Vol 21. N°3. 2020  |  Julio-Septiembre de 2020


ARTÍCULOS ORIGINALES - OBESIDAD


FENOTIPOS DE COMPORTAMIENTO ALIMENTARIO: DISEÑO DE UNA NUEVA ESCALA MULTIDIMENSIONAL (EFCA)

Autores: VANESA ANGER, JESICA FORMOSO, MÓNICA KATZ


RESUMEN

Introducción: las características conductuales de las personas juegan un papel importante en la heterogeneidad de la respuesta al tratamiento de la obesidad. Existe evidencia de que ciertos rasgos de la conducta ingestiva humana serían mediadores entre la susceptibilidad genética individual y el exceso de peso corporal. Los fenotipos de comportamiento alimentario pueden utilizarse como predictores de éxito terapéutico. Para mejorar la eficacia de los tratamientos de la obesidad es necesario contar con herramientas prácticas que evalúen dichos fenotipos para realizar abordajes personalizados o de precisión.
Objetivos: diseñar y evaluar las propiedades psicométricas de una escala autoadministrada destinada a identificar fenotipos de comportamiento alimentario.
Materiales y métodos: 177 sujetos adultos participaron voluntariamente en un estudio de validación de una escala autoadministrada para identificar fenotipos comportamentales en adultos (Escala de Fenotipos de Comportamiento Alimentario, EFCA). La misma consta de 16 ítems que evalúan creencias y actitudes personales de la conducta ingestiva medidos a partir de una escala de Likert de cinco valores (1. nunca a 5. siempre). Se identificaron cinco factores por análisis paralelo y se realizó un análisis factorial exploratorio por máxima verosimilitud con rotación varimax como método de extracción.
Resultados: se incluyeron 177 adultos, 75,7% mujeres, 75% con exceso de peso con media de índice de masa corporal (IMC) 30,46 kg/m2 (DE=7,06). La estructura factorial mostró buen ajuste a los datos, con cargas factoriales superiores a .40 en todos los casos. El coeficiente Alpha de Cronbach indicó fiabilidad aceptable de .86 para la escala total y entre .73 y .88 para las subescalas obtenidas.
Conclusiones: la EFCA es una escala con niveles aceptables de validez y confiabilidad para identificar fenotipos de comportamiento alimentario en adultos.

PALABRAS CLAVE: comportamiento alimentario; fenotipo de comportamiento alimentario; ingesta emocional; picoteo; medicina de precisión.

REFERENCIAS:
1. Roth J, Qiang X, Marbán SL, Redelt H, Lowell BC. The obesity pandemic: where have we been and where are we going? Obes Res 2004; 12:88S-101S.
2. Diabetes Prevention Program Group. 10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcome Study. Lancet 2009; 374:1677-1686.
3. Dansinger ML, Tatsioni A, Wong JB, Chung M, Balk EM. Metaanalysis: the effect of dietary counseling for weight loss. Annals of Internal Medicine 2007; 147:41-50.
4. Jacob R, Drapeau V, Tremblay A, Provencher V, Bouchard C, Pérusse L. The role of eating behavior traits in mediating genetic susceptibility to obesity. Am J Clin Nutr 2018; 108:445-452.
5. Kelly NR, Shomaker LB, Pickworth CK, Brady SM, Courville AB, Bernstein S, et al. A prospective study of adolescent eating in the absence of hunger and body mass and fat mass outcomes. Obesity (Silver Spring) 2015; 23:1472-8.
6. Swinburn B, Egger G, Raza F. Dissecting obesogenic environments: the development and application of a framework for identifying and prioritizing environmental interventions for obesity. Prev Med 1999; 29:563-70.
7. Hobb M, McKenna J. In which population groups are food and physical activity environments related to obesity? Perspect Public Health 2019; 139:222-3.
8. Vannucci A, Nelson EE, Bongiorno DM, Pine DS, Yanovski JA, Tanofsky-Kraff M. Behavioral and neurodevelopmental precursors to binge-type eating disorders: support for the role of negative valence systems. Psychol Med 2015; 45:2921-36.
9. Mann T, Tomiyama AJ, Westling E, Lew AM, Samuels B. Chatman Medicare's search for effective obesity treatments: diets are not the answer. J Am Psychol 2007; 3:220-33.
10. Evers C, Dingemans A, Junghans AF, Boevé A. Feeling bad or feeling good, does emotion affect your consumption of food? A meta-analysis of the experimental evidence. Neurosci Biobehav Rev 2018; 92:195-208.
11. Braden A, Musher-Eizenman D, Watford T, Emley E. Eating when depressed, anxious, bored, or happy: Are emotional eating types associated with unique psychological and physical health correlates? Appetite 2018; 125:410-417.
12. Lazarevich I, Irigoyen Camacho ME, Velázquez-Alva MDC, Zepeda M. Relationship among obesity, depression, and emotional eating in young adults. Appetite 2016; 107:639-644.
13. Hwang Y, Kim HJ, Choi HJ, Lee J. Exploring abnormal behavior patterns of online users with emotional eating behavior: topic modeling study. J Med Internet Res 2020; 3: e15700.
14. Cassidy SB, Morris CA. Behavioral phenotypes in genetic syndromes: genetic clues to human behavior. Adv Pediatr 2002; 49:59-86.
15. Drewnowski A. The behavioral phenotype in human obesity. Why we eat what we eat: The psychology of eating. In E. D. Capaldi (Ed.), 1996. 291-308.
16. Dalton M, Finlayson G, Walsh B. Early improvement in food cravings are associated with long-term weight loss success in a large clinical sample. Int J Obes 2017; 41: 1232-1236.
17. Fisher JO, Birch LL. Eating in the absence of hunger and overweight in girls from 5 to 7 y of age. Am J Clin Nutr 2002; 76:226-231.
18. Boutelle KN, Peterson CB, Crosby RD, Rydell SA, Zucker N, Harnack L. Overeating phenotypes in overweight and obese children. Appetite 2014; 76:95-100.
19. Field AE, Inge TH, Belle SH, et al. Association of obesity subtypes in the longitudinal assessment of bariatric surgery study and 3-year postoperative weight change. Obesity 2018; 12:1931-1937.
20. Yang N, Ginsburg GS, Simmons LA. Personalized medicine in women's obesity prevention and treatment: implications for research, policy and practice. Obes Rev 2013 Feb; 14(2):145-61.
21. Yanovski SZ, Yanovski JA. Toward precision approaches for the prevention and treatment of obesity. JAMA 2018; 319:223-4.
22. Balantekin KN, Hayes JF, Sheinbein DH, Kolko RP, Stein RI, Saelens BE, et al. Patterns of eating disorder pathology are associated with weight change in family-based behavioral obesity treatment. Obesity (Silver Spring) 2017; 25:2115-22.
23. Jameson JL, Longo DL. Precision medicine-personalized, problematic, and promising. N Engl J Med 2015; 372: 2229-2234.
24. Bray MS, Loos RJF, McCaffery JM, et al. The Conference Working G. NIH working group report using genomic information to guide weight management: from universal to precision treatment. Obesity 2016; 24:14-22.
25. Bouhlal S, McBride CM, Trivedi NS, Agurs-Collins T, Persky S. Identifying eating behavior phenotypes and their correlates: a novel direction toward improving weight management interventions. Appetite 2017; 111:142-50.
26. Wood ND, Akloubou-Gnonhosou DC, Bowling J. Combining parallel and exploratory factor analysis in identifying relationship scales in secondary data. Marriage & Family Review 2015; 51:385-395.
27. Lloret S, Ferreres A, Hernández A, Tomás I. The exploratory factor analysis of items: guided analysis based on empirical data and software. Anales de Psicología 2017; 33: 417-432.
28. Rudolph A, Hilibert A. Post-operative behavioural management in bariatric surgery: a systematic review and metaanalysis of randomized controlled trials. Obesity Rev 2013; Vol 14, Issue 4: 292-302.
29. Kaouk L, Hsu AT, Tanuseputro P, Jessri M. Modifiable factors associated with weight regain after bariatric surgery: a scoping review. F1000Research 2019; 10.12688/f1000research.18787.1, 8:615.
30. Voils CI, Adler R, Liu N, Funk L. Understanding weight regain and the need for life-long follow-up after bariatric surgery. Current Surgery Reports 2017; 10.1007/s40137-017-0196-z, 5, 12.
31. Fujioka K, O'Neill PM, Davies M. Early weight loss with liraglutide 3.0 mg predicts 1-year weight loss and is associated with improvements in clinical markers. Obesity 2016; 24:2278-2288.
32. Gorgojo-Martínez JJ, Gargallo-Fernández MA, Brito-Sanfiel M. Real-world clinical outcomes and predictors of glycaemic and weight response to exenatide once weekly in patients with type 2 diabetes: The CIBELES project. Int J Clin Pract 2018; 72:1-10.
33. Thomas EA, McNair B, Betchell JL. Greater hunger and less restraint predict weight loss success with phentermine treatment. Obesity 2016; 24:37-43.
34. Acosta A, Camilleri M, Shin A. Quantitative gastrointestinal and psychological traits associated with obesity and response to weight-loss therapy. Gastroenterology 2015; 148:537-546.
35. Guajardo-Salinas GE, Hilmy A, Martínez-Ugarte ML. Predictors of weight loss and effectiveness of roux-en-y gastric bypass in the morbidly obese Hispano-American population. Obes Surg 2008; 18:1369-1375.
36. Anger V, Katz M. Relación entre IMC, emociones percibidas, estilo de ingesta y preferencias gustativas en una población de adultos. Actualización en Nutrición Marzo 2015; Vol. 16 Nº 1:31-36.
37. Martínez J. A perspectives on personalized nutrition for obesity. J Nutrigenet Nutrigenomics 2014; 7:I–III
38. Peña-Romero AC, Navas-Carrillo D, Marín F, Orenes-Piñero E. The future of nutrition: nutrigenomics and nutrigenetics in obesity and cardiovascular diseases. Crit Rev Food Sci Nutr 2018; 58(17):3030-3041.
39. Bomberg EM, Ryder JR, Brundage RC, Straka RJ, Fox CK, Gross AC, Oberle MM, Bramante CT, Sibley SD, Kelly AS. Precision medicine in adult and pediatric obesity: a clinical perspective. Therapeutic Advances in Endocrinology and Metabolism 2019; 10: 1-25.
40. Brunner-Huber LR. Validity of self-reported height and weight in women of reproductive age. Matern Child Health J 2007; 11:137-44.

---

EATING BEHAVIOR PHENOTYPES: DESIGN OF A NEW MULTIDIMENSIONAL SCALE (EFCA)

SUMMARY

Introduction: the behavioral characteristics of people play an important role in the heterogeneity of the response to the obesity treatments. There is evidence that certain human traits of ingestive behavior are mediators between individual genetic susceptibility and excess of body weight. Eating behavior phenotypes can be used as predictors of therapeutic success. To improve the efficacy of obesity treatments, it is necessary to have clinical simple tools that evaluate these phenotypes to carry out personalized or precision approaches.
Objectives: to design and evaluate the psychometric properties of a self-administered scale aimed at identifying phenotypes of eating behavior.
Materials and methods: 177 adult subjects voluntarily participated in a validation study of a self-administered scale to identify behavioral phenotypes (eating behavior phenotype scale, EFCA). It consists of 16 items that evaluate personal beliefs and attitudes of ingestive behavior measured using a Likert type scale with 5 point values (1. never to 5. always). Five factors were identified by a parallel analysis followed by an exploratory factor analysis with varimax rotation and maximum likelihood as the extraction method.
Results: 177 adults 75.7% women, 75% overweight with a mean body mass index (BMI) of 30.46 kg/m2 (SD=7.06) were included. Model fit indices show an adequate adjustment of this structure to the data, with factor loads greater than .40 in all cases. Cronbach´s Alpha coefficient indicated acceptable reliability of .86 for the full scale and between .73 and .88 for the subscales obtained.
Conclusions: EFCA is a scale with acceptable validity levels and reliability to identify eating behavior phenotypes in adults.

Key words: eating behavior; behavioral phenotype; emotional hunger; snacking; compulsive eating; precision medicine.


DESCARGAR TEXTO COMPLETO EN PDF