Signs of Warning: Do Health Warning Messages on Sweets Affect the Neural Prefrontal Cortex Activity?
<p>Four different health warning messages were created. For the “Stop” examination condition, a stop sign was used (two pictures on the left). For the “Shock” examination condition, two shocking pictures (one of a denture affected by caries and one of a foot with diabetic foot syndrome) were used. The textual information informed about caries and the diabetic foot syndrome and was identical for both types of warning messages.</p> "> Figure 2
<p>Experimental Design of the fNIRS experiment. A block design with three experimental conditions (“Shock”, “Stop”, and “Neutral”) was used. The order of the trials was randomized.</p> "> Figure 3
<p>(<b>Left</b>) Topographical layout of the NIRx headband. The red numbers (1–8) point out the placement of the light sources, and the blue numbers (1–7) the placement of the light detectors. One source and one detector result in one measurement channel, visualized through the black channel numbers (1–22). The reference points refer to the EEG 10–20 system. (<b>Right</b>) The coverage of the headband is shown on the ICBM 152 head model. The color shadings do not have any meaning here.</p> "> Figure 4
<p>Significantly decreased neural prefrontal cortex activation for the main effects of the “Neutral” (<b>left</b> brain), “Stop” (<b>middle</b> brain), and “Shock” condition (<b>right</b> brain). Activation threshold set to <span class="html-italic">p</span> < 0.05.</p> "> Figure 5
<p>Significantly increased neural prefrontal cortex activation for the contrast between the “Stop” condition versus the “Neutral” condition: channel 22: t(78) = 1.93, <span class="html-italic">p ≤</span> 0.1, d = 0.437; channel 21: t(78) = 1.69, <span class="html-italic">p ≤</span> 0.1, d = 0.382; channel 19: t(78) = 1.97, <span class="html-italic">p ≤</span> 0.1, d = 0.315, and channel 17: t(78) = 1.71, <span class="html-italic">p ≤</span> 0.1, d = 0.446. The activation threshold was set to <span class="html-italic">p</span> < 0.1.</p> "> Figure 6
<p>Significantly increased neural prefrontal cortex activation for the contrast between the “Shock” condition versus the “Neutral” condition: channel 15: t (78) = 1.757, <span class="html-italic">p ≤</span> 0.1, d = 0.398. The activation threshold was set to <span class="html-italic">p</span> < 0.1.</p> "> Figure 7
<p>Contrast of the NormalBMI group (n = 56) with the HighBMI group (n = 22) for the two experimental conditions. The participants with a normal BMI showed significantly increased prefrontal cortex activation compared to the ones with a high BMI in both experimental conditions. <b>Left</b> brain: For the NormalBMI group, neural activity in the dlPFC increased when exposed to the “Stop” condition. <b>Right</b> brain: For the NormalBMI group, neural activity in the dlPFC increased when exposed to the “Shock” condition.</p> ">
Abstract
:1. Introduction
2. Materials and Methods
2.1. Participants
2.2. Stimuli
2.3. Experimental Design
2.4. Study Procedure
2.5. fNIRS Measurement and Data Analysis
2.6. Direct Assessment (Questionnaire)
3. Results
3.1. Main Effects of the Experimental Conditions
3.2. Experimental Conditions Compared to Control Condition
3.3. Group Comparison of High vs. Normal BMI
3.4. Direct Assessment (Questionnaire)
4. Discussion
Strengths and Limitations
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- WHO (World Health Organization). Fact Sheet Obesity and Overweight. Available online: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight (accessed on 5 November 2019).
- DESTATIS (Statistisches Bundesamt). Mikrozensus—Fragen zur Gesundheit Körpermaße der Bevölkerung 2017; Bundesamt, S., Ed.; DESTATIS: Wiesbaden, Germany, 2018. [Google Scholar]
- Guh, D.P.; Zhang, W.; Bansback, N.; Amarsi, Z.; Birmingham, C.L.; Anis, A.H. The incidence of co-morbidities related to obesity and overweight: A systematic review and meta-analysis. BMC Public Health 2009, 9, 88. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Yates, N.; Teuner, C.M.; Hunger, M.; Holle, R.; Stark, R.; Laxy, M.; Hauner, H.; Peters, A.; Wolfenstetter, S.B. The economic burden of obesity in Germany: Results from the population-based KORA studies. Obes. Facts 2017, 9, 397–409. [Google Scholar] [CrossRef] [PubMed]
- Whelan, M.E.; Morgan, P.S.; Sherar, L.B.; Orme, M.W.; Esliger, D.W. Can functional magnetic resonance imaging studies help with the optimization of health messaging for lifestyle behavior change? A systematic review. Prev. Med. 2017, 99, 185–196. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Swinburn, B.A.; Caterson, I.; Seidell, J.; James, W. Diet, nutrition and the prevention of excess weight gain and obesity. Public Health Nutr. 2004, 7, 123–146. [Google Scholar] [CrossRef]
- BMEL (Bundesministerium für Ernährung und Landwirtschaft). Versorgung mit Zucker in Weißzuckerwert; BMEL: Bonn/Berlin, Germany, 2019. [Google Scholar]
- WHO (World Health Organization). Guideline: Sugars Intake for Adult and Children. Available online: https://www.who.int/nutrition/publications/guidelines/sugars_intake/en/ (accessed on 5 November 2019).
- Cohen, D.A.; Lesser, L.I. Obesity prevention at the point of purchase. Obes. Rev. 2016, 17, 389–396. [Google Scholar] [CrossRef] [Green Version]
- Alonso-Alonso, M.; Woods, S.C.; Pelchat, M.; Grigson, P.S.; Stice, E.; Farooqi, S.; Khoo, C.S.; Mattes, R.D.; Beauchamp, G.K. Food reward system: Current perspectives and future research needs. Nutr. Rev. 2015, 73, 296–307. [Google Scholar] [CrossRef]
- Inauen, J.; Shrout, P.E.; Bolger, N.; Stadler, G.; Scholz, U. Mind the gap? An intensive longitudinal study of between-person and within-person intention-behavior relations. Ann. Behav. Med. 2016, 50, 516–522. [Google Scholar] [CrossRef] [Green Version]
- Simmons, W.K.; Martin, A.; Barsalou, L.W. Pictures of appetizing foods activate gustatory cortices for taste and reward. Cereb. Cortex 2005, 15, 1602–1608. [Google Scholar] [CrossRef]
- Keesman, M.; Aarts, H.; Vermeent, S.; Häfner, M.; Papies, E.K. Consumption simulations induce salivation to food cues. PLoS ONE 2016, 11, e0165449. [Google Scholar] [CrossRef] [Green Version]
- Nederkoorn, C.; Smulders, F.T.Y.; Jansen, A. Cephalic phase responses, craving and food intake in normal subjects. Appetite 2000, 35, 45–55. [Google Scholar] [CrossRef] [Green Version]
- Nederkoorn, C.; Houben, K.; Hofmann, W.; Roefs, A.; Jansen, A. Control yourself or just eat what you Like? Weight gain over a year is predicted by an interactive effect of response inhibition and implicit preference for snack foods. Health Psychol. Off. J. Div. Health Psychol. Am. Psychol. Assoc. 2010, 29, 389–393. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Pursey, K.M.; Stanwell, P.; Callister, R.J.; Brain, K.; Collins, C.E.; Burrows, T.L. Neural responses to visual food cues according to weight status: A systematic review of functional magnetic resonance imaging studies. Front. Nutr. 2014, 1, 7. [Google Scholar] [CrossRef] [PubMed]
- Stoeckel, L.E.; Weller, R.E.; Cook, E.W.; Twieg, D.B.; Knowlton, R.C.; Cox, J.E. Widespread reward-system activation in obese women in response to pictures of high-calorie foods. NeuroImage 2008, 41, 636–647. [Google Scholar] [CrossRef] [PubMed]
- Batterink, L.; Yokum, S.; Stice, E. Body mass correlates inversely with inhibitory control in response to food among adolescent girls: An fMRI study. NeuroImage 2010, 52, 1696–1703. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Brooks, S.J.; Cedernaes, J.; Schiöth, H.B. Increased prefrontal and parahippocampal activation with reduced dorsolateral prefrontal and insular cortex activation to food images in obesity: A meta-analysis of fMRI studies. PLoS ONE 2013, 8, e60393. [Google Scholar] [CrossRef] [PubMed]
- Mehl, N.; Mueller-Wieland, L.; Mathar, D.; Horstmann, A. Retraining automatic action tendencies in obesity. Physiol. Behav. 2018, 192, 50–58. [Google Scholar] [CrossRef]
- Mehl, N.; Morys, F.; Villringer, A.; Horstmann, A. Unhealthy yet avoidable—How cognitive bias modification alters behavioral and brain responses to food cues in individuals with obesity. Nutrients 2019, 11, 874. [Google Scholar] [CrossRef] [Green Version]
- Fürtjes, S.; King, J.A.; Goeke, C.; Seidel, M.; Goschke, T.; Horstmann, A.; Ehrlich, S. Automatic and controlled processing: Implications for eating behavior. Nutrients 2020, 12, 1097. [Google Scholar] [CrossRef] [Green Version]
- Dohle, S.; Diel, K.; Hofmann, W. Executive functions and the self-regulation of eating behavior: A review. Appetite 2017, 124. [Google Scholar] [CrossRef]
- Boswell, R.G.; Kober, H. Food cue reactivity and craving predict eating and weight gain: A meta-analytic review. Obes. Rev. 2016, 17, 159–177. [Google Scholar] [CrossRef]
- Davidson, T.L.; Jones, S.; Roy, M.; Stevenson, R.J. The cognitive control of eating and body weight: It’s more than what you “think”. Front. Psychol. 2019, 10. [Google Scholar] [CrossRef] [PubMed]
- Adams, J.; Hart, W.; Gilmer, L.; Lloyd-Richardson, E.; Alex Burton, K. Concrete images of the sugar content in sugar-sweetened beverages reduces attraction to and selection of these beverages. Appetite 2014, 83, 10–18. [Google Scholar] [CrossRef] [PubMed]
- Billich, N.; Blake, M.R.; Backholer, K.; Cobcroft, M.; Li, V.; Peeters, A. The effect of sugar-sweetened beverage front-of-pack labels on drink selection, health knowledge and awareness: An online randomised controlled trial. Appetite 2018, 128, 233–241. [Google Scholar] [CrossRef] [PubMed]
- Roberto, C.A.; Wong, D.; Musicus, A.; Hammond, D. The influence of sugar-sweetened beverage health warning labels on parents’ choices. Pediatrics 2016, 137, e20153185. [Google Scholar] [CrossRef] [Green Version]
- VanEpps, E.M.; Roberto, C.A. The influence of sugar-sweetened beverage warnings: A randomized trial of adolescents’ choices and beliefs. Am. J. Prev. Med. 2016, 51, 664–672. [Google Scholar] [CrossRef] [Green Version]
- Rosenblatt, D.H.; Summerell, P.; Ng, A.; Dixon, H.; Murawski, C.; Wakefield, M.; Bode, S. Food product health warnings promote dietary self-control through reductions in neural signals indexing food cue reactivity. NeuroImage Clin. 2018, 18, 702–712. [Google Scholar] [CrossRef]
- Rosenblatt, D.H.; Bode, S.; Dixon, H.; Murawski, C.; Summerell, P.; Ng, A.; Wakefield, M. Health warnings promote healthier dietary decision making: Effects of positive versus negative message framing and graphic versus text-based warnings. Appetite 2018, 127, 280–288. [Google Scholar] [CrossRef]
- Corvalán, C.; Reyes, M.; Garmendia, M.L.; Uauy, R. Structural responses to the obesity and non-communicable diseases epidemic: Update on the Chilean law of food labelling and advertising. Obes. Rev. 2019, 20, 367–374. [Google Scholar] [CrossRef]
- Acton, R.B.; Hammond, D. The impact of price and nutrition labelling on sugary drink purchases: Results from an experimental marketplace study. Appetite 2018, 121, 129–137. [Google Scholar] [CrossRef] [Green Version]
- Bollard, T.; Maubach, N.; Walker, N.; Ni Mhurchu, C. Effects of plain packaging, warning labels, and taxes on young people’s predicted sugar-sweetened beverage preferences: An experimental study. Int. J. Behav. Nutr. Phys. Act. 2016, 13, 95. [Google Scholar] [CrossRef] [Green Version]
- Donnelly, G.E.; Zatz, L.Y.; Svirsky, D.; John, L.K. The effect of graphic warnings on sugary-drink purchasing. Psychol. Sci. 2018, 29, 1321–1333. [Google Scholar] [CrossRef] [PubMed]
- Hammond, D. Health warning messages on tobacco products: A review. Tob. Control 2011, 20, 327–337. [Google Scholar] [CrossRef] [PubMed]
- Mantzari, E.; Vasiljevic, M.; Turney, I.; Pilling, M.; Marteau, T. Impact of warning labels on sugar-sweetened beverages on parental selection: An online experimental study. Prev. Med. Rep. 2018, 12, 259–267. [Google Scholar] [CrossRef] [PubMed]
- Noar, S.M.; Hall, M.G.; Francis, D.B.; Ribisl, K.M.; Pepper, J.K.; Brewer, N.T. Pictorial cigarette pack warnings: A meta-analysis of experimental studies. Tob. Control 2016, 25, 341–354. [Google Scholar] [CrossRef] [PubMed]
- Stafford, L.D.; Salmon, J. Alcohol health warnings can influence the speed of consumption. J. Public Health 2017, 25, 147–154. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sutton, J.A.; Yang, S.; Cappella, J.N. Perceived effectiveness of objective features of pictorial warning messages. Tob. Control 2018. [Google Scholar] [CrossRef]
- Wigg, S.; Stafford, L.D. Health warnings on alcoholic beverages: Perceptions of the health risks and intentions towards alcohol consumption. PLoS ONE 2016, 11, e0153027. [Google Scholar] [CrossRef] [Green Version]
- Ariely, D.; Berns, G.S. Neuromarketing: The hope and hype of neuroimaging in business. Nat. Rev. Neurosci. 2010, 11, 284–292. [Google Scholar] [CrossRef] [Green Version]
- Kopton, I.M.; Kenning, P. Near-infrared spectroscopy (NIRS) as a new tool for neuroeconomic research. Front. Hum. Neurosci. 2014, 8, 549. [Google Scholar] [CrossRef] [Green Version]
- Pinti, P.; Tachtsidis, I.; Hamilton, A.; Hirsch, J.; Aichelburg, C.; Gilbert, S.; Burgess, P.W. The present and future use of functional near-infrared spectroscopy (fNIRS) for cognitive neuroscience. Ann. N. Y. Acad. Sci. 2018, 1464, 5–29. [Google Scholar] [CrossRef]
- Delli Bovi, A.P.; Di Michele, L.; Laino, G.; Vajro, P. Obesity and obesity related diseases, sugar consumption and bad oral health: A fatal epidemic mixtures: The pediatric and odontologist point of view. Transl. Med. UniSa 2017, 16, 11–16. [Google Scholar] [PubMed]
- Ferrari, M.; Quaresima, V. A brief review on the history of human functional near-infrared spectroscopy (fNIRS) development and fields of application. NeuroImage 2012, 63, 921–935. [Google Scholar] [CrossRef] [PubMed]
- Masataka, N.; Perlovsky, L.; Hiraki, K. Near-infrared spectroscopy (NIRS) in functional research of prefrontal cortex. Front. Hum. Neurosci. 2015, 9, 274. [Google Scholar] [CrossRef] [Green Version]
- Meyerding, S.G.H.; Mehlhose, C.M. Can neuromarketing add value to the traditional marketing research? An exemplary experiment with functional near-infrared spectroscopy (fNIRS). J. Bus. Res. 2020, 107, 172–185. [Google Scholar] [CrossRef]
- Hoshi, Y.; Kobayashi, N.; Tamura, M. Interpretation of near-infrared spectroscopy signals: A study with a newly developed perfused rat brain model. J. Appl. Physiol. 2001, 90, 1657–1662. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Jurcak, V.; Tsuzuki, D.; Dan, I. 10/20, 10/10, and 10/5 systems revisited: Their validity as relative head-surface-based positioning systems. NeuroImage 2007, 34, 1600–1611. [Google Scholar] [CrossRef] [PubMed]
- Mayring, P. Qualitative inhaltsanalyse. In Handbuch Qualitative Forschung in der Psychologie; Mey, G., Mruck, K., Eds.; VS Verlag für Sozialwissenschaften: Wiesbaden, Germany, 2010; pp. 601–613. [Google Scholar] [CrossRef] [Green Version]
- Chua, H.F.; Ho, S.S.; Jasinska, A.J.; Polk, T.A.; Welsh, R.C.; Liberzon, I.; Strecher, V.J. Self-related neural response to tailored smoking-cessation messages predicts quitting. Nat. Neurosci. 2011, 14, 426–427. [Google Scholar] [CrossRef]
- Dinh-Williams, L.; Mendrek, A.; Bourque, J.; Potvin, S. Where there’s smoke, there’s fire: The brain reactivity of chronic smokers when exposed to the negative value of smoking. Prog. Neuropsychopharmacol. Biol. Psychiatry 2014, 50, 66–73. [Google Scholar] [CrossRef]
- Newman-Norlund, R.D.; Thrasher, J.F.; Fridriksson, J.; Brixius, W.; Froeliger, B.; Hammond, D.; Cummings, M.K. Neural biomarkers for assessing different types of imagery in pictorial health warning labels for cigarette packaging: A cross-sectional study. BMJ Open 2014, 4, e006411. [Google Scholar] [CrossRef]
- Wang, A.-L.; Lowen, S.B.; Romer, D.; Giorno, M.; Langleben, D.D. Emotional reaction facilitates the brain and behavioural impact of graphic cigarette warning labels in smokers. Tob. Control 2015, 24, 225–232. [Google Scholar] [CrossRef]
- Kringelbach, M.L. The human orbitofrontal cortex: Linking reward to hedonic experience. Nat. Rev. Neurosci. 2005, 6, 691–702. [Google Scholar] [CrossRef] [PubMed]
- Peters, J.; Büchel, C. Neural representations of subjective reward value. Behav. Brain Res. 2010, 213, 135–141. [Google Scholar] [CrossRef] [PubMed]
- Blechert, J.; Klackl, J.; Miedl, S.F.; Wilhelm, F.H. To eat or not to eat: Effects of food availability on reward system activity during food picture viewing. Appetite 2016, 99, 254–261. [Google Scholar] [CrossRef]
- Gottfried, J.A.; O’Doherty, J.; Dolan, R.J. Encoding predictive reward value in human amygdala and orbitofrontal cortex. Science 2003, 301, 1104–1107. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kringelbach, M.L. Food for thought: Hedonic experience beyond homeostasis in the human brain. Neuroscience 2004, 126, 807–819. [Google Scholar] [CrossRef] [PubMed]
- Kringelbach, M.L.; Rolls, E.T. The functional neuroanatomy of the human orbitofrontal cortex: Evidence from neuroimaging and neuropsychology. Prog. Neurobiol. 2004, 72, 341–372. [Google Scholar] [CrossRef]
- O’Doherty, J.P.; Deichmann, R.; Critchley, H.D.; Dolan, R.J. Neural responses during anticipation of a primary taste reward. Neuron 2002, 33, 815–826. [Google Scholar] [CrossRef] [Green Version]
- van der Laan, L.N.; de Ridder, D.T.; Viergever, M.A.; Smeets, P.A. The first taste is always with the eyes: A meta-analysis on the neural correlates of processing visual food cues. Neuroimage 2011, 55, 296–303. [Google Scholar] [CrossRef]
- Zald, D.H. Orbitofrontal cortex contributions to food selection and decision making. Ann. Behav. Med. Publ. Soc. Behav. Med. 2009, 38 (Suppl. 1), S18–S24. [Google Scholar] [CrossRef]
- Hollmann, M.; Hellrung, L.; Pleger, B.; Schlögl, H.; Kabisch, S.; Stumvoll, M.; Villringer, A.; Horstmann, A. Neural correlates of the volitional regulation of the desire for food. Int. J. Obes. 2012, 36, 648–655. [Google Scholar] [CrossRef] [Green Version]
- Chua, H.F.; Liberzon, I.; Welsh, R.C.; Strecher, V.J. Neural correlates of message tailoring and self-relatedness in smoking cessation programming. Biol. Psychiatry 2009, 65, 165–168. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Han, J.E.; Boachie, N.; Garcia-Garcia, I.; Michaud, A.; Dagher, A. Neural correlates of dietary self-control in healthy adults: A meta-analysis of functional brain imaging studies. Physiol. Behav. 2018, 192, 98–108. [Google Scholar] [CrossRef] [PubMed]
- Hare, T.A.; 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. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Hare, T.A.; Camerer, C.F.; Rangel, A. Self-control in decision-making involves modulation of the vmPFC valuation system. Science 2009, 324, 646–648. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kober, H.; Mende-Siedlecki, P.; Kross, E.F.; Weber, J.; Mischel, W.; Hart, C.L.; Ochsner, K.N. Prefrontal–striatal pathway underlies cognitive regulation of craving. Proc. Natl. Acad. Sci. USA 2010, 107, 14811–14816. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Yokum, S.; Stice, E. Cognitive regulation of food craving: Effects of three cognitive reappraisal strategies on neural response to palatable foods. Int. J. Obes. 2013, 37, 1565–1570. [Google Scholar] [CrossRef] [Green Version]
- Do, K.T.; Galván, A. FDA cigarette warning labels lower craving and elicit frontoinsular activation in adolescent smokers. Soc. Cogn. Affect. Neurosci. 2015, 10, 1484–1496. [Google Scholar] [CrossRef] [Green Version]
- Enax, L.; Hu, Y.; Trautner, P.; Weber, B. Nutrition labels influence value computation of food products in the ventromedial prefrontal cortex. Obesity 2015, 23, 786–792. [Google Scholar] [CrossRef]
- Ang, F.J.L.; Agrawal, S.; Finkelstein, E.A. Pilot randomized controlled trial testing the influence of front-of-pack sugar warning labels on food demand. BMC Public Health 2019, 19, 164. [Google Scholar] [CrossRef]
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Mehlhose, C.; Risius, A. Signs of Warning: Do Health Warning Messages on Sweets Affect the Neural Prefrontal Cortex Activity? Nutrients 2020, 12, 3903. https://doi.org/10.3390/nu12123903
Mehlhose C, Risius A. Signs of Warning: Do Health Warning Messages on Sweets Affect the Neural Prefrontal Cortex Activity? Nutrients. 2020; 12(12):3903. https://doi.org/10.3390/nu12123903
Chicago/Turabian StyleMehlhose, Clara, and Antje Risius. 2020. "Signs of Warning: Do Health Warning Messages on Sweets Affect the Neural Prefrontal Cortex Activity?" Nutrients 12, no. 12: 3903. https://doi.org/10.3390/nu12123903