Risk of eating disorder and sociocultural influence on appearance in gym-going women: the role of diet
DOI:
https://doi.org/10.56294/mw2025884Keywords:
eating disorder, sociocultural influence, body ideal, social pressure, dietAbstract
Introduction. The risk of eating disorder symptoms (ED-R) among gym-attending women is linked to sociocultural influences on appearance, including thin-ideal internalization (IB), muscular-ideal internalization (IM), and pressures from peers (PP), family (FP), and media (MP). A network approach enables the characterization of their interdependence.
Objective. To compare the architecture and centrality of ED-R–sociocultural networks according to diet adherence (yes/no). Method. Cross-sectional study with women attending gyms. The EAT-25 (ED-R) and SATAQ (IB, IM, PP, FP, MP) were administered. Networks were estimated using EBICglasso; strength, betweenness, closeness, and expected influence were computed; accuracy was assessed via bootstrapping.
Results. Both networks included six nodes (15 possible edges). Without diet adherence: a less dense network, with PP and ED-R as the most central nodes, and IB showing moderate magnitudes. With diet adherence: a denser network, where IB emerged with the highest positive expected influence; ED-R retained structural centrality (high betweenness/closeness) but displayed negative expected influence; PP maintained positive influence with low strength; IM and MP remained peripheral.
Discussion. Diet adherence was associated with increased density and functional reorganization: sociocultural propagation concentrated in IB, while ED-R acted as a structural but negatively influential node.
Conclusions. Diet adherence reconfigures the pathways between ED-R and sociocultural factors (IB, IM, PP, FP, MP). Longitudinal and interventional studies are recommended to test causality and design targeted strategies focusing on IB and PP.
References
1. Barakat S, McLean SA, Bryant E, Le A, Marks P, National Eating Disorder Research Consortium, et al. Risk factors for eating disorders: Findings from a rapid review. Journal of Eating Disorders. 2023;11. https://doi.org/10.1186/s40337-022-00717-4 DOI: https://doi.org/10.1186/s40337-022-00717-4
2. Solmi M, Radua J, Stubbs B, Ricca V, Moretti D, Busatta D, et al. Risk factors for eating disorders: An umbrella review of published meta-analyses. Brazilian Journal of Psychiatry. 2021;43(3):314-323. https://doi.org/10.1590/1516-4446-2020-1099 DOI: https://doi.org/10.1590/1516-4446-2020-1099
3. Gjestvang C, Mathisen TF, Bratland-Sanda S, Haakstad LAH. The risk of disordered eating in fitness club members—a cross-sectional study. Sports. 2024;12(12):343. https://doi.org/10.3390/sports12120343 DOI: https://doi.org/10.3390/sports12120343
4. Lev Arey D, Sagi A, Blatt A. The relationship between exercise addiction, eating disorders, and insecure attachment styles among recreational exercisers. J Eat Disord. 2023;11:131. doi:10.1186/s40337-023-00855-3. DOI: https://doi.org/10.1186/s40337-023-00855-3
5. Keery H, van den Berg P, Thompson JK. An evaluation of the Tripartite Influence Model of body dissatisfaction and eating disturbance with adolescent girls. Body Image. 2004;1(3):237-251. https://doi.org/10.1016/j.bodyim.2004.03.001 DOI: https://doi.org/10.1016/j.bodyim.2004.03.001
6. Rodgers RF, McLean SA, Paxton SJ. Longitudinal relationships among internalization of the media ideal, peer social comparison, and body dissatisfaction: Implications for the tripartite influence model. Developmental Psychology. 2015;51(5):706-713. https://doi.org/10.1037/dev0000013 DOI: https://doi.org/10.1037/dev0000013
7. Thompson JK, Heinberg LJ, Altabe M, Tantleff-Dunn S. Exacting beauty: Theory, assessment, and treatment of body image disturbance. Washington, DC: American Psychological Association; 1999. https://doi.org/10.1037/10312-000 DOI: https://doi.org/10.1037/10312-000
8. Bennett BL, Wagner AF, Marshall RD, Latner JD. Appearance pressure from the media mediates the relationship between internalized weight bias and eating disorder risk for young women: A cross-sectional study. Journal of the Academy of Nutrition and Dietetics. 2025;125(10):1534-1541. https://doi.org/10.1016/j.jand.2025.06.031 DOI: https://doi.org/10.1016/j.jand.2025.06.031
9. Dahlgren CL, Sundgot-Borgen C, Kvalem IL, Wennersberg AL, Wisting L. Further evidence of the association between social media use, eating disorder pathology and appearance ideals and pressure: A cross-sectional study in Norwegian adolescents. Journal of Eating Disorders. 2024;12. https://doi.org/10.1186/s40337-024-00992-3 DOI: https://doi.org/10.1186/s40337-024-00992-3
10. Moufawad M, Hoque A, Kells M, Sonneville KR, Hahn SL. Social media use and weight bias internalization: Association moderated by age and weight perception. Journal of Eating Disorders. 2024;12. https://doi.org/10.1186/s40337-024-01043-7 DOI: https://doi.org/10.1186/s40337-024-01043-7
11. Shroff H, Thompson JK. The tripartite influence model of body image and eating disturbance: A replication with adolescent girls. Body Image. 2006;3(1):17-23. https://doi.org/10.1016/j.bodyim.2005.10.004 DOI: https://doi.org/10.1016/j.bodyim.2005.10.004
12. Van den Berg P, Thompson JK, Obremski-Brandon K, Coovert M. The Tripartite Influence Model of body image and eating disturbance: A covariance-structure-modeling investigation testing the mediational role of appearance comparison. J Psychosom Res. 2002;53(5):1007-1020. doi:10.1016/S0022-3999(02)00499-3. DOI: https://doi.org/10.1016/S0022-3999(02)00499-3
13. Fredrickson BL, Roberts T. Objectification theory: Toward understanding women’s lived experiences and mental health risks. Psychology of Women Quarterly. 1997;21(2):173-206. https://doi.org/10.1111/j.1471-6402.1997.tb00108.x DOI: https://doi.org/10.1111/j.1471-6402.1997.tb00108.x
14. Teixeira PJ, Carraça EV, Markland D, Silva MN, Ryan RM. Exercise, physical activity, and self-determination theory: A systematic review. International Journal of Behavioral Nutrition and Physical Activity. 2012;9:78. https://doi.org/10.1186/1479-5868-9-78 DOI: https://doi.org/10.1186/1479-5868-9-78
15. Tiggemann M, Zaccardo M. “Exercise to be fit, not skinny”: The effect of fitspiration imagery on women’s body image. Body Image. 2015;15:61-67. https://doi.org/10.1016/j.bodyim.2015.04.001 DOI: https://doi.org/10.1016/j.bodyim.2015.06.003
16. Stice E, Gau JM, Rohde P, Shaw H. Risk factors that predict future onset of each DSM-5 eating disorder: A systematic review and meta-analysis. Journal of Abnormal Psychology. 2017;126(6):730-749. https://doi.org/10.1037/abn0000219 DOI: https://doi.org/10.1037/abn0000219
17. Neumark-Sztainer D, Wall M, Haines J, Story M. Why does dieting predict weight gain in adolescents? Findings from Project EAT-II: A 5-year longitudinal study. J Am Diet Assoc. 2007;107(3):448-455. doi:10.1016/j.jada DOI: https://doi.org/10.1016/j.jada.2006.12.013
18. Keel PK, Forney KJ. Psychosocial risk factors for eating disorders. International Journal of Eating Disorders. 2013;46(5):433-439. https://doi.org/10.1002/eat.22094 DOI: https://doi.org/10.1002/eat.22094
19. Westenhoefer J. Dietary restraint and disinhibition: Is restraint a homogeneous construct? Appetite. 1991;16(1):45-55. https://doi.org/10.1016/0195-6663(91)90110-E DOI: https://doi.org/10.1016/0195-6663(91)90110-E
20. Stewart TM, Williamson DA, White MA. Rigid vs. flexible dieting: association with eating disorder symptoms in nonobese women. Appetite. 2002;38(1):39-44. doi:10.1006/appe.2001.0445 DOI: https://doi.org/10.1006/appe.2001.0445
21. Schaumberg K, Anderson DA, Anderson LM, Reilly EE, Gorrell S. Dietary restraint: What’s the harm? A review of the relationship between dietary restraint, weight trajectory and the development of eating pathology. Clinical Obesity. 2016;6(2):89-100. https://doi.org/10.1111/cob.12134 DOI: https://doi.org/10.1111/cob.12134
22. Tylka TL. Development and psychometric evaluation of a measure of intuitive eating. Journal of Counseling Psychology. 2006;53(2):226-240. https://doi.org/10.1037/0022-0167.53.2.226 DOI: https://doi.org/10.1037/0022-0167.53.2.226
23. Van Dyke N, Drinkwater EJ. Relationships between intuitive eating and health indicators: literature review. Public Health Nutr. 2014;17(8):1757-1766. doi:10.1017/S1368980013002139. DOI: https://doi.org/10.1017/S1368980013002139
24. Linardon J, Tylka TL, Fuller-Tyszkiewicz M. Intuitive eating and its psychological correlates: A meta-analysis. International Journal of Eating Disorders. 2021;54(7):1073-1098. https://doi.org/10.1002/eat.23509 DOI: https://doi.org/10.1002/eat.23509
25. Vinkers CDW, Evers C, Adriaanse MA, de Ridder DTD. Body esteem and eating disorder symptomatology: The mediating role of appearance-motivated exercise in a non-clinical adult female sample. Eating Behaviors. 2012;13(3):214-218. https://doi.org/10.1016/j.eatbeh.2012.02.006 DOI: https://doi.org/10.1016/j.eatbeh.2012.02.006
26. Vartanian LR, Shaprow JG. Effects of weight stigma on exercise motivation and behavior: A preliminary investigation among college-aged females. Journal of Health Psychology. 2008;13(1):131-138. https://doi.org/10.1177/1359105307084318 DOI: https://doi.org/10.1177/1359105307084318
27. Borsboom D. A network theory of mental disorders. World Psychiatry. 2017;16(1):5-13. https://doi.org/10.1002/wps.20375 DOI: https://doi.org/10.1002/wps.20375
28. Epskamp S, Cramer AOJ, Waldorp LJ, Schmittmann VD, Borsboom D. qgraph: Network visualizations of relationships in psychometric data. Journal of Statistical Software. 2012;48(4):1-18. https://doi.org/10.18637/jss.v048.i04 DOI: https://doi.org/10.18637/jss.v048.i04
29. Garner DM, Olmsted MP, Bohr Y, Garfinkel PE. The Eating Attitudes Test: Psychometric features and clinical correlates. Psychological Medicine. 1982;12(4):871-878. https://doi.org/10.1017/S0033291700049163 DOI: https://doi.org/10.1017/S0033291700049163
30. Rivas T, Bersabé R, Castro S. Adaptación y validación del Eating Attitudes Test (EAT-26) en una muestra española de adolescentes. Psicothema. 2010;22(4):882-888.
31. Constaín GA, Ricardo Ramírez C, Rodríguez-Gázquez MDLÁ, Álvarez Gómez M, Marín Múnera C, Agudelo Acosta C. Validez y utilidad diagnóstica de la escala EAT-26 para la evaluación del riesgo de trastornos de la conducta alimentaria en población femenina de Medellín, Colombia. Aten Primaria. 2014;46(6):283-289. DOI: https://doi.org/10.1016/j.aprim.2013.11.009
32. Heinberg LJ, Thompson JK, Stormer S. Development and validation of the Sociocultural Attitudes Toward Appearance Questionnaire. Int J Eat Disord. 1995;17(1):81-89. doi:10.1002/1098-108X(199501)17:1. DOI: https://doi.org/10.1002/1098-108X(199501)17:1<81::AID-EAT2260170111>3.0.CO;2-Y
33. Schaefer LM, Burke NL, Thompson JK, Dedrick RF, Heinberg LJ, Calogero RM, et al. Development and validation of the Sociocultural Attitudes Toward Appearance Questionnaire-4 (SATAQ-4). Psychological Assessment. 2015;27(1):54-67. https://doi.org/10.1037/a0037917 DOI: https://doi.org/10.1037/a0037917
34. Villegas-Moreno MJ, Londoño NH. Validación del Cuestionario de Actitudes Socioculturales sobre la Apariencia (SATAQ-4) en población colombiana. Acta Colombiana de Psicología. 2021;24(1):86-95. DOI: https://doi.org/10.14718/ACP.2021.24.1.8
35. Friedman J, Hastie T, Tibshirani R. Sparse inverse covariance estimation with the graphical lasso. Biostatistics. 2008;9(3):432-441. https://doi.org/10.1093/biostatistics/kxm045 DOI: https://doi.org/10.1093/biostatistics/kxm045
36. Foygel R, Drton M. Extended Bayesian information criteria for Gaussian graphical models. In: Advances in Neural Information Processing Systems. 2010. p. 604-612.
37. Robinaugh DJ, Millner AJ, McNally RJ. Identifying highly influential nodes in the complicated grief network: A novel centrality measure. Journal of Abnormal Psychology. 2016;125(6):747-757. https://doi.org/10.1037/abn0000181 DOI: https://doi.org/10.1037/abn0000181
38. Barrat A, Barthélemy M, Pastor-Satorras R, Vespignani A. The architecture of complex weighted networks. Proceedings of the National Academy of Sciences. 2004;101(11):3747-3752. https://doi.org/10.1073/pnas.0400087101 DOI: https://doi.org/10.1073/pnas.0400087101
39. Onnela JP, Saramäki J, Kertész J, Kaski K. Intensity and coherence of motifs in weighted complex networks. Physical Review E. 2005;71(6):065103. https://doi.org/10.1103/PhysRevE.71.065103 DOI: https://doi.org/10.1103/PhysRevE.71.065103
40. Watts DJ, Strogatz SH. Collective dynamics of “small-world” networks. Nature. 1998;393(6684):440-442. https://doi.org/10.1038/30918 DOI: https://doi.org/10.1038/30918
41. Epskamp S, Borsboom D, Fried EI. Estimating psychological networks and their accuracy: A tutorial paper. Behavior Research Methods. 2018;50(1):195-212. https://doi.org/10.3758/s13428-017-0862-1 DOI: https://doi.org/10.3758/s13428-017-0862-1
42. World Medical Association. Declaration of Helsinki: Ethical Principles for Medical Research Involving Human Subjects. JAMA. 2013;310(20):2191-2194. doi:10.1001/jama.2013.281053. DOI: https://doi.org/10.1001/jama.2013.281053
43. Barnes K, et al. A comparison of the impact of exposure to fit ideal and non-fit ideal content on women’s body image. Computers in Human Behavior. 2023;143:107678. https://doi.org/10.1016/j.chb.2023.107678 DOI: https://doi.org/10.1016/j.chb.2023.107728
44. Stice E, Shaw H, Marti CN. A meta-analytic review of eating disorder prevention programs: New directions and recommendations for improved effectiveness. Clinical Psychology Review. 2021;84:101974. https://doi.org/10.1016/j.cpr.2021.101974 DOI: https://doi.org/10.1016/j.cpr.2021.101974
45. Panão I, Carraça EV. Effects of exercise motivations on body image and eating habits/behaviours: A systematic review. Nutr Diet. 2020;77(1):41-59. doi:10.1111/1747-0080.12575. DOI: https://doi.org/10.1111/1747-0080.12575
46. Homan KJ, Tylka TL. Appearance-based exercise motivation moderates the relationship between exercise frequency and positive body image. Body Image. 2014;11(2):101-108. https://doi.org/10.1016/j.bodyim.2014.01.003. DOI: https://doi.org/10.1016/j.bodyim.2014.01.003
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