Obesity has limited behavioural overlap with addiction and psychiatric phenotypes

Abstract

Obesity is a widespread health condition1, likely to be driven by the increased availability of inexpensive high-calorie food2. People vary greatly in their behavioural response to food. Such variation is likely to be driven by behavioural styles3,4, as behaviour accounts for overall food intake5. A prominent hypothesis is that people with obesity respond to rewards similarly to people with addictions such as alcohol abuse or smoking6,7. For instance, perceived overeating or ‘uncontrolled eating’ (UE) is the most common obesity-associated personality trait8 and resembles the perceived loss of control seen in drug addiction. Likewise, both obesity and addictive behaviours have similar correlations with broad personality domains3. Here we seek to empirically test whether obesity and UE overlap behaviourally with addiction and psychiatric disorders, collectively referred to as phenotypes. We test for behavioural similarity by linking the personality profiles of each phenotype. NEO Personality Inventory profiles of 28 phenotypes were extracted from 22 studies, encompassing summary statistics from 18,611 unique participants. Obesity had moderate and UE high behavioural similarity with addictions. UE also overlapped behaviourally with most psychiatric phenotypes, whereas obesity was behaviourally similar with mood disorders and certain personality disorders. Facet-based phenotype profiles provided more information than domain-based profiles.

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Fig. 1: Personality trait profiles of obesity and selected addictions.
Fig. 2: Personality correlations (rp) with addiction phenotypes.
Fig. 3: Personality correlations (rp) with psychiatric phenotypes.
Fig. 4: Scatterplots of personality correlations (rp) between profiles of UE and obesity, and addiction and psychiatric phenotypes.

Data availability

The correlation profiles of phenotypes used in the analysis are available at https://osf.io/zfsxd/ and also as Supplementary Data and part of Supplementary Software.

Code availability

The analysis script used to generate results based on the correlation profiles is available at https://osf.io/zfsxd/ and also as Supplementary Software.

References

  1. 1.

    Abajobir, A. A. et al. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet 390, 1345–1422 (2017).

    Article  Google Scholar 

  2. 2.

    Drewnowski, A. Obesity and the food environment: dietary energy density and diet costs. Am. J. Prev. Med. 27, 154–162 (2004).

    PubMed  Article  PubMed Central  Google Scholar 

  3. 3.

    Michaud, A., Vainik, U., García-García, I. & Dagher, A. Overlapping neural endophenotypes in addiction and obesity. Front. Endocrinol. 8, 1–15 (2017).

    Article  Google Scholar 

  4. 4.

    Vainik, U., Dagher, A., Dubé, L. & Fellows, L. K. Neurobehavioural correlates of body mass index and eating behaviours in adults: a systematic review. Neurosci. Biobehav. Rev. 37, 279–299 (2013).

    PubMed  Article  PubMed Central  Google Scholar 

  5. 5.

    Blundell, J. E. & Finlayson, G. Is susceptibility to weight gain characterized by homeostatic or hedonic risk factors for overconsumption? Physiol. Behav. 82, 21–25 (2004).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  6. 6.

    Volkow, N. D., Wang, G.-J., Tomasi, D. & Baler, R. D. Obesity and addiction: neurobiological overlaps. Obes. Rev. 14, 2–18 (2013).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  7. 7.

    Tang, D. W., Fellows, L. K., Small, D. M. & Dagher, A. Food and drug cues activate similar brain regions: a meta-analysis of functional MRI studies. Physiol. Behav. 106, 317–324 (2012).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  8. 8.

    Vainik, U., Neseliler, S., Konstabel, K., Fellows, L. K. & Dagher, A. Eating traits questionnaires as a continuum of a single concept. Uncontrolled Eat. Appetite 90, 229–239 (2015).

    Article  Google Scholar 

  9. 9.

    Price, M., Higgs, S. & Lee, M. Self-reported eating traits: underlying components of food responsivity and dietary restriction are positively related to BMI. Appetite 95, 203–210 (2015).

    PubMed  Article  PubMed Central  Google Scholar 

  10. 10.

    Vainik, U., García‐García, I. & Dagher, A. Uncontrolled eating: a unifying heritable trait linked with obesity, overeating, personality and the brain. Eur. J. Neurosci. 50, 1–16 (2019).

    Article  Google Scholar 

  11. 11.

    Blundell, J. E. & Cooling, J. Routes to obesity: phenotypes, food choices and activity. Br. J. Nutr. 83(Suppl 1), S33–S38 (2000).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  12. 12.

    Murphy, C. M. et al. Autism spectrum disorder in adults: diagnosis, management, and health services development. Neuropsychiatr. Dis. Treat. 12, 1669–1686 (2016).

    PubMed  PubMed Central  Article  Google Scholar 

  13. 13.

    Gariepy, G., Nitka, D. & Schmitz, N. The association between obesity and anxiety disorders in the population: a systematic review and meta-analysis. Int. J. Obes. 34, 407–419 (2010).

    CAS  Article  Google Scholar 

  14. 14.

    McElroy, S. L. et al. Are mood disorders and obesity related? A review for the mental health professional. J. Clin. Psychiatry 65, 634–651 (2004).

    PubMed  Article  PubMed Central  Google Scholar 

  15. 15.

    Gerlach, G., Loeber, S. & Herpertz, S. Personality disorders and obesity: a systematic review. Obes. Rev. 17, 691–723 (2016).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  16. 16.

    Costa, P. T. & McCrae, R. R. Revised NEO Personality Inventory (NEO-PI-R) and NEO Five-Factor Inventory (NEOFFI)—Professional Manual (Psychological Assessment Resources, 1992).

  17. 17.

    McCrae, R. R., Costa, P. T.Jr. & Martin, T. A. The NEO–PI–3: a more readable revised NEO personality inventory. J. Pers. Assess. 84, 261–270 (2005).

    PubMed  Article  PubMed Central  Google Scholar 

  18. 18.

    Emery, R. L. & Levine, M. D. Questionnaire and behavioral task measures of impulsivity are differentially associated with body mass index: a comprehensive meta-analysis. Psychol. Bull. 143, 868–902 (2017).

    PubMed  Article  PubMed Central  Google Scholar 

  19. 19.

    Malouff, J. M., Thorsteinsson, E. B. & Schutte, N. S. The relationship between the five-factor model of personality and symptoms of clinical disorders: a meta-analysis. J. Psychopathol. Behav. Assess. 27, 101–114 (2005).

    Article  Google Scholar 

  20. 20.

    Sutin, A. R., Ferrucci, L., Zonderman, A. B. & Terracciano, A. Personality and obesity across the adult life span. J. Pers. Soc. Psychol. 101, 579–592 (2011).

    PubMed  PubMed Central  Article  Google Scholar 

  21. 21.

    Jansen, A., Houben, K. & Roefs, A. A cognitive profile of obesity and its translation into new interventions. Front. Psychol. 6, 1–9 (2015).

    Google Scholar 

  22. 22.

    van Strien, T., Frijters, J. E. R., Bergers, G. P. A. & Defares, P. B. The Dutch eating behavior questionnaire (DEBQ) for assessment of restrained, emotional, and external eating behavior. Int. J. Eat. Disord. 5, 295–315 (1986).

    Article  Google Scholar 

  23. 23.

    Finlayson, G. Food addiction and obesity: unnecessary medicalization of hedonic overeating. Nat. Rev. Endocrinol. 13, 493–498 (2017).

    PubMed  Article  PubMed Central  Google Scholar 

  24. 24.

    Ormel, J. et al. Neuroticism and common mental disorders: meaning and utility of a complex relationship. Clin. Psychol. Rev. 33, 686–697 (2013).

    PubMed  PubMed Central  Article  Google Scholar 

  25. 25.

    American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders https://doi.org/10.1176/appi.books.9780890425596 (2013).

  26. 26.

    Lillis, J., Luoma, J. B., Levin, M. E. & Hayes, S. C. Measuring weight self-stigma: the weight self-stigma questionnaire. Obesity 18, 971–976 (2010).

    PubMed  Article  PubMed Central  Google Scholar 

  27. 27.

    Lemaitre, B. Connecting the obesity and the narcissism epidemics. Med. Hypotheses 95, 10–19 (2016).

    PubMed  Article  PubMed Central  Google Scholar 

  28. 28.

    Samuel, D. B. & Widiger, T. A. A meta-analytic review of the relationships between the five-factor model and DSM-IV-TR personality disorders: a facet level analysis. Clin. Psychol. Rev. 28, 1326–1342 (2008).

    PubMed  PubMed Central  Article  Google Scholar 

  29. 29.

    Mõttus, R., Kandler, C., Bleidorn, W., Riemann, R. & McCrae, R. R. Personality traits below facets: the consensual validity, longitudinal stability, heritability, and utility of personality nuances. J. Pers. Soc. Psychol. 112, 474–490 (2017).

    PubMed  Article  PubMed Central  Google Scholar 

  30. 30.

    Mõttus, R. Towards more rigorous personality trait–outcome research. Eur. J. Personal. 30, 292–303 (2016).

    Article  Google Scholar 

  31. 31.

    Mõttus, R., Bates, T., Condon, D. M., Mroczek, D. & Revelle, W. Your personality data can do more: Items provide leverage for explaining the variance and co-variance of life outcomes Preprint at psyArXiv https://doi.org/10.17605/OSF.IO/4Q9GV (2017).

  32. 32.

    McCrae, R. R. The place of the FFM in personality psychology. Psychol. Inq. 21, 57–64 (2010).

    Article  Google Scholar 

  33. 33.

    John, O. & Srivastava, S. in Handbook of Personality: Theory and Research 102–138 (Guilford, 1999).

  34. 34.

    Haigler, E. D. & Widiger, T. A. Experimental manipulation of NEO-PI-R items. J. Pers. Assess. 77, 339–358 (2001).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  35. 35.

    Carter, J. A. et al. Short-term stability of NEO–PI–R personality trait scores in opioid-dependent outpatients. Psychol. Addict. Behav. 15, 255–260 (2001).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  36. 36.

    Costa, P. T., Bagby, R. M., Herbst, J. H. & McCrae, R. R. Personality self-reports are concurrently reliable and valid during acute depressive episodes. J. Affect. Disord. 89, 45–55 (2005).

    PubMed  Article  PubMed Central  Google Scholar 

  37. 37.

    Kentros, M. et al. Stability of personality traits in schizophrenia and schizoaffective disorder: a pilot project. J. Nerv. Ment. Dis. 185, 549–555 (1997).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  38. 38.

    Costa, P. J., Terracciano, A. & McCrae, R. R. Gender differences in personality traits across cultures: robust and surprising findings. J. Pers. Soc. Psychol. 81, 322–331 (2001).

    PubMed  Article  PubMed Central  Google Scholar 

  39. 39.

    Elfhag, K. & Morey, L. C. Personality traits and eating behavior in the obese: poor self-control in emotional and external eating but personality assets in restrained eating. Eat. Behav. 9, 285–293 (2008).

    PubMed  Article  PubMed Central  Google Scholar 

  40. 40.

    Mõttus, R., Realo, A., Vainik, U., Allik, J. & Esko, T. Educational attainment and personality are genetically intertwined. Psychol. Sci. 28, 1631–1639 (2017).

    PubMed  Article  PubMed Central  Google Scholar 

  41. 41.

    Ruiz, M. A., Pincus, A. L. & Dickinson, K. A. NEO PI-R predictors of alcohol use and alcohol-related problems. J. Pers. Assess. 81, 226–236 (2003).

    PubMed  Article  PubMed Central  Google Scholar 

  42. 42.

    Sutin, A. R. et al. The association between personality traits and body mass index varies with nativity among individuals of Mexican origin.Appetite 90, 74–79 (2015).

    PubMed  Article  PubMed Central  Google Scholar 

  43. 43.

    Vainik, U., Mõttus, R., Allik, J., Esko, T. & Realo, A. Are trait–outcome associations caused by scales or particular items? Example analysis of personality facets and BMI. Eur. J. Personal. 29, 688–634 (2015).

    Article  Google Scholar 

  44. 44.

    Wakabayashi, A., Baron-Cohen, S. & Wheelwright, S. Are autistic traits an independent personality dimension? A study of the Autism-Spectrum Quotient (AQ) and the NEO-PI-R. Personal. Individ. Differ. 41, 873–883 (2006).

    Article  Google Scholar 

  45. 45.

    Bienvenu, O. J. et al. Anxiety and depressive disorders and the five-factor model of personality: a higher- and lower-order personality trait investigation in a community sample. Depress. Anxiety 20, 92–97 (2004).

    PubMed  Article  PubMed Central  Google Scholar 

  46. 46.

    Davtian, M., Reid, R. C. & Fong, T. W. Investigating facets of personality in adult pathological gamblers with ADHD. Neuropsychiatry 2, 163–174 (2012).

    PubMed  PubMed Central  Article  Google Scholar 

  47. 47.

    Rector, N. A., Bagby, R. M., Huta, V. & Ayearst, L. E. Examination of the trait facets of the five-factor model in discriminating specific mood and anxiety disorders. Psychiatry Res. 199, 131–139 (2012).

    PubMed  Article  PubMed Central  Google Scholar 

  48. 48.

    Quirk, S. W., Christiansen, N. D., Wagner, S. H. & McNulty, J. L. On the usefulness of measures of normal personality for clinical assessment: evidence of the incremental validity of the Revised NEO Personality Inventory. Psychol. Assess. 15, 311–325 (2003).

    PubMed  Article  PubMed Central  Google Scholar 

  49. 49.

    Bagby, R. M. et al. Relationship between the five-factor model of personality and unipolar, bipolar and schizophrenic patients. Psychiatry Res. 70, 83–94 (1997).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  50. 50.

    Terracciano, A., Löckenhoff, C. E., Crum, R. M., Bienvenu, O. J. & Costa, P. T. Five-factor model personality profiles of drug users. BMC Psychiatry 8, 22 (2008).

    PubMed  PubMed Central  Article  Google Scholar 

  51. 51.

    Terracciano, A. et al. Facets of personality linked to underweight and overweight. Psychosom. Med. 71, 682–689 (2009).

    PubMed  PubMed Central  Article  Google Scholar 

  52. 52.

    Morey, L. C. et al. The representation of borderline, avoidant, obsessive-compulsive, and schizotypal personality disorders by the five-factor model. J. Personal. Disord. 16, 215–234 (2002).

    Article  Google Scholar 

  53. 53.

    Rector, N. A., Hood, K., Richter, M. A. & Michael Bagby, R. Obsessive-compulsive disorder and the five-factor model of personality: distinction and overlap with major depressive disorder. Behav. Res. Ther. 40, 1205–1219 (2002).

    CAS  PubMed  Article  Google Scholar 

  54. 54.

    Levallius, J., Clinton, D., Bäckström, M. & Norring, C. Who do you think you are? Personality in eating disordered patients.J. Eat. Disord. 3, 3 (2015).

    PubMed  PubMed Central  Article  Google Scholar 

  55. 55.

    Terracciano, A. & Costa, P. T. Smoking and the five-factor model of personality. Addict. Abingdon Engl. 99, 472–481 (2004).

    Article  Google Scholar 

  56. 56.

    Bagby, R. M. et al. Pathological gambling and the five-factor model of personality. Personal. Individ. Differ. 43, 873–880 (2007).

    Article  Google Scholar 

  57. 57.

    Ruxton, G. D. The unequal variance t-test is an underused alternative to Student’s t-test and the Mann–Whitney U test. Behav. Ecol. 17, 688–690 (2006).

    Article  Google Scholar 

  58. 58.

    Arnholt, A. T. BSDA: basic statistics and data analysis https://alanarnholt.github.io/BSDA/ (2012).

  59. 59.

    Del Re, A. C. compute.es: compute effect sizes (R Foundation for Statistical Computing, 2014).

  60. 60.

    Borenstein, M. in The Handbook of Research Synthesis and Meta-analysis 2nd edn (eds. Cooper, H., Hedges, L. V. & Valentine, J. C.) 221–235 (Russell Sage Foundation, 2009).

  61. 61.

    Shadish, W. R. & Haddock, C. K. in The Handbook of Research Synthesis and Meta-Analysis 2nd edn (eds. Cooper, H., Hedges, L. V. & Valentine, J. C.) 257–277 (Russell Sage Foundation, 2009).

  62. 62.

    R Core Team. R: a language and environment for statistical computing (R Foundation for Statistical Computing, 2013).

  63. 63.

    Schwarzer, G. meta: general package for meta-analysis (2017).

  64. 64.

    Furr, R. M. The double-entry intraclass correlation as an index of profile similarity: meaning, limitations, and alternatives. J. Pers. Assess. 92, 1–15 (2010).

    PubMed  Article  PubMed Central  Google Scholar 

  65. 65.

    Murtagh, F. & Legendre, P. Ward’s hierarchical agglomerative clustering method: which algorithms implement ward’s criterion? J. Classif. 31, 274–295 (2014).

    Article  Google Scholar 

  66. 66.

    Fruchterman, T. M. J. & Reingold, E. M. Graph drawing by force-directed placement. Softw. Pract. Exp. 21, 1129–1164 (1991).

    Article  Google Scholar 

  67. 67.

    Epskamp, S. et al. qgraph: Network visualizations of relationships in psychometric data. J. Stat. Softw. 48, 1–18 (2012).

    Article  Google Scholar 

  68. 68.

    Phillips, N. yarrr: a companion to the e-book ‘YaRrr!: The Pirate’s Guide to R’ https://cran.r-project.org/web/packages/yarrr/yarrr.pdf (2017).

  69. 69.

    Revelle, W. psych: procedures for psychological, psychometric, and personality research https://cran.r-project.org/web/packages/psych/index.html (2014).

  70. 70.

    Wei, T. & Simko, V. corrplot: visualization of a correlation matrix https://cran.r-project.org/web/packages/corrplot/index.html (2016).

  71. 71.

    Wickham, H. & R Studio. tidyverse: easily install and load the ‘Tidyverse’ https://tidyverse.tidyverse.org/ (2017).

  72. 72.

    Wilke, C. O. & Wickham, H. cowplot: streamlined plot theme and plot annotations for ‘ggplot2’ https://wilkelab.org/cowplot/index.html (2016).

  73. 73.

    Postuma Partners. lmvar: linear regression with non-constant variances https://rdrr.io/cran/lmvar/ (2018).

  74. 74.

    Gromer, D. apa: format outputs of statistical tests according to APA guidelines https://rdrr.io/cran/apa/ (2019).

  75. 75.

    Stanley, D. apaTables: create American Psychological Association (APA) style tables https://cran.rstudio.com/web/packages/apaTables/vignettes/apaTables.html (2018).

  76. 76.

    Torchiano, M. effsize: efficient effect size computation https://www.researchgate.net/publication/270758702_Effsize_Efficient_Effect_Size_Computation (2018).

  77. 77.

    Slowikowski, K. et al. ggrepel: automatically position non-overlapping text labels with ‘ggplot2’ https://rdrr.io/cran/ggrepel/ (2018).

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Acknowledgements

We thank J. Allik, K. Konstabel, M. Kõiv-Vainik and T. Tillmann for their helpful comments on the manuscript. U.V. was supported by Personal Post-doctoral Research Funding project PUTJD654 and by a Fonds de recherche du Québec – Santé (FRQS) foreign post-doctoral training award. A.M. was supported by Canadian Institutes of Health Research (CIHR). This work was supported by a CIHR Foundation Scheme award to A.D. The funders had no role in the conceptualization, design, data collection, analysis, decision to publish, or preparation of the manuscript.

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All authors read and contributed significantly to the manuscript and approved the submitted version. U.V. collected data, analysed data and wrote the paper. B.M. contributed to data analysis. Y.Z. contributed to data analysis methods. A.M. contributed to interpretation. R.M. contributed to data analysis methods and interpretation A.D. contributed to data analysis methods and interpretation.

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Correspondence to Uku Vainik.

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Extended data

Extended Data Fig. 1 Personality correlation matrix between profiles across 5 NEO-PI domains.

Correlations were multiplied by 100 for visual clarity. ALC, alcohol; ANX, anxiety disorders; ASD, autism; ASO, antisocial; AVO, avoidant; BDL, borderline; BIP, bipolar; DEP, depression; DPD, dependent; ED, non-anorexic eating disorders; EDU, education; GEN, gender; GMB, gambling; GMB.A, gambling with attention deficit hyperactivity disorder; HIS, histrionic; NAR, narcissistic; OB, obesity; OCD, obsessive compulsive disorder; OCPD, obsessive compulsive personality disorder; OPI, opioid abuse; PAR, paranoid; PTSD, post traumatic stress disorder; SCH, schizophrenia; SMK, smoking; SZD, schizoid; SZT, schizotypal; THC, cannabis; UE, uncontrolled eating.

Extended Data Fig. 2 Personality correlation matrix between profiles across 30 NEO-PI facets.

Correlations were multiplied by 100 for visual clarity. ALC, alcohol; ANX, anxiety disorders; ASD, autism; ASO, antisocial; AVO, avoidant; BDL, borderline; BIP, bipolar; DEP, depression; DPD, dependent; ED, non-anorexic eating disorders; EDU, education; GEN, gender; GMB, gambling; GMB.A, gambling with attention deficit hyperactivity disorder; HIS, histrionic; NAR, narcissistic; OB, obesity; OCD, obsessive compulsive disorder; OCPD, obsessive compulsive personality disorder; OPI, opioid abuse; PAR, paranoid; PTSD, post traumatic stress disorder; SCH, schizophrenia; SMK, smoking; SZD, schizoid; SZT, schizotypal; THC, cannabis; UE, uncontrolled eating.

Supplementary information

Supplementary Information

Supplementary Tables 2 and 3.

Reporting Summary

Supplementary Table 1

Overview of the data sources used in this article.

Supplementary Software

An R project folder tree with analysis script and datasets.

Supplementary Data

Csv files of correlation profiles used in the analysis, and the acronyms of the profiles.

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Vainik, U., Misic, B., Zeighami, Y. et al. Obesity has limited behavioural overlap with addiction and psychiatric phenotypes. Nat Hum Behav 4, 27–35 (2020). https://doi.org/10.1038/s41562-019-0752-x

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