Vol.2, No.6, 639-644 (2010) Health
doi:10.4236/health.2010.26097
Copyright © 2010 SciRes. Openly accessible at http://www.scirp.org/journal/HEALTH/
Gender and environment: general and monthly gender
distribution of newborns and cosmophysical
parameters
Eliyahu Stoupel1,2*, Evgeny Abramson3, Peter Israelevich4, Mordechai Shohat2,5,
Jaqueline Sulkes3
1Division of Cardiology, Rabin Medical Center, Petah Tiqwa, Israel; *Corresponding Author: stoupel@inter.net.il
2Sackler Faculty of Medicine Tel Aviv University, Tel Aviv; Israel
3Management Data Center, Rabin Medical Center, Petah Tiqwa, Israel
4Department of Geophysics & Planetary Science, Tel Aviv University, Tel Aviv; Israel
5Recanati Institute of Medical Genetics, Rabin Medical Center, Petah Tiqwa, Israel
Received 23 March 2010; revised 27 April 2010; accepted 28 April 2010.
ABSTRACT
Recent publications have described a relation-
ship between fluctuations in environmental
physical activity and several aspects of fetal
development. This study explored the possible
effects of cosmophysical parameters on new-
born gender, overall and by maternal age. The
gender distribution of 123,368 infants born over
a 189-month period (November 1993–July 2009)
was analyzed against levels of solar, geomag-
netic, and cosmic ray activity at the time of
conception. The cohort was then divided into
three groups by maternal age (< 28 years, 29-35
years, > 35 years) for further analysis. Pearson
correlation coefficients and their probabilities
were calculated, and chi-square test was ap-
plied, as necessary. The physical data were de-
rived from space science centers in the USA,
Russia, and Finland. The results showed that
the male/female ratio for the whole cohort over
the study period was 1.06. However, on monthly
analysis, there was a significant male predomi-
nance in most months, with a male/female ratio
of up to 4. Younger mothers (< 28 years) gave
birth to significantly more boys than older
mothers. The gender distribution in the three
maternal age groups was partially linked to the
different physical factors. These findings sug-
gest that environmental physical activity in the
month of conception may play a role in newborn
gender. Further study is needed to determine
the mechanism underlying this effect.
Keywords: Newborn; Gender; Solar; Geomagnetic;
Cosmic Ray; Activity; Age; Mother; Pregnancy
1. INTRODUCTION
Newborn gender is a focus of human and scientific in-
terest. In addition to the known genetic factors that affect
fetal development, several studies published in the last
decades have considered the potential influence of fluc-
tuations in environmental physical activity (solar, geo-
magnetic, cosmic ray) on physiologic and pathologic
aspects of pregnancy and fetal development [1-9].
The aim of the present study was to investigate the
possible effect of fluctuations in cosmophysical parame-
ters at conception on newborn gender distribution, over-
all and by maternal age.
2. METHODS
The study included all 123,368 infants born at a tertiary
university hospital in Israel from November 1993 to July
2009 (189 months): 63,415 male and 59,953 female
(liveborn or stillborn). Distribution by maternal age
showed that 54,158 (43.86%) infants were born to moth-
ers younger than 29 years, 47,655 (38.60%) to mothers
aged 29-35 years, and 21,657 (17.54%) to mothers older
than 35 years. These data were correlated against levels
of the following cosmophysical parameters in the month
of conception: solar activity indices sunspot number,
smoothed sunspot number, solar flux at 2800 MGH and
10.7 cm wavelength, and adjusted solar flux; geomag-
netic activity (GMA) indicesAp, Cp, and Am (plane-
tary and regional, for middle latitudes); and cosmic ray
activity (CRA)represented by neutron activity at the
Earth’s surface (in imp/min). The cosmophysical data for
E. Stoupel et al. / HEALTH 2 (2010) 639-644
Copyright © 2010 SciRes. Openly accessible at http://www.scirp.org/journal/HEALTH/
640
the study period were derived from weekly and monthly
calculations published by space science institutions in
the United States, Russia, and Finland that regularly
monitor these parameters worldwide (National Geo-
physical Data Center, Space Weather Prediction Center,
Moscow Neutron Monitor, Space Weather Prediction
Center; Space Environment Services Center; November
2003-July 2009) [10-15].
2.1. Statistical Analysis
Pearson correlation coefficients (r) and their probabili-
ties (p) were calculated between newborn gender distri-
bution and the physical parameters. Chi-square test was
used to analyze the likelihood of a newborn being male
or female by physical parameters and maternal age
group. Probabilities of 95% and higher were considered
significant, probabilities of 90%-94% were considered
trends toward significance. Non significant results were
marked N.S.
3. RESULTS
The male/female ratio in the whole population of new-
borns was 1.06. Maximal monthly deviations ranged
from 1.387 to 0.7399. One hundred fifty months (79.36%)
were characterized by a significant prevalence of male
newborns (79.36%), and 39 months (20.1%) by a sig-
nificant prevalence of female newborns; in one month,
the gender distribution was equal.
Table 1 presents the newborn gender relationship with
cosmophysical parameters during the month of concep-
tion. Table 2 presents the same relationship by maternal
age group: 28 years or less; 29-35 years; and 35 years or
mor e .
The results showed that mothers aged 28 years or less
gave birth to significantly more male newborns than
older mothers (χ2 = 3.9, p = 0.047). The ratio of months
with more male newborns to months with more female
infants in this maternal age group was 2.62. In the two
older groups, this ratio was 2.16 (p < 0.0001).
The differences among the maternal age groups
prompted our use of multifactorial analysis for each
gender and each of the three maternal age groups to pre-
dict the chances of a mother of particular age giving
birth to a boy or girl according to levels of the cosmo-
physical parameters. The findings are shown in Tables
3-5. Factors that failed to show a significant relationship
in the total correlation study (Table 1) were included as
significant in the subgroup of multifactorial analysis (for
example, monthly GMA Cp for mothers older 35 years)
(Tables 3-5).
The relationship of solar and neutron activity was also
different among the three age groups, changing from a po-
sitive in the young mother group to an inverse relationship
Table 1. Monthly (n = 189) newborn (n = 123683) gender distribution by physcial parameters in the month of conception (Pearson
correlation coefficients and their probabilities).
Parameters Physical Activity 9 Months to Delivery
Male (n = 63415) Female (n = 59953) Ratio (1.06)
Year 0.72 p < 0.0001 0.704 p < 0.0001 NS
Month NS NS NS
Solar activity
Sunspot number 0.21 p = 0.0039 0.16 p = 0.02 NS
Smoothed sunspot number 0.24 p = 0.0012 0.2 p = 0.0056 NS
Solar flux 2800 MGH, 10.7 cm 0.3 p < 0.0001 0.26 p = 0.0003 NS
Adjusted solar flux 0.283 p < 0.0001 0.243 p = 0.0008 NS
Geomagnetic activity
Ap NS NS NS
Cp NS NS NS
Am NS NS NS
Cosmic ray (neutron) activity (imp/min)
Moscow –0.295 p < 0.0001 –0.28 p = 0.0001 NS
Oulo –0.27 p = 0.0002 –0.25 p = 0.0005 NS
Note: 150 months, more males; 39 months, more females Chi-square = 134.8, p < 0.0001; range: 1.387-0.7399.
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Table 2. Monthly (n = 189) gender distribution by environmental physical activity in month of conception and maternal age (Pearson
correlation coefficients and their probabilities).
Parameter Age 28 Age 29-35 Age > 35
Male
(n = 27997)
Female
(n = 26161)
Male
(n = 24352)
Female
(n = 23303)
Male
(n = 11168)
Female
(n = 10489)
Year 0.263
0.0003
0.233
0.0013
0.88
< 0.0001
0.86
< 0.0001
0.68
< 0.0001
0.735
0.0001
Month NS NS NS NS NS NS
Solar activity
Sunspot number 0.46
< 0.0001
0.44
< 0.0001 NS NS
–0.19
0.0085
–0.21
0.0031
Smoothed sunpsot number 0.51
< 0.0001
0.49
< 0.0001 NS NS
–0.2
0.0057
–0.2
0.0055
Solar flux 2800 MGH, 10.7
cm
0.53
< 0.0001
0.51
< 0.0001
0.13
0.08 NS –0.12
0.1
–0.13
0.07
Adjusted solar flux 0.51
0.0001
0.49
< 0.0001
0.12
0.09 NS –0.13
0.07
–0.14
0.049
Geomagnetic activity
Ap NS NS NS NS
–0.12
0.1
–0.17
0.018
Cp NS NS
–0.17
0.02
–0.16
0.03
–0.17
0.018
–0.2
0.0055
Am 0.13
0.07 NS NS NS
–0.14
0.056
–0.165
0.023
Cosmic ray (neutron) activity (imp/min)
Moscow –0.465
< 0.0001
–0.44
< 0.0001
–0.16
0.025
–0.14
0.06
0.15
0.033
0.134
0.065
Oulo –0.4
< 0.0001
–0.34
< 0.0001
–0.17
0.02
–0.16
0.03
0.14
0.057
0.12
0.1
Table 3. Prediction model to determine likelihood of a woman older than 29 years giving birth to a male or female infant by levels of
physical factors in the month of conception.
Variables Parameter estimate Standard error Probability
Likelihood of male infant (n = 27897)
Intercept –3569 621.2 < 0.0001
Year 1.85 0.311 < 0.0001
Solar flux 2800 MGH 2.485 0.436 < 0.01
Adjusted solar flux –2.54 0.454 < 0.0001
Smoothed sunspot number 0.4 0.123 0.0012
Likelihood of female infant (n = 26161)
Intercept –3097 610.4 < 0.0001
Year 1.61 0.306 < 0.0001
Solar flux 2800 MGH 2.43 0.428 < 0.0001
Adjusted solar flux –2.5 0.446 < 0.0001
Smoothed sunspot number 0.l38 0.12 0.0016
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Table 4. Prediction model to determine likelihood of a woman aged 29-35 years giving birth to a male or female infant by levels of
physical factors in the month of conception.
Variables Parameter estimate Standard error Probability
Likelihood of male infant (n = 24352)
Intercept –12310 437 < 0.0001
Year 6.21 0.218 < 0.0001
Month 0.788 0.289 0.0071
Smoothed sunspot number 0.124 0.00257 < 0.0001
Likelihood of female infant (n =23303)
Intercept –11071 469.76 < 0.0001
Year 5.62 0.234 < 0.0001
Month 0.54 0.311 0.08
CRA –0.01 0.003 0.0028
CRA—cosmic ray activity
Table 5. Prediction model to determine likelihood of a woman older than 35 years giving birth to a male or female infant by levels of
physical factors in the month of conception.
Variables Parameter estimate Standard error Probability
Likelihood of male infant (n = 11166)
Intercept –4343 323 < 0.0001
Year 2.16 0.159 < 0.0001
GMA (Cp) 10.98 4.267 < 0.01
CRA 0.011 0.00258 < 0.0001
Likelihood of female infant (n = 10489)
Intercept –4339 288.08 < 0.0001
Year 2.167 0.14 < 0.0001
GMA (Cp) 19.98 4.267 < 0.001
CRA 0.0062 0.00158 0.0001
GMA—geomagnetic activity, CRA—cosmic ray activity
in the older than 35. In the intermediate age group (age
28-35) non significant relationship was seen (Table 2).
4. DISCUSSION
Newborn gender is known to be affected by genetic
(chromosome X, Y interaction) and endocrine (hormonal)
factors [16,17]. A series of publications has demon-
strated that environmental physical parameters, such as
solar, cosmic ray and geomagnetic activity, at the begin-
ning of pregnancy may also play a role [1-9,17-19], per-
haps via their effects on chromosome function (clearly
shown in the case of Down syndrome) and hormone
secretion [5] Accordingly, other neonatology parameters,
including monthly number of infants born, newborn
length and weight, preterm deliveries, and occurrence of
congenital heart disease and other malformations have
been linked to cosmophysical activity [1-6,9,15,17,19,
20]
The mechanism underlying this relationship is still
unknown, although the physiologic and teratogenic po-
tential of cosmophysical factors is clear. The effect of
solar activity on human biological behavior is apparently
due to solar corpuscular and wave energy. High levels of
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cosmic rays in space leave remains of crushed atoms in
the form of neutrons, and the measurement of neutron
activity on the Earths’ surface serves as an indirect
measure of cosmic ray activity. It is assumed that neu-
trons, by the nature of their physical properties, connect
with H+ ions and are converted to protons, which attack
cell nuclei in enzymes and other regulatory systems
[19,21]. Solar and geomagnetic activities shield the
Earth from cosmic rays; when they are weak, the effect
of cosmic ray activity increases. One study conducted
over a 216-month period found that the correlation be-
tween solar and cosmic ray activity was –0.84 (p <
0.0001) [22,23]. Recent study, describing the Y chro-
mosome as a very labile structure [24], allows to see it as
an object for possible physical influences.
According to the world-renowed physicist, Dr. Fein-
mann, “Probably the most powerful single assumption
that contributes to the progress of biology is the assump-
tion that everything from the animals to the atoms can do
that are seen in the biological world are the result of the
behavior of physical and chemical phenomena” [25].
Overall, we found that the number of male newborns
only slightly surpassed the number of female newborns.
A male/female ratio of 1.06 to 1.07 has been consistently
reported in studies in various countries and regions [6].
However, males showed a considerable predominance
when we compared monthly deliveries: in some months,
the male/female ratio was close to 4. This trend was
more apparent in younger mothers (age 28 years or less).
Further analysis of gender distribution by maternal age
showed that in the youngest age group, solar activity had
a strong effect and cosmic ray activity a weak effect,
whereas in the older groups, this relationship was re-
versed. Given that the youngest group was larger, our
findings for the overall link of monthly gender distribu-
tion with physical factors were close to those for the
youngest group.
Although we focused only on maternal age in this
study, we assume a concomitant younger age of the fa-
thers as well, which may also play a role in the physical
influences at the time of conception.
The presented data constitute another chapter in the
study of clinical cosmobiology and the opposing physi-
cal forces in our environment (“equilibrium paradigm”)
[26]. The link between the physical environmental and
human homeostasis brings to mind the statement of Al-
bert Einstein: “The human will is free only within the
bounds of a determined cosmic system” [27].
5. CONCLUSIONS
Both gender monthly newborn number is linked with the
level of cosmophysical activity.
Overall, there is a small male prevalence among
newborns, although monthly calculation of this relation-
ship reveals a considerable male predominance. In addi-
tion to other known factors that determine newborn
gender, environmental physical activity during the month
of conception may also be involved.
The relationship of the different physical factors with
newborn gender varies by maternal age.
More studies are needed to further our understanding
of the ways in which physical forces affect newborn
gender.
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