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Temporal trends in sperm count: a systematic review and meta-regression analysis of samples collected globally in the 20th and 21st centuries [1]

['Levine', 'Braun School Of Public Health', 'Community Medicine', 'Hadassah Medical Center', 'The Faculty Of Medicine', 'Hebrew University Of Jerusalem', 'Jerusalem', 'Jørgensen', 'Department Of Growth', 'Reproduction']

Date: 2023-03-01

Abstract

BACKGROUND Numerous studies have reported declines in semen quality and other markers of male reproductive health. Our previous meta-analysis reported a significant decrease in sperm concentration (SC) and total sperm count (TSC) among men from North America–Europe–Australia (NEA) based on studies published during 1981–2013. At that time, there were too few studies with data from South/Central America–Asia–Africa (SAA) to reliably estimate trends among men from these continents. OBJECTIVE AND RATIONALE The aim of this study was to examine trends in sperm count among men from all continents. The broader implications of a global decline in sperm count, the knowledge gaps left unfilled by our prior analysis and the controversies surrounding this issue warranted an up-to-date meta-analysis. SEARCH METHODS We searched PubMed/MEDLINE and EMBASE to identify studies of human SC and TSC published during 2014–2019. After review of 2936 abstracts and 868 full articles, 44 estimates of SC and TSC from 38 studies met the protocol criteria. Data were extracted on semen parameters (SC, TSC, semen volume), collection year and covariates. Combining these new data with data from our previous meta-analysis, the current meta-analysis includes results from 223 studies, yielding 288 estimates based on semen samples collected 1973–2018. Slopes of SC and TSC were estimated as functions of sample collection year using simple linear regression as well as weighted meta-regression. The latter models were adjusted for predetermined covariates and examined for modification by fertility status (unselected by fertility versus fertile), and by two groups of continents: NEA and SAA. These analyses were repeated for data collected post-2000. Multiple sensitivity analyses were conducted to examine assumptions, including linearity. OUTCOMES Overall, SC declined appreciably between 1973 and 2018 (slope in the simple linear model: –0.87 million/ml/year, 95% CI: –0.89 to –0.86; P < 0.001). In an adjusted meta-regression model, which included two interaction terms [time × fertility group (P = 0.012) and time × continents (P = 0.058)], declines were seen among unselected men from NEA (–1.27; –1.78 to –0.77; P < 0.001) and unselected men from SAA (–0.65; –1.29 to –0.01; P = 0.045) and fertile men from NEA (–0.50; –1.00 to –0.01; P = 0.046). Among unselected men from all continents, the mean SC declined by 51.6% between 1973 and 2018 (–1.17: –1.66 to –0.68; P < 0.001). The slope for SC among unselected men was steeper in a model restricted to post-2000 data (–1.73: –3.23 to –0.24; P = 0.024) and the percent decline per year doubled, increasing from 1.16% post-1972 to 2.64% post-2000. Results were similar for TSC, with a 62.3% overall decline among unselected men (–4.70 million/year; –6.56 to –2.83; P < 0.001) in the adjusted meta-regression model. All results changed only minimally in multiple sensitivity analyses. WIDER IMPLICATIONS This analysis is the first to report a decline in sperm count among unselected men from South/Central America–Asia–Africa, in contrast to our previous meta-analysis that was underpowered to examine those continents. Furthermore, data suggest that this world-wide decline is continuing in the 21st century at an accelerated pace. Research on the causes of this continuing decline and actions to prevent further disruption of male reproductive health are urgently needed.

Graphical Abstract Open in new tabDownload slide Sperm count is declining at an accelerated pace globally.

Introduction

In 2017, ‘Temporal Trends in Sperm Count: A Systematic Review and Meta-Regression Analysis’ was published by this journal (Levine et al., 2017). That article, which was widely discussed and highly cited, includes all eligible English-language publications in 1981–2013 that contained data on sperm count. We reported a very strong decline in sperm concentration (SC) and total sperm count (TSC) in North America, Europe, Australia/New Zealand (hereafter NEA) but too few studies have been published in South/Central America, Asia and Africa (hereafter SAA) to draw a conclusion about trends in those continents. We examined mean SC and TSC as a function of collection year, as approximated by the mid-year of the sample collection period. Because sample collection preceded the year of publication by an average of 6 years, our results were already somewhat dated by the time we published our analysis in 2017. Therefore, we conducted a new literature search in the spring of 2020 to identify eligible studies published between 1 January 2014 and 31 December 2019. Here, we report on global trends in SC and TSC in publications 1981 through 2019, which combines results of both searches and analyses. This expanded analysis addresses two important questions. With increased sample size, was a trend seen in South America, Africa and Asia? Did the trends we reported continue post-2011?

Recognition of the importance of male reproductive function, and sperm count, has increased since 2017 (Levine et al., 2018; United Nations Human Rights Office of the High Commissioner, 2019). The economic and societal burden of male infertility is now widely recognized, as is the unequal burden of male infertility which falls most heavily on low-income populations (Winters and Walsh, 2014; Hauser et al., 2015; Dupree, 2016; Skakkebaek et al., 2016). Increasingly strong evidence links reduced sperm count and concentration to increases in all-cause mortality and morbidity (Latif et al., 2017; Del Giudice et al., 2021; Ferlin et al., 2021). Links between sperm count and infertility are well-recognized (Bonde et al., 1998; Skakkebæk et al., 2022). Furthermore, the decline in sperm count is paralleled by declines in testosterone and increases in testicular cancer and male genital anomalies (Skakkebæk et al., 2022). In fact, the decline in semen quality and male reproductive health has recently been described as a crisis (De Jonge and Barratt, 2019). Relative to declines in sperm counts, these latter trends are far more difficult to document. There is currently no systematic collection of such data, making the examination of those trends difficult. Therefore, an international group of scientists, including several of the authors, has suggested the formation of a multidisciplinary monitoring system for reproductive health indicators that would provide ongoing surveillance of reproductive health outcomes (Le Moal et al., 2016).

The broad implications of a global decline in sperm count, the data gaps left unfilled by our prior analysis and the controversies surrounding these issues warrant an up-to-date meta-analysis. This meta-analysis was conducted to address these aims.

Methods

This systematic review and meta-regression analysis was conducted, and the results reported, in accordance with Meta-analysis in Observational Studies in Epidemiology (Stroup et al., 2000) (Supplementary Table SI) and Preferred Reporting Items for Systematic reviews and Meta-Analysis guidelines (Liberati et al., 2009; Moher et al., 2009). Our research team included epidemiologists, andrologists and a medical librarian. Our predefined protocol was developed following best practices (Borenstein et al., 2009; Higgins and Green 2011; National Toxicology Program 2015) and informed by our previous study. Throughout, unless otherwise noted, the methods of the current study are those employed and published in the previous study (Levine et al., 2017), including keywords and databases searched, eligibility criteria and statistical methods.

Systematic review and study selection

A comprehensive search of the PubMed/MEDLINE and EMBASE was conducted, to identify English-language publications that reported primary data on human sperm count, published in 2014–2019, i.e. from the last date included in our prior search through 2019. On 15 May 2020, we searched MEDLINE/PubMed and Embase (Excerpta Medica database) for peer-reviewed publications meeting our inclusion criteria. Following the recommendation of the Cochrane Handbook for Systematic Reviews, we searched in title and abstract for both index (MeSH) terms and keywords and filtered out animal-only studies. We used the MeSH term ‘sperm count’, which includes seven additional terms, and to increase sensitivity, we added 13 related keywords (e.g. ‘sperm density’, ‘sperm concentration’).

All English-language studies that reported primary data on human SC were considered eligible for abstract screening. We evaluated the eligibility of all subgroups within a study. For example, in a case–control study, the control group might have been eligible for inclusion even though, based on our exclusion criteria, the case group was not.

We divided eligible studies into two fertility-defined groups: (i) studies of men unselected by fertility status, hereafter ‘Unselected’ (e.g. young men unlikely to be aware of their fertility, such as young men being screened for military service or college students) and (ii) studies of men whose partners had born a child or whose partners were pregnant regardless of pregnancy outcome, hereafter ‘Fertile’. ‘Total’ refers to both groups.

A study was excluded if participants were selected based on: (i) infertility or sub-fertility; (ii) their range of semen parameters (e.g. studies selecting normospermic men); and (iii) genital abnormalities, diseases or medications. We also excluded studies limited to men with exposures that may affect fertility, such as an occupational exposure, post-clinical trial intervention or smoking. Studies of candidates for vasectomy or semen donation were included only if semen quality was not a criterion for men’s study participation. We excluded studies that used non-standard methods for sperm collection (e.g. methods other than masturbation) or counting methods other than hemocytometer and studies with fewer than 10 men.

First, the publication was either excluded or advanced to full-text screening based on the title and abstract. Any publication without an abstract was automatically referred for full-text screening. Second, we reviewed the full text and assigned it to exclusion (and categorized the reason for exclusion) or to data extraction. We then confirmed study eligibility and identified multiple publications from the same study to ensure that estimates from the same population were not used more than once.

Data extraction

For each estimate, we extracted summary statistics on SC and TSC (mean, standard deviation, minimum, maximum, median and percentiles), semen volume (mean and measured method), sample size, sample collection years, data on covariates (fertility group, country, age, ejaculation abstinence time reported and per protocol, method of semen collection, method of assessing of SC and semen volume, selection of population, study exclusion criteria and number of samples per man). The range of permissible values, both for categorical and numerical variables and information on data completeness were recorded. Data were extracted on the total population as well as on all eligible subgroups.

Quality control

The current study followed the same protocol as used in the previous study. For the new search, we used Covidence systematic review software for the process of screening the articles that were not available for our prior search. In addition, one member of the research team was replaced. Screening of this extensive systematic review was conducted by a team of eight reviewers (H.L., N.J., A.M.-A., J.M., D.W.-D., M.J., R.P., S.H.S.). As in our previous analysis, the screening protocol was piloted and reviewers were trained by screening of 50 abstracts by all reviewers followed by a comparison of results, resolution of any inconsistencies and clarification of the protocol as needed. The same quality control process was followed for full-text screening and data extraction by all reviewers. All data were entered into digital spreadsheets with explicit permissible values (no open-ended entries) to increase consistency. After data extraction, an additional round of data editing and quality control of all studies was conducted by H.L. and M.J. The process ensured that each study was evaluated by at least two different trained reviewers.

Statistical analysis

We ran all models both on the data used in our 2017 study (for quality control) and for the dataset including all years. In all models, the midpoint of the sample collection period was the independent variable (‘collection year’) and mean SC (or TSC) was the dependent variable(s). Units were million/ml for SC and million for TSC (reported or defined as SC × sample volume). All slopes denote unit change per calendar year, reported with 95% confidence intervals (CI). We also reported values for the first and last years, and the % change/year.

We first used simple linear regression models to estimate SC and TSC as functions of collection year, with each study weighted by sample size. Beside a model for all men (Unselected plus Fertile), we also ran a model stratified by fertility status.

Then, we used random-effects meta-regression to model both SC and TSC as linear functions of time, weighting estimates by the standard error (SE).

In the meta-regression models, we controlled for a predetermined set of potential confounders: fertility group, age, abstinence time, whether semen collection and counting methods were reported, number of samples per man and indicators for exclusion criteria (Supplementary Table SII). The method used to determine sample volume was included when modeling TSC. In all meta-regression analyses, we included indicator variables to denote studies with more than one SC/TSC estimate.

Several variables were imputed including mean SC (and TSC), as described in our 2017 study. For example, for studies that reported median (not mean) SC or TSC, we estimated the mean by adding the average difference between the mean and median in studies for which both were reported.

We included indicators in all models for imputed values. We included continental group (NEA or SAA) and fertility group (Unselected or Fertile), as variables in the model when applicable.

We ran several meta-regression models for both SC and TSC: (i) basic, unadjusted model; (ii) adjusted model for all men; (iii) stratified by fertility; (iv) unselected men only with time × continent interaction; (v) all men with two interactions: time × fertility and time × continent.

These analyses were repeated for subsets of data collection to examine recent trends (>1972, >1985, >1995 and >2000).

We conducted several sensitivity analyses: (i) adding cubic and quadratic terms for collection year in meta-regression analyses to assess non-linearity; (ii) removing covariates one at a time from the model; (iii) excluding a specific group, i.e. the group with no information on age, for each covariate; (iv) replacing age group by mean age, excluding studies that did not report mean age; (v) adding a covariate for high smoking prevalence (>30%); (iv) removing each continent one at a time; (vii) excluding studies with five or more data points to examine the influence of large studies; and (viii) removing studies with SEs >20 million/ml.

All analyses were conducted using STATA version 14.1 (StataCorp).

Results

Systematic review and summary statistics

Using PubMed/MEDLINE and Embase searches, we identified 2936 new publications meeting our criteria for abstract screening (Fig. 1). Of these, 151 duplicate records were removed and 1917 were excluded based on title or abstract screening. Full texts of the remaining 868 articles were reviewed for eligibility and 743 studies were excluded. Of the remaining 125 articles, 87 were excluded during data extraction through the second round of full-text screening; 44 of them were multiple publications. The remaining 38 studies of semen samples from 14 233 men included 44 unique mean SC estimates that met the protocol criteria. Combining these new data with data from our previous meta-analysis, the current meta-analysis includes results from 223 studies, yielding 288 estimates based on semen samples collected 1973–2018 provided by 57 168 men. Data were available from 6 continents and 53 countries (complete list in Supplementary Table SIII and Supplementary Fig. S1). Of the 288 estimates, 118 (41%) were Unselected NEA, 35 (12%) were Unselected SAA, 81 (28%) were Fertile NEA and 54 (19%) were Fertile SAA. The number of estimates from SAA increased by 29%.

Figure 1. Open in new tabDownload slide PRISMA flow chart showing the selection of studies eligible for meta-regression analysis.

Data from the 223 publications included in the meta-analysis are available upon reasonable request through contact with corresponding author (Abyholm, 1981; Fariss et al., 1981; Leto and Frensilli, 1981; Wyrobek et al., 1981a,b; Aitken et al., 1982; Nieschlag et al., 1982; Obwaka et al., 1982; Albertsen et al., 1983; Fowler and Mariano, 1983; Sultan Sheriff, 1983; Wickings et al., 1983; Asch et al., 1984; de Castro and Mastrorocco, 1984; Fredricsson and Sennerstam, 1984; Freischem et al., 1984; Ward et al., 1984; Ayers et al., 1985; Heussner et al., 1985; Rosenberg et al., 1985; Aribarg et al., 1986; Comhaire et al., 1987; Kirei, 1987; Giblin et al., 1988; Kjaergaard et al., 1988; Mieusset et al., 1988, 1995; Jockenhovel et al., 1989; Sobowale and Akiwumi, 1989; Svanborg et al., 1989; Zhong et al., 1990; Culasso et al., 1991; Dunphy et al., 1991; Gottlieb et al., 1991; Nnatu et al., 1991; Pangkahila, 1991; Weidner et al., 1991; Levine et al., 1992; Sheriff and Legnain, 1992; Ali et al., 1993; Arce et al., 1993; Bartoov et al., 1993; Fedder et al., 1993; Noack-Füller et al., 1993; World Health Organization and Task Force on Methods for the Regulation of Male Fertility, 1993; Hill et al., 1994; Rehan, 1994; Rendon et al., 1994; Taneja et al., 1994; Vanhoorne et al., 1994; Auger et al., 1995; Cottell and Harrison, 1995; Figà-Talamanca et al., 1996; Fisch et al., 1996; IrVine et al., 1996; Van Waeleghem et al., 1996; Vierula et al., 1996; Vine et al., 1996; Auger and Jouannet, 1997; Jensen et al., 1997; Lemcke et al., 1997; Handelsman, 1997a,b; Chia et al., 1998; Muller et al., 1998; Naz et al., 1998; Gyllenborg et al., 1999; Kolstad et al., 1999; Kuroki et al., 1999; Larsen et al., 1999; Purakayastha et al., 1999; Reddy and Bordekar, 1999; De Celis et al., 2000; Glazier et al., 2000; Mak et al., 2000; Selevan et al., 2000; Wiltshire et al., 2000; Zhang et al., 2000; Foppiani et al., 2001; Guzick et al., 2001; Hammadeh et al., 2001; Jørgensen et al., 2001, 2002, 2011, 2012; Kelleher et al., 2001; Lee and Coughlin, 2001; Patankar et al., 2001; Tambe et al., 2001; Xiao et al., 2001; Costello et al., 2002; Junqing et al., 2002; Kukuvitis et al., 2002; Luetjens et al., 2002; Punab et al., 2002; Richthoff et al., 2002; Danadevi et al., 2003; de Gouveia Brazao et al., 2003; Firman et al., 2003; Liu et al., 2003; Lundwall et al., 2003; Roste et al., 2003; Serra-Majem et al., 2003; Uhler et al., 2003; Xu et al., 2003; Ebesunun et al., 2004; Rintala et al., 2004; Toft et al., 2004, 2005; Bang et al., 2005; Mahmoud et al., 2005; Muthusami and Chinnaswamy, 2005; O’Donovan, 2005; Tsarev et al., 2005, 2009; Durazzo et al., 2006; Fetic et al., 2006; Giagulli and Carbone, 2006; Haugen et al., 2006; Iwamoto et al., 2006, 2013a,b; Pal et al., 2006; Yucra et al., 2006; Aneck-Hahn et al., 2007; Garcia et al., 2007; Multigner et al., 2007; Plastira et al., 2007; Rignell-Hydbom et al., 2007; Wu et al., 2007; Akutsu et al., 2008; Bhattacharya, 2008; Gallegos et al., 2008; Goulis et al., 2008; Jedrzejczak et al., 2008; Kobayashi et al., 2008; Korrovits et al., 2008; Li and Gu, 2008; Lopez-Teijon et al., 2008; Paasch et al., 2008; Peters et al., 2008; Recabarren et al., 2008; Recio-Vega et al., 2008; Saxena et al., 2008; Shine et al., 2008; Andrade-Rocha, 2009; Kumar et al., 2009, 2011; Rylander et al., 2009; Stewart et al., 2009; Vani et al., 2009, 2012; Verit et al., 2009; Engelbertz et al., 2010; Hossain et al., 2010; Ortiz et al., 2010; Rubes et al., 2010; Tirumala Vani et al., 2010; Al Momani et al., 2011; Auger and Eustache, 2011; Axelsson et al., 2011; Brahem et al., 2011; Jacobsen et al., 2011; Khan et al., 2011; Linschooten et al., 2011; Venkatesh et al., 2011; Vested et al., 2011; Absalan et al., 2012; Al-Janabi et al., 2012; Katukam et al., 2012; Mostafa et al., 2012; Nikoobakht et al., 2012; Rabelo-Junior et al., 2012; Splingart et al., 2012; Bujan et al., 2013; Girela et al., 2013; Halling et al., 2013; Ji et al., 2013; Mendiola et al., 2013; Redmon et al., 2013; Thilagavathi et al., 2013; Valsa et al., 2013; Zalata et al., 2013; Zareba et al., 2013; Huang et al., 2014; Castiglione et al., 2014; Giagulli et al., 2014; Kavitha and Malini, 2014; Liu et al., 2014; Mendiola et al., 2014; Tainio et al., 2014; Evgeni et al., 2015; Franken, 2015; Hosen et al., 2015; Layali et al., 2015; Mohammed et al., 2015; Ramzan et al., 2015; Romero-Otero et al., 2015; Tsao et al., 2015; Valsa et al., 2015; Altintas et al., 2016; Karimian and Colagar, 2016; Malić Vončina et al., 2016; Shirota et al., 2016; Malini, 2017; Mínguez-Alarcón et al., 2017; Pullar et al., 2017; Azad et al., 2018; Fanny et al., 2018; Inih et al., 2018; López-Espín et al., 2018; Lotti et al., 2018; Palani, 2018; Priskorn et al., 2018; Recio-Vega et al., 2018; Ahmed et al., 2019; Bassey et al., 2019; Dhawan et al., 2019; García Rodríguez et al., 2019; Lazzarino et al., 2019; Rodprasert et al., 2019; Antonio et al., 2020; Dias et al., 2020).

Simple linear models

Combining results from all men, SC declined steeply (slope per year –0.87 million/ml; 95% CI: –0.89 to –0.86; P < 0.001) between 1973 and 2018 when using simple linear models, unadjusted and weighted by sample size (Supplementary Table SIV, Supplementary Fig. S2). For all men combined, SC declined by 0.93% per year and overall, by 41.5% between 1973 and 2018. In a model stratified by fertility group, the slope was much steeper for Unselected (–1.23; –1.25 to –1.20; P < 0.001) than for Fertile men (–0.30; –0.33 to –0.27; P < 0.001) (Supplementary Table SIV). A similar trend was seen for TSC when combining the two fertility groups (slope per year = –2.80 million; –2.86 to –2.74; P < 0.001), and the slope was steeper for the Unselected group (–3.77; –3.83 to –3.71; P < 0.001) (Supplementary Table SIV, Supplementary Fig. S2). Semen volume did not change over the study period (slope per year = 0.0002 ml; –0.0001 to 0.0005; P = 0.249).

Meta-regression models for SC

In a basic meta-regression model for SC, in which estimates were weighted by their SE but without covariate adjustment, slopes were slightly less steep than for the simple regression model, and with wider CIs (slope per year –0.66 million/ml; 95% CI: –0.92 to –0.40; P < 0.001). Covariate adjustment did not appreciably alter the slope but widened the CI further (–0.59; –0.90 to –0.27; P < 0.001) (Table I, betas for covariates in Supplementary Table SII).

Table I Model . Category . N (estimates) . First year . First year SC (million/ml) . Last year . Last year SC (million/ml) . %change/year . Slope (95% CI), million/ml/year . Total All men 288 1973 83.5 2018 57.1 –0.71 –0.59 (–0.90 to –0.27) Stratified Unselected 153 1973 101.2 2018 49.0 –1.16 –1.17 (–1.66 to –0.68) Fertile 135 1977 77.3 2017 72.8 –0.14 –0.11 (–0.54 to 0.32) Unselected with interaction Unselected NEA b 118 1973 103.7 2015 49.1 –1.25 –1.30 (–1.89 to –0.71) Unselected SAA b 35 1986 88.3 2018 61.2 –0.96 –0.84 (–1.82 to 0.13) Two interactions Unselected NEA b 118 1973 100.3 2015 46.8 –1.27 –1.27 (–1.78 to –0.77) Unselected SAA b 35 1986 75.8 2018 54.9 –0.86 –0.65 (–1.29 to –0.01) Fertile NEA 81 1977 85.5 2017 65.1 –0.59 –0.50 (–1.00 to –0.01) Fertile SAA 54 1978 71.5 2016 76.4 0.18 0.13 (–0.42 to 0.67) Model . Category . N (estimates) . First year . First year SC (million/ml) . Last year . Last year SC (million/ml) . %change/year . Slope (95% CI), million/ml/year . Total All men 288 1973 83.5 2018 57.1 –0.71 –0.59 (–0.90 to –0.27) Stratified Unselected 153 1973 101.2 2018 49.0 –1.16 –1.17 (–1.66 to –0.68) Fertile 135 1977 77.3 2017 72.8 –0.14 –0.11 (–0.54 to 0.32) Unselected with interaction Unselected NEA b 118 1973 103.7 2015 49.1 –1.25 –1.30 (–1.89 to –0.71) Unselected SAA b 35 1986 88.3 2018 61.2 –0.96 –0.84 (–1.82 to 0.13) Two interactions Unselected NEA b 118 1973 100.3 2015 46.8 –1.27 –1.27 (–1.78 to –0.77) Unselected SAA b 35 1986 75.8 2018 54.9 –0.86 –0.65 (–1.29 to –0.01) Fertile NEA 81 1977 85.5 2017 65.1 –0.59 –0.50 (–1.00 to –0.01) Fertile SAA 54 1978 71.5 2016 76.4 0.18 0.13 (–0.42 to 0.67) Model . Category . N (estimates) . First Year . First year TSC (million) . Last year . Last year TSC (million) . %change/year . Slope (95% CI), million/year . Total All men 288 1973 297.4 2018 205.6 –0.69 –2.06 (–3.25 to –0.87) Stratified Unselected 153 1973 335.7 2018 126.6 –1.40 –4.70 (–6.56 to –2.83) Fertile 135 1977 305.8 2017 296.1 –0.08 –0.24 (–1.99 to 1.52) Unselected with interaction Unselected NEA b 118 1973 337.9 2015 125.9 –1.49 –5.05 (–7.31 to –2.79) Unselected SAA b 35 1986 263.2 2018 141.7 –1.44 –3.79 (–7.58 to –0.01) Two interactions Unselected NEA b 118 1973 350.9 2015 153.3 –1.34 –4.71 (–6.53 to –2.88) Unselected SAA b 35 1986 229.8 2018 173.0 –0.77 –1.78 (–4.10 to 0.55) Fertile NEA 81 1977 303.8 2017 219.3 –0.69 –2.09 (–3.86 to –0.32) Fertile SAA 54 1978 216.6 2016 250.2 0.40 0.87 (–1.11 to 2.85) Model . Category . N (estimates) . First Year . First year TSC (million) . Last year . Last year TSC (million) . %change/year . Slope (95% CI), million/year . Total All men 288 1973 297.4 2018 205.6 –0.69 –2.06 (–3.25 to –0.87) Stratified Unselected 153 1973 335.7 2018 126.6 –1.40 –4.70 (–6.56 to –2.83) Fertile 135 1977 305.8 2017 296.1 –0.08 –0.24 (–1.99 to 1.52) Unselected with interaction Unselected NEA b 118 1973 337.9 2015 125.9 –1.49 –5.05 (–7.31 to –2.79) Unselected SAA b 35 1986 263.2 2018 141.7 –1.44 –3.79 (–7.58 to –0.01) Two interactions Unselected NEA b 118 1973 350.9 2015 153.3 –1.34 –4.71 (–6.53 to –2.88) Unselected SAA b 35 1986 229.8 2018 173.0 –0.77 –1.78 (–4.10 to 0.55) Fertile NEA 81 1977 303.8 2017 219.3 –0.69 –2.09 (–3.86 to –0.32) Fertile SAA 54 1978 216.6 2016 250.2 0.40 0.87 (–1.11 to 2.85) Open in new tab

Table I Model . Category . N (estimates) . First year . First year SC (million/ml) . Last year . Last year SC (million/ml) . %change/year . Slope (95% CI), million/ml/year . Total All men 288 1973 83.5 2018 57.1 –0.71 –0.59 (–0.90 to –0.27) Stratified Unselected 153 1973 101.2 2018 49.0 –1.16 –1.17 (–1.66 to –0.68) Fertile 135 1977 77.3 2017 72.8 –0.14 –0.11 (–0.54 to 0.32) Unselected with interaction Unselected NEA b 118 1973 103.7 2015 49.1 –1.25 –1.30 (–1.89 to –0.71) Unselected SAA b 35 1986 88.3 2018 61.2 –0.96 –0.84 (–1.82 to 0.13) Two interactions Unselected NEA b 118 1973 100.3 2015 46.8 –1.27 –1.27 (–1.78 to –0.77) Unselected SAA b 35 1986 75.8 2018 54.9 –0.86 –0.65 (–1.29 to –0.01) Fertile NEA 81 1977 85.5 2017 65.1 –0.59 –0.50 (–1.00 to –0.01) Fertile SAA 54 1978 71.5 2016 76.4 0.18 0.13 (–0.42 to 0.67) Model . Category . N (estimates) . First year . First year SC (million/ml) . Last year . Last year SC (million/ml) . %change/year . Slope (95% CI), million/ml/year . Total All men 288 1973 83.5 2018 57.1 –0.71 –0.59 (–0.90 to –0.27) Stratified Unselected 153 1973 101.2 2018 49.0 –1.16 –1.17 (–1.66 to –0.68) Fertile 135 1977 77.3 2017 72.8 –0.14 –0.11 (–0.54 to 0.32) Unselected with interaction Unselected NEA b 118 1973 103.7 2015 49.1 –1.25 –1.30 (–1.89 to –0.71) Unselected SAA b 35 1986 88.3 2018 61.2 –0.96 –0.84 (–1.82 to 0.13) Two interactions Unselected NEA b 118 1973 100.3 2015 46.8 –1.27 –1.27 (–1.78 to –0.77) Unselected SAA b 35 1986 75.8 2018 54.9 –0.86 –0.65 (–1.29 to –0.01) Fertile NEA 81 1977 85.5 2017 65.1 –0.59 –0.50 (–1.00 to –0.01) Fertile SAA 54 1978 71.5 2016 76.4 0.18 0.13 (–0.42 to 0.67) Model . Category . N (estimates) . First Year . First year TSC (million) . Last year . Last year TSC (million) . %change/year . Slope (95% CI), million/year . Total All men 288 1973 297.4 2018 205.6 –0.69 –2.06 (–3.25 to –0.87) Stratified Unselected 153 1973 335.7 2018 126.6 –1.40 –4.70 (–6.56 to –2.83) Fertile 135 1977 305.8 2017 296.1 –0.08 –0.24 (–1.99 to 1.52) Unselected with interaction Unselected NEA b 118 1973 337.9 2015 125.9 –1.49 –5.05 (–7.31 to –2.79) Unselected SAA b 35 1986 263.2 2018 141.7 –1.44 –3.79 (–7.58 to –0.01) Two interactions Unselected NEA b 118 1973 350.9 2015 153.3 –1.34 –4.71 (–6.53 to –2.88) Unselected SAA b 35 1986 229.8 2018 173.0 –0.77 –1.78 (–4.10 to 0.55) Fertile NEA 81 1977 303.8 2017 219.3 –0.69 –2.09 (–3.86 to –0.32) Fertile SAA 54 1978 216.6 2016 250.2 0.40 0.87 (–1.11 to 2.85) Model . Category . N (estimates) . First Year . First year TSC (million) . Last year . Last year TSC (million) . %change/year . Slope (95% CI), million/year . Total All men 288 1973 297.4 2018 205.6 –0.69 –2.06 (–3.25 to –0.87) Stratified Unselected 153 1973 335.7 2018 126.6 –1.40 –4.70 (–6.56 to –2.83) Fertile 135 1977 305.8 2017 296.1 –0.08 –0.24 (–1.99 to 1.52) Unselected with interaction Unselected NEA b 118 1973 337.9 2015 125.9 –1.49 –5.05 (–7.31 to –2.79) Unselected SAA b 35 1986 263.2 2018 141.7 –1.44 –3.79 (–7.58 to –0.01) Two interactions Unselected NEA b 118 1973 350.9 2015 153.3 –1.34 –4.71 (–6.53 to –2.88) Unselected SAA b 35 1986 229.8 2018 173.0 –0.77 –1.78 (–4.10 to 0.55) Fertile NEA 81 1977 303.8 2017 219.3 –0.69 –2.09 (–3.86 to –0.32) Fertile SAA 54 1978 216.6 2016 250.2 0.40 0.87 (–1.11 to 2.85) Open in new tab

After stratifying by fertility group and adjusting for all covariates including continental group, there was a strong decline in SC among unselected men (–1.17; –1.66 to –0.68; P < 0.001) but not among fertile men (–0.11; –0.54 to 0.32; P = 0.615) (Table I, Fig. 2). Using SC model estimates of 101.2 million/ml in 1973 and 49.0 million/ml in 2018, SC declined among unselected men by 1.16% per year and 51.6% overall (Table I).

Figure 2. Open in new tabDownload slide Meta-regression models for mean sperm concentration (SC) and total sperm count (TSC) by collection year among unselected men from all continents, adjusted for potential confounders, for the whole period and restricted to studies post 2000. (a) Sperm concentration. (b) Total sperm count. Meta-regression model weighted by sperm concentration (SC) SE, adjusted for continents, age, abstinence time, semen collection method reported, counting method reported, having more than one sample per man, indicators for study selection of population and exclusion criteria (some vasectomy candidates, some semen donor candidates, exclusion of men with chronic diseases, exclusion by other reasons not related to fertility, selection by occupation not related to fertility), whether collection year was estimated, whether arithmetic mean of SC was estimated, whether SE of SC was estimated and indicator variable to denote studies with more than one estimate. Total sperm count (TSC) meta-regression models weighted by TSC SE, adjusted for similar covariates and method used to assess semen volume. SE, standard error.

In an adjusted meta-regression model among unselected men that included interaction by geographic group (P for interaction = 0.44), the slope for Unselected NEA was –1.30 (–1.89 to –0.71; P < 0.001) and the slope for Unselected SAA was –0.84 (–1.82 to 0.13, P = 0.088) (Table I, Fig. 3).

Figure 3. Open in new tabDownload slide Meta-regression models for mean sperm concentration (SC) and total sperm count (TSC) by collection year with interaction for continents among unselected men, adjusted for potential confounders. (a) Sperm concentration (SC). (b) Total sperm count. NEA, North America–Europe–Australia; SAA, South/Central America–Asia–Africa. Meta-regression model weighted by sperm concentration (SC) SE, adjusted for continents, age, abstinence time, semen collection method reported, counting method reported, having more than one sample per man, indicators for study selection of population and exclusion criteria (some vasectomy candidates, some semen donor candidates, exclusion of men with chronic diseases, exclusion by other reasons not related to fertility, selection by occupation not related to fertility), whether collection year was estimated, whether arithmetic mean of SC was estimated, whether SE of SC was estimated and indicator variable to denote studies with more than one estimate. Total sperm count (TSC) meta-regression models weighted by TSC SE, adjusted for similar covariates and method used to assess semen volume. SE, standard error.

In an adjusted meta-regression model, which included all men and two interaction terms [time × fertility group (P = 0.012) and time × continents (P = 0.058)], declines were seen among Unselected NEA (–1.27; –1.78 to –0.77; P < 0.001), Unselected SAA (–0.65; –1.29 to –0.01; P = 0.045) and Fertile NEA (–0.50; –1.00 to –0.01; P = 0.046) (Table I, Supplementary Fig. S3).

Meta-regression models for TSC

Overall, TSC trends were similar to those for SC. In an adjusted meta-regression model for all men, there was a steep decline in TSC (slope per year –2.06 million, –3.25 to –0.87; P = 0.001) (Table I).

After stratifying by fertility group and adjusting for all covariates including continent, there was a strong decline in TSC among unselected men (–4.70; –6.56 to –2.83; P < 0.001) but not among fertile men (–0.24; –1.99 to 1.52; P = 0.788) (Table I, Fig. 2). Using TSC model estimates of 335.7 million in 1973 and 126.6 million in 2018, TSC declined among unselected men by 1.40% per year and 62.3% overall (Table I).

In an adjusted meta-regression model among unselected men, including interaction by geographic group (P for interaction = 0.44), the slope for Unselected NEA was –5.05 (–7.31 to –2.79; P < 0.001) and the slope for Unselected SAA was –3.79 (–7.58 to –0.01, P = 0.049) (Table I, Fig. 3).

In an adjusted meta-regression model, which included all men and two interaction terms [time × fertility group (P = 0.013) and time × continents (P = 0.015)], declines were seen among Unselected NEA (–4.71; –6.53 to –2.88; P < 0.001), Unselected SAA (–1.78; –4.10 to 0.55; P = 0.133) and Fertile NEA (–2.09; –3.86 to –0.32; P = 0.021) (Table I, Supplementary Fig. S3).

Meta-regression models for recent periods

We also restricted the analysis of unselected men (in all continents) to recent time intervals (Table II, Fig. 2). Post-1995, the slope for SC was somewhat steeper (–1.33; –2.41 to –0.26; P = 0.016) and was steeper still post-2000 (–1.73; –3.23 to –0.24; P = 0.024). There was a marked increase in the percent decline in SC per year in the recent period, from 1.16% post-1972 to 2.64% post-2000 (Fig. 4). Post-2000, the slope for TSC (–5.26, –10.72 to 0.19; P = 0.058) was also steeper than that for post-1972 (Table II, Fig. 2).

Figure 4. Open in new tabDownload slide Percent of decline according to periods, for mean sperm concentration (SC) and total sperm count (TSC) among unselected men using stratified meta-regression model. Stratified meta-regression model weighted by sperm concentration (SC) SE, adjusted for continents, age, abstinence time, semen collection method reported, counting method reported, having more than one sample per man, indicators for study selection of population and exclusion criteria (some vasectomy candidates, some semen donor candidates, exclusion of men with chronic diseases, exclusion by other reasons not related to fertility, selection by occupation not related to fertility), whether collection year was estimated, whether arithmetic mean of SC was estimated, whether SE of SC was estimated and indicator variable to denote studies with more than one estimate. Total sperm count (TSC) stratified meta-regression models weighted by TSC SE, adjusted for similar covariates and method used to assess semen volume. SE, standard error.

Table II Period (years) . N (estimates) . First year . First year SC (million/ml) . Last year . Last year SC (million/ml) . % change/year . Slope (95% CI), million/ml/year . >1972 153 1973 101.2 2018 49.0 –1.16 –1.17 (–1.66 to –0.68) >1985 131 1985 82.3 2018 47.1 –1.31 –1.08 (–1.68 to –0.49) >1995 89 1995 70.1 2018 40.1 –1.90 –1.33 (–2.41 to –0.26) >2000 60 2000 65.6 2018 35.3 –2.64 –1.73 (–3.23 to –0.24) Period (years) . N (estimates) . First year . First year SC (million/ml) . Last year . Last year SC (million/ml) . % change/year . Slope (95% CI), million/ml/year . >1972 153 1973 101.2 2018 49.0 –1.16 –1.17 (–1.66 to –0.68) >1985 131 1985 82.3 2018 47.1 –1.31 –1.08 (–1.68 to –0.49) >1995 89 1995 70.1 2018 40.1 –1.90 –1.33 (–2.41 to –0.26) >2000 60 2000 65.6 2018 35.3 –2.64 –1.73 (–3.23 to –0.24) Period (years) . N (estimates) . First year . First year TSC (million) . Last year . Last year TSC (million) . % change/year . Slope (95% CI), million/year . >1972 153 1973 335.7 2018 126.6 –1.40 –4.70 (–6.56 to –2.83) >1985 131 1985 275.2 2018 105.6 –1.90 –5.22 (–7.62 to –2.82) >1995 89 1995 231.1 2018 138.5 –1.78 –4.11 (–8.21 to –0.02) >2000 60 2000 212.1 2018 120.0 –2.48 –5.26 (–10.72 to 0.19) Period (years) . N (estimates) . First year . First year TSC (million) . Last year . Last year TSC (million) . % change/year . Slope (95% CI), million/year . >1972 153 1973 335.7 2018 126.6 –1.40 –4.70 (–6.56 to –2.83) >1985 131 1985 275.2 2018 105.6 –1.90 –5.22 (–7.62 to –2.82) >1995 89 1995 231.1 2018 138.5 –1.78 –4.11 (–8.21 to –0.02) >2000 60 2000 212.1 2018 120.0 –2.48 –5.26 (–10.72 to 0.19) Open in new tab

Table II Period (years) . N (estimates) . First year . First year SC (million/ml) . Last year . Last year SC (million/ml) . % change/year . Slope (95% CI), million/ml/year . >1972 153 1973 101.2 2018 49.0 –1.16 –1.17 (–1.66 to –0.68) >1985 131 1985 82.3 2018 47.1 –1.31 –1.08 (–1.68 to –0.49) >1995 89 1995 70.1 2018 40.1 –1.90 –1.33 (–2.41 to –0.26) >2000 60 2000 65.6 2018 35.3 –2.64 –1.73 (–3.23 to –0.24) Period (years) . N (estimates) . First year . First year SC (million/ml) . Last year . Last year SC (million/ml) . % change/year . Slope (95% CI), million/ml/year . >1972 153 1973 101.2 2018 49.0 –1.16 –1.17 (–1.66 to –0.68) >1985 131 1985 82.3 2018 47.1 –1.31 –1.08 (–1.68 to –0.49) >1995 89 1995 70.1 2018 40.1 –1.90 –1.33 (–2.41 to –0.26) >2000 60 2000 65.6 2018 35.3 –2.64 –1.73 (–3.23 to –0.24) Period (years) . N (estimates) . First year . First year TSC (million) . Last year . Last year TSC (million) . % change/year . Slope (95% CI), million/year . >1972 153 1973 335.7 2018 126.6 –1.40 –4.70 (–6.56 to –2.83) >1985 131 1985 275.2 2018 105.6 –1.90 –5.22 (–7.62 to –2.82) >1995 89 1995 231.1 2018 138.5 –1.78 –4.11 (–8.21 to –0.02) >2000 60 2000 212.1 2018 120.0 –2.48 –5.26 (–10.72 to 0.19) Period (years) . N (estimates) . First year . First year TSC (million) . Last year . Last year TSC (million) . % change/year . Slope (95% CI), million/year . >1972 153 1973 335.7 2018 126.6 –1.40 –4.70 (–6.56 to –2.83) >1985 131 1985 275.2 2018 105.6 –1.90 –5.22 (–7.62 to –2.82) >1995 89 1995 231.1 2018 138.5 –1.78 –4.11 (–8.21 to –0.02) >2000 60 2000 212.1 2018 120.0 –2.48 –5.26 (–10.72 to 0.19) Open in new tab

Sensitivity analyses

We performed multiple analyses to examine the sensitivity of results to assumptions about our model, linearity, influence of covariates and imputation of missing data. Results from sensitivity analyses are only shown here for SC in unselected men (slope = –1.17 million/ml/year in the main model). In all sensitivity analyses (except one elaborated hereafter), there was a strong (>1.0 million/ml/year) decline in SC in the Unselected group, with P < 0.01.

Adding a quadratic or cubic function of year to meta-regression model did not substantially change the association between year and SC or improve the model fit: coefficient for the quadratic term: 0.04; 95% CI: –0.07 to 0.08, P = 0.135; for the cubic term 0.0005; 95% CI: –0.0007 to 0.001, P = 0.086).

For each covariate, we conducted two sensitivity analyses: (i) removing the covariate and (ii) by excluding a specific group, for each covariate (Supplementary Table SV). Excluding 47 estimates with no data on mean age and adjusting for mean age instead of age group, yielded a slope of –1.27 million/ml/year (–1.86 to –0.68; P < 0.001), which is similar to the main model. The sensitivity analysis which showed a more than minimal change in slope was the exclusion of 39 estimates with no information on age, which yielded a slightly diminished slope of –0.94 million/ml/year (–1.51 to –0.37, P = 0.002).

The proportion of smokers was reported in only 26.0% of studies and in 18.1% of studies of unselected men. To examine this variable, we ran a sensitivity analysis including a covariate for ‘high proportion of smokers’ (> 30%), and the slopes changed only slightly (–1.20 million/ml, –1.70 to –0.71; P < 0.001).

Results for Unselected men did not materially change with additional sensitivity analysis, by exclusion of estimates from any specific continent (Supplementary Table SVI). Slopes were also robust after excluding the four studies with five or more data points (–1.04, –1.55 to –0.53; P < 0.001), or excluding five estimates with a SE of SC > 20 million/ml (−1.11, –1.61 to –0.62; P < 0.001).

Due to a typo in the value extracted for Rubes et al. (2010) in the previous meta-analysis, we repeated the analysis without this study as well as with the corrected value. The results did not materially change.

Discussion

The results of the present study extend those of our 2017 meta-analysis. As further elaborated below, the new data allow for new analyses and new results. We provide strong evidence, for the first time, of a decline in sperm counts among men from South/Central America, Asia, and Africa, as well as a world-wide decline in the 21st century, with data suggesting that the pace of this decline has accelerated.

Key findings

In our prior systematic review and meta-analysis (Levine et al., 2017), we reported a marked, continuing decline in both SC and TSC in North America, Europe and Australia based on samples collected between 1973 and 2011. What is new in the current analysis?

Our current analysis, the largest ever to examine temporal trends in sperm counts, extends both the study period and the number of estimates. This new analysis includes seven additional years of sample collection and adds 44 estimates to the 244 included in the earlier analysis. It is therefore both more robust and more temporally relevant.

The distribution of contributing countries has changed since our 2017 analysis. The new analysis appreciably increases the number of studies from SAA. With this increase in sample size, there is now adequate power to examine trends in SC and TSC in those continents. This analysis provides strong evidence, for the first time, of an appreciable decline in sperm counts among unselected men from SAA. Importantly, this analysis also demonstrates an accelerated decline in SC and TSC post-2000. In summary, this update confirms, extends and strengthens the results of our 2017 analysis.

Comparison to prior studies

Table III compares basic characteristics and results of the current study with those of Carlsen et al. (1992), Swan et al. (2000) and Levine et al. (2017), studies that together include data collected over more than 80 years. It is notable that although search and statistical analysis methods have become more sophisticated, and the distribution of studies has changed (with the proportion from SAA increasing), these slopes are remarkably consistent.

Comparing the current analysis with Levine et al. (2017), we note that the methods for searching and screening the literature, which are well documented in both, have not changed, nor have the analytic methods.

In both our current and past analyses, we excluded studies that selected men based on criteria that were likely to affect sperm count (e.g. requiring a minimum sperm count, or men’s participation in a sperm bank) with one exception. Studies of fertile men were included as a separate stratum (denoted Fertile). This group of studies includes fathers or partners of pregnant women. Thus, these men had either themselves helped to conceive a pregnancy, or the pregnancy was the result of in vitro fertilization (IVF). The proportion of IVF births has increased over the study period of this analysis, with eight million IVF babies born worldwide since the world’s first IVF birth in 1978 (European Society of Human Reproduction and Embryology, 2018). Among the 135 studies categorized as Fertile in this analysis, only 27.4% explicitly excluded pregnancies conceived by IVF.

Here, as in our 2017 analysis, we stratified countries into two groups, because of the potential for confounding of trends by geography. In the past, we referred to these two groups of countries as ‘Western’ and ‘Other’. Though not our intent, it became apparent that these terms had the potential to be misinterpreted and become politicized. Therefore, we now refer to these two groups of studies by the continent in which data were collected: ‘NEA’ (North America, Europe, and Australia) and ‘SAA’ (South/Central America, Africa, and Asia). We present results stratified by continental group, as well as combined.

Other issues

Could the declines we report be simply the result of a random decrease in a pattern of fluctuations (termed ‘sperm variability’) (Boulicault et al., 2021)? The continued decline demonstrated in this, and earlier, meta-analyses provide strong evidence that this is not the case. If, in fact, the declines we are reporting were merely the result of random fluctuation in sperm count, we would expect, on average, some percent of studies to report no change and the remainder to report (approximately) an equal number of increases and decreases. The literature does not support this (Jørgensen et al., 2021; Aitken, 2022).

While sperm count is an imperfect proxy for fertility, SC and TSC are closely linked to fertility chances (Guzick et al., 2001). The relationship between SC and time to conception is nonlinear. Thus, past a threshold of 40–50 million/ml, a higher SC does not necessarily imply a higher probability of conception. On the other hand, below that threshold, the probability of conception drops off rapidly as SC declines (Bonde et al., 1998). On a population level, the drop in mean SC from 104 to 49 million/ml that we report here implies a substantial increase in the proportion of men with delayed time to conception. Thus, SC provides the most stable and reliable measurement for comparisons within and among populations and over time.

Strengths

In this study, as in Levine et al. (2017), we used written protocols and extensive quality control procedures that minimized potential information and selection bias in all steps of the study. Further strengths of this study include our complete and documented literature search, the review of all retrieved articles by two members of the study team, and the use of current meta-analytic methods. All estimates were weighted by the SE of the measurement and all assumptions were examined in sensitivity analyses. In this study, we re-ran all steps of the prior meta-analyses on the larger, combined data set, as well as on the newly retrieved publications.

Our large number of studies and data points allowed us to control for a pre-determined set of covariates as well as for modification by fertility status and geographic group and variables indicating data completeness and study exclusion criteria.

The methods we used for the systematic literature review and meta-analysis are the most current and widely accepted by the scientific community.

Limitations

We analyzed sperm count (SC and TSC) but not sperm motility and morphology. Interpreting trends in sperm motility and morphology is difficult, since methods have changed markedly over the study period, However, methods for measuring SC have remained largely unchanged. Counting by hemocytometer is the classical way to assess SC and has been recommended by the World Health Organization in all versions of organizations semen analysis manuals (Wang et al., 2022).

If no counting method was stated or use of a method other than hemocytometer was reported, the study was excluded. Overall, 334 studies were excluded because a method other than hemocytometer was used, while 128 studies were excluded because no sperm count method was provided. Of the 288 estimates for SC and TSC included, about half (146) were from studies that stated explicitly that a hemocytometer was used. The remaining 142 estimates were from studies that used World Health Organization methods without naming the particular type of hemocytometer used. We included both groups of studies in our analyses together with a variable indicating whether hemocytometer had been named explicitly as the counting method. In the sensitivity analyses, none of the slopes changed appreciably if we restricted the analysis to studies in which hemocytometer was named as the counting method or if this indicator variable was removed from the model.

Complete elimination of all selection/recruitment bias is impossible, since it is not possible to collect semen samples at random. However, we minimized recruitment bias by evaluating recruitment methods in all included studies. As stated in Methods, studies which selected men based on any variable known to affect sperm count were not eligible. This includes studies that selected men based on a semen parameter, a condition associated with a semen parameter (such as varicocele), or an exposure or occupation associated with semen quality. However, we did include ‘Fertile’ men as a separate group, even though this is a selected group. Compared to unselected men, the slope for fertile men was more modest than that for unselected men from NEA, and no decline was seen among fertile men from SAA. Men classified as ‘fertile’ are problematic in several ways. First, they include both those whose partner has conceived without medical assistance and with medical assistance, the fraction of which varied by time and location. Second, men with lower semen quality are underrepresented among fertile men. Changes in the proportion of fertile men in the population over time could lead to a selection bias in the Fertile group. In contrast, the Unselected group is not prone to such selection bias.

It is also possible that men providing a semen sample differ from those who do not. We previously studied this important question by comparing testosterone and Inhibin B levels in unselected men (potential military recruits undergoing a compulsory routine physical exam to determine their fitness for military service) who agreed to deliver a semen sample to those in men who only agreed to give a blood sample. In both groups of men, the hormone levels were similar (Andersen et al., 2000). Therefore, recruitment bias is unlikely in studies of unselected men.

As in our prior analysis, we included only English-language publications, which was unavoidable given the size of the task and the limited size of our study team. However, of the 2936 publications identified through our database searches in 2020, only 49 were excluded because of language.

In addition, it would be interesting to explore trends in sperm count in a specific continent or even within countries and sub-populations. However, we had inadequate statistical power to examine this question at a finer geographic level. Repeated studies on semen quality in specific populations would complement the current study by providing information about local trends.

Conclusion and wider implications

Our new data and analyses confirm our prior findings of an appreciable decline in sperm count between 1973 and 2018 among men from North America, Europe and Australia and support a decline among unselected men from South/Central America, Africa and Asia. This decline has continued, as predicted by our prior analysis, and has become steeper since 2000. This substantial and persistent decline is now recognized as a significant public health concern. In 2018, a group of leading clinicians and scientists called for governments to acknowledge decreased male fertility as a major public health problem and to recognize the importance of male reproductive health for the survival of the human (and other) species (Levine et al., 2018). Research on the causes of this continuing decline and an immediate focused response to prevent further disruption of male reproductive health are needed.

We hope that the new evidence provided here will receive attention not only from clinicians and scientists, but also from decision-makers and the general public.

Supplementary data

Supplementary data are available at Human Reproduction Update online.

Data availability

The data underlying this article will be shared on reasonable request to the corresponding author.

Acknowledgements

We thank Alexandria Albert for her assistance in the literature review.

Authors’ roles

H.L. had full access to all the data and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: H.L. and S.H.S. Search strategy design and execution: H.L. and R.P. Acquisition, analysis or interpretation of data: H.L., N.J., A.M.-A., J.M., D.W.-D., M.J., R.P. and S.H.S. Drafting of the manuscript: H.L., S.H.S. and M.J. Critical revision of the manuscript for important intellectual content: H.L., N.J., A.M.-A, J.M., D.W.-D., M.J., R.P. and S.H.S. Statistical analysis: H.L. and M.J. Administrative, technical or material support: H.L., R.P., S.H.S. and M.J. Study supervision: H.L. and S.H.S.

Funding

We gratefully acknowledge financial support from The Grantham Foundation for the Protection of the Environment. None of the funding sources played a role in the design and conduct of the study; collection, management, analysis and interpretation of the data; preparations, review or approval of the manuscript; or decision to submit the manuscript for publication. Anderson Martino-Andrade is a scholarship recipient from the National Council for Scientific and Technological Development (CNPq, Brazil).

Conflict of interest

All authors declare they have no conflict of interest.

References

Abyholm T. An andrological study of 51 fertile men . Int J Androl 1981 ; 4 : 646 – 656 . Ahmed FK , Memon AS , Khan AM , Burney I , Bano K. Effect of BMI on semen parameters in male infertility in tertiary care hospital of Karachi . Natl Editor Advis Board 2019 ; 30 : 104 . Aitken RJ , Best FS , Richardson DW , Djahanbakhch O , Lees MM. The correlates of fertilizing capacity in normal fertile men . Fertil Steril 1982 ; 38 : 68 – 76 . Aitken RJ. The changing tide of human fertility . Hum Reprod 2022 ; 37 : 629 – 638 . Akutsu K , Takatori S , Nozawa S , Yoshiike M , Nakazawa H , Hayakawa K , Makino T , Iwamoto T. Polybrominated diphenyl ethers in human serum and sperm quality . Bull Environ Contam Toxicol 2008 ; 80 : 345 – 350 . Al-Janabi AS , Al-Mehdawi FA , Al-Lami MQ. Relationship of seminal biochemical parameters and serum reproductive hormones with sperm function tests in asthenospermic patients . Jordan Med J 2012 ; 46 : 97 – 107 . Al Momani W , Abu Shaqra QM , Wahed AA. Relationship between the recovery of aerobic bacteria from semen and male infertility in Jordan . Jordan Med J 2011 ; 45 : 62 – 69 . Albertsen PC , Chang TS , Vindivich D , Robinson JC , Smyth JW. A critical method of evaluating tests for male infertility . J Urol 1983 ; 130 : 467 – 475 . Ali ST , Shaikh RN , Siddiqi NA , Siddiqi PQ. Semen analysis in insulin-dependent/non-insulin-dependent diabetic men with/without neuropathy . Arch Androl 1993 ; 30 : 47 – 54 . Altintas R , Ediz C , Celik H , Camtosun A , Tasdemir C , Tanbek K , Tekin S , Colak C , Alan C. The effect of varicocoelectomy on the relationship of oxidative stress in peripheral and internal spermatic vein with semen parameters . Andrology 2016 ; 4 : 442 – 446 . Andersen AA , Jørgensen N , Andersson A , Skakkebæk NE , Jensen TK , Keiding N , Swan SH , Berg G. Serum levels of testosterone do not provide evidence of selection bias in studies of male reproductive health . Epidemiology 2000 ; 11 : 232 – 234 . Andrade-Rocha FT. Colonization of Gardnerella vaginalis in semen of infertile men: prevalence, influence on sperm characteristics, relationship with leukocyte concentration and clinical significance . Gynecol Obstet Invest 2009 ; 68 : 134 – 136 . Aneck-Hahn NH , Schulenburg GW , Bornman MS , Farias P , de Jager C. Impaired semen quality associated with environmental DDT exposure in young men living in a malaria area in the Limpopo Province, South Africa . J Androl 2007 ; 28 : 423 – 434 . Antonio L , Priskorn L , Nordkap L , Bang AK , Jensen TK , Skakkebaek NE , Petersen JH , Vanderschueren D , Jørgensen N. Bone mineral density is preserved in men with idiopathic infertility . Andrology 2020 ; 8 : 315 – 322 . Arce JC , De Souza MJ , Pescatello LS , Luciano AA. Subclinical alterations in hormone and semen profile in athletes . Fertil Steril 1993 ; 59 : 398 – 404 . Aribarg A , Kenkeerati W , Vorapaiboonsak V , Leepipatpaiboon S , Farley TM. Testicular volume, semen profile and serum hormone levels in fertile Thai males . Int J Androl 1986 ; 9 : 170 – 180 . Asch RH , Fernandez EO , Siler-Khodr TM , Pauerstein CJ. Peptide and steroid hormone concentrations in human seminal plasma . Int J Fertil 1984 ; 29 : 25 – 32 . Auger J , Eustache F. Second to fourth digit ratios, male genital development and reproductive health: a clinical study among fertile men and testis cancer patients . Int J Androl 2011 ; 34 : e49 – e58 . 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 1997 ; 12 : 740 – 745 . 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 1995 ; 332 : 281 – 285 . Axelsson J , Rylander L , Rignell-Hydbom A , Giwercman A. No secular trend over the last decade in sperm counts among Swedish men from the general population . Hum Reprod 2011 ; 26 : 1012 – 1016 . Azad N , Nazarian H , Nazari L , Novin MG , Piryaei A , Heidari MH , Farahani RM , Sadjadpour SS. Evaluation of PAWP and PLCζ expression in infertile men with previous ICSI fertilization failure . Urol J 2018 ; 15 : 38 – 43 . Ayers JW , Komesu Y , Romani T , Ansbacher R. Anthropomorphic, hormonal, and psychologic correlates of semen quality in endurance-trained male athletes . Fertil Steril 1985 ; 43 : 917 – 921 . Bang AK , Carlsen E , Holm M , Petersen JH , Skakkebaek NE , Jorgensen N. A study of finger lengths, semen quality and sex hormones in 360 young men from the general Danish population . Hum Reprod 2005 ; 20 : 3109 – 3113 . Bartoov B , Eltes F , Pansky M , Lederman H , Caspi E , Soffer Y. Estimating fertility potential via semen analysis data . Hum Reprod 1993 ; 8 : 65 – 70 . Bassey IE , , Isong KP , , Esiere KUS , , Essien OE , , Udoh AE , , Akpan UO. Seminal Oxidative Stress Markers, Calcium, Magnesium, and Semen Profile of Infertile Diabetic and Nondiabetic Nigerian Men . Int J Appl Basic Med Res 2019 ; 9 : 159 – 164 . Bhattacharya SM. Association of various sperm parameters with unexplained repeated early pregnancy loss–which is most important? Int Urol Nephrol 2008 ; 40 : 391 – 395 . Bonde JP , Ernst E , Jensen TK , Hjollund NH , Kolstad H , Henriksen TB , Scheike T , Giwercman A , Olsen J , Skakkebaek NE. Relation between semen quality and fertility: a population-based study of 430 first-pregnancy planners . Lancet 1998 ; 352 : 1172 – 1177 . Borenstein M , Hedges LV , Higgins J , Rothstein HR. Introduction to Meta-Analysis . Chichester : Wiley , 2009 . Boulicault M , Perret M , Galka J , Borsa A , Gompers A , Reiches M , Richardson S. The future of sperm: a biovariability framework for understanding global sperm count trends . Hum Fertil 2021 ; 9 : 1 – 15 . Brahem S , Mehdi M , Elghezal H , Saad A. The effects of male aging on semen quality, sperm DNA fragmentation and chromosomal abnormalities in an infertile population . J Assist Reprod Genet 2011 ; 28 : 425 – 432 . Bujan L , Walschaerts M , Moinard N , Hennebicq S , Saias J , Brugnon F , Auger J , Berthaut I , Szerman E , Daudin M et al. Impact of chemotherapy and radiotherapy for testicular germ cell tumors on spermatogenesis and sperm DNA: a multicenter prospective study from the CECOS network . Fertil Steril 2013 ; 100 : 673 – 680 . Carlsen E , , Giwercman A , , Keiding N , , Skakkebaek NE. Evidence for decreasing quality of semen during past 50 years . Br Med J 1992 ; 305 : 609 – 613 . Chia SE , Tay SK , Lim ST. What constitutes a normal seminal analysis? Semen parameters of 243 fertile men . Hum Reprod 1998 ; 13 : 3394 – 3398 . Castiglione R , Salemi M , Vicari LO , Vicari E. Relationship of semen hyperviscosity with IL-6, TNF-α, IL-10 and ROS production in seminal plasma of infertile patients with prostatitis and prostato-vesiculitis . Andrologia 2014 ; 46 : 1148 – 1155 . Comhaire FH , Vermeulen L , Schoonjans F. Reassessment of the accuracy of traditional sperm characteristics and adenosine triphosphate (ATP) in estimating the fertilizing potential of human semen in vivo . Int J Androl 1987 ; 10 : 653 – 662 . Costello MF , Sjoblom P , Haddad Y , Steigrad SJ , Bosch EG. No decline in semen quality among potential sperm donors in Sydney, Australia, between 1983 and 2001 . J Assist Reprod Genet 2002 ; 19 : 284 – 290 . Cottell E , Harrison RF. The value of subcellular elemental analysis in the assessment of human spermatozoa . Hum Reprod 1995 ; 10 : 3186 – 3189 . Culasso F , Lenzi A , Favilli S , Dondero F. Statistical analysis in andrology . Arch Androl 1991 ; 26 : 163 – 172 . Danadevi K , Rozati R , Reddy PP , Grover P. Semen quality of Indian welders occupationally exposed to nickel and chromium . Reprod Toxicol 2003 ; 17 : 451 – 456 . de Castro MP , Mastrorocco DA. Reproductive history and semen analysis in prevasectomy fertile men with and without varicocele . J Androl 1984 ; 5 : 17 – 20 . De Celis R , Feria-Velasco A , Gonzalez-Unzaga M , Torres-Calleja J , Pedron-Nuevo N. Semen quality of workers occupationally exposed to hydrocarbons . Fertil Steril 2000 ; 73 : 221 – 228 . de Gouveia Brazao CA , Pierik FH , Erenpreiss Y , de Jong FH , Dohle GR , Weber RF. The effect of cryptorchidism on inhibin B in a subfertile population . Clin Endocrinol (Oxf) 2003 ; 59 : 136 – 141 . De Jonge C , Barratt CLR. The present crisis in male reproductive health: an urgent need for a political, social, and research roadmap . Andrology 2019 ; 7 : 762 – 768 . Del Giudice F , Kasman AM , Li S , Belladelli F , Ferro M , de Cobelli O , De Berardinis E , Busetto GM , Eisenberg ML. Increased mortality among men diagnosed with impaired fertility: analysis of US claims data . Urology 2021 ; 147 : 143 – 149 . Dhawan V , Kumar M , Deka D , Malhotra N , Singh N , Dadhwal V , Dada R. Paternal factors and embryonic development: role in recurrent pregnancy loss . Andrologia 2019 ; 51 : e13171 . Dias TR , Agarwal A , Pushparaj PN , Ahmad G , Sharma R. New insights on the mechanisms affecting fertility in men with non-seminoma testicular cancer before cancer therapy . World J Mens Health 2020 ; 38 : 198 – 207 . Dunphy BC , Barratt CL , Kay R , Thomas EJ , Neal LM , Cooke ID. The importance of employing stringent methods to recruit fertile male controls . Andrologia 1991 ; 23 : 35 – 39 . Dupree JM. Insurance coverage for male infertility care in the United States . Asian J Androl 2016 ; 18 : 339 – 341 . Durazzo M , Premoli A , Di Bisceglie C , Bertagna A , Faga E , Biroli G , Manieri C , Bo S , Pagano G. Alterations of seminal and hormonal parameters: an extrahepatic manifestation of HCV infection? World J Gastroenterol 2006 ; 12 : 3073 – 3076 . Ebesunun MO , Solademi BA , Shittu OB , Anetor JI , Onuegbu JA , Olisekodiaka JM , Agbedana EO , Onyeaghala AA. Plasma and semen ascorbic levels in spermatogenesis . West Afr J Med 2004 ; 23 : 290 – 293 . Engelbertz F , Korda JB , Engelmann U , Rothschild M , Banaschak S. Longevity of spermatozoa in the post-ejaculatory urine of fertile men . Forensic Sci Int 2010 ; 194 : 15 – 19 . European Society of Human Reproduction and Embryology . “More than 8 million babies born from IVF since the world’s first in 1978: European IVF pregnancy rates now steady at around 36 percent, according to ESHRE monitoring”. ScienceDaily 2018 . . “More than 8 million babies born from IVF since the world’s first in 1978: European IVF pregnancy rates now steady at around 36 percent, according to ESHRE monitoring”. ScienceDaily https://www.sciencedaily.com/releases/2018/07/180703084127.htm (31 May 2022, date last accessed). Evgeni E , Lymberopoulos G , Gazouli M , Asimakopoulos B. Conventional semen parameters and DNA fragmentation in relation to fertility status in a Greek population . Eur J Obstet Gynecol Reprod Biol 2015 ; 188 : 17 – 23 . Fanny J , Julien S , FG F-J , Sabiha E , Sophie DD , Luc B , Hélène B , Nicolas S , Valérie M. Gel electrophoresis of human sperm: a simple method for evaluating sperm protein quality . Basic Clin Androl 2018 ; 28 : 10 . 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 1981 ; 35 : 325 – 327 . Fedder J , Askjaer SA , Hjort T. Nonspermatozoal cells in semen: relationship to other semen parameters and fertility status of the couple . Arch Androl 1993 ; 31 : 95 – 103 . Ferlin A , Garolla A , Ghezzi M , Selice R , Palego P , Caretta N , Di Mambro A , Valente U , De Rocco Ponce M , Dipresa S et al. Sperm count and hypogonadism as markers of general male health . Eur Urol Focus 2021 ; 7 : 205 – 213 . Fetic S , Yeung CH , Sonntag B , Nieschlag E , Cooper TG. Relationship of cytoplasmic droplets to motility, migration in mucus, and volume regulation of human spermatozoa . J Androl 2006 ; 27 : 294 – 301 . Figà-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 1996 ; 30 : 750 – 758 . Firman RC , Simmons LW , Cummins JM , Matson PL. Are body fluctuating asymmetry and the ratio of 2nd to 4th digit length reliable predictors of semen quality? Hum Reprod 2003 ; 18 : 808 – 812 . 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 1996 ; 65 : 1009 – 1014 . Foppiani L , Cavani S , Piredda S , Perroni L , Fazzuoli L , Giusti M. Lack of evidence of a genetic origin in the impaired spermatogenesis of a patient cohort with low-grade varicocele . J Endocrinol Invest 2001 ; 24 : 217 – 223 . Fowler JE Jr, Mariano M. Immunoglobulin in seminal fluid of fertile, infertile, vasectomy and vasectomy reversal patients . J Urol 1983 ; 129 : 869 – 872 . Franken DR. Office-based sperm concentration: a simplified method for intrauterine insemination therapy . S Afr Med J 2015 ; 105 : 295 – 297 . Fredricsson B , Sennerstam R. Morphology of live seminal and postcoital cervical spermatozoa and its bearing on human fertility . Acta Obstet Gynecol Scand 1984 ; 63 : 329 – 333 . Freischem CW , Knuth UA , Langer K , Schneider HP , Nieschlag E. The lack of discriminant seminal and endocrine variables in the partners of fertile and infertile women . Arch Gynecol 1984 ; 236 : 1 – 12 . Gallegos G , Ramos B , Santiso R , Goyanes V , Gosalvez J , Fernandez JL. Sperm DNA fragmentation in infertile men with genitourinary infection by Chlamydia trachomatis and Mycoplasma . Fertil Steril 2008 ; 90 : 328 – 334 . Garcia PC , Rubio E , Pereira OCM. Antisperm antibodies in infertile men and their correlation with seminal parameters . Reprod Med Biol 2007 ; 6 : 33 – 38 . García Rodríguez A , de la Casa M , Johnston S , Gosálvez J , Roy R. Association of polymorphisms in genes coding for antioxidant enzymes and human male infertility . Ann Hum Genet 2019 ; 83 : 63 – 72 . Giagulli VA , Carbone D. Hormonal control of inhibin B in men . J Endocrinol Invest 2006 ; 29 : 706 – 713 . Giagulli VA , Carbone MD , De Pergola G , Guastamacchia E , Resta F , Licchelli B , Sabbà C , Triggiani V. Could androgen receptor gene CAG tract polymorphism affect spermatogenesis in men with idiopathic infertility? J Assist Reprod Genet 2014 ; 31 : 689 – 697 . Giblin PT , Poland ML , Moghissi KS , Ager JW , Olson JM. Effects of stress and characteristic adaptability on semen quality in healthy men . Jockenhovel 1988 ; 49 : 127 – 132 . Girela JL , Gil D , Johnsson M , Gomez-Torres MJ , De Juan J. Semen parameters can be predicted from environmental factors and lifestyle using artificial intelligence methods . Biol Reprod 2013 ; 88 : 99 . Glazier DB , Marmar JL , Diamond SM , Gibbs M , Corson SL. A modified acrosome induction test . Arch Androl 2000 ; 44 : 59 – 64 . Gottlieb C , Svanborg K , Bygdeman M. Adenosine triphosphate (ATP) in human spermatozoa . Andrologia 1991 ; 23 : 421 – 425 . Goulis DG , Iliadou PK , Tsametis C , Gerou S , Tarlatzis BC , Bontis IN , Papadimas I. Serum anti-Mullerian hormone levels differentiate control from subfertile men but not men with different causes of subfertility . Gynecol Endocrinol 2008 ; 24 : 158 – 160 . Guzick DS , Overstreet JW , Factor-Litvak P , Brazil CK , Nakajima ST , Coutifaris C , Carson SA , Cisneros P , Steinkampf MP , Hill JA , et al. ; National Cooperative Reproductive Medicine Network . Sperm morphology, motility, and concentration in fertile and infertile men . N Engl J Med 2001 ; 345 : 1388 – 1393 . Gyllenborg J , Skakkebaek NE , Nielsen NC , Keiding N , Giwercman A. Secular and seasonal changes in semen quality among young Danish men: a statistical analysis of semen samples from 1927 donor candidates during 1977–1995 . Int J Androl 1999 ; 22 : 28 – 36 . Halling J , Petersen MS , Jorgensen N , Jensen TK , Grandjean P , Weihe P. Semen quality and reproductive hormones in Faroese men: a cross-sectional population-based study of 481 men . BMJ Open 2013 ; 3 : e001946 . Hammadeh ME , Greiner S , Rosenbaum P , Schmidt W. Comparison between human sperm preservation medium and TEST-yolk buffer on protecting chromatin and morphology integrity of human spermatozoa in fertile and subfertile men after freeze-thawing procedure . J Androl 2001 ; 22 : 1012 – 1018 . Handelsman DJ. Estimating familial and genetic contributions to variability in human testicular function: a pilot twin study . Int J Androl 1997a ; 20 : 215 – 221 . Handelsman DJ. Sperm output of healthy men in Australia: magnitude of bias due to self-selected volunteers . Hum Reprod 1997b ; 12 : 2701 – 2705 . Haugen TB , Egeland T , Magnus O. Semen parameters in Norwegian fertile men . J Androl 2006 ; 27 : 66 – 71 . Hauser R , Skakkebaek NE , Hass U , Toppari J , Juul A , Andersson AM , Kortenkamp A , Heindel JJ , Trasande L. Male reproductive disorders, diseases, and costs of exposure to endocrine-disrupting chemicals in the European Union . J Clin Endocrinol Metab 2015 ; 100 : 1267 – 1277 . Heussner JC , Ward JB Jr, Legator MS. Genetic monitoring of aluminum workers exposed to coal tar pitch volatiles . Mutat Res 1985 ; 155 : 143 – 155 . Higgins J , Green S. Cochrane handbook for systematic reviews of interventions. version 5.1. 0. [updated March 2011]. The Cochrane Collaboration, 2011 . Hill JA , Abbott AF , Politch JA. Sperm morphology and recurrent abortion . Fertil Steril 1994 ; 61 : 776 – 778 . Hosen MB , Islam MR , Begum F , Kabir Y , Howlader MZH. Oxidative stress induced sperm DNA damage, a possible reason for male infertility . Iran J Reprod Med 2015 ; 13 : 525 – 532 . Hossain F , Ali O , D’Souza UJ , Naing DK. Effects of pesticide use on semen quality among farmers in rural areas of Sabah, Malaysia . J Occup Health 2010 ; 52 : 353 – 360 . Huang LP , Lee CC , Fan JP , Kuo PH , Shih TS , Hsu PC. Urinary metabolites of di(2-ethylhexyl) phthalate relation to sperm motility, reactive oxygen species generation, and apoptosis in polyvinyl chloride workers . Int Arch Occup Environ Health 2014 ; 87 : 635 – 646 . Inih OS , Esther YE , Adetola FO , Chinedu AA , Brenda NC , Efedaye OA. Testicular dysfunction is a common feature in men with type 2 diabetes mellitus in a Nigerian tertiary hospital . Curr Diabetes Rev 2018 ; 14 : 298 – 306 . 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 . BMJ 1996 ; 312 : 467 – 471 . Iwamoto T , Nozawa S , Mieno MN , Yamakawa K , Baba K , Yoshiike M , Namiki M , Koh E , Kanaya J , Okuyama A et al. Semen quality of 1559 young men from four cities in Japan: a cross-sectional population-based study . BMJ Open 2013a ; 3 : e002222 . Iwamoto T , Nozawa S , Yoshiike M , Hoshino T , Baba K , Matsushita T , Tanaka SN , Naka M , Skakkebaek NE , Jorgensen N. Semen quality of 324 fertile Japanese men . Hum Reprod 2006 ; 21 : 760 – 765 . Iwamoto T , Nozawa S , Yoshiike M , Namiki M , Koh E , Kanaya J , Okuyama A , Matsumiya K , Tsujimura A , Komatsu K et al. Semen quality of fertile Japanese men: a cross-sectional population-based study of 792 men . BMJ Open 2013b ; 3 : e002223 . Jacobsen K , Ramlau-Hansen CH , Thulstrup AM , Olsen J , Bonde JP. Maternal folic acid supplement intake and semen quality in Danish sons: a follow-up study . Fertil Steril 2011 ; 96 : 295 – 298 . Jedrzejczak P , Taszarek-Hauke G , Hauke J , Pawelczyk L , Duleba AJ. Prediction of spontaneous conception based on semen parameters . Int J Androl 2008 ; 31 : 499 – 507 . Jensen TK , Andersson AM , Hjollund NH , Scheike T , Kolstad H , Giwercman A , Henriksen TB , Ernst E , Bonde JP , Olsen J et al. Inhibin B as a serum marker of spermatogenesis: correlation to differences in sperm concentration and follicle-stimulating hormone levels. A study of 349 Danish men . J Clin Endocrinol Metab 1997 ; 82 : 4059 – 4063 . Ji G , Yan L , Liu W , Huang C , Gu A , Wang X. Polymorphisms in double-strand breaks repair genes are associated with impaired fertility in Chinese population . Reproduction 2013 ; 145 : 463 – 470 . Jockenhovel F , Khan SA , Nieschlag E. Diagnostic value of bioactive FSH in male infertility . Acta Endocrinol (Copenh) 1989 ; 121 : 802 – 810 . Jørgensen N , Andersen AG , Eustache F , Irvine DS , Suominen J , Petersen JH , Andersen AN , Auger J , Cawood EH , Horte A et al. Regional differences in semen quality in Europe . Hum Reprod 2001 ; 16 : 1012 – 1019 . Jørgensen N , Carlsen E , Nermoen I , Punab M , Suominen J , Andersen AG , Andersson AM , Haugen TB , Horte A , Jensen TK et al. East-West gradient in semen quality in the Nordic-Baltic area: a study of men from the general population in Denmark, Norway, Estonia and Finland . Hum Reprod 2002 ; 17 : 2199 – 2208 . Jørgensen N , Joensen UN , Jensen TK , Jensen MB , Almstrup K , Olesen IA , Juul A , Andersson AM , Carlsen E , Petersen JH et al. Human semen quality in the new millennium: a prospective cross-sectional population-based study of 4867 men . BMJ Open 2012 ; 2 : e000990 . Jørgensen N , Lamb DJ , Levine H , Pastuszak AW , Sigalos JT , Swan SH , Eisenberg ML. Are worldwide sperm counts declining? Fertil Steril 2021 ; 116 : 1457 – 1463 . Jørgensen N , Vierula M , Jacobsen R , Pukkala E , Perheentupa A , Virtanen HE , Skakkebaek NE , Toppari J. Recent adverse trends in semen quality and testis cancer incidence among Finnish men . Int J Androl 2011 ; 34 : e37 – e48 . Junqing W , Qiuying Y , Jianguo T , Wei Y , Liwei B , Yuxian L , Yumei Z , Kangshou Y , Weiqun L , Lu C et al. Reference value of semen quality in Chinese young men . Contraception 2002 ; 65 : 365 – 368 . Karimian M , Colagar AH. Association of C677T transition of the human methylenetetrahydrofolate reductase (MTHFR) gene with male infertility . Reprod Fertil Dev 2016 ; 28 : 785 – 794 . Katukam V , Kulakarni M , Syed R , Alharbi K , Naik J. Effect of benzene exposure on fertility of male workers employed in bulk drug industries . Genet Test Mol Biomarkers 2012 ; 16 : 592 – 597 . Kavitha P , Malini SS. Positive association of sperm dysfunction in the pathogenesis of recurrent pregnancy loss . J Clin Diagnostic Res 2014 ; 8 : OC07 – OC10 . Kelleher S , Wishart SM , Liu PY , Turner L , Di Pierro I , Conway AJ , Handelsman DJ. Long-term outcomes of elective human sperm cryostorage . Hum Reprod 2001 ; 16 : 2632 – 2639 . Khan MS , Deepa F , Ahmed Z , Tahir F , Khan MA. Assessment of male reproductive health by conventional method of semen analysis . J Ayub Med Coll Abbottabad 2011 ; 23 : 84 – 88 . Kirei BR. Semen characteristics in 120 fertile Tanzanian men . East Afr Med J 1987 ; 64 : 453 – 457 . Kjaergaard N , Kjaergaard B , Lauritsen JG. Prazosin, an adrenergic blocking agent inadequate as male contraceptive pill . Contraception 1988 ; 37 : 621 – 629 . Kobayashi K , Masumori N , Hisasue S , Kato R , Hashimoto K , Itoh N , Tsukamoto T. Inhibition of seminal emission is the main cause of anejaculation induced by a new highly selective alpha1A-blocker in normal volunteers . J Sex Med 2008 ; 5 : 2185 – 2190 . Kolstad HA , Bonde JP , Spano M , Giwercman A , Zschiesche W , Kaae D , Larsen SB , Roeleveld N. Change in semen quality and sperm chromatin structure following occupational styrene exposure. ASCLEPIOS . Int Arch Occup Environ Health 1999 ; 72 : 135 – 141 . Korrovits P , Ausmees K , Mandar R , Punab M. Prevalence of asymptomatic inflammatory (National Institutes of Health Category IV) prostatitis in young men according to semen analysis . Urology 2008 ; 71 : 1010 – 1015 . Kukuvitis A , Georgiou I , Bouba I , Tsirka A , Giannouli CH , Yapijakis C , Tarlatzis B , Bontis J , Lolis D , Sofikitis N et al. Association of oestrogen receptor alpha polymorphisms and androgen receptor CAG trinucleotide repeats with male infertility: a study in 109 Greek infertile men . Int J Androl 2002 ; 25 : 149 – 152 . Kumar K , Venkatesh S , Sharma PR , Tiwari PK , Dada R DAZL 260A > G and MTHFR 677C > T variants in sperm DNA of infertile Indian men . Indian J Biochem Biophys 2011 ; 48 : 422 – 426 . Kumar R , Venkatesh S , Kumar M , Tanwar M , Shasmsi MB , Kumar R , Gupta NP , Sharma RK , Talwar P , Dada R. Oxidative stress and sperm mitochondrial DNA mutation in idiopathic oligoasthenozoospermic men . Indian J Biochem Biophys 2009 ; 46 : 172 – 177 . Kuroki Y , Iwamoto T , Lee J , Yoshiike M , Nozawa S , Nishida T , Ewis AA , Nakamura H , Toda T , Tokunaga K et al. Spermatogenic ability is different among males in different Y chromosome lineage . J Hum Genet 1999 ; 44 : 289 – 292 . Larsen SB , Spano M , Giwercman A , Bonde JP. Semen quality and sex hormones among organic and traditional Danish farmers. ASCLEPIOS Study Group . Occup Environ Med 1999 ; 56 : 139 – 144 . Latif T , Jensen TK , Mehlsen J , Holmboe SA , Brinth L , Pors K , Skouby SO , Jørgensen N , Lindahl-Jacobsen R. Semen quality as a predictor of subsequent morbidity: a Danish cohort study of 4,712 men with long-term follow-up . Am J Epidemiol 2017 ; 186 : 910 – 917 . Layali I, Tahmasbpour E, Joulaei M, Jorsaraei SGA, Farzanegi P. Total antioxidant capacity and lipid peroxidation in semen of patient with hyperviscosity . Cell J 2015 ; 16 : 554 – 559 . Lazzarino G , Listorti I , Bilotta G , Capozzolo T , Amorini AM , Longo S , Caruso G , Lazzarino G , Tavazzi B , Bilotta P. Water- and fat-soluble antioxidants in human seminal plasma and serum of fertile males . Antioxidants 2019 ; 8 : 96 – 13 . Le Moal J , Sharpe RM , Jϕrgensen N , Levine H , Jurewicz J , Mendiola J , Swan SH , Virtanen H , Christin-Maître S , Cordier S et al. ; HURGENT Network . Toward a multi-country monitoring system of reproductive health in the context of endocrine disrupting chemical exposure . Eur J Public Health 2016 ; 26 : 76 – 83 . Lee PA , Coughlin MT. Fertility after bilateral cryptorchidism. Evaluation by paternity, hormone, and semen data . Horm Res 2001 ; 55 : 28 – 32 . Lemcke B , Behre HM , Nieschlag E. Frequently subnormal semen profiles of normal volunteers recruited over 17 years . Int J Androl 1997 ; 20 : 144 – 152 . Leto S , Frensilli FJ. Changing parameters of donor semen . Fertil Steril 1981 ; 36 : 766 – 770 . Levine H , Jørgensen N , Martino-Andrade A , Mendiola J , Weksler-Derri D , Mindlis I , Pinotti R , Swan SH. Temporal trends in sperm count: a systematic review and meta-regression analysis . Hum Reprod Update 2017 ; 23 : 646 – 659 . Levine H , Mohri H , Ekbom A , Ramos L , Parker G , Roldan E , Jovine L , Koelle S , Lindstrand A , Immler S et al. Male reproductive health statement (XIIIth international symposium on Spermatology, May 9th–12th 2018, Stockholm, Sweden) . Basic Clin Androl 2018 ; 28 : 13 . 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 1992 ; 57 : 1075 – 1083 . Li JW , Gu YQ. Predictors for partial suppression of spermatogenesis of hormonal male contraception . Asian J Androl 2008 ; 10 : 723 – 730 . Liberati A , Altman DG , Tetzlaff J , Mulrow C , Gøtzsche PC , Ioannidis JPA , Clarke M , Devereaux PJ , Kleijnen J , Moher D. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration . BMJ 2009 ; 339 : b2700 . Linschooten JO , Laubenthal J , Cemeli E , Baumgartner A , Anderson D , Sipinen VE , Brunborg G , Haenen GRMM , Fthenou E , Briedé JJ et al. Incomplete protection of genetic integrity of mature spermatozoa against oxidative stress . Reprod Toxicol 2011 ; 32 : 106 – 111 . Liu DY , Stewart T , Baker HW. Normal range and variation of the zona pellucida-induced acrosome reaction in fertile men . Fertil Steril 2003 ; 80 : 384 – 389 . Liu J , Wang Q , Ji X , Guo S , Dai Y , Zhang Z , Jia L , Shi Y , Tai S , Lee Y. Prevalence of Ureaplasma urealyticum, Mycoplasma hominis, Chlamydia trachomatis infections, and semen quality in infertile and fertile men in China . Urology 2014 ; 83 : 795 – 799 . López-Espín JJ , Pérez-Palazón C , Maldonado-Cárceles AB , Román-Arias JD , Mendiola J , Torres-Cantero AM. Anogenital distance and variability in semen parameters . Syst Biol Reprod Med 2018 ; 64 : 71 – 79 . Lopez-Teijon M , Elbaile M , Alvarez JG. Geographical differences in semen quality in a population of young healthy volunteers from the different regions of Spain . Andrologia 2008 ; 40 : 318 – 328 . Lotti F , Corona G , Cocci A , Cipriani S , Baldi E , Degl’Innocenti S , Franco PN , Gacci M , Maggi M. The prevalence of midline prostatic cysts and the relationship between cyst size and semen parameters among infertile and fertile men . Hum Reprod 2018 ; 33 : 2023 – 2034 . Luetjens CM , Rolf C , Gassner P , Werny JE , Nieschlag E. Sperm aneuploidy rates in younger and older men . Hum Reprod 2002 ; 17 : 1826 – 1832 . Lundwall A , Giwercman A , Ruhayel Y , Giwercman Y , Lilja H , Hallden C , Malm J. A frequent allele codes for a truncated variant of semenogelin I, the major protein component of human semen coagulum . Mol Hum Reprod 2003 ; 9 : 345 – 350 . Mahmoud A , Kiss P , Vanhoorne M , De Bacquer D , Comhaire F. Is inhibin B involved in the toxic effect of lead on male reproduction? Int J Androl 2005 ; 28 : 150 – 155 . Mak V , Jarvi K , Buckspan M , Freeman M , Hechter S , Zini A. Smoking is associated with the retention of cytoplasm by human spermatozoa . Urology 2000 ; 56 : 463 – 466 . Malić Vončina S , Golob B , Ihan A , Kopitar AN , Kolbezen M , Zorn B. Sperm DNA fragmentation and mitochondrial membrane potential combined are better for predicting natural conception than standard sperm parameters . Fertil Steril 2016 ; 105 : 637 – 644.e1 . Malini SS. Impact of ornithine decarboxylase on semen parameters and functional status of spermatozoa in type 2 diabetes mellitus . Asian J Pharm 2017 ; 11 : 11 – 17 . Mendiola J , Jørgensen N , Andersson AM , Stahlhut RW , Liu F , Swan SH. Reproductive parameters in young men living in Rochester, New York . Fertil Steril 2014 ; 101 : 1064 – 1071 . Mendiola J , Jørgensen N , Mínguez-Alarcón L , Sarabia-Cos L , López-Espín JJ , Vivero-Salmerón G , Ruiz-Ruiz KJ , Fernández MF , Olea N , Swan SH et al. Sperm counts may have declined in young university students in Southern Spain . Andrology 2013 ; 1 : 408 – 413 . Mieusset R , Bujan L , Mansat A , Pontonnier F , Grandjean H , Chap H. Glycerophosphocholine in seminal plasma of fertile and infertile men . Int J Androl 1988 ; 11 : 405 – 413 . Mieusset R , Bujan L , Massat G , Mansat A , Pontonnier F. Clinical and biological characteristics of infertile men with a history of cryptorchidism . Hum Reprod 1995 ; 10 : 613 – 619 . Mínguez-Alarcón L , Sergeyev O , Burns JS , Williams PL , Lee MM , Korrick SA , Smigulina L , Revich B , Hauser R. A longitudinal study of peripubertal serum organochlorine concentrations and semen parameters in young men: the Russian children’s study . Environ Health Perspect 2017 ; 125 : 460 – 466 . Mohammed EEM , Mosad E , Zahran AM , Hameed DA , Taha EA , Mohamed MA. Acridine orange and flow cytometry: which is better to measure the effect of varicocele on sperm DNA integrity? Adv Urol 2015 ; 2015 : 1 – 6 . Moher D , Liberati A , Tetzlaff J , Altman DG; PRISMA Group . Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement . BMJ 2009 ; 339 : b2535 . Moridi A , Roozbeh N , Yaghoobi H , Soltani S , Dashti S , Shahrahmani N , Banaei M. Etiology and risk factors associated with infertility . Int J Women’s Health Reprod Sci 2019 ; 7 : 346 – 353 . Mostafa T , El-Shahid LH , El Azeem AA , Shaker O , Gomaa H , Abd El Hamid HM. Androgen receptor-CAG repeats in infertile Egyptian men . Andrologia 2012 ; 44 : 147 – 151 . Muller CH , Coombs RW , Krieger JN. Effects of clinical stage and immunological status on semen analysis results in human immunodeficiency virus type 1-seropositive men . Andrologia 1998 ; 30 : 15 – 22 . Multigner L , Ben Brik E , Arnaud I , Haguenoer JM , Jouannet P , Auger J , Eustache F. Glycol ethers and semen quality: a cross-sectional study among male workers in the Paris Municipality . Occup Environ Med 2007 ; 64 : 467 – 473 . Muthusami KR , Chinnaswamy P. Effect of chronic alcoholism on male fertility hormones and semen quality . Fertil Steril 2005 ; 84 : 919 – 924 . National Toxicology Program . Handbook for Conducting a Literature-Based Health Assessment Using OHAT Approach for Systematic Review and Evidence Integration . US Department of Health and Human Services , 2015 . https://ntp.niehs.nih.gov/pubhealth/hat/noms/index-2.html (23 October 2022, date last accessed). Naz RK , Evans L , Armstrong JS , Sikka SC. Decreased levels of interleukin-12 are not correlated with leukocyte concentration and superoxide dismutase activity in semen of infertile men . Arch Androl 1998 ; 41 : 91 – 96 . Nieschlag E , Lammers U , Freischem CW , Langer K , Wickings EJ. Reproductive functions in young fathers and grandfathers . J Clin Endocrinol Metab 1982 ; 55 : 676 – 681 . Nikoobakht MR , Aloosh M , Nikoobakht N , Mehrsay AR , Biniaz F , Karjalian MA. The role of hypothyroidism in male infertility and erectile dysfunction . Urol J 2012 ; 9 : 405 – 409 . Nnatu SN , Giwa-Osagie OF , Essien EE. Effect of repeated semen ejaculation on sperm quality . Clin Exp Obstet Gynecol 1991 ; 18 : 39 – 42 . Noack-Füller G , De Beer C , Seibert H. Cadmium, lead, selenium, and zinc in semen of occupationally unexposed men . Andrologia 1993 ; 25 : 7 – 12 . O'Donovan M. An evaluation of chromatin condensation and DNA integrity in the spermatozoa of men with cancer before and after therapy . Andrologia 2005 ; 37 : 83 – 90 . Obwaka JM , Mati JK , Lequin RM , Sekadde-kigondu CB , Muitta MN , Nthale JM , Njoroge JK. Baseline studies on semen and hormonal parameters in fertile Black males in Kenya . J Obstet Gynaecol East Cent Africa 1982 ; 1 : 96 – 99 . Ortiz A , Espino J , Bejarano I , Lozano GM , Monllor F , Garcia JF , Pariente JA , Rodriguez AB. The correlation between urinary 5-hydroxyindoleacetic acid and sperm quality in infertile men and rotating shift workers . Reprod Biol Endocrinol 2010 ; 8 : 138 . Paasch U , Salzbrunn A , Glander HJ , Plambeck K , Salzbrunn H , Grunewald S , Stucke J , Vierula M , Skakkebaek NE , Jørgensen N. Semen quality in sub-fertile range for a significant proportion of young men from the general German population: a co-ordinated, controlled study of 791 men from Hamburg and Leipzig . Int J Androl 2008 ; 31 : 93 – 102 . Pal PC , Rajalakshmi M , Manocha M , Sharma RS , Mittal S , Rao DN. Semen quality and sperm functional parameters in fertile Indian men . Andrologia 2006 ; 38 : 20 – 25 . Palani AF. Effect of serum antioxidant levels on sperm function in infertile male . Middle East Fertil Soc J 2018 ; 23 : 19 – 22 . Pangkahila W. Reversible azoospermia induced by an androgen-progestin combination regimen in Indonesian men . Int J Androl 1991 ; 14 : 248 – 256 . Patankar SS , Deshkar AM , Sawane MV , Mishra NV , Kale AH , Gosavi GB. The role of hypo-osmotic swelling test in recurrent abortions . Indian J Physiol Pharmacol 2001 ; 45 : 373 – 377 . Peters M , Rhodes G , Simmons LW. Does attractiveness in men provide clues to semen quality? J Evol Biol 2008 ; 21 : 572 – 579 . Plastira K , Msaouel P , Angelopoulou R , Zanioti K , Plastiras A , Pothos A , Bolaris S , Paparisteidis N , Mantas D. The effects of age on DNA fragmentation, chromatin packaging and conventional semen parameters in spermatozoa of oligoasthenoteratozoospermic patients . J Assist Reprod Genet 2007 ; 24 : 437 – 443 . Priskorn L , Nordkap L , Bang AK , Krause M , Holmboe SA , Egeberg Palme DL , Winge SB , Mørup N , Carlsen E , Joensen UN et al. Average sperm count remains unchanged despite reduction in maternal smoking: results from a large cross-sectional study with annual investigations over 21 years . Hum Reprod 2018 ; 33 : 998 – 1008 . Pullar JM , Carr AC , Bozonet SM , Rosengrave P , Kettle AJ , Vissers MCM. Elevated seminal plasma myeloperoxidase is associated with a decreased sperm concentration in young men . Andrology 2017 ; 5 : 431 – 438 . Punab M , Zilaitiene B , Jørgensen N , Horte A , Matulevicius V , Peetsalu A , Skakkebaek NE. Regional differences in semen qualities in the Baltic region . Int J Androl 2002 ; 25 : 243 – 252 . Purakayastha M , Mukhopadhyay SK , Chattopadhyay S. Heterogeneity in antigen distribution on spermatozoa of fertile and infertile subjects . J Indian Med Assoc 1999 ; 97 : 65 – 67 . Rabelo-Junior CN , Freire de Carvalho J , Lopes Gallinaro A , Bonfa E , Cocuzza M , Saito O , Silva CA. Primary antiphospholipid syndrome: morphofunctional penile abnormalities with normal sperm analysis . Lupus 2012 ; 21 : 251 – 256 . Ramzan MH , Ramzan M , Khan MM , Ramzan F , Wahab F , Khan MA , Jillani M , Shah M. Human semen quality and sperm DNA damage assessed by comet assay in clinical groups . Turk J Med Sci 2015 ; 45 : 729 – 737 . Recabarren SE , Sir-Petermann T , Rios R , Maliqueo M , Echiburu B , Smith R , Rojas-Garcia P , Recabarren M , Rey RA. Pituitary and testicular function in sons of women with polycystic ovary syndrome from infancy to adulthood . J Clin Endocrinol Metab 2008 ; 93 : 3318 – 3324 . Recio-Vega R , Ocampo-Gómez G , Borja-Aburto VH , Moran-Martínez J , Cebrian-Garcia ME. Organophosphorus pesticide exposure decreases sperm quality: association between sperm parameters and urinary pesticide levels . J Appl Toxicol 2008 ; 28 : 674 – 680 . Recio-Vega R , Olivas-Calderon E , Michel-Ramirez G , Martinez-Salinas RI , Gallegos-Arreola MP , Ocampo-Gomez GL , Perez-Morales R. Associations between sperm quality, DNA damage, and CYP1A1, GSTT1 and GSTM1 polymorphisms with 1-hydroxypyrene urinary levels in men occupationally exposed to polycyclic aromatic hydrocarbons . Int Arch Occup Environ Health 2018 ; 91 : 725 – 734 . Reddy KV , Bordekar AD. Spectrophotometric analysis of resazurin reduction test and semen quality in men . Indian J Exp Biol 1999 ; 37 : 782 – 786 . Redmon JB , Thomas W , Ma W , Drobnis EZ , Sparks A , Wang C , Brazil C , Overstreet JW , Liu F , Swan SH; Study for Future Families Research Group Semen parameters in fertile US men: the study for future families . Andrology 2013 ; 1 : 806 – 814 . Rehan N. Semen characteristics of fertile Pakistani men . J Pak Med Assoc 1994 ; 44 : 62 – 64 . Rendon A , Rojas A , Fernandez SI , Pineda I. Increases in chromosome aberrations and in abnormal sperm morphology in rubber factory workers . Mutat Res 1994 ; 323 : 151 – 157 . Richthoff J , Rylander L , Hagmar L , Malm J , Giwercman A. Higher sperm counts in Southern Sweden compared with Denmark . Hum Reprod 2002 ; 17 : 2468 – 2473 . Rignell-Hydbom A , Axmon A , Lundh T , Jonsson BA , Tiido T , Spano M. Dietary exposure to methyl mercury and PCB and the associations with semen parameters among Swedish fishermen . Environ Health 2007 ; 6 : 14 . Rintala MA , Grenman SE , Pollanen PP , Suominen JJ , Syrjanen SM. Detection of high-risk HPV DNA in semen and its association with the quality of semen . Int J STD AIDS 2004 ; 15 : 740 – 743 . Rodprasert W , Virtanen HE , Sadov S , Perheentupa A , Skakkebaek NE , Jørgensen N , Toppari J. An update on semen quality among young Finnish men and comparison with Danish data . Andrology 2019 ; 7 : 15 – 23 . Romero-Otero J , Medina-Polo J , García-Gómez B , Lora-Pablos D , Duarte-Ojeda JM , García-González L , García-Cruz E , Rodríguez-Antolín A. Semen quality assessment in fertile men in madrid during the last 3 decades . Urology 2015 ; 85 : 1333 – 1338 . 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 1985 ; 42 : 123 – 127 . Roste LS , Tauboll E , Haugen TB , Bjornenak T , Saetre ER , Gjerstad L. Alterations in semen parameters in men with epilepsy treated with valproate or carbamazepine monotherapy . Eur J Neurol 2003 ; 10 : 501 – 506 . Rubes J , Rybar R , Prinosilova P , Veznik Z , Chvatalova I , Solansky I , Sram RJ. Genetic polymorphisms influence the susceptibility of men to sperm DNA damage associated with exposure to air pollution . Mutat Res 2010 ; 683 : 9 – 15 . Rylander L , Wetterstrand B , Haugen TB , Malm G , Malm J , Bjorsvik C , Henrichsen T , Saether T , Giwercman A. Single semen analysis as a predictor of semen quality: clinical and epidemiological implications . Asian J Androl 2009 ; 11 : 723 – 730 . Saxena P , Misro MM , Chaki SP , Chopra K , Roy S , Nandan D. Is abnormal sperm function an indicator among couples with recurrent pregnancy loss? Fertil Steril 2008 ; 90 : 1854 – 1858 . Selevan SG , Borkovec L , Slott VL , Zudova Z , Rubes J , Evenson DP , Perreault SD. Semen quality and reproductive health of young Czech men exposed to seasonal air pollution . Environ Health Perspect 2000 ; 108 : 887 – 894 . Serra-Majem L , Bassas L , Garcia-Glosas R , Ribas L , Ingles C , Casals I , Saavedra P , Renwick AG. Cyclamate intake and cyclohexylamine excretion are not related to male fertility in humans . Food Addit Contam 2003 ; 20 : 1097 – 1104 . Sheriff DS , Legnain M. Evaluation of semen quality in a local Libyan population . Indian J Physiol Pharmacol 1992 ; 36 : 83 – 87 . Shine R , Peek J , Birdsall M. Declining sperm quality in New Zealand over 20 years . N Z Med J 2008 ; 121 : 50 – 56 . Shirota K , Yotsumoto F , Itoh H , Obama H , Hidaka N , Nakajima K , Miyamoto S. Separation efficiency of a microfluidic sperm sorter to minimize sperm DNA damage . Fertil Steril 2016 ; 105 : 315 – 321.e1 . Skakkebæk NE , Lindahl-Jacobsen R , Levine H , Andersson A-M , Jørgensen N , Main KM , Lidegaard Ø , Priskorn L , Holmboe SA , Bräuner EV et al. Environmental factors in declining human fertility . Nat Rev Endocrinol 2022 ; 18 : 139 – 157 . Skakkebaek NE , Rajpert-De Meyts E , Buck Louis GM , Toppari J , Andersson A-M , Eisenberg ML , Jensen TK , Jørgensen N , Swan SH , Sapra KJ et al. Male reproductive disorders and fertility trends: Influences of environment and genetic susceptibility . Physiol Rev 2016 ; 96 : 55 – 97 . Sobowale OB , Akiwumi O. Testicular volume and seminal fluid profile in fertile and infertile males in Ilorin, Nigeria . Int J Gynaecol Obstet 1989 ; 28 : 155 – 161 . Splingart C , Frapsauce C , Veau S , Barthelemy C , Royere D , Guerif F. Semen variation in a population of fertile donors: evaluation in a French centre over a 34-year period . Int J Androl 2012 ; 35 : 467 – 474 . Stewart TM , Liu DY , Garrett C , Jørgensen N , Brown EH , Baker HW. Associations between andrological measures, hormones and semen quality in fertile Australian men: inverse relationship between obesity and sperm output . Hum Reprod 2009 ; 24 : 1561 – 1568 . Stroup DF , Berlin JA , Morton SC , Olkin I , Williamson GD , Rennie D , Moher D , Becker BJ , Sipe TA , Thacker SB. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group . JAMA 2000 ; 283 : 2008 – 2012 . Sultan Sheriff D. Setting standards of male fertility I. Semen analyses in 1500 patients–a report . Andrologia 1983 ; 15 : 687 – 692 . Svanborg K , Gottlieb C , Bendvold E , Bygdeman M. Variation in, and inter-relationship between, prostaglandin levels and other semen parameters in normal men . Int J Androl 1989 ; 12 : 411 – 419 . Swan SH, Elkin EP, Fenster L. The question of declining sperm density revisited: an analysis of 101 studies published 1934–1996 . Environ Health Perspect 2000 ; 108 : 961 – 966 . Tambe AS , Kaore SB , Sawane MV , Gosavi GB. Acrosome intactness and seminal hyaluronidase activity: relationship with conventional seminal parameters . Indian J Med Sci 2001 ; 55 : 125 – 132 . Tainio J , Jahnukainen K , Nurmio M , Pakarinen M , Jalanko H , Jahnukainen T. Testicular function, semen quality, and fertility in young men after renal transplantation during childhood or adolescence . Transplantation 2014 ; 98 : 987 – 993 . Taneja N , Kucheria K , Jain S , Maheshwari MC. Effect of phenytoin on semen . Epilepsia 1994 ; 35 : 136 – 140 . Thilagavathi J , Kumar M , Mishra SS , Venkatesh S , Kumar R , Dada R. Analysis of sperm telomere length in men with idiopathic infertility . Arch Gynecol Obstet 2013 ; 287 : 803 – 807 . Tirumala Vani G , Mukesh N , Siva Prasad B , Rama Devi P , Hema Prasad M , Usha Rani P , Pardhanandana Reddy P. Role of glutathione S-transferase Mu-1 (GSTM1) polymorphism in oligospermic infertile males . Andrologia 2010 ; 42 : 213 – 217 . Toft G , Axmon A , Giwercman A , Thulstrup AM , Rignell-Hydbom A , Pedersen HS , Ludwicki JK , Zvyezday V , Zinchuk A , Spano M et al. ; INUENDO . Fertility in four regions spanning large contrasts in serum levels of widespread persistent organochlorines: a cross-sectional study . Environ Health 2005 ; 4 : 26 . Toft G , Pedersen HS , Bonde JP; INUENDO Research Team . Semen quality in Greenland . Int J Circumpolar Health 2004 ; 63 Suppl 2 : 174 – 178 . Tsao CW , Liu CY , Chou YC , Cha TL , Chen SC , Hsu CY. Exploration of the association between obesity and semen quality in a 7630 male population . PLoS ONE 2015 ; 10 : e0119458 . Tsarev I , Bungum M , Giwercman A , Erenpreisa J , Ebessen T , Ernst E , Erenpreiss J. Evaluation of male fertility potential by Toluidine Blue te

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