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Biological, environmental and socioeconomic determinants of the human birth sex ratio in the Czech Republic

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Abstract

The Trivers–Willard Hypothesis (TWH) states that parents in good conditions bias the sex ratio towards sons and parents in poor conditions bias the sex ratio towards daughters. This study used data from a large nationwide population dataset (N=1,401,851) from the Czech Republic – a modern contemporary society. The study included air pollution and property prices in the TWH estimation, and had a more detailed focus on stillbirths than previous studies. Using official natality microdata from the Czech Statistical Office for years between 1992 and 2010 and data on levels of air pollution in the country over the same period, the study assessed whether the biological and socioeconomic status of mothers and environmental factors affected the sex of children. The results were largely insignificant and not robust across specifications. The presented epidemiological evidence suggests that stillbirths are randomly distributed in the Czech Republic and that the sex ratio is not affected by the socioeconomic status of mothers or by environmental characteristics.
RESEARCH ARTICLE
Biological, environmental and socioeconomic
determinants of the human birth sex ratio in the
Czech Republic
Petr Houdek1* , Ondřej Dvouletý2and Marek Pažitka1
1Faculty of Social and Economic Studies, Jan Evangelista PurkyněUniversity, Ústí nad Labem, Czech Republic and 2Faculty of
Business Administration, University of Economics, Prague, Czech Republic
*Corresponding author. Email: petr.houdek@gmail.com
(Received 12 June 2018; revised 02 February 2019; accepted 04 February 2019; first published online 13 June 2019)
Abstract
The TriversWillard Hypothesis (TWH) states that parents in good conditions bias the sex ratio towards
sons and parents in poor conditions bias the sex ratio towards daughters. This study used data from a large
nationwide population dataset (N=1,401,851) from the Czech Republic a modern contemporary society.
The study included air pollution and property prices in the TWH estimation, and had a more detailed
focus on stillbirths than previous studies. Using official natality microdata from the Czech Statistical
Office for years between 1992 and 2010 and data on levels of air pollution in the country over the same
period, the study assessed whether the biological and socioeconomic status of mothers and environmental
factors affected the sex of children. The results were largely insignificant and not robust across specifica-
tions. The presented epidemiological evidence suggests that stillbirths are randomly distributed in the
Czech Republic and that the sex ratio is not affected by the socioeconomic status of mothers or by envi-
ronmental characteristics.
Keywords: TriversWillard hypothesis; Sex ratio; Economic status
Introduction
Trivers and Willard (1973) proposed a simple mechanism by which natural selection favours
parents biasing the sex ratio of their offspring according to their ability to invest in them. The
TriversWillard Hypothesis (TWH) states that there is a difference in investments in sons and
in daughters depending on parental conditions and their position on the socioeconomic scale.
Like many other studies (Almond & Edlund, 2007; Cameron & Dalerum, 2009; Schnettler 2013),
this study operationalized parental conditions in terms of their socioeconomic status and wealth.
In this way, it was possible to test if evolution would favour systematic deviations from the popu-
lation sex ratio: higher sex ratio of the offspring of mothers living in good conditions (large family
income, high parental education or good environment) and lower sex ratio of the offspring of
mothers living in poor conditions (small family income, low parental education or harsh environ-
ment). In other words, the TWH expects women are considered a safe bet, since women almost
always have some children, in contrast to men, who are only considered when enough resources
are available to ensure that they will have children (the reproductive success of a male child tends
to have a bigger variance, and it is more resource-sensitive).
There is a substantial amount of literature on the TriversWillard hypothesis (Veller et al.,
2016; Bereczkei & Dunbar, 1997; Valente, 2015; Kolk & Schnettler, 2016; Grech, 2018). An
excellent example is a study by Almond and Edlund (2007), on which this study is built and
© Cambridge University Press 2019.
Journal of Biosocial Science (2020), 52: 1, 3756
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expands on in multiple ways. Almond and Edlund used a general sample US natality data from
19832001 (48 million births and 310,000 infant deaths) and found results consistent with the
TWH. It provided two main results: that married, better-educated and younger mothers bear
more sons and that the infant deaths of males are greater if the mothers are young and unmarried.
Tests of the TWH are rare in modern contemporary societies. Moreover, tests of it on a general
country population dataset are extremely uncommon since most research has been done on spe-
cific samples. To the authorsknowledge, this study is the first to consider the TWH in the Czech
Republic, although Kaňková et al. (2007) found an increased sex ratio in the clients of expensive
private reproductive medicine clinics in the Czech Republic. In addition, the research attempted to
connect the TWH with the capitalization hypothesis. In other words, air pollution and property
prices were tested among other determinants of the TWH (properties in a cleaner environment
are more expensive as well, thus giving a better proxy of a households socioeconomic status).
Finally, the research focused on stillbirths in more detail than most previous papers.
The main research question was whether the biological and socioeconomic status of mothers
and environmental characteristics such as air pollution affect the sex of children. To test the
hypothesis, natality microdata were drawn from the Czech Statistical Office (CZSO) and data con-
cerning levels of air pollution in the country were drawn from the Czech Hydrometeorological
Institute (CHMI).
The TriversWillard Hypothesis
Trivers and Willard (1973) showed that under certain well-defined conditions, natural selection
favours systematic deviations from the natural sex ratio of 105106 at conception and that these devi-
ations tend to cancel out in the local breeding population. The hypothesis predicts that mothers living
in wealthy conditions (relatively large parental investments) will have more sons, and that mothers in
poor conditions (relatively small parental investments) will have more daughters. Because the repro-
ductive success of a male child tends to be more variable and resource-sensitive, higher reproductive
success is achieved if parents have a daughter in poor conditions and a son in wealthy conditions. The
TWH says nothing about conscious motivations, as Hopcroft (2005, p. 1114) commented, and behav-
ioural strategies that favour reproductive success have simply been selected and proliferated.
There are at least two biologic and/or economic reasons why parents should behave according to
the TWH. The first is that parents should invest resources with the highest rate of return. In this
case, the rate of return is their offsprings reproductive success. When the variance in the reproduc-
tive success is greater for males than for females, and when the males reproductive success is more
resource-sensitive, parents will invest more in males (or they will wanta male rather than a female),
because then they will have a greater return on their investment (Clutton-Brock & Iason, 1986).
Secondly, costs to the mothers future reproductive potential of producing a son versus a daughter
vary with maternal conditions (Higashi & Yamamura, 1994). It is necessary to consider the effect of
a given unit of investment, not only on the reproductive success of the offspring but also on the
mothers future reproductive success (Clutton-Brock & Iason, 1986). For example, a poor mother
cannot invest many other things except the time spent with a child. Moreover, because she comes
from poor conditions, she probably has to go back to work earlier after pregnancy than a mother
from good conditions. So, a female child can be, in some circumstances, a cheaper and more ad-
vantageous investment for a mother in poor conditions in terms of the offsprings reproductive suc-
cess, the mothers reproductive success and the cost of children (Dubois & Rubio-Codina, 2012).
The model of Trivers and Willard depends on the following three assumptions:
1. The conditions of a child at the end of the parental investment will be correlated with the
conditions of the parents during the parental investments. For example, more educated peo-
ple will produce more educated children (Sewell & Shah, 1968; Oreopoulos et al.,2006).
Similarly, children of wealthy people will be wealthier.
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2. The differences in the childrens conditions at the end of the parental investment will tend to
endure into adulthood. In the case of humans, parental investments are quite long and not
pre-defined. In other words, parents can support their offspring for their whole life.
3. Resources have heterogeneous effects on males/females reproductive success. The reason-
ing for this assumption is as follows: women prefer men with greater resources (wealthier),
so such men can attract a larger number of high-quality mates, and simultaneously men
prefer younger and more attractive women for their mates (Buss, 1989,2007; Kanazawa,
2003). As a result, womens reproductive success is largely orthogonal (not correlated) to
their parents socioeconomic status. Furthermore, women cannot produce many offspring
due to their greater obligatory role in parental investment into each offspring (Kanazawa,
2003). Therefore, men with greater resources can afford more offspring, but for a woman,
this does not hold. One of the problems with this assumption could be paternal investments.
Trivers and Willard (1973) commented on this as follows:
The application of the model to humans is complicated by the tendency for males to invest
parental effort in their young (which reduces variance in male reproductive success), and by
the importance of kin interactions among adults. Despite these complications, the model can
be applied to humans differentiated on a socioeconomic scale, if the reproductive success of a
male at the upper end of the scale exceeds his sisters, while that of a female at the lower end
of the scale exceeds her brothers. (Trivers & Willard, 1973, p. 91).
Pérusse (1993) found that male reproductive success in Quebec in the years 19881989 did not
increase with status (as measured by a composite of income, education and occupational prestige),
but it did lead to greater sexual access. This finding, however, does not universally hold. Offspring
numbers have been found to grow with income, wealth and educational level in men in most
countries, whereas an inverse pattern, or no pattern at all, is true for women (Fieder & Huber
2007; Hopcroft, 2006,2015; Nettle & Pollet, 2008; Goodman & Koupil, 2010; Lappegård &
Rønsen, 2013; Morita et al.,2017; Nisén et al.,2018). For example Cameron and Dalerum (2009)
investigated a group of the wealthiest people in the world (400 people from the Forbes billionaire
list) and found that male billionaires had significantly more children, and a more variable number
of children, than female billionaires. Nevertheless, Hopcroft (2005) argued that the differences in
reproductive success do not need to hold today for the TWH to be valid:
Given this situation in the evolutionary environment, by the logic of TriversWillard, there
may exist evolved psychological and physiological mechanisms that promote high-status
parents to invest more in sons and low-status parents to invest more in daughters, regardless
of any contemporary sex differences in reproductive success. Given such evolved mecha-
nisms, high-status parents are expected to invest more in sons, and low-status parents to
invest more in daughters, even if males are not actually more reproductively successful in
the contemporary environment. (Hopcroft, 2005, p. 1115).
This statement is also supported by the study of Freese and Powell (1999):
Once such a tendency has evolved, its influence on parental investment should persist even in
evolutionary environments in which the TriversWillard effect does not contribute to greater
fertility (e.g., in contemporary American society and others in which social status and num-
ber of offspring are not positively related). (Freese & Powell, 1999, p. 1710).
Hill (1984), in their study of contemporary huntergatherer societies, stated that it is probable
that a reliable relationship between reproductive success and male status existed among human
ancestors. Moreover, Nielsen (1994) and Crawford (1998) claimed that modern developed
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societies have not existed long enough to reverse or substantively alter the cognitive mechanisms
that have evolved over the last thousands or millions of years.
It can be expected that low-status parents will invest more in a female child than a male child,
while high-status parents will invest more in a male child than a female child. The TWH can be
further divided into two separate hypotheses. The first is that alteration of the sex ratio depending
upon maternal conditions, both in utero and through infanticide after birth, is called Sex Ratio
Biasing (SRB). The second is that allocation of more resources to offspring of one sex after birth
(larger parental investments) depending upon the parentsconditions (family income, education,
age or health) is called Resource Allocation Biasing (RAB) (Koziel & Ulijaszek, 2001). In the case
of humans, this is not only the provision of nutrition to children while they are young, but also
investment in education and the social and cultural development of children (Hopcroft, 2005).
Interestingly, a distinction between RAB and SRB predictions can be made. This article is not
the first to emphasize the distinction and its implication for predictions based on the TWH.
Anderson and Crawford (1993, p. 151) addressed the question with a simple model: Under what
conditions do the parental behaviors that maximize numbers of grandchildren resemble the
TriversWillard rules of thumb?Using data from the !Kung of southern Africa, they found that
optimal sex ratios are heavily influenced by the existing children of different ages and sexes in
ways not predicted by the TWH. For this reason, some researchers only used the first child in
their analysis (Kanazawa & Apari, 2009). For the RAB, Anderson and Crawford stated that opti-
mum parental behaviour is sensitive to population dynamics, type of parental investment and,
most importantly, relative ages of sons and daughters. Moreover, they concluded that it is doubtful
whether the TWH rules (for the RAB) would maximize the number of descendants.
Another critique of the RAB is Keller et al. (2001); they argued that the TWH does not, in fact,
predict the RAB in already existing offspring. According to the authors, the TWH should be lim-
ited to predicting those parental investments (e.g. the SRB, protection) that are related to fitness
value. They used the following example:
::: consider two mothers in equally poor condition, one that has a son and one a daughter.
Given the TWH assumptions, the mother with the daughter should have a fitness advantage
over the mother with the son due to the different fitness values of the offspring; therefore
selection favours a female-biased sex ratio for mothers in poor condition. However, the
low-condition mother with the son should invest more in the son than the low-condition
mother does in the daughter if the marginal benefit of investing additional resources is
greater for sons. The bias for SRB, in this case, is in the opposite direction from the RAB
bias. (Keller et al., p. 357).
In conclusion, the RAB predictions are far more complex, and a simple prediction of the TWH
about this matter can often be non-maximization strategy. This research focuses on the SRB only.
The TriversWillard Hypothesis more research on humans
There is an immense challenge in the testing of the TWH. It is probable that it may not be
observed in societies that are resource-rich compared with ancestral environments. However,
across time and area, the absolute level of resources varied considerably between ancestral groups,
yet within each group, high-status males had higher reproductive success than low-status males.
Keller et al. (2001) further commented on this issue:
Because of this, a mechanism tracking absolute inputs (e.g. calories) would be disadvanta-
geous compared to a mechanism that tracked relative inputs (e.g. status). Therefore, it is
unlikely that the absolute level of resources has an effect on the putative TW mechanism.
(Keller et al., 2001, p. 347).
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Koziel and Ulijaszek (2001) added that the TWH probably reveals itself in those populations
where the extent of social stratification is sufficiently diverse.
Perhaps the best-known report on the TWH on humans is Dickemanns analysis of female in-
fanticide in historically hypergynous societies (Dickemann, 1979). Her main result is that female
infanticide was widespread among the upper classes in historically hypergynous societies because
higher-class daughters had a smaller chance of marrying upcompared with higher-class sons. This
fact can be interpreted as an indicator of an unwillingness to invest in the children of the murdered
sex. However, other theoretical papers have suggested that infanticide would rarely be an adaptive
strategy (Anderson & Crawford, 1993). Moreover, as Keller et al. (2001) pointed out, the sex bias
produced by infanticide can be the opposite of that predicted by the TWH. An example is the study
of Voland et al. (1991), who investigated high-status 18th and 19th century Germans in Krummhorn.
They reported that high-status Germans were more likely to commit male infanticide in that time.
This strategy helped them to keep their property undivided. Infanticide can sometimes be consistent
with the TWH but it depends on the situation and the immediate goals of parents.
Chacon-Puignau and Jaffe (1996) and Zaldívar et al. (1991) tested the TWH in Venezuela using
a large sample from the national birth registry (578,000 observations). They identified only a very
small effect of womens marital status on the sex ratio. Zaldívar et al. reported no relationship
between womens marital status and birth sex ratios or sex ratios at later ages. Using data from
the Gabbra pastoralists of Kenya, Mace (1996) also reported no relationship between womens
marital status and sex ratio at birth or among living children. On the other hand, Cronk (1989),
investigating Mukogodo children (aged 04), found that this population was female-biased, and
since the Mukogodo are at the bottom of a regional hierarchy, the results are consistent with the
TWH. Jha et al. (2006) investigated the sex ratio of the population of India (N=133,738). Their
main result in the context of this study was that better-educated women had a significantly higher
adjusted sex ratio (683 girls to 1000 boys; 99% CI 610756) than illiterate women (869 girls to
1000 boys; 99% CI 820917). Finally, Luo et al. (2017) found that, in China, low-status family
heads have more grandchildren through their daughters than their sons, whereas high-status
family heads have more grandchildren through sons.
Overall, tests of the TWH in more developed societies have been inconclusive. Betzig and
Weber (1995) used data on men in the US Executive Branch, including presidents, vice presidents
and cabinet secretaries. They reported that parents in their sample produced more sons than
daughters in the first cohort (Presidents Washington through Garfield); however, in the second
cohort (Presidents Arthur through Reagan), they produced roughly equal numbers of sons and
daughters. Essock-Vitale (1984) examined the number of children among the Forbes list of the 400
wealthiest Americans. She found that they had on average more children than the general US
population and that wealthy Americans appeared equally likely to have sons as to have daughters.
Cameron and Dalerum (2009) conducted a similar study on a sample of the 1000 wealthiest
people in the world (they also used the Forbes billionaire list). However, they used just 399 obser-
vations (350 male billionaires and 49 female billionaires).
The goal of Schnettlers(2013) paper was to shed light on the matter of mixed results in the
literature. He proposed two hypotheses sample selection (mostly due to missing data) and lack
of specification of the timing of wealth accumulation. He corrected both problems. Firstly, the
analysis was based on a dataset of US billionaires with near-complete information on the sex
of their offspring. Secondly, the subgroups of billionaires were distinguished according to the
timing of their wealth accumulation. Although he found that the results on the hypothesis that
billionaires have a higher share of male offspring than the general population were not consistent
for all subgroups of billionaires, he also reported that heirs, but not self-made billionaires, had a
higher share of male offspring than the US population. Contrary to this finding, the author also
reported that heiresses had a much lower share of male offspring than the US average. These
results imply that there are other mechanisms affecting the sex birth ratio as well; nevertheless,
they were not uncovered in the paper.
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There are also several papers that used a general population sample; Abernethy and Yip (1990)
used linked birthdeath records from the years 1976 to 1983 in the state of Tennessee. After strat-
ification of the sample by socioeconomic indicators, they found the pattern for post-neonatal
infant deaths to be supportive of the TWH. Norberg (2004) investigated maternal partnership
status at the time of conception, and found that status could be taken as a determinant of the
sex ratio. Almond and Edlund (2007) analysed the linked births and infant deaths of white moth-
ers in the US from 1983 to 2001. The study provided two main results. Firstly, married, better-
educated and younger mothers bore more sons and, secondly, male infant deaths occurred more
frequently if the mother was unmarried and young. Finally, Guggenheim et al. (2007) provided a
comprehensive analysis of nationally representative samples from 35 countries (survey data were
collected by the Demographic and Health Surveys) and reported that the analyses did not support
the TWH, but there was evidence of regional- and country-level differences.
Mechanism of the TriversWillard Hypothesis
Most previous studied worked with a simple mechanism of the TWH: the effect of socioeconomic
status on sex ratio at birth is based on the conditions of the mother. High-status mothers are more
likely to be in good condition and are better able to carry a male fetus to term (Hopcroft, 2005).
Almond and Edlund (2007) argued a similar mechanism, but nevertheless acknowledged that
mortality in utero would be a more advantageous measure because the closer to conception,
the lower the replacement cost of terminated offspring.
Another branch of research has focused on maternal diet. Apparently, a diethigh in saturated fats
but low in carbohydrates results in higher levels of circulating glucose, which can lead to the birth of
significantly more male than female offspring (in laboratory mice) (Folmer et al.,2003). Mathews
et al. (2008) investigated the effect in a human population; they used data on 740 Britishwomen who
were unaware of their fetusssex.Theyreportedthat:Fifty-six per cent of women in the highest
third of preconceptional energy intake bore boys, compared with 45% in the lowest third. Intakes
during pregnancy were not associated with sex, suggesting that the foetus does not manipulate ma-
ternal diet,(Mathews et al.,2008, p. 1661). In contrast, Gibson and Mace (2003) reported a strong
association between the sex of the most recent birth and maternal nutritional status in Kenya in
2000. Based on this evidence it seems likely that the nutritional status of the mother (as an important
part of the costs of reproduction) plays a significant role in adjusting sex ratios.
Air pollution and property prices
First, a simple yet informative model is used to explain why this paper used air pollution and
property prices to test the validity of the TWH. Lets assume two identical communities which
differ only in air pollution level. In the case of zero moving costs and identical property prices,
everybody would want to live in the community with the lower level of air pollution. However, as
people move out from the more polluted community, the property prices go down in the more
polluted community. Because of the moving people, the property price in the less-polluted com-
munity increases. This mechanism continues up to the point where the two communities reach
equilibrium the difference between the property prices in the two communities is greater than
the marginal willingness to pay for a reduction in air pollution of the people in the more polluted
community. In this situation, the pollution is capitalized in property prices.
Polinsky and Shavell (1975) summarized the debate over the relationship between air pollution
and property values. Smith and Huang (1995) conducted a more recent meta-analysis. They reported
that the range of these estimated marginal values (measured as a change in asset prices) lies between
US$0 and US$98.52 (in 19821984 dollars) for a unit reduction in total suspended particulates (in
micrograms per cubic metre). Furthermore, the mean marginal willingness to pay for the reduction
in air pollution is about five times larger than the median (US$109.90 vs US$22.40), so the outliers
play an important role in any summary statistics for these estimates. Moreover, suburban properties
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(with lower air pollution and in an overall cleaner environment) are much more expensive than
properties in the city centre (Harrison & Rubinfeld, 1978).
The second mechanism explaining why air pollution can affect the sex ratio is motivated by the
fact that male fetuses are more vulnerable and thus more prone to miscarriages (Catalano, 2003;
Peterka et al.,2004; Helle et al.,2008). Worse quality of air can cause miscarriages, and since boys
are more likely to be a miscarriage, they should be affected more frequently. In other words, more
girls should be observed in more polluted areas.
Methods
Czech Statistical Office (CZSO) dataset
The study utilized official microdata on newborns and stillbirths and their parents from the CZSO
dataset for the following available years: 1992, 1994, 19962004, 2006, 2008 and 2010 (i.e. all births
in a given year in the Czech Republic). The whole country population dataset contains 1,401,851
observations with the below-described variables.
The data on the prices of flats and houses also came from the CZSO. Annual data on these
prices for all Czech districts in the period of 2001 to 2011 were also used. The prices in a district
where the child was born were matched to the dataset of births (at a Local Administrative Unit
(LAU1) level based on the EU Classification of Territorial Units for Statistics). There are 77 LAU1
districts in the Czech Republic. The variables are described in Table 1.
Czech Hydrometeorological Institute (CHMI) data
Daily data were taken from the CHMI on level of air pollution from 216 district stations in the
Czech Republic ranging from 1993 to 2012. The variable was measured at a LAU1 district where
the child was born. For the purposes of the study, such a detailed dataset was not needed because
the prices of properties do not react on a daily basis, but rather on a long-term average level.
Because of this, the data on pollution were transformed to monthly averages.
The dataset contained many missing observations. Ideally, the dataset should contain 216 (the
number of stations) times 240 (the number of months in the 20-year period), which is 51,840
measurements. However, it only contained 28,513 measurements, so approximately 45% were
missing, which is a clear limitation of this variable. However, as the variable might enrich the
existing knowledge in the field, it was still considered in the empirical analysis. The air pollution
variable was Air pollution (PM10). Particulate matter concentrations refer to fine suspended
particulates less than 10 microns in diameter (PM10) that are capable of penetrating deep into
the respiratory tract and causing significant health damage (World Development Indicators,
World Bank, 1993 to 2012).
The Index of Property Prices
The correlation between the prices of flats and houses was 0.93, which is quite large. These data are
ideal for a dimension reduction, which means that a new variable could be created the Index of
Property Prices representing the flat and house price variables using principal component anal-
ysis (PCA). Bartletts test χ2with one degree of freedom has a critical value of 6.63 (based on a 99%
level of confidence, i.e. α=0.01). The resulting statistic is around one and a half million, which is
much higher than the critical one. The p-value is practically zero, so the null hypothesis is rejected.
Based on the test, the dimension reduction is justified. In the PCA, the number of variables is equal
to the sum of eigenvalues. Table 2demonstrates that the first component can explain almost 97%
of the variance in the original two variables. Applying Kaisers rule, only the first component is
included. This decision is further supported by the evidence in Table 3, which presents the
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Table 1. Descriptions of study variables
Variable Description
Birth date Full date of birth (day, month and year)
Male child Dummy variable; male=1, female=0
Vitality Dummy variable; child born alive=1; not alive=0
Multiple birth A multiple birth occurs when more than one fetus is carried to term
in a single pregnancy. The variable has a value of 1 for single births;
2 for twins; 3 for triplets, and so on.
Multiple birth dummy variable Dummy variable: 1 if woman had multiple births, and 0 otherwise
Weight Birth weight (g)
Gestation age Length of pregnancy, from last normal menstrual period to birth
(weeks)
Czech citizen Dummy variable: 1 if mother has Czech citizenship, and 0 otherwise
Number of previous children Number of children the mother had before the current child.
Childs order Variable reflecting the childs order calculated as a number of previous
children plus one.
Single Dummy variable: 1 if mother is single, 0 otherwise
Divorced Dummy variable: 1 if mother is divorced, 0 otherwise
Married Dummy variable: 1 if mother is married, 0 otherwise
Widowed Dummy variable: 1 if mother is widowed, 0 otherwise
Education of father 1=basic education; 2=lower secondary education; 3=higher secondary
education; 4=tertiary education
Education of mother As above
Mothers age Age of the mother (years)
Flat prices Average price per square metre of a flat at the time of a childs birth in
the district in which they were born (LAU1).
House prices Average price per square metre of a house at the time of a childs birth
in the district in which they were born (LAU1).
Air pollution (PM10) Particulates less than 10 microns in diameter (PM10) that are capable
of penetrating deep into the respiratory tract and causing significant
health damage. The variable is measured in the district the child was
born (LAU1).
LAU1 district Dummy variable reflecting district at the LAU1 level based on the EU
Classification of Territorial Units for Statistics, where the child was born
Year Dummy variable reflecting the year the child was born
Table 2. Eigenvalues and total variance explained: the Index of Property Prices
Initial eigenvalue
Component Total % of variance Cumulative %
1 1.938 96.877 96.877
2 0.062 3.123 100.000
Source: authorscalculations based on property prices from CZSO data.
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component loadings. The component loadings and their least squares, as well as the communali-
ties, also suggest that the one resulting variable represents the original variables very well.
Analysis
The TriversWillard sex ratio hypothesis was tested in two ways. First, the CZSO microdata sam-
ple was used to assess whether high-status people are more likely to have male offspring. Sex ratio
was analysed by mothers age, citizenship, marital status and education of the mother and father.
Inspired by Almond and Edlund (2007), the same perspective was adopted whereby the sex of a
child is mostly endogenous to the characteristics of the mother. Marital status, education and citi-
zenship are also good proxies for socioeconomic status in the Czech Republic: there is general
mortality advantage for married people (Murphy et al.,2007) and depressive symptoms have been
found to be positively associated with being unmarried (Bobak et al.,2006); low level of education
strongly correlates with low income and well-being, mortality and stress-related illnesses, and is a
good measure of deprivation (Bobak et al.,1999,2005; Chase 1998; Hayo & Seifert, 2003); female
immigrants have poorer self-rated health in the Czech Republic (Pikhart et al.,2010).
Although there could be mechanisms affecting the sex ratio at conception, the authors do not
possess data to test this possibility. Therefore, the study focused on how mortality in utero shapes
the sex ratio at birth. Data on early fetal deaths were not available, whereas data on stillbirths were
available, so these were used to study the extent to which mortality in the late fetal period (more
than 28 weeks) may be considered a proximate mechanism for the TriversWillard effect. The
authors hypothesize that there will be greater mortality among males born to mothers in poor
conditions, which would lead to a positive association between maternal conditions and male
sex among live births.
The regression specification was as follows:
maleiα0α1Xiα2Hiα3CiγtNt2
i(1)
where male
i
is a dummy variable taking the value 1 if child iis male; α
0
is the intercept; X
i
is a
matrix of the socioeconomic (citizenship, marital status and education) and biological (age) char-
acteristics of the mother, which capture her conditions; H
i
is a matrix of variables capturing the
father´s education; C
i
is a matrix of control variables (pollution, property prices); γ
t
is a vector of
dummy variables for particular years (when the child was born), which accounts for the annual
differences in the sex ratio and captures trend changes; N
i
is a vector of dummy variables captur-
ing the districts where the child was born (at LAU1 level) and ϵiis an error term. Under the TWH,
α
1
can be expected to be positive characteristics such as education. Also, married mothers can be
expected to be more likely to have a son (under the assumption that married mothers are in a
better conditions than unmarried mothers). As there might be differences with respect to the sur-
vival of the child, equation (1) was solved for three samples: 1) all births; 2) all live births; and 3)
stillbirths. Under the TWH, children born to mothers in good conditions would be less likely to be
stillbirths.
Table 3. Component matrix and communalities
Component loading 1 2 Communalities
Flat prices 0.984 0.177 0.969
House prices 0.984 0.177 0.969
Source: authorscalculations based on property prices from CZSO data.
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As an additional robustness check, the study aimed to include variables concerning infants
health status at birth (measured by gestation time and birth weight) because boys are heavier
on average than girls, but also suffer from a different mortality risk at a given birth weight.
Empirically, the relationships among variables were first described with the help of a correla-
tion matrix, and then the logistic regression was estimated because the dependent variable only
have values of 0 and 1 (Wooldridge, 2002).
Results
Descriptive statistics
Table 4presents the descriptive statistics of study sample. In terms of the mothers characteristics,
most had Czech citizenship, their average age at the time of birth was almost 27, and most of them
had had their first or second child (more precisely, 85.4%). More than 75% were married, and
more than a half had higher secondary education or even tertiary (university) education.
The childrens characteristics revealed that approximately 51.4% were boys, which is close to
the natural ratio of 105 boys to 100 girls (51.2%). Most of the babies were alive at the time of birth,
and the proportion of multiple births was 3%. The gestation time was close to 40 weeks with a
standard deviation of 2.2, and the birth weight was 3308 g on average. The Index of Property
Prices had zero mean and standard deviation of one, which is caused by the design of the PCA.
Unfortunately, information on fatherseducation was filled in on a voluntary basis and thus
there were many missing values in the dataset. Table 4shows that about 20.1% of fathers reported
that they had no education (compared with 0.4% of mothers), which of course does not reflect the
educational structure of the Czech economy. This issue was caused by the fact that the coding of
the CZSO´s dataset for father´s education did not make any distinction between missing data and
the no educationcategory. There were two options on how to face this potential source of bias.
First, all values with no educationcould have been treated as missing and the regressions esti-
mated. This could have resulted in losing about 20% of the original sample. Second, all values
could have been treated as the no educationcategory and compared with the estimates based
on the reduced sample to see if there were any differences in the findings.
Correlation matrix
As the first step in the empirical approach, a correlation matrix of all variables was created
(Table 5). Most of the variables did not appear to be correlated with the variable of interest (male
child born), except the variables quantifying gestation time and birth weight, which significantly
relate to the child´s sex.
Logistic regression estimates
Table 6shows the regression estimates for the whole sample, and it includes three estimated mod-
els considering the impact of the different independent/control variables. Table 7shows separate
estimates for just live births and stillbirths (all models were estimated with the robust standard
errors).
Also, the level of collinearity among the estimated regressions was inspected with the help of
correlation matrices and the Variance Inflation Factors (VIF) test, and a high level of collinearity
was found between factors reflecting a childs health (gestation time and birth weight) and the
mothers education. Every time these characteristics were included in the regressions, all param-
eters became statistically significant. Thus, models including both mothers conditions and
childs birth characteristics were biased from multicollinearity and could not be used for evalua-
tion of the TWH. The present estimates therefore relied only on parentscharacteristics and did
not suffer from multicollinearity (Wooldridge, 2002). The regressions also included dummies for
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LAU1 districts and year dummies. Finally, the models were estimated with the two operational-
izations of fathers education. No differences in the estimates were observed in the two cases, once
the observations with fathers no education/missing category were excluded, as well as when they
Table 4. Descriptive statistics of study samplea
Variable % Min/Max
Male child 51.4
Child alive 99.7
Mother Czech citizen 98.2
Mothers marital status
Single 19.2
Married 75.5
Divorced 5.1
Widowed 0.3
Mothers education
No education 0.4
Basic education 12.3
Lower secondary education 35.8
Higher secondary education 39.3
Tertiary education 12.2
Fathers education
No education or missing data 20.1
Basic education 4.5
Lower secondary education 31.7
Higher secondary education 24.9
Tertiary education 12.8
Mean (SD) Min/Max
Mothers age 26.7 (5.1) 12/61
Number of previous children 1.7 (0.9) 1/17
Multiple births 1.0 (0.2) 1/4
Gestation time (weeks) 39.3 (2.2) 0/46
Birth weight (g) 3308.2 (561.6) 0/6890
Flat prices (per m2) 14,368.2 (10,622.5) 1914/51,649 (N=712,746)
House prices (per m2) 2302.4 (1793.9) 648/7979 (N=715,107)
Index of Property Prices 0.0 (1.0) 0.0/3.4 (N=708,524)
Air pollution (PM10) 35.8 (19.9) 3.7/205.1 (N=935,014)
aN=1,401,851, unless indicated otherwise.
The Index of Property Prices was extracted from the principal component analysis and represents two variables :
flat price per m2and the house price per m2(all in CZK).
Source: authorscalculations based on the natality dataset from the CZSO; the property prices were also from the
CZSO, and the air pollution dataset was from the CHMI.
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Table 5. Correlation matrix showing bivariate zero-order correlations
Malechild
Mothers
age
Mothers
nationality
Number of
previous
children
Mothers
marital
status
Mothers
education
Fathers
education
Air
pollution
Flat
prices
House
prices
Index
Property
Prices
Gestation
time
Birth
weight
Male child 1.0000
Mothers age 0.0005 1.0000
Mothers
nationality
0.0003 0.0064* 1.0000
Number of
previous
children
0.0012 0.4321* 0.0012 1.0000
Mothers marital
status
0.0003 0.2713* 0.0131* 0.2230* 1.0000
Mothers
education
0.0015 0.2880* 0.0370* 0.1605* 0.1623* 1.0000
Fathers
education
0.0002 0.2392* 0.0181* 0.1089* 0.0361* 0.5672* 1.0000
Air pollution
(PM10)
0.0002 0.0228* 0.0044* 0.0040* 0.0067* 0.0055* 0.0179* 1.0000
Flat prices 0.0004 0.2184* 0.1023* 0.0594* 0.0174* 0.1469* 0.1865* 0.0190* 1.0000
House prices 0.0002 0.1980* 0.1114* 0.0615* 0.0177* 0.1329* 0.1932* 0.0146* 0.9375* 1.0000
Index of
Property Prices
0.0003 0.2117* 0.1091* 0.0617* 0.0181* 0.1420* 0.1931* 0.0020 0.9843* 0.9843* 1.0000
Gestation time 0.0191* 0.0558* 0.0210* 0.0516* 0.0280* 0.0647* 0.0548* 0.0036* 0.0496* 0.0454* 0.0486* 1.0000
Birth weight 0.1227* 0.0406* 0.0166* 0.0063* 0.0764* 0.1150* 0.1158* 0.0016 0.0060* 0.0046* 0.0053* 0.5811* 1.0000
*Correlation significant at the 0.05 level (two-tailed).
Source: authorscalculations based on the natality dataset from the CZSO; property prices were also from the CZSO and the air pollution dataset was from the CHMI.
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Table 6. Logistic regression estimates for the whole sample to test the TriversWillard hypothesis (that high-status mothers
bear more sons)a
Variable Model 1 Model 2 Model 3
Mothers age 1821 years 0.0220 0.0562 0.102
(0.0793) (0.107) (0.313)
Mothers age 2229 years 0.0206 0.00402 0.0977
(0.0442) (0.0508) (0.0892)
Mothers age 30+ years 0.0785 0.0936 0.119
(0.0539) (0.0627) (0.0930)
Mothers nationality: Czech 0.00587 0.00854 0.0339
(0.0129) (0.0150) (0.0241)
Childs birth order 0.00304 0.00434* 0.00104
(0.00193) (0.00221) (0.00355)
Mother married 0.00294 0.00544 0.0149
(0.00483) (0.0103) (0.0112)
Mother divorced 0.00242 0.00725 0.0128
(0.00877) (0.0207) (0.0223)
Mother widowed 0.0156 0.113 0.0411
(0.0318) (0.0996) (0.105)
Mothers education: basic 0.0151 0.0791 0.0668
(0.0275) (0.0630) (0.0718)
Mothers education: lower secondary education 0.0200 0.0871 0.0679
(0.0272) (0.0626) (0.0708)
Mothers education: higher secondary education 0.0164 0.0773 0.0671
(0.0271) (0.0626) (0.0707)
Mothers education: tertiary education 0.00269 0.0637 0.0493
(0.0273) (0.0627) (0.0709)
Fathers education: lower secondary education 0.00501 0.000398
(0.00925) (0.0155)
Fathers education: higher secondary education 0.0119 0.00483
(0.00974) (0.0161)
Fathers education: tertiary education 0.0107 0.00665
(0.0109) (0.0176)
Air pollution (PM10) 0.0000123
(0.000194)
Index of Property Prices 0.00150
(0.0137)
Constant 0.0775* 0.157* 0.177*
(0.0305) (0.0659) (0.0808)
(Continued)
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Table 6. (Continued )
Variable Model 1 Model 2 Model 3
Year dummies Yes Yes Yes
LAU1 districts dummies Yes Yes Yes
Observations 1,401,851 1,120,096 446,411
Pseudo R20.000 0.000 0.000
AIC 1,942,343.5 1,551,967.8 618,597.9
BIC 1,943,583.2 1,553,220.4 619,577.7
Log likelihood 971,069.8 775,878.9 309,209.9
Wald χ295.90 88.28 59.29
aSex of child: boy=1.
Robust SE logistic regression. Standard errors in parentheses: *p<0.05.
Reference categories for dummy variables: mothers age: <18; mothers nationality : non-Czech; mothers marital status: single; mothers
education: no education; fathers education: basic.
Source: authorscalculations based on the natality dataset from the CZSO; property price s were also from the CZSO and the air pollution
dataset was from the CHMI.
Table 7. Logistic regression estimates for the whole sample to test the TriversWillard hypothesis
(that high-status mothers bear more sons)a: pattern reinforced by post-neonatal mortality
Model 4 Model 5
Variable Live births only Stillbirths only
Mothers age 1821 years 0.415
(0.770)
Mothers age 2229 years 0.435
(0.767)
Mothers age 30+ years 0.578
(0.771)
Mothers nationality: Czech 0.00252 0.201
(0.0152) (0.484)
Childs birth order 0.00438* 0.0149
(0.00222) (0.0347)
Mother married 0.00501 0.226
(0.0103) (0.262)
Mother divorced 0.00587 0.960
(0.0207) (0.537)
Mother widowed 0.114
(0.0996)
Mothers education: basic 0.0813 0.145
(0.0631) (0.983)
Mothers education: lower secondary education 0.0895 0.125
(0.0628) (0.977)
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were left in the analysis. However, as it is not known which observations are missing and which
really describe the fathers with no education, the results have been reported without this education
category, even though it decreases the sample size.
Evaluation of the TriversWillard hypothesis for the whole sample
Table 6reports three regressions showing different model specifications depending on a set of
independent variables. Model 1 includes only mothers characteristics, Model 2 adds fathers
education and Model 3 adds pollution and property prices. The obtained estimates do not prove
a statistically significant impact of parentscharacteristics and environmental determinants on the
likelihood of a male being born. The only variable that was found to be statistically significant was
that measuring a childs birth order in Model 2, which might indicate that the more children a
mother has, the less likely it is that the next one will be a boy. Nevertheless, the significance of this
Table 7. (Continued )
Model 4 Model 5
Variable Live births only Stillbirths only
Mothers education: higher secondary education 0.0800 0.248
(0.0627) (0.976)
Mothers education: tertiary education 0.0663 0.216
(0.0628) (0.982)
Fathers education: lower secondary education 0.00479 0.151
(0.00926) (0.157)
Fathers education: higher secondary education 0.0113 0.318
(0.00976) (0.172)
Fathers education: tertiary education 0.0102 0.333
(0.0109) (0.207)
Constant 0.153* 0.0904
(0.0661) (1.262)
Year dummies Yes Yes
LAU1 district dummies Yes Yes
Observations 1,117,154 2942
Pseudo R20.000 0.027
AIC 1,547,891.7 4167.7
BIC 1,549,108.2 4790.4
Log likelihood 773,843.9 1979.9
Wald χ285.69 106.4
aSex of child: boy=1.
Robust SE logistic regression. Standard errors in parentheses: p<0.10; *p<0.05.
Reference categories for dummy variables: mothers age: <18; mothers nationality: non-Czech; mothers marital
status: single; mothers education: no education; fathers education: basic.
Note that mothers age dummies were excluded during the estimation procedure in Model 4. However, when a
control model was estimated where mothers age was included as a continuous variable , the results were not
different from the presented estimates.
Source: authorscalculations based on the natality dataset from the CZSO; the property prices also from the CZSO
and the air pollution dataset was from the CHMI.
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variable was not proven in the remaining models. The presented estimates do not empirically
support the TriversWillard hypothesis.
Evaluation of the TriversWillard hypothesis for live births and stillbirths only
If stillbirths operate in a manner consistent with the TWH, the coefficients in the sample live
birthscan be expected to be reinforced to the side consistent with the TWH. However, Table 7
does not confirm this hypothesis. Besides the childs birth order, there is only one new significant
variable in Model 5 fathers higher secondary education. This finding indicates that, compared
with fathers with basic education, the likelihood of a stillborn boy is lower for fathers who
obtained higher level of secondary education. This nevertheless suggests that stillbirths are pri-
marily random, or at least not affected by the variables this study possessed. In other words, high-
status women have the same likelihood of experiencing a male stillbirth as low-status women.
Interestingly, no empirical support was found for the often-observed pattern of competing forces
(biological and socioeconomical) as noted by Royer (2004). The effect of maternal age on an
infants health comprises a tension between biological and socioeconomic conditions. Younger
mothers tend to be healthier than older mothers, but their socioeconomic status tends to be worse.
Discussion
The study findings suggest that the TriversWillard mechanism is not active in the Czech
Republic. Three possible explanations for these results are identified. First is the biological and
socioeconomic status of the father. Probably one of the most severe problems in this dataset is
the lack of information on the biological and socioeconomic characteristics of fathers.
Information was only available for mothers, and by using only that, the assumption is simply that
the biological and socioeconomic conditions of parents (on aggregate) are correlated. If this as-
sumption does not hold (as is probably the case), then the data used were not adequate to test or
reject the TWH properly.
Secondly, there was insufficient variability of wealth: absolute wealth is unlikely to be a driver of
the TriversWillard mechanism. That said, relative differences do matter. However, imagine a
situation where the relative differences are too small and the TriversWillard mechanism cannot
operate. In other words, to assess the size of the relative differences in the Czech Republic, a proxy
can be used for example, the Gini coefficient. The Czech Republic, with a value of 24.9, was the
fourth most egalitarian country among 31 European countries in the year 2012 (Eurostat, 2012).
In previous years, the situation was similar.
Lastly, the evolutionarily novel environment might be responsible. This hypothesis is related to
the previous one. It is highly possible that various forces of the cultural evolution of human
co-operation (Richerson & Boyd, 2006; Houdek & Novakova, 2016; Houdek et al.,2016) mask
the TWH or the TWH is not culturally compatible with some aspects of modern society.
Guggenheim et al. (2007) provided a comprehensive analysis of nationally representative samples
from 35 countries and found only regional and country-level evidence. Further research is needed
to answer the question of why the TWH mechanisms are active in some countries and inactive in
others.
In conclusion, this study investigated the effect of the biological and socioeconomic status of
mothers and environmental characteristics (air pollution and property prices) on the sex of chil-
dren born in the Czech Republic. No evidence for the TriversWillard hypothesis was found.
Three causes of the insignificant results were identified, but none was testable with the current
dataset. There are many potential topics for future research. An obvious one is to extend the data-
set presented in this article especially for fathersbiological and socioeconomic characteristics.
Secondly, it should be determined why the TWH is active in some areas of the world but inactive
in others. Thirdly, TWH research should be connected to (income) inequality research.
52 Petr Houdek et al.
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The TWH poses several interesting questions (Jayachandran & Kuziemko, 2011; Baker &
Milligan, 2013; Bharadwaj & Lakdawala, 2013; Barcellos et al.,2014). For example, if the TWH
mechanisms work, then there is reason to believe that the effect will be stronger in more unequal
countries (Deaton & Paxson, 1997; Deaton, 2003). If this is the case, then the TWH can contribute
to social mobility, since parents in poor conditions will be more likely to have a girl, and parents in
good conditions will be more likely to have a boy, and the probability that those two will marry
will increase. In contrast, one may pose the question as to whether the TWH contributes to the
selection of abortions. Moreover, when focused on the after-birth TWH, where more resources are
allocated to a boy by parents in good conditions, while parents in poor conditions should invest
more in a girl, other relevant questions can be raised, such as: Are mothers in good conditions with
a girl expected to return to the workforce earlier than those with a boy (or vice versa)? Or, is the
TWH mechanism at least partly responsible for the education gap between men and women?
Lastly, are fathers with a boy more interested in their paternal investments or in having the mother
breastfeed longer? Generally, the most interesting question in the context of the TWH is whether
parents ever maximize their number of offspring, and if yes, under what conditions they do so.
Author ORCIDs. Petr Houdek, 0000-0001-9755-6635, Ondřej Dvouletý, 0000-0001-9151-2033
Funding. This work was supported by the Internal Grant Agency of J. E. PurkyněUniversity and by the Internal Grant Agency
of Faculty of Business Administration, University of Economics in Prague, under No. IP300040. The authors thank the editor
and the reviewers for their thoughtful, constructive and detailed suggestions, which improved the quality of the manuscript.
Conflicts of Interest. The authors declare that the study was conducted in the absence of any commercial or financial rela-
tionships that could be construed as a potential conflict of interest.
Ethical Approval. The authors assert that all procedures contributing to this work comply with the ethical standards of the
relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as
revised in 2008.
References
Abernethy V and Yip R (1990) Parent characteristics and sex differential infant mortality: the case in Tennessee. Human
Biology 62(2), 279290.
Almond D and Edlund L (2007) Trivers-Willard at birth and one year: evidence from US natality data 19832001.
Proceedings of the Royal Society B: Biological Sciences 274(1624), 24912496.
Anderson JL and Crawford CB (1993) Trivers-Willard rules for sex allocation. Human Nature 4(2), 137174.
Baker M and Milligan K (2013) Boy-girl differences in parental time investments: evidence from three countries. National
Bureau of Economic Research Working Paper Series No. 18893, doi: 10.3386/w18893.
Barcellos SH, Carvalho LS and Lleras-Muney A (2014) Child gender and parental investments in India: are boys and girls
treated differently? American Economic Journal: Applied Economics 6(1), 157189.
Bereczkei T and Dunbar RIM (1997) Female-biased reproductive strategies in a Hungarian Gypsy population. Proceedings of
the Royal Society of London Series B: Biological Sciences 264(1378), 1722.
Betzig L and Weber S (1995) Presidents preferred sons. Politics and the Life Sciences 14(1), 6164.
Bharadwaj P and Lakdawala LK (2013) Discrimination begins in the womb: evidence of sex-selective prenatal investments.
Journal of Human Resources 48(1), 71113.
Bobak M, Dejmek J, Solansky I and Sram RJ (2005) Unfavourable birth outcomes of the Roma women in the Czech Republic
and the potential explanations: a population-based study. BMC Public Health 5(1), 106.
Bobak M, Hertzman C, Skodova Z and Marmot M (1999) Socioeconomic status and cardiovascular risk factors in the Czech
Republic. International Journal of Epidemiology 28(1), 4652.
Bobak M, Pikhart H, Pajak A, Kubinova R, Malyutina S, Sebakova H et al. (2006) Depressive symptoms in urban popula-
tion samples in Russia, Poland and the Czech Republic. British Journal of Psychiatry 188(4), 359365.
Buss D (2007) Evolutionary Psychology: The New Science of the Mind. 3rd Edition. Allyn & Bacon, Boston.
Buss DM (1989) Sex differences in human mate preferences: evolutionary hypotheses tested in 37 cultures. Behavioral and
Brain Sciences 12(1), 114.
Cameron EZ and Dalerum F (2009) A Trivers-Willard effect in contemporary humans: male-biased sex ratios among
billionaires. PLoS One 4(1): e4195.
Journal of Biosocial Science 53
https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0021932019000233
Downloaded from https://www.cambridge.org/core. IP address: 89.177.25.28, on 15 Dec 2019 at 08:09:45, subject to the Cambridge Core terms of use, available at
Catalano RA (2003) Sex ratios in the two Germanies: a test of the economic stress hypothesis. Human Reproduction 18(9),
19721975.
ChaconPuignau GC and Jaffe K (1996) Sex ratio at birth deviations in modern Venezuela: the TriversWillard effect. Social
Biology 43(3-4), 257270.
Chase RS (1998) Markets for communist human capital: returns to education and experience in the Czech Republic and
Slovakia. ILR Review 51(3), 401423.
Clutton-Brock TH and Lason GR (1986) Sex ratio variation in mammals. Quarterly Review of Biology 61(3), 339374.
Crawford C (1998) The theory of evolution in the study of human behavior: an introduction and overview. In CrawfordC, and
Krebs DL (eds) Handbook of Evolutionary Psychology: Ideas, Issues, and Applications. Lawrence Erlbaum Associates,
London, pp. 341.
Cronk L (1989) Low socioeconomic status and female-biased parental investment: the Mukogodo example. American
Anthropologist 91(2), 414429.
Deaton A (2003) Health, inequality, and economic development. Journal of Economic Literature 41(1), 113158.
Deaton AS and Paxson CH (1997) The effects of economic and population growth on national saving and inequality.
Demography 34(1), 97114.
Dickemann M (1979) The ecology of mating systems in hypergynous dowry societies. Social Science Information 18(2),
163195.
Dubois P and Rubio-Codina M (2012) Child care provision: semiparametric evidence from a randomized experiment in
Mexico. Annals of Economics and Statistics 105/106, 155184.
Essock-Vitale SM (1984) The reproductive success of wealthy Americans. Ethology and Sociobiology 5(1), 4549.
Eurostat (2012) Gini Coefficient of Equivalised Disposable IncomeEU-SILC survey 2012. URL: http://ec.europa.eu/eurostat/
tgm/table.do?tab=table&language=en&pcode=tessi190 [Date accessed: 2017-02-01]
Fieder M and Huber S (2007) The effects of sex and childlessness on the association between status and reproductive output
in modern society. Evolution and Human Behavior 28(6), 392398.
Folmer V, Soares JCM, Gabriel D and Rocha JBT (2003) A high fat diet inhibits δ-aminolevulinate dehydratase and
increases lipid peroxidation in mice (Mus musculus). Journal of Nutrition 133(7), 21652170.
Freese J and Powell B (1999) Sociobiology, status, and parental investment in sons and daughters: testing the Trivers-Willard
Hypothesis. American Journal of Sociology 104(6), 17041743.
Gibson MA and Mace R (2003) Strong mothers bear more sons in rural Ethiopia. Proceedings of the Royal Society of London
Series B: Biological Sciences 270(Supplement 1), S108S109.
Goodman A and Koupil I (2010) The effect of school performance upon marriage and long-term reproductive success in 10,
000 Swedish males and females born 19151929. Evolution and Human Behavior 31(6), 425435.
Grech V (2018) Maternal educational attainment and sex ratio at birth by race in the United States, 20072015. Journal of
Biosocial Science, doi: 10.1017/s0021932018000123
Guggenheim CB, Davis MF and Figueredo AJ (2007) Sons or daughters: a cross-cultural study of sex ratio biasing and
differential parental investment. Journal of the ArizonaNevada Academy of Science 39(2) 7390.
Harrison D and Rubinfeld DL (1978) The air pollution and property value debate: some empirical evidence. Review of
Economics and Statistics 60(4), 635638.
Hayo B and Seifert W (2003) Subjective economic well-being in Eastern Europe. Journal of Economic Psychology 24(3),
329348.
Helle S, Helama S and Jokela J (2008) Temperature-related birth sex ratio bias in historical Sami: warm years bring more
sons. Biology Letters 4(1), 6062.
Hill J (1984) Prestige and reproductive success in man. Ethology and Sociobiology 5(2), 7795.
Higashi M and Yamamura N (1994) Resolution of evolutionary conflict: a general theory and its applications. Researches on
Population Ecology 36(1), 1522.
Hopcroft RL (2005) Parental status and differential investment in sons and daughters:Trivers-Willard revisited. Social Forces
83(3), 11111136.
Hopcroft RL (2006) Sex, status, and reproductive success in the contemporary United States. Evolution and Human Behavior
27(2), 104120.
Hopcroft RL (2015) Sex differences in the relationship between status and number of offspring in the contemporary U.S.
Evolution and Human Behavior 36(2), 146151.
Houdek P and Novakova J (2016) Frozen cultural plasticity. Behavioral and Brain Sciences 39, doi: 10.1017/
s0140525x15000151.
Houdek P, Novakova J and Stastny D (2016) Ultrasociality: when institutions make a difference. Behavioral and Brain
Sciences 39, doi: 10.1017/s0140525x15001089
Jayachandran S and Kuziemko I (2011) Why do mothers breastfeed girls less than boys? Evidence and implications for child
health in India. Quarterly Journal of Economics 126(3), 14851538.
54 Petr Houdek et al.
https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0021932019000233
Downloaded from https://www.cambridge.org/core. IP address: 89.177.25.28, on 15 Dec 2019 at 08:09:45, subject to the Cambridge Core terms of use, available at
Jha P, Kumar R, Vasa P, Dhingra N, Thiruchelvam D and Moineddin R (2006) Low male-to-female sex ratio of children
born in India: national survey of 1.1 million households. The Lancet 367(9506), 211218.
Kanazawa S (2003) Can evolutionary psychology explain reproductive behavior in the contemporary United States?
Sociological Quarterly 44(2), 291302.
Kanazawa S and Apari P (2009) Sociosexually unrestricted parents have more sons: a further application of the generalized
TriversWillard hypothesis (gTWH). Annals of Human Biology 36(3), 320330.
Kaňková Š,Šulc J, Nouzová K, Fajfrlík K, Frynta D and Flegr J (2007) Women infected with parasite Toxoplasma have
more sons. Naturwissenschaften 94(2), 122127.
Keller MC, Nesse RM and Hofferth S (2001) The TriversWillard hypothesis of parental investment: no effect in the con-
temporary United States. Evolution and Human Behavior 22(5), 343360.
Kolk M and Schnettler S (2016) Socioeconomic status and sex ratios at birth in Sweden: no evidence for a TriversWillard
effect for a wide range of status indicators. American Journal of Human Biology 28(1), 6773.
Koziel S and Ulijaszek SJ (2001) Waiting for Trivers and Willard: do the rich really favor sons? American Journal of Physical
Anthropology 115(1), 7179.
Lappegård T and Rønsen M (2013) Socioeconomic differences in multipartner fertility among Norwegian men. Demography
50(3), 11351153.
Luo L, Ding R, Gao X, Sun J and Zhao W (2017) Socioeconomic status influences sex ratios in a Chinese rural population.
PeerJ 5, e3546.
Mace R (1996) Biased parental investment and reproductive success in Gabbra pastoralists. Behavioral Ecology and
Sociobiology 38(2), 7581.
Mathews F, Johnson PJ and Neil A (2008) You are what your mother eats: evidence for maternal preconception diet influ-
encing foetal sex in humans. Proceedings of the Royal Society Series B: Biological Sciences 275(1643), 16611668.
Morita M, Go T, Hirabayashi K and Heike T (2017) Parental condition and infant sex at birth in the Japan environment and
childrens study: a test of the TriversWillard Hypothesis. Letters on Evolutionary Behavioral Science 8(2), 4044.
Murphy M, Grundy E and Kalogirou S (2007) The increase in marital status differences in mortality up to the oldest age in
seven European countries, 199099. Population Studies 61(3), 287298.
Nettle D and Pollet TV (2008) Natural selection on male wealth in humans. American Naturalist 172(5), 658666. doi:
10.1086/591690
Nielsen F (1994) Sociobiology and Sociology. Annual Review of Sociology 20, 267303.
Nisén J, Martikainen P, Myrskylä M and Silventoinen K (2018) Education, other socioeconomic characteristics across the
life course, and fertility among Finnish men. European Journal of Population 34(3), 337366.
Norberg K (2004) Partnership status and the human sex ratio at birth. Proceedings of the Royal Society of London Series B:
Biological Sciences 271(1555), 24032410.
Oreopoulos P, Page M and Stevens AH (2006) The intergenerational effects of compulsory schooling. Journal of Labor
Economics 24(4), 729760.
Pérusse D (1993) Cultural and reproductive success in industrial societies: testing the relationship at the proximate and
ultimate levels. Behavioral and Brain Sciences 16(2), 267283.
Peterka M, Peterková R and Likovský Z (2004) Chernobyl: prenatal loss of four hundred male fetuses in the Czech Republic.
Reproductive Toxicology 18(1), 7579.
Pikhart H, Drbohlav D, and Dzurova D (2010) The self-reported health of legal and illegal/irregular immigrants in the
Czech Republic. International Journal of Public Health 55(5), 401411.
Polinsky AM and Shavell S (1975) The air pollution and property value debate. Review of Economics and Statistics 57(1),
100104.
Richerson PJ and Boyd R (2006) Not by Genes Alone, How Culture Transformed Human Evolution. University of Chicago
Press, Chicago.
Royer H (2004) What All Women (and Some Men) Want to Know: Does Maternal Age Affect Infant Health? URL: http://eml.
berkeley.edu/~cle/wp/wp68.pdf (accessed 1 January 2017).
Schnettler S (2013) Revisiting a sample of U.S. billionaires: how sample selection and timing of maternal condition influence
findings on the Trivers-Willard effect. PLoS One 8(2), e57446.
Sewell WH and Shah VP (1968) Parentseducation and childrens educational aspirations and achievements. American
Sociological Review 33(2), 191209.
Smith VK and Huang JC (1995) Can markets value air quality? A meta-analysis of hedonic property value models. Journal of
Political Economy 103(1), 209227.
Trivers RL and Willard DE (1973) Natural selection of parental ability to vary the sex ratio of offspring. Science 179(4068),
9092.
Valente C (2015) Civil conflict, gender-specific fetal loss, and selection: a new test of the TriversWillard hypothesis. Journal
of Health Economics 39,3150.
Journal of Biosocial Science 55
https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0021932019000233
Downloaded from https://www.cambridge.org/core. IP address: 89.177.25.28, on 15 Dec 2019 at 08:09:45, subject to the Cambridge Core terms of use, available at
Veller C, Haig D and Nowak MA (2016) The Trivers-Willard hypothesis: sex ratio or investment? Proceedings of the Royal
Society Series B: Biological Sciences 283(1830), doi: 10.1098/rspb.2016.0126.
Voland E, Siegelkow E and Engel C (1991) Cost/benefit oriented parental investment by high status families. Ethology and
Sociobiology 12(2), 105118.
Wooldridge JM (2002) Econometric Analysis of Cross Section and Panel Data. MIT Press, Cambridge, MA.
Zaldívar ME, Lizarralde R and Beckerman S (1991) Unbiased sex ratios among the Barí: an evolutionary interpretation.
Human Ecology 19(4), 469498.
Cite this article: Houdek P, Dvouletý O, and Pažitka M (2020). Biological, environmental and socioeconomic determinants of
the human birth sex ratio in the Czech Republic. Journal of Biosocial Science 52,3756. https://doi.org/10.1017/
S0021932019000233
56 Petr Houdek et al.
https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0021932019000233
Downloaded from https://www.cambridge.org/core. IP address: 89.177.25.28, on 15 Dec 2019 at 08:09:45, subject to the Cambridge Core terms of use, available at
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