Obesity has limited behavioural overlap with addiction and psychiatric phenotypes

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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.


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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.

Author information

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.

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 (2019) doi:10.1038/s41562-019-0752-x

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