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Socio-cultural norms of body size in Westerners and Polynesians affect heart rate variability and emotion during social interactions

  • Anne Schrimpf
  • Stephen McGarvey
  • Daniel Haun
  • Jana Kube
  • Arno Villringer
  • Michael Gaebler
Open Access
Original Research Article

Abstract

The perception of body size and thus weight-related stigmatization vary between cultures. Both are stronger in Western than in Polynesian societies. Negative emotional experiences alter one’s behavioral, psychological, and physiological reactions in social interactions. This study compared affective and autonomic nervous system responses to social interactions in Germany and American Samoa, two societies with different body-size related norms. German (n = 55) and Samoan (n = 56) volunteers with and without obesity participated in a virtual ball-tossing game that comprised episodes of social inclusion and social exclusion. During the experiment, heart rate was measured and parasympathetic activity (i.e., high-frequency heart rate variability) was analyzed. We found differences in both emotional experience and autonomic cardio-regulation between the two cultures: during social inclusion, Germans but not Samoans showed increased parasympathetic activity. In Germans with obesity, this increase was related to a more negative body image (comprising high rates of weight-related teasing). During social exclusion, Samoans showed parasympathetic withdrawal regardless of obesity status, while Germans with obesity showed a stronger increase in parasympathetic activity than lean Germans. Furthermore, we found fewer obesity-related differences in emotional arousal after social exclusion in Samoans as compared to Germans. Investigating the interplay of socio-cultural, psychological, and biological aspects, our results suggest influences of body size-related socio-cultural norms on parasympathetic cardio-regulation and negative emotions during social interactions.

Keywords

Emotion Culture Obesity Social cognition Samoa Parasympathetic activity Body image Social exclusion 

Introduction

Culture and idealized bodies

Human bodies and their shapes, sizes, and variations are significantly embodied in social relations. They are both reflection and construction of a society’s beliefs and norms. Hence, they create identity and either affiliation to or dissociation from a social group (McCullough 2013; Waskul and van der Riet 2002). Regarding body size, ethnographic research demonstrates a huge variability of body norms and body perception in different cultures, ranging from idealization to stigmatization of higher body weight (Brown and Konner 1987; Treloar et al. 1999).

In today’s Western societies, the idealized body is slender. In addition, being obese is often accompanied by weight-related stigmatization and social exclusion. Individuals with excess weight—especially women (Puhl et al. 2007)—are facing disadvantages in professional contexts such as on the labour market (Puhl and Brownell 2001) but also in private areas, for example in the form of teasing in significant interpersonal relationships (Puhl et al. 2008).

In other societies, excess body weight does not always have the same negative social consequences as in Western societies. Although an idealization of slim bodies has been increasingly reported worldwide (Becker 2004; Brewis et al. 2011; Swami et al. 2010), there is still considerable variation between cultural groups (Anderson-Fye 2012; Furnham et al. 2002; Gupta et al. 2001; Kronenfeld et al. 2010; Swami et al. 2013). A parallel development has been reported for weight-related stigmatization: prejudice towards individuals with excess body weight is spreading worldwide, even in cultures that were conventionally understood to show no to little weight-related stigmatization (Brewis et al. 2011). Nevertheless, the extent of prejudice still varies between cultural groups (Brewis and Wutich 2014; Hebl et al. 2009; Pepper and Ruiz 2007; Puhl et al. 2015).

Polynesian societies are particularly known to value bigger bodies. Traditionally, Pacific Islanders relate individual plumpness to the well-being of the community and, especially in women, to fertility (Pollock 1995). Although morbid obesity was not valued per se, excess weight was traditionally more likely to be associated with a certain rank or status within the society and represented authority or power (Mavoa and McCabe 2008; Pollock 2001). Nowadays, an idealization of slim body sizes has been observed in the overall population of Polynesian societies (also on the Samoan islands; Brewis et al. 1998; Swami et al. 2007; Wilkinson et al. 1994). Nevertheless, this idealization is generally less pronounced in Pacific Islanders than in Westerners (Brewis and McGarvey 2000; Craig et al. 1999; Metcalf et al. 2000; Wilkinson et al. 1994). Further, an increased idealization of slim body sizes might not be accompanied by increased stigmatization in Samoa. Research suggests that Samoans do not view individuals with obesity as negatively as Westerners do (Brewis et al. 1998). Hardin (2015) described in her study in Samoa an ambivalent interpretation of body fat, which is dependent on the person’s relations and behavior. On the one hand, oversized bodies identify ranked positions, are a visible display of the quality of interpersonal relationships, and represent generosity, caregiving, and reciprocity (Becker 1995; Hardin 2015; Pollock 2001). On the other hand, wealth accumulation, greed, or sickness can similarly be embodied in large body sizes—as signs of unethical behavior and violation of the society’s interests (Hardin 2015). In the context of health care, obesity is widely accepted as a major concern for public health in Samoa (McGarvey 2009). In summary, (1) size and shape of human bodies play an important role in social relations, but (2) bigger bodies are not stigmatized per se in every culture—despite a spreading slim ideal worldwide. Individuals with obesity in different cultures might therefore be affected differently in social interactions—on emotional and psychophysiological levels.

The impact of stigma on emotionality and physiology

To understand the impact of weight-related stigmatization on individuals with obesity, the literature was reviewed for general effects of social exclusion: Stigmatization, exclusion, and rejection have effects on emotionality and behavior in social situations and impact the target’s well-being by increasing emotional distress, depressive symptoms, and risks for psychopathology (e.g., eating disorders; Baumeister and Leary 1995). Indeed, experimentally induced social exclusion in Western participants was associated with negative affect (Blackhart et al. 2009). Further, individuals with recurrent negative social experiences anticipate potentially stigmatizing situations in future social interactions (Swim et al. 1998) and show an increased attention to signs of prejudice (Kaiser et al. 2006; Tanaka and Ikegami 2015). This adaptive behavior allows the target of prejudice to apply coping strategies—such as avoidance or disengagement—that reduce the negative impact on psychological well-being (Barreto and Ellemers 2015).

Social exclusion is associated not only with behavioral and affective, but also with autonomic alterations. Studies analyzing heart rate (HR) and HR variability (HRV) linked socio-emotional processes to activity of the autonomic—particularly the parasympathetic (PNS)—nervous system: The “polyvagal theory” relates PNS or vagal activation (measurable as increased HRV) to emotional and particularly social processing or behavior (Porges 2003, 2007). In this view, vagal withdrawal supports the mobilization of fight-or-flight behavior, whereas increased vagal influence supports emotion regulation, attention, and (spontaneous) social engagement behaviors (Porges 2003, 2007). The “neurovisceral integration model” associates increased HRV with physiological and behavioral flexibility to changing environmental demands (Thayer and Lane 2000, 2009). It thereby connects psychological phenomena like affect and attention (also in the shape of emotion regulation) to the nervous systems (Thayer and Lane 2000, 2009). Studies support these models by associating heightened PNS activity with attention to motivationally relevant stimuli like threatening animals (Jönsson and Hansson-Sandsten 2008), angry facial expressions (Jönsson and Sonnby-Borgström 2003), receiving negative as compared to positive social feedback (Vanderhasselt et al. 2015), or watching other people suffer (Stellar et al. 2015). Associations between heightened PNS activity and effortful emotion regulation have also been found: participants reappraising or suppressing their emotions during social interactions showed higher PNS activity than uninstructed participants (Butler et al. 2006). Other studies report increased PNS activity relative to baseline during emotion suppression while watching a negative but not while watching a positive film clip (Musser et al. 2011) and a general association between increased HRV and better self-regulation (Holzman and Bridgett 2017). During negative social interactions and rejection, PNS activity has been reported to decrease (Iffland et al. 2014; Murray-Close 2011; Shahrestani et al. 2015) but also to increase (Gunther Moor et al. 2014; Gunther Moor et al. 2010; Papousek et al. 2014). These divergent results provide first evidence for alterations in autonomic activity during negative social feedback but require further investigation.

To our knowledge, there has been little psychophysiological research on how individuals with obesity and stigmatizing experiences respond to social situations. The two existing studies are from our own lab: We found that women with obesity compared to lean women showed slower response times during the anticipation of social compared to monetary feedback. This differential response was more pronounced in women with obesity with higher body mass index (BMI) and more intense weight-related teasing experiences (Kube et al. 2016). Further, we showed that German women with obesity responded with a stronger increase in PNS activity during a social interaction episode than lean participants. This increase in PNS activity in the group with obesity but not in the lean group was positively associated with negative body image. Additionally, women with obesity reported a stronger decrease in mood after social exclusion than other participants (Schrimpf et al. 2017). Other studies found that participants with higher BMI perceive themselves as less socially included than participants with lower BMI (Hartung and Renner 2013) and women with a negative body image perceived social feedback regarding their own body portrait as more negative in comparison with another woman’s body portrait, even though the feedback was equal (Alleva et al. 2014). In conclusion, there is first evidence that negative social experiences in general—and weight-related stigmatization in particular—affect emotionality and autonomic activity during social situations. However, these studies did not consider culture or varying cultural norms.

Cultural differences in emotional and physiological responses

To date, research comparing emotional or physiological responses to social-cognitive tasks in different human populations is scarce and research comparing body-size related socio-emotional experiences in different cultural environments is nonexistent. At the same time, the few existing studies suggest that populations differ considerably in their behavior during experimental tasks (see for review: Henrich et al. 2010). Further, a line of research showed that, on a continuum, collectivistic (personal goals overlap with goals of the in-group, e.g. family) and individualistic (personal goals might be independent of in-group goals) self-concepts vary between cultural groups and influence social experiences (Markus and Kitayama 1991; Triandis 1989). Individuals from individualistic backgrounds spend equal time with in-group and out-group members and belong to more groups, whereas individuals from collectivistic backgrounds spend more time with in-group members and differentiate more strongly between in-group and out-group members (see meta-analysis by Oyserman et al. 2002). Lower individualism was also related to higher levels of conformity during social interactions (Bond and Smith 1996). Emotional responses to social interactions are also influenced by culture: empirical results support the hypothesis that more individualistic groups are more strongly affected by social exclusion than more collectivistic groups as their social ties might differ in their reliability. That is, members of a more interdependent group can rely more strongly on social networks (Markus and Kitayama 1991; Over and Uskul 2016; Pfundmair et al. 2015). For instance, farmers children (a more interdependent group) rated social exclusion as less painful than herders children (a more independent group) in Turkey (Over and Uskul 2016) and German participants (a more independent group) showed lower fulfillment of basic social needs after social exclusion than Turkish, Chinese, or Indian participants (more interdependent groups; Pfundmair et al. 2015).

Dissecting the more biological, interculturally relatively stable components of emotional responses and the aspects that are modified by culture is difficult (Barrett 2012; Gerber 1985; Lindquist et al. 2013; Scherer and Wallbott 1994). According to a recent “biopsychosocial framework” (Immordino-Yang and Yang 2017), socio-emotional experience and its psychophysiological components depend on culturally constructed norms of emotional behavior and emotion expression. In particular, the model mentions culture-specific expectations about appropriate behavior (Immordino-Yang et al. 2016; Mesquita et al. 2016; Mesquita and Frijda 1992) and verbal descriptions and definitions of emotions (Crivelli et al. 2016; Gerber 1985; Saxbe et al. 2012). Thus, varying cultural demands and contexts can result in different interpretations of emotions as well as in different physiological responses during emotional arousal.

The present study

Although HRV has been associated with social and emotional processing and socio-emotional phenomena are influenced by culture (Barrett 2012; Immordino-Yang and Yang 2017), cultural aspects are not explicitly part of either of the prominent theories of HRV (see above and Porges 2003, 2007; Thayer and Lane 2000, 2009). Furthermore, most HRV studies have been conducted with Western participants and the association between culture and HRV is rarely investigated (but cf. Immordino-Yang and Yang 2017). Cross-cultural research using HRV in individuals with obesity and potentially differing body ideals is nonexistent. By investigating socio-emotional experience and parasympathetic cardioregulation during social interactions in different cultures, we aimed to contribute to a more comprehensive understanding of the psychophysiology of HRV and of emotion in general. The present study was carried out in Germany, an individualistic society, and American Samoa, a collectivistic society. We investigated (1) general differences in emotional and physiological responses to social situations between a Western and a Polynesian population, and (2) how socio-cultural norms regarding body size influence the psychophysiological processing of social interactions in individuals with and without obesity. We used a virtual ball-tossing game (“Cyberball” by Williams et al. 2000) to induce standardized episodes of social inclusion and exclusion. With regard to general location differences (1), we hypothesized—in accordance with the “biopsychosocial framework” (Immordino-Yang and Yang 2017) and with studies showing differences in emotional responses to social exclusion between individualistic and collectivistic societies (Over and Uskul 2016; Pfundmair et al. 2015)—an effect of location on affective and PNS responses to social interactions. With regard to body size-related socio-cultural norms (2), we expected to find a comparable ideal in slim body sizes as has been shown in previous studies (Brewis et al. 2011; Swami et al. 2010). However, as the Samoan society does not entertain the same negative attitudes towards individuals with excess body weight as Western societies (Brewis et al. 2011), we expected to find less weight-related teasing experiences and body dissatisfaction in the former than in the latter. We also expected the Samoan sample to show fewer obesity-related differences in affective and PNS responses during social inclusion and exclusion—due to a more ambiguous interpretation of body sizes (Hardin 2015)—than we found in the German sample (Schrimpf et al. 2017). We also expected in Germans with obesity and with a potential history of weight-related negative social experiences psychophysiological alterations in the social inclusion session due to a potential enhanced sensitivity to social cues even in neutral social situations (Barreto and Ellemers 2015; Kaiser et al. 2006; Swim et al. 1998; Tanaka and Ikegami 2015). As these previous results from Germany were more pronounced in women with obesity, we hypothesized interactions with sex in affective and PNS responses during social interactions. Lastly, we examined potential influencing factors such as negative body image and/or interpersonal stress, which we anticipated to alter emotional and psychophysiological responses to social interactions.

Methods

Participants

Two sets of data were collected in Germany (from 12/2012 to 03/2014) and American Samoa (from 09/2015 to 12/2015). The German sample has been described in more detail in Schrimpf et al. (2017). German participants were recruited from the database of the Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany and pre-selected by weight status. A total of 112 healthy individuals, matched for educational background and age, were included in the study. Participants were required to be between 18 and 35 years of age and have BMIs ≥ 30.0 kg/m2 for obese, or between 18.5 and 24.9 kg/m2 for lean participants. Exclusion criteria were a self-reported history of neurological and psychiatric disorders, smoking, and regular substance or medication use. In the previous study (Schrimpf et al. 2017), half of the 112 participants first completed the social inclusion and then the social exclusion session while the experiment for the other half of participants consisted of two social inclusion sessions. As we were particularly interested in social exclusion, we adapted the experiment for American Samoa. There, all participants first completed the social inclusion and then the social exclusion session (more details of the procedure below). To ensure comparability between the two data sets, we only included German participants that underwent the same procedure as in American Samoa. Thus, 55 German participants entered the analyses (14 lean women, 14 women with obesity, 13 lean men and 14 men with obesity).

As the recruited participants in Germany were mostly University students, we recruited a comparable sample—young, educated adults—in American Samoa. The American Samoa Community College is the only institution on the island for higher education, which is why study participants were randomly recruited at the campus area by (1) availability and (2) by a pre-weight screening. A total of 60 healthy individuals, matched for educational background and age, participated in this study. Inclusion criteria were similar to the ones in Germany (i.e., participants should be between 18 and 35 years of age). Additionally, participants were required to be fluent in English. BMI criteria were adjusted to a recommended cut-off for Polynesian populations as Pacific Islander’s body composition consists of a higher percentage of muscle mass and thus differs from Europeans with an equivalent BMI (Rush et al. 2009): BMI ≥ 32.0 kg/m2 for participants with obesity and BMI between 18.5 and 27.9 kg/m2 for lean participants. Exclusion criteria were the same as in the German sample. Four individuals were excluded because of a BMI between 28.0 and 31.9 kg/m2, so that 56 participants were included in the analyses: 13 lean women, 15 women with obesity, 12 lean men and 16 men with obesity (detailed sample characteristics for both data sets in Table 1).
Table 1

Sample characteristics

 

Germany

American Samoa

Weight

Culture

Weight *culture

Lean individuals

n = 27

Individuals with obesity

n = 28

Lean individuals

n = 25

Individuals with obesity

n = 31

F

p

F

p

F

p

Anthropometrics

 Age

27.11 ± 3.2

27.43 ± 3.3

19.84 ± 2.0

20.55 ± 1.8

0.963

.329

190.533

.001

0.142

.707

 BMI

21.90 ± 1.7

35.18 ± 3.3

25.55 ± 2.7

40.55 ± 6.5

309.073

.001

9.695

.002

1.217

.273

 WHR

.77 ± .06

.90 ± .11

.78 ± .04

.85 ± .07

93.797

.001

0.698

.406

11.008

.001

 Sports h/week

3.64 ± 3.7

2.84 ± 2.7

4.54 ± 3.8

2.87 ± 2.7

4.081

.046

0.324

.570

0.558

.457

Components derived from questionnaires

 Social stress

− .42 ± .77

− .48 ± .73

.47 ± .95

.42 ± 1.1

0.085

.771

7.850

.006

0.002

.962

 Negative body image

− .92 ± .54

.93 ± .75

− .61 ± .50

.45 ± .78

150.463

.001

2.128

.148

11.101

.001

 Interpersonal trust

.16 ± 1.1

.04 ± 1.1

.15 ± .90

− .30 ± .80

2.164

.144

0.152

.697

0.916

.341

 Low self-monitoring in public

.73 ± .70

.59 ± .72

− .72 ± .81

− .59 ± .80

0.016

.900

21.497

.001

0.828

.365

Visual analogue scales baseline

 Mood (mm)

7.30 ± 1.3

7.68 ± 1.4

8.24 ± 1.1

7.45 ± 2.2

0.587

.445

1.424

.236

3.894

.051

 Happiness (mm)

6.70 ± 1.3

6.54 ± 1.2

7.66 ± 1.9

7.15 ± 2.2

1.092

.299

4.033

.047

0.289

.592

 Feelings of acceptance (mm)

7.70 ± 1.5

7.76 ± 1.5

7.95 ± 1.6

8.12 ± 1.7

0.106

.746

2.283

.134

0.008

.928

Heart rate baseline

 Mean HR (bpm)

81.40 ± 11.6

79.75 ± 8.1

70.90 ± 11.4

75.74 ± 10.8

0.814

.369

7.878

.006

2.804

.097

 LF power (ms2)

1346 ± 1293

1403 ± 1221

2774 ± 3797

1908 ± 2174

1.086

.300

1.849

.177

1.311

.255

 HF power (ms2)

516 ± 611

787 ± 822

1874 ± 2613

1237 ± 1566

0.298

.586

0.641

.425

2.497

.117

 HF power n.u.

26.67 ± 17.3

34.47 ± 20.3

40.37 ± 19.4

38.51 ± 14.9

1.030

.313

0.916

.341

2.068

.153

 LF/HF power (log10)

.51 ± .41

.35 ± .47

.18 ± .38

.22 ± .30

0.986

.323

1.102

.296

2.121

.148

Significant p-values appear in bold

BMI Body Mass Index, WHR waist-to-hip-ratio, HR heart rate, LF low frequency power, HF high frequency power, HF power n.u. normalized units, LF/HF ratio between LF and HF power. Univariate ANCOVAs. Values represent mean ± SD

All participants gave written informed consent and received a monetary reimbursement for their participation. The study was carried out in accordance with the Declaration of Helsinki and was approved by the research ethics committees of the Leipzig University and the American Samoa Department of Health, respectively.

Procedure

All participants completed questionnaires assessing demographic information, body image, stress, depressive symptoms, and rejection sensitivity. Body weight, body height, as well as waist and hip circumference were measured and a full-body picture was taken of each participant. Participants then completed the Cyberball paradigm, a virtual ball-tossing game to induce a standardized social interaction experience (Williams et al. 2000). They were instructed by the experimenter that two other invited participants were sitting in nearby rooms (in Germany) or online (in American Samoa) and would play a ball game with the participant. In reality, the two confederates were computer-generated. All players were represented on the computer screen by avatars and a full-body picture. The participant’s avatar and picture were located at the bottom center (Fig. 1). The two confederates had the same sex as the participant. To induce a potentially stigmatizing situation, the pictures of the computer-generated players were in a lean body shape. Photographs of the two female and male lean players were taken of coworkers at the Max Planck Institute.
Fig. 1

Paradigm. a Overall experimental timeline. b The participant and the two confederates were represented on the computer screen by drawings, a full-body picture, and their names. The participant’s character, picture, and name were located at the bottom center

At the beginning, participants completed initial visual analogue scales (VASs) to assess baseline mood, happiness, and feelings of being accepted (Table 1). Scores ranged from “not at all” (0 mm) to “very much” (100 mm). Then, the ECG electrodes were attached (see below for details). Before the start of the experiment, a 4-min HR measurement at rest was acquired. This was followed by two 6-min sessions of the Cyberball game. In the first session, all participants were included in the game, whereas in the second session, all participants were excluded. Participants were able to throw the ball to the confederates with a computer mouse. The inclusion session consisted of approximately 150 ball throws and every player received the ball equally often throughout the game. Each trial of the computer-generated players lasted between 1600 and 4600 ms, consisting of a randomized waiting period (1000–4000 ms) and a “throw and flight” period (600 ms).

The inclusion session ended with a break, during which participants completed a second set of VASs to assess mood, happiness, and feelings of being accepted. In the exclusion session of the game, participants received just one ball per minute after the first three throws. This resulted in approximately seven ball tosses during the 6 min (as compared to ~ 50 in the inclusion condition). At the end, participants completed a final set of VASs to again measure mood, happiness, and feelings of being accepted. All participants were debriefed at the end of the experiment.

Psychometric measures and factor analysis

All participants completed a battery of questionnaires in German or English, to assess individual personality traits, body image, and stress: Body Image Avoidance Questionnaire (BIAQ, Legenbauer et al. 2007; Rosen et al. 1991), Body Shape Questionnaire (BSQ, Cooper et al. 1987; Pook et al. 2002), Eating Disorder Inventory (EDI-2, Garner 1991; Thiel et al. 1997), Figure Rating Scales (FRS, Stunkard et al. 1983), NEO Five-Factor Inventory (NEO-FFI, Borkenau and Ostendorf 1993; Costa and McCrae 1992), Perceived Stress Questionnaire (PSQ-20, Fliege et al. 2001; Levenstein et al. 1993), Perceived Stress Scale (PSS-10, Cohen et al. 1983; Klein et al. 2016), Perception of Teasing Scale (POTS, Thompson et al. 1991), Rejection Sensitivity Questionnaire (RSQ, Downey and Feldman 1996; Staebler et al. 2011), and Trier Inventory for Chronic Stress (TICS, Schulz and Schlotz 1999).

A principal component analysis (PCA) with oblique rotation (oblimin) was conducted using IBM SPSS Statistics 23 (Armonk, NY, USA) to reduce the number of variables and extract convergent latent factors across different measures of self-related social experiences. Only those total scores of questionnaires or specific subscales were included that fulfilled criteria for PCA. The Kaiser–Meyer–Olkin (KMO) measure of .86 (with all KMO values for individual scales > .65 and thus above the threshold of .5) confirmed the sampling adequacy for the analysis. The correlations between scales were sufficiently large for a PCA (Bartlett’s test of sphericity χ2(300) = 1673.343, p < .001). In the initial analysis, five components had eigenvalues over 1 (Kaiser’s criterion) and explained 67.25% of the variance. The scree plot showed inflexions that justified retaining four components (explaining 61.97% of the variance). Cronbach’s alpha was sufficient for the first two components (Table S1), which is why only those two were included in further analysis. After evaluation of the scales that clustered on the same component, component one was summarized as social stress and component two as negative body image. Scales clustering on component social stress, among others, high social tensions, social isolation, and social overload. Scales clustering on component negative body image included, among others, body dissatisfaction, high frequency of weight-related teasing and a pronounced drive for thinness.

HR data recordings and analysis

For the German sample, a one-lead ECG was recorded at 500 Hz using a BrainAmp ExG amplifier and BrainVision Recorder software (Version 1.20.0506, Brain Products, München, Germany). Three Ag/AgCl electrodes (MES Forschungssysteme GmbH, Gilching, Germany) were placed between the right clavicle and sternum, on the left side between the two lower rips, and on the right lower abdomen.

For the Samoan sample, a one-lead ECG was measured using a Polar H6 chest strap (centered on the sternum) and interbeat (RR) intervals were recorded (in ms, i.e., at 1000 Hz) using the app “Heart Rate Variability Logger” (http://www.marcoaltini.com/apps.html) via Bluetooth on an Android smartphone (LG L40). Before the data acquisition in Samoa, comparability between the two devices, setups, and electrode placements was tested in a small validation experiment, which showed that simultaneously acquired interbeat intervals were correlated with r > .99 (the details including data, scripts, and results with figures can be found at https://github.com/michagaebler/Polar_H6_ECG_Test/), confirming previous observations by other researchers (e.g., http://www.marcoaltini.com/blog/heart-rate-variability).

Raw ECG data (for the data acquired in Germany) and tachograms (for the data acquired in Samoa) were imported into Kubios (Version 2.2, Biosignal Analysis and Medical Imaging Group, University of Eastern Finland, http://kubios.uef.fi/) and visually inspected. The Kubios artifact correction level “very low” was applied, which identifies and (cubic-spline) interpolates RR intervals that differ more than 0.45 s from the local mean RR interval. The amount of corrected peaks did not exceed 0.3% of the total analyzed data and the number of corrected peaks was equally distributed in subsamples (interaction of location * weight: F(3, 107) = 0.003, p = .957). HR and HRV were analyzed in the frequency domain, the latter through Fast Fourier transformation using Welch’s periodogram method with a sliding window of 256 s and 50% overlap. We extracted low frequency (LF, 0.04–0.15 Hz) and high frequency (HF, 0.15–0.4 Hz) power but will focus on HF power, since it is more clearly interpretable as PNS activation (Billman 2013; Thayer and Lane 2000). LF power was used to transform HF power into normalized units (n.u.) by dividing HF power through the total LF and HF power. This normalization removes unequal distribution of the raw data and increases comparability between individuals and studies (Burr 2007). The values of mean HR and HF power n.u. were normally distributed. All raw HRV values for baseline and experimental sessions can be found in Table S2.

Statistical analysis

All statistical analyses were carried out using IBM SPSS Statistics 23 (Armonk, NY, USA) with a two-sided α-level of .05. Greenhouse–Geisser corrections were used to adjust the degrees of freedom in mixed-design analyses of variance (ANOVAs) in case the assumption of sphericity was violated according to the Mauchly test. In this case, we report uncorrected degrees of freedom, corrected p-values, and epsilon (ε). Estimated effect sizes are reported using partial eta squared (η p 2 ). Post-hoc tests were adjusted using Bonferroni correction. Between-subject factors are defined as follows: “weight” (lean, obese), “location” (Germany, American Samoa), and “sex” (women, men). As the two location groups significantly differed in age, the mean-centered covariate “age” was included in all mixed-design analyses of covariance (ANCOVAs). Age has been found to decrease PNS activity at rest (Agelink et al. 2001), cardiac reactivity to induced emotions (Labouvie-Vief et al. 2003), as well as intensity of emotions experienced during social interactions (Charles and Piazza 2007). Even in our sample, which had a relatively restricted age range, higher age was significantly associated with lower PNS activity (HF power: r(111) = − .30, p = .002; HF power n.u.: r(111) = − .24, p = .011) and with lower negative emotional responses after social exclusion (changes in happiness: r(111) = .19, p = .050; changes in mood.: r(111) = .19, p = .048).

Group differences in the participant characteristics (components, body size preference, and weight-related teasing) and baseline affect and HRV data (Table 1) were analyzed using univariate ANCOVAs with between-subject factors “weight”, “location”, and “sex”. VAS changes over time were analyzed using separate mixed-design ANCOVAs for all time points, employing the within-subject factor “time” (baseline, social inclusion, social exclusion) and between-subject factors “location”, “weight”, and “sex”. HRV changes from baseline to social inclusion and HRV changes from baseline to social exclusion were examined separately. Mixed-design ANCOVAs for all time points were used with the within-subject factor “time” and between-subject factors “weight”, “sex”, and “location”.

Furthermore, two-sided bivariate correlations were calculated to analyze the association of HRV with state and trait variables (VAS and principle components).

Results

Weight-related teasing and body image

Means and standard deviations for each variable in each group can be found in Table 1. Statistics on group characteristics can be found in the online supplementary material (Supplement S3). To test the assumption that while body size ideal is comparable between the two locations, American Samoans experience less weight-related teasing and have a more positive body image than Westerners/Germans, the (1) preferred body figure on the Figure Rating Scale and the two POTS sub-scales (2) frequency of weight-related teasing and (3) emotional pain after teasing were analyzed: (1) We did not find a significant difference in body size preference between the two locations (F(1, 103) = 0.812, p = .157, η p 2  = .019). (2) A significant main effect of weight (F(1, 102) = 34.931, p < .001, η p 2  = .255) indicates that individuals with obesity reported a higher frequency of weight-related teasing than lean individuals. No effects of sex, location, or interactions were found. (3) The analysis of emotional pain after teasing showed a main effect of weight (F(1, 102) = 32.925, p < .001, η p 2  = .244), a location * weight interaction (F(1, 102) = 7.608, p = .007, η p 2  = .069), and a location * sex * weight interaction (F(1, 102) = 4.520, p = .036, η p 2  = .042). The latter interaction indicated that Samoan women with obesity reported lower emotional pain after teasing (M = 1.62, SE = .26) than German women with obesity (M = 3.15, SE = .28, p < .001). While German women with obesity reported more emotional pain after teasing (M = 3.15, SE = .28) than German lean women (M = 1.09, SE = .27, p < .001), there was no statistically significant difference between Samoan women with (M = 1.62, SE = .26) and without obesity (M = 1.27, SE = .29, p = .315). Further, German men with obesity reported more emotional pain after teasing (M = 2.22, SE = .28) than German lean men (M = 1.30, SE = .28, p = .011).

The PCA component negative body image showed significant group differences (main effect of sex: F(1, 102) = 6.410, p = .013, η p 2  = .059; main effect of weight: F(1, 102) = 150.463, p < .001, η p 2  = .596; location * weight interaction: F(1, 102) = 11.101, p = .001, η p 2  = .098). The interactions indicated that German participants with obesity had a more negative body image (M = 1.05, SE = .15) than Samoan participants with obesity (M = .35, SE = .14, p = .003).

Social stress

A significant main effect of location for the component social stress (F(1, 102) = 7.850, p = .006, η p 2  = .071) indicated more social stress in the Samoan (M = .41, SE = .17) as compared to the German group (M = -.42, SE = .17).

Experimental results: affect

The analyses over all three measurement times for mood showed significant main effects of time (F(2, 204) = 13.341, p < .001, η p 2  = .116), location (F(1, 102) = 5.253, p = .024, η p 2  = .049), and a location * weight interaction (F(1, 102) = 4.788, p = .031, η p 2  = .045). Samoans had a better mood (M = 7.85, SE = .28) than Germans (M = 6.73, SE = .28) and mood was decreasing from social inclusion (M = 7.35, SE = .17) to exclusion (M = 6.86, SE = .19, p = .010). Further, Samoan lean participants had a better mood (M = 8.29, SE = .37) than German lean participants (M = 6.54, SE = .35, p = .003) as well as Samoan participants with obesity (M = 7.41, SE = .32, p = .033, Fig. 2a).
Fig. 2

Affect ratings assessed with visual analogue scales. a Differences in mood between individuals with and without obesity in Samoa and Germany (location * weight interaction: (F(1, 102) = 4.788, p = .031, η p 2  = .045). Samoan lean participants had a better mood than German participants as well as Samoan participants with obesity. b Differences in happiness between the two locations (main effect location: F(1, 102) = 6.728, p = .011, η p 2  = .062). Samoans felt happier than Germans. c Feeling of being accepted (location * sex * weight interaction: F(1, 102) = 6.684, p = .011, η p 2  = .061). Samoan women with obesity felt more accepted than German women with obesity, Samoan lean men felt more accepted than German lean men. Values represent mean ± SE

For happiness, we found significant main effects of time (F(2, 204) = 5.178 ε = .801, p = .011, η p 2  = .048) and location (F(1, 102) = 6.728, p = .011, η p 2  = .062). Participants felt less happy after social exclusion (M = 6.56, SE = .18) compared to baseline (M = 7.00, SE = .16, p = .031), whereas there was no difference between social inclusion (M = 6.90, SE = .16) and baseline (M = 7.00, SE = .16, p = 1.000). Samoans (M = 7.47, SE = .29) felt overall happier than Germans (M = 6.17, SE = .29) (Fig. 2b).

For the feeling of being accepted, we found significant main effects of time (F(2, 204) = 40.760, ε = .723, p < .001, η p 2  = .286) and location (F(1, 102) = 8.734, p = .004, η p 2  = .079). Participants felt less accepted after social exclusion (M = 6.51, SE = .20) compared to social inclusion (M = 7.68, SE = .16) and to baseline (M = 7.88, SE = .15). Samoans (M = 8.06, SE = .28) felt overall more accepted than Germans (M = 6.65, SE = .28). A significant between-subject interaction of location*sex*weight (F(1, 102) = 6.684, p = .011, η p 2  = .061) indicated that Samoan women with obesity (M = 8.28, SE = .43) felt more accepted than German women with obesity (M = 6.30, SE = .44, p = .004) and Samoan lean men (M = 8.31, SE = .48) felt more accepted than German lean men (M = 6.02, SE = .45, p = .002, Fig. 2c).

Experimental results: cardiac measures

Social inclusion

The analysis of the HF power n.u. showed significant main effects of time (F(1, 102) = 10.941, p = .001, η p 2  = .097) and sex (F(1, 102) = 19.717, p < .001, η p 2  = .162). A significant time * location interaction (F(1, 102) = 4.825, p = .030, η p 2  = .045) indicated a significant increase in HF power n.u. in German (baseline: M = 32.25, SE = 3.31, social inclusion: M = 42.23, SE = 2.87, p = .001) but not in Samoan participants (baseline: M = 37.69, SE = 3.29, social inclusion: M = 37.12, SE = 2.86, p = .838). A time * sex * weight interaction (F(1, 102) = 7.698, p = .007, η p 2  = .070) showed that only women with obesity and lean women had a significant increase from baseline to social inclusion (lean women baseline: M = 37.18, SE = 3.41, social inclusion: M = 43.91, SE = 2.96, p = .022; women with obesity baseline: M = 39.77, SE = 3.28, social inclusion: M = 53.42, SE = 2.85, p < .001; lean men baseline: M = 29.33, SE = 3.54, social inclusion: M = 32.99, SE = 3.07, p = .224; men with obesity baseline: M = 33.59, SE = 3.24, social inclusion M = 28.38, SE = 2.81, p = .060). Further, the increase in HF power n.u. was stronger in women with obesity (M = 13.65, SE = 2.78) than in men with obesity (M = -5.22, SE = 2.74, p < .001) and in lean women (M = 6.73, SE = 2.88, p = .087). Men with obesity had a stronger decrease (M = -5.22, SE = 2.74) than lean men (M = 3.66, SE = 2.99, p = .031; Fig. 3a).
Fig. 3

Parasympathetic cardio-regulation. a Changes in high-frequency (HF) power normalized units (n.u.) for social inclusion (relative to baseline): a significantly stronger increase in women with obesity during social interaction independent of culture (time * sex * weight interaction: F(1, 102) = 7.698, p = .007, η p 2  = .070). b Changes in HF power n.u. for social exclusion showed that German individuals with obesity had a higher HF power n.u. than German lean individuals, while there was no group difference in the Samoan sample. Women with obesity showed a stronger response of HF power n.u. during social exclusion than lean women and men with obesity (non-significant trend for a location * weight interaction: F(1, 102) = 3.880, p = .052, η p 2  = .037; and time * sex * weight interaction: F(1, 102) = 3.840, p = .053, η p 2  = .036). Values represent mean ± SE

Social exclusion

The analysis of HF power n.u. showed a main effect of sex (F(1, 102) = 18.407, p < .001, η p 2  = .153), a time * location interaction (F(1, 102) = 8.069, p = .005, η p 2  = .073), and a non-significant trends for the interactions of location * weight (F(1, 102) = 3.880, p = .052, η p 2  = .037) and time * sex * weight (F(1, 102) = 3.840, p = .053, η p 2  = .036). Women had a higher HF power n.u. (M = 40.08, SE = 1.95) than men (M = 28.14, SE = 1.98, p < .001). German participants showed an increase in HF power n.u. during exclusion (baseline: M = 32.25, SE = 3.31, social exclusion: M = 38.02, SE = 2.95, p = .063), whereas Samoan participants showed a decrease (baseline: M = 37.69, SE = 3.29, social exclusion: M = 28.50, SE = 2.94, p = .003). In the German sample, individuals with obesity had a higher HF power n.u. (M = 39.69, SE = 3.40) than lean individuals (M = 30.57, SE = 3.35, p = .023), while there was no group difference in the Samoan sample. Further, women with obesity showed a stronger response of HF power n.u. during social exclusion (M = 46.25, SE = 2.93) than lean women (M = 37.14, SE = 3.04, p = .033) and men with obesity (M = 24.11, SE = 2.89, p < .001). Over time, women with obesity showed an increase in HF power n.u. (baseline: M = 39.77, SE = 3.28, social exclusion: M = 46.25, SE = 2.93, p = .035), whereas men with obesity showed a decrease (baseline: M = 33.59, SE = 3.24, social exclusion: M = 24.11, SE = 2.89, p = .002; Fig. 3b). There was no difference in HF power n.u. over time in lean women and men.

Psychometrics and HRV

Correlation coefficients were calculated between changes in HF power n.u. and the components social stress and negative body image. The analysis of the changes from baseline to social inclusion showed in the German group with obesity a significant positive correlation between the changes of HF power n.u. and negative body image (r(28) = .38, p = .047).

Discussion

The present study investigated the influence of the socio-cultural environment on the psychological and physiological processing of social interactions. Participants with and without obesity were tested in Germany (high exposure to weight-related prejudice and more negative perception of excess body weight) and the Samoan Islands (less exposure to weight-related prejudice and less negative perception of excess body weight). We found complex influences of weight status, location, and sex, and their interactions on psychometrics as well as on affect and parasympathetic cardioregulation during social interactions. Each finding will be discussed below.

Weight-related teasing and body image

In line with the literature, we expected to find no significant difference in body size preference between the two locations (Brewis et al. 1998; Swami et al. 2007; Wilkinson et al. 1994). Indeed, the body size preference did not vary between the populations which has been explained with reference to increasing Westernization and Western media exposure (Brewis et al. 1998; Swami et al. 2007). We further expected to find differences in weight-related teasing experiences and body dissatisfaction between the two cultures due to differences in body size-related socio-cultural norms. While our results did not show significant cultural differences in the frequency of weight-related teasing, we found that emotional pain after teasing differed between cultures: Samoan women with obesity reported to be less affected by teasing than German women with obesity. Also, obesity-related differences in emotional pain after teasing were found in Germans but not in Samoans. Importantly, Germans with obesity held a significantly more negative body image than Samoans with obesity. These results partially confirmed our hypothesis: although BMI was higher in the Samoan sample, negative body image and emotional pain after weight-related teasing were lower than in the German sample. This is in line with previous comparative research on body image (Brewis and McGarvey 2000; Metcalf et al. 2000; Wilkinson et al. 1994).

Social stress

In this sample, Samoans reported more social stress than Germans. Rapid socio-cultural and economical transitions have been related to psychosocial stress in Samoans (Bergey et al. 2011; McDade 2002), but also to increased incidences of suicide since the 1970s (Booth 1999). It has been hypothesized that the gap between expectations—caused by westernization, new consumer goods, and media—and traditional norms and values might favor suicide rates (Macpherson and Macpherson 1987). Other scholars discussed additional causes, such as repeated familial conflicts and the simultaneous refusal of expressing anger due to traditional community values and fear of a potential bad reputation for the family (Tousignant 1998). Hence, higher self-reported social stress in Samoans might be associated with the discrepancy between traditionally strict social obligations and progressive Westernization.

Affective responses during social interactions

We hypothesized to find differences in emotional responses to experimentally induced social interactions between the two locations. We measured mood, happiness, and the feeling of being accepted prior, between, and after the two sessions. In this study, participants generally felt worse, less accepted, and were less happy after social exclusion as compared to baseline. These findings indicate that we—like previous studies (cf. Blackhart et al. 2009; Gerber and Wheeler 2009)—successfully induced the experience of social exclusion. The average level of mood, happiness, and the feeling of being accepted was higher in Samoan than in German participants, which is in line with the claim that socio-emotional experience is shaped by the cultural environment (Barrett 2012; Immordino-Yang and Yang 2017; Mesquita et al. 2016). The public display of strong negative emotions is discouraged in Samoa and the maintenance of interpersonal harmony is a strongly approved value (Gerber 1985; Shore 1982). The expressed emotions via visual analogue scales in this sample might thus be influenced by cultural norms.

We also hypothesized fewer obesity-related differences in affect after social exclusion in Samoan than in German participants. We found that Samoan women with obesity and Samoan lean men generally felt more accepted than German women with obesity and German lean men, respectively. Since Polynesian as compared to Western societies have been reported to be less preoccupied with their body sizes (Brewis and McGarvey 2000; Metcalf et al. 2000; Teevale 2011; Wilkinson et al. 1994) and have fewer negative attitudes towards excess body weight (Becker 1995; Brewis et al. 1998; Hardin 2015; Pollock 2001), Samoans might not expect weight-related prejudice in a new social situation. Alternatively, due to a more ambiguous interpretation of body weight (Hardin 2015), Samoan participants might be less likely to attribute social exclusion to body weight. Further, social exclusion has been found to be less painful in collectivistic societies due to more reliable social networks (Over and Uskul 2016; Pfundmair et al. 2015). As a collectivistic society, Samoans might be less affected by social exclusion independent of weight status. In Western societies, it has been shown that especially women with overweight attribute ambiguous negative social feedback to their weight and are more negatively affected by it than lean women (Crocker et al. 1993). These results suggest that cultural norms regarding slimness might influence negative emotions during social interactions in individuals with overweight or obesity particularly in Westerners.

Cardiac activity during social interactions: location effects

The hypothesized differences in PNS activity during social inclusion and exclusion between the two locations could be confirmed: German participants exhibited a significant increase in PNS activity when engaged in an inclusive social situation relative to a resting baseline. This effect was absent in Samoan participants (with a significant time * location interaction). According to the models of PNS cardioregulation, a heightened engagement with the environment would be accompanied by increased PNS activity to improve an individual’s capacity to make effective and rapid responses (Porges 2003, 2007; Thayer and Lane 2000, 2009). Heightened PNS activity has also been associated with attention to motivationally relevant social stimuli (Jönsson and Sonnby-Borgström 2003; Stellar et al. 2015; Vanderhasselt et al. 2015) and effortful emotion regulation (Butler et al. 2006; Musser et al. 2011). Accordingly, the increase in PNS activity in German participants might be interpreted as stronger emotion regulation during social inclusion compared to Samoan participants. Due to the preliminary nature of the experimental results, we would like to cautiously discuss this finding in two potential directions. First, as mentioned above, in the traditional Samoan society the expression of emotion was described to be under external control and focus on their implication for social cohesion: negative emotional display, especially anger, was discouraged and obedience to those in authority was emphasized (Gerber 1985; Shore 1982). Developmental research in Western societies found associations of emotion regulation abilities with parental encouragement of and control over emotional display (Morris et al. 2007). Further, individuals with emotion regulation difficulties showed reduced PNS activation while watching anger-eliciting movies (Berna et al. 2014). Second, the effort, for example for emotion suppression, might differ between individualistic and collectivistic societies. That is, to maintain relationship harmony, individuals in collectivistic societies more frequently and habitually use the suppression of discouraged emotions—even during positive social interactions (Butler et al. 2007). In contrast, in individualistic societies, emotion regulation might be more frequently used in negative social situations to protect the self (Butler et al. 2007; Gross and John 2003). However, further studies are needed to investigate these potential interpretations in more detail.

During social exclusion, German participants showed increased PNS activity while Samoan participants showed a PNS withdrawal. Based on the aforementioned literature, results might indicate higher attentional engagement or stronger emotion regulation during social exclusion in German than in Samoan participants (Butler et al. 2006; Jönsson and Hansson-Sandsten 2008; Jönsson and Sonnby-Borgström 2003; Vanderhasselt et al. 2015). PNS withdrawal, in contrast, has been associated with disengagement from threat-related but not from happy or neutral cues (Schwerdtfeger and Derakshan 2010) as well as with emotional deficits (Beauchaine 2001; Berna et al. 2014). However, it has also been interpreted as response mobilization (Oppenheimer et al. 2013) and related to better recovery from stress (Rottenberg et al. 2007) or depression (Rottenberg et al. 2005). Although our study design does not allow a differentiation of disengagement or response mobilization potentially reflected in the PNS responses, we would like to propose the observed PNS withdrawal during social exclusion in Samoan participants as indicating a greater disengagement or a better ability to recover from potential threat (Rottenberg et al. 2007; Schwerdtfeger and Derakshan 2010). In the anthropological literature about the Samoan culture, the term musu is found in relation to emotion regulation in Samoans. Musu refers to an emotional state of withdrawal from stressful situations as a strategy to cope with interpersonal conflicts or criticism and, simultaneously, to avoid the display of socially undesirable emotions, like anger or impulse (Gerber 1985; Steele and McGarvey 1996). Musu might therefore be a socially learned behavior to disguise inappropriate feelings and might be reflected in the PNS response to social exclusion.

Cardiac activity during social interactions: weight effects

The hypothesized obesity-related differences during social inclusion in German but not in Samoan individuals could not be confirmed. Independent of location, we found an effect that corroborated our previous study results: the increase in PNS activity to social inclusion was more pronounced in women with obesity. This might be interpreted as an anticipatory regulation or increased vigilance. We argued that in the presence of a full-body picture, women with obesity—exhibiting the highest increase in PNS activity from baseline to social inclusion—might show higher attention to or emotion regulation in a novel and potentially stigmatizing social interaction (Schrimpf et al. 2017). Fittingly, it has been shown that individuals that played the Cyberball paradigm in an MRI and attributed social exclusion to (racial) discrimination showed more activity in brain regions linked with emotion and pain regulation during social exclusion (Masten et al. 2011). Further, women with higher BMI are more sensitive to their social inclusion or exclusion status than women with lower BMI (Hartung and Renner 2013) and that visibility of weight status might enhance this effect (Blodorn et al. 2016). It has been proposed that individuals with a higher need to belong show greater sensitivity to potential social threats (Pickett and Gardner 2005)—provoked in the present study via a full-body picture. Indeed, we observed a positive association between PNS activity during social inclusion and negative body image in Germans with obesity, but not in Samoans with obesity or lean individuals. Notably, the factor negative body image in this study included not only body dissatisfaction, but also a high frequency of weight-related teasing. The anticipation of being a target of weight-related prejudice might increase attention or emotion regulation during social interactions. Hence, the visibility of weight status in this study and the culturally stronger preoccupation with slimness in Western societies (Brewis and McGarvey 2000; Metcalf et al. 2000; Wilkinson et al. 1994) might have evoked a higher attention or emotion regulation during new social situations in German individuals with obesity and a more negative body image.

During social exclusion, a non-significant location * weight interaction suggested that PNS activity is more pronounced in German individuals with obesity than in German lean individuals, while this difference might be absent in the Samoan group. As we argued above, the results might indicate that German participants with obesity might be more attentionally engaged or regulate their emotional response more actively in a social exclusion interaction in which their weight status is visible. The Samoan group showed no obesity-related difference in PNS activity, which might suggest that body size is less salient during social interactions. Further studies could directly test this interpretation.

Additional findings

As in our previous study and as described in a meta-analysis on sex differences in autonomic cardiac control (Koenig and Thayer 2016), baseline HF-HRV indicated significantly greater dominance of PNS activity in females relative to males. Interestingly, groups in this study differed in WHR in that German men with obesity have a higher WHR than Samoan men with obesity—although Samoan men with obesity have a higher BMI than German men with obesity. It has been described that the percentage of muscle mass is higher and the percentage of body fat mass is lower in Polynesians as compared to Westerners with the same BMI (Rush et al. 2009), which is why we adjusted the BMI cut-offs for obesity accordingly. Since lower WHR is also an indicator for a healthier fat distribution (De Koning et al. 2007), it might be that WHR needs to be adjusted for ethnic differences in body composition as well—although the evidence for the need of WHR cut-offs in Polynesians is insufficient (Lear et al. 2010).

Limitations

We did not account for the influence of respiration on HF-HRV (Grossman and Taylor 2007; Penttilä et al. 2001). However, it has been argued that the influence can be neglected for tasks with comparable demands and under spontaneous breathing (Denver et al. 2007; Grossman and Taylor 2007). We did not expect changes in breathing frequencies between participants and tasks as participants were instructed to sit calmly without speaking during ECG measurements. Further, the amount of motor responses between inclusion and exclusion differed, which might influence HRV. However, small increases in motor activity have not been found to be related to changes in cardiac measures (Porges et al. 2007).

As the Cyberball paradigm is an experimental instrument designed to be highly standardized, the social interaction is restricted to tossing a ball and contains—besides the body pictures—little contextual information. The paradigm is therefore restricted in its transferability to real-life, complex social interactions. Hence, inferences from affective and psychophysiological results obtained with the Cyberball paradigm in the lab to real-life interactions must be carefully considered. Further, this paradigm has never been used in a Polynesian population and its applicability has not been sufficiently investigated. Additionally, the confederates’ pictures were the same as in Germany. Although American Samoans are very familiar with Westerners, mainly with US citizens working in American Samoa, the depiction of Western-looking confederates might generate an out-group setting and may have influenced the results. However, previous studies found similar effects of social exclusion with out-group and in-group confederates (Gonsalkorale and Williams 2007; Hartgerink et al. 2015). In addition, the instruction of the procedure slightly varied between the two locations, which might be a confounding factor: Participants were told they would play with two other individuals either sitting in nearby rooms (Germany) or connected online (Samoa). The Cyberball paradigm has been shown to induce negative emotions even when participants were told beforehand that the other players’ behavior was scripted (Zadro et al. 2004) or when comparing social exclusion by humans with computers (Filipkowski and Smyth 2012; Zadro et al. 2004). Social exclusion therefore might induce negative affect robustly in varying situations and experimental designs.

In addition, the order of social inclusion and exclusion was not balanced but fixed for all participants (first inclusion, second exclusion). In our between-subject analyses of weight- and location-related differences, potential order effects should have cancelled out. In addition, we were interested in psychophysiological effects of previous negative social experiences in novel, inclusive social interactions. Research showed that chronic stigmatization might enhance sensitivity to social cues even in neutral social situations (Barreto and Ellemers 2015; Kaiser et al. 2006; Swim et al. 1998; Tanaka and Ikegami 2015). Therefore, we kept the order of the sessions constant to preserve the psychological experience across participants: starting with an exclusion session might have provoked the expectation of being excluded in the second session as well.

As participants in both locations were young and had an above average education, they do not represent the entire population. Further, we recommend including the whole weight range including overweight participants in future studies. Importantly, due to the small sample size and the small statistical power of some results, they have to be considered preliminary and require further replication. Additionally, we recommend including factors as social status and reputation in future studies on weight-related stigmatization in Samoa or in other collectivistic societies, as it has been shown that these factors contribute considerably to the view on body weight and stigma (Hardin 2015).

Implications

HRV has rarely been studied in non-Western participants. Our study contributes an underrepresented cultural perspective to the two main theoretical frameworks of parasympathetic function (“polyvagal theory”, Porges 2003, 2007; “neurovisceral integration model”, Thayer and Lane 2000, 2009) and supports models about the influence of culture on socio-emotional phenomena (Barrett 2012; Immordino-Yang and Yang 2017). Further, the results indicate that socio-cultural norms regarding body size and—the potentially associated—stigmatizing experiences influence the processing of new social situations on a psychological and a physiological level. In Western societies, behavioral interventions for individuals with obesity that put a special focus on body image might be promising for an improvement in well-being and social functioning. On a more general note, our results support the importance of body size neutral media representations to reduce weight bias.

Conclusion

Our findings add to the understanding of (1) cultural influences on psychophysiological functioning, and (2) how social norms regarding body size accompanied by recurrent negative social experience might affect the processing of new social encounters. We confirm that Samoans’ excess body weight has a smaller impact on well-being and social relationships than Germans’ excess body weight. We previously found that Western women with obesity exhibit higher PNS activity during social interactions, which we interpreted as a higher vigilance to quickly detect signs of prejudice and apply adaptive psychophysiological strategies. We now add that Polynesians show fewer obesity-related psychophysiological differences during social interactions. These results emphasize the importance of perceptions of size, shape, or appearance of the human body for social interactions. By jointly investigating socio-cultural, psychological, and biological aspects of emotional processing, our “traveling experiment” contributes to better understanding socio-cultural aspects of HRV as well as the nature of emotion.

Notes

Acknowledgements

Open access funding provided by Max Planck Society. We thank all study participants for their cooperation. We also thank Rebecca Jost, Jenny Tippmann, Michael Vollmann, Carolin Wickner, and Mandy Ziermann for their help in recruiting participants and data collection in Germany. For assistance and support during the preparation of the study, we thank Bettina Johst, Ramona Menger, and Jonas Obleser. For hospitality, we thank the American Samoa Community College, Dan Aga, Mark Schmaedick, and especially Micah van der Ryn for discussion and advice. We also thank Nicola Hawley for helping with the ethics committee in American Samoa and with the translation of the consent form. We thank an anonymous reviewer for thoughtful comments. This work was supported by the German Academic Exchange Service (DAAD: AS), the Max Planck International Research Network on Aging (MaxNetAging; AS), and the German Federal Ministry of Education and Research (FKZ: 01EO1001; JK, AV).

Compliance with ethical standards

Conflict of interest

The authors declare that there are no conflicts of interest.

Supplementary material

40167_2018_71_MOESM1_ESM.docx (27 kb)
Supplementary material 1 (DOCX 27 kb)

References

  1. Agelink, M. W., Malessa, R., Baumann, B., Majewski, T., Akila, F., Zeit, T., et al. (2001). Standardized tests of heart rate variability: Normal ranges obtained from 309 healthy humans, and effects of age, gender, and heart rate. Clinical Autonomic Research, 11(2), 99–108.  https://doi.org/10.1007/BF02322053.PubMedCrossRefGoogle Scholar
  2. Alleva, J. M., Lange, W.-G., Jansen, A., & Martijn, C. (2014). Seeing ghosts: Negative body evaluation predicts overestimation of negative social feedback. Body Image, 11(3), 228–232.  https://doi.org/10.1016/j.bodyim.2014.03.001.PubMedCrossRefGoogle Scholar
  3. Anderson-Fye, E. P. (2012). Anthropological perspectives on physical appearance and body image. In T. F. Cash (Ed.), Encyclopedia of body image and human appearance (Vol. 1, pp. 15–22). San Diego: Academic Press.CrossRefGoogle Scholar
  4. Barreto, M., & Ellemers, N. (2015). Chapter three—Detecting and experiencing prejudice: New answers to old questions. Advances in Experimental Social Psychology, 52, 139–219.  https://doi.org/10.1016/bs.aesp.2015.02.001.CrossRefGoogle Scholar
  5. Barrett, L. F. (2012). Emotions are real. Emotion, 12(3), 413–429.  https://doi.org/10.1037/a0027555.PubMedCrossRefGoogle Scholar
  6. Baumeister, R. F., & Leary, M. R. (1995). The need to belong: Desire for interpersonal attachments as a fundamental human motivation. Psychological Bulletin, 117(3), 497–529.  https://doi.org/10.1037/0033-2909.117.3.497.PubMedCrossRefGoogle Scholar
  7. Beauchaine, T. (2001). Vagal tone, development, and Gray’s motivational theory: Toward an integrated model of autonomic nervous system functioning in psychopathology. Development and Psychopathology, 13(2), 183–214.  https://doi.org/10.1017/S0954579401002012.PubMedCrossRefGoogle Scholar
  8. Becker, A. E. (1995). Body, self, and society: The view from Fiji. Incorporated: University of Pennsylvania Press.Google Scholar
  9. Becker, A. E. (2004). Television, disordered eating, and young women in Fiji: Negotiating body image and identity during rapid social change. Culture, Medicine and Psychiatry, 28(4), 533–559.  https://doi.org/10.1007/s11013-004-1067-5.PubMedCrossRefGoogle Scholar
  10. Bergey, M. R., Steele, M. S., Bereiter, D. A., Viali, S., & McGarvey, S. T. (2011). Behavioral and perceived stressor effects on urinary catecholamine excretion in adult samoans. American Journal of Human Biology, 23(5), 693–702.  https://doi.org/10.1002/ajhb.21198.PubMedPubMedCentralCrossRefGoogle Scholar
  11. Berna, G., Ott, L., & Nandrino, J. L. (2014). Effects of emotion regulation difficulties on the tonic and phasic cardiac autonomic response. PLoS ONE, 9(7), e102971.  https://doi.org/10.1371/journal.pone.0102971.PubMedPubMedCentralCrossRefGoogle Scholar
  12. Billman, G. (2013). The LF/HF ratio does not accurately measure cardiac sympatho-vagal balance. Frontiers in Physiology, 4, 26.  https://doi.org/10.3389/fphys.2013.00026.PubMedPubMedCentralCrossRefGoogle Scholar
  13. Blackhart, G. C., Nelson, B. C., Knowles, M. L., & Baumeister, R. F. (2009). Rejection elicits emotional reactions but neither causes immediate distress nor lowers self-esteem: A meta-analytic review of 192 studies on social exclusion. Personality and Social Psychology Review, 13(4), 269–309.  https://doi.org/10.1177/1088868309346065.PubMedCrossRefGoogle Scholar
  14. Blodorn, A., Major, B., Hunger, J., & Miller, C. (2016). Unpacking the psychological weight of weight stigma: A rejection-expectation pathway. Journal of Experimental Social Psychology, 63, 69–76.  https://doi.org/10.1016/j.jesp.2015.12.003.PubMedPubMedCentralCrossRefGoogle Scholar
  15. Bond, R., & Smith, P. B. (1996). Culture and conformity: A meta-analysis of studies using Asch’s (1952b, 1956) line judgment task. Psychological Bulletin, 119, 111–137.  https://doi.org/10.1037/0033-2909.119.1.111.CrossRefGoogle Scholar
  16. Booth, H. (1999). Pacific Island suicide in comparative perspective. Journal of Biosocial Science, 31(4), 433–448.  https://doi.org/10.1017/s0021932099004332.PubMedCrossRefGoogle Scholar
  17. Borkenau, P., & Ostendorf, F. (1993). NEO-FFI: NEO-Fünf-Faktoren Inventar nach Costa und McCrae. Göttingen: Hogrefe.Google Scholar
  18. Brewis, A. A., & McGarvey, S. T. (2000). Body image, body size, and Samoan ecological and individual modernization. Ecology of Food and Nutrition, 39(2), 105–120.  https://doi.org/10.1080/03670244.2000.9991609.CrossRefGoogle Scholar
  19. Brewis, A. A., McGarvey, S. T., Jones, J., & Swinburn, B. A. (1998). Perceptions of body size in Pacific Islanders. International Journal of Obesity, 22(2), 185–189.  https://doi.org/10.1038/sj.ijo.0800562.PubMedCrossRefGoogle Scholar
  20. Brewis, A. A., & Wutich, A. (2014). A world of suffering? Biocultural approaches to fat stigma in the global contexts of the obesity epidemic. Annals of Anthropological Practice, 38(2), 269–283.  https://doi.org/10.1111/napa.12056.CrossRefGoogle Scholar
  21. Brewis, A. A., Wutich, A., Falletta-Cowden, A., & Rodriguez-Soto, I. (2011). Body norms and fat stigma in global perspective. Current Anthropology, 52(2), 269–276.  https://doi.org/10.1086/659309.CrossRefGoogle Scholar
  22. Brown, P. J., & Konner, M. (1987). An anthropological perspective on obesity. Annals of the New York Academy of Sciences, 499, 29–46.  https://doi.org/10.1111/j.1749-6632.1987.tb36195.x.PubMedCrossRefGoogle Scholar
  23. Burr, R. L. (2007). Interpretation of normalized spectral heart rate variability indices in sleep research: A critical review. Sleep, 30(7), 913–919.PubMedPubMedCentralCrossRefGoogle Scholar
  24. Butler, E. A., Lee, T. L., & Gross, J. J. (2007). Emotion regulation and culture: Are the social consequences of emotion suppression culture-specific? Emotion, 7(1), 30.  https://doi.org/10.1037/1528-3542.7.1.30.PubMedCrossRefGoogle Scholar
  25. Butler, E. A., Wilhelm, F. H., & Gross, J. J. (2006). Respiratory sinus arrhythmia, emotion, and emotion regulation during social interaction. Psychophysiology, 43(6), 612–622.  https://doi.org/10.1111/j.1469-8986.2006.00467.x.PubMedCrossRefGoogle Scholar
  26. Charles, S. T., & Piazza, J. R. (2007). Memories of social interactions: Age differences in emotional intensity. Psychology and Aging, 22(2), 300–309.  https://doi.org/10.1037/0882-7974.22.2.300.PubMedCrossRefGoogle Scholar
  27. Cohen, S., Kamarck, T., & Mermelstein, R. (1983). A global measure of perceived stress. Journal of Health and Social Behavior, 24(4), 385–396.  https://doi.org/10.2307/2136404.PubMedCrossRefGoogle Scholar
  28. Cooper, P. J., Taylor, M. J., Cooper, Z., & Fairbum, C. G. (1987). The development and validation of the body shape questionnaire. International Journal of Eating Disorders, 6(4), 485–494.  https://doi.org/10.1002/1098-108X(198707)6:4<485:AID-EAT2260060405>3.0.CO;2-O.CrossRefGoogle Scholar
  29. Costa, P. T., & McCrae, R. R. (1992). Professional manual: revised NEO personality inventory (NEO-PI-R) and NEO five-factor inventory (NEO-FFI) (Vol. 3, p. 101). Odessa, FL: Psychological Assessment Resources.  https://doi.org/10.1037//1040-3590.4.1.5.CrossRefGoogle Scholar
  30. Craig, P., Halavatau, V., Comino, E., & Caterson, I. (1999). Perception of body size in the Tongan community: Differences from and similarities to an Australian sample. International Journal of Obesity, 23, 1288–1294.  https://doi.org/10.1038/sj.ijo.0801069.PubMedCrossRefGoogle Scholar
  31. Crivelli, C., Russell, J. A., Jarillo, S., & Fernández-Dols, J.-M. (2016). The fear gasping face as a threat display in a Melanesian society. Proceedings of the National Academy of Sciences, 113(44), 12403–12407.  https://doi.org/10.1073/pnas.1611622113.CrossRefGoogle Scholar
  32. Crocker, J., Cornwell, B., & Major, B. (1993). The stigma of overweight: Affective consequences of attributional ambiguity. Journal of Personality and Social Psychology, 64(1), 60–70.  https://doi.org/10.1037/0022-3514.64.1.60.PubMedCrossRefGoogle Scholar
  33. De Koning, L., Merchant, A. T., Pogue, J., & Anand, S. S. (2007). Waist circumference and waist-to-hip ratio as predictors of cardiovascular events: Meta-regression analysis of prospective studies. European Heart Journal, 28(7), 850–856.  https://doi.org/10.1093/eurheartj/ehm026.PubMedCrossRefGoogle Scholar
  34. Denver, J. W., Reed, S. F., & Porges, S. W. (2007). Methodological issues in the quantification of respiratory sinus arrhythmia. Biological Psychology, 74(2), 286–294.  https://doi.org/10.1016/j.biopsycho.2005.09.005.PubMedCrossRefGoogle Scholar
  35. Downey, G., & Feldman, S. I. (1996). Implications of rejection sensitivity for intimate relationships. Journal of Personality and Social Psychology.  https://doi.org/10.1037/0022-3514.70.6.1327.PubMedCrossRefGoogle Scholar
  36. Filipkowski, K. B., & Smyth, J. M. (2012). Plugged in but not connected: Individuals’ views of and responses to online and in-person ostracism. Computers in Human Behavior, 28(4), 1241–1253.  https://doi.org/10.1016/j.chb.2012.02.007.CrossRefGoogle Scholar
  37. Fliege, H., Rose, M., Arck, P., Levenstein, S., & Klapp, B. F. (2001). Validierung des “perceived stress questionnaire“(PSQ) an einer deutschen Stichprobe. Diagnostica, 47(3), 142–152.  https://doi.org/10.1026//0012-1924.47.3.142.CrossRefGoogle Scholar
  38. Furnham, A., Moutafi, J., & Baguma, P. (2002). A cross-cultural study on the role of weight and waist-to-hip ratio on female attractiveness. Personality and Individual Differences, 32(4), 729–745.  https://doi.org/10.1016/S0191-8869(01)00073-3.CrossRefGoogle Scholar
  39. Garner, D. M. (1991). Eating disorder inventory-2. Odessa: Psychological assessment resources.Google Scholar
  40. Gerber, E. R. (1985). Rage and obligation: Samoan emotions in conflict. In G. M. White & J. Kirkpatrick (Eds.), Person, self and experience: Exploring Pacific ethnopsychologies (pp. 121–167). Berkeley: University of California Press.Google Scholar
  41. Gerber, J., & Wheeler, L. (2009). On being rejected: A meta-analysis of experimental research on rejection. Perspectives on Psychological Science, 4(5), 468–488.  https://doi.org/10.1111/j.1745-6924.2009.01158.x.PubMedCrossRefGoogle Scholar
  42. Gonsalkorale, K., & Williams, K. D. (2007). The KKK won’t let me play: Ostracism even by a despised outgroup hurts. European Journal of Social Psychology, 37(6), 1176–1186.  https://doi.org/10.1002/ejsp.392.CrossRefGoogle Scholar
  43. Gross, J. J., & John, O. P. (2003). Individual differences in two emotion regulation processes: Implications for affect, relationships, and well-being. Journal of Personality and Social Psychology, 85(2), 348.  https://doi.org/10.1037/0022-3514.85.2.348.PubMedCrossRefGoogle Scholar
  44. Grossman, P., & Taylor, E. W. (2007). Toward understanding respiratory sinus arrhythmia: Relations to cardiac vagal tone, evolution and biobehavioral functions. Biological Psychology, 74(2), 263–285.  https://doi.org/10.1016/j.biopsycho.2005.11.014.PubMedCrossRefGoogle Scholar
  45. Gunther Moor, B., Bos, M. G. N., Crone, E. A., & van der Molen, M. W. (2014). Peer rejection cues induce cardiac slowing after transition into adolescence. Developmental Psychology, 50(3), 947–955.  https://doi.org/10.1037/a0033842.PubMedCrossRefGoogle Scholar
  46. Gunther Moor, B., Crone, E. A., & van der Molen, M. W. (2010). The heartbrake of social rejection: Heart rate deceleration in response to unexpected peer rejection. Psychological Science, 21(9), 1326–1333.  https://doi.org/10.1177/0956797610379236.PubMedCrossRefGoogle Scholar
  47. Gupta, M. A., Chaturvedi, S. K., Chandarana, P. C., & Johnson, A. M. (2001). Weight-related body image concerns among 18–24-year-old women in Canada and India: An empirical comparative study. Journal of Psychosomatic Research, 50(4), 193–198.  https://doi.org/10.1016/S0022-3999(00)00221-X.PubMedCrossRefGoogle Scholar
  48. Hardin, J. (2015). Christianity, fat talk, and Samoan pastors: Rethinking the fat-positive-fat-stigma framework. Fat Studies, 4(2), 178–196.  https://doi.org/10.1080/21604851.2015.1015924.CrossRefGoogle Scholar
  49. Hartgerink, C. H., Van Beest, I., Wicherts, J. M., & Williams, K. D. (2015). The ordinal effects of ostracism: A meta-analysis of 120 Cyberball studies. PLoS ONE, 10(5), e0127002.  https://doi.org/10.1371/journal.pone.0127002.PubMedPubMedCentralCrossRefGoogle Scholar
  50. Hartung, F.-M., & Renner, B. (2013). Perceived and actual social discrimination: The case of overweight and social inclusion. Frontiers in Psychology, 4, 147.  https://doi.org/10.3389/fpsyg.2013.00147.PubMedPubMedCentralCrossRefGoogle Scholar
  51. Hebl, M. R., King, E. B., & Perkins, A. (2009). Ethnic differences in the stigma of obesity: Identification and engagement with a thin ideal. Journal of Experimental Social Psychology, 45(6), 1165–1172.  https://doi.org/10.1016/j.jesp.2009.04.017.CrossRefGoogle Scholar
  52. Henrich, J., Heine, S. J., & Norenzayan, A. (2010). The weirdest people in the world? Behavioral and Brain Sciences, 33(2–3), 61–83.  https://doi.org/10.1017/s0140525x0999152x.PubMedCrossRefGoogle Scholar
  53. Holzman, J. B., & Bridgett, D. J. (2017). Heart rate variability indices as bio-markers of top-down self-regulatory mechanisms: A meta-analytic review. Neuroscience & Biobehavioral Reviews, 74(Part A), 233–255.  https://doi.org/10.1016/j.neubiorev.2016.12.032.CrossRefGoogle Scholar
  54. Iffland, B., Sansen, L. M., Catani, C., & Neuner, F. (2014). Rapid heartbeat, but dry palms: Reactions of heart rate and skin conductance levels to social rejection. Frontiers in Psychology, 5, 956.  https://doi.org/10.3389/fpsyg.2014.00956.PubMedPubMedCentralCrossRefGoogle Scholar
  55. Immordino-Yang, M. H., & Yang, X. F. (2017). Cultural differences in the neural correlates of social–emotional feelings: An interdisciplinary, developmental perspective. Current Opinion in Psychology, 17, 34–40.  https://doi.org/10.1016/j.copsyc.2017.06.008UR.PubMedCrossRefGoogle Scholar
  56. Immordino-Yang, M. H., Yang, X. F., & Damasio, H. (2016). Cultural modes of expressing emotions influence how emotions are experienced. Emotion, 16(7), 1033–1039.  https://doi.org/10.1037/emo0000201.PubMedPubMedCentralCrossRefGoogle Scholar
  57. Jönsson, P., & Hansson-Sandsten, M. (2008). Respiratory sinus arrhythmia in response to fear-relevant and fear-irrelevant stimuli. Scandinavian Journal of Psychology, 49(2), 123–131.  https://doi.org/10.1111/j.1467-9450.2008.00638.x.PubMedCrossRefGoogle Scholar
  58. Jönsson, P., & Sonnby-Borgström, M. (2003). The effects of pictures of emotional faces on tonic and phasic autonomic cardiac control in women and men. Biological Psychology, 62(2), 157–173.  https://doi.org/10.1016/S0301-0511(02)00114-X.PubMedCrossRefGoogle Scholar
  59. Kaiser, C. R., Vick, S. B., & Major, B. (2006). Prejudice expectations moderate preconscious attention to cues that are threatening to social identity. Psychological Science, 17(4), 332–338.  https://doi.org/10.1111/j.1467-9280.2006.01707.x.PubMedCrossRefGoogle Scholar
  60. Klein, E. M., Brähler, E., Dreier, M., Reinecke, L., Müller, K. W., Schmutzer, G., et al. (2016). The German version of the Perceived Stress Scale—psychometric characteristics in a representative German community sample. BMC Psychiatry, 16(159), 1–10.  https://doi.org/10.1186/s12888-016-0875-9.CrossRefGoogle Scholar
  61. Koenig, J., & Thayer, J. (2016). Sex differences in healthy human heart rate variability: A meta-analysis. Neuroscience and Biobehavioral Reviews, 64, 288–310.  https://doi.org/10.1016/j.neubiorev.2016.03.007.PubMedCrossRefGoogle Scholar
  62. Kronenfeld, L. W., Reba-Harrelson, L., Von Holle, A., Reyes, M. L., & Bulik, C. M. (2010). Ethnic and racial differences in body size perception and satisfaction. Body Image, 7(2), 131–136.  https://doi.org/10.1016/j.bodyim.2009.11.002.PubMedPubMedCentralCrossRefGoogle Scholar
  63. Kube, J., Schrimpf, A., Garcia-Garcia, I., Villringer, A., Neumann, J., & Horstmann, A. (2016). Differential heart rate responses to social and monetary reinforcement in women with obesity. Psychophysiology, 53, 868–879.  https://doi.org/10.1111/psyp.12624.PubMedCrossRefGoogle Scholar
  64. Labouvie-Vief, G., Lumley, M. A., Jain, E., & Heinze, H. (2003). Age and gender differences in cardiac reactivity and subjective emotion responses to emotional autobiographical memories. Emotion, 3(2), 115–126.  https://doi.org/10.1037/1528-3542.3.2.115.PubMedCrossRefGoogle Scholar
  65. Lear, S. A., James, P. T., Ko, G. T., & Kumanyika, S. (2010). Appropriateness of waist circumference and waist-to-hip ratio cutoffs for different ethnic groups. European Journal of Clinical Nutrition, 64, 42–61.  https://doi.org/10.1038/ejcn.2009.70.PubMedCrossRefGoogle Scholar
  66. Legenbauer, T., Vocks, S., & Schütt-Strömel, S. (2007). Validierung einer deutschsprachigen version des body image avoidance questionnaire BIAQ. Diagnostica, 53(4), 218–225.  https://doi.org/10.1026/0012-1924.53.4.218.CrossRefGoogle Scholar
  67. Levenstein, S., Prantera, C., Varvo, V., Scribano, M. L., Berto, E., Luzi, C., et al. (1993). Development of the perceived stress questionnaire: A new tool for psychosomatic research. Journal of Psychosomatic Research, 37(1), 19–32.  https://doi.org/10.1016/0022-3999(93)90120-5.PubMedCrossRefGoogle Scholar
  68. Lindquist, K. A., Siegel, E. H., Quigley, K. S., & Barrett, L. F. (2013). The hundred-year emotion war: Are emotions natural kinds or psychological constructions? Comment on Lench, Flores, and Bench (2011). Psychological Bulletin, 139(1), 255–263.  https://doi.org/10.1037/a0029038.PubMedPubMedCentralCrossRefGoogle Scholar
  69. Macpherson, C., & Macpherson, L. (1987). Towards an explanation of recent trends in suicide in Western Samoa. Man, 22(2), 305–330.  https://doi.org/10.2307/2802867.CrossRefGoogle Scholar
  70. Markus, H. R., & Kitayama, S. (1991). Culture and the self: Implications for cognition, emotion, and motivation. Psychological Review, 98(2), 224.  https://doi.org/10.1037/0033-295X.98.2.224.CrossRefGoogle Scholar
  71. Masten, C. L., Telzer, E. H., & Eisenberger, N. I. (2011). An fMRI investigation of attributing negative social treatment to racial discrimination. Journal of Cognitive Neuroscience, 23(5), 1042–1051.  https://doi.org/10.1162/jocn.2010.21520.PubMedCrossRefGoogle Scholar
  72. Mavoa, H. M., & McCabe, M. (2008). Sociocultural factors relating to Tongans’ and Indigenous Fijians’ patterns of eating, physical activity and body size. Asia Pacific Journal of Clinical Nutrition, 17(3), 375–383.  https://doi.org/10.6133/apjcn.2008.17.3.03.PubMedCrossRefGoogle Scholar
  73. McCullough, M. B. (2013). Fat and knocked up: An embodied analysis of stigma, visibility and invisibility in the biomedical management of an obese pregnancy. In M. B. McCullough & J. A. Hardin (Eds.), Reconstructing obesity: The meaning of measures and the measure of meanings (pp. 215–234). New York: Berghahn Books.Google Scholar
  74. McDade, T. W. (2002). Status incongruity in Samoan youth: A biocultural analysis of culture change, stress, and immune function. Medical Anthropology Quarterly, New Series, 16(2), 123–150.  https://doi.org/10.1525/maq.2002.16.2.123.CrossRefGoogle Scholar
  75. McGarvey, S. T. (2009). Interdisciplinary translational research in anthropology, nutrition, and public health. Annual Review of Anthropology, 38, 233–249.  https://doi.org/10.1146/annurev-anthro-091908-164327.CrossRefGoogle Scholar
  76. Mesquita, B., Boiger, M., & De Leersnyder, J. (2016). The cultural construction of emotions. Current Opinion in Psychology, 8, 31–36.  https://doi.org/10.1016/j.copsyc.2015.09.015.PubMedCrossRefGoogle Scholar
  77. Mesquita, B., & Frijda, N. H. (1992). Cultural variations in emotions: A review. Psychological Bulletin, 112(2), 179–204.  https://doi.org/10.1037/0033-2909.112.2.179.PubMedCrossRefGoogle Scholar
  78. Metcalf, P. A., Scragg, R. K., Willoughby, P., Finau, S., & Tipene-Leach, D. (2000). Ethnic differences in perceptions of body size in middle-aged European, Maori and Pacific people living in New Zealand. International Journal of Obesity, 24(5), 593–599.  https://doi.org/10.1038/sj.ijo.0801202.PubMedCrossRefGoogle Scholar
  79. Morris, A. S., Silk, J. S., Steinberg, L., Myers, S. S., & Robinson, L. R. (2007). The role of the family context in the development of emotion regulation. Social Development, 16(2), 361–388.  https://doi.org/10.1111/j.1467-9507.2007.00389.x.PubMedCrossRefGoogle Scholar
  80. Murray-Close, D. (2011). Autonomic reactivity and romantic relational aggression among female emerging adults: Moderating roles of social and cognitive risk. International Journal of Psychophysiology, 80(1), 28–35.  https://doi.org/10.1016/j.ijpsycho.2011.01.007.PubMedCrossRefGoogle Scholar
  81. Musser, E. D., Backs, R. W., Schmitt, C. F., Ablow, J. C., Measelle, J. R., & Nigg, J. T. (2011). Emotion regulation via the autonomic nervous system in children with attention-deficit/hyperactivity disorder (ADHD). Journal of Abnormal Child Psychology, 39(6), 841–852.  https://doi.org/10.1007/s10802-011-9499-1.PubMedPubMedCentralCrossRefGoogle Scholar
  82. Oppenheimer, J. E., Measelle, J. R., Laurent, H. K., & Ablow, J. C. (2013). Mothers’ vagal regulation during the still-face paradigm: Normative reactivity and impact of depression symptoms. Infant Behavior and Development, 36(2), 255–267.  https://doi.org/10.1016/j.infbeh.2013.01.003.PubMedCrossRefGoogle Scholar
  83. Over, H., & Uskul, A. K. (2016). Culture moderates children’s responses to ostracism situations. Journal of Personality and Social Psychology, 110(5), 710.  https://doi.org/10.1037/pspi0000050.PubMedCrossRefGoogle Scholar
  84. Oyserman, D., Coon, H. M., & Kemmelmeier, M. (2002). Rethinking individualism and collectivism: Evaluation of theoretical assumptions and meta-analyses. Psychological Bulletin, 128(1), 3.  https://doi.org/10.1037/0033-2909.128.1.3.PubMedCrossRefGoogle Scholar
  85. Papousek, I., Aydin, N., Lackner, H. K., Weiss, E. M., Bühner, M., Schulter, G., et al. (2014). Laughter as a social rejection cue: Gelotophobia and transient cardiac responses to other persons’ laughter and insult. Psychophysiology, 51(11), 1112–1121.  https://doi.org/10.1111/psyp.12259.PubMedCrossRefGoogle Scholar
  86. Penttilä, J., Helminen, A., Jartti, T., Kuusela, T., Huikuri, H. V., Tulppo, M. P., et al. (2001). Time domain, geometrical and frequency domain analysis of cardiac vagal outflow: Effects of various respiratory patterns. Clinical Physiology, 21(3), 365–376.  https://doi.org/10.1046/j.1365-2281.2001.00337.x.PubMedCrossRefGoogle Scholar
  87. Pepper, A. C., & Ruiz, S. Y. (2007). Acculturation’s influence on antifat attitudes, body image and eating behaviors. Eating Disorders, 15(5), 427–447.  https://doi.org/10.1080/10640260701667912.PubMedCrossRefGoogle Scholar
  88. Pfundmair, M., Aydin, N., Du, H., Yeung, S., Frey, D., & Graupmann, V. (2015). Exclude me if you can: Cultural effects on the outcomes of social exclusion. Journal of Cross-Cultural Psychology, 46(4), 579–596.  https://doi.org/10.1177/0022022115571203.CrossRefGoogle Scholar
  89. Pickett, C. L., & Gardner, W. L. (2005). The social monitoring system: Enhanced sensitivity to social cues as an adaptive response to social exclusion. In K. D. Williams, J. P. Forgas, & W. von Hippel (Eds.), The social outcast: Ostracism, social exclusion, rejection, and bullying (pp. 213–226). New York: Psychology Press.Google Scholar
  90. Pollock, N. J. (1995). Cultural elaborations of obesity—Fattening practices in Pacific societies. Asia Pacific Journal of Clinical Nutrition, 4(4), 357–360.PubMedGoogle Scholar
  91. Pollock, N. J. (2001). Obesity or large body size? A study in Wallis and Futuna. Pacific Health Dialog, 8(1), 119–123.PubMedGoogle Scholar
  92. Pook, M., Tuschen-Caffier, B., & Stich, N. (2002). Evaluation des Fragebogens zum Figurbewusstsein (FFB, deutsche version des body shape questionnaire). Verhaltenstherapie, 12(2), 116–124.  https://doi.org/10.1159/000064375.CrossRefGoogle Scholar
  93. Porges, S. W. (2003). The polyvagal theory: Phylogenetic contributions to social behavior. Physiology & Behavior, 79(3), 503–513.  https://doi.org/10.1016/S0031-9384(03)00156-2.CrossRefGoogle Scholar
  94. Porges, S. W. (2007). The polyvagal perspective. Biological Psychology, 74(2), 116–143.  https://doi.org/10.1016/j.biopsycho.2006.06.009.PubMedCrossRefGoogle Scholar
  95. Porges, S. W., Heilman, K. J., Bazhenova, O. V., Bal, E., Doussard-Roosevelt, J. A., & Koledin, M. (2007). Does motor activity during psychophysiological paradigms confound the quantification and interpretation of heart rate and heart rate variability measures in young children? Developmental Psychobiology, 49(5), 485–494.  https://doi.org/10.1002/dev.20228.PubMedCrossRefGoogle Scholar
  96. Puhl, R., & Brownell, K. D. (2001). Bias, discrimination, and obesity. Obesity Research, 9(12), 788–805.  https://doi.org/10.1038/oby.2001.108.PubMedCrossRefGoogle Scholar
  97. Puhl, R. M., Latner, J. D., O’Brien, K., Luedicke, J., Danielsdottir, S., & Forhan, M. (2015). A multinational examination of weight bias: Predictors of anti-fat attitudes across four countries. International Journal of Obesity, 39(7), 1166–1173.  https://doi.org/10.1038/ijo.2015.32.PubMedCrossRefGoogle Scholar
  98. Puhl, R. M., Moss-Racusin, C. A., & Schwartz, M. B. (2007). Internalization of weight bias: Implications for binge eating and emotional well-being. Obesity, 15(1), 19–23.  https://doi.org/10.1038/oby.2007.521.PubMedCrossRefGoogle Scholar
  99. Puhl, R. M., Moss-Racusin, C. A., Schwartz, M. B., & Brownell, K. D. (2008). Weight stigmatization and bias reduction: Perspectives of overweight and obese adults. Health Education Research, 23(2), 347–358.  https://doi.org/10.1093/her/cym052.PubMedCrossRefGoogle Scholar
  100. Rosen, J. C., Srebnik, D., Saltzberg, E., & Wendt, S. (1991). Development of a body image avoidance questionnaire. Psychological Assessment: A Journal of Consulting and Clinical Psychology, 3(1), 32–37.  https://doi.org/10.1037/1040-3590.3.1.32.CrossRefGoogle Scholar
  101. Rottenberg, J., Clift, A., Bolden, S., & Salomon, K. (2007). RSA fluctuation in major depressive disorder. Psychophysiology, 44(3), 450–458.  https://doi.org/10.1111/j.1469-8986.2007.00509.x.PubMedCrossRefGoogle Scholar
  102. Rottenberg, J., Salomon, K., Gross, J. J., & Gotlib, I. H. (2005). Vagal withdrawal to a sad film predicts subsequent recovery from depression. Psychophysiology, 42(3), 277–281.  https://doi.org/10.1111/j.1469-8986.2005.00289.x.PubMedCrossRefGoogle Scholar
  103. Rush, E. C., Freitas, I., & Plank, L. D. (2009). Body size, body composition and fat distribution: Comparative analysis of European, Maori, Pacific Island and Asian Indian adults. British Journal of Nutrition, 102(04), 632–641.  https://doi.org/10.1017/S0007114508207221.PubMedCrossRefGoogle Scholar
  104. Saxbe, D. E., Yang, X. F., Borofsky, L. A., & Immordino-Yang, M. H. (2012). The embodiment of emotion: Language use during the feeling of social emotions predicts cortical somatosensory activity. Social Cognitive and Affective Neuroscience, 8(7), 806–812.  https://doi.org/10.1093/scan/nss075.PubMedPubMedCentralCrossRefGoogle Scholar
  105. Scherer, K. R., & Wallbott, H. G. (1994). Evidence for universality and cultural variation of differential emotion response patterning. Journal of Personality and Social Psychology, 66(2), 310–328.  https://doi.org/10.1037/0022-3514.67.1.55.PubMedCrossRefGoogle Scholar
  106. Schrimpf, A., Kube, J., Neumann, J., Horstmann, A., Villringer, A., & Gaebler, M. (2017). Parasympathetic cardio-regulation during social interactions in individuals with obesity—The influence of negative body image. Cognitive, Affective, & Behavioral Neuroscience, 17, 330–347.  https://doi.org/10.3758/s13415-016-0482-8.CrossRefGoogle Scholar
  107. Schulz, P., & Schlotz, W. (1999). Trierer Inventar zur Erfassung von chronischem Stress (TICS): Skalenkonstruktion, teststatistische Überprüfung und Validierung der Skala Arbeitsüberlastung. Diagnostica, 45(1), 8–19.  https://doi.org/10.1026//0012-1924.45.1.8.CrossRefGoogle Scholar
  108. Schwerdtfeger, A., & Derakshan, N. (2010). The time line of threat processing and vagal withdrawal in response to a self-threatening stressor in cognitive avoidant copers: Evidence for vigilance-avoidance theory. Psychophysiology, 47(4), 786–795.  https://doi.org/10.1111/j.1469-8986.2010.00965.x.PubMedCrossRefGoogle Scholar
  109. Shahrestani, S., Stewart, E. M., Quintana, D. S., Hickie, I. B., & Guastella, A. J. (2015). Heart rate variability during adolescent and adult social interactions: A meta-analysis. Biological Psychology, 105, 43–50.  https://doi.org/10.1016/j.biopsycho.2014.12.012.PubMedCrossRefGoogle Scholar
  110. Shore, B. (1982). Sala’ilua: A Samoan mystery. New York: Columbia University Press.Google Scholar
  111. Staebler, K., Helbing, E., Rosenbach, C., & Renneberg, B. (2011). Rejection sensitivity and borderline personality disorder. Clinical Psychology & Psychotherapy, 18(4), 275–283.  https://doi.org/10.1002/cpp.705.CrossRefGoogle Scholar
  112. Steele, M. S., & McGarvey, S. T. (1996). Expression of anger by Samoan adults. Psychological Reports, 79(3 Pt 2), 1339–1348.  https://doi.org/10.2466/pr0.1996.79.3f.1339.PubMedCrossRefGoogle Scholar
  113. Stellar, J. E., Cohen, A., Oveis, C., & Keltner, D. (2015). Affective and physiological responses to the suffering of others: Compassion and vagal activity. Journal of Personality and Social Psychology, 108(4), 572–585.  https://doi.org/10.1037/pspi0000010.PubMedCrossRefGoogle Scholar
  114. Stunkard, A. J., Sorensen, T., & Schulsinger, F. (1983). Use of the Danish adoption register for the study of obesity and thinness. In S. S. Kety, L. P. Rowland, R. L. Sidman, & S. W. Matthysse (Eds.), The genetics of neurological and psychiatric disorders (pp. 115–120). New York: Raven Press.Google Scholar
  115. Swami, V., Frederick, D. A., Aavik, T., Alcalay, L., Allik, J., Anderson, D., et al. (2010). The attractive female body weight and female body dissatisfaction in 26 countries across 10 world regions: Results of the international body project I. Personality and Social Psychology Bulletin, 36(3), 309–325.  https://doi.org/10.1177/0146167209359702.PubMedCrossRefGoogle Scholar
  116. Swami, V., Knight, D., Tovée, M. J., Davies, P., & Furnham, A. (2007). Preferences for female body size in Britain and the South Pacific. Body Image, 4(2), 219–223.  https://doi.org/10.1016/j.bodyim.2007.01.002.PubMedCrossRefGoogle Scholar
  117. Swami, V., Tovée, M., & Harris, A. S. (2013). An examination of ethnic differences in actual-ideal weight discrepancy and its correlates in a sample of Malaysian women. International Journal of Culture and Mental Health, 6(2), 96–107.  https://doi.org/10.1080/17542863.2011.643315.CrossRefGoogle Scholar
  118. Swim, J. K., Cohen, L. L., & Hyers, L. L. (1998). Experiencing everyday prejudice and discrimination. In J. K. S. C. Stangor (Ed.), Prejudice: The target’s perspective (pp. 37–60). San Diego: Academic Press.CrossRefGoogle Scholar
  119. Tanaka, H., & Ikegami, T. (2015). Fear of negative evaluation moderates effects of social exclusion on selective attention to social signs. Cognition and Emotion, 29(7), 1306–1313.  https://doi.org/10.1080/02699931.2014.977848.PubMedCrossRefGoogle Scholar
  120. Teevale, T. (2011). Body image and its relation to obesity for Pacific minority ethnic groups in New Zealand: a critical analysis. Pacific Health Dialog, 17(1), 33–53.PubMedGoogle Scholar
  121. Thayer, J. F., & Lane, R. D. (2000). A model of neurovisceral integration in emotion regulation and dysregulation. Journal of Affective Disorders, 61(3), 201–216.  https://doi.org/10.1016/S0165-0327(00)00338-4.PubMedCrossRefGoogle Scholar
  122. Thayer, J. F., & Lane, R. D. (2009). Claude Bernard and the heart–brain connection: Further elaboration of a model of neurovisceral integration. Neuroscience and Biobehavioral Reviews, 33(2), 81–88.  https://doi.org/10.1016/j.neubiorev.2008.08.004.PubMedCrossRefGoogle Scholar
  123. Thiel, A., Jacobi, C., Horstmann, S., Paul, T., Nutzinger, D. O., & Schüssler, G. (1997). A German version of the eating disorder inventory EDI-2. Psychotherapie, Psychosomatik, Medizinische Psychologie, 47(9–10), 365–376.PubMedGoogle Scholar
  124. Thompson, J. K., Fabian, L. J., Moulton, D. O., Dunn, M. E., & Altabe, M. N. (1991). Development and validation of the physical appearance related teasing scale. Journal of Personality Assessment, 56(3), 513–521.  https://doi.org/10.1207/s15327752jpa5603_12.PubMedCrossRefGoogle Scholar
  125. Tousignant, M. (1998). Suicide in small-scale societies. Transcultural Psychiatry, 35(2), 291–306.  https://doi.org/10.1177/136346159803500207.CrossRefGoogle Scholar
  126. Treloar, C., Porteous, J., Hassan, F., Kasniyah, N., Lakshmanudu, M., Sama, M., et al. (1999). The cross cultural context of obesity: An INCLEN multicentre collaborative study. Health & Place, 5(4), 279–286.  https://doi.org/10.1016/S1353-8292(99)00018-0.CrossRefGoogle Scholar
  127. Triandis, H. C. (1989). The self and social behavior in differing cultural contexts. Psychological Review, 96, 506.  https://doi.org/10.1037/0033-295X.96.3.506.CrossRefGoogle Scholar
  128. Vanderhasselt, M.-A., Remue, J., Ng, K., Mueller, S., & De Raedt, R. (2015). The regulation of positive and negative social feedback: A psychophysiological study. Cognitive, Affective, & Behavioral Neuroscience, 15(3), 553–563.  https://doi.org/10.3758/s13415-015-0345-8.CrossRefGoogle Scholar
  129. Waskul, D. D., & van der Riet, P. (2002). The abject embodiment of cancer patients: Dignity, selfhood, and the grotesque body. Symbolic Interaction, 25(4), 487–513.  https://doi.org/10.1525/si.2002.25.4.487.CrossRefGoogle Scholar
  130. Wilkinson, J. Y., Ben-Tovim, D. I., & Walker, M. K. (1994). An insight into the personal and cultural significance of weight and shape in large Samoan women. International Journal of Obesity, 18, 602–606.PubMedGoogle Scholar
  131. Williams, K. D., Cheung, C. K. T., & Choi, W. (2000). Cyberostracism: Effects of being ignored over the Internet. Journal of Personality and Social Psychology, 79(5), 748.  https://doi.org/10.1037/0022-3514.79.5.748.PubMedCrossRefGoogle Scholar
  132. Zadro, L., Williams, K. D., & Richardson, R. (2004). How low can you go? Ostracism by a computer is sufficient to lower self-reported levels of belonging, control, self-esteem, and meaningful existence. Journal of Experimental Social Psychology, 40(4), 560–567.  https://doi.org/10.1016/j.jesp.2003.11.006.CrossRefGoogle Scholar

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© The Author(s) 2018

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
  2. 2.International Health Institute, Department of EpidemiologyBrown University School of Public HealthProvidenceUSA
  3. 3.Leipzig Research Center Early Child Development (LFE)Leipzig UniversityLeipzigGermany
  4. 4.Leipzig University Medical CenterIFB Adiposity DiseasesLeipzigGermany
  5. 5.Faculty 5 – Business, Law and Social SciencesBrandenburg University of Technology Cottbus–SenftenbergCottbusGermany
  6. 6.Clinic of Cognitive NeurologyUniversity Hospital LeipzigLeipzigGermany
  7. 7.MindBrainBody Institute at the Berlin, School of Mind and BrainHumboldt-Universität zu BerlinBerlinGermany
  8. 8.Leipzig Research Center for Civilization Diseases (LIFE)Leipzig UniversityLeipzigGermany

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