Found a significant, negative relationship between resting metabolic rate and Extraversion; less extraverted individuals had a 30% higher RMR than the most extraverted ones; seems an allocation energy trade-off

Bergeron P, Pagé A, Trempe M (2021) Integrating humans into pace-of-life studies: The Big Five personality traits and metabolic rate in young adults. PLoS ONE 16(4): e0248876. doi:10.1371/journal.pone.0248876

Abstract: The pace-of-life syndrome (POLS) predicts that personality and metabolism should be correlated if they function as an integrated unit along a slow-fast continuum. Over the last decade, this conceptual framework has been tested in several empirical studies over a wide array of non-human animal taxa, across multiple personality traits and using standardized measures of metabolism. However, studies associating metabolic rate and personality in humans have been surprisingly scarce. Here, we tested whether there was covariation among personality scores, measured using the Big Five Inventory test, resting metabolic rate (RMR) and preferred walking speed (PWS) in a cohort of young human adults aged between 18 and 27 years old. We found a significant, negative relationship between RMR and Extraversion; less extraverted individuals had a 30% higher RMR than the most extraverted ones. No other personality traits correlated with RMR and none correlated with PWS. The negative correlation between Extraversion and RMR may suggest an allocation energy trade-off between personality and basal metabolism. Our results yielded equivocal support for the POLS and emphasized the need for more research on human to test the generality of this conceptual framework and further assess its validity.

Discussion

Our goal was to examine the correlations between the Big Five personality traits and metabolism in young adults. This research was inspired by the vast literature on the POLS using non-human animals, with the hope that standardized personality traits could contribute to reducing the measurement noise around this construct [7]. Our main result was that Extraversion correlated negatively with RMR. All other traits showed no correlations with RMR, and none of the traits was correlated with PWS.

While never reported before, the significant correlation between Extraversion and RMR is coherent with previous personality work. According to DeYoung’s cybernetic model [14], Extraversion and Openness share a common variance and can be regrouped under the metatrait Plasticity, which indicates one’s “tendency toward behavioral exploration, using motor output to pursue potentially rewarding possibilities […]”. In addition, when assessed using the 44-item Big Five Inventory test (as in the present study), Extraversion included several questions pertaining to the facet Activity [26]. This language is strikingly similar to that used in animal studies, in which “activity” and “exploration” scores are personality traits that have been shown to covary with metabolism [3]. In fact, when used in animal studies, “personality” cannot be dissociated from behavior since observing the animal’s behavior is the only way in which researchers can infer the animal’s personality [27]. It therefore may not come as a surprise if, in our dataset, the only significant correlation between RMR and personality was obtained with Extraversion, the trait highest in visibility and the one that can be most accurately assessed by other raters [28]. Thus, our results suggest that the components of personality linked to behavior and movements are attuned to the body metabolism.

The negative correlation between RMR and Extraversion, however, adds to a growing number of reports failing to support the POLS [7]. More specifically, the POLS would predict that personalities associated with energy-demanding behaviors should positively correlate with basal energy expenditure and not the opposite [3]. In contrast, Careau et al. [29] suggested that a negative correlation between personality and metabolism could be observed if “fast” personalities are maintained via an energetic allocation trade-off with metabolism. In other words, individuals could be able to sustain energetically demanding personalities (or the behaviors associated with these personalities) by spending less energy at rest. Such a trade-off has been observed between metabolic rate and boldness in fall field crickets (Gryllus pennsylvanicus) [30] and with activity in mosquito fish (Gambusia holbrooki) [31]. In humans, there have been suggestions that total daily energy expenditure is bounded to a fixed level such that an increase in daily energy expenditure (e.g., by engaging in physical activity) is associated with a corresponding decrease in basal energy expenditure [32]. Our results support the energy trade-off model and suggest that the energy cost associated with Extraversion (and, indirectly, the metatrait Plasticity) are compensated for by a decrease in basal metabolic rate. This conclusion is also coherent with Terracciano et al.’s observation that individuals who scored high on Extraversion saved energy by increasing their walking efficiency [23]. Whether individuals can energetically “afford” to be extraverted because of their metabolism or whether metabolism adapts to sustain the energetically demanding behaviors of some personality traits remains open for investigation.

The finding that Agreeableness, Conscientiousness, Neuroticism and, to a certain extent, Openness were not correlated with RMR can be interpreted in different ways. First, because these traits mainly encompass facets related to internal thoughts and affective states, it is possible that they vary independently from metabolism. However, we cannot exclude the possibility that a relationship does exist, but we were unable to capture it. As demonstrated before, these traits are higher in evaluativeness compared to Extraversion, indicating that social norms and values can influence how one responds to their associated questions [28]. Since our experiment was conducted on a small and intimate university campus, it is possible our participants’ responses were, intentionally or unintentionally, biased. This possibility could explain the rather low Cronbach’s alpha that we reported for these traits. In our context, an other-rater procedure may have led to a more accurate evaluation. Alternatively, our analysis may have been underpowered to detect a relationship of this size, making a larger sample size more desirable in future studies. Considered together, our results demonstrate the importance of further exploring the energetic costs of personality traits and their possible variations over the full life span.

The failure to observe a relationship between personality and PWS on a treadmill is difficult to interpret because the participants’ familiarity with this equipment was not homogenous in our sample. Future studies may want to utilize a more ecological measurement, such as the average walking speed over a 24-hour period assessed using a GPS or smartphone. In addition, the correlative nature of this research, using a single point measurement per subject and small sample size, requires caution in inferring causality since our approach does not allow for distinguishing among- and inter-individual contributions to the observed phenotypic correlation [33]. Additionally, we cannot exclude the possibility that a third, unmeasured trait affects the observed phenotypic correlation. For instance, ethnicity and time since last exercise could have been relevant control variables [22]. Nevertheless, our results raise important questions about the expected relationship between personality and metabolism within the POLS conceptual framework and highlight the importance of better understanding models of energy allocation.