin. Nutr. 2006;83:132–138. doi: 10.1093/ajcn/83.1.132.
    1. Appelhans B.M., Woolf K., Pagoto S., Schneider K.L., Whited M.C., Liebman R. Inhibiting Food Reward: Delay Discounting, Food Reward Sensitivity, and Palatable Food Intake in Overweight and Obese Women. Obesity. 2011;19:2175–2182. doi: 10.1038/oby.2011.57.
    1. Epstein L.H., Yokum S., Feda D.M., Stice E. Food reinforcement and parental obesity predict future weight gain in non-obese adolescents. Appetite. 2014;82:138–142. doi: 10.1016/j.appet.2014.07.018.
    1. Rollins B.Y., Loken E., Savage J.S., Birch L.L. Measurement of food reinforcement in preschool children. Associations with food intake, BMI, and reward sensitivity. Appetite. 2014;72:21–27. doi: 10.1016/j.appet.2013.09.018.
    1. French S.A., Epstein L.H., Jeffery R.W., Blundell J.E., Wardle J. Eating behavior dimensions. Associations with energy intake and body weight. A review. Appetite. 2012;59:541–549. doi: 10.1016/j.appet.2012.07.001.
    1. Feig E.H., Piers A.D., Kral T.V., Lowe M.R. Eating in the absence of hunger is related to loss-of-control eating, hedonic hunger, and short-term weight gain in normal-weight women. Appetite. 2018;123:317–324. doi: 10.1016/j.appet.2018.01.013.
    1. Sadoul B.C., Schuring E.A., Mela D.J., Peters H.P. The relationship between appetite scores and subsequent energy intake: An analysis based on 23 ran-domized controlled studies. Appetite. 2014;83:153–159. doi: 10.1016/j.appet.2014.08.016.
    1. Stubbs R.J., Hughes D.A., Johnstone A.M., Rowley E., Reid C., Elia M., Stratton R., Delargy H., King N., Blundell J.E. The use of visual analogue scales to assess motivation to eat in human subjects: A review of their reliabil-ity and validity with an evaluation of new hand-held computerized systems for temporal tracking of appetite ratings. Br. J. Nutr. 2000;84:405–415. doi: 10.1017/S0007114500001719.
    1. Ruddick-Collins L.C., Byrne N., King N.A. Assessing the influence of fasted and postprandial states on day-to-day variability of appetite and food preferences. Physiol. Behav. 2018;199:219–228. doi: 10.1016/j.physbeh.2018.11.015.
    1. Flint A., Raben A., Blundell J.E., Astrup A. Reproducibility, power and validity of visual analogue scales in assessment of appetite sensations in single test meal studies. Int. J. Obes. 2000;24:38–48. doi: 10.1038/sj.ijo.0801083.
    1. Smethers A.D., Roe L.S., Sanchez C.E., Zuraikat F.M., Keller K.L., Kling S.M.R., Rolls B.J. Portion size has sustained effects over 5 days in preschool children: A randomized trial. Am. J. Clin. Nutr. 2019;109:1361–1372. doi: 10.1093/ajcn/nqy383.
    1. Kling S.M., Roe L.S., Keller K.L., Rolls B.J. Double trouble: Portion size and energy density combine to increase preschool children’s lunch intake. Physiol. Behav. 2016;162:18–26. doi: 10.1016/j.physbeh.2016.02.019.
    1. Boutelle K.N., Manzano M.A., Eichen D.M. Appetitive traits as targets for weight loss: The role of food cue respon-siveness and satiety responsiveness. Physiol. Behav. 2020;224:113018. doi: 10.1016/j.physbeh.2020.113018.
    1. Dalton M., Hollingworth S., Blundell J., Finlayson G. Weak Satiety Responsiveness Is a Reliable Trait Associated with Hedonic Risk Factors for Overeating among Women. Nutrients. 2015;7:7421–7436. doi: 10.3390/nu7095345.
    1. Edholm O.G. Energy expenditure in relation to nutrition. Proc. Nutr. Soc. 1956;15:80–83. doi: 10.1079/PNS19560016.
    1. Mayer J., Roy P., Mitra K.P. Relation between caloric intake, body weight, and physical work: Studies in an industrial male population in West Bengal. Am. J. Clin. Nutr. 1956;4:169–175. doi: 10.1093/ajcn/4.2.169.
    1. Blundell J.E., Caudwell P., Gibbons C., Hopkins M., Näslund E., King N.A., Finlayson G. Body composition and appetite: Fat-free mass (but not fat mass or BMI) is positively associated with self-determined meal size and daily energy intake in humans. Br. J. Nutr. 2012;107:445–449. doi: 10.1017/S0007114511003138.
    1. Caudwell P., Finlayson G., Gibbons C., Hopkins M., King N., Näslund E., Blundell J.E. Resting metabolic rate is associated with hunger, self-determined meal size, and daily energy intake and may represent a marker for appetite. Am. J. Clin. Nutr. 2012;97:7–14. doi: 10.3945/ajcn.111.029975.
    1. Weise C.M., Hohenadel M.G., Krakoff J., Votruba S.B. Body composition and energy expenditure predict ad-libitum food and macronutrient intake in humans. Int. J. Obes. 2013;38:243–251. doi: 10.1038/ijo.2013.85.
    1. Hopkins M., Finlayson G., Duarte C., Whybrow S., Ritz P., Horgan G.W., Blundell J.E., Stubbs R.J. Modelling the associations between fat-free mass, resting metabolic rate and energy intake in the con-text of total energy balance. Int. J. Obes. 2015;40:312–318. doi: 10.1038/ijo.2015.155.
    1. Cameron J.D., Sigal R.J., Kenny G.P., Alberga A.S., Prud’Homme D., Phillips P., Doucette S., Goldfield G. Body composition and energy intake—Skeletal muscle mass is the strongest predictor of food intake in obese adolescents: The HEARTY trial. Appl. Physiol. Nutr. Metab. 2016;41:611–617. doi: 10.1139/apnm-2015-0479.
    1. Fearnbach S.N., Masterson T.D., Schlechter H.A., Loken E., Downs D.S., Thivel D., Keller K.L. Perceived Exertion during Exercise Is Associated with Children’s Energy Intake. Med. Sci. Sports Exerc. 2017;49:785–792. doi: 10.1249/MSS.0000000000001165.
    1. Hopkins M., Finlayson G., Duarte C., Gibbons C., Johnstone A., Whybrow S., Horgan G.W., Blundell J.E., Stubbs R.J. Biological and psychological mediators of the relationships between fat mass, fat-free mass and energy intake. Int. J. Obes. 2018;43:233–242. doi: 10.1038/s41366-018-0059-4.
    1. Kracht C., Champagne C.M., Hsia D.S., Martin C.K., Newton R.L., Katzmarzyk P.T., Staiano A.E. Association Between Meeting Physical Activity, Sleep, and Dietary Guidelines and Cardiometabolic Risk Factors and Adiposity in Adolescents. J. Adolesc. Health. 2020;66:733–739. doi: 10.1016/j.jadohealth.2019.12.011.
    1. Kracht C.L., Chaput J.-P., Martin C.K., Champagne C.M., Katzmarzyk P.T., Staiano A.E. Associations of Sleep with Food Cravings, Diet, and Obesity in Adolescence. Nutrients. 2019;11:2899. doi: 10.3390/nu11122899.
    1. American College of Sports Medicine . ACSM’s Guidelines for Exercise Testing and Prescription. 10th ed. Wolters Kluwer; Philadelphia, PA, USA: 2018. 472p
    1. Kuczmarski R., Ogden C., Guo S., Grummer-Strawn L.M., Flegal K., Mei Z., Wei R., Curtin L., Roche A., Johnson C. 2000 CDC Growth Charts for the United States: Methods and Development. Department of Health and Human Services; Washington, DC, USA: 2002.
    1. VanItallie T.B., Yang M.U., Heymsfield S.B., Funk R.C., Boileau R.A. Height-normalized indices of the body’s fat-free mass and fat mass: Potentially useful indicators of nutritional status. Am. J. Clin. Nutr. 1990;52:953–959. doi: 10.1093/ajcn/52.6.953.
    1. Fearnbach S.N., Johannsen N.M., Martin C.K., Katzmarzyk P.T., Beyl R.A., Hsia D., Carmichael O.T., Staiano A.E. A Pilot Study of Cardiorespiratory Fitness, Adiposity, and Cardiometabolic Health in Youth with Overweight and Obesity. Pediatr. Exerc. Sci. 2020;32:124–131. doi: 10.1123/pes.2019-0192.
    1. Karlsson J., Persson L.-O., Sjöström L., Sullivan M. Psychometric properties and factor structure of the Three-Factor Eating Questionnaire (TFEQ) in obese men and women. Results from the Swedish Obese Subjects (SOS) study. Int. J. Obes. 2000;24:1715–1725. doi: 10.1038/sj.ijo.0801442.
    1. Cappelleri J.C., Bushmakin A.G., Gerber R.A., Leidy N.K., Sexton C.C., Lowe M.R., Karlsson J. Psychometric analysis of the Three-Factor Eating Questionnaire-R21: Results from a large diverse sample of obese and non-obese participants. Int. J. Obes. 2009;33:611–620. doi: 10.1038/ijo.2009.74.
    1. Stunkard A.J., Messick S. The three-factor eating questionnaire to measure dietary restraint, disinhibition and hunger. J. Psychosom. Res. 1985;29:71–83. doi: 10.1016/0022-3999(85)90010-8.
    1. Harris P.A., Taylor R., Thielke R., Payne J., Gonzalez N., Conde J.G. Research electronic data capture (REDCap)—A metadata-driven methodology and workflow process for providing translational research informatics support. J. Biomed. Inform. 2009;42:377–381. doi: 10.1016/j.jbi.2008.08.010.
    1. Harris P.A., Taylor R., Minor B.L., Elliott V., Fernandez M., O’Neal L., McLeod L., Delacqua G., Delacqua F., Kirby J., et al. The REDCap consortium: Building an international community of software platform partners. J. Biomed. Inform. 2019;95:103208. doi: 10.1016/j.jbi.2019.103208.
    1. Grammer J.K., Carrasco M., Gehring W.J., Morrison F.J. Age-related changes in error processing in young children: A school-based investigation. Dev. Cogn. Neurosci. 2014;9:93–105. doi: 10.1016/j.dcn.2014.02.001.
    1. Tanofsky-Kraff M., Yanovski J., Ba N.A.S., Olsen C.H., Bs J.G., Yanovski J.A. A prospective study of loss of control eating for body weight gain in children at high risk for adult obesity. Int. J. Eat. Disord. 2009;42:26–30. doi: 10.1002/eat.20580.
    1. Ravussin E. Energy Metabolism in Obesity: Studies in the Pima Indians. Diabetes Care. 1993;16:232–238. doi: 10.2337/diacare.16.1.232.
    1. Lange S.J., Kompaniyets L., Freedman D.S., Kraus E.M., Porter R., Blanck H.M., Goodman A.B. Dnp3 Longitudinal Trends in Body Mass Index before and during the COVID-19 Pandemic among Persons Aged 2–19 Years—United States, 2018–2020. MMWR Morb. Mortal. Wkly. Rep. 2021;70:1278–1283. doi: 10.15585/mmwr.mm7037a3.
    1. Calvo D., Galioto R., Gunstad J., Spitznagel M.B. Uncontrolled eating is associated with reduced executive functioning. Clin. Obes. 2014;4:172–179. doi: 10.1111/cob.12058.
    1. Thivel D., Rumbold P., King N.A., Pereira B., Blundell J.E., Mathieu M.-E. Acute post-exercise energy and macronutrient intake in lean and obese youth: A systematic review and meta-analysis. Int. J. Obes. 2016;40:1469–1479. doi: 10.1038/ijo.2016.122.
    1. Hazell T.J., Islam H., Townsend L.K., Schmale M.S., Copeland J.L. Effects of exercise intensity on plasma concentrations of appetite-regulating hormones: Potential mechanisms. Appetite. 2016;98:80–88. doi: 10.1016/j.appet.2015.12.016.
    1. Ouerghi N., Feki M., Bragazzi N.L., Knechtle B., Hill L., Nikolaidis P.T., Bouassida A. Ghrelin Response to Acute and Chronic Exercise: Insights and Implications from a Systematic Review of the Literature. Sports Med. 2021;51:2389–2410. doi: 10.1007/s40279-021-01518-6.

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