Prior studies by ourselves and others have shown regional differences in semen parameters in recently fertile men living in diverse geographic areas in Europe and the US respectively (Jørgensen et al ., 2001 ; Swan et al ., 2003a ). We previously reported initial results from the U.S. Study for Future Families (SFF) of semen parameters in fertile men living in New York City, Los Angeles, Minneapolis and Columbia, Missouri (Swan et al ., 2003a ). Subsequently, fertile men living in Iowa City, Iowa were enrolled in SFF and provided semen samples. In this report, we present final data from SFF on the range of semen parameters observed in this cohort of recently fertile men. We also report on factors associated with time to pregnancy (TTP) for SFF couples.

Characterization of semen parameters in men is of interest for several reasons. On an individual basis, estimates of expected or typical values for semen parameters may aid couples who are having difficulty conceiving by identifying possible male factors impacting on fertility, providing prognostic information and identifying opportunities for therapeutic interventions. On a population basis, concerns have been raised about possible temporal or geographic differences in male fertility and studying these differences requires precise measurement of semen parameters observed in well‐characterized populations of men. Studies of semen parameters have typically recruited men identified on the basis of their fertility (e.g. sperm donors or male partners in infertile couples) or other self‐selected groups of men whose characteristics may not be readily extrapolated to a wider population (Auger et al ., 1995 ; Bonde et al ., 1998 ; Zinaman et al ., 2000 ; Guzick et al ., 2001 ).

The methods for collection and analyses of semen samples were previously described (Brazil et al ., 2004a ). Men were asked to observe a 2–5 day abstinence period and then provide semen samples by masturbation at study clinics. Samples were not rejected if a man deviated from the requested abstinence period, but for this analysis we arbitrarily excluded 34 men with very short (<2 h) or very long (>240 h) reported abstinence times. Almost all samples (95%) were analysed within 45 min of collection. Most men (approximately 85%) provided two samples an average of 24 days apart. Semen volume was measured by both weighing and pipetted volume and sperm concentration was determined by counting using a haemacytometer (first semen sample only) and μ‐cell disposable counting chamber (both samples if two were provided). For purposes of this analysis, we report semen parameters for men from the first semen specimen, using volume determined by weight and sperm concentration determined by haemacytometer. We have previously shown that semen quality did not differ in SFF between men who gave one or two samples (Stokes‐Riner et al ., 2007 ). Morphology was assessed both by WHO ( 1999 ) criteria (strict criteria) and by older WHO ( 1987 ) criteria in the central laboratory by two observers, one for each morphology classification as previously described (Swan et al ., 2003a ).

For all couples with a planned pregnancy, TTP was defined as the number of consecutive months, counting backwards from the LMP month, in which the effort code was 1 or greater. As the effort a couple was exerting in trying to achieve pregnancy could vary substantially between couples or even month to month for a given couple, TTP might not adequately reflect the ease or difficulty with which a couple achieved pregnancy. To try to better capture the effort required by a couple to achieve pregnancy, we also calculated a parameter ‘total effort’ as the sum of the effort scores for months with effort ≥1.

In analysing women's responses to these questions, it was apparent that in many cases couples were not consistently ‘trying to become pregnant’ or ‘trying to avoid pregnancy’ over the months leading up to the pregnancy. Therefore, in an attempt to better reflect each couple's individual practices, an algorithm was developed to categorize the couple's ‘effort’ to achieve pregnancy in each of the 13 months leading up to and including the LMP month (Appendix 1 ). Months in which a couple was judged to be actively avoiding pregnancy were assigned negative effort codes (−3 to −1); months in which a couple was judged to be actively trying to achieve pregnancy were assigned positive codes (1–3). Months in which the couple's responses were contradictory or indicated some indecision or ambivalence in achieving pregnancy were categorized as ‘undecided’ with an effort code of 0. Using the effort code for the LMP month, the study pregnancy was classified as ‘planned’ (couple was actively trying to conceive and was not trying to avoid pregnancy, effort >0), ‘unplanned’ (not actively trying to conceive and trying to avoid pregnancy, effort <0) or ‘equivocal’ (effort =0).

Participating couples completed questionnaires providing demographic data including self‐identified race/ethnicity (Hispanic or Latino; White (not Hispanic); Black; Asian; Other); lifestyle and habits; reproductive and other medical history; and occupational history. The pregnant woman provided detailed information characterizing the couples intentions and effort at achieving pregnancy for each month beginning with the last menstrual period (LMP) month of the study pregnancy and extending back for the previous 12 months prior to the LMP month. For each month, women were asked if they were (i) using oral contraceptive pills (ii) using an intrauterine device (IUD) (iii) consistently using other methods to prevent pregnancy (iv) sometime using other methods to prevent pregnancy (v) trying to get pregnant (vi) trying not to get pregnant and (vii) nursing regularly or pregnant. All responses were yes/no.

All pregnant women keeping prenatal appointments during defined recruitment sessions were potential subjects and were offered study participation. Couples were ineligible if the pregnancy was assisted, either partner was <18 years of age, either partner did not read or speak English or Spanish, father of the pregnancy was unknown or unavailable, the couple did not plan to stay in the area or the pregnancy was medically threatened.

The design and research protocol for the SFF has been previously described (Swan et al ., 2003a ; Brazil et al ., 2004a ). Briefly, pregnant women attending prenatal clinics affiliated with SFF clinical sites in Los Angeles (Harbor‐UCLA and Cedar Sinai Medical Centers); Minneapolis (University of Minnesota); Columbia, Missouri (University Physicians) and New York (Mount Sinai School of Medicine) were prospectively recruited between September, 1999 and June, 2002. In 2002, the University of Iowa (Iowa City, Iowa) was added as a fifth SFF clinical site and enrolled couples between September, 2002 and February, 2005. Owing to unforeseen circumstances, recruitment at the New York study site was low relative to the other four centres.

Table 3 shows semen parameters for White men with a planned pregnancy divided between those who exerted less or shorter effort to achieve pregnancy (total effort score <4) and those who exerted more or longer effort to achieve pregnancy (total effort score ≥4). The two groups did not differ significantly in any of the female or male demographic factors measured, with the exception that oral contraceptive use in the year prior to pregnancy was more common in women in the lower effort group (52% vs. 38%, p = 0.02). TTP was shorter in couples with lower effort scores compared with those with higher effort (3 months vs. 7 months, p < 0.0001) confirming an association between our derived effort score and the traditional TTP parameter. As shown in Table 3 , all of the measured semen parameters tended to be higher in men with lower pregnancy effort score, although only the morphology parameter, as determined by strict criteria, approached statistical significance. We also analysed semen parameters by TTP ≤ 12 months compared to >12 months and found no difference in semen parameters between these two groups (data not shown). Only 29 (8%) of couples included in Table 3 had a TTP > 12 months which limited our power to detect small differences.

We examined relationships between semen parameters and the time or effort required for a couple to achieve the study pregnancy. In a preliminary analysis, we found significant differences between racial/ethnic groups in TTP in addition to differences in some semen parameters (Table 2 ). There were also significant differences in a number of female and male demographic factors among the racial/ethnic groups, including self‐rated health status, educational level, history of contraceptive use and intercourse frequency (data not shown). Because the number of non‐White males in our sample was small, we restricted the TTP analysis to the 372 White couples with a planned pregnancy (77% of the planned pregnancy group).

Race/ethnicity varied by centre with most Hispanic/Latino men in CA and Black subjects mainly in CA and MO, whereas participants from MN, NY and IA were predominantly White. To separate the effects of race/ethnicity and centre on semen parameters, we compared total sperm count by race/ethnicity within study centre (Fig. 3 ). In this analysis, the NY centre was excluded because of small numbers. As shown in Fig. 3 , Black men had consistently lower total sperm count in all four study centres, suggesting that the differences seen were independent of study centre.

Table 2 compares semen parameters by male race/ethnicity. As only 36 men (5%) reported a race other than Hispanic/Latino, White or Black, we limited the analysis to these three groups. White men were slightly older on average and were more likely to report education beyond high school and better health status than Hispanic/Latino or Black men (data not shown). The three groups did not differ in body mass index, history of urogenital disease or smoking status (data not shown). Semen parameters were very similar between Hispanic/Latino and White men, but Black men had significantly lower values for semen volume and sperm concentration. Per cent motile spermatozoa was also slightly lower in Black men, although the difference was not statistically significant. Consequently total sperm count and total motile sperm count were almost 50% lower for Black men compared with men in the other two groups ( p < 0.0001). Morphology showed little difference by race/ethnicity. The percentage of men with semen volume, sperm concentration and total sperm count below current WHO reference values (WHO, 2010 ) was greater for Black men compared with White and Hispanic/Latino men (Appendix 2 ).

We previously reported that sperm counts were lower in men from MO compared with men living in MN, CA or NY based on an initial analysis of 512 study couples (Swan et al ., 2003a ). Analysis of the full SFF cohort confirmed this finding. Mean sperm concentrations for men living in NY, MN, IA, CA and MO were 85, 72, 62, 55 and 48 million/mL respectively ( p < 0.0001 for difference between centres). Corresponding total sperm counts were 261, 264, 244, 176 and 167 million and total motile sperm counts were 145, 135, 111, 92 and 79 million respectively ( p < 0.0001).

Semen samples were obtained on average at 26 ± 8 weeks of the female partner's pregnancy. The percentage of samples obtained in each trimester of pregnancy was 4, 46 and 50% for the first, second and third trimesters respectively. We found no difference in semen parameters by pregnancy trimester with the exception that average % normal spermatozoa (strict) was slightly higher in samples given during the first trimester (13 ± 5%) compared with samples from the second and third trimesters (11 ± 5% for each) p < 0.03.

There was no difference in semen parameters by season in which the sample was given except for strict morphology. The average % normal spermatozoa (strict) was 10% for samples given during summer months compared to 11% in each of the other seasons ( p < 0.02).

We found no difference in semen parameters between men who reported their health status as fair/poor (9% of men) compared with those who reported it as excellent/good (data not shown). Similar analysis by education level showed no difference in semen parameters between men with reported education level of high school or less (19% of men) compared with those with education level beyond high school, with the exception of semen volume. Semen volume was 3.3 ± 1.5 mL for men reporting educational level of high school or less compared to 4.0 ± 1.6 mL for men with education beyond high school ( p < 0.0001).

Table 1 shows characteristics of the study population by pregnancy category. Couples with unplanned pregnancies tended to be younger, non‐White, have lower education level and self‐reported health status, report more frequent sexual intercourse and have a male partner who smoked. Unplanned pregnancies were more common at the CA site which also had the highest percentage of non‐White couples. There were no differences in semen parameters among men in the three pregnancy categories with the exception of per cent motile spermatozoa which was slightly lower in men who fathered planned pregnancies compared with men in the equivocal pregnancy group ( p = 0.03). Mean (5th–50th to 95th percentile) values for semen parameters for the entire cohort of 763 men are shown in Table 1 . Figure 2 shows these data as the corresponding frequency distributions of the semen parameters.

Nine hundred and forty‐five couples enrolled in the study provided questionnaire data for both partners. This included 148 men (16%) who were enrolled, but declined to give a semen sample. We excluded 34 men (4%) who had a very short or very long abstinence times. As a result, there were 763 couples in the final study cohort (Fig. 1 ). Of the 763 pregnancies with complete data, 485 (64%) were classified as planned pregnancies, 186 (24%) were classified as unplanned and 92 (12%) were classified as equivocal.

Discussion

We obtained semen samples from 763 fertile men recruited as the partners of women who were currently pregnant. These men, although predominantly White, included several racial/ethnic groups and five geographic locations across the US. Our data provide robust estimates of semen parameters observed in fertile US men. Men in our cohort averaged approximately 4 mL of semen per ejaculate with 60–70 million spermatozoa/mL, sperm motility of 50% and approximately 10% of the spermatozoa showing normal morphology by strict criteria (approximately 60% by WHO, 1987 criteria).

Summary statistics for semen parameters in our study were similar to those reported by other studies of US men who were self‐selected volunteers (Zinaman et al., 2000; Guzick et al., 2001) (Table 4). SFF was designed to employ semen analysis techniques similar to those employed by Jørgensen et al. (2001) in their study of fertile men living in four European cities. Men in the SFF study had sperm counts more similar to men from Copenhagen, Denmark than men from Turku, Finland (Table 4). To the extent that differences in semen quality in European men might reflect adverse effects of environmental exposure, the SFF results might raise similar concerns about possible effects in US men as well. Consistent with this hypothesis, sperm counts were lowest in SFF men from Missouri, and in a previous report comparing a small subset of SFF men from Missouri and Minnesota we noted an association between higher levels of agricultural pesticide metabolites in urine samples and poorer semen quality in Missouri men (Swan et al., 2003b).

Table 4. Reported semen parameters in fertile men SFF US Jørgensen et al. ( 2001 Jørgensen et al. ( 2001 Zinaman et al. ( 2000 Guzick et al. ( 2001 Number of men 763 349 275 156 696 Age (years) 32 ± 6 32 ± 4 30 ± 4 32 ± 4 34 ± 5 Abstinence time (days) 3.2 (3.0) (1.5–5.3) 3.4 (2.7) 4.5 (2.9) NR NR Semen volume (mL) 3.9 (3.7) (1.5–6.8) 3.8 (3.6) (1.4–6.7) 4.1 (3.9) (2.1–7.4) 2.9 (2.8) NR Sperm concentration (×106/mL) 60 (67) (12–192) 77 (61) (10–207) 105 (82) (19–262) 67 (56) 67 (56) Total sperm count (×106) 209 (240) (32–763) 276 (215) (32–795) 412 (328) (71–1063) 178 (151) NR Motile spermatozoa (%) 51 (52) (28–67) 60 (61) (40–79) 66 (66) (49–81) 57 (58) 54 (55) Total motile sperm count (×106) 104 (128) (14–395) NR NR 104 (86) NR Normal spermatozoa – strict (%) 11 (10) (3–20) NR NR 6 (6) 14 (14) Normal spermatozoa – WHO 87 (%) 57 (59) (38–72) 49 (51) (23–71) 52 (53) (24–74) NR NR

We found significant differences in semen parameters among men of different race/ethnicity. Black men in our cohort had mean values for semen volume, sperm concentration, total sperm count and total motile sperm count that were significantly lower than White or Hispanic/Latino men. These differences did not appear to be attributable to study centre. We are not aware of previous reports of differences in semen quality by race or ethnicity, and there appear to be few data regarding semen parameters in Black and Hispanic/Latino men. Povey et al. (2012) reported that Black ethnicity was a risk factor for low motile sperm concentration in a case–control study of male partners of infertile couples. Huang, 2010 noted that current WHO reference ranges are based on men living in Australia, Europe and North America and that data on semen parameters in fertile men living outside these continents are lacking and that the possibility of ethnic differences should be considered in establishing reference ranges. As the number of Black men in our study was relatively small compared with White or Hispanic/Latino men, these results should be viewed as preliminary, but worthy of further study. If this finding is confirmed, further investigation into possible explanations for differences would be important as such differences could reflect genetic variation or possibly acquired differences owing to lifestyle or environmental exposures.

We found little difference in semen parameters between men whose partners conceived quickly and with little ‘effort’ and those who took longer to conceive. This is not surprising as all of the men in our study were fertile and traditional semen parameters are relatively poor predictors of fertility status (Guzick et al., 2001; Nallella et al., 2006). Men whose partners conceived quickly tended to have higher sperm counts and sperm morphology, but the differences were small and not statistically significant. In the aforementioned European study of fertile men, which included a larger number of fertile men than SFF, Slama et al. (2002) found an association between TTP and both morphologically normal spermatozoa and sperm concentration; however, their results also confirmed the poor predictive value of semen parameters in identifying couples who will require longer to conceive.

The most recent WHO laboratory manual for the examination and processing of human semen (WHO, 2010) recommends reference ranges for interpreting semen analysis parameters based on studies of fertile men whose partners conceived within 1 year of initiating attempts at conception (Cooper et al., 2010; WHO, 2010). Preliminary results from SFF were among the data used in the development of these reference ranges (Cooper et al., 2010). The data presented in this report of the full SFF cohort are consistent with the ranges reported in the larger WHO analysis.

A strength of our study is the large number of fertile men recruited while their partners were pregnant. SFF represents one of the largest studies to date of semen parameters in fertile men using current laboratory methodology (Bonde et al., 1998; Zinaman et al., 2000; Guzick et al., 2001; Jørgensen et al., 2001; Nallella et al., 2006; Rolland et al., 2013) and includes men from a wide geographic area within the US and a variety of racial/ethnic groups. By using a strategy of first approaching and recruiting pregnant women at study obstetrical clinics and then recruiting their partner, we likely eliminated or reduced the selection bias that might arise when men are recruited through self‐selection or at infertility clinics. Semen samples were all obtained at study sites using strict protocols under standard conditions and analysed promptly by study laboratories. This reduced the likelihood of improper collection and possible effects of delays in sample processing on semen parameters.

Another strength of our study is the rigorous training of study technicians and quality control monitoring employed during the study to ensure comparability across centres and technicians (Brazil et al., 2004a,b). Technicians performing semen analyses all received training at the study's central andrology laboratory, used common laboratory protocols, supplies and equipment and underwent quality control and proficiency testing approximately every 3 months. As previously reported, intertechnician coefficients of variation for sperm concentrations and motility from quality control testing were 15 and 10% respectively. Intratechnician coefficients of variation for these parameters were 12 and 5% respectively (Brazil et al., 2004b). Thus we feel our data accurately reflect the range of semen parameters exhibited by US fertile men using contemporary laboratory methodology.

Our study recruited recently fertile men by approaching their pregnant partners through our study prenatal clinics. Not all women agreed to participate and not all men whose partners were willing to participate agreed to the study. We do not have information on men who declined participation. However, as previously reported, women who declined participation, but provided limited questionnaire data were similar to women who agreed to participate in SFF in terms of history of fertility investigation and reported TTP (Swan et al., 2003a). Similarly, men who participated in the study, but declined to provide a semen sample were similar to men who provided a sample for a number of demographic and lifestyle factors including age, race/ethnicity and education level (Swan et al., 2003a).

The data we present are from a single semen sample collected, on average, at week 26 of pregnancy. While it is possible that the study semen analysis might not accurately reflect a man's semen quality at the time he conceived the pregnancy, stratifying the analysis by trimester of the partner's pregnancy did not suggest any clinically important differences. Approximately 85% of men in SFF provided two semen samples, but only for the first sample was sperm concentration measured by haemacytometer. However, as we have previously reported, there was little difference in semen parameters between men who gave only one sample and men who gave two, and little difference between the first and second semen samples in men who gave two samples (Stokes‐Riner et al., 2007).

In summary, SFF provides a robust estimate of the range of semen parameters exhibited by fertile men living in the US. In addition to our previous observation of differences in semen parameters by geographic location, we also found differences in some semen parameters by racial group with Black men having lower semen volume and sperm concentration than White and Hispanic/Latino men. As the number of Black men in our cohort was relatively small, this finding requires confirmation in larger studies. Semen parameters tended to be higher in men who conceived their pregnancy relatively quickly and with less ‘effort’ compared with other men; however, the differences were small and generally did not reach statistical significance. Further work is needed to understand factors which influence fertility potential in men which may not be reflected in traditional semen parameters. The results of SFF provide baseline data for future studies of semen quality in fertile US men and may also help guide physicians involved in the evaluation and care of infertile couples as they interpret semen parameters from male partners of infertile couples.