You Are What Your Mother Eats: Evidence for Maternal Preconception Diet Influencing Foetal Sex in Humans

Abstract

Facultative adjustment of sex ratios by mothers occurs in some animals, and has been linked to resource availability. In mammals, the search for consistent patterns is complicated by variations in mating systems, social hierarchies and litter sizes. Humans have low fecundity, high maternal investment and a potentially high differential between the numbers of offspring produced by sons and daughters: these conditions should favour the evolution of facultative sex ratio variation. Yet little is known of natural mechanisms of sex allocation in humans. Here, using data from 740 British women who were unaware of their foetus's gender, we show that foetal sex is associated with maternal diet at conception. 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 maternal diet. Our results support hypotheses predicting investment in costly male offspring when resources are plentiful. Dietary changes may therefore explain the falling proportion of male births in industrialized countries. The results are relevant to the current debate about the artificial selection of offspring sex in fertility treatment and commercial 'gender clinics'.

Full text

You are what your mother eats:
evidence for maternal preconception diet
influencing foetal sex in humans
Fiona Mathews
1,
*, Paul J. Johnson
2
and Andrew Neil
3
1
Hatherly Laboratories, School of Biosciences, University of Exeter, Prince of Wales Road, Exeter EX4 4PS, UK
2
Wildlife Conservation Research Unit, Department of Zoology, University of Oxford,
Tubney House, Tubney, Oxon OX13 5QL, UK
3
Division of Public Health and Primary Health Care, Institute of Health Sciences,
University of Oxford, PO Box 777, Oxford OX3 7LF, UK
Facultative adjustment of sex ratios by mothers occurs in some animals, and has been linked to resource
availability. In mammals, the search for consistent patterns is complicated by variations in mating systems,
social hierarchies and litter sizes. Humans have low fecundity, high maternal investment and a potentially
high differential between the numbers of offspring produced by sons and daughters: these conditions
should favour the evolution of facultative sex ratio variation. Yet little is known of natural mechanisms of
sex allocation in humans. Here, using data from 740 British women who were unaware of their foetus’s
gender, we show that foetal sex is associated with maternal diet at conception. 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
maternal diet. Our results support hypotheses predicting investment in costly male offspring when
resources are plentiful. Dietary changes may therefore explain the falling proportion of male births in
industrialized countries. The results are relevant to the current debate about the artificial selection of
offspring sex in fertility treatment and commercial ‘gender clinics’.
Keywords: sex ratio; nutrition; diet; mammal; fertility treatment; Trivers–Willard hypothesis
1. INTRODUCTION
The ability of parents to influence their offspring’s sex
should be favoured by natural selection (Trivers & Willard
1973;Myers 1978;Clutton-Brock 1991). Perhaps the best-
known evolutionary theory of sex ratio variation, the Trivers
and Willard hypothesis (1973), proposes that if increased
parental condition differentially enhances the reproductive
success of sons, then parents in good condition should
favour male offspring. Competing hypotheses have also
been proposed to explain differential sex ratio allocations in
relation to resource availability and local conditions.
Whether such models can be expected to apply to
modern-day humans might reasonably be disputed: not
only do we have complex social structures that govern
mating patterns but also resources are more readily
available to us than to most wild mammals. Yet the
technological age represents only a tiny fraction of the time
scale over which reproductive strategies have evolved:
phylogenetic inertia is therefore to be expected. In
industrialized, as well as traditional societies, tall men
and those of higher social status have greater reproductive
success (Pawlowski et al.2000;Fielder et al. 2005;
Hopcroft 2006). Similarly, men exhibit more risk-taking
behaviour than do women, particularly in young adult-
hood when sexual competitiveness is greatest (Daly &
Wilson 1985;Wilson & Daly 1997;Kruger & Nesse
2007); men have strong preferences for physical traits
associated with fertility (Buss et al. 1990); and they also
have a much greater desire for multiple partners and
short-term relationships than do women (Schmitt et al.
2001;Buss 2006). All of these traits are likely to have
evolved because they contributed to reproductive success
in an ancestral age. Human reproductive biology would be
expected to favour the evolution of parental control over
offspring sex, since there is low fecundity and high
maternal investment, and sons are more costly to produce
in both the short and long terms than daughters
(Clutton-Brock & Iason 1986;Frank 1987;Hrdy 1999;
Rickard et al. 2007; for further discussion of evolutionary
context, see electronic supplementary material).
Weak relationships between sex ratios and the nutri-
tional resources of mothers in late pregnancy and post-
natally have been reported (Gibson & Mace 2003;Tamimi
et al. 2003) but are controversial (Stein et al. 2003). Even if
real, they do not imply any maternal command over foetal
sex. Differential provisioning in late pregnancy or after
delivery may reflect either manipulation of maternal
metabolism and behaviour by the offspring, for example,
through the action of foetal testosterone, or alterations in
maternal behaviour due to knowledge of foetal sex (Shay
2003;Stein et al. 2003). The mechanism for controlling
the sex ratio at birth in mammals is likely to be the
differential conception and maintenance of male and
female embryos ( McMillen 1979). If there is maternal
Proc. R. Soc. B (2008) 275, 1661–1668
doi:10.1098/rspb.2008.0105
Published online 22 April 2008
Electronic supplementary material is available at http://dx.doi.org/10.
1098/rspb.2008.0105 or via http://journals.royalsociety.org.
*Author for correspondence (f.mathews@exeter.ac.uk).
Received 23 January 2008
Accepted 1 April 2008
1661 This journal is q2008 The Royal Society

manipulation of sex ratios in response to resource
availability, then diet before and shortly after conception
should be correlated with offspring sex: in non-human
mammals, high resource availability around conception is
consistently linked with male-biased sex ratios, whereas
indices from later pregnancy or after birth produce contra-
dictory results (Cameron 2004). We explored whether high
resource availability around conception was linked with
differential investment in male offspring in a large cohort
of British women who were unaware of the sex of their
foetuses. Determining whether infant sex is ‘naturally’
influenced by maternal conditions is of direct relevance to
the current debate about the artificial selection of an
embryo’s sex during fertility treatment and in commercial
‘gender clinics’, and may offer insights into the falling
proportion of male births in developed countries ( James
2000;Davis et al. 2007).
2. MATERIAL AND METHODS
(a)Study design and dietary assessment
Nulliparous white women with no medical problems
(including obesity) were recruited from a district general
hospital in the south of England at their first antenatal clinic
visit early in pregnancy (approx. 14 weeks gestation).
Regardless of their medical history, all pregnant women in
the region were referred to these clinics by their family
physician; stratified random sampling was used to ensure that
the proportion of smokers in the cohort represented that in
the local population. Full details of the study methods have
been reported elsewhere ( Mathews et al. 1999). A total
of 740 women with normal singleton pregnancies kept a
prospective food diar y of their diet in early pregnancy
(hereafter referred to as ‘early pregnancy’ data); of these,
721 gave a retrospective report of their usual diet in the year
prior to conception (‘preconception’ data) and 661 reported
their usual diet during pregnancy at approximately 28 weeks
gestation (‘later pregnancy’ data). Seventeen additional
women provided dietary data, but were excluded from the
analysis because they moved out of the district before giving
birth. The women were ‘blind’ to the sex of their offspring at
the time of completing their questionnaires: owing to hospital
policy, offspring sex was not disclosed at ultrasound scans.
The only mothers to know the sex of their infant during the
study were those who had amniocentesis (nZ25) or had
abnormality scans (nZ27): even here, the information was
available only later in gestation, after the preconception and
early pregnancy data had been obtained. All women provided
written informed consent and the study was approved by the
Research Ethics Committees of Portsmouth Hospitals and of
the University of Oxford Medical School.
Food frequency questionnaires are the most widely used
method of dietary assessment in epidemiological studies
(including previous work on maternal provisioning; Tamimi
et al. 2003), and substantial effort has been put into assessing
their repeatability and validity ( Willett 1990). The time scale
for recall was relatively short (a matter of months) compared
with many studies, for example, those evaluating risks of
cancer or cardiovascular disease, which attempt to evaluate
dietary exposures experienced years ago. Those adopted for
this work have been used in large epidemiological studies in
Europe are based on the questionnaire used in the US Nurses
Health Study and have been validated (with comparable
intervals between food consumption and recall) against a
7-day food diary (Bingham et al. 1997). Food diaries, as used
in this project, are considered a ‘gold standard’ method of
dietary assessment ( Willett 1990). Further details of the
methods used and their reliability are given in the electronic
supplementary material.
(b)Statistical analysis
We explored the differences between proportions using
c
2
-tests, and between means using Z-tests. Food and nutrient
intakes were measured on interval scales and were always
analysed as continuous variables. The groupings given in
figures for illustrative purposes are derived from splitting as
closely as possible to the tertiles; the unequal group size for
breakfast cereals is due to the large numbers of women who
habitually consumed cereal daily. Because intakes of different
nutrients are correlated, we used principal components
analysis (PCA; SAS FACTOR procedure) to summarize
dietary patterns: the computed factor scores were used in
further analyses. This method has been shown elsewhere to
be a good method of summarizing dietary patterns, and is
preferable to other methods such as cluster analysis, which
result in the formation of categorical rather than continuous
variables (Crozier et al. 2006). The joint effects of exposures
were investigated using logistic regression (SAS GENMOD
procedure). For the analyses of individual nutrient intakes
and foetal sex, the ranks of intakes were used for data derived
from the food frequency questionnaires. This was owing to
the difficulties in assessing absolute intakes using this method
and the technique reduces the leverage of outlying values. All
tests of significance were two-tailed. Given the multiplicity of
testing, we interpreted p-values conservatively for individual
nutrient items.
In the simple multivariate models (SAS GLM type 1
models; used because the predictors were correlated), the
coefficient for energy represents energy independent of
the other nutrients in the model. For example, for a model
including fat and energy, the term for energy represents
energy from sources other than fat, i.e. carbohydrate, protein
and alcohol. Alternatively, the residual method ( Willett
1990) can be used to adjust specific nutrients for energy
intakes. The relationships between the total energy intake
and outcome and the nutrient density and outcome can then
be analysed distinctly. Concordant results were obtained
with our data whichever method of analysis was used.
3. RESULTS
Nutritional patterns were summarized separately for
nutritional data from three time periods: usual intake
before conception (preconception); intake at approxi-
mately 16 weeks gestation (early pregnancy); and usual
intake between 16 and 28 weeks gestation (later
pregnancy). For each period, two derived factors
encapsulated a high proportion of the variability in the
data and can therefore be considered good summary
statistics (table 1). The factor-loading patterns in all
three time periods (correlations between the input
variables and the scores) indicated that high scores for
factor 1 described diets high in many nutrients including
protein, fat, vitamin C, folate and a range of minerals;
while high scores for factor 2, described diets high in the
vitamin A components and vitamin B
12
(table 1). The
factor scores for the three time periods were correlated
1662 F. Mathews et al. Preconceptional diet predicts foetal sex
Proc. R. Soc. B (2008)

(rZ0.2, p!0.001), indicating some consistency in
individual women’s dietary intake over time.
Given the correlations between the dietary measures
across time, we first tested whether dietary patterns overall
were linked to offspring sex by using the factor scores from
the different times as multivariate responses (MANOVA)
and sex as a predictor. Factor 1 scores were influential
(MANOVA F
3,620
Z2.6, pZ0.051), but no models using
factor 2 were significant. Further, a profile analysis, using
the differences between the factor 1 scores in different time
periods, indicated that the difference varied significantly
across time (non-parallelism test: F
3,620
Z3.64, pZ0.03).
Inspection of the within-time period factor score pattern
showed that the diet difference was greatest for the
preconception diet, whereas there was not a significant
difference for either early or later pregnancy (Wald
c
2
%0.22, pR0.47). Factor 1 score was a significant
predictor of foetal sex preconception (Wald c
2
Z6.74,
pZ0.00095), with male offspring being more frequent
among women with high scores. Factor 2 was not
associated with foetal sex (Wald c
2
Z0.22, pZ0.64).
Having established the existence of relationships
between preconceptional nutritional patterns and foetal
sex, we went on to examine individual nutrients in more
detail. As would be predicted from the factor pattern,
factor 1 scores were highly correlated with energy intake
(rZ0.87, p!0.001): in logistic regression, energy intake
gave a similar model fit to factor 1 (Wald c
2
Z4.87,
pZ0.023). In support of the prediction that mothers with
more resources before conception would have more sons,
mothers of males had higher intakes of macronutrients and
a range of micronutrients at this time than did mothers of
females, when individual nutrients were used in the
analyses (table 2). The proportions of male offspring born
to women in different thirds of energy intake are illustrated
in figure 1: the odds ratio for having a male infant was 1.5
for women in the highest third of energy intake compared
with those in the lowest third (95% CI 1.1, 2.2).
The relationships between nutritional exposures and
outcome variables may be analysed either in terms of
absolute intakes, or in relation to total energy intake
(intakes of many nutrients are positively correlated with
total energy intake, and some, e.g. the macronutrients, are
metabolized in proportion to total energy consumption;
Willett 1990). After adjusting for energy in simple multi-
variate models, no other nutrient was independently
associated with infant sex. Thus, an increased prevalence
of male foetuses was associated with high maternal nutrient
intakes, but not with high-nutrient density. Although the
associations with energy are compatible with predictions
from evolutionary approaches to sex ratio variation, it is
possible that the causal mechanism involves other nutri-
ents. In forward stepwise regression, potassium intake was
selected as the predictor of offspring sex ( pZ0.004) and no
other variable was selected for inclusion in the model after
adjusting for the effect of potassium.
No socio-demographic or anthropometric charac-
teristic was a significant predictor of foetal sex (table 3).
Nor was smoking status or caffeine intake prior to, or
during, pregnancy (table 3). We also tested whether
offspring sex was a nonlinear function of body mass index
(BMI) to allow for the possibility that an optimum
‘condition’ exists on this continuum. There was no
evidence for this (a quadratic function of BMI was not a
significant predictor of offspring sex).
We then examined whether there is differential
postconception investment in the foetus according to
sex, possibly induced by the foetus itself. Nutrient intakes
in early pregnancy, but beyond the period when most
foetal losses occur—approximately 16 weeks gestation—
were not associated with foetal sex (table 2). The same was
true for later pregnancy (see electronic supplementary
material). Thus, the additional energetic cost of producing
a male infant, males being approximately 100 g heavier
than females, does not appear to be met via detectable
differences in maternal nutritional intake.
Table 1. PCA factor loadings for daily dietary intakes, and proportion of variability in data encapsulated by the factors at each
time point. (Notes. Because sodium is difficult to measure accurately with any dietary method due to variation between brands of
processed food, and addition of table salt to food and cooking, it was not included in the PCA. Italics indicate PCA factor
loadings with absolute values R0.70 which by convention indicate that the variables are excellent components of the factors
(Comfrey & Lee 1992).)
preconception early pregnancy later pregnancy
factor 1 factor 2 factor 1 factor 2 factor 1 factor 2
fat 0.73 0.25 0.84 0.07 0.90 0.11
protein 0.88 0.26 0.74 0.50 0.79 0.48
carbohydrate 0.60 K0.08 0.03 0.76 0.13 0.76
vitamin C 0.85 0.18 0.61 0.42 0.81 0.33
vitamin E 0.70 0.18 0.41 0.10 0.60 0.39
b-carotene 0.50 K0.13 0 0.59 0.10 0.67
retinol 0.01 0.91 0.67 K0.13 0.83 0.04
vitamin B
12
0.25 0.82 0.62 0.24 0.18 0.57
folate 0.82 0.11 0.36 0.80 0.47 0.77
iron 0.84 0.28 0.50 0.60 0.61 0.62
zinc 0.86 0.29 0.67 0.53 0.79 0.44
calcium 0.74 0.19 0.67 0.41 0.81 0.24
potassium 0.89 0.13 0.56 0.70 0.71 0.58
proportion of variability
encapsulated by factor (%)
55.40 11.00 48.80 10.50 59.60 10.20
Preconceptional diet predicts foetal sex F. Mathews et al. 1663
Proc. R. Soc. B (2008)

Table 2. Daily dietary intakes
a
by foetal sex.
preconception early pregnancy
median (lower, upper quartile) c
2
p-value median (lower, upper quartile) c
2
p-value
male foetus (nZ360) female foetus (nZ361) male foetus (nZ372) female foetus (nZ368)
energy (kcal) 2413 (1986, 2912) 2283 (1781, 2720) 4.80 0.029 2033 (1763, 2283) 2061 (1730, 2326) 1.06 0.304
total fat (g) 87.0 (70.7, 112.0) 85.5 (67.3, 106.2) 2.20 0.138 84.2 (69.6, 98.0) 84.8 (70.4, 101.3) 0.16 0.692
% energy from fat 33.5 (30.6, 37.0) 34.2 (31.0, 37.4) 0.59 0.441 37.6 (34.5, 40.7) 37.9 (34.7, 41.2) 1.43 0.232
protein (g) 95.9 (77.3, 113.9) 91.3 (73.7, 109.8) 7.25 0.007 71.7 (62.0, 84.2) 74.6 (61.8, 85.2) 0.68 0.409
% energy from protein 15.9 (14.3, 17.7) 15.7 (14.1, 17.6) 0.49 0.484 14.5 (12.9, 16.1) 14.6 (13.2, 16.0) 0.19 0.663
carbohydrate (g) 342 (281, 406) 323 (259, 384) 4.46 0.035 257.3 (220.5, 292.4) 255.2 (214.3, 293.1) 2.43 0.119
% energy from carbohydrate 52.8 (49.0, 56.1) 52.4 (49.0, 56.1) 0.08 0.784 47.4 (44.7, 50.5) 47.2 (43.6, 50.3) 1.51 0.219
vitamin C (mg) 111 (78, 72) 103 (72, 140) 2.29 0.130 76.5 (49.0, 109.8) 71.0 (46.0, 107.0) 0.72 0.397
vitamin E (mg) 8.0 (6.3, 10.4) 7.7 (6.0, 9.6) 2.75 0.097 8.0 (5.8, 11.3) 8.2 (6.0, 11.2) 0.03 0.872
b-carotene (mg) 1658 (998, 2564) 1479 (999, 2560) 0.00 0.975 897 (449, 1542) 869 (481, 1345) 0.83 0.360
retinol (mg) 469 (321, 888) 433 (302, 832) 0.14 0.708 406 (311, 503) 417 (317, 532) 0.62 0.432
vitamin B
12
(mg) 7.2 (4.8, 10.9) 6.8 (4.5, 10.5) 0.02 0.875 3.7 (2.8, 4.7) 3.6 (2.8, 4.6) 0.02 0.879
folate (mg) 396 (321, 479) 367 (293, 460) 3.76 0.052 240 (189, 279) 236 (192, 292) 0.96 0.327
iron (mg) 14.6 (11.8, 18.3) 13.5 (11.1, 16.8) 4.14 0.042 10.2 (8.4, 12.2) 10.0 (8.7, 11.9) 1.04 0.308
zinc (mg) 12.0 (9.5, 14.9) 11.3 (9.1, 13.9) 4.45 0.035 8.0 (6.5, 9.5) 8.1 (6.7, 9.6) 0.02 0.880
sodium (mg)
b
4267 (3445, 5105) 3944 (3226, 4807) 8.73 0.003 2976 (2534, 3553) 2971 (2522, 3547) 1.57 0.209
calcium (mg) 1246 (970, 1572) 1154 (905, 1437) 7.41 0.006 896 (725, 1103) 903 (721, 1129) 0.52 0.437
potassium (mg) 4630 (3952, 5492) 4342 (3646, 5190) 3.97 0.046 2952 (2516, 3390) 2967 (2462, 3478) 0.76 0.382
a
Diet before conception was assessed using a food frequency questionnaire, and in early pregnancy using a 7-day food diary. The absolute values for intakes are therefore not directly comparable due to the
methodological differences, but good agreement is obtained for the ranking of subjects (see electronic supplementary material).
b
Sodium intake is difficult to measure accurately with any dietary method due to variation between brands of processed food and addition of table salt to food and cooking.
1664 F. Mathews et al. Preconceptional diet predicts foetal sex
Proc. R. Soc. B (2008)

We went on to test whether particular foods were
associated with infant sex. Data of the 133 food items from
our food frequency questionnaire were analysed, and we
also performed additional analyses using broader food
groups. Prior to pregnancy, breakfast cereal, but no other
item, was strongly associated with infant sex (Wald
c
2
Z8.2, pZ0.004). Women producing male infants
consumed more breakfast cereal than those with female
infants (figure 1). The odds ratio for a male infant was
1.87 (95% CI 1.31, 2.65) for women who consumed at
least one bowl of breakfast cereal daily compared with
those who ate less than or equal to one bowlful per week.
No other foods were significantly associated with infant
sex (given the multiplicity of testing, p%0.01 was
considered significant), and was also true for the broader
food categories. During later pregnancy, breakfast cereal
consumption remained considerably higher among
mothers of males (Wald c
2
Z4.0, pZ0.04). There were
no differences for any other foods. Our data did not permit
us to examine the consumption of breakfast per se, but
breakfast cereal is the main food eaten for breakfast in the
UK and is only rarely consumed at other times of day.
4. DISCUSSION
We have provided evidence of facultative selection of
offspring sex by individual women according to environ-
mental cues experienced around conception. The results
fit into evolutionary frameworks developed with other
species where, as in humans, males have greater potential
lifetime reproductive success and are also more costly to
produce (Trivers & Willard 1973;Myers 1978;Clutton-
Brock 1991; see also electronic supplementary material).
The overall sex ratio in our population was close to
50 : 50, but individual mothers had a greater chance of
bearing male offspring if their nutrient intake was high
prior to conception. The consumption of breakfast cereals
was also strongly associated with having a male infant. The
effect sizes in our study are striking even though our
cohort was relatively well nourished. Parity is the main
factor consistently associated with sex ratio in humans
(Novitski & Kimball 1958;Rostron & James 1977). The
difference in sex ratio between women in the highest and
lowest tertiles of energy intake is approximately 10 times
more than that reported between women with first and
third births, and is comparable with differences found in
classic experimental manipulations of maternal nutrition
in animals (e.g. Sachdeva et al. 1973;Labov et al. 1986).
The lack of dietary differences between mothers of sons
and daughters during pregnancy itself is consistent with
well-established observations that the very slow growth rate
of the human foetus generates a lower incremental
nutritional stress than in any other mammal: additional
energy requirements, for example, are met via metabolic
and behavioural energy-sparing mechanisms rather than
increased intakes (Prentice et al.1995). The marginally
significant greater energy intake among pregnant mothers of
males reported by one previous study ( Ta m i m i et al.2003)
may have been due to maternal knowledge of foetal sex, or
because preconceptional dietary patterns were carried over
into pregnancy to a greater extent than in our cohort.
Although strong associations were seen for energy
consumption, it is possible that any of the other correlated
nutrients may be important in the aetiological pathway.
There is tremendous interest in popular literature and the
media about a possible link between dietary mineral intake
(particularly calcium, sodium and potassium) and off-
spring sex (e.g. Chesterman-Phillips 2005). This is despite
there being only scant support for the mechanism
operating in humans (Papa et al. 1983) or animals (Cluzan
et al. 1965;Bird & Contreras 1986). Doubt has also been
cast on the mechanism of altered blood and vaginal pH
linking offspring sex with mineral intake (Roche & Lee
2007). Although all of these nutrients did show highly
significant associations with foetal sex in our study, we are
cautious in the interpretation of the data until further
research is available: the associations for sodium and
potassium were in the predicted direction, but the
association for calcium was not.
In general, the mechanisms of sex allocation in
mammals are not well understood; however, a pathway
has been proposed that could explain our associations of
foetal sex with energy intake and breakfast cereal
consumption around conception. In vitro,glucose
enhances the growth and development of male con-
ceptuses while inhibiting that of females (Larson et al.
2001). Skipping breakfast extends the normal period of
nocturnal fasting, depresses circulating glucose levels
and may be interpreted by the body as indicative of poor
environmental conditions. A range of sequelae has
previously been reported, including elevated risks of
chronic diseases, such as non-insulin-dependent Diabetes
mellitus, and abnormal blood glucose levels (Lecomte
et al.2002).
Various non-nutritional factors have been associated
with sex allocation in humans, and these may act in
concert with nutritional factors or may be confounded
with them. These factors include environmental tempera-
ture (Helle et al. 2008); variations in hormonal profiles in
women at around the time of conception according to
their status and ‘stress’ levels (James 1990;Grant 2007);
and the timing of insemination relative to ovulation (which
is closely correlated with coital frequency since fertili-
zation early in the cycle is more likely if there is frequent
insemination; James 1971;Guerrero 1974;Harlap 1979).
0
10
20
30
40
50
60
70
energy cereal
intakes
percentage of males
240 240 241 216 205 300
Figure 1. Relationship between usual maternal intakes of
energy and breakfast cereal prior to pregnancy, split at
approximate tertiles, and the proportion of male infants
(Cs.e.m.). Comparisons of the numbers of males and females
across the groups were made using c
2
-test for linear
association. The numbers above each bar indicate the
numbers of women in each category of intake. For energy,
the bars represent the low (open), moderate (filled) and
high ( hatched) thirds of intake; c
2
Z5.83, pZ0.016. For
breakfast cereal, the bars represent less than one bowl per
week (open), two to six bowls per week (filled) and one or
more bowl per day (hatched); c
2
Z13.96, p!0.001.
Preconceptional diet predicts foetal sex F. Mathews et al. 1665
Proc. R. Soc. B (2008)

Attention has focused particularly on the latter, with
conceptions earlier in the oestrus cycle apparently being
more likely to be male, and there being greater
maintenance of male blastocysts if they are in synchrony
with uterine ripeness (Krackow 1995). However, more
recent clinical studies dispute these associations ( Wilcox
et al. 1995;Reubinoff & Schenker 1996). It remains to be
seen whether women with greater nutritional intakes, and
higher frequency of breakfast cereal consumption, prior to
conception are also those with more active sex lives.
All methods of dietary assessment are prone to some
degree of error. However, it is highly unlikely that these
errors (formally, the within-subject differences between
true and measured intakes) would produce spurious
associations. Rather they will attenuate the observed
associations between the outcome and exposure measures,
depressing odds ratios towards zero: the generation of
artefactual relationships would generally require differ-
ential misreporting of diet by women carrying male rather
than female foetuses ( Willett 1990;Clayton & Gill 1991;
see electronic supplementary material). Given that the
women in this study did not know the sex of their foetus,
the latter possibility is unlikely.
Since all of the women in the study were white and
nulliparous, we avoided the potentially confounding
effects of race and birth order, both of which are associated
with sex ratio ( Novitski & Kimball 1958;Rostron & James
1977). Maternal age has not generally been associated
with sex ratio independent of parity ( Teitelbaum &
Mantel 1971;Rostron & James 1977), and accordingly
we found no association between any maternal age and sex
ratio. Weight and condition measures are poor predictors
of offspring sex in non-human mammals (Cameron 2004;
Sheldon & West 2004), and we found no associations in
our study. The measures are relatively weak indicators of
resource availability, reflecting a combination of basal
metabolic rate (a variable practically impossible to
measure in large-scale studies), frame size and long-term
levels of physical activity and dietary intake. Of these
factors, variation in physical activity appears to be a major
determinant of differences between individuals in energy
expenditure, and is likely to explain why obesity is only
poorly correlated with energy intake in epidemiological
studies (Willett 1990). Although BMI (weight/height
2
)is
widely used as an index of body fat, it is error prone due to
the large variation in lean body mass among people of the
same height. Even in Ethiopia, a country with marked
regional variations in the prevalence of maternal under-
nutrition, the associations between such indices and infant
sex are questionable (Shay 2003;Stein et al. 2003): from
an evolutionary perspective, there is no reason to assume
that body fat indices—reflecting historical imbalances
between energy intake and expenditure—should be a good
marker of resources currently available. For many
nutrients, circulating levels are highly dependent on recent
intakes and not on stored fat reserves. This is the case, for
example, with water-soluble vitamins, and circulating
glucose levels are influenced by the glycaemic index of
foods. The recent finding that change in condition indices
is more predictive of sex ratio than is condition per se
(Roche et al. 2006;Cameron & Linklater 2007) further
supports our contention that sex ratio is linked more
directly to diet than to maternal condition.
Over the past 40 years, there have been small, but
highly consistent, declines in the proportion of male
infants born in industrialized countries ( James 2000).
This has caused considerable concern, and is regarded as a
health sentinel, possibly of exposure to toxins (Davis et al.
1998;James 2000). However, population-level changes in
the diets of young women may explain the pattern. Trends
of declining mean energy intake over time among adults
and children are reported by most ( Heini & Weinsier
Table 3. Maternal characteristics and foetal sex.
%(n) or mean [s.d.]
male foetus (nZ372) female foetus (nZ368) test statistic
a
p-value
current smoker
b
39.0 (145) 42.4 (156) 0.89 0.35
cigarettes yesterday (n)
0 73.9 (275) 69.8 (257) 1.72 0.27
1–8 14.8 (55) 17.4 (64)
9–16 8.6 (32) 9.2 (34)
17 or more 2.7 (10) 3.5 (13)
folic acid used prior to conception 34.4 (128) 34.2 (126) 0.002 0.96
education
!O level 23.1 (86) 19.6 (72) 1.40 0.50
O level 51.1 (190) 53.5 (197)
OO level 25.8 (96) 26.9 (99)
age ( years) 25.8 [5.0] 25.8 [4.9] 0.01 0.92
weight prior to conception ( kg)
c
62.8 [11.7] 62.6 [15.0] 0.06 0.80
weight at booking ( kg)
d
67.2 [12.5] 66.2 [12.3] 1.16 0.28
height (cm) 164.3 [6.5] 164.3 [6.6] 0.01 0.91
body mass index prior to conception
(kg m
K2
)
c
23.2 [4.0] 23.2 [5.3] 0.06 0.81
body mass index at first antenatal clinic
(kg m
K2
)
d
24.9 [4.3] 24.5 [4.3] 1.18 0.28
a
Wald c
2
-test for continuous and categorical predictors in logistic models.
b
Defined by self-report or by a serum cotinine concentration greater than 14 ng ml
K1
in self-reported ‘non-smokers’.
c
Data missing from medical records for 18 (4.8%) mothers of boys and 11 (3.0%) mothers of girls.
d
Data missing from medical records for 9 (2.4%) mothers of boys and 11 (3.0%) mothers of girls.
1666 F. Mathews et al. Preconceptional diet predicts foetal sex
Proc. R. Soc. B (2008)

1997;Troiano et al. 2000;Fletcher et al. 2004) though not
all (Nielsen et al. 2002) large-scale studies, with the
current obesity epidemic being ascribed to declines in
physical activity and alterations in the distribution of
energy intakes. At the same time, there is good evidence
that the prevalence of breakfast skipping is increasing,
particularly among younger age groups: for example, in
the USA, the proportion of adults consuming breakfast
fell from 86 to 75% between 1965 and 1991, and for
adolescent girls, the decline was from 85 to 65% (Haines
et al. 1996;Siega-Riz et al. 1998). More work using
biomarkers of nutrient status pre-pregnancy is warranted
to further explore the relationship between infant sex and
maternal resources.
All women provided written informed consent and the
study was approved by the Research Ethics Committees of
Portsmouth Hospitals and of the University of Oxford
Medical school.
We thank the women who participated in the project, and
the staff of St Mary’s Hospital, Portsmouth. We are grateful
to the European Prospective Investigation of Cancer
(EPIC) for permission to use their dietary questionnaires.
Lin McRoberts and Linda Willis helped with data
collection and management. The project was funded by
the Sir Jules Thorn Charitable Trust. F.M. was a Royal
Society Dorothy Hodgkin Research Fellow. The manuscript
was improved by discussion with John Clarke, Ben Sheldon
and Tom Tregenza.
None of the authors has any competing interest.
REFERENCES
Bingham, S. A. et al. 1997 Dietary assessment in the
European prospective investigation of diet and cancer
(EPIC). Eur. J. Cancer Prev. 1, 118–124.
Bird, E. & Contreras, R. J. 1986 Maternal dietary sodium
chloride levels affect the sex-ratio in rat litters. Physiol.
Behav. 36,307–310.(doi:10.1016/0031-9384(86)90021-1)
Buss, D. M. 2006 Strategies of human mating. Psychol. Top.
15, 239–260.
Buss, D. M. et al. 1990 International preferences in selecting
mates: a study of 37 societies. J. Cross Cult. Psychol. 21,
5– 47. (doi:10.1177/0022022190211001)
Cameron, E. Z. 2004 Facultative adjustment of mammalian
sex ratios in support of the Trivers–Willard hypothesis:
evidence for a mechanism. Proc. R. Soc. B 271,
1723–1728. (doi:10.1098/rspb.2004.2773)
Cameron, E. Z. & Linklater, W. L. 2007 Extreme sex ratio
variation in relation to change in condition around
conception. Biol. Lett. 3, 395–397. (doi:10.1098/rsbl.
2007.0089)
Chesterman-Phillips, H. 2005 Choose the sex of your baby—the
natural way. London, UK: Bloomsbury.
Clayton, D. & Gill, C. 1991 Covariate measurement errors in
nutritional epidemiology: effects and remedies. In Design
concepts in nutritional epidemiology (eds B. M. Margetts &
M. Nelson), pp. 79–96. Oxford, UK: Oxford University
Press.
Clutton-Brock, T. H. 1991 The evolution of parental care,
pp. 215–217. Princeton, NJ: Princeton University Press.
Clutton-Brock, T. H. & Iason, G. R. 1986 Sex ratio variation
in mammals. Q. Rev. Biol. 61, 339–374. (doi:10.1086/
415033)
Cluzan, R., Causeret, J. & Hugot, D. 1965 Le me
´tabisulfite
de potassium. E
´tude de toxicite
´a long terme chez le rat.
Ann. Biol. Anim. Biochem. Biophys. 5, 267–281. (doi:10.
1051/rnd:19650207)
Comfrey, A. I. & Lee, H. B. 1992 A first course in factor
analysis, 2nd edn. Hillsdale, NJ: Lawrence Erlbaum
Associates.
Crozier, S. R., Robinson, S. M., Borland, S. E. & Inskip,
H. M. 2006 Dietary patterns in the Southampton
Women’s Survey. Eur. J. Clin. Nutr. 60, 1391–1399.
(doi:10.1038/sj.ejcn.1602469)
Daly, M. & Wilson, M. 1985 Competitiveness, risk taking
and violence: the young male syndrome. Ethol. Sociobiol. 6,
59–73. (doi:10.1016/0162-3095(85)90041-X)
Davis, D. L., Gottlieb, M. B. & Stampnitzky, J. R. 1998
Reduced ratio of male to female births in several
industrialised countries. A sentinel health indicator?
J. Am. Med. Assoc. 279, 1018–1023. (doi:10.1001/jama.
279.13.1018)
Davis, D. L., Webster, P., Stainthorpe, H., Chilton, J., Jones,
L. & Doi, R. 2007 Declines in sex ratio at birth and fetal
deaths in Japan and in US whites but not African
Americans. Environ. Health Perspect. 115, 941–946.
Fielder, M., Huber, S., Bookstein, F. L., Iber, K., Scha¨fer,
K., Winckler, G. & Wallner, B. 2005 Status and
reproduction in humans: new evidence for the validity of
evolutionary explanations on basis of a university sample.
Ethology 111, 940–950. (doi:10.1111/j.1439-0310.2005.
01129.x)
Fletcher, E. S., Rugg-Gunn, A. J., Matthews, J. N. S.,
Hackett, A., Moynihan, P. J., Mathers, J. C. & Adamson,
A. J. 2004 Changes over 20 years in macronutrient intake
and body mass index in 11- to 12-year old adolescents
living in Northumberland. Br. J. Nutr. 92, 321–333.
(doi:10.1079/BJN20041199)
Frank, S. A. 1987 Individual and population sex allocation
patterns. Theor. Popul. Biol. 31, 47–74. (doi:10.1016/
0040-5809(87)90022-0)
Gibson, M. A. & Mace, R. 2003 Strong mothers bear more
sons in rural Ethiopia. Proc. R. Soc. B 270, S108–S109.
(doi:10.1098/rsbl.2003.0031)
Grant, V. J. 2007 Could maternal testosterone levels govern
mammalian sex ratio deviations? J. Theor. Biol. 246,
708–719. (doi:10.1016/j.jtbi.2007.02.005)
Guerrero, R. 1974 Association of the type and time of
insemination within the menstrual cycle with the human
sex ratio at birth. N. Engl. J. Med. 291, 1056–1059.
Haines, P. S., Guilkey, D. K. & Popkin, B. M. 1996 Trends in
breakfast consumption of US adults between 1965 and
1991. J. Am. Diet. Assoc. 96, 464– 470. (doi:10.1016/
S0002-8223(96)00130-7)
Harlap, S. 1979 Gender of infants conceived on different days
of the menstrual cycle. N. Engl. J. Med. 300, 1445–1448.
Heini, A. F. & Weinsier, R. L. 1997 Divergent trends in
obesity and fat intake patterns: the American paradox.
Am. J. Med. 102, 259–264. (doi:10.1016/S0002-
9343(96)00456-1)
Helle, S., Helama, S. & Jokela, J. 2008 Temperature-related
birth sex ratio bias in historical Sami: warm years bring
more sons. Biol. Lett 4, 60–62. (doi:10.1098/rsbl.2007.
0482)
Hopcroft, R. L. 2006 Sex, status and reproductive success in
the contemporary United States. Evol. Hum. Behav. 27,
104–120. (doi:10.1016/j.evolhumbehav.2005.07.004)
Hrdy, S. B. 1999 Mother Nature: a history of mothers, infants
and natural selection. New York, NY: Random House.
James, W. H. 1971 Cycle day of insemination, coital rate, and
sex ratio. Lancet 1, 112–114. (doi:10.1016/S0140-
6736(71)90844-0)
James, W. H. 1990 The hypothesised hormonal control of
human sex ratio at birth: an update. J. Theor. Biol. 143,
555–564.
Preconceptional diet predicts foetal sex F. Mathews et al. 1667
Proc. R. Soc. B (2008)

James, W. H. 2000 Secular movements in sex ratios of adults
and of births in populations during the last half-century.
Hum. Reprod. 15, 1178–1183. (doi:10.1093/humrep/15.5.
1178)
Krackow, S. 1995 The developmental asynchrony hypothesis
of sex ratio manipulation. J. Theor. Biol. 176, 273–280.
(doi:10.1006/jtbi.1995.0197)
Kruger, D. J. & Nesse, R. M. 2007 Economic transition, male
competition and sex differences in mortality rates. Evol.
Psychol. 5, 411–427.
Labov, J. B., Huck, U. W., Vaswani, P. & Lisk, R. D. 1986 Sex
ratio manipulation and decreased growth of male offspring
of prenatally and postnatally undernourished golden
hamsters. Behav. Ecol. Sociobiol. 18, 241–249. (doi:10.
1007/BF00300000)
Larson, M. A., Kimura, K., Kubisch, H. M. & Roberts, R. M.
2001 Sexual dimorphism among bovine embryos in their
ability to make the transition to expanded blastocyst and in
the expression of the signaling molecule IFN-tau. Proc.
Natl Acad. Sci. USA 98, 9677–9682. (doi:10.1073/pnas.
171305398)
Lecomte, P., Vol, S., Caces, E., Lasfargues, G., Combe, H.,
Laurent, S. & Tichet, J. 2002 Impaired fasting glycaemia
and undiagnosed diabetes: prevalence, cardiovascular and
behavioural risk factors. Diabetes Metab. 28, 311–320.
Mathews, F., Yudkin, P. & Neil, A. 1999 Influence of
maternal nutrition on outcome of pregnancy: prospective
cohort study. Br. Med. J. 319, 339–343.
McMillen, M. M. 1979 Differential mortality by sex on fetal
and neonatal deaths. Science 204, 89–91. (doi:10.1126/
science.571144)
Myers, J. H. 1978 Sex ratio adjustment under food stress:
maximization of quality or numbers of offspring? Am. Nat.
112, 381–388. (doi:10.1086/283280)
Nielsen, S. J., Siega-Riz, A. M. & Popkin, B. M. 2002 Trends
in energy intake in US between 1977 and 1996: similar
shifts seen across age groups. Obes. Res. 10, 370–378.
Novitski, E. & Kimball, A. W. 1958 Birth order, parental ages,
and sex of offspring. Am.J.Hum.Genet.10, 268–275.
Papa, F., Henrion, R. & Breart, G. 1983 Selection
preconceptionelle du sexe par la methode ionique.
J. Gynecol. Obstet. Biol. Reprod. (Paris ) 12, 415– 422.
Pawlowski, B., Dunbar, R. I. M. & Lipowicz, A. 2000 Tall
men have more reproductive success. Nature 403, 156.
Prentice, A. M., Poppitt, S. D., Goldberg, G. R. & Prentice,
A. 1995 Adaptive strategies regulating energy balance in
human pregnancy. Oxf. Rev. Reprod. Biol. 17, 33–60.
Reubinoff, B. & Schenker, J. 1996 New advances in sex
preselection. Fertil. Steril. 66, 343–350.
Rickard, I. J., Russell, A. F. & Lummaa, V. 2007 Producing
sons reduces lifetime reproductive success in subsequent
offspring in pre-industrial Finns. Proc. R. Soc. B 274,
2981–2988. (doi:10.1098/rspb.2007.1051)
Roche, J. R. & Lee, J. M. 2007 Altering systemic acid–base balance
through nutrition failed to change secondary sex ratio. Reprod.
Fer t il. D ev. 19, 887–890. (doi:10.1071/RD06053)
Roche, J. R., Lee, J. M. & Berry, D. P. 2006 Pre-conception
energy balance and secondary sex ratio—partial support
for the Trivers–Willard hypothesis in dairy cows. J. Dairy
Sci. 89, 2119–2125.
Rostron, J. & James, W. H. 1977 Maternal age, parity, social
class and sex ratio. Ann. Hum. Genet. 41, 205–217.
(doi:10.1111/j.1469-1809.1977.tb01916.x)
Sachdeva, K. K., Sengar, O. P. S., Singh, S. N. & Lindaht,
I. L. 1973 Studies on goats. 1. Effect of plane of nutrition
on reproductive performance of does. J. Agric. Sci. Camb.
80, 375–379.
Schmitt, D. P., Shackelford, T. K. & Buss, D. M. 2001 Are men
really more ‘oriented’ toward short-term mating than
women? A critical review of theory and research. Psychol.
Evol. Gend. 3, 211–239. (doi:10.1080/14616660110119331)
Shay, S. D. 2003 Energy in take in pregnant women carrying
boys or girls: energy intake may correlate with prebirth
knowledge of sex of child. Br. Med. J. 327, 621–622.
(doi:10.1136/bmj.327.7415.621-c)
Sheldon, B. C. & West, S. A. 2004 Sex ratio variation in
ungulate mammals. Am. Nat. 163, 40–45. (doi:10.1086/
381003)
Siega-Riz, A. M., Popkin, B. M. & Carson, T. 1998 Trends in
breakfast consumption for children in the United States
from 1965 to 1991. Am. J. Clin. Nutr. 67, 748S–756S.
Stein, A. D., Barnett, P. G. & Sellen, D. W. 2003 Maternal
undernutrition and the sex ratio at birth in Ethiopia:
evidence from a national sample. Proc. R. Soc. B 271,
S37–S39. (doi:10.1098/rsbl.2003.0086)
Tamimi, R. M., Lagiou, P., Mucci, L. A., Hsieh, C., Adami,
H. & Trichopoulos, D. 2003 Average energy intake among
pregnant women carrying a boy compared with a girl.
Br. Med. J. 326, 1245–1246. (doi:10.1136/bmj.326.7401.
1245)
Teitelbaum, M. S. & Mantel, N. 1971 Socio-economic
factors and the sex ratio at birth. J. Biosoc. Sci. 3, 23 – 41.
Trivers, R. L. & Willard, D. E. 1973 Natural selection of
parental ability to vary the sex ratio of offspring. Science
179, 90–92. (doi:10.1126/science.179.4068.90)
Troiano, R. P., Briefel, R. R., Carroll, M. D. & Bialostosky,
K. 2000 Energy and fat intakes of children and
adolescents in the United States: data from the National
Health and Nutrition Examination Surveys. Am. J. Clin.
Nutr. 72, 1343S–2353S.
Wilcox, A. J., Weinberg, C. R. & Baird, D. D. 1995 Timing
of sexual intercourse in relation to ovulation—effects on
the probability of conception, survival of the pregnancy,
and sex of the baby. N. Engl. J. Med. 333, 1517–1521.
(doi:10.1056/NEJM199512073332301)
Willett, W. 1990 Nutritional epidemiology. New York, NY:
Oxford University Press.
Wilson, M. & Daly, M. 1997 Life expectancy, economic
inequality, homicide and reproductive timing in Chicago
neighbourhoods. Br. Med. J. 314, 1271–1274.
1668 F. Mathews et al. Preconceptional diet predicts foetal sex
Proc. R. Soc. B (2008)