Friday, September 23, 2022

Are people more averse to microbe-sharing contact with ethnic outgroup members? It seems not.

Are people more averse to microbe-sharing contact with ethnic outgroup members? A registered report. Lei Fan, Joshua M. Tybur, Benedict C. Jones. Evolution and Human Behavior, September 22 202.

Abstract: Intergroup biases are widespread across cultures and time. The current study tests an existing hypothesis that has been proposed to explain such biases: the mind has evolved to interpret outgroup membership as a cue to pathogen threat. In this registered report, we test a core feature of this hypothesis. Adapting methods from earlier work, we examine (1) whether people are less comfortable with microbe-sharing contact with an ethnic outgroup member than an ethnic ingroup member, and (2) whether this difference is exacerbated by additional visual cues to a target's infectiousness. Using Chinese (N = 1533) and British (N = 1371) samples recruited from the online platforms WJX and Prolific, we assessed contact comfort with targets who were either East Asian or White and who were either modified to have symptoms of infection or unmodified (or, for exploratory purposes, modified to wear facemasks). Contact comfort was lower for targets modified to have symptoms of infection. However, we detected no differences in contact comfort with ethnic-ingroup targets versus ethnic-outgroup targets. These results do not support the hypothesis that people interpret ethnic outgroup membership alone as a cue to infection risk.

5. Discussion

The current study was designed to improve upon van Leeuwen and Petersen (2018), which tested the outgroup-as-pathogen-cue hypothesis using only a small number of male targets and a two-item assessment of contact comfort via an English-language survey with participants recruited from the U.S. and India. Consistent with van Leeuwen and Petersen, but sampling from different populations, using larger stimulus pools and broader assessments of contact comfort, and presenting materials in participants' native languages, we did not detect effects supportive of the outgroup-as-pathogen-cue hypothesis. Nevertheless, many of our other findings were consistent with those from previous studies in the behavioral immune system literature. For example, contact comfort was negatively related to pathogen disgust sensitivity (Tybur et al., 2020; van Leeuwen & Jaeger, 2022), and was lower for faces manipulated to appear infectious relative to those unmanipulated (e.g., van Leeuwen & Petersen, 2018; van Leeuwen & Jaeger, 2022). Hence, while results indicated that people are more motivated to avoid microbe-sharing contact with individuals possessing symptoms of current infection, they did not reveal evidence that people are motivated to avoid microbe-sharing contact with ethnic-outgroup members more than ethnic-ingroup members.

5.1. Do other findings support the outgroup-as-pathogen-cue hypothesis?

We found that ethnic outgroup targets were rated as slightly more likely to have an infectious disease than were ethnic ingroup targets. However, participants reported no greater discomfort with pathogen-risky contact with outgroup members. This finding complements findings suggesting that people are averse to indirect contact with individuals possessing facial disfigurements known to not be symptoms of infection (Ryan et al., 2012). Here, rather than contact avoidance being higher for targets believed to be non-infectious, contact avoidance was no higher for targets believed to be (slightly) more infectious (cf. Petersen, 2017). Thus, such results did not entirely support the outgroup-as-pathogen-cue hypothesis.

We also detected a small relation between contact comfort and perceptions that a target is similar to individuals in the local community (Bressan, 2021). Although perceived similarity has been interpreted as a continuous measure of outgroupness (Bressan, 2021), it can also reflect myriad factors unrelated to group membership (e.g., facial morphology, eye color, etc.). Further, similarity perceptions could reflect outputs of the behavioral immune system rather than inputs into it, if similarity perceptions partially regulate contact. And, while we also detected a relation between contact comfort and reported frequency of contact with members of the target's ethnic group, the pattern was quadratic. Contact comfort was lowest for participants who reported the least previous contact with people of the target's ethnicity. However, it was lower for participants who reported the most contact frequency than it was for people who reported intermediate contact frequency.

5.2. Effects of facemasks

In addition to investigating the effects of group membership and explicit cues of infectious disease on contact comfort, we also tested whether people were more or less comfortable with microbe-sharing contact with targets wearing facemasks. We carried out this latter test because facemasks might be interpreted as indicative of infection risk and/or prosociality, and perhaps differently in a Western versus an East Asian country. Although masked targets were perceived as slightly more likely to be infectious than unmasked targets (and more so among British participants than Chinese participants), we did not detect an effect of facemask wearing on contact comfort. However, the perception of infectiousness of targets wearing a facemask varied across the two samples. As with ethnic outgroups, beliefs about infectiousness in mask wearers might not influence the infection-neutralizing motivations outputted by the behavioral immune system. Alternatively, beliefs about target infectiousness could also be offset by beliefs about the prophylactic effects of facemasks. Future research could distinguish between these possibilities.

5.3. The impact of the COVID-19 pandemic

We collected data in January 2022, when many countries were experiencing a surge in infections caused by the Omicron variants of the SARS-CoV-2 virus. The degree to which pandemic conditions impact the behavioral immune system is an open question (Ackerman, Tybur, & Blackwell, 2021). Nevertheless, this surge – as well as infections over the previous two years – might have led to a general decrease in contact comfort across targets. Even so, any decrease in global contact comfort did not prevent us from observing an effect of infection symptom on contact comfort, nor did it prevent us from observing a relation between pathogen disgust sensitivity and contact comfort (cf. Tybur et al., 2022). Indeed, the relation between pathogen disgust sensitivity and contact comfort observed here (r = −0.28) was nearly identical to that observed in similar studies before the pandemic (e.g., Tybur et al., 2020, r's = −0.22, −0.24, and −0.33 across three studies). The pandemic might have also influenced how masked faces are perceived. Given that wearing a facemask was mandatory in many settings in both the UK and China from 2020 to 2022, the pandemic might have decreased the degree to which a mask is interpreted as providing information regarding infectiousness. Further, the widespread use of facemasks across the world might have also dampened cross-cultural differences in how masks are perceived.

5.4. Limitations and future research

We recruited from the White population in the UK and the East-Asian population in China, and we used White and East-Asian stimuli. Our inferences are thus limited to these two populations, both in terms of targets and perceivers. Some findings suggest that pathogen-avoidance motives only impact antipathy toward members of groups that are sufficiently culturally distant or sufficiently associated with infectious disease (Faulkner et al., 2004; Ji et al., 2019). Even so, UK participants explicitly associated China with infectious disease, as did Chinese participants the UK, perhaps due to the origins of COVID-19 (in the case of China) and the high number of COVID-19 cases in deaths in 2020 and 2021 (in the case of the UK). Further, China and the UK differ markedly along broad cultural variables (Muthukrishna et al., 2020). For these reasons, the UK and China seem they appear suitable for testing even a narrower version of the outgroup-as-pathogen-cue hypothesis that require additional associations between a target group and cultural differences in pathogens. Nevertheless, future work could certainly test the outgroup-as-pathogen-cue hypothesis using different target groups.

We also used only a single cue to infectiousness – a skin condition intended to mimic the appearance of shingles. Naturally, infectious disease can lead to other symptoms, including other skin changes (e.g., pallor, rashes, jaundice), vocal changes (e.g., hoarseness), behavioral changes (e.g., lethargy, coughing). Infectiousness and health status can also be detected via other senses, such as olfaction (e.g., body odor, Sarolidou et al., 2020; Zakrzewska et al., 2020) and audition (e.g., voice; Fasoli, Maass, & Sulpizio, 2018). Future studies could test whether the outgroup-as-pathogen-cue hypothesis applies when targets possess different cues to infectiousness.

To date, the literature examining relations between pathogen-avoidance and intergroup biases has largely focused on phenomena such as explicit prejudice (e.g., Huang, Sedlovskaya, Ackerman, & Bargh, 2011; O'Shea et al., 2019) or implicit attitudes (e.g., Faulkner et al., 2004; Klavina et al., 2011). Less work has focused on whether people treat individual outgroup members as if they pose more of a pathogen threat than individual ingroup members. Results reported here and in van Leeuwen and Petersen (2018) cast doubt on the outgroup-as-pathogen-cue interpretation of relations between disgust sensitivity and, for example, anti-immigrant bias. Future work can naturally use approaches apart from contact-comfort ratings to evaluate the outgroup-as-pathogen-cue hypothesis. In the meantime, the field will benefit from generating and testing other hypotheses for explaining why more pathogen-avoidant individuals might feel more negatively toward outgroups.

Powerlessness Also Corrupts: Lower Power Increases Self-Promotional Lying

Powerlessness Also Corrupts: Lower Power Increases Self-Promotional Lying. Huisi (Jessica) Li, Ya-Ru Chen, John Angus D. Hildreth. Organization Science, Sep 21 2022.

Abstract: The popular maxim holds that power corrupts, and research to date supports the view that power increases self-interested unethical behavior. However, we predict the opposite effect when unethical behavior, specifically lying, helps an individual self-promote: lower rather than higher power increases self-promotional lying. Drawing from compensatory consumption theory, we propose that this effect occurs because lower power people feel less esteemed in their organizations than do higher power people. To compensate for this need to view themselves as esteemed members of their organizations, lower power individuals are more likely to inflate their accomplishments. Evidence from four studies supports our predictions: compared with those with higher power, executives with lower power in their organizations were more likely to lie about their work achievements (Study 1, n = 230); graduate students with lower power in their Ph.D. studies were more likely to lie about their publication records (Study 2, n = 164); and employees with lower power were more likely to lie about having signed a business contract (Studies 3 and 4). Mediation analyses suggest that lower power increased lying because lower power individuals feel lower esteem in their organizations (Study 3, n = 562). Further supporting this mechanism, a self-affirmation intervention reduced the effect of lower power on self-promotional lying (Study 4, n = 536). These converging findings show that, when lies are self-promotional, lower power can be more corruptive than higher power.

Men exhibit much greater variability in energy expenditure than women, being more likely to fall in the extremes

Variability in energy expenditure is much greater in males than females. Lewis G.Halsey et al. Journal of Human Evolution, Volume 171, October 2022, 103229.

Abstract: In mammals, trait variation is often reported to be greater among males than females. However, to date, mainly only morphological traits have been studied. Energy expenditure represents the metabolic costs of multiple physical, physiological, and behavioral traits. Energy expenditure could exhibit particularly high greater male variation through a cumulative effect if those traits mostly exhibit greater male variation, or a lack of greater male variation if many of them do not. Sex differences in energy expenditure variation have been little explored. We analyzed a large database on energy expenditure in adult humans (1494 males and 3108 females) to investigate whether humans have evolved sex differences in the degree of interindividual variation in energy expenditure. We found that, even when statistically comparing males and females of the same age, height, and body composition, there is much more variation in total, activity, and basal energy expenditure among males. However, with aging, variation in total energy expenditure decreases, and because this happens more rapidly in males, the magnitude of greater male variation, though still large, is attenuated in older age groups. Considerably greater male variation in both total and activity energy expenditure could be explained by greater male variation in levels of daily activity. The considerably greater male variation in basal energy expenditure is remarkable and may be explained, at least in part, by greater male variation in the size of energy-demanding organs. If energy expenditure is a trait that is of indirect interest to females when choosing a sexual partner, this would suggest that energy expenditure is under sexual selection. However, we present a novel energetics model demonstrating that it is also possible that females have been under stabilizing selection pressure for an intermediate basal energy expenditure to maximize energy available for reproduction.

4. Discussion

Our study represents a first exploration of GMV in energy expenditure, a trait that captures the net effect of many morphological, physiological, and behavioral factors. Our results indicate considerable GMV in human energy expenditure in terms of TEE, BEE, and AEE (Table 1; Figure 1, Figure 2), although the data cannot distinguish between the two prominent explanations for GMV, heterogamy and sexual selection, since both explanations predict greater trait variance in males than females. We also found GMV in key measures of body condition associated with energy expenditure: height and in particular fat-free mass (Heymsfield et al., 2007; Pontzer et al., 2021; Table 1). Height and fat-free mass correlate strongly with energy expenditure in humans (Cameron et al., 2016; Hopkins et al., 2016; Thomas et al., 2019), raising the possibility that GMV in energy expenditure is simply a result of the GMV in those morphometric traits. However, while statistically accounting for height and fat-free mass considerably reduced the within-sex variance in all three measures of energy expenditure in both males and females (with no clear, systematic, additional reduction in variance when accounting for fat mass and age), the variance ratio between males and females did not systematically decrease. In fact, statistically accounting for these morphometric variables and age resulted in a slight increase in the male:female variance ratio in all three measures of energy expenditure. In other words, remarkably, even when attempting to compare, with statistics, males and females of the same height, fat-free mass, fat mass, and age, males exhibit far more variation in TEE, BEE, and AEE than do females.

The fact that the considerable GMV in energy expenditure is not explained by variation in age, body morphometrics, and condition—key correlates of energy expenditure (Heymsfield et al., 2007; Pontzer et al., 2021)—indicates that GMV in energy expenditure is affected by other factors. It has long been known that behavioral traits are important drivers of energy expenditure. Indeed, when Lavoisier (1743–1794) first started measuring metabolic rate more than 225 years ago, it became immediately clear that organisms spend a lot more energy when active than when resting (Lighton, 2008). Activity levels are more variable in males than females consistently across diverse cultures (Althoff et al., 2017), along with hours slept per night (Ban and Lee, 2001), hours spent sitting (Parsons et al., 2009), and aerobic capacity (Olds et al., 2006), which probably explains why males have more variable AEE than do females. In turn, this is probably reflected in TEE given that AEE constitutes 33% of TEE in the current sample of adult humans (Careau et al., 2021).

In contrast to AEE, BEE by definition all but eliminates the direct effect of behavior on metabolic measurements. The fact that we observed considerable GMV in BEE, and even after factoring out body size and composition, is particularly surprising (though a similar finding can be calculated for resting energy expenditure in 104 adult males and 155 adult females having adjusted for fat-free mass; Müller et al., 2011, their Table 1). It suggests that males are more variable than females in the maintenance costs of some of the physiological components that underpin BEE and which are not reflected in measures of fat-free mass. Although hormonal differences could be a factor (Wu and O'Sullivan 2011; Wang and Xu, 2019), the proximate explanation must be the energy expenditures of the various physiological components of the body. More than 80% of the interindividual variance in BEE in humans is explained by the major body systems (Müller et al., 2018), and the remaining factors probably include the immune system (Buttgereit et al., 2000; Wolowczuk et al., 2008) and the digestive systems, including the influence of the gut microbiota on anaerobic resting metabolism (Riedl et al., 2017; Müller et al., 2018). Although there is no evidence that the mass-independent energy expenditures of various individual organs exhibit GMV (Müller et al., 2013), key elements of the cardiorespiratory system such as heart mass and lung vital capacity vary in size more in males than females (Lauer et al., 1992; Müller et al., 2011; Wierenga et al., 2017), as do two other energy-demanding systems (Müller et al., 2013), the brain (Wierenga et al., 2017) and the kidneys (Gong et al., 2012; cf. Müller et al., 2011), though probably not the liver (Chouker et al., 2004; Müller et al., 2011; Patzak et al., 2014). The spleen also exhibits GMV (Spielmann et al., 2005; Hosey et al., 2006; Müller et al., 2011), as perhaps does ‘residual mass’ which includes bone, skin, stomach, intestines, and glands (Müller et al., 2013). There is also evidence that mitochondrial energetics in response to low metabolic demands vary more in males, as does the abundance of different mitochondrial proteins in skeletal muscle, although sample sizes are fairly small and such studies are in vitro; thus extrapolation of the findings to resting muscles must be tentative (Miotto et al., 2018; Monaco et al., 2020). Blood parameters more often show GMV than the reverse (Lehre et al., 2009), though two reported measures in that study which one might a priori posit show GMV but exhibit the reverse are thyroid-stimulating hormone and tetraiodothyronine. Core temperature, albeit subtly, also exhibits GMV (Chamberlain et al., 1995).

Even though activity is eliminated from the BEE measurements, GMV in activity might still have an indirect role to play in generating GMV in BEE due to training effects. For example, regular exercise is known to increase heart size, mitochondrial count, and blood volume (McArdle et al., 2015), decrease levels of certain hormones and cytokines (Node et al., 2010; Silverman and Deuster, 2014; Pontzer, 2018), and improve mitochondrial oxidative capacity (Cardinale et al., 2018). One possibility, then, is that males have evolved to exhibit considerably more interindividual variation in AEE than have females, and that this drives greater variability in both BEE and TEE.

High energy expenditure is related to various traits that are arguably attractive to females. High BEE for a given size and body condition could positively correlate with aerobic fitness (Poehlman et al., 1989), cognitive capacity (Goncerzewicz et al., 2022), or organ function (Müller et al., 2018). High AEE is associated with high levels of physical activity, and also strength and muscle mass, characteristics known to be attractive to females or at least associated with gaining access to females (Schulte-Hostedde et al., 2008; Neave et al., 2011; Lidborg et al., 2022), in part because these characteristics signal physical fitness (Sharp et al., 1992), athletic ability, and thus competitiveness (Hugill et al., 2010), and also access to high levels of energy resources (Bonduriansky, 2007). If so, then energy expenditure does have a sexual signal component, which would associate with greater variation in males. In turn, by viewing everyday energy expenditure in adults ultimately as reproductive investment (directly and indirectly; Key and Ross, 1999), some males are investing considerably more energy in (anticipated) reproduction than are others, whereas in contrast, the variation between females in terms of energy investment in their potential reproduction is much smaller.

However, an alternative explanation for GMV in energy expenditure arises through consideration not of why male variation is greater but why female variation is lower. That is, why might females have undergone stabilizing selection—both low and high energy expenditures being selected against over time? Maximal sustained energy expenditure is intrinsically constrained at a fixed multiple of BEE, both in animals (Drent and Daan, 1980; Peterson et al., 1990) and humans (Hammond and Diamond, 1997; Thurber et al., 2019). Thus, people with a higher BEE will tend to be those with a higher maximal sustained energy expenditure. For females, this could be advantageous during lactation because it would allow them to expend more energy on reproduction (Fig. 5A). However, if there is an external constraint on sustained energy expenditure due to limited food supply, then the energy available for female reproduction would follow a peaked function with BEE (Fig. 5B). In turn, females with either high or low BEE would be selected against because this would be associated with submaximal energy being expended on reproduction. Because BEE is the dominant component of nonreproductive energy expenditure, reduced variation in BEE results in reduced variation in TEE when females are not reproducing.

[Figure 5. Conceptual model of energy availability during pregnancy in relation to basal energy expenditure (BEE). A) Sustained maximal energy expenditure is a multiple of BEE. Consequently, the energy potentially available for reproduction (calculated as sustained maximal energy expenditure minus BEE) is higher in females with a higher BEE. B) If food availability is limited, then energy intake can create a limit to sustained maximal energy expenditure (dashed line) and in turn, energy available for reproduction is not only low for females with a low BEE but also for females with a high BEE; it is highest when BEE is an intermediate value. The arrows denote selection against the extremes of low BEE and high BEE. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)]

Although our study indicates that GMV is a robust phenomenon in human energy expenditure, we cannot assume that the magnitude of GMV is consistent across all human populations and cultures. Indeed, there is a tentative indication in the present data that people from non-Western countries exhibit a still substantial but reduced GMV, due to a reduction in male variability (Fig. 4). It could be that there are features of Western cultures/societies that serve to exacerbate or attenuate GMV although what these could be are not immediately obvious (perhaps, for example, more time and money enable the sexes to pursue hobbies and lifestyles, e.g., Stoet and Geary, 2018, that contrast in terms of energy expenditure). Cultural variations in the magnitude of GMV might indicate that heterogamy is at best only part of the underlying mechanism but do not offer evidence for or against sexual selection as a predominant mechanism underlying GMV because sexual selection can have strong cultural components (Nakahashi, 2017).