Environmental Hazards and Male Fertility: Why Don't We Know More?

Abstract

Nearly all (97%) the studies in the recent literature addressing the relationship between environmental hazards and male fertility use at least one of three common study design strategies: recruiting men presenting to fertility centers (53%), evaluating only one environmental exposure at a time (87%), and using conventional semen quality parameters as the only study outcome (45%). While each of these study design features is logical, defensible, and has generated an enormous amount of information regarding the impact of the environment on male reproductive function, they may also be barriers to furthering our understanding. In this article, we examine in which ways each of these study design features limits progress on male fertility research and propose strategies to go beyond them. Rather than abandoning these strategies, we propose that they should be a starting point instead of the default strategy for the future of male fertility research to more fully understand how men's environmental exposures impact human fertility and human reproduction more generally.

Keywords

male reproductive health - endocrine disruptors - exposome - semen analysis - study design

With the increasing awareness of the importance of considering the impact on male reproduction of environmental factors such as endocrine-disrupting chemicals, diet, air pollution, climate change, heavy metals, alcohol, and cigarette smoking, numerous reviews have been published.[1] [2] [3] [4] [5] [6] Collectively, the literature provides strong evidence that environmental factors can have an important impact on spermatogenesis and other aspects of male reproductive function. Experimental and animal studies have revealed that environmental exposures such as phenols, phthalates, pesticides, air pollution, dioxins, furans, increased ambient temperatures, heavy metals, and tobacco smoke can impair male fertility.[2] [3] [7] These effects are assessed through traditional semen parameters, serum hormone level, or sperm epigenome. Potential mechanisms include antiandrogenic or estrogenic activity,[8] [9] [10] [11] impairing spermatogenesis,[12] [13] steroidogenesis,[14] [15] altering Leydig cell or Sertoli cell gene expression,[16] [17] [18] oxidative stress,[19] damaging sperm DNA,[20] or altering sperm small RNAs.[21] Although there are some inconsistencies in the findings of studies in humans, reviews from clinical and epidemiological studies largely align with the experimental data.[2] [22] [23] Clearly, despite important knowledge gaps, the literature on the relation between environmental hazards and male fertility is sufficiently strong to point toward further research aimed at addressing extant uncertainties that could help with the design of clinical and public health interventions that can prevent, mitigate, or reverse the adverse impact of multiple environmental contaminants on male reproductive function.

In light of the state of the literature as summarized earlier, an additional review article addressing this topic is likely to be redundant. Therefore, the goal of this article is not to restate what we already know but rather to ask why is it that we do not know more about how the environment affects male reproductive function specifically and human reproduction through the paternal line more generally, from fertility through offspring and intergenerational health outcomes, and to suggest a way forward. Our hypothesis is that specific design features of the most common type of studies investigating the role of environmental factors on human fertility hamper our ability to increase our understanding of how environmental factors influence male reproductive function. The most typical study addressing the relation between environmental factors and male fertility has at least two of the following three design features: (1) it recruits men presenting to a fertility clinic for fertility evaluation; (2) it considers a relatively narrow range of exposures, usually a single environmental factor or a family of closely related environmental factors; and (3) it uses bulk semen quality parameters—either alone or, rarely, in combination with reproductive hormone levels or other biomarkers—as the outcome measures. Each of these design decisions is logical and defensible, but they are also limited ([Fig. 1]). In this article, we will examine how each of these hampers progress.

Fig. 1 Study design features and their impact on observable knowledge on the relation between environmental hazards and men's contribution to fertility.

To test these hypotheses, we conducted a literature search aimed at identifying study design characteristics in articles evaluating the relation between environmental hazards, broadly defined, and male fertility. We found 259 articles published in the past 5 years (October 2019 to September 2024) by searching PubMed using the terms “((((“Infertility, Male”[Mesh]) or (“male fertility”[All fields]) or (“fertility”[Mesh]) or (“Semen”[Mesh]) or (“Sperm”[All fields]) or (“Spermatogenesis”[Mesh]) or (“Pregnancy Outcome”[Mesh]) or (“Reproductive Techniques, Assisted”[Mesh])) and ((“Air Pollutants”[Mesh]) or (“Environmental Exposure”[Mesh]) or (“Exposome”[Mesh]) or (“Endocrine Disruptors”[Mesh])) and “Humans”[Mesh] and “Male”[Mesh] NOT (“Review”[Publication Type] or “Systematic Review”[Publication Type] or “Meta-Analysis”[Publication Type] or (“Editorial”[Publication Type])) and (“last 5 years”[PDat]) and (English[lang]))). After excluding irrelevant and duplicate records, 110 studies addressing this question were identified. Each study was classified according to (1) the study population (seeking fertility care vs. not); (2) exposure of interest (single exposure vs. not; where single exposure was defined as (a) a uniquely identifiable substance [e.g., Pb], or (b) a group of substances with close chemical relation [e.g., phthalates]), or (c) a group of substances with shared mechanism of exposure [e.g., air pollution]); and (3) primary study outcome (conventional semen analysis alone, conventional semen analysis plus reproductive hormone, conventional semen analysis plus other male-specific outcomes, male-specific outcomes without conventional semen analysis vs. couple-based outcomes). [Table 1] summarizes the characteristics of these studies and details are presented as a Supplementary Material (available in the online version only).

Table 1 Distribution of key study design features in studies addressing the relation between environmental factors and male fertility published between 2019 and 2024 (n = 110)

Study design features
Population
Men seeking fertility care	58 (53%)
Men not selected based on their fertility care seeking status	52 (47%)
Men presumed to be healthy	9 (17%)
Men selected based on exposure status (occupational or environmental)	15 (29%)
Men in couples attempting pregnancy	12 (23%)
Sperm bank donors	12 (23%)
Men who have recently become fathers	4 (8%)
Exposure
Single exposure	96 (87%)
Outcome
Conventional semen analysis alone	50 (45%)
Conventional semen analysis plus reproductive hormone	2 (2%)
Conventional semen analysis plus other male-specific outcomes[a]	24 (22%)
Male-specific outcomes without conventional semen analysis	15 (14%)
Couple-based outcomes[b]	19 (17%)
Number of conservative study design features[c]
0	3 (3%)
1	33 (30%)
2	51 (46%)
3	23 (21%)

^a Male-specific outcomes include characteristics of semen and sperm other than traditional analysis (sperm acrosome reaction, seminal plasma metabolites), reproductive hormones, oxidative stress and biochemical markers, genetic and epigenetic factors (sperm DNA fragmentation, oxidative DNA damage, DNA methylation, Y chromosome instability, microRNAs, and messenger RNAs).

^b Couple-based outcomes include pregnancy outcomes such as time to pregnancy, number of children, IVF outcomes, and infertility diagnosis. Studies with these outcomes were included regardless of whether they involved semen analysis or male-specific results.

^c Defined as studies that (1) recruited men seeking fertility care, (2) evaluated a single environmental exposure, or (3) used semen parameters as the only study outcome.

Are We Studying the Right Populations?

Recruiting patients presenting to fertility centers seeking diagnosis and/or treatment is a popular study design strategy in the field. More than half of the studies identified in our search (53%, n = 58) recruited individuals seeking fertility care. This study design strategy is completely understandable given that clinical sites undoubtedly offer important advantages. Logistical convenience is probably the most important advantage of this study design strategy. Specimen collection rooms and andrology laboratories are not extensively distributed. The scarcity of these facilities creates an enormous incentive—and often a critical limitation—to rely on existing clinical andrology laboratories associated with fertility centers. Understandably, andrology laboratories prioritize the use of specimen collection rooms for clinical purposes which results in limited and often inconvenient scheduling options for access to these facilities for research purposes. When facing these logistical realities, deciding to recruit men who will be providing semen samples for clinical purposes and using the results of clinically necessary testing becomes an extremely attractive option. Recruiting at fertility clinics has the additional advantage of having a direct gold-standard assessment of semen quality collected as a part of clinical assessment, which remains the cornerstone of male reproductive medicine and male fertility research.

Despite the undeniable advantages of recruiting at fertility centers, this practice can nevertheless be problematic, particularly as it relates to the generalizability of study findings. In some cases, exposure distribution may differ between clinical and general populations. Subfertile patients visiting fertility centers may have stronger motivation to search for information on preconception care with the goal of modifying their lifestyle in hopes this will improve their fertility treatment results.[24] [25] [26] For example, among male participants in the EARTH Study which recruited couples seeking fertility care, close to 40% of men in the study met the recommended daily intake of fruits and vegetables[27] (one of the most important sources of exposure to pesticide residues in the general population), whereas the corresponding figure for adult men in the general population is approximately 10%.[28] Furthermore, the distribution of critical outcomes may differ between clinical and nonclinical populations. For example, a Danish study found systematic differences in the distribution of semen quality parameters between men in the general population (military conscripts), men who had recently become fathers, and men presenting to fertility clinics.[29] Others have also demonstrated systematic differences in semen parameters between fertile men and men in subfertile couples presenting to fertility centers.[30] Although more difficult to quantify, an additional potential limitation that studying clinical populations may pose is that they likely over-represent individuals who are particularly susceptible to the influence of environmental exposures on the reproductive system relative to men in the general population. The combined effect of differences in exposure distribution, differences in outcome distribution, and differences in underlying susceptibility can add up to an immediate benefit since these factors can make it easier to identify associations when they do exist. However, it may also overstate the population-wide impact of any given exposure on fertility.

This type of study design can also present a challenge to causal inference. Most of these studies assess exposures and outcomes of interest concurrently and therefore it is not always possible to assess the temporality between a purported environmental hazard and the outcome of interest. This may be less of a concern for some environmental exposures, such as air pollution, where questionnaire data can be used to reconstruct exposure status at different relevant windows of exposure. It can be a challenge for other exposures. For example, biomarkers of exposure to plasticizers have a notoriously short half-life and considerable within-person variability.[31] Therefore, interpreting an observed association as potentially causal requires strong assumptions about the stability of exposure measures over time. Similarly, some environmental exposures are subject to volitional change. For example, men in couples facing difficulties conceiving may decide to change their lifestyle, which could result in substantial changes in exposure to some environmental contaminants (e.g., increased exposure to pesticides and Hg by following a healthier diet) or to geographically determined and contextual exposures (e.g., increased exposure to air pollution and outdoor greenness by increasing outdoor physical activity). This could result in complete distortions of the hypothesized versus actual causal structure and in the identification and misinterpretation of spurious associations.

This does not mean that clinical populations should not be studied. In fact, studying couples undergoing infertility treatment with assisted reproductive technology (ART) can be incredibly informative regarding the role of male contributions to a couple's fertility as we will discuss later. Instead, the main point of the above discussion is that an overall research strategy that narrowly focuses on men seeking fertility care is likely to distort the overall picture and therefore it is important to also study men in nonclinical settings.

Are We Studying the Right Exposures?

Most of the existing literature on the relationship between environmental factors and male fertility focuses on identifying associations with one exposure or a limited set of closely related exposures at a time. Nearly 9 out of 10 studies in recent literature (87%, n = 96) have followed this strategy ([Table 1]). As is the case for the strategy to recruit primarily at clinical centers, the decision to focus on a single exposure or a limited set of related exposures at a time is also defensible and understandable. An important consideration driving this decision is economic. Environmental epidemiology has embraced the use of biomarkers as a near-default exposure assessment method, particularly for chemical exposures, more strongly than other fields in epidemiology. This largely reflects a strong emphasis on investigating the health effects of physical and chemical agents that can be accurately measured and quantified. The heavy reliance on biomarkers of exposure has numerous advantages for causal inference, such as being able to more strongly link specific agents to specific health effects, facilitating independent replication of study findings, and creating a relatively seamless bidirectional relation with mechanistic studies where findings from epidemiologic studies can be revisited in the laboratory to identify specific biologic mechanisms underpinning associations identified in humans and, vice versa, findings from in vitro and animal models can be revisited in humans to identify relevance to human exposure. These advantages come at a significant cost: environmental epidemiology is expensive, particularly for studies focusing on chemical agents. Many chemicals measured in bodily fluids are known to have substantial within-person measurement variability, which often requires multiple measurements to accurately describe human exposure to environmental chemicals. Furthermore, there is a paucity of laboratories with the capacity to measure chemical agents that may be potentially hazardous to human health. These two factors together can result in major costs to define exposures in a population. For example, nutritional biomarkers that overlap with clinical markers of nutrient deficiencies are inexpensive, and a high-volume project can be contracted with research laboratories for ∼$20 or less per sample. In contrast, the costs per sample are usually 5- to 10-fold higher for measuring phenols, plasticizers, or pesticides in human samples. This means that, at 2024 prices, measuring a chemical agent in a modestly sized study (∼400 participants) could easily take a quarter of the yearly budget of a standard investigator-initiated research grant from the U.S. National Institutes of Health even before taking into consideration costs associated with collecting, processing, transporting, and storing the samples in which these chemicals are measured, and before considering costs associated with measuring study outcomes. Deciding to focus on a limited set of environmental agents can therefore be the difference between a financially viable and an unviable research project, scientific merit aside. Some studies have addressed this problem by progressively increasing their scope over time through multiple rounds of funding, but there is no guarantee from the outset that this incremental strategy will work.

Arguing for the disadvantages of this approach is not complicated. First, focusing on a single exposure or narrow set of related exposures may overlook the correlations and interactions among multiple pollutants and fail to address their combined effects. Relatedly, because people are never exposed to a single environmental agent at a time, this approach will not necessarily reflect the reality of human exposure and health effects which can, on occasion, lead to incorrect conclusions. The simplest version of this problem is interactions between an environmental agent and another factor. Notably, interactions may mask the main effects. In theory, if there is an interaction between an environmental exposure and a modifier of the exposure, the distribution of the modifier in the study population will impact the ability to identify a main effect. For instance, in some of the initial work leading the description of adverse effects of bisphenol A (BPA) on oogenesis, investigators also identified an interaction between BPA and diet when experiments failed to replicate in some mice.[32] They had previously reported the effect of BPS on the oocyte but did not observe this effect when the mice were fed soy-based chow. Other groups have described a similar interaction between BPA and soy for other outcomes and identified additional interactions with the content of methyl donors in the diet.[33] When our group investigated the relationship between BPA exposure and reproductive outcomes in humans, we did not observe the association of urinary BPA concentration in female participants with outcomes of infertility treatment with ART.[34] However, when we revisited this question taking into consideration women's soy and folate intakes to follow up on biological interactions identified in rodents, we found a deleterious effect of BPA on live birth rates among women who did not consume any soy but no relation among soy consumers in line with the animal studies.[35] Although less clear, we also saw a suggestion of an interaction between BPA and dietary folates on the live birth rates.[35] [36] Similarly, our group documented how supplemental folate may modify the relationship between estimated residence-based daily nitrogen dioxide (NO₂) and live births among female participants undergoing infertility treatment with assisted reproduction in the EARTH study.[37] [38] Similar phenomena may be at play for male reproductive outcomes. For example, our group reported interactions that the relationship between hair mercury (Hg) levels and semen quality parameters differs by fish intake levels,[39] likely reflecting different patterns of exposure.

As the cost of simultaneous assessment of multiple environmental exposures decreases, environmental epidemiology, including reproductive environmental epidemiology, is slowly moving toward exposome-based approaches. This is especially true of exposures that can be measured without biomarkers, such as temperature and air pollution.

Are We Studying the Right Outcomes?

The standard semen analysis has been and remains a diagnostic pillar of male reproductive medicine and by extension a cornerstone of male fertility research. Nearly half (45%, n = 50) of the studies in the recent literature addressing questions on the relation between environmental factors and male fertility used semen parameters as the only study outcome, two more studies used semen parameters, and nearly four in five studies (83%, n = 91) used semen parameters and/or an additional male partner-related outcome such as reproductive hormone levels or sperm-associated characteristics ([Table 1]). Some of the preference for semen quality parameters as study outcome reflects the preference for recruiting men at fertility centers as study participants, as discussed earlier, which makes it very easy to use semen quality parameters as a default outcome measure. As is the case with the previous two factors we have discussed, this is not something inherently wrong. It should go without saying that sperm are essential for human reproduction and therefore a comprehensive assessment of semen parameters is an obvious starting place. Moreover, when paired with assessments of reproductive hormone levels, it can provide a picture of the integrity of the hypothalamic–pituitary–testicular axis and, possibly, the site of action (e.g., central vs. testicular) of a given environmental hazard. There are, however, some important problems inherent to using semen quality parameters as study outcomes, which we can broadly divide into technical and conceptual challenges. There is extensive literature on the technical difficulties of analyzing semen samples for clinical and research purposes.[40] [41] [42] Here, we will focus on conceptual issues.

One of the key conceptual problems is that using semen quality parameters as proxies for male fertility rests on the underlying assumption that capturing variability in semen quality captures necessary and sufficient causes of male fertility. This is a very strong and potentially problematic assumption. We do not contend that semen quality parameters do not capture the necessary causes of male fertility. However, it does not capture all sufficient causes. In other words, while it is not possible for a couple to be fertile in the absence of sperm (i.e., the presence of sperm is a necessary cause), it is possible to be a fertile couple with very poor semen quality and, vice versa, it is possible to be an infertile couple because of an underlying male problem that is not identifiable with conventional semen quality parameters (e.g., high levels of sperm DNA fragmentation). In other words, good semen quality is not a sufficient cause of fertility. Some of this should be immediately apparent. It is true that semen parameters are predictive of a couple's fertility both in couples with untested fertility[43] [44] and in subfertile couples.[45] [46] Therefore, it seems logical to assume that associations of environmental agents with semen quality will directly translate into associations with fertility. This assumption ignores two key facts. First, the relationship between semen parameters and fertility is not linear.[43] [44] [45] [46] Across studies, there appear to be threshold effects on the relationship between semen quality and couple fertility. Second, the World Health Organization (WHO) reference values for semen quality fall within the range of semen parameters empirically associated with couple fertility. As a result, falling above or below the reference levels has a relatively poor discriminative ability to identify fertile and infertile men as the semen quality distributions of these two groups of men overlap substantially.[29] [30] To this last point, it is worth keeping in mind that the reference values in the 5th and 6th editions of the WHO manual are based on the observed distribution of semen parameters among men with proven fertility and a time to pregnancy ≤12 months[40] [47] further proving the point that semen quality is not a sufficient cause of fertility. Even though the WHO manual itself[40] and others[48] caution against overinterpretation of the reference values and remind users of the manual that fertility must be considered as a continuum rather than a dichotomy, interpreting associations between environmental factors and semen quality as associations with fertility remain widespread.

A related conceptual problem is that thinking of semen quality as a strong proxy outcome for fertility has the additional underlying assumptions that (1) any effect identified with semen quality must have a downstream consequence and (2) lack of effect on semen quality rules out downstream effects. Both assumptions can be proven to be false. For example, soy intake or biomarkers of soy intake have been associated with lower semen quality to varying degrees in studies of men in subfertile couples,[49] and studies of pregnancy planners,[50] including in studies of men from East Asia[51] where intake of soy products is much higher than in western countries. However, the same studies that have documented associations between soy intake and biomarkers thereof with semen quality have failed to identify associations with time to pregnancy[52] or live birth rates during infertility treatment.[53] A similar situation has been documented for dietary patterns whereby dietary factors strongly related to semen quality are unrelated to fertility in the same study population.[54] [55] The opposite situation has also been documented. For example, even though there is abundant evidence that caffeine intake has no significant effect on semen quality,[56] it has been related to live birth rates during infertility treatment.[57] These examples demonstrate that associations between environmental factors and semen quality do not automatically imply that the same factor will affect fertility. Similarly, they also show that a lack of association with semen parameters does not imply a lack of association with fertility.

Despite the concerns discussed earlier, it is important to keep in mind that the problem of relying on semen quality as an outcome is not that it is not a good starting point; the problem is that it is often also the ending point. It may be useful to think about what the analogous outcome(s) would be in female fertility. A study documenting ovulation and assessing ovarian reserve and reproductive hormones can provide valuable insights into the hypothalamic–pituitary–ovarian axis in relation to environmental agents. However, few would equate this characterization as a valid proxy for fertility. If it is not sufficient to understand female fertility, why should it be to understand male fertility?

If Not the Way We Have Always Done It, Then How?

The challenges outlined in the previous sections are numerous and readers may get the impression that the road toward an improved understanding of male fertility is daunting. It does not have to be. As we have emphasized in previous sections, there is nothing inherently invalid about the core strategies used to date to understand how environmental factors affect male fertility. In fact, they have been enormously helpful (and our group has used these strategies a lot). The main problem is that these core strategies are insufficient. It may also be evident by this point that there will not be a single research strategy that will address all the concerns presented above. Instead, moving beyond the status quo will require addressing these concerns through multiple fronts. In this section, we discuss some examples of how the field is moving forward.

Studying Populations Not Selected for Fertility Status or Pregnancy Intention

The challenges of studying male individuals who are not selected based on fertility status align with logistical concerns for obtaining semen samples. There are instances in which this logistical concern has been successfully overcome. For example, since the mid-1990s, Jorgensen and colleagues at Rigshospitalet in Copenhagen have successfully recruited thousands of men presenting for military service fitness medical evaluations to complete semen analyses at the hospital after their military evaluations. This has resulted in one of the largest cohorts in the world of men from the general population that has been enormously useful understanding the impact of environmental and lifestyle factors on male reproductive function.[58] [59] [60] This study is unfortunately an exception as it directly benefited from the intersection of two circumstances that may be difficult to replicate elsewhere: a large, unselected population of men (military conscripts) presenting to a location where investigators had access to and control of an andrology laboratory.

The recent increase in the offerings for at-home semen testing opens an opportunity to diversify the groups of men included in studies of male reproductive function. Developments in this area have been reviewed in detail.[61] [62] Briefly, there are currently multiple devices in the United States and other markets that allow for at-home semen analysis testing. These devices fall into three broad categories: (1) devices that estimate sperm concentration based on centrifugation; (2) devices that estimate sperm concentration, or concentration and motility based on antibody reactions; and (3) microfluidic devices, often used in conjunction with a smartphone, that can estimate concentration alone or in conjunction with motility. Some investigators have already made use of these commercially available devices for research purposes.[63] We have used a smartphone-based system originally designed as a point-of-care device for setting without access to andrology laboratories[64] to assess concentration and motility in the Reproductive Effects of Chemicals and Air Pollutants (RECAP) Study,[65] a cohort embedded within the Growing Up Today Study[66]; a prospective cohort of individuals followed up since childhood throughout the United States.

The value of these technologies for research purposes depends on the validity and comprehensiveness of the methods used for remote collection and subsequent analysis of semen samples. Most of the commercially available at-home semen analysis devices assess only sperm concentration, and many provide only qualitative or semiquantitative information on sperm concentration. Importantly, while many of these products have been validated by performing simulated remote use against analyses conducted under standard clinical conditions, the results of these validation studies may overestimate the performance of these devices when used in real-life conditions. Nearly all validation studies have been performed using samples obtained from patients at fertility clinics which, as we mentioned earlier, are known to have a different distribution of semen parameters than men in the general population. In addition, most of these devices rely on participants self-processing their samples, which can be an important source of variability that is difficult to quantify and may not be captured in the validation studies conducted so far. Of note, none of the commercially available at-home testing products can provide CLIA-certified semen analysis results. In that regard, it is worth highlighting mail-in semen analysis services, some of which are able to provide CLIA-certified results, including results for motility.[67] Further refinement and evaluation of at-home testing methods, particularly as it relates to addressing their validity in real-life conditions, as well as broader use of CLIA-certified mail-in services for research purposes will be important to move the field forward by allowing male fertility research to move beyond the confines of fertility centers.

Embracing Exposomics

Exposome research aims to comprehensively investigate all environmental factors an individual is exposed throughout the life course and has been growing in interest.[68] [69] The three domains of exposome consist of (1) a general external environment, including the urban environment, climate, green spaces, and social capital; (2) a specific external environment such as diet, physical activity, consumer products, and smoking; and (3) an internal environment, including internal biological factors omics data.[70] It is not difficult to argue in favor of exposome-wide approaches to understanding health in general and men's reproductive health in particular. The challenge is doing it on a large scale and with limited budgets.

In RECAP, we used multiple strategies to achieve this goal. We embedded the study within an existing cohort. As a result, participants already have lifelong data, encompassing not only their demographic data, lifestyle factors, and health outcome data but also their mother's information and residential address histories, which allowed us to append information on a broad range of environmental exposures over decades. To further characterize men's exposures during the 90 days prior to semen sample collection, we collected data from three other sources of multidimensional data. First, participants were provided with a custom-built indoor sensor that captured data on indoor air pollution, temperature, and noise.[71] RECAP participants also used during this period the Beiwe smartphone app; an open-source non-for-profit application available for iOS and Android devices that allows the collection of research-grade accelerometry and geolocation data along with ecological momentary assessment micro-surveys[72] [73] that can be used to estimate geographically determined exposures with greater granularity than residential data alone and obtain dynamic measures of key behavioral risk factors. Last, participants were asked to wear a silicone wristband personal monitoring device which can be used to assess personal exposures to over 1,500 chemicals, including over 300 endocrine-disrupting chemicals.[74] Consequently, the combined data become unique exposome data.

The next challenge is handling exposome data with high dimensional structures with highly correlated variables. Mixture modeling methods such as Bayesian kernel machine regression and quantile-based g-computation have been developed to detect associations with large numbers of highly correlated environmental exposures, as opposed to individual exposures.[75] [76] These mixture models can accommodate multiple pollutants, account for nonlinear associations, and consider the interactions among pollutants.

Assessing Male Contributions to Fertility in Studies of Pregnancy Planners and Couples Undergoing Infertility Treatment

As mentioned earlier, the assumptions built into the use of semen quality parameters as the default outcome to understand how exposures to the male partner impact a couple's fertility are fragile and counterexamples have been documented. Because of the insufficient discriminative ability of semen parameters, there has been a long-standing interest in assessing nontraditional molecular markers of sperm integrity or function as additional proxy markers of male fertility. Some, such as methods used to assess sperm DNA fragmentation, are widely available and appear to provide valuable information not captured by semen parameters in the context of infertility treatment.[77] [78] Additional molecular markers that hold promise as markers of fertility that are not already captured by bulk semen parameters include sperm DNA methylation patterns, including sperm epigenetic clocks, sperm telomere length, and non-coding RNAs.[77] [79] [80] Clarifying the utility of these and future novel markers will depend on the extent to which they capture information that is independent of semen parameters and, crucially, the extent to which they can predict couple fertility.

This last issue requires an important shift in study design to the point where, ideally, the default study design is one where couples, rather than males or females alone, are recruited in studies sufficiently powered to assess pregnancy or live birth as the primary outcome. This task is difficult, but not impossible. Several groups have demonstrated that it is possible to recruit couples to evaluate the independent effects of exposure to males and females on fertility: an outcome where the unit of analysis is, inherently, the couple not either individual. Efforts have included prospective preconception cohorts explicitly recruiting couples rather than females only, such as the LIFE Study[81]; prospective preconception cohorts targeting enrollment of females with optional, opportunistic enrollment of male partners, such as the PRESTO Study[82]; and the preconception cohort embedded within the Nurses' Health Study 3[83]; recruitment of couples seeking infertility treatment, such as the EARTH Study[84]; and large randomized trials aimed at testing the effects of interventions on the male partner on couple fertility, such as the FAZST trial.[85] The most obvious advantage of this type of studies is being able to directly assess the impact of exposure to the male partner on a clinically relevant outcome while considering partner coexposures. They also do not negate the possibility of studying traditional semen quality parameters. Studies of couples undergoing infertility treatment with ART offer the additional advantage of shedding light into biologically relevant intermediate outcomes only observable in the setting of assisted reproduction.

Conclusion

Research aimed at understanding the impacts of the environment on male fertility has relied on three key and very common strategies: studying men presenting to fertility centers, studying one exposure at a time, and using semen quality parameters as the primary study outcome. Each of these strategies is very common as is the use of them in combination. In the recent literature, only three studies did not use any of the three strategies to describe the impact of environmental hazards on male fertility ([Table 1]). This strategy has been enormously fruitful and has advanced our understanding dramatically. It may not be possible to go much further, however, without embracing the creative design of studies that depart significantly from the current norm ([Fig. 1]).

Conflict of Interest

All authors have nothing to disclose.

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Publication History

Article published online:
10 February 2025