The predictive scales.

Personality traits consistently relate to and allow predicting body mass index (BMI), but these associations may not be adequately captured with existing inventories’ domains or facets. Here, we aimed to test the limits of how accurately BMI can be predicted from and described with personality traits. We used three large datasets (combined N ≈ 100,000) with nearly 700 personality assessment items to (a) empirically identify clusters of personality traits linked to BMI and (b) identify relatively small sets of items that predict BMI as accurately as possible. Factor analysis revealed 14 trait clusters showing well-established personality trait–BMI associations (disorganization, anger) and lesser-known or novel ones (altruism, obedience). Most of items’ predictive accuracy (up to r = .24 here but plausibly much higher) was captured by relatively few items. Brief scales that predict BMI have potential clinical applications—for instance, screening for risk of excessive weight gain or related complications.</div

Sample characteristics.

Personality traits consistently relate to and allow predicting body mass index (BMI), but these associations may not be adequately captured with existing inventories’ domains or facets. Here, we aimed to test the limits of how accurately BMI can be predicted from and described with personality traits. We used three large datasets (combined N ≈ 100,000) with nearly 700 personality assessment items to (a) empirically identify clusters of personality traits linked to BMI and (b) identify relatively small sets of items that predict BMI as accurately as possible. Factor analysis revealed 14 trait clusters showing well-established personality trait–BMI associations (disorganization, anger) and lesser-known or novel ones (altruism, obedience). Most of items’ predictive accuracy (up to r = .24 here but plausibly much higher) was captured by relatively few items. Brief scales that predict BMI have potential clinical applications—for instance, screening for risk of excessive weight gain or related complications.</div

Summary of personality variables’ correlations with BMI.

Summary of personality variables’ correlations with BMI.</p

Analysis flowchart.

The colored dots denote the datasets used in the different steps of the analysis (blue: dataset A, green: dataset B, yellow: dataset C).</p

Accuracy of predicting BMI at different criteria of interitem correlations.

Accuracy of predicting BMI at different criteria of interitem correlations.</p

Correlations between the 15 factors and IPIP-NEO domains.

The factors and domains were calculated after residualizing the items for age, age2, sex, and continent. Factors and domains were calculated for people for whom at least three items in the factor (domain) were available. (PNG)</p

Summary of the 14 factors.

Personality traits consistently relate to and allow predicting body mass index (BMI), but these associations may not be adequately captured with existing inventories’ domains or facets. Here, we aimed to test the limits of how accurately BMI can be predicted from and described with personality traits. We used three large datasets (combined N ≈ 100,000) with nearly 700 personality assessment items to (a) empirically identify clusters of personality traits linked to BMI and (b) identify relatively small sets of items that predict BMI as accurately as possible. Factor analysis revealed 14 trait clusters showing well-established personality trait–BMI associations (disorganization, anger) and lesser-known or novel ones (altruism, obedience). Most of items’ predictive accuracy (up to r = .24 here but plausibly much higher) was captured by relatively few items. Brief scales that predict BMI have potential clinical applications—for instance, screening for risk of excessive weight gain or related complications.</div

Variable sets’ correlations With BMI in elastic net.

r marks the correlation between actual BMI and BMI as predicted by the elastic net model with the given set of personality variables; error bars indicate 95% confidence intervals. The results are shown numerically in S3 Table.</p

Observed BMI and Weight by Predicted BMI Decile.

Personality traits consistently relate to and allow predicting body mass index (BMI), but these associations may not be adequately captured with existing inventories’ domains or facets. Here, we aimed to test the limits of how accurately BMI can be predicted from and described with personality traits. We used three large datasets (combined N ≈ 100,000) with nearly 700 personality assessment items to (a) empirically identify clusters of personality traits linked to BMI and (b) identify relatively small sets of items that predict BMI as accurately as possible. Factor analysis revealed 14 trait clusters showing well-established personality trait–BMI associations (disorganization, anger) and lesser-known or novel ones (altruism, obedience). Most of items’ predictive accuracy (up to r = .24 here but plausibly much higher) was captured by relatively few items. Brief scales that predict BMI have potential clinical applications—for instance, screening for risk of excessive weight gain or related complications.</div

Variable Set’s correlations with BMI.

Dots denote the absolute values of the items’ correlations with BMI; crossbars show their medians and interquartile ranges. Variable sets are ordered based on the included number of predictors in the set. Lead items are the factor’s items with the strongest correlation with BMI; all items related to BMI include the 242 items with statistically significant links to BMI selected for EFA; items related to BMI left over include items related to BMI that were not included in the factors. The correlations are summarized numerically in S3 Table.</p