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Psychosomatic Medicine 67:16-23 (2005)
© 2005 American Psychosomatic Society

ORIGINAL ARTICLES

Genetic and Environmental Influences on Anger Expression, John Henryism, and Stressful Life Events: The Georgia Cardiovascular Twin Study

Xiaoling Wang, PhD, Ranak Trivedi, MS, Frank Treiber, PhD and Harold Snieder, PhD

From the Georgia Prevention Institute, Department of Pediatrics, Medical College of Georgia, Augusta, Georgia (X.W., R.T., F.T., H.S.); the Department of Psychiatry, Duke University Medical Center, Durham, North Carolina (R.T.); and the Twin Research & Genetic Epidemiology Unit, St. Thomas’ Hospital, London, U.K. (H.S.).

Address correspondence and reprint requests to Harold Snieder, PhD, Georgia Prevention Institute, Medical College of Georgia, Building HS-1640, Augusta, GA 30912. E-mail: hsnieder{at}mcg.edu


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 CONCLUSION
 NOTES
 REFERENCES
 
Objective: To examine the genetic and/or environmental origin of variation and covariation of perceived stressful life events and two stress-related coping styles, anger expression and John Henryism.

Methods: Data were available from 306 European American (EA) and 213 African American (AA) twin pairs, including monozygotic and dizygotic of same as well as opposite sex (mean age, 14.8 ± 3.1 years; range, 10.0–25.9 years). Anger expression, John Henryism, and life events were measured with the Anger Expression Scale (subscales: Anger-in, Anger-out, and Anger-control), the John Henryism Active Coping Scale, and the Adolescent Resources Challenges Scale, respectively.

Results: Model fitting showed no ethnic or sex differences for any of the scales. All traits showed at least some degree of familial resemblance, best explained by shared environment for Anger-in (18%), heritability for Anger-control (34%), John Henryism (34%), and life events (47%), and a combination of heritability (14% and 15%) and shared environment (10% and 20%) for Anger-out and overall anger expression, respectively. The remaining part of the variation for all traits was explained by environmental influences that are unique to the individual. Anger expression and life events were correlated (r = 0.28), and bivariate genetic modeling showed that 61% of this correlation was mediated by common genetic factors.

Conclusions: Individual differences in coping styles and life events in youth can be explained by moderate genetic and substantial environmental influences, of which most are idiosyncratic to the individual. The association between anger expression and life events is largely the result of common genes.

Key Words: anger expression • John Henryism • life events • genetics • twins • ethnicity

Abbreviations: AA = African American; A = additive genetic component; AIC = Akaike’s information criterion; ARCS = Adolescent Resources Challenges Scale; C = common environmental component; CVD = cardiovascular disease; D = dominant genetic component; DZ = dizygotic; E = unique environmental component; EA = European American; MZ = monozygotic.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
METHODS
 RESULTS
 DISCUSSION
 CONCLUSION
 NOTES
 REFERENCES
 
Stress-relatedcoping styles play an important role in moderating deleterious effects of stress on cardiovascular health (1). One such stress-related coping style is anger experience, which can be measured as state or trait anger (2). In contrast to the emotional experience of anger, anger expression is a behavior that can range from the strong suppression of angry feelings (Anger-in) to the extreme expression of anger toward other people or the environment through yelling, slamming doors, and so on (Anger-out).Anger-control refers to the ability to cognitively control anger (3). There is evidence that the frequent and intense experience as well as expression of anger contributes to the onset and exacerbation of coronary heart disease (4,5). Furthermore, both Anger-in and Anger-out have been associated with various forms of cardiovascular disease (CVD), including coronary heart disease and essential hypertension (6,7). Recently, the beneficial role of Anger-control has become apparent. Hauber and Carmon (8) reported a significant inverse relationship between Anger-control and blood pressure.

Another stress-related coping style that has received particular attention in CVD research is "John Henryism," which is characterized by a strong behavioral disposition to actively handle psychosocial and environmental stresses of daily living (9). A number of studies by James (9–11) have shown that among African Americans, individuals who score high on John Henryism and have few resources for effective coping such as low level of education or socioeconomic status tend to have higher blood pressure and are more likely to have hypertension than others. This finding has also been confirmed in a white Dutch population (12). High John Henryism has also been found to potentiate an association between high job status and blood pressure among women and African Americans (13).

Despite demonstrated relationships between anger or John Henryism and CVD, few studies have examined the development and origin of individual differences in coping styles. Busjahn et al. (14) examined the heritability of 19 different coping styles in a study of 117 monozygotic (MZ) and 95 dizygotic (DZ) adult twin pairs aged 34 ± 14 years. Of the 19 scales, 17 showed genetic influences with or without shared environment (heritabilities ranged from 0.22–0.68), and two showed only shared environmental effects. Kendler et al. (15) studied 827 female twin pairs aged 28.9 ± 7.9 years and identified a heritability of 30% for two coping styles, turning toward others and problem-solving, and shared environment for another coping style, denial. To our knowledge, only one twin study involving youth has been conducted. Mellins et al. (16) assessed coping in a study of 44 MZ and 30 DZ pairs aged 9 to 16 years and found considerable familial resemblance. Four of seven coping scales exhibited genetic influences in their study (heritability estimates were 99% for distraction, 53% for use of parents, 18% for use of peers, and 53% for self-soothing), two were influenced by shared environmental factors (problem-solving and emotion-focused coping), and one was influenced by both factors (problem-focused coping, heritability of 57%). These studies provide evidence for the heritability of coping styles. However, to the best of our knowledge, no study included anger expression and John Henryism. Twin studies involving anger have focused on trait anger and indicated low to moderate heritability estimates (17,18). In addition, none of the studies have examined sex and ethnicity differences in the heritability of coping styles. Although one study included nonwhite twins, the small sample size made it impossible to explore potential ethnic differences (16).

Stressful life events are situational occurrences that most individuals would perceive as threatening and/or challenging. Individuals exposed to frequent or ongoing stressful life events may exhibit persistent psychologic and physiological changes that may adversely affect health, including development of CVD (19). Although life events have been used in more than 1000 studies as measures of environmental risk (20), with one exception (21), twin studies have consistently observed significant heritability (26–70%) for total life event scores in childhood (22) as well as in adulthood (23–26). This implies that such events happen (or are perceived to happen) to some people more than others, and this "bad luck" may be related to genetically influenced personality characteristics. Of note, these twin studies only involved white twins.

Accordingly, the first aim of our study was to examine the genetic and environmental origins of individual differences in anger expression, John Henryism, and stressful life events and the extent to which these may depend on ethnicity or sex. To this end, we performed quantitative genetic modeling in a large sample of young European-American (EA) and African-American (AA) twins.

More importantly, if environmental measures like life events show genetic influence as do behavioral measures like anger expression and John Henryism, it is likely that genetic factors contribute to any correlations between them (20). A few multivariate genetic analyses between measures of the environment and behavior have reported that such associations are genetically mediated to some extent (27,28). For example, a bivariate genetic analysis suggested a common genetic influence on life events and depression (29). We hypothesized that individuals experiencing multiple stressful life events are more likely to express angry feelings (ie, higher scores for Anger-in and Anger-out), have more difficulty controlling their anger (lower Anger control scores), and show increased efforts of active coping (higher John Henryism scores). We also hypothesized that any covariance between life events and these coping styles is largely the result of common genes rather than common environment and we conducted multivariate modeling to test this.


   METHODS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
RESULTS
 DISCUSSION
 CONCLUSION
 NOTES
 REFERENCES
 
Subjects and Procedure
Subjects were 308 EA and 226 AA twin pairs from the southeastern United States, including MZ and DZ pairs of same as well as opposite sex (mean age, 14.8 ± 3.1 years; range, 10.0–25.9 years). All subjects were reared together and apparently healthy based on parental report of the child’s medical history. Zygosity was determined using five standard microsatellite markers in DNA collected with buccal swabs (30). Recruitment of twin pairs into the Georgia Cardiovascular Twin Study has been described previously (31) as have been the criteria to classify subjects as AA or EA (32).

As part of their participation in the Georgia Cardiovascular Twin Study, subjects completed a battery of self-report questionnaires by themselves on a computer programmed to prevent errors of omission and out-of-range responses. Fifteen twin pairs were excluded because at least one twin of each of these pairs did not complete the questionnaires. The Institutional Review Board at the Medical College of Georgia gave approval for the study. Informed consent was provided by all subjects and by parents if subjects were <18 years of age.

Measures
Anger expression was assessed with the 24-item Anger Expression Scale (3). The scale consists of three subscales of eight items each, which assess Anger-in, Anger-out, and Anger-control. An overall score for anger expression is computed as the sum of scores on Anger-in and Anger-out minus Anger-control (33). Respondents use a four-point Likert scale ("none" to "almost always") to indicate how often they behave in the manner described when they are angry or furious. Internal consistency of Anger-in and Anger-out as measured by Cronbach’s alpha was reported to be 0.82 and 0.74, respectively (3); no value was reported for Anger-control. One-year test–retest reliability estimates for Anger-in, Anger-out, and Anger-control ranged from 0.44 to 0.60 (33). With respect to the current study, the internal consistency as measured by Cronbach’s alpha for Anger-in, Anger-out, and Anger-control was 0.59, 0.70, and 0.80, respectively.

John Henryism was measured with the 12-item John Henryism Active Coping Scale (9). The scale was designed to measure the degree to which one possesses a strong tendency to actively cope with environmental and psychosocial stressors. Sample items from this scale are: "Once I make up my mind to do something, I stay with it until the job is completely done" and "when things don’t go the way I want them to, that just makes me work even harder." Response options for each question range from "completely true" (score = 5) to "completely false" (score = 1). The internal consistency of the John Henryism Active Coping Scale in youth, as assessed by Cronbach alpha coefficients, ranges from 0.70 to 0.74. Two-week test–retest reliability estimation was 0.59 (34). In the current study, acceptable internal consistency was observed (Cronbach’s alpha = 0.69).

Life events were measured with the Adolescent Resources Challenges Scale (ARCS), which assesses whether the respondent has experienced any of 35 stressful events during the past 12 months (35) (C. K. Ewart, unpublished data). The scale lists stressful life experiences from the neighborhood environment (eg, "I saw or heard people my age or older fighting on the street where I live"), family (eg, "family members abused alcohol or drugs"), and peer environment (eg, "I argued or had problems with my boyfriend/girlfriend"). This scale was chosen because 1) it was designed specifically for use with adolescent populations, and 2) it assesses the accumulation of life events rather than single discrete stressors, a strategy recommended in stress assessment (36). Total ARCS scores have acceptable test–retest reliability over 4 years (r = 0.49) (C. K. Ewart, unpublished data). Evidence of construct validity of the scale is noted in significant correlations between total scores and measures of risk-taking behavior (r = 0.37), depression (r = 0.36), general negative affect (r = 0.44), and reports of illness and injury (r = 0.40) and negative correlations with self-esteem and social support (r = –0.25) (C. K. Ewart, unpublished data). Ewart and Suchday (37) recently found that depression, anger, hostility, and low self-esteem were positively correlated to a stress index measured with an instrument based on the ARCS. With respect to the current study, the total ARCS scale had an internal consistency of 0.71 (Cronbach’s alpha).

Analytical Approach
The aims of our analyses were twofold. First, we estimated the relative influence of genetic and environmental factors on individual differences in Anger expression scales, John Henryism, and stressful life events and tested for their dependency on ethnicity and sex. To this end, we first applied univariate model fitting techniques in AA and EA twins separately to estimate ethnicity-specific genetic and environmental variance components and investigate sex differences. Eventually we combined both ethnic groups into one univariate model to test for potential differences in AAs and EAs. Second, to determine the extent to which potential correlations between coping styles and stressful life events can be explained by genetic and/or environmental factors, we used multivariate modeling.

Model Fitting to Twin Data
Twin methodology makes use of the fact that MZ twins share identical genotypes, whereas DZ twins share on average 50% of their genes. It is assumed that both types of twins share their common family environment to the same extent, so any greater similarity between MZ compared with DZ twins reflects genetic influences. A higher MZ than DZ intraclass correlation (r) provides a first impression of the magnitude of genetic influence as reflected by the classic formula to estimate heritability: h2 = 2(rMZ – rDZ). Model fitting analyses of twin data, however, has some major advantages over the classic twin methodology and is now standard in twin research (38,39). The technique is based on the comparison of the covariances (or correlations) in MZ and DZ twin pairs and allows a more extensive separation of the observed phenotypic variance into its genetic and environmental components: additive (A) or dominant (D) genetic components and common (C) or unique (E) environmental components. E also contains measurement error. Dividing each of these components by the total variance yields the different standardized components of variance, for example, the heritability (h2) can be defined as the proportion of the total variance attributable to additive genetic variation. Extension of univariate to multivariate models additionally allows exploration of the question whether the origin of the covariance between the different variables is genetically and/or environmentally determined.

Sex Differences
Sex differences were examined by comparing a full model in which parameter estimates are allowed to differ in magnitude between males and females, with a reduced model in which parameter estimates are constrained to be equal across the sexes. In addition to those models, a scalar model was tested. In a scalar model, heritabilities are constrained to be equal across sexes, but total variances may be different. All (nonstandardized) variance components for females are constrained to be equal to a scalar multiple, k2, of the male variance components, such that hf2 =k2hm2, cf2 =k2cm2, ef2 =k2em2, and df2 =k2dm2. As a result, the standardized variance components such as heritabilities are equal across sexes, although the unstandardized components differ (38). A path diagram of the applied twin model is shown inFigure 1; k is the scalar factor that indicates that the total variance of the phenotype might differ between males and females.



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  		Figure 1. Path diagram for a univariate scalar model. An opposite-sex twin pair is shown, twin 1 being male and twin 2 female. Observed phenotypes (P) for twin 1 and twin 2 are shown in squares; latent (ie, unmeasured) factors are shown in circles. Correlations between additive genetic factors are 1 in MZ twins and 0.5 in DZ twins. Path coefficients (or factor loadings) of observed variables on the different latent factors are shown in lower case: h = additive genetic effect; c = shared environmental effect; e = unique environmental effect;k = scalar factor. D, the dominance genetic influence, was also tested but is omitted to simplify the diagram.

 

Ethnic Differences
Ethnic differences were, just like sex differences, examined by comparing a full model in which parameter estimates are allowed to differ in magnitude between AAs and EAs, with a reduced model in which parameter estimates are constrained to be equal across ethnicity. In addition to those models, a scalar model was tested in a similar fashion as for sex. All (nonstandardized) variance components for AAs are constrained to be equal to a scalar multiple, k2, of the EA variance components. In these models, heritabilities are equal across ethnicity, although the total variance differs.

Bivariate Genetic Models
A bivariate Cholesky decomposition (38) was used to model the covariance between stressful life events and coping styles. This model allows determination of the extent to which the covariance can be explained by common genetic or environmental factors. Genetic and environmental correlation between two traits can be calculated. The genetic correlation (rg) between two traits gives an indication of the amount of overlap between (sets of) genes influencing those traits. rg is calculated as the (additive) genetic covariance (COVA) between two traits divided by the square root of the product of the total genetic variance components (VA) of each of the traits. The genetic correlation between two traits therefore equals: rg = COVA(trait 1, trait 2)/{surd} (VAtrait1 * VAtrait2). Shared and unique environmental correlations are calculated in a similar fashion.

Model Fitting Procedure
Before analysis, Anger-out (natural log) and John Henryism (square root) were transformed to obtain better approximations of normal distributions. Effects of age(a), sex(s), ethnicity(e), and their interactions (a*s, a*e, e*s, e*r*s) were regressed out for all variables before using the residuals in model fitting. The significance of variance components A, C, and D was assessed by testing the deterioration in model fit after each component was dropped from the full model. Standard hierarchic chi-squared tests were used to select the best fitting models (38) in combination with Akaike’s information criterion (AIC = {chi}2-2 df). The model with the lowest AIC reflects the best balance of goodness-of-fit and parsimony.

Statistical Software
Preliminary analyses were done using STATA 8 (Stata Corp., College Station, TX). Ethnic and sex effects on mean values of anger expression, John Henryism, and stressful life events were tested in regression models, including ethnicity, sex, and their interaction using Generalized Estimating Equations (40), which takes the nonindependency of twin data into account and yields unbiased p values. Genetic modeling was carried out with Mx, a computer program specifically designed for the analysis of twin and family data (41).


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
DISCUSSION
 CONCLUSION
 NOTES
 REFERENCES
 
Descriptive statistics are presented by ethnicity and sex in Table 1. Age, height, and weight were very similar for AAs and EAs. Males were taller and heavier than females. The mean scores of Anger-in for AAs were significantly higher than those of EAs. For John Henryism, an interaction between ethnicity and sex was identified, because AA females showed higher values compared with the other three ethnicity by sex categories. None of the other scales showed significant ethnicity or sex effects.


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  		TABLE 1. General Characteristics, Coping Styles, and Life Events Data of European and African American Males and Females

 

Table 2 lists the twin correlations for each sex by zygosity group in EAs and AAs. MZ correlations show higher values than DZ correlations for most scales, indicating an important contribution of genetic factors. The only clear exception is the Anger-in scale in EAs, in which DZ same-sex correlations were higher than MZ correlations, pointing to a shared environmental effect.


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  		TABLE 2. Twin Correlations for Each Sex by Zygosity Group in European and African Americans

 

Separate model fitting analyses in AA and EA twins allowed us to estimate ethnicity-specific genetic and environmental variance components and investigate sex differences. These results are not shown but helped guide our eventual model fitting in which we included both ethnic groups into one model. Within this model, including all 10 sex by ethnicity by zygosity groups, we tested for potential differences in AA and EA variance components and selected the best fitting overall model for each variable. Parameter estimates and 95% confidence intervals of these best fitting models are presented in Table 3. For all the scales, the best fitting model showed no significant differences in genetic and environmental variance component estimates between AAs and EAs or males and females. All traits showed at least some degree of familial resemblance, best explained by shared environment for Anger-in (18%) and heritability for Anger-control (34%), John Henryism (34%), and life events (47%). For Anger-out and Anger expression, no statistically significant distinction could be made between a model that attributed familial resemblance solely to shared environment or heritability. Thus, the more general ACE model that included both components is reported for these traits in Table 3. The remaining part of the variation for all traits is explained by environmental influences that are unique to the individual. For Anger-in, Anger-out, John Henryism, and life events, significant scalar effects for ethnicity were found, indicating that AAs show larger variability in these traits than EAs.


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  		TABLE 3. Parameter Estimates and 95% Confidence Intervals (CIs) of Best Fitting Models for European and African Americans

 

Table 4 shows phenotypic correlations between life events and coping styles by ethnicity and sex. Life events showed significant positive associations with Anger-in, Anger-out, and Anger expression in all groups, with strongest correlations with Anger expression (ranging from 0.25 to 0.31). No correlation between life events and John Henryism was observed except in AA males (–0.18). We decided to only include Anger expression and life events into the bivariate model to test for common genes and/or environments, because Anger expression showed the strongest correlation with life events, its score incorporates the three separate Anger scales, and no consistent association between life events and John Henryism was found. Model fitting revealed that shared environment could be dropped without a significant deterioration of fit (ACE vs. AE model, {chi}2(3) = 4.04, p = .26), whereas dropping A led to a worsening of fit that was borderline significant (ACE vs. CE model, {chi}2(3) = 7.19, p = .07). Thus, the AE model provided a better fit than the CE model. Similar to the univariate model, no differences between AAs and EAs or males and females were observed; and for life events, the scalar effect allowing for larger total variance in AAs was still included. In this best fitting model (see Figure 2), moderate heritability estimates were found for Anger-expression (38%) and life events (47%), with most of the phenotypic variance of both traits explained by environmental influences specific to the individual (62% for Anger-expression and 53% for life events). Genetic and environmental correlations between Anger-expression and life events were 0.41 (95% confidence interval [CI], 0.25–0.57) and 0.19 (95% CI, 0.09–0.29), respectively. The factor loadings and correlations can be used to calculate the proportion of the phenotypic correlation between Anger-expression and life events (r = 0.28) explained by genetic factors (61%) and environmental factors (39%) as predicted by this best fitting model. These results confirm the expectation that much of the phenotypic correlation of life events with anger expression is attributable to genetic factors. This suggests that the modest genetic contribution to anger expression is partly attributable to genes also associated with life event scores.


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  		TABLE 4. Correlations Between Life Events and Anger Expression or John Henryism for Males and Females in European Americans (EAs) and African Americans (AAs)

 


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  		Figure 2. Genetic and environmental correlations and factor loadings of the best fitting bivariate model for Anger expression and life events. For clarity, only one twin is depicted. Factor loadings (or path coefficients) are expressed as square roots to make clear that squaring those factor loadings yields estimates of genetic and environmental variance components as shown in text. A = additive genetic factor; E = unique environmental factor.

 


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
CONCLUSION
 NOTES
 REFERENCES
 
We determined the contribution of genetic and environmental factors to individual differences in anger expression, John Henryism, and stressful life events in a large sample of young EA and AA twins. All scales showed at least some degree of familial resemblance. The relative influence of genetic and environmental factors to the variability of these traits was not significantly different for AA and EA youth or for males and females. A strong positive correlation between overall anger expression and life events was identified, and further investigation with a bivariate quantitative genetic model found common genetic factors for those two traits.

To the best of our knowledge, this is the first twin study to explore the origins of individual differences in anger expression and John Henryism. This is somewhat surprising given the large number of studies indicating links between these stress-related coping styles and CVD (6–8,10,11). Our results provide strong evidence for familial aggregation for all of the coping styles. However, the sources of familial resemblance were not the same across the scales. For Anger-in, the preferred model indicated that familial resemblance was solely the result of shared environmental factors (18%). By contrast, for Anger-control and John Henryism, the best fitting model indicated that familial resemblance was solely the result of genetic factors with a heritability estimate of 34% for both traits, whereas for Anger-out and overall anger expression, the sources of familial resemblance could be explained by a combination of heritability (14% and 15%, respectively) and shared environment (10% and 20%, respectively). The remaining part of the variation for all coping styles is explained by environmental influences that are unique to the individual. These results show that in young individuals, coping styles are largely determined by environmental influences, most of which are idiosyncratic to the individual.

Anger Expression
Of the three dimensions of anger expression, Anger-in and Anger-control can be classified as internal coping styles based on the lack of external reactions to anger-provoking situations. These internal coping styles may be more difficult to learn through mimicking the parents. Thus, the lack of shared environmental influences on Anger-control might have been expected, but the influence of shared environment rather than genetic factors on the Anger-in scale was surprising. A possible explanation could be that twin resemblance for Anger-in might result from other aspects of the environment likely to be shared by members of a twin pair rather than learning from parents. Further exploration of specific environmental factors shared by members of a twin pair and interviewing the parents to obtain information about their child-rearing strategies will help identify the specific environmental influences on this coping strategy in both EAs and AAs.

In contrast to Anger-in and Anger-control, Anger-out is an acting-out behavior. In our study, 24% of the variance could be attributed to familial effects, but no statistically significant distinction could be made between shared environment or genes, and a model including both components showed a small heritability of 14%. As demonstrated by our results of Anger-in and studies by others (14), we cannot generally conclude that external coping behavior is learned and that internal coping behavior is heritable.

An alternative explanation for the observed contribution of shared environment to the anger expression scales might be found in the young age of our subjects. The importance of familial environment may diminish after subjects leave home in the early adult years as demonstrated by studies on human mental abilities. Approximately 30% of individual differences in childhood IQ are determined by shared environment. This decreases to zero in adulthood at which time a concomitant rise in heritability is shown (42).

Small twin studies often lack the power to detect moderate size influences of common environment, and even our relatively large cohort may lack the power to adequately discriminate between genetic factors and shared environment as sources of familial resemblance (43). In these cases (eg, for Anger-out and overall anger expression), we decided to report the more general (univariate) ACE model reflecting contributions of both genetic factors and shared environment. However, when using a more powerful multivariate model including anger expression and life events, the best fitting model more clearly favored a genetic explanation for the familial resemblance in anger expression with a heritability estimate of 38%.

Continued follow-up of this twin cohort will provide additional power and show whether the majority of the familial effect is the result of shared environment or genetic factors.

John Henryism
Our results suggest that genetic factors significantly influence an individual’s tendency to use the active coping strategy of John Henryism. Previous twin studies have reported that genetic factors were responsible for familial resemblance in coping strategies of problem-solving, active and problem-focused coping (14–16). Although the definitions of these coping strategies were different among these studies and different from John Henryism, many of these psychosocial constructs overlap, ie, confronting adversity or stressors and attempting to solve problems or conflicts in an active fashion. In addition, heritability of John Henryism in AA adults has been addressed in a preliminary study. Brandon et al. (44) identified a heritability of 37% for John Henryism in a study of 102 MZ and 118 DZ twin pairs, very similar to the heritability of 34% we observed in our sample of AA and EA youth. However, a similar heritability in childhood and adulthood does not necessarily mean that the same genes are responsible for the genetic variation in John Henryism in these different periods of life. Longitudinal follow up of this twin cohort and collecting information about John Henryism at older ages will permit us to test this issue.

Stressful Life Events
Previous twin studies have found heritabilities of 26% to 40% for life events in adults (23–26) but have exclusively involved white twins. Among these twin studies, the study by Kendler et al. (23) is the only one that tested for sex differences in heritability of life events and found the results were similar for males and females. Life events were not heritable in a British twin study of 68 MZ and 109 DZ adult pairs, but this study was different from the others in that the sample consisted of referred depressed patients (21). Our findings indicate that heritability for life events in childhood is similar to those estimated in adults and confirm the lack of a significant difference between males and females.

It is noteworthy that our study is the first twin study to test the heritability of life events in AAs and found it was similar to EAs. There is only one study that we are aware of that reported heritability of life events in childhood. Thapar et al. (22) found a heritability of 70% for self-reported life events in a small sample of 43 MZ and 71 DZ twin pairs aged 8 to 17. This estimate is considerably higher than the one in our study and the adult population-based studies, but this heritability estimate is likely to be unreliable as a result of the small sample size. In addition, this study just involved white twins and sex difference for self-reported life events was not explored.

Several explanations have been put forward in the literature to explain the fact that an "environmental" variable like stressful life events shows considerable heritable variation. It is important to keep in mind that life event questionnaires measure perceived rather than actual stressful life events. Thus, a propensity to report life events is influenced by internal characteristics of the rater as well as by external circumstances. Characteristics such as attributional style, self-esteem, mood, and personality traits, some of which are known to be heritable, are likely to affect a person’s perception, interpretation, recall, and reporting of life events (45–47). Although life events may previously have been considered as chance occurrences and unpleasant events to reflect bad luck, it is increasingly recognized that the relationship between individuals and their environment is an interactive one. For example, some people may seek out certain challenging or stressful environments more than others for genetic reasons, for example, related to their personality. If such a gene–environment correlation exists, it will be reflected in the heritable component (20).

Relation Between Coping Styles and Life Events
We did not observe an increase in active coping effort in the face of adversity. On the contrary, the only significant correlation between life events and John Henryism was a negative correlation for AA males. A possible explanation for the lack of a linear relationship might be that an increase in life events will initially lead to increased efforts of active coping, but to decreases in John Henryism scores after a further increase in life events ("giving up"). We found some support for this pattern in our data with a highly significant quadratic life events term in the regression equation indicating that the relation between John Henryism and life events was characterized by an inverted U shape. In future studies, it would be of interest to examine the relation between life events and measures of passive or emotion-focused coping style not collected in this study, eg, distancing and self-soothing. According to our hypothesis that individuals "give up" if life events increase beyond some manageable threshold, a decrease in active coping and concomitant increase in passive or emotion-focused coping would be expected.

In agreement with our hypothesis, we found positive correlations among life events and Anger-in, Anger-out, and anger expression as well as a negative correlation between life events and Anger-control. Overall anger expression, which incorporates the three separate anger scales, showed the strongest correlation with life events (r = 0.28 overall), and a bivariate model was used to test for common genes and/or environments between these two traits. The best fitting model indicated that common genes could explain 61% of the phenotypic association between anger expression and life events. A genetic correlation by itself, like any phenotypic correlation, does not imply directional causality. This common genetic influence may be mediated indirectly, for example, by effects on personality that we know to be heritable. Previous studies suggested that individual perceptions are an important influence in reporting life events (22) and in predicting responses to adversity (48). Thus, another possibility is that genes influence a cognitive style, which in turn has a common influence on reported life events and anger expression. Overlap in unique environmental factors influencing both life events and anger expression was also found, explaining the remaining 39% of the phenotypic association between these two scales. Our findings about the genetic and environmental correlation between life events and anger expression are novel and need to be replicated using a larger sample size with other measures, which ideally should include measures of possible mediating traits such as personality and cognitive style. It remains to be seen what sorts of heritable traits account for the common mediating influence of genes on both life events and Anger-expression and whether these genes can be identified.

Ethnic Differences
Ethnic differences in anger expression, John Henryism, and life events have been noted with AAs having higher mean values than EAs (10,33,49). We partly confirmed these observations and found higher scores for John Henryism in AA females and higher Anger-in scores for AAs in general. The classic twin study is established as the ideal study design to estimate the relative importance of genetic and environmental factors to the variance of traits and diseases in human populations (39). However, without actual measurement of specific genes or environments, it cannot attribute the ethnic difference in mean values to either of these factors. However, our study does show that the observed difference in mean values did not translate to many differences in genetic and environmental variability within each ethnic group. The fact that a similar amount of variation is explained by genetic or (shared) environmental factors within different ethnic groups does not exclude the possibility, however, that the actual genes (or their number) or specific environmental factors responsible for these effects also differ between ethnic groups.


   CONCLUSION
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 CONCLUSION
NOTES
 REFERENCES
 
In summary, the results of the present study suggest moderate genetic influences in youth on most scales of anger expression, John Henryism, and life events in addition to substantial environmental influence, chiefly reflecting unique environmental experiences. The relative influence of genetic and environmental factors was not different between EAs and AAs or between males and females. Common genes explained most of the observed correlation between life events and anger expression. Continued follow-up of our twin cohort will enable us to test whether the same or different genetic and environmental effects influence stress-related coping styles, stressful life events, and the relation between them as individuals make the transition into adulthood.


   NOTES
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 CONCLUSION
 NOTES
REFERENCES
 
Received for publication October 31, 2003; revision received July 28, 2004.

This study was supported by grant HL56622 from the National Heart Lung and Blood Institute.

DOI:10.1097/01.psy.0000146331.10104.d4


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 CONCLUSION
 NOTES
 REFERENCES
 

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