Abstract
Background and objectives
Family-based behavioral treatment (FBT) is the recommended treatment for children with common obesity. However, there is a large variability in short- and long-term treatment response, and mechanisms for unsuccessful treatment outcomes are not fully understood. In this study, we tested if brain response to visual food cues among children with obesity before treatment predicted weight or behavioral outcomes during a 6-month behavioral weight management program and/or long-term relative weight maintenance over a 1-year follow-up period.
Subjects and methods
Thirty-seven children with obesity (age 9–11 years, 62% male) who entered active FBT (attended two or more sessions) and had outcome data. Brain activation was assessed at pretreatment by functional magnetic resonance imaging across an a priori set of appetite-processing brain regions that included the ventral and dorsal striatum, mOFC, amygdala, substantia nigra/ventral tegmental area, and insula in response to viewing food images before and after a standardized meal.
Results
Children with more robust reductions in brain activation to high-calorie food cue images following a meal had greater declines in BMI z-score during FBT (r = 0.42; 95% CI: 0.09, 0.66; P = 0.02) and greater improvements in Healthy Eating Index scores (r = −0.41; 95% CI: −0.67, −0.06; P = 0.02). In whole-brain analyses, greater activation in the ventromedial prefrontal cortex, specifically by high-calorie food cues, was predictive of better treatment outcomes (whole-brain cluster corrected P = 0.02). There were no significant predictors of relative weight maintenance, and initial behavioral or hormonal measures did not predict FBT outcomes.
Conclusions
Children’s brain responses to a meal prior to obesity treatment were related to treatment-based weight outcomes, suggesting that neurophysiologic factors and appetitive drive, more so than initial hormone status or behavioral characteristics, limit intervention success.
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References
Fryar CD, Carroll MD, OGden CL. Prevalence of overweight and obesity among children and adolescents: United States, 1962–1965 through 2011–2012. Health E-Stats. 2014.
U. S. Preventive Services Task Force, Grossman DC, Bibbins-Domingo K, Curry SJ, Barry MJ, Davidson KW, et al. Screening for obesity in children and adolescents: US Preventive Services Task Force Recommendation Statement. JAMA. 2017;317:2417–26.
Styne DM, Arslanian SA, Connor EL, Farooqi IS, Murad MH, Silverstein JH, et al. Pediatric obesity-assessment, treatment, and prevention: an Endocrine Society Clinical Practice Guideline. J Clin Endocrinol Metab. 2017;102:709–57.
Epstein LH, Paluch RA, Roemmich JN, Beecher MD. Family-based obesity treatment, then and now: twenty-five years of pediatric obesity treatment. Health Psychol. 2007;26:381–91.
Saelens BE, Lozano P, Scholz K. A randomized clinical trial comparing delivery of behavioral pediatric obesity treatment using standard and enhanced motivational approaches. J Pediatr Psychol. 2013;38:954–64.
Mead E, Brown T, Rees K, Azevedo LB, Whittaker V, Jones D, et al. Diet, physical activity and behavioural interventions for the treatment of overweight or obese children from the age of 6 to 11 years. Cochrane Database Syst Rev. 2017;6:CD012651.
Wilfley DE, Stein RI, Saelens BE, Mockus DS, Matt GE, Hayden-Wade HA, et al. Efficacy of maintenance treatment approaches for childhood overweight: a randomized controlled trial. JAMA. 2007;298:1661–73.
Danielsson P, Kowalski J, Ekblom O, Marcus C. Response of severely obese children and adolescents to behavioral treatment. Arch Pediatr Adolesc Med. 2012;166:1103–8.
Goldschmidt AB, Best JR, Stein RI, Saelens BE, Epstein LH, Wilfley DE. Predictors of child weight loss and maintenance among family-based treatment completers. J Consult Clin Psychol. 2014;82:1140–50.
Reinehr T, Kleber M, Lass N, Toschke AM. Body mass index patterns over 5 y in obese children motivated to participate in a 1-y lifestyle intervention: age as a predictor of long-term success. Am J Clin Nutr. 2010;91:1165–71.
Sabin MA, Ford A, Hunt L, Jamal R, Crowne EC, Shield JP. Which factors are associated with a successful outcome in a weight management programme for obese children? J Eval Clin Pract. 2007;13:364–8.
Shalitin S, Phillip M, Krepel-Volsky S. Predictors of successful weight reduction and maintenance in obese children and adolescents. Acta Paediatr. 2016;105:e42–6.
Goldschmidt AB, Stein RI, Saelens BE, Theim KR, Epstein LH, Wilfley DE. Importance of early weight change in a pediatric weight management trial. Pediatrics. 2011;128:e33–9.
Madsen KA, Garber AK, Mietus-Snyder ML, Orrell-Valente JK, Tran CT, Wlasiuk L, et al. A clinic-based lifestyle intervention for pediatric obesity: efficacy and behavioral and biochemical predictors of response. J Pediatr Endocrinol Metab. 2009;22:805–14.
Wiegand S, Keller KM, Lob-Corzilius T, Pott W, Reinehr T, Robl M, et al. Predicting weight loss and maintenance in overweight/obese pediatric patients. Horm Res Paediatr. 2014;82:380–7.
Best JR, Theim KR, Gredysa DM, Stein RI, Welch RR, Saelens BE, et al. Behavioral economic predictors of overweight children’s weight loss. J Consult Clin Psychol. 2012;80:1086–96.
Moens E, Braet C, Van Winckel M. An 8-year follow-up of treated obese children: children’s, process and parental predictors of successful outcome. Behav Res Ther. 2010;48:626–33.
Kumar S, King EC, Christison AL, Kelly AS, Ariza AJ, Borzutzky C, et al. Health Outcomes of Youth in Clinical Pediatric Weight Management Programs in POWER. J Pediatr. 2019;208:57–65.e4.
Burger KS, Berner LA. A functional neuroimaging review of obesity, appetitive hormones and ingestive behavior. Physiol Behav. 2014;136:121–7.
Martin LE, Holsen LM, Chambers RJ, Bruce AS, Brooks WM, Zarcone JR, et al. Neural mechanisms associated with food motivation in obese and healthy weight adults. Obesity. 2010;18:254–60.
Rothemund Y, Preuschhof C, Bohner G, Bauknecht HC, Klingebiel R, Flor H, et al. Differential activation of the dorsal striatum by high-calorie visual food stimuli in obese individuals. Neuroimage. 2007;37:410–21.
Stoeckel LE, Weller RE, Cook EW, Twieg DB, Knowlton RC, Cox JE. Widespread reward-system activation in obese women in response to pictures of high-calorie foods. Neuroimage. 2008;41:636–47.
Bruce AS, Holsen LM, Chambers RJ, Martin LE, Brooks WM, Zarcone JR, et al. Obese children show hyperactivation to food pictures in brain networks linked to motivation, reward and cognitive control. Int J Obes. 2010;34:1494–500.
Davids S, Lauffer H, Thoms K, Jagdhuhn M, Hirschfeld H, Domin M, et al. Increased dorsolateral prefrontal cortex activation in obese children during observation of food stimuli. Int J Obes. 2010;34:94–104.
Roth CL, Melhorn SJ, Elfers CT, Scholz K, De Leon MRB, Rowland M, et al. Central nervous system and peripheral hormone responses to a meal in children. J Clin Endocrinol Metab. 2019;104:1471–83.
Melhorn SJ, Askren MK, Chung WK, Kratz M, Bosch TA, Tyagi V, et al. FTO genotype impacts food intake and corticolimbic activation. Am J Clin Nutr. 2018;107:145–54.
Demos KE, Heatherton TF, Kelley WM. Individual differences in nucleus accumbens activity to food and sexual images predict weight gain and sexual behavior. J Neurosci. 2012;32:5549–52.
Holsen LM, Davidson P, Cerit H, Hye T, Moondra P, Haimovici F, et al. Neural predictors of 12-month weight loss outcomes following bariatric surgery. Int J Obes. 2018;42:785–93.
Murdaugh DL, Cox JE, Cook EW III, Weller RE. fMRI reactivity to high-calorie food pictures predicts short- and long-term outcome in a weight-loss program. Neuroimage. 2012;59:2709–21.
Mehta S, Melhorn SJ, Smeraglio A, Tyagi V, Grabowski T, Schwartz MW, et al. Regional brain response to visual food cues is a marker of satiety that predicts food choice. Am J Clin Nutr. 2012;96:989–99.
Guenther PM, Casavale KO, Reedy J, Kirkpatrick SI, Hiza HA, Kuczynski KJ, et al. Update of the Healthy Eating Index: HEI-2010. J Acad Nutr Diet. 2013;113:569–80.
Evenson KR, Catellier DJ, Gill K, Ondrak KS, McMurray RG. Calibration of two objective measures of physical activity for children. J Sports Sci. 2008;26:1557–65.
Mifflin MD, St Jeor ST, Hill LA, Scott BJ, Daugherty SA, Koh YO. A new predictive equation for resting energy expenditure in healthy individuals. Am J Clin Nutr. 1990;51:241–7.
Cleary J, Daniells S, Okely AD, Batterham M, Nicholls J. Predictive validity of four bioelectrical impedance equations in determining percent fat mass in overweight and obese children. J Am Diet Assoc. 2008;108:136–9.
Schaefer F, Georgi M, Zieger A, Scharer K. Usefulness of bioelectric impedance and skinfold measurements in predicting fat-free mass derived from total body potassium in children. Pediatr Res. 1994;35:617–24.
Shields BJ, Palermo TM, Powers JD, Grewe SD, Smith GA. Predictors of a child’s ability to use a visual analogue scale. Child Care Health Dev. 2003;29:281–90.
Epstein LH, Squires S. The stoplight diet for children. Boston, MA: Little, Brown and Co; 1988.
Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28:412–9.
Goldstone AP, de Hernandez CGP, Beaver JD, Muhammed K, Croese C, Bell G, et al. Fasting biases brain reward systems towards high-calorie foods. Eur J Neurosci. 2009;30:1625–35.
Holsen LM, Savage CR, Martin LE, Bruce AS, Lepping RJ, Ko E, et al. Importance of reward and prefrontal circuitry in hunger and satiety: Prader-Willi syndrome vs simple obesity. Int J Obesity. 2012;36:638–47.
Holsen LM, Zarcone JR, Brooks WM, Butler MG, Thompson TI, Ahluwalia JS, et al. Neural mechanisms underlying hyperphagia in Prader-Willi syndrome. Obesity. 2006;14:1028–37.
Roth CL, Aylward E, Liang O, Kleinhans NM, Pauley G, Schur EA. Functional neuroimaging in craniopharyngioma: a useful tool to better understand hypothalamic obesity? Obes Facts. 2012;5:243–53.
Kelley AE, Baldo BA, Pratt WE, Will MJ. Corticostriatal-hypothalamic circuitry and food motivation: integration of energy, action and reward. Physiol Behav. 2005;86:773–95.
Palmiter RD. Dopamine signaling in the dorsal striatum is essential for motivated behaviors: lessons from dopamine-deficient mice. Ann N Y Acad Sci. 2008;1129:35–46.
Small DM, Jones-Gotman M, Dagher A. Feeding-induced dopamine release in dorsal striatum correlates with meal pleasantness ratings in healthy human volunteers. Neuroimage. 2003;19:1709–15.
Ghahremani DG, Lee B, Robertson CL, Tabibnia G, Morgan AT, De Shetler N, et al. Striatal dopamine D2/D3 receptors mediate response inhibition and related activity in frontostriatal neural circuitry in humans. J Neurosci. 2012;32:7316–24.
Gottfried JA, O’Doherty J, Dolan RJ. Encoding predictive reward value in human amygdala and orbitofrontal cortex. Science. 2003;301:1104–7.
Rolls ET. Taste, olfactory and food texture reward processing in the brain and obesity. Int J Obes. 2011;35:550–61.
Weygandt M, Mai K, Dommes E, Leupelt V, Hackmack K, Kahnt T, et al. The role of neural impulse control mechanisms for dietary success in obesity. Neuroimage. 2013;83:669–78.
Goldman RL, Canterberry M, Borckardt JJ, Madan A, Byrne TK, George MS, et al. Executive control circuitry differentiates degree of success in weight loss following gastric-bypass surgery. Obesity. 2013;21:2189–96.
Bartra O, McGuire JT, Kable JW. The valuation system: a coordinate-based meta-analysis of BOLD fMRI experiments examining neural correlates of subjective value. Neuroimage. 2013;76:412–27.
Hare TA, Camerer CF, Rangel A. Self-control in decision-making involves modulation of the vmPFC valuation system. Science. 2009;324:646–8.
Neseliler S, Hu W, Larcher K, Zacchia M, Dadar M, Scala SG, et al. Neurocognitive and hormonal correlates of voluntary weight loss in humans. Cell Metab. 2019;29:39–49.e4.
Hare TA, Malmaud J, Rangel A. Focusing attention on the health aspects of foods changes value signals in vmPFC and improves dietary choice. J Neurosci. 2011;31:11077–87.
Cavanna AE, Trimble MR. The precuneus: a review of its functional anatomy and behavioural correlates. Brain: J Neurol. 2006;129:564–83.
Golby A, Silverberg G, Race E, Gabrieli S, O’Shea J, Knierim K, et al. Memory encoding in Alzheimer’s disease: an fMRI study of explicit and implicit memory. Brain: J Neurol. 2005;128:773–87.
Grill-Spector K, Kourtzi Z, Kanwisher N. The lateral occipital complex and its role in object recognition. Vision Res. 2001;41:1409–22.
Gettens KM, Gorin AA. Executive function in weight loss and weight loss maintenance: a conceptual review and novel neuropsychological model of weight control. J Behav Med. 2017;40:687–701.
Juonala M, Magnussen CG, Berenson GS, Venn A, Burns TL, Sabin MA, et al. Childhood adiposity, adult adiposity, and cardiovascular risk factors. N Engl J Med. 2011;365:1876–85.
Reinehr T, Lass N, Toschke C, Rothermel J, Lanzinger S, Holl RW. Which amount of BMI-SDS reduction is necessary to improve cardiovascular risk factors in overweight children? J Clin Endocrinol Metab. 2016;101:3171–9.
Acknowledgements
This work was supported by the National Institutes of Health award R01DK098466 (CLR), P30DK035816 (University of Washington Nutrition and Obesity Research Center); and the University of Washington Institute of Translational Health Sciences (UL1TR002319). We would like to thank Sue Kearns and Holly Callahan for their contributions to study planning and execution, Mark Abbey-Lambertz for support during treatment visits and execution of study assessments, and Gabrielle D’Ambrosio, Habiba Mohamed and Cordelia Franklin for their excellent support for performing the study visits.
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EAS, BES, and CLR designed the study; SJM, KS, CTE, MGR, and MRBDL acquired data; CTE performed assays; SJM and EAS designed and/or performed fMRI analyses; SJM, CTE, CLR, and EAS performed statistical analyses; EAS, SJM, CTE, BES, and CLR wrote the manuscript.
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Schur, E.A., Melhorn, S.J., Scholz, K. et al. Child neurobiology impacts success in family-based behavioral treatment for children with obesity. Int J Obes 44, 2011–2022 (2020). https://doi.org/10.1038/s41366-020-0644-1
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DOI: https://doi.org/10.1038/s41366-020-0644-1
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