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The Question of Declining Sperm Density Revisited: An Analysis of 101 Studies Published 1934-1996
Shanna H. SwanIn 1992 Carlsen et al. reported a significant global decline in sperm density between 1938 and 1990 [Evidence for Decreasing Quality of Semen during Last 50 Years. Br Med J 305:609-613 (1992)]. We subsequently published a reanalysis of the studies included by Carlsen et al. [Swan et al. Have Sperm Densities Declined? A Reanalysis of Global Trend Data. Environ Health Perspect 105:1228-1232 (1997)]. In that analysis we found significant declines in sperm density in the United States and Europe/Australia after controlling for abstinence time, age, percent of men with proven fertility, and specimen collection method. The declines in sperm density in the United States (approximately 1.5%/year) and Europe/Australia (approximately 3%/year) were somewhat greater than the average decline reported by Carlsen et al. (approximately 1%/year). However, we found no decline in sperm density in non-Western countries, for which data were very limited. In the current study, we used similar methods to analyze an expanded set of studies. We added 47 English language studies published in 1934-1996 to those we had analyzed previously. The average decline in sperm count was virtually unchanged from that reported previously by Carlsen et al. (slope = -0.94 vs. -0.93). The slopes in the three geographic groupings were also similar to those we reported earlier. In North America, the slope was somewhat less than the slope we had found for the United States (slope = -0.80; 95% confidence interval (CI), -1.37 - -0.24). Similarly, the decline in Europe (slope = -2.35; CI, -3.66 - -1.05) was somewhat less than reported previously. As before, studies from other countries showed no trend (slope = -0.21; CI, -2.30-1.88). These results are consistent with those of Carlsen et al. and our previous results, suggesting that the reported treads are not dependent on the particular studies included by Carlsen et al. and that the observed trends previously reported for 1938-1990 are also seen in data from 1934-1996. Key words: epidemiology, geography, regression analysis, semen quality, sperm density, trend. Environ Health Perspect 108:961-966 (2000). [Online 5 September 2000] http://ehpnet1.niehs.nih.gov/docs/2000/108p961-966swan/abstract.html
In 1992 Carlsen et al. (1) stated that
... reports published worldwide indicate clearly that sperm density has &dined appreciably during 1938-1990.
Subsequently, this conclusion has been supported by findings from some studies (2-4), but not by others (5-7). The critical issues raised concerning this study fall, broadly, into three categories. Some authors suggested that poor or highly variable data invalidated any inference about trends in sperm counts (8,9). Others questioned the validity of the statistical methods used in this analysis (8,10,11). Bias due to changing study populations (12) or confounding by factors such as age and abstinence time (time between sample collection and last ejaculation) were also suggested (4,8).
We conducted several analyses designed to examine these concerns. The first, published in 1997, reanalyzed the studies used by Carlsen et al. (1) to examine model selection, confounding, and selection bias (13). In that paper, we noted that estimates of mean sperm density from the United States and Europe declined somewhat more rapidly than had been reported by Carlsen et al. (1). In other parts of the world, where studies were few and most were quite recent, there was insufficient data to evaluate this question. We also found that controlling for confounding bias, to the extent possible, provided additional support for the conclusions of Carlsen et al. (1) rather than reducing the estimated decline in sperm density. In the second analysis, published in 1999, we looked at sperm counting methods and the reliability of measurements from these historical studies (14). We found no evidence that counting methods had changed appreciably or that counts from older studies were less reliable than those from recent studies.
The current study extends our previous analyses in three ways. First, we conducted an independent literature review to evaluate possible bias in the selection of studies used by Carlsen et al. (1). Second, we examined the robustness of the models utilized in that analysis (and ours) by applying these models to an expanded data set. Finally, we assessed the consistency of post-1990 data with trends in sperm density from studies published before 1990.
Methods
Analysis of Carlsen et aL study. Carlsen et al. (1) screened studies published from 1930 to mid-1990 to identify studies that included estimates of sperm density. They excluded studies that included men in infertile couples, men who were referred because of genital abnormalities, and studies that selected men on the basis of their sperm count. Studies that used nonmanual methods for counting sperm were also excluded. Carlsen et al. (1) included 61 studies published between 1938 and 1990. The authors estimated the rate of change in mean sperm density as a function of publication year by fitting a simple regression model.
Current analysis. The current analysis includes 54 of the 61 studies analyzed by Carlsen et al. (1). As in our previous paper (13), we excluded three non-English language studies (15-17) because it was not practical for us to systematically review the non-English language literature on this subject. We also excluded two studies that included men who conceived only after an infertility work up (18,19), studies that did not meet the eligibility criteria of Carlsen et al. (1). Finally, we did not include any studies with less than 10 subjects, which resulted in two additional exclusions (20,21). The most recent study in Carlsen et al.'s analysis (1) and our 1997 reanalysis (1) was published in June 1990. To extend the study period, we conducted a search of Medline (National Library of Medicine, Bethesda, MD) for English-language studies published between 1990 and 1996 and found 19 that met these eligibility criteria. We also conducted a less systematic search of the 60-year period 1930-1990 and identified 28 additional eligible studies. Therefore, the current analysis is based on 101 English-language studies published in 1934-1996 (54 "Carlsen" studies and 47 "non-Carlsen" studies), each with at least 10 men and all satisfying the eligibility criteria published by Carlsen et al. (1). The 47 "non-Carlsen" studies are summarized in the Appendix.
Each of these 101 studies was reviewed independently by two of us to systematically abstract detailed information on potential confounders and several measures of semen quality. These variables included mean (or median) sperm density, publication year, study location (state and country), study goal (to estimate population parameters, other), criteria for recruiting study subjects (proven fertility, prevasectomy, potential sperm donor, other), percent of men with proven fertility, semen collection method (masturbation into container, other, unspecified), sperm counting methods (manual, not reported), number of samples per individual, age (mean or range), and abstinence time (mean or range, protocol requirement if applicable). Information on the completeness of this information was also recorded.
Previous analyses, including ours (13), have looked at the trend in sperm density as a function of publication year. However, because time of sample collection always predated publication, often by several years, we decided to use the time of sample collection, or its estimate, rather than the year of study publication. For the 22 studies that reported the beginning and end of the sample collection period, which often spanned several years, we used the midpoint to estimate the year of sample collection. The median lag time from the midpoint year to publication was 3 years for these studies. Therefore, when the dates of sample collection were unavailable, we subtracted 3 years from the publication year to estimate the year of sample collection. Finally, to obtain intercepts that were more easily interpretable and to aid in convergence of more complex models, we subtracted 1,900 from the estimated year of sample collection.
The arithmetic mean sperm density was reported in all but six studies. For these six studies we estimated the difference between the arithmetic mean and the reported summary measure (median or geometric mean) using data from studies for which multiple summary measures were available. For the five studies that reported median sperm density only, we estimated the arithmetic mean by adding 12.0 to the median, whereas for the single study that reported only a geometric mean, we added 22.7 to approximate the arithmetic mean.
We followed an analysis strategy similar to the one we used previously (13). After conducting a simple linear regression, we stratified the 101 studies into three broad geographic groupings: North America (44 studies, published 1934-1996), Europe (34 studies, published 1949-1996), and other countries (23 studies, published 1978-1995). We then used multiple regression models (using procedures for linear and nonlinear regression as well as generalized linear models) to fit linear, step, spline, and quadratic models (22). In these models we included confounders that were related to sperm density and/or year in univariate analyses. Interactions between year and region, which can indicate geographic differences in the rates at which sperm density changed, were examined in all multiple regression models. To assess the extent to which each variable confounded the relationship between sperm density and year, we calculated the slope (in the model without interaction terms) with and without that variable included in the model. The magnitude of confounding is estimated by the degree of discrepancy between these two estimates (23). As with previous analyses, data from each study were weighted by the number of men included in that study, and sperm densities are given in units of [10.sup.6]/mL.
Results
The estimated year of sample collection in these 101 studies ranged from 1931 to 1994 (publication year 1934-1996). As shown in Table 1, the majority of new studies were published after 1980. Mean sperm density and mean publication year from studies with and without information about year(s) of sample collection did not differ appreciably. The geographic distribution of these 101 studies, representing 28 countries and 19 states within the United States, was similar to that in previous analyses, but with a somewhat greater proportion of European studies (Table 2). We made two changes in our geographic strata; the stratum we previously labeled United States is now denoted as North America in order to include a (new) Canadian study. In addition, Australia, which was previously included with European studies, is now included with "other countries."
Table 1. Publication year of studies in three analyses. Publication year Carlsen et al. (1) Swan et al. (13) 1930-1959 10 (16%) 8 (14%) 1960-1979 17 (28%)(a) 14 (25%)(a) 1980-1989 33 (54%)(a) 33 (59%)(a) 1990-1996 1 (2%) 1 (2%) Total 61 56 Publication New studies in All studies in year current analysis current analysis 1930-1959 2 (4%) 10 (10%) 1960-1979 3 (6%) 16 (16%) 1980-1989 23 (49%) 55 (54%) 1990-1996 19 (40%) 20 (20%) Total 47 101
(a) Includes one study with < 10 subjects that was excluded from the current analysis.
Table 2. Geographic distribution of studies in three analyses.
Region Carlsen et al. (1) Swan et al. (13)
North America 28 (46%)(a) 27 (48%)(a)
Europe 17 (28%)(b) 15 (28%)(b)
Other 16 (26%) 14 (25%)
Total 61 56
New studies in All studies in
Region current analysis current analysis
North America 18 (38%) 43 (43%)
Europe 20 (43%) 35 (35%)
Other 9 (19%) 23 (23%)
Total 47 101
(a) Includes two studies with < 10 men that were excluded from the current analysis.
(b) Includes one Australian study included in "other" in the current analysis.
Simple linear model. For comparison with Carlsen et al. (1), we first replicated their simple linear regression. As shown in Table 3, the slope for the regression line in the expanded data set (-0.94 x [10.sup.6] mL/year; p [is less than] 0.0001) is very similar to that found for the original 61 studies (-0.93 x [10.sup.6] mL/year; p [is less than] 0.0001). These estimates differ only slightly from the slope we reported in our 1997 analysis (13): (-0.95 x [10.sup.6] mL/year; p [is less than] 0.0001). The fit of the regression line to the 101 data points is shown in Figure 1.
[Figure 1 ILLUSTRATION OMITTED]
Table 3. Results of fitting a simple linear regression model in three analyses.
Subset of Carlsen
Factor Carlsen et al. (1) in current analysis(a)
Number 61 54
Publication years 1938-1990 1938-1990
Slope -0.93 -0.95
p-Value < 0.0001 < 0.0001
[R.sup.2] 0.36 0.36
All studies in
Factor current analysis(a)
Number 101
Publication years 1934-1996
Slope -0.94
p-Value < 0.0001
[R.sup.2] 0.22
(a) Excludes non-English language studies and those with < 10 men.
Assessing confounding and interaction. To select variables for our analysis, we initially included all variables for which we had abstracted data and we noted the percent change in the slope that resulted when we removed them one at a time. Several of these were unrelated to sperm density or publication year (change [is less than] 10%) and were dropped from further analysis. These variables were the number of samples per subject, whether the years of sample collection were reported, whether the arithmetic mean was reported, and purpose of the study. Although removing age changed the slope by only 1.2%, we included this variable in the final model because it is a basic demographic variable often included in analyses of sperm density. The method of counting sperm was also included (although removing it changed the slope by only 6%). In this expanded set of studies, recruiting criteria and the percent of men with proven fertility were highly correlated, so only one of these variables (fertility) was retained for further analyses. The following variables were included in all subsequent multiple regression models: geographic region, age, abstinence time, percentage of men with proven fertility, method of counting sperm, and method of sample collection (Table 4). Of these, all but the method of counting sperm had been included in our previous analysis (13). Because one of the goals of this study was to examine the effect of adding new studies, we also kept a variable that indicated whether the study had been included by Carlsen et al. (1), even though removing it from the model had little effect on the slope. Despite the incompleteness of data on many covariates, the inclusion of the variables contained in Table 4 did improve model fit. When the simple linear model was compared with the multivitriate linear model, including these covariates, the adjusted [R.sup.2] increased from 0.22 to 0.59.
Table 4. Distribution of covariates retained in multiple regression models.(a)
No. of studies
Variable (n = 101)
Region
North America 44
Europe 34
Other 23
Included by Carlsen et al. (1)
Yes 54
No 47
Age
All men [is less than or equal to] 23
40 years of age
Some men [is greater than or equal to] 53
40 years of age
No information 25
Abstinence time
Data reported: none < 3 days 14
Data reported: some < 3 days 14
No data reported: protocol 49
restrictions reported
No information 24
Proven fertility
Wife pregnant or post-partum 20
At least 90% proven fertility (past) 31
< 90% proven fertility (past) 8
No information 42
Method of semen collection
Masturbation into container 70
Other or no information 31
Method of counting sperm
Manual 66
No information 35
Mean sperm
density(b)
Variable ([10.sup.6]/mL)
Region
North America 78
Europe 87
Other 65
Included by Carlsen et al. (1)
Yes 77
No 68
Age
All men [is less than or equal to] 97
40 years of age
Some men [is greater than or equal to] 71
40 years of age
No information 88
Abstinence time
Data reported: none < 3 days 81
Data reported: some < 3 days 78
No data reported: protocol 80
restrictions reported
No information 68
Proven fertility
Wife pregnant or post-partum 82
At least 90% proven fertility (past) 67
< 90% proven fertility (past) 84
No information 86
Method of semen collection
Masturbation into container 70
Other or no information 95
Method of counting sperm
Manual 71
No information 79
Mean year of
sample
Variable collection(b)
Region
North America 1970
Europe 1982
Other 1984
Included by Carlsen et al. (1)
Yes 1974
No 1985
Age
All men [is less than or equal to] 1970
40 years of age
Some men [is greater than or equal to] 1980
40 years of age
No information 1963
Abstinence time
Data reported: none < 3 days 1976
Data reported: some < 3 days 1983
No data reported: protocol 1977
restrictions reported
No information 1976
Proven fertility
Wife pregnant or post-partum 1968
At least 90% proven fertility (past) 1978
< 90% proven fertility (past) 1979
No information 1984
Method of semen collection
Masturbation into container 1979
Other or no information 1971
Method of counting sperm
Manual 1982
No information 1971
(a) Does not include geographic region, which is shown in Table 2.
(b) Univariate/unadjusted, weighted by the number of men in each study.
In addition to including these covariates singly, we examined interaction terms to allow for different slopes in the three geographic regions. In our previous analysis (13), the three slopes that we estimated differed considerably (-1.50, -3.13, and +1.56, respectively, for the United States, Europe/Australia, and other countries). In the current analysis the European slope (-2.35) still differed from that for North American (difference in slopes -1.55; CI, -2.90- -0.21), indicating significant interaction (Figure 2). Although we did include the slope of the best fitting line for other countries (-0.60), the fit to a linear model for data from these countries was not good and the confidence interval was very broad. Given the limited data, there was no evidence that this slope differed appreciably from those from other regions (Table 5).
[Figure 2 ILLUSTRATION OMITTED]
Table 5. Comparison of multiple regression models from Swan et al. (13) (n = 56) and the current analysis (n = 101).(a)
Adjusted
Model [R.sup.2] Region
Linear 0.80 United States
Swan et al. (13) Europe/Australia
Other countries
Current analysis 0.61 North America
Europe
Other countries
Spline 0.79 United States < 1970
Swan et al. (13) United States
[is greater than
or equal to] 1970
Europe/Australia
Other countries
Current analysis 0.60 North America <1970
North America
[is greater than
or equal to] 1970
Europe
Other countries
Step 0.72 United States < 1977
Swan et al. (13) United States
[is greater than
or equal to] 1970
Europe/Australia
Other countries
Current analysis 0.57 North America < 1970
North America
[is greater than
or equal to] 1970
Europe
Other countries
Model Region Slope within region
Linear United States -1.50 (-1.90 - -1.10)
Swan et al. (13) Europe/Australia -3.13 (-4.96 - -1.30)
Other countries 1.56 (-1.00 - 4.12)
Current analysis North America -0.80 (-1.37 - -0.24)
Europe -2.35 (-3.66 - -1.05)
Other countries -0.21 (-2.30 - 1.88)
Spline United States < 1970 -1.52 (-2.37 - -0.66)
Swan et al. (13) United States -1.47 (-3.00 - 0.06)
[is greater than
or equal to] 1970
Europe/Australia -3.12 (-4.99 - -1.26)
Other countries 1.56 (-1.03 - 4.16)
Current analysis North America <1970 -0.93 (-1.81 - -0.05)
North America -0.55 (-2.00 - 0.89)
[is greater than
or equal to] 1970
Europe -2.32 (-3.64 - -1.00)
Other countries -0.25 (-2.37 - 1.86)
Step United States < 1977 106.7 (91.0 - 122.5)
Swan et al. (13) United States 67.7 (55.9 - 79.5)
[is greater than
or equal to] 1970
Europe/Australia 75.0 (60.0 - 90.0)
Other countries 58.3 (46.0 - 70.7)
Current analysis North America < 1970 137.9 (116.6 - 159.3)
North America 113.2 (95.9 - 130.6)
[is greater than
or equal to] 1970
Europe 120.1 (103.6 - 136.6)
Other countries 104.0 (84.7 - 123.4)
Interaction
Model Region beta p-Value
Linear United States Referent
Swan et al. (13) Europe/Australia -1.63 0.08
Other countries 3.06 0.03
Current analysis North America Referent
Europe -1.55 0.03
Other countries 0.60 0.56
Spline United States < 1970 Referent
Swan et al. (13) United States 0.04 0.97
[is greater than
or equal to] 1970
Europe/Australia -1.61 0.13
Other countries 3.08 0.04
Current analysis North America <1970 Referent
North America 0.37 0.71
[is greater than
or equal to] 1970
Europe -1.39 0.09
Other countries 0.68 0.52
Step United States < 1977 --
Swan et al. (13) United States --
[is greater than
or equal to] 1970
Europe/Australia --
Other countries --
Current analysis North America < 1970 --
North America --
[is greater than
or equal to] 1970
Europe --
Other countries --
(a) Controlled for proven fertility, abstinence time, age, specimen collection method, study goal and interaction of region and study year [Swan et al. (13)]; and proven fertility, abstinence time, age, specimen collection method, method of counting sperm, whether study was included by Carlsen et al. (1); and interaction of region and study year (current analysis).
Nonlinear models. We also fit a number of nonlinear models (quadratic, spline, and step) using the same set of covariates that were used for the linear model (Table 4). Olsen et al. (8) suggested that these models were preferable to Carlsen's simple linear model (1). In our 1997 analysis (13), we showed this was not the case, once geographic region and the interaction of region and year were included in the model.
In our previous study (13), we had not seen any difference between the spline and linear models except a slight (nonsignificant) change in the United States post-1970 (from -1.52 to -1.47; p for spline term = 0.97). When a spline model was fit to the current expanded data set, the pre-1970 North American studies showed a somewhat steeper decline than those published after 1970 (-0.93 vs. -0.55), although this difference was still not significant (p for spline term = 0.71).
In our 1997 analysis (13), quadratic terms could not be estimated and we found no evidence of curvature within any of the three regions studied. In the present analysis, it was possible to estimate the quadratic term, but its addition did not improve the fit of the model; the quadratic terms were negligible and none approached statistical significance. Thus, we again found no evidence to support either curvature, or a "leveling off" in the rate of decline in recent years.
In our 1997 analysis (13), we also fit a step function and found a significant post-1970 decrease in sperm density in all regions relative to pre-1970 data (which was entirely from the United States). Again, results were similar in the current analysis. When a step function was fit, comparing the mean sperm density for North America before and after 1970, a large step was seen (138 x [10.sup.6]/mL vs. 113 x [10.sup.6[/mL; p for difference [is less than] 0.001). The pre-1970 mean from North America was also significantly higher than the mean for studies from other (p [is less than] 0.001), whereas the mean for all post-1970 European studies fell between the pre- and post-1970 North American mean.
Overall, the data fit these multiple regression models approximately equally (all adjusted [R.sup.2]s were between 0.56 and 0.61), but not quite as well as the models fit the data in our previous analyses (13) (Table 5). As in our 1997 analysis (13), when multiple regression models that include terms for the interaction of geographic region and year are used, there is no support for the use of a nonlinear model.
Discussion
As we stated previously (13), control for confounding in these analyses can be only partial because of incomplete data. Therefore, it is possible that residual confounding remains. How large is this likely to be?
One of the strongest confounders in this analysis was the type of population studied. We examined this factor in two ways: the percent of men with proven fertility and the type of study population (sperm donor, prevasectomy, etc.) Because these variables were highly correlated, we retained only one (the percent of men with proven fertility) in the final model. When this variable was added to the other variables in the multiple regression model, it increased the magnitude of the slope considerably (37.2%).
Zavos and Goodpasture (24) reported that sperm concentration is higher when semen samples are obtained using a collection device during intercourse than when the same subjects collect samples by masturbation (p [is less than] 0.01), a result that has been reported by others (25). In the current analysis, studies that did not require collection by masturbation tended to be earlier (mean publication year 1970 vs. 1978). Therefore, this variable was a strong (positive) confounder; when it was added to the model, the magnitude of the slope decreased 34.1%.
Carlsen et al. (1) required that sperm be counted by manual methods in all the studies that they included in their analysis. Nevertheless, because manual counting devices have changed somewhat over the study period, when reviewing these studies, we abstracted information on the specific counting method that was used. When the particular counting device was not specified, we assumed it was manual. Nonmanual methods are a relatively recent advance and are still considered experimental, so that studies that use nonmanual methods are likely to specify the use of such methods. In 62 of these 101 studies, the counting device was specified to be the hemocytometer, the method that has been continually recommended by the World Health Organization since 1980 (26,27). The only other counting method that was specified, the Makler chamber (28), was mentioned in only 2 studies of 101 studies. Thus, we found no evidence that the introduction of newer counting devices has resulted in lower sperm counts. In fact, when systematic changes have been introduced by newer methods, they tended to result in higher counts (14). In any case, this variable appeared to have little effect on the observed decline in sperm density.
Some researchers have criticized the use of sperm count estimates from early in the study period, arguing that greater measurement error was likely in these historical studies. Greater imprecision in earlier studies could not have produced the negative slope we observed in Western countries. A change in the variability of sperm counts would, however, violate a basic assumption underlying the regression methods used in these analyses, the assumption of constant variance. Was this assumption justified? To answer this question we looked for a trend in the standard deviation of sperm density in these historical studies. We modeled the standard deviation (which was reported in 34 studies) as a function of year and found no evidence of a trend (slope = -0.24; p = 0.22) (14). We also used a multiple regression model to examine possible confounding of this relationship, but found no evidence of this. We concluded, therefore, that there has been no significant change in the standard deviation of sperm density over time.
Geographic region and the interactions of region and year were important covariates in these analyses. However, these geographic groupings are large and heterogeneous. For example, the category "other countries" included Thailand, India, Hong Kong, Brazil, Australia, Kuwait, Nigeria, Israel, Libya, Tanzania, Peru, Egypt, China, and Saudi Arabia. Several studies suggested that mean sperm density and trends in semen quality may vary considerably, even within small areas (29,30), so that it would have been desirable to stratify studies into narrower geographic categories if sufficient data had been available. Unfortunately, because many of these countries contributed only one study, it was not possible to use narrower geographic strata.
Abstinence time is known to be strongly related to sperm density (31-33). In this analysis, when abstinence time was added to a linear model that included all other variables, the magnitude of the slope decreased by 10.6%, suggesting moderate confounding. Although the inclusion of abstinence time in the model appears to have reduced confounding to some extent, control for this variable was undoubtedly incomplete because less than one-third of these studies included reported abstinence times. An additional 49% of studies noted that abstinence times were restricted by study protocol but, as has been demonstrated, these protocols are only advisory. Auger et al. (2) noted that only 66% of men adhered to the protocol-specified abstinence time of 3-5 days. On the other hand, to account for the observed decline in sperm density, abstinence time would have had to decline appreciably over the study period. The evidence for this is not strong; studies with longer abstinence times (none [is less than] 3 days) were published only slightly earlier than those that included some abstinence times [is less than] 3 days (1976 vs. 1983).
After controlling for abstinence time and other covariates, the addition of age to the model increased the magnitude of the slope by only 1.2%. However, we found little evidence that age is an important predictor of sperm density. Information was quite incomplete for this variable. Twenty-five studies contained no information on age, and these tended to be older studies (mean publication year 1962). For the remaining studies, many only included an age range, so that we were only able to categorize age into broad categories. Nevertheless, we chose to retain this variable in the model for comparability to other analyses.
The current analysis suggests that the previously reported trends have continued, at least until 1996. We have also shown that the studies initially used by Carlsen et al. (1) did not represent a biased selection of the English language literature. Nevertheless, it is likely that neither this publication nor further statistical analyses of historical data will resolve the continuing debate over declining sperm counts. Critics will continue to challenge the reliability of historical data, and most will agree that residual confounding, which may be appreciable, cannot be completely eliminated.
The entire issue of declining sperm count has gained in importance because of the recognition of several other trends that reflect a decline in male reproductive health. Testicular cancer incidence has increased significantly for at least the past 20 years in most of the Caucasian populations that have been studied (30,34,35). Trends in rates of cryptorchidism are consistent with those for testicular cancer, for which cryptorchidism is a significant risk factor (30). These increases in rates of testicular cancer and male genital tract abnormalities, like decreasing sperm density, have primarily been seen in Western countries. Several authors have suggested that these trends, together with decreases in semen quality, may reflect a more generalized increase in testicular dysfunction (30,36,37). Although few of these trend studies have examined possible causes, common environmental exposures are plausible. If environmental factors have produced some, or all, of the temporal changes in sperm density, the regional differences that have been reported in semen quality, even within countries (6,38), may also reflect variation in these environmental factors.
Studies that examine differences in semen quality between geographically diverse cohorts may help identify such factors. An ongoing network of international studies, begun in 1997, was designed to address this question. In these collaborative prospective studies, the use of common study protocols, analytic methods, and quality control procedures should minimize extraneous interstudy differences. These studies should provide unbiased estimates of variability among cities that have been reported to differ widely in semen quality, provide baseline levels of male biomarkers for future studies, and generate hypotheses of environmental causes of variation in these parameters.
REFERENCES AND NOTES
(1.) Carlsen E, Giwercman A, Keiding N, Skakkebaek N. Evidence for decreasing quality of semen during past 50 years. Br Med J 305:609-613 (1992).
(2.) Auger J, Kunstmann JM, Czyglik F, Jouannet P. Decline in semen quality among fertile men in Paris during the past 20 years. N Engl J Med 332:281-285 (1995).
(3.) Irvine S, Cawood E, Richardson D, MacDonald E, Aitken J. Evidence of deteriorating semen quality in the United Kingdom: birth cohort study in 577 men in Scotland over 11 years. Br Med J 312:467-471 (1996).
(4.) Van Waeleghem K, De Clercq N, Vermeulen L, Schoonjans F, Comhaire F. Deterioration of sperm quality in young healthy Belgian men. Hum Reprod 11(2):325-329 (1996).
(5.) Vierula M, Niemi M, Keiski A, Saaranen M, Saarikoski S, Suominen J. High and unchanged sperm counts of Finnish men. Int J Androl 19(1):11-17 (1996).
(6.) Fisch H, Goluboff ET, Olson JH, Feldshuh J, Broder SJ, Barad DH. Semen analyses in 1,283 men from the United States over a 25-year period: no decline in quality. Fertil Steril 65(5):1009-1014 (1996).
(7.) Paulsen CA, Berman NG, Wang C. Data from men in greater Seattle area reveals no downward trend in semen quality: further evidence that deterioration of semen quality is not geographically uniform. Fertil Steril 65(5):1015-1020 (1996).
(8.) Olsen GW, Bodner KM, Ramlow JM, Ross CE, Lipshultz LI. Have sperm counts been reduced 50 percent in 50 years? A statistical model revisited. Fertil Steril 63(4):887-893 (1995).
(9.) Lerchl A, Nieschlag E. Decreasing sperm counts? A critical (re)view. Exp Clin Endocrinol Diabetes 104(4):301-307 (1996).
(10.) Brake A, Krause W. Decreasing quality of semen [Letter]. Br Med J 305:1498 (1992).
(11.) Farrow S. Falling sperm quality: fact or fiction? Br Med J 309:1-2 (1994).
(12.) Bromwich P, Cohen J, Stewart I, Walker A. Decline in "sperm counts: an artefact of changed reference range of "normal"? Br Med J 309(6946):19-22 (1994).
(13.) Swan SH, Elkin EP, Fenster L. Have sperm densities declined? A reanalysis of global trend data. Environ Health Perspect 105:1228-1232 (1997).
(14.) Swan SH, Elkin EP. Declining semen quality: can the past inform the present? Bioessays 21(7):614-621 (1989).
(15.) Varnek J. Spermaens maegde. In: Spermaundersogeser ved sterililet:Med specielt henblik pa sparmiernes morfologi Aarhus, Denmark:Universitetsforlaget, 1944;42-52.
(16.) Robles GG. Estudio del liquido espermatico. Arch Peruanos Patol Clin 1:615-661 (1947).
(17.) Sturde H-C, Glowania HJ, Bohm K. Vergleichende ejaculatuntersuchungen bei mannern aus sterilen und fertilen ehen. Arch Dermatol Forsch 241:426-437 (1971).
(18.) Santomauro AG, Sciarra JJ, Varma AO. A clinical investigation of the role of the semen analysis and postcoital test in the evaluation of male infertility. Fertil Steril 23:245-251 (1972).
(19.) Bahamondes L, Abdelmassih R, Dachs JN. Survey of 185 sperm analyses of fertile men in an infertility service. Int J Androl 2:526-533 (1979).
(20.) Polakoski KL, Zahler WL, Paulson JD. Demonstration of proacrosin and quantitation of acrosin in ejaculated human spermatazoa. Fertil Steril 28(6):668-673 (1977).
(21.) Lewis EL, Brazil CK, Overstreet JW. Human sperm function in the ejaculate following vasectomy. Fertil Steril 42(6):895-898 (1984).
(22.) SAS Institute Inc. SAS/STAT User's Guide, Version 6. 4th ed. Cary, NC:SAS Institute Inc., 1989.
(23.) Rothman KJ, Greenland S. Introduction to stratified analysis. In: Modern Epidemiology. Philadelphia, PA:Lippincott-Raven, 1998;253-279.
(24.) Zavos PM, Goodpasture JC. Clinical improvements of specific seminal deficiencies via intercourse with a seminal collection device versus masturbation. Fertil Steril 51(1):190-193 (1989).
(25.) Levine RJ, Bordson BL, Mathew RM, Brown MH, Stanley JM, Star TB. Deterioration of semen quality during summer in New Orleans. Fertil Steril 49(5):900-907 (1988).
(26.) Laboratory Manual for the Examination of Human Semen and Semen-Cervical Mucus Interaction: Based on Consultations Held within the WHO Special Programme of Research, Development and Research Training in Human Reproduction. Singapore:Press Concern, 1980.
(27.) WHO Laboratory Manual for the Examination of Human Semen and Semen-Cervical Mucus Interactions. 2nd ed. Cambridge, UK:Cambridge University Press, 1987.
(28.) Makler A. The improved ten-micrometer chamber for rapid sperm count and motility evaluation. Fertil Steril 33(3):337-338 (1980).
(29.) Fisch H, Goluboff ET. Geographic variations in sperm counts: a potential cause of bias in studies of semen quality. Fertil Steril 65(5):1044-1046 (1996).
(30.) Toppari J, Larsen JC, Christiansen P, Giwercman A, Grandjean P, Guillette LJ Jr, Jegou B, Jensen TK, Jouannet P, Keiding N, et al. Male reproductive health and environmental xenoestrogens. Environ Health Perspect 104(suppl 4):741-803 (1996).
(31.) Macleod J, Gold RZ. The male factor in fertility and infertility: spermatozoan counts in 1000 men of known fertility and in 1000 cases of infertile marriage. J Urol 66:436-449 (1951).
(32.) Schwartz D, Laplanche A, Jouannet P, David G. Within-subject variability of human semen in regard to sperm count, volume, total number of spermatozoa and length of abstinence. J Reprod Fertil 57:391-395 (1979).
(33.) Magnus O, Tollefsrud A, Abyholm T, Purvis K. Effects of varying the abstinence period in the same individuals on sperm quality. Arch Androl 26:199-203 (1991).
(34.) Bergstrom R, Adami HO, Mohner M, Zatonski W, Storm H, Ekbom A, Tretli S, Teppo L, Akre O, Hakulinen T. Increase in testicular cancer incidence in six European countries: a birth cohort phenomenon. J Natl Cancer Inst 88(11):727-733 (1996).
(35.) Adami H, Bergstrom R, Mohner M, Zatonski W, Storm H, Ekbom H, Tretli S, Teppo L, Ziegler H, Rahu M Testicular cancer in nine northern European countries. Int J Cancer 59:33-38 (1994).
(36.) Sharpe RM, Skakkebaek NE. Are oestrogens involved in falling sperm counts and disorders of the male reproductive tract? Lancet 341(8857):1392-1395 (1993).
(37.) Giwercman A, Carlsen E, Keiding N, Skakkebaek NE. Evidence for increasing incidence of abnormalities of the human testis: a review. Environ Health Perspect 101(suppl 2):65-71 (1993).
(38.) Auger J, Jouannet P. Evidence for regional differences of semen quality among fertile French men. Federation Francaise des Centres d'Etude et de Conservation des Oeufs et du Sperme humains. Hum Reprod 12(4):740-745 (1997).
(39.) Aitken RJ, Best FS, Richardson DW, Djahanbakhch O, Lees MM. The correlates of fertilizing capacity in normal fertile men. Fertil Steril 38(1):68-76 (1982).
(40.) Assennato G, Paci C, Baser ME, Molinini R, Candela RG, Altamura BM, Giorgino R. Sperm count suppression without endocrine dysfunction in lead-exposed men. Arch Environ Health 42(2):124-127 (1987).
(41.) Belding DL. Fertility in the male; technique of spermatozoa count. Am J Obstet Gynecol 27:25-31 (1934).
(42.) Cooper TG, Jockenhovel F, Nieschlag E. Variations in semen parameters from fathers. Hum Reprod 6:859-866 (1991).
(43.) Cottell E, Harrison RF. The value of subcellular elemental analysis in the assessment of human spermatozoa. Hum Reprod 10(12):3186-3189 (1995).
(44.) Davidson HA. Male subfertility: interim report of 3,182 cases. Br Med J 2:1326-1332 (1949).
(45.) de Castro MP, Mastrorocco DA. Reproductive history and semen analysis in prevasectomy fertile men with and without varicocele. J Androl 5(1):17-20 (1984).
(46.) de Castro M, Jeyendran RS, Zaneveld LJ. Hypo-osmotic swelling test: analysis of prevasectomy ejaculates. Arch Androl 24(1):11-16 (1990).
(47.) Dougherty RC, Whitaker MJ, Tang SY, Bottcher R, Keller M, Kuehl DW. Sperm density and toxic substances: a potential key to environmental health hazards. In: Environmental Health Chemistry: The Chemistry of Environmental Agents of Potential Human Hazards (McKinney JD, ed). Ann Arbor, MI:Ann Arbor Science Publishers, 1981;263-278.
(48.) el Shoura SM, Abdel AM, Ali ME, el Said MM, Ali KZ, Kemeir MA, Raoof AM, Allam M, Elmalik EM. Deleterious effects of khat addiction on semen parameters and sperm ultrastructure. Hum Reprod 10(9):2295-2300 (1995).
(49.) Eskenazi B, Wyrobek AJ, Fenster L, Katz DF, Sadler M, Lee J, Hudes M, Rempel DM. A study of the effect of perchloroethylene exposure on semen quality in dry cleaning workers. Am J Ind Med 20(5):576-591 (1991).
(50.) Fariss BL, Fenner DK, Plymate SR, Brannen GE, Jacob WH, Thomason AM. Seminal characteristics in the presence of a varicocele as compared with those of expectant fathers and prevasectomy men. Fertil Steril 35(3):325-327 (1981).
(51.) Fedder J, Askjaer SA, Hjort T. Nonspermatozoal cells in semen: relationship to other semen parameters and fertility status of the couple. Arch Androl 31(2):95-103 (1993).
(52.) Figa-Talamanca I, Cini C, Varricchio GC, Dondero F, Gandini L, Lenzi A, Lombardo F, Angelucci L, Di Grezia R, Patacchioli FR. Effects of prolonged autovehicle driving on male reproduction function: a study among taxi drivers. Am J Ind Med 30(6):750-758 (1998).
(53.) Frick J, Danner C, Joos H, Kunit G, Luukkainen T. Spermatogenesis in men treated with subcutaneous application of levonorgestrel and estrone rods. J Androl 2(6):331-338 (1981).
(54.) Glass RI, Lyness RN, Mengle DC, Powell KE, Kahn E. Sperm count depression in pesticide applicators exposed to dibromochloropropane. Am J Epidemiol 109(3):346-351 (1979).
(55.) Jelnes JE. Semen quality in workers producing reinforced plastic. Reprod Toxicol 2(3-4):209-212 (1988).
(56.) Jensen TK, Giwercman A, Carlsen E, Scheike T, Skakkebaek NE. Semen quality among members of organic food associations in Zealand, Denmark [Letter]. Lancet 347(9018):1844 (1996).
(57.) Kolon TF, Philips KA, Buch JP. Custom cryopreservation of human semen. Fertil Steril 58(5):1020-1023 (1992).
(58.) Levine RJ, Brown MH, Bell M, Shue F, Greenberg GN, Bordson BL. Air-conditioned environments do not prevent deterioration of human semen quality during the summer. Fertil Steril 57(5):1075-1083 (1992).
(59.) Milby TH, Whorton D. Epidemiological assessment of occupationally related, chemically induced sperm count suppression. J Occup Med 22(2):77-82 (1980).
(60.) Nnatu SN, Giwa-Osagie OF, Essien EE. Effect of repeated semen ejaculation on sperm quality. Clin Exp Obstet Gynecol 18(1):39-42 (1991).
(61.) Noack-Fuller G, De Beer C, Seibert H. Cadmium, lead, selenium, and zinc in semen of occupationally unexposed men. Andrologia 25(1):7-12 (1993).
(62.) Ratcliffe JM, Schrader SM, Steenland K, Clapp DE, Turner T, Hornung RW. Semen quality in papaya workers with long term exposure to ethylene dibromide. Br J Ind Med 44(5):317-326 (1987).
(63.) Richardson DW, Aitken RJ, Loudon NB. The functional competence of human spermatozoa recovered after vasectomy. J Reprod Fertil 70(2):575-579 (1984).
(64.) Rogers BJ, Van Campen H, Ueno M, Lambert H, Bronson R, Hale R. Analysis of human spermatozoal fertilizing ability using zona-free ova. Fertil Steril 32(6):664-670 (1979).
(65.) Rosenberg MJ, Wyrobek AJ, Ratcliffe J, Gordon LA, Watchmaker G, Fox SH, Moore DH, Hornung RW. Sperm as an indicator of reproductive risk among petroleum refinery workers. Br J Ind Med 42(2):123-127 (1985).
(66.) Saaranen M, Suonio S, Kauhanen O, Saarikoski S. Cigarette smoking and semen quality in men of reproductive age. Andrologia 19(6):670-676 (1987).
(67.) Schrader SM, Turner TW, Breitenstein MJ, Simon SD. Longitudinal study of semen quality of unexposed workers. I. Study overview. Reprod Toxicol 2(3-4):183-190 (1988).
(68.) Shaarawy M, Mahmoud KZ. Endocrine profile and semen characteristics in male smokers. Fertil Steril 38(2):255-257 (1982).
(68.) Sheriff DS. Semen analyses in Hansen's disease. Trans R Soc Trop Med Hyg 81(1):113-114 (1987).
(70.) Sheriff DS, Legnain M. Evaluation of semen quality in a local Libyan population. Indian J Physiol Pharmacol 36(2):83-87 (1992).
(71.) Spira A. Seasonal variations of sperm characteristics. Arch Androl 12(suppl):23-28 (1984).
(72.) Stankovic H, Mikac-Devic D. Zinc and copper in human semen. Clinica Chimica Acta 70(1):123-126 (1976).
(73.) Sugkraroek P, Kates M, Leader A, Tanphaichitr N. Levels of cholesterol and phospholipids in freshly ejaculated sperm and Percoll-gradient-pelletted sperm from fertile and unexplained infertile men. Fertil Steril 55(4):820-827 (1991).
(74.) Venable JR, McClimans CD, Flake RE, Dimick DB. A fertility study of male employees engaged in the manufacture of glycerine. J Occup Med 22(2):87-91 (1980).
(75.) Vignon F, Le Faou A, Montagnon D, Pradignac A, Cranz C, Winiszewsky P, Pinget M. Comparative study of semen in diabetic and healthy men. Diabete Metab 17(3):350-354 (1991).
(76.) Vogt HJ, Heller WD, Borelli S. Sperm quality of healthy smokers, ex-smokers, and never-smokers. Fertil Steril 45(1):106-110 (1986).
(77.) Wallace EM, Gow SM, Wu FC. Comparison between testosterone enanthate-induced azoospermia and oligozoospermia in a male contraceptive study. I: Plasma luteinizing hormone, follicle stimulating hormone, testosterone, estradiol, and inhibin concentrations. J Clin Endocrinol Metab 77(1):290-293 (1993).
(78.) Wang C, Yeung KK. Use of low-dosage oral cyproterone acetate as a male contraceptive. Contraception 21(3):245-272 (1980).
(79.) Ward JB Jr, Hokanson JA, Smith ER, Chang LW, Pereira MA, Whorton EB Jr, Legator MS. Sperm count, morphology and fluorescent body frequency in autopsy service workers exposed to formaldehyde. Mutat Res 130(6):417-424 (1984).
(80.) Weidner W, Jantos C, Schiefer HG, Haidl G, Friedrich HJ. Semen parameters in men with and without proven chronic prostatitis. Arch Androl 26(3):173-183 (1991).
(81.) Weyandt TB, Schrader SM, Turner TW, Simon SD. Semen analysis of military personnel associated with military duty assignments. Reprod Toxicol 10(6):521-528 (1996).
(82.) Wickings EJ, Freischem CW, Langer K, Nieschlag E. Heterologous ovum penetration test and seminal parameters in fertile and infertile men. J Androl 4(4):261-271 (1983).
(83.) Wyrobek AJ, Watchmaker G, Gordon L, Wong K, Moore D II, Whorton D. Sperm shape abnormalities in carbaryl-exposed employees. Environ Health Perspect 40:255-265 (1981).
(84.) Wyrobek AJ, Brodsky J, Gordon L, Moore DH, Watchmaker G, Cohen EN. Sperm studies in anesthesiologists. Anesthesiology 55(5):527-532 (1981).
(85.) Zhong CQ, Lui QL, Tang YJ, Wang Y, Shi FJ, Qian SZ. Study on sperm function in men long after cessation of gossypol treatment. Contraception 41(6):617-622 (1990).
Appendix 1. Studies not included by Carlsen et al. (1).
Author (reference) Year Country
Aitden et al. (39) 1982 United Kingdom
Assennato et al. (40) 1987 Italy
Belding (41) 1934 United States
Cooper et al. (42) 1991 Germany
Cottell and Harrison (43) 1995 Ireland
Davidson (44) 1949 United Kingdom
De Castro and Mastrorocco (45) 1984 Brazil
De Castro et al. (46) 1990 Brazil
Dougherty et al. (47) 1981 United States
el Shoura et al. (48) 1995 Saudi Arabia
Eskenazi et al. (49) 1991 United States
Fariss et al. (50) 1981 United States
Fedder et al. (51) 1993 Denmark
Figa-Talamanca et al. (52) 1996 Italy
Frick et al. (53) 1981 Finland
Glass et al. (54) 1979 United States
Jelnes (55) 1988 Denmark
Jensen et al. (56) 1996 Denmark
Kolon et al. (57) 1992 United States
Levine et al. (59) 1992 United States
Milby and Whorton (59) 1980 United States
Nnatu et al. (60) 1991 Nigeria
Noack-Fuller et al. (61) 1993 Germany
Ratcliffe et al. (62) 1987 United States
Richardson et al. (63) 1984 United Kingdom
Rogers et al. (64) 1979 United States
Rosenberg et al. (65) 1985 United States
Saaranen et al. (65) 1987 Finland
Schrader et al. (67) 1988 United States
Shaarawy and Mahmoud (68) 1982 Egypt
Sheriff (69) 1987 Libya
Sheriff and Legnain (70) 1992 Libya
Spira (71) 1984 France
Stankovic and Mikac-Devic (72) 1976 Yugoslavia
Sugkraroek et al. (73) 1991 Canada
Venable et al. (74) 1980 United States
Vignon et al. (75) 1991 France
Vogt et al. (76) 1986 Germany
Wallace et al. (77) 1993 United Kingdom
Wang and Yeung (78) 1980 Hong Kong
Ward et al. (79) 1984 United States
Weidner et al. (80) 1991 Germany
Weyandt et al. (81) 1996 United States
Wickings et al. (82) 1983 Germany
Wyrobek et al. (83) 1981 United States
Wyrobek et al. (84) 1981 United States
Zhong et al. (85) 1990 China
Sample Mean sperm
Author (reference) size density
Aitden et al. (39) 35 129.30
Assennato et al. (40) 18 85.00(*)
Belding (41) 15 119.00
Cooper et al. (42) 25 94.20
Cottell and Harrison (43) 10 159.90
Davidson (44) 15 143.00
De Castro and Mastrorocco (45) 501 66.20
De Castro et al. (46) 1,890 37.00
Dougherty et al. (47) 132 83.00
el Shoura et al. (48) 50 116.04
Eskenazi et al. (49) 48 87.00
Fariss et al. (50) 112 75.00
Fedder et al. (51) 42 80.00
Figa-Talamanca et al. (52) 50 62.00
Frick et al. (53) 13 43.90
Glass et al. (54) 22 61.70
Jelnes (55) 68 70.20(*)
Jensen et al. (56) 141 69.20
Kolon et al. (57) 10 132.80
Levine et al. (59) 142 70.74
Milby and Whorton (59) 90 93.00(*)
Nnatu et al. (60) 21 64.40
Noack-Fuller et al. (61) 22 86.50
Ratcliffe et al. (62) 43 68.72
Richardson et al. (63) 47 130.60
Rogers et al. (64) 21 114.00
Rosenberg et al. (65) 71 99.20
Saaranen et al. (65) 190 141.07
Schrader et al. (67) 45 47.43
Shaarawy and Mahmoud (68) 45 77.50
Sheriff (69) 10 51.40
Sheriff and Legnain (70) 1,250 85.00
Spira (71) 52 92.30
Stankovic and Mikac-Devic (72) 67 55.20
Sugkraroek et al. (73) 20 128.50
Venable et al. (74) 63 113.53
Vignon et al. (75) 20 76.50
Vogt et al. (76) 239 62.69
Wallace et al. (77) 28 86.50
Wang and Yeung (78) 15 88.90
Ward et al. (79) 11 87.40
Weidner et al. (80) 42 52.00(*)
Weyandt et al. (81) 31 38.00
Wickings et al. (82) 25 84.70
Wyrobek et al. (83) 26 66.20
Wyrobek et al. (84) 34 128.70
Zhong et al. (85) 19 96.60
(*) Arithmetic mean estimated from median or geometric mean (see text).
Shanna H. Swan,(1) Eric P. Elkin,(2) and Laura Fenster(3)
(1) Family and Community Medicine, University of Missouri, Columbia, Missouri, USA; (2) California Public Health Institute, Berkeley, California, USA; (3) Reproductive Epidemiology Section, California Department of Health Services, Emeryville, California, USA
Address correspondence to S.H. Swan, Department of Family and Community Medicine, University of Missouri-Columbia, MA306 Medical Sciences Building, Columbia, MO 65212 USA. Telephone: (573) 882-3126. Fax: (573) 884-6172. E-mail: swans@health.missouri.edu
We thank the reviewers for their helpful suggestions.
Received 8 February 2000; accepted 1 June 2000.
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