SH, C Brazil, EZ Brobnis, F Liu, RL Kruse, M Hatch, JB Redmon, C
Wang, JW Overstreet, and the Study for Future Families Research
Group. 2003. Geographic differences in semen quality of
fertile US males. Environmental
Health Perspectives 111:414-420.
et al. present conclusive proof of significant
differences in sperm count among geographic areas within the United
States. Previous studies had suggested geographic variation,
but problems in comparing different studies and measurement techniques
prevented firm conclusions.
this new study, Swan et al. developed and applied a rigorous
protocol that was shared by labs in four different regions of the
country. Their work reveals that men from rural areas of Missouri
have lower sperm counts than urban dwellers in New York, Minnesota
and Los Angeles.
these differences exist or over what time span they developed remains
did they do? Swan et al. obtained sperm samples
from the husbands of pregnant women coming to a university hospital
for prenatal care in the four study areas: New York NY, Minneapolis
MN, Los Angeles CA and Columbia, MO. Only husbands at least 18 yrs
old were selected, and only if the pregnancy was not medically assisted.
Several other criteria were also used consistently at each participating
university hospital. The care taken to choose the sample was a key
methodological breakthrough for this work because most studies of
sperm counts have been based upon samples that were unlikely to
be representative of the local population (one
notable exception; and see comment below).
participants contributed two sperm samples, separated by approximately
3 weeks. Subjects were asked to abstain from ejaculating for 2-5
days prior to providing a semen sample. The time of the last ejaculation
prior to providing the sample was obtained by interview as were
data on a variety of other factors known to affect sperm count.
These variables were all included in the statistical analysis. Men
with abstinence times of less than 2 hrs or greater than 10 days
samples were examined at the four university hospitals using procedures
that were carefully developed to minimize any measurement artifacts;
technicians conducting the measurements were trained and tested
for proficiency. They measured sperm density, volume and motility,
and also compared sperm morphologies. Extensive statistical analysis
and adjustment were used to correct for differences among the centers
in confounding variables, such as age, race, smoking, history of
fever and sexual-transmitted diseases, genital problems, etc.
did they find? Semen samples came from 493 men, of whom
410 provided two samples (on average 24 days apart). The average
abstinence time overall was 78 hours; each of the four study sites
averaged within 6 hours of that overall average.
concentration, percent motile sperm and total motile count were
lower in Missouri than at all other centers (see table below).
et al. measured sperm density using two different techniques,
both of which reported the lowest average in Missouri. The table
below presents the averages of their measurements using a standardized
technique called the µ-Cell (a disposable counting chamber).
their extensive statistical analyses, adjusting the measurements
to correct for the effects of the confounding variables recorded
in interviews by Swan et al. did not eliminate the large
differences between Columbia MO and the other sites, even though
a number of these variables, by themselves, were important.
example" "Smoking more than ten cigarettes per day was
associated with decreased semen volume, but had little effect on
concentration, motility or morphology. Fever within the prior three
months significantly decreased sperm concentration and motility,
but not morphology or semen volume. The percent morphologically
normal sperm was reduced among men who reported a history of a STD"
does it mean? Swan et al. observed striking differences
between Missouri men and those from the other study locations. Why?
At present, they do not know. The most conspicuous difference between
the areas is Columbia, Missouri's, close proximity to industrial
agriculture and its pesticides. Yet the data that Swan et al.
present in the study do not allow any conclusions to be reached
about whether this obvious difference is involved in causing the
differences between the regions. They conclude with the observation:
current study finds considerably reduced semen quality in
Columbia MO compared to NY, MN and CA. While there may well
be multiple factors on which MO differs from the other centers,
MO is unusual among sites for semen studies because of its
proximity to intensive agriculture. The limited availability
of semen quality data from semi-rural, agricultural communities,
the historically low concentrations in IA [referring to an
earlier study in Iowa], and the low sperm concentration and
percent motile sperm reported here for Columbia MO suggest
the need for further study in such communities.
There is no reason to propose that large genetic differences in
the population makeup of Missouri vs. the other sites account for
the observed geographic patterns... the US population is too mobile.
If that is true, then a clear implication of Swan et al.'s
data is that sperm count in Missouri has declined, although over
what time scale this may have occurred is unknown.
limiting the study subjects to fertile husbands only, Swan et
al. may have reduced the real differences between Missouri
and other men. Their selection criteria bias the sample against
men with very low sperm counts, particularly those so low they are
incapable of fertilization. Given the observed differences between
Missouri and other regions, men with extremely low sperm counts
are more likely in Missouri than elsewhere. Thus it is possible
that the selection criteria led to inclusion within the study of
men in Missouri with higher sperm counts than would be obtained
were the sample truly random.