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Human cognitive abilities inter-correlate to form a positive matrix, from which a large first factor, called ‘Spearman's g’ or general intelligence, can be extracted. General intelligence itself is correlated with many important health outcomes including cardio-vascular function and longevity. However, the important evolutionary question of whether intelligence is a fitness-related trait has not been tested directly, let alone answered. If the correlations among cognitive abilities are part of a larger matrix of positive associations among fitness-related traits, then intelligence ought to correlate with seemingly unrelated traits that affect fitness—such as semen quality. We found significant positive correlations between intelligence and 3 key indices of semen quality: log sperm concentration (r = .15, p = .002), log sperm count (r = .19, p < .001), and sperm motility (r = .14, p = .002) in a large sample of US Army Veterans. None was mediated by age, body mass index, days of sexual abstinence, service in Vietnam, or use of alcohol, tobacco, marijuana, or hard drugs. These results suggest that a phenotype-wide fitness factor may contribute to the association between intelligence and health. Clarifying whether a fitness factor exists is important theoretically for understanding the genomic architecture of fitness-related traits, and practically for understanding patterns of human physical and psychological health.
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Intelligence and semen quality are positively correlated
Rosalind Arden
, Linda S. Gottfredson
, Geoffrey Miller
, Arand Pierce
Social, Genetic, Developmental & Psychiatry Centre, Institute of Psychiatry, King's College London, London SE5 8AF, United Kingdom
School of Education, University of Delaware, Newark, DE 19716 USA
Psychology Department, Logan Hall 160, University of New Mexico, MSC03 2220 Albuquerque, NM 87131 USA
Department of Pathology, School of Medicine, University of New Mexico, MSCO8 4640, Albuquerque, NM 87131 USA
article info abstract
Article history:
Received 3 July 2008
Revised 10 September 2008
Accepted 1 November 2008
Available online xxxx
Human cognitive abilities inter-correlate to form a positive matrix, from which a large rst
factor, called Spearman's gor general intelligence, can be extracted. General intelligence itself
is correlated with many important health outcomes including cardio-vascular function and
longevity. However, the important evolutionary question of whether intelligence is a tness-
related trait has not been tested directly, let alone answered. If the correlations among cognitive
abilities are part of a larger matrix of positive associations among tness-related traits, then
intelligence ought to correlate with seemingly unrelated traits that affect tnesssuch as
semen quality. We found signicant positive correlations between intelligence and 3 key
indices of semen quality: log sperm concentration (r=.15, p=.002), log sperm count (r=.19,
pb.001), and sperm motility (r=.14, p=.002) in a large sample of US Army Veterans. None
was mediated by age, body mass index, days of sexual abstinence, service in Vietnam, or use of
alcohol, tobacco, marijuana, or hard drugs. These results suggest that a phenotype-wide tness
factor may contribute to the association between intelligence and health. Clarifying whether a
tness factor exists is important theoretically for understanding the genomic architecture of
tness-related traits, and practically for understanding patterns of human physical and
psychological health.
© 2008 Published by Elsevier Inc.
Semen quality
1. Introduction
The new eld of cognitive epidemiologyis emerging from
the surprising discovery that intelligence correlates with many
important health outcomes, even longevity (Batty, Deary, &
Gottfredson, 2007). These correlations may be mediated by
lifestyle factors such as eating well, exercising, avoiding
cigarettes, working in safer, less stressful jobs, and having
better access to health care. However, there is a further
possibility, suggested by the nature of intelligence itself: all
cognitive abilities, no matter how diverse, inter-correlate
positively, forming a matrix (or manifold). This commonality
depends primarily on a single underlying factor called
Spearman's g, named for its discovererthe Britishpsychologist
Charles Spearman (18631945). Spearman's gusually accounts
for around half the total variance in any broad battery of tests
(Carroll, 1993). The term intelligenceis often used inter-
changeably with g(as here) because the behavioural manifes-
tations of gt well with popular conceptions of intelligence:
the faculty of understanding, quickness of mental apprehen-
sion(Little, Fowler, & Coulson,1984).
Could the positive manifold among cognitive abilities be
part of a larger manifold among all tness-related traits? (By
tnesswe mean the statistical propensity to survival and
reproductive success, given ancestrally typical conditions:
tness-related traits help or harm tness). If so, the gfactor
may be a special case of a more general tness factoror f
factor that captures individual differences in general pheno-
typic quality (Houle, 2000). To investigate this possibility, we
analysed correlations between intelligence and a tness-
related trait that has little face-value association: semen
qualit y (Bonde et al.,1998; World Health Organization,1999).
These two traits arise from distinct organ systems (brain
Intelligence xxx (2008) xxxxxx
Corresponding author.
E-mail address: (R. Arden).
INTELL-00490; No of Pages 6
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versus testicles), composed of distinct cells types: neurons
and glia in brains, spermatagonia and Sertoli cells in sperm
(for a cytological comparison of neurons and sperm see
Meizel, 2004).
2. Methods
2.1. Participants
Our sample consists of US Vietnam-era Army veterans
enrolled in the Vietnam Experience Study (VES) by the US
Centers for Disease Control. In 1985 4462 veterans underwent
extensive medical and mental examinations; of these, 571
provided semen samples. Our analyses focused on the 425
men who had not been vasectomised, who collected their
entire ejaculate without spillage, and for whom we had
complete cognitive data for the measures listed below. These
425 men were aged 31 to 44 (mean 37.6, SD 2.5) at time of
testing. 355 were White, 48 Black, 16 Hispanic, 4 Asian or
Pacic Islanders and 2 Native American or Native Alaskan. The
characteristics of the men who participated in the semen
analysis were nearly identical to those of the larger group of
4462 medical examinees (The Centers for Disease Control,
1989 p.216). Comprehensive details of the sampling design
are found in VES project reports (The Centers for Disease
Control, 1989 pp.1114 and also on the web Centers for
Disease Control, 2007).
We ascertained representativeness further by examining
the General Technical Test (GT) and Armed Forces Qualica-
tion Test scores obtained at induction (~age 18) for (a) the full
sample of 18,313 veterans in the VES study, (b) the subsample
of 4462 men who were given comprehensive examinations in
1985 (~age 37), and (c), of those, the 425 men in our analyses
who provided semen samples. GT means (and SDs) at the
three levels of sampling were very similar, respectively,104.4
(20.1), 106.0 (20.3), and 106.5 (20.5).
2.2. Semen collection and measures
The men were asked to abstain from ejaculating for at least
48 h before semen collection. They were given plastic
containers for collection and insulating cups to keep the
semen warm. Following masturbation in their hotel rooms
(without using lubricants or condoms), the men delivered
their samples to the VES study receiving desk within 30 min
of ejaculation. They noted the number of days since their most
recent ejaculation. In the mid 1980s, objective, standardized
computerised imaging had become available for measuring
sperm concentration and motility. The Cellsoft computer-
assisted semen analyzer system was used to video-record
semen samples within 140 min of collection. For methodo-
logical details of the semen analysis protocols see (Centers for
Disease Control, 1989 pp.197199 and Centers for Disease
Control, 2007, Supplement B pp.35).
We analysed three semen measures: sperm concentration
(millions of sperm per ml of semen, log
transformed to
minimize skew), sperm count (millions of sperm in the total
ejaculate, log
transformed to minimize skew), and sperm
motility (percentage of motile sperm). We selected these
three measures because they are associated with fertility
(World Health Organization, 1999). Sperm concentration and
sperm motility are associated with the likelihood of fertiliza-
tion (Guzick et al., 2001; van der Merwe, Kruger, Oehninger, &
Lombard, 2005). Sperm morphology which is also associated
in the andrology literature with the likelihood of conception
was excluded from our analyses because there is ongoing
debate among evolutionary researchers over whether differ-
ent adaptive sperm morphs exist in humans as a response to
sperm competition (see for review Shackelford & Pound,
2006). If there are sperm morphs that are adaptive under
some conditions (such as sperm competition) then knowing
the quantity of morphologically-typical sperm will be only
partially useful, whereas even under sperm competition,
concentration, count and motility would be useful indicators
of fertility.
2.3. Cognitive tests and extraction of the g factor
The 4462 veterans studied in 1985 took 16 neuropsycho-
logical tests. Of these, we selected the 5 tests that provided
the most psychometrically sound measures of the broad
spatial, quantitative, and verbal abilities typically tapped by
IQ test batteries. These were: the Verbal and Arithmetic tests
of the Army Classication Battery (Montague, Williams,
Gieseking, & Lubin, 1957), the Information and Block Design
subtests of the Wechsler Adult Intelligence ScaleRevised
(Wechsler, 1981); and the Reading subtest of the Wide Range
Achievement Test (Jastak & Jastak, 1965). We used principal
axis factoring on these ve tests to extract a gfactor (which
explained N60% of the total variance among the test scores).
We calculated gscores for all the men in the sample of 4462,
which included the 425 men in this report, and used those g
scores as the index of each man's intelligence.
2.4. Covariates
We assessed ve key covariates that might confound any
observed statistical relation between intelligence and semen
quality. We focused on covariates that might confound our
results by inuencing both semen quality and intelligence
since factors that inuence only one trait would not explain
the correlation between the two traits.
These covariates were: age (at time of testing in 1985),
reported days of sexual abstinence before ejaculation (days
abstinence), body mass index (BMI), alcohol use (self-
reported alcoholic drinks per month currently), and smoking
(self-reported cigarettes per day smoked currently). Intelli-
gence and semen quality may both decline with age; days
abstinence increases sperm concentration and count (Levitas
et al., 2005); intelligence may predict compliance with VES
instructions to abstain for at least 48 h before semen
collection. Finally, less intelligent men might take poorer
care of their health, resulting in more obesity, alcohol
consumption, and smoking. Cigarette smoking is known to
harm semen quality (Soares & Melo, 2008) as does higher BMI
(Nguyen, Wilcox, Skjaerven, & Baird, 2007). Cigarette smok-
ing, alcohol use and obesity have not been shown to harm
intelligence, but since they are pervasively harmful to health
in many epidemiological studies we included them as
potential confounds.
We also examined service in Vietnam (because of possible
exposure to toxins) and self-reported use of marijuana and
2R. Arden et al. / Intelligence xxx (2008) xxxxxx
Please cite this article as: Arden, R., et al., Intelligence and semen quality are positively correlated, Intelligence (2008),
hard drugs (both past and current use for each) because all of
these might undermine semen qualityand more intelligent
men might more effectively avoid them. However, biserial
correlations for these dichotomous variables showed that
none of the ve had a signicant effect on any aspect of semen
quality, so we did not include them in further analyses.
We considered the possibility that an unmeasured third
variable might inuence both intelligence and semen quality.
Variables that inuence only intelligence or semen quality
would not explain any association between the two traits,
although we would still like to know about them. We
considered what factors (for which we have data) inuence
the intelligence of middle-aged men, to see whether they
might also inuence semen quality. The strongest inuence
on intelligence differences in adulthood is genetic. The
heritability of intelligence in men of our sample age is around
70% (Plomin & Petrill, 1997). This does not rule out non
genetic inuences, but we could not identify any specic
examples of environmental inuences on intelligence in
middle-aged men from published reports, other than those
that would have led to the men being excluded from the Army
(such as lead poisoning, iodine deciency). Quantitative
genetic analyses of intelligence nd that the inuence of
shared family background of twins and adoptees is zero in
adulthood (Plomin & Petrill, 1997; Scarr & Weinberg, 1978).
The relatively small non genetic contribution to intelligence
differences among middle-aged men may be non systematic,
arising from idiopathic inuences, random biological noise
and measurement error (Jensen, 1997).
3. Results
3.1. Descriptive statistics
Table 1 provides basic descriptive statistics for intelligence
(g), the three semen measures (sperm concentration, count,
and motility), and the ve key covariates (age, days
abstinence, BMI, alcohol use, and smoking) for the 425 men.
Sperm count, sperm concentration and alcohol use, were
highly skewed, so we log
transformed them for the analyses.
We also log
transformed BMI because its kurtosis deviated
signicantly from normal.
3.2. Correlations
Table 2 shows that intelligence correlates signicantly and
positively with all three measures of semen quality: sperm
concentration (r=.15, p= .002), sperm count (r=.19 , pb.001)
and percentage of motile sperm (% motility) (r=.14, p=.005).
The three semen measures also correlate substantially with
each other (r=.56 to .82). The sample size here (425) affords
above 80% power to detect a correlation of r=.14 at the p=.05
level (two tailed), which is the smallest of the three zero-order
correlations between gand semen quality (SISA website).
3.3. Multiple regressions
Table 3 shows the results fromthe multiple regressions. In
Model 1 we regressed each of the three semen quality
measures, in turn, as the outcome variable on all ve
continuous covariates that might inuence semen quality:
age, day's abstinence, BMI, alcohol, and smoking. In Model 2
we included intelligence (the gfactor) as an additional
predictor. The increase in Rand the R
show that adding the
gfactor improves the t of the model. We also tested several
curve-t regression models but none offered a better t than
the linear model. These results show that the positive
correlations between gand semen quality were not mediated
by age or by three major health hazards: smoking cigarettes,
alcohol and adverse BMI. Nor were they mediated by
Table 1
Descriptive statistics (n=425)
Mean SD Skewness Kurtosis
gfactor 0.02 0.98 0.61 0.45
Sperm concentration (mil/ml) 102.39 80.13 1.24 1.52
Sperm concentration (mil/ml) (log
) 1.86 0.40 0.59 0.11
Sperm count (mil/ejac) 263.23 246.17 1.93 4.81
Sperm count (mil/ejac) (log
) 2.23 0.46 0.61 0.16
Sperm motility (% motile) 58.98 23.37 0.42 0.76
Abstinence (days) 3.15 1.78 2.42 8.40
Abstinence (days) (log
) 0.45 0.20 0.68 0.48
Alcohol (current drinks/mo) 25.85 40.86 2.38 5.80
Alcohol (current drinks/mo) (log
) 0.47 1.21 0.19 1.65
Smoking (current cig/day) 10.66 14.03 1.01 0.06
Age at interview 37.62 2.55 0.11 0.13
Body mass index 25.60 3.64 1.07 3.01
Body mass index (log
) 1.40 0.06 0.42 1.05
Table 2
Correlations among g, semen measures and covariates (n=425)
Intelligence Sperm concentration (mil/ml) Sperm count (mil/ejac) Motility % Abstinence Alcohol Smoking Age BMI
gfactor 1.00
Sperm conc. (mil/ml)
0.15** 1.00
Sperm count (mil/ejac)
0.19** 0.82** 1.00
Motility (%) 0.14** 0.63** 0.56** 1.00
Abstinence (days) 0.01 0.16** 0.24** 0.08 1.00
Alcohol (drinks/mo) 0.08 0.05 0.04 0.07 0.01 1.00
Smoking (cigs/day) 0.09 0.06 0.08 0.02 0.01 0.11* 1.00
Age 0.03 0.09 0.06 0.01 0.00 0.05 0.13** 1.00
Body mass index 0.03 0.02 0.03 0.05 0.09 0.03 0.10* 0.07 1.00
*pb05 (2-tailed)
**pb.01 (2-tailed)
+indicates log base 10
Notes: Abstinence (days), Alcohol (current drinks per month), BMI (Body Mass Index) were log
transformed. Smoking (current cigarettes per day), age at interview.
3R. Arden et al. / Intelligence xxx (2008) xxxxxx
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abstinence, because abstinence and gwere uncorrelated and
therefore made independent contributions to variance in
predicting semen quality.
The assumptions of the multiple regression demand that
the errors, or residuals, are normally distributed (not that the
predictors are normally distributed (Field, 2005 p.170). For
each of the semen quality variables, we examined a
scatterplot of the standardised predicted values with the
standardised residuals to check for heteroscedasticity. We
found, in each case, that the residuals were homoscedastic
having roughly equal variance at each level of the predictors.
We tested for inuential cases that could bias the
regression model by examining the range of Mahalanobis
distances within the sample. Given our sample size and the
number of predictors in our model, Mahalanobis values above
25 may indicate distortion; the largest value in our data was
16.57. A second measure of leverage, Cook's distance, was .18
at the maximum, where values over 1 indicate possible
distortion. Together these analyses gave us condence that
the model does not suffer from serious biases of those kinds.
4. Discussion
The observed correlations between intelligence and
semen quality may under-estimate the true correlations,
given the limited reliability of single semen samples. We
extracted a principal axis factor (unrotated) from the three
semen measures to see whether this improved the reliability
of the measures, but the correlation with gwas very similar
(r= .17). Semen quality varies across ejaculates not just
according to days abstinence, but also by collection method
(Gerris, 1999; Pellestor, Girardet, & Andreo, 1994), and
psychological context (such as cues of partner indelity
(Baker & Bellis, 1989; Kilgallon & Simmons, 2005; Pound,
Javed, Ruberto, Shaikh, & Del Valle, 2002). Thus, each man's
single ejaculate as measured in this study is an imperfectly
reliable indicator of his average semen quality across actual
copulations. Finally, more functional aspects of semen quality
can be assayed today (such as capacitation, acrosomal
reactions and cervical mucus penetration (Aitken, 2006;
Weber, Dohle, & Romijn, 2005); these might inuence tness
more directly than do our measures.
The correlations between gand semen quality are small
(r=.14 to.19). This is not evidence of their irrelevance; on the
contrary the effect size is congruent with phenotypic
correlations observed for other bodily correlates of intelli-
gence such as height (r=.14, r=.15) (Silventoinen, Posthuma,
van Beijsterveldt, Bartels, & Boomsma, 2006; Sundet, Tambs,
Harris, Magnus, & Torjussen, 2005). Notably, these effect sizes
t with average effect sizes (r=.18.19) found across all
studies in evolution and ecology, as reported bya large survey
of meta-analyses (Jennions & Moller, 2003). Very small
correlations with tness can, as Jennions and Moller put it,
turn a mouse into an elephant. This does not mean,
however, that if intelligence or semen quality is positively
correlated with tness, high intelligence or semen quality
would become xed within each mating population.
Although it used to be thought that any trait under selection
would go to xation, this has been falsied empirically: an
extensive literature on the maintenance of additive genetic
variation among tness-related traits now exists, including
for life-history traits (such as height, or time to rst child)
(Houle, 1992; Merila & Sheldon, 1999).
The results in this paper are consistent with the hypothe-
sized general tness factor (ffactor) which, if conrmed,
might help explain the many correlations between intelli-
gence and physical health measures now being documented
in cognitive epidemiology (Batty & Deary, 2004; Hart et al.,
2005; Kuh, Richards, Hardy, Butterworth, & Wadsworth,
2004; Osler, 2003). If a tness factor does exist, and if gis a
component of a more general factor, we will want to know
how this tness factor arises.
One possibility is that an ffactor emerges from individual
differences in mutation load (Houle, 2000; Miller, 2000). While
everyone carries many mildly harmful mutations (Nachman &
Crowell, 2000), people differ in mutation loadthe overall
number of mutations that disrupt tness-related traits. Assor-
tative mating for overall genetic quality in socially monoga-
mous species such as humans would amplify such variance in
mutation load. If most genes have pleiotropic effects on several
traits, then most mutations will harm several traits in parallel
and create positive genetic correlations among traits, as
manifest in an ffactor. The new eld of phenomics (Oti,
Huynen, & Brunner, 2008) reveals correlations among complex
human phenotypic traits, often hinting at underlying genetic
correlations. Such correlations are also found throughout
research on body symmetry (Furlow, Armijo-Prewitt, Gang-
estad, & Thornhill, 1997) and mate preferences (Thornhill &
Table 3
Multiple regressions of semen measures on covariates and g (n=425)
Sperm conc. (mil/ml) (log
) Sperm count (mil/ejac) (log
) Motile sperm (%)
Model 1 Model 2 Model1 Model 2 Model 1 Model 2
Abstinence 0.16 0.00 0.16 0.00 0.24 0.00 0.24 0.00 0.07 0.13 0.07 0.13
Alcohol 0.07 0.17 0.05 0.27 0.05 0.30 0.03 0.48 0.08 0.12 0.07 0.18
Smoking 0.05 0.27 0.04 0.42 0.08 0.10 0.06 0.19 0.03 0.49 0.02 0.67
Age 0.09 0.08 0.09 0.06 0.05 0.29 0.06 0.23 0.01 0.81 0.02 0.75
BMI 0.01 0.78 0.01 0.84 0.02 0.76 0.01 0.84 0.04 0.39 0.04 0.43
gfactor 0.14 0.0 0 0.18 0.0 0 0.13 0.01
R0.20 0.25 0.26 0.32 0.12 0.17
0.04 0.06 0.07 0.10 0.01 0.03
Adjusted R
0.03 0.05 0.06 0.09 0.00 0.02
Notes: Abstinence (days), Alcohol (current drinks permonth), BMI (Body Mass Index) were log
transformed. Smoking (current cigarettes per day), age at interview.
4R. Arden et al. / Intelligence xxx (2008) xxxxxx
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Gangestad, 1999). The correlations between intelligence and
semen quality add to the plausibility of a phenotype-wide f
factor precisely because there is no obvious morphological or
functional relationship between the two traits.
Mutations acting on pleiotropic genes will result in correla-
tions between the traits affected by those genes. Gene expression
is more similar between brain and testes than between many
other human tissues investigated (Guo, Huang, Studholme, Wu, &
Zhao, 2005). Mutations in several genes on the X chromosome
result in both mental retardation and gonadal abnormalities
(Graves, 2006; Wilda et al., 2000). If a gene is very widely
expressed and its products have a pervasively useful and
important job to do, then massive pleiotropy should be detectable
with the appropriate sample size. Some genes now on the human
X chromosome were earlier on autosomes (Kohn, Kehrer-
Sawatzki, Steinbach, Graves, & Hameister, 2007). Evidence
concerning the recruitment of ancestrally old genes to new
functions (including spermatogenesis and intelligence) will
elucidate the connection between sperm quality and intelligence
(Kohn et al., 2007).
A second possibility is that traits under positive selection may
become linkedby assortative mating occurring over many
generationsresulting in what is called gametic-phase disequili-
brium. In a landmark study of people in 37 countries, intelligence
was found to be valued highly by both men and women as a mate
choice characteristic (Buss, 1989). If this preference has been
stable for an evolutionarily-relevant period (see Hawks, Wang,
Cochran, Harpending, & Moyzis, 2007 for a discussion of selection
rates), then trans-generational, cross-trait assortative mating
preferences may be another source of covariance between
intelligence and sperm quality.
The notion of the ffactor is under-explored empirically, yet it
is theoretically important for understanding human genomics,
phenomics, evolution, and intelligence itself. It is also practically
important for interpreting any observed correlations between
physical health, intelligence and socio-economic outcomes
affected by intelligence such as education, occupation, and
traits will be required to establish or refute the existence of a
genuine tness matrix in our species.
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... Tal como fue dicho, podemos suponer que nuestros sentimientos y emociones no son tan diferentes de los sentidos por nuestros antepasados, así, podemos suponer también que los desafíos sexuales tampoco eran diferentes. Por un lado, las fuerzas culturales de la sociedad moderna modificaron radicalmente la manera de sobrevivir, pero los desafíos románticos de seducción parecen mantenerse bastante parecidos a los de entonces (Arden, Gottfredson, Miller& Pierce, 2009). ...
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Desarrollamos el modelo teórico M8 - Modelo de ocho dispositivosadaptativos del cerebro social ? donde incluímos el módulo de puniciónentre los siete que ya estaban previstos en modelos anteriores de cogniciónsocial (Kanazawa, 2004 ). Definimos que el Big five ? 5 grandes rasgos de personalidad , que resultan de la acción estratégica de los módulos . Para testear la existencia del módulo cognitivo de punición, estudiamos elinterés popular por la pena de muerte y la punición en el mundo, conénfasis en los Estados Unidos (2004-2013). Buscamos correlaciones entrecuatro fuentes: 1) datos del Gallup institute ; 2) dados del trabajo de PeterJason Rentfrow (2010); 3) datos del The Democracy Ranking of the Quality of Democracy sobre la calidad de la democracia en los países del mundo y4) datos de Big Data creados a partir de la herramienta Google Trends .Trazamos 4 hipótesis para realizar el estudio: 1) la influencia del M8 (ymás precisamente del módulo de punición), el interés por la punición y la pena de muerte es universal y no varía mucho en su distribución, incluso enescenarios estruturales distintos; 2) existe una fuerte correlación entre altosniveles de extroversión e interés por la pena de muerte en los EstadosUnidos; 3) hay una sólida relación entre interés por la pena de muerte einterés en campañas electorales en los Estados Unidos; 4) existe unatendencia para que niveles similares en cuanto al interés por la pena demuerte aparezca en grupos con preferencias distintas (política y religión),en tanto haya semejanza en cuanto a la distribución de los rasgos de la personalidad (con variaciones en los mismos rasgos). Nuestros resultadosapuntan que la primera y la segunda hipótesis son partidarias tanto en países de alto como de bajo s core democrático, hay incidencia de interés por la punición y la pena de muerte; en los Estados Unidos hay una fuertísima correlación entre interés por la pena de muerte y la extroversión( r = 0,472; p = 0,001). La tercera hipótesis tiene también alta adhesión,existe una correlación altísima entre interés electoral e interés por la penade muerte ( r = 0,336; p < 0,001). Además de eso, encontramos un patrón deestacionalidad de interés consistente, inédito en la literatura. La cuartahipótesis muestra relativa adhesión, puesto que escenarios donde haydistribución de personalidad semejante (con variaciones en los mismosrasgos), los individuos tienden a mostrar niveles de interés semejante por la pena de muerte. La corroboración de las hipótesis 1, 2 y 3 dan base para laexistencia de un módulo punitivo propio del modelo M8 de cognición social.
... Genetic mutations that hinder normal development also impact the quality of sperm (Jeffery et al., 2016). One study found a positive correlation between sperm quality and intelligence (Arden et al., 2009b); however, another, more recent one, did not (DeLecce et al., 2020). Geary (2019) suggested that detrimental mutations that affect cognitive performance involve small inefficiencies in cellular processes. ...
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Cultural innovations, such as tools and other technical articles useful for survival, imply that creativity is an outcome of evolution. However, the existence of purely ornamental items obfuscates the functional value of creativity. What is the functional or adaptive value of aesthetic and intellectual ornaments? Recent evidence shows a connection between ornamental creativity, an individual’s attractiveness, and their reproductive success. However, this association is not sufficient for establishing that creativity in humans evolved by sexual selection. In this critical review, we synthesize findings from many disciplines about the mechanisms, ontogeny, phylogeny, and the function of creativity in sexual selection. Existing research indicates that creativity has the characteristics expected of a trait evolved by sexual selection: genetic basis, sexual dimorphism, wider variety in males, influence of sex hormones, dysfunctional expressions, an advantage in mating in humans and other animals, and psychological modules adapted to mating contexts. Future studies should investigate mixed findings in the existing literature, such as creativity not being found particularly attractive in a non-WEIRD society. Moreover, we identified remaining knowledge gaps and recommend that further research should be undertaken in the following areas: sexual and reproductive correlates of creativity in non-WEIRD societies, relationship between androgens, development, and creative expression, as well as the impact of ornamental, technical and everyday creativity on attractiveness. Evolutionary research should analyze whether being an evolved signal of genetic quality is the only way in which creativity becomes sexually selected and therefore passed on from generation to generation. This review has gone a long way toward integrating and enhancing our understanding of ornamental creativity as a possible sexual selected psychological trait.
... Additionally, Yousef et al. [11] have reported that the accumulation of Al 2 O 3 NP s in the hippocampus of rats affected mitochondrial membrane function and lipoprotein integrity. Interestingly, a relation between dysfunctions of the brain and testis has been evident in recent studies [129,130]. Of note, the marked accumulation of Al in testicular tissues of the Al 2 O 3 NP s + PbAc-co-exposed group could be related partly to the Pb-induced-impaired excretion of Al [125][126][127]. ...
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This study examined the effects of exposure to lead acetate (PbAc) and/or aluminum trioxide nanoparticles (Al2O3NPs) on testicular function. Additionally, the probable reproprotective effects of quercetin (QTN) against Al2O3NPs and PbAc co-exposure in male Sprague Dawely rats were assessed. Al2O3NPs (100 mg/kg b.wt.), PbAc (50 mg/kg b.wt.), and QTN (20 mg/kg b.wt.) were orally administered for 60 days. Then, spermiogram, histopathological examinations of the testis and accessory glands, and immunohistochemical detection of androgen receptors (AR) and tumor necrotic factor alpha (TNF-�) were achieved. Moreover, serum levels of male sex hormones and testicular levels of antioxidant indices were estimated. The results showed that Al2O3NPs and/or PbAc caused significant sperm abnormalities, testicular oxidative stress, and histopathological changes. Furthermore, serum testosterone, LH, and FSH levels significantly decreased, while estradiol levels significantly increased. The Al2O3NPs and/or PbAc co-exposed group had more obvious disturbances. Furthermore, QTN co-administration significantly reversed the Al2O3NPs and PbAcinduced testicular histopathological alterations, reduced antioxidant defenses, and altered AR and TNF-� immune expression in testicular tissues. Conclusively, Al2O3NPs and/or PbAc evoked testicular dysfunction by inducing oxidative injury and inflammation. However, QTN oral dosing effectively mitigated the negative effects of Al2O3NPs and PbAc by suppressing oxidative stress and inflammation and improving the antioxidant defense system.
... Yet it is acknowledged that natural and sexual selection may interact to shape the evolution of phenotypic (Castillo & Núñez-Farfán, 2008;Jiménez-Arcos et al., 2017;Ryder et al., 2012) and signaling (Ríos-Chelén, 2009) traits, hence the importance of considering both selective forces. Intra and intersexual selection could actually improve male cognitive abilities (e.g., Arden et al., 2009;Boogert et al., 2011;Garamszegi et al., 2005;Schillaci, 2006). For instance, intra-sexual selection might enhance male cognition if males with greater cognitive abilities are better able to locate and discriminate among mates. ...
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There has been an increased focus on the role of natural and sexual selection in shaping cognitive abilities, but the importance of the interaction between both forces remains largely unknown. Intersexual selection through female mate choice might be an important driver of the evolution of cognitive traits, especially in monogamous species, where females may obtain direct fitness benefits by choosing mates with better cognitive abilities. However, the importance given by female to male cognitive traits might vary among species and/or populations according to their life‐history traits and ecology. To disentangle the effects of natural and sexual selection, here we use an agent‐based simulation model and compare the model's predictions when females mate with the first randomly encountered male (i.e., under natural selection) versus when they choose among males based on their cognitive trait values (i.e., under natural and intersexual selection). Males and females are characterized, respectively, by their problem‐solving ability and assessment strategy. At each generation, agents go through (1) a choosing phase during which females assess the cognitive abilities of potential mates until eventually finding an acceptable one and (2) a reproductive phase during which all males compete for limited resources that are exploited at a rate, which depends on their cognitive abilities. Because males provide paternal care, the foraging success of mated males determines the breeding success of the pair through its effect on nestling provisioning efficiency. The model predicts that intersexual selection plays a major role in most ecological conditions, by either reinforcing or acting against the effect of natural selection. The latter case occurs under harsh environmental conditions, where intersexual selection contributes to maintaining cognitive diversity. Our findings thus demonstrate the importance of considering the interaction between both selective forces and highlight the need to build a conceptual framework to target relevant cognitive traits. We developed an agent‐based simulation model to investigate the role of natural and intersexual selection through female mate choice on the evolution of a cognitive trait in monogamous species. Here, we predict that intersexual selection should play a major role in most ecological conditions, by either reinforcing or acting against the effect of natural selection. Specifically, female mate choice might favour the rapid evolution of high cognitive abilities in favourable environments but might contribute to maintaining cognitive diversity in harsher ones.
... The similarity was further confirmed by analysis of gene expression, with evidence that human brain and testis, among all the organs of the body, share the highest number of genes [5,6]. More recently, authors found a positive correlation between general intelligence and three key measures of semen quality: sperm concentration, sperm count and sperm motility [7]. A possible association between male sexual dysfunction and neurological disorders was also proposed by several authors [8,9]. ...
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Several strands of evidence indicate the presence of marked similarities between human brain and testis. Understanding these similarities and their implications has become a topic of interest among the scientific community. Indeed, an association of intelligence with some semen quality parameters has been reported and a relation between dysfunctions of the human brain and testis has also been evident. Numerous common molecular features are evident when these tissues are compared, which is reflected in the huge number of common proteins. At the functional level, human neurons and sperm share a number of characteristics, including the importance of the exocytotic process and the presence of similar receptors and signalling pathways. The common proteins are mainly involved in exocytosis, tissue development and neuron/brain-associated biological processes. With this analysis, we conclude that human brain and testis share several biochemical characteristics which, in addition to their involvement in the speciation process, could, at least in part, be responsible for the expression of a huge number of common proteins. Nonetheless, this is an underexplored topic, and the connection between these tissues needs to be clarified, which could help to understand the dysfunctions affecting brain and testis, as well as to develop improved therapeutic strategies.
... Consistent with this is the relatively low additive heritability of fertility in modern populations (≈.30;Tropf et al., 2015), which indicates considerable potential plasticity in response to environmental mediators such as years of schooling. Furthermore genes for higher IQ do not seem to supress intrinsic fertility, as indicated by the presence of small-magnitude positive phenotypic correlations with indicators of reproductive fitness potential, such as sperm quality (Arden, Gottfredson, Miller & Pierce, 2009). This is also consistent with the observation that among Western population, in the absence of factors such as universal education prior to the 19 th century, potential proxies for IQ such as social status actually seem to have been positively phenotypically correlated with fitness outcomes (Skirbekk, 2008). ...
Utilizing a newly released cognitive Polygenic Score (PGS) from Wave IV of Add Health ( n = 1,886), structural equation models (SEMs) examining the relationship between PGS and fertility (which is approximately 50% complete in the present sample), utilizing measures of verbal IQ and educational attainment as potential mediators, were estimated. The results of indirect pathway models revealed that verbal IQ mediates the positive relationship between PGS and educational attainment, and educational attainment in turn mediates the negative relationship between IQ and a latent fertility measure. The direct path from PGS to fertility was non-significant. The model was robust to controlling for age, sex and race, furthermore the results of a multi-group SEM revealed no significant differences in the estimated path coefficients across sex. These results indicate that those predisposed towards higher IQ by virtue of higher PGS values are also predisposed towards trading fertility against time spent in education, which contributes to those with higher PGS values producing fewer offspring.
The interface of sexual behavior and evolutionary psychology is a rapidly growing domain, rich in psychological theories and data as well as controversies and applications. With nearly eighty chapters by leading researchers from around the world, and combining theoretical and empirical perspectives, The Cambridge Handbook of Evolutionary Perspectives on Sexual Psychology is the most comprehensive and up-to-date reference work in the field. Providing a broad yet in-depth overview of the various evolutionary principles that influence all types of sexual behaviors, the handbook takes an inclusive approach that draws on a number of disciplines and covers nonhuman and human psychology. It is an essential resource for both established researchers and students in psychology, biology, anthropology, medicine, and criminology, among other fields. Volume 1: Foundations of Evolutionary Perspectives on Sexual Psychology addresses foundational theories and methodological approaches.
Sperm competition occurs when a female copulates with two or more males within a sufficiently brief period, resulting in sperm of the different males competing to fertilize ova. Sperm competition has been documented or inferred to occur across many species, ranging from insects to primates, including humans. To open the chapter, the theory of sperm competition is introduced and the role of sperm competition as a recurrent adaptive problem for humans is highlighted. Because sperm competition could be detrimental to male reproductive success through cuckoldry, males have likely evolved anti-cuckoldry adaptations. Therefore, convergent evidence of anatomical, genetic, and physiological adaptations to sperm competition in human males is presented. This is followed by a discussion of behavioral and psychological evidence that is unique to humans and that differentiates them from nonhuman species, such as negative affect in response to sexual rejection by a man’s female partner. The remainder of the chapter is devoted to issues still debated within sperm competition theory, such as male precedence, intensity of sperm competition, the role of sperm heteromorphism, and the relationship between male phenotypic quality and ejaculate quality. The chapter concludes with the message that the evidence for anatomical, biological, physiological, genetic, and behavioral adaptations to human sperm competition provides compelling evidence that sperm competition has been a recurrent feature of human evolutionary history.
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Over the past decade, there has been a vast amount of interest in the subject of human sperm competition. This volume brings together, in one place, a key set of classic and contemporary papers that have examined possible adaptations to sperm competition in humans. In addition to classic papers by Robin Baker & Mark Bellis, it includes later work by other researchers some developing their ideas, some refuting their findings. As is to be expected in any comparatively new area of investigation, there are conflicting findings and unresolved issues. This, however, should encourage rather than discourage future research in this field. This collection of papers is essential reading for students of evolutionary biology, evolutionary psychology, human sexuality and researchers considering conducting work in this area. © 2006 Springer Science+Business Media, Inc. All rights reserved.
"Family background" frequently has been found to have long-term effects on adult intellectual, occupational, and economic outcomes. Since families differ both genetically and environmentally, it has been difficult to interpret family effects in studies of individuals or biological relatives. This study includes samples of adoptive and biologically-related families with children between 16 and 22 years of age. We regressed child IQ on several family demographic variables, on parental IQ, and on natural parent characteristics (for the adopted children) to estimate the degree of genetic bias in the coefficients on measured family background. The results indicate that there is little effect of those family environmental differences studied on IQ differences among the adolescents in the SES range of working to upper middle class. Parent-child and sibling correlations further indicate that genetic differences among families account for the major part of the long-term effects of "family background" on IQ.