www.epjournal.net – 2009. 7(1): 28-39
Original Article Is a Successful High-K Fitness Strategy Associated with Better Mental Health?
Cezar Giosan, Department of Psychiatry, Weill Medical College of Cornell University, New York, USA.
Email: email@example.com (corresponding author)
Katarzyna Wyka, Department of Psychiatry, Weill Medical College of Cornell University, New York, USA.
This study examined the associations between a high-K fitness strategy and
mental health. These associations were tested on a sample of 1400 disaster workers who
had exposure to a singular traumatic event and who underwent psychological evaluations.
The results showed that high-K was an important negative predictor of psychopathology,
accounting for significant variance in PTSD, general psychopathology, functional
disability, anger, and sleep disturbances. Implications of the results are discussed. Keywords:
Fitness, adaptedness, high-K, r/K, life history theory, psychopathology, PTSD,
anger, sleep disturbance, disability.
Clinical psychology is one area where evolutionary psychology is having a major
impact (see Nesse, 2005, for a review). The persistent, cross-cultural, relatively high
incidence of mental disorder in the general population suggests that it might have
evolutionary significance. The attempts to explain mental disorder from an evolutionary
perspective centered on the possible functions of distinct mental conditions (e.g., Crow,
1991, 1997, 1995; Fiske and Haslam, 1997; Mealey, 2000) or on the definitions or
taxonomy of mental disorder (Wakefield, 1997; Wakefield and First, 2003). To this end,
disorder is seen either as evolutionary dysfunction—failure of natural design, or as
naturally selected conditions having present or past fitness advantages (Nesse, 2005).
For instance, very much unlike the prevalent view that it is a brain disorder
(Andreasen, 1984; Valenstein, 1998; Wolpert, 1999), evolutionary psychology attempts to
explain depression through the functions it may serve, with some authors arguing that low
mood is associated with less likelihood of engaging in risk-taking behaviors (Leith and
Baumeister, 1996) and others arguing that low levels of depression seem to be “normal” or
functional states (McGuire, Troisi, and Raleigh, 1997; Nesse, 1998; Nesse and Williams,
High-K and psychopathology
Likewise, phobias are explained as “prepared” fears gone awry. Prepared fears are
fears of things that were a threat to survival during the environment of evolutionary
adaptedness. Most phobias are exaggerations of such fears (e.g., spiders, heights, storms,
snakes, strangers, blood, unfamiliar places) (Marks, 1987; Marks and Nesse, 1994) and few
develop phobias of modern threats to survival (e.g., cars, cigarettes, or alcohol).
Mental illness has negative effects on fitness. Severe depression is associated with
reduced fitness (McGuire et al., 1997), as is schizophrenia (Avila, Thaker, and Adami,
2001; Haukka, Suvisaari, and Lönnqvist, 2003). Women with psychotic disorders have
been shown to have lower fertility than matched normal comparison subjects (Howard,
Kumar, Lesse, and Thornicroft, 2002). Likewise, people suffering from non-affective
psychoses have been shown to have significantly fewer children than their unaffected
siblings, with the effect more pronounced for male patients versus well brothers (McGrath
et al., 1998).
Mental illness of the parents seems not only to affect their resultant fitness
translated in sheer number of children but it also compromises offspring quality. Children
of parents with severe mental illness are themselves at increased risk of childhood
psychiatric disorders (Cowling, Luk, Mileshkin, and Birleson, 2004) and the risk of
offspring with impaired intellectual handicap is significantly increased for schizophrenia
and affective psychoses mothers compared with controls (Jablensky et al., 1998). Purpose of the study
The purpose of this study was to examine the associations between a high-K
reproductive strategy and mental illness. According to Life History Theory (e.g., Bogaert
and Rushton, 1989; Figueredo et al., 2006; Mac Arthur and Wilson, 1967; Pianka, 1970;
Wilson, 1975), for any organism, its available resources are finite, which translates into
trade-offs in their allocation for solving various fitness-relevant tasks. For instance, the
resources allocated to grow a bigger body cannot be used to pursue mates, and vice versa.
The extremes of these fundamental dimensions of reproduction are traditionally termed the
r/K theory, with r representing the maximum egg output and no investment and K
representing the opposite. Rushton (1985, 1990) extrapolated the r/K continuum of life
history strategies to human differences from Wilson’s (1975) analysis of cross-species
differences in reproductive strategies. In humans, since they appear to be highly K-selected,
these dimensions are often referred to as “differential K.”
A high-K strategy in humans is theorized as a specific and cohesive fitness strategy,
in which the individual invests in somatic and parental effort to produce a fewer number of
“fitter” and more competitive offspring. Measures of high-K strategy have been shown to
correlate with offspring quality and with resultant fitness (Giosan, 2006). Traits associated
with a high-K strategy are long-term thinking and planning, commitment to long-term
relationships, extensive parental investment, existence of social support structures,
adherence to social rules (e.g., altruism and cooperation) and careful consideration of risks
(Figueredo et al., 2006; Giosan, 2006).
Because a high-K strategy is associated with greater somatic effort as opposed to
reproductive effort, “slow” strategists should manifest the benefits of this in terms of better
mental and physical health. Likewise, low-K ("fast") strategists should exhibit increased
psychopathology and increased physical illness, because these individuals do not allocate
sufficient somatic effort to prevent such problems. Indeed, in one of the first studies on this
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High-K and psychopathology
topic, high-K strategy was shown to be an important negative predictor of depressive
symptomatology, accounting for 20% in the variance in the Beck Depression Inventory
scores, after controlling for risk factors in depression such as demographics, prior trauma,
prior psychopathology, or recent negative life events (Giosan, 2007).
Expanding on these findings, the principal aim of this study was to explore the
associations between a high-K fitness strategy and a larger array of mental conditions,
including PTSD and related psychopathology, sleep disturbances, anger, and functional
disability. The overarching hypothesis tested in this study was that a successful high-K
strategy is a negative predictor of mental illness. Materials and Methods
Participants were a sample of n
= 1400 disaster workers who were deployed to the
World Trade Center in the immediate aftermath of the 9/11 attack. They were administered
a full battery of self-reports and a subsample of 436 (31%) respondents were also
administered a structured clinical interview conducted by doctoral level clinicians. Measures
Clinician-Administered Measures 1) Clinician-Administered PTSD Scale.
The Clinician-Administered PTSD scale
(CAPS; Blake et al., 1995) is a structured interview for posttraumatic stress
disorder (PTSD) that yields both a dichotomous (present/absent) diagnosis of
PTSD and a continuous measure of its severity. The CAPS assesses the
frequency and intensity of each PTSD symptom on separate 5-point rating
scales (0 - 4). Frequency and intensity may be summed for each item to yield a
nine-point (0 - 8) severity rating, and these ratings may be summed across items
to yield a severity score for the full PTSD syndrome. 2) The Structured Clinical Interview for the DSM-IV
(SCID; First, Spitzer,
Williams, and Gibbon, 1997) is a semi-structured clinical interview designed to
determine DSM-IV diagnoses, and its psychometric properties have been well-
established (First et al., 1997). The SCID and selected modules for the DSM-IV,
which included past major depression, past panic disorder, and past generalized
anxiety disorder, were administered and collapsed into one variable (past
psychopathology present or absent). 3) The WTC Exposure Questionnaire
was developed by a panel of trauma experts
to assess occupational exposure through performance of disaster work as well as
personal exposure to the WTC attacks (e.g., loss of loved ones). The
development of the exposure index in this study began with variables that were
shown in the disaster literature to predict PTSD and revised with questions that
emerged as unique to working at the WTC site. For the purposes of this study, a
total exposure score was calculated by summing up the items that the
participants reported as having experienced.
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High-K and psychopathology Self-reports 4) High-K Strategy Scale
(HKSS; Giosan, 2006). HKSS is a 26-item scale tapping
into various indicators of high-K strategy. These indicators include upward
mobility (high-K strategists seek opportunities to gain resources for greater
investment in their offspring), health and attractiveness (high-K strategists
invest in somatic, rather than reproductive, effort, therefore they should enjoy
better health and be, consequently, more attractive), social capital, or risk
consideration. As predicted, this construct correlated significantly with
perceived offspring quality (through the fact that high-K strategists invest their
time and resources in parental effort). It also correlated negatively with number
of previous marriages (because high-K strategists are committed to long-term
relationships). Also, it correlated with objective measures of health, educational
level and social support (because high-K strategists invest in somatic,
educational opportunities and social capital for gaining better access to
resources for their offspring). As expected, this construct showed a weak but
significant correlation with actual number of children (the net result of a
successful high-K strategy is fitness, but characterized through smaller number
of children). Lastly, since a high-K strategy is theorized as a cohesive
reproductive strategy, the indicators that make it up were predicted to have high
internal consistency. Indeed, HKSS’s Cronbach’s ?
was .92 (Giosan, 2006). The
items of this scale are summed up to yield a total score. 5) The PTSD Checklist
(PCL; Weathers, Herman, Huska, and Keane, 1993) is a
DSM-correspondent, 17-item self-report measure of PTSD. Using a five-point
rating scale (1 = “not at all,” 5 = “extremely”), respondents indicate how much
they were bothered in the past month by each of the DSM-IV PTSD symptoms.
The PCL is psychometrically sound and has been used in nearly two hundred
studies across a variety of trauma populations (Weathers et al., 1993). The PCL
yields both a continuous severity score and a PTSD diagnosis. 6) Brief Symptom Inventory.
The Brief Symptom Inventory (BSI; Derogatis, 1993)
is a 53-item abbreviated version of the Symptom Checklist 90-Revised
(Derogatis and Spencer, 1982) that assesses a broad range of symptoms of
psychopathology. The BSI yields scores for nine symptom dimensions as well
as global indices, based on the calculation of mean item responses. In the
present study we used the Global Severity Index (GSI) from the BSI, where
higher scores indicate more severe overall psychopathology. 7) The State Trait Anger Expression Inventory
-2 (STAXI-2). The STAXI-2, a
revised 57-item version of the STAXI (Spielberger, 1988), provides concise
measures of the experience, expression, and control of anger. For the purposes
of this study, the 15-item STAXI State Anger (S-Ang) scale was used to assess
total state anger. The Cronbach’s ?
for this scale in this study was 0.93. 8) Sheehan Disability Scale
. The Sheehan Disability Scale (SDS; Sheehan, 1983)
is a 10-point visual analogue scale that assesses disability across three domains:
work, social life, and family life. The three items may be summed into a single
dimensional measure of global functional impairment that ranges from 0
(unimpaired) to 30 (highly impaired), which was used in this study. This scale
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High-K and psychopathology
has been widely used in psychopharmacology randomized controlled trials and
has strong internal consistency (Cronbach’s ?
= 0.89 for the three-item scale). 9) The Sleep Index
is a modified version of the Pittsburg Sleep Quality Index
(PSQI) (Buysse, Reynolds, Monk, Berman, and Kupfer, 1989), and was used to
assess sleep disturbances and their frequency. PSQI has been widely used to
measure sleep difficulty in different populations (Chesson et al., 2000) and has
good reliability and validity (Buysse et al., 1989; Doi et al., 2000). The
of the sleep index in this study was acceptable (Cronbach’s ?
0.77). Statistical approach
Examining the independent effects of high-K on measures of psychopathology was
the main goal of the study. To this end, correlations between high-K, demographics (age,
race, education, marital status), past psychopathology (dichotomized: “yes” for presence of
past psychopathology, “no” for absence), prior trauma, self-reported (PCL) and clinician-
administered (CAPS) PTSD severity score, general psychopathology (GSI), anger (STAXI-
2), disability (Sheehan), sleep disturbance (total Sleep Index score) and Exposure to 9/11
total score, were first performed.
Simultaneous regressions of the outcomes examined (PCL, CAPS, GSI, STAXI-2,
Sheehan and total Sleep Index score) on the variables that were significantly correlated
with them were then performed to identify the variables that account for significant
variance (tolerances greater than .8) in these outcomes. To examine the unique
contribution of high-K, variables that showed tolerances greater than .8 were then
controlled for in regressions of the outcomes on high-K. Results Demographics
Table 1 depicts the demographic characteristics of the sample (n
= 1400). Overall,
the sample consisted of primarily middle-aged, white, married men with the majority
having at least a high-school education. High-K and psychopathology
The correlation table for all the measures is presented in Table 2. Significant
correlations between high-K and age, marital status, prior trauma, Clinician-Administered
PTSD Scale total severity score, PTSD checklist total severity score, Global Severity
Index, State-Trait Anger Expression Inventory score and Sheehan Disability Scale score,
were found (all p
s ? .01).
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High-K and psychopathology Table 1.
Characteristics of sample (n
) 45.88 (8.86)
Some or no high-school 2.0
Some college or training 34.9
More than college
Separated or divorced
Regressions of PTSD Checklist (PCL) scores on high-K, after controlling for
marital status, exposure and past psychopathology—variables that had tolerances greater
than .8 in simultaneous regressions of PCL on variables that correlated significantly with
it—showed that high-K accounts for an important 10% of the variance in the PCL (negative
relationship) (Table 3).
Regressions of Clinician-Administered PSTD Scale (CAPS) severity scores on
high-K, after controlling for past psychology, prior trauma, and exposure to 9/11 score,
showed that high-K accounts for 5% in the variance (negative relationship) (Table 3).
Regressions of Sheehan total disability score on high-K, after controlling for age,
race, marital status and prior trauma, showed that high-K accounts for 7% of the variance
(negative relationship) (Table 4).
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High-K and psychopathology Table 2.
< .05 Legend:
Pastpsych = prior psychopathology
CAPS = Clinician-Administered PTSD Scale total severity score
PCL = The PTSD Checklist severity score
Sleep = Sleep Disturbances score
Sheehan = Sheehan Disability Scale total score
Staxi = The State Trait Anger Expression Inventory score
GSI = Global Severity Index, where higher scores indicate more severe
Exposure = The WTC Exposure score
Regressions of PCL and CAPS on high-K
PCL CAPS R2 F
Beta t R2 F
- Past psych
- Prior trauma
- Past psych
Regressions of Sleep disturbance on high-K, after controlling for total exposure
score, prior trauma and past psychology showed that high-K accounts for 7% of the
variance (negative relationship) in the sleep index (Table 4).
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High-K and psychopathology Table 4.
Regressions of Sleep disturbance and Sheehan on high-K
SHEEHAN R2 F
Beta t R2 F
- Prior trauma
- Past psych
-.26 -4.93** - High-K
.14 27.97 -.28
Regressions of the Global Severity Index (GSI) on high-K, after controlling for total
exposure score, marital status, past psychopathology and prior trauma, showed that high-K
is a negative predictor of general psychopathology, accounting for on important 12% in the
variance (Table 5).
Regressions of State Trait Anger Expression Inventory (STAXI-2) scores on high-
K, after controlling for age, race, marital status and prior trauma, showed that high-K is an
independent negative predictor of anger, accounting for 6% in the variance (Table 5).
Regressions of STAXI-2 and GSI on high-K
STAXI-2 GSI R2 F
Beta t R2 F
- Marital status
- Past psych
- Marital Status
- Prior trauma
- Prior trauma
.25 26.86 -.42
** p < .01
* p < .05 Discussion
The present study examined the associations between a high-K fitness strategy and
psychopathology, assessed both through clinician-administered measures and self-reports.
It was found that people who had higher scores on HKSS were also those who reported
lower levels of psychopathology, and that high-K emerged as a significant predictor of
psychopathology. This pattern was not singular, but was found across a range of
psychopathologies, including PTSD, sleep disturbances, functional disability, anger, or
These findings, along with previous findings that found high-K to be strongly
inversely related to depressive symptomatology (Giosan, 2007), suggest that high-K
appears to be an important buffer of psychopathology. In our study, high-K accounted for
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High-K and psychopathology
variance ranging from 5% to 12% in the different psychopathologies assessed, the greatest
variance being found in the General Symptom Inventory total score.
The strong negative association between high-K and PTSD seems to speak against
an evolutionary view that argues for the adaptive value of PTSD symptoms (e.g., Nesse,
2005), at least for this particular reproductive strategy. Our results show that lower scores
on high-K, which are associated with reduced fitness (Giosan, 2006), are also associated
with increased severity in PTSD symptoms. Since the findings documented in this study
show that this reproductive strategy correlates negatively with the severity of PTSD, this
result may offer indirect support to the view that holds that PTSD is the expression of an
overlearned survival response in vulnerable individuals (Silove, 1998), which, when it
develops, may have significant negative effects on those individuals’ fitness.
Despite these important findings, several caveats are in order: First, as in any
correlational study, the direction of causality cannot be established with certainty. One can
argue that people score highly on the high-K precisely because they enjoyed better mental
health in the first place and their resources could thus be channeled to the indicators that
make up the high-K factor. This is a legitimate claim and testing the direction of causality
is not a small feat. Further longitudinal studies examining the associations between changes
in high-K and changes in psychopathology are needed to address such questions. Second,
the logistics of the data collection biased the sample toward white males, which may raise
questions about the generalizability of these results to other populations. Further studies on
different populations need to be done to address this aspect. Third, one might argue that the
relationships found in this study might be the result of a broad association between general
mate quality/value and psychopathology. The design of the study did not have mate quality
in the list of the variables examined therefore it could not address this question. Further
research aimed at clarifying these complex associations should be done.
Despite these limitations, the present study, to our knowledge the first to link high-
K and psychopathology, offers evidence that this specific life history strategy is strongly
negatively linked to, and a negative predictor of, a broad range of psychopathologies. Directions for further research
The ramifications of the findings in the present study are multiple. One avenue of
research is to examine the effects of interventions on high-K on psychopathology. Indeed,
since many of the indicators making up the high-K independent criterion of fitness are
modifiable (e.g., appearance, social capital, personal safety, status) the question of whether
active interventions on such indicators would translate into decreased psychopathology
gains practical and clinical significance. A positive answer to this empirical question would
likely aid therapists in their quests of finding more effective interventions.
Also, the high-K measure used in this study is understood as a unidimensional
construct tapping into “slow” life history strategy, with high scores representing successful
resolution of the challenges associated with a high-K strategy, and low scores representing
a faulty high-K fitness strategy and not necessarily “fast” life history strategy. It would be
important and complementary to this work to examine whether faulty fitness strategies in
general—being they faulty high-K or faulty low-K—are associated with mental illness.
Evolutionary Psychology – ISSN 1474-7049 – Volume 7(1). 2009. -36-
High-K and psychopathology Received 4 August 2008; Revision submitted 22 September 2008; Accepted 17
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