Prospective pregnancy study designs for assessing reproductive and developmental toxicants.
A growing body of evidence challenges traditional thinking that only in utero exposures are of concern for the health of the developing fetus. Specifically, reproductive biologists, epidemiologists, and toxicologists recognize the potential importance of parental exposures at critical periconceptional windows, in addition to exposures during organogenesis (Chapin et al. 2004; Selevan et al. 2000). A spectrum of human health end points can be conceptualized for study, as reflected in the evaluative guidelines set forth by various regulatory agencies or organizations (California Environmental Protection Agency 1991; European Commission 2002; International Programme on Chemical Safety 2001; Moore et al. 1995; U.S. Environmental Protection Agency 1991, 1996). Recent biomedical advances offer promise for population-based studies of this type that can potentially address the many critical data gaps that confront this field.
Strategies for weighing scientific evidence regarding reproductive and developmental toxicity highlight study design as a criterion for evaluating the strength of available evidence (Subcommittee on Reproductive and Developmental Toxicology 2001). Although experimental study designs present the strongest data, they are not an ethical option for assessing the effect(s) of potentially toxic exposures on human reproductive and developmental end points. Hence, observational designs are the sole choice for epidemiologic investigation. Among observational studies, data from properly designed and implemented prospective cohort studies usually receive more weight than data obtained via retrospective cohort or case-control studies. This is mainly because of the investigator's ability to ensure a temporal ordering between exposure(s) and outcome(s), measure exposure more accurately, measure relevant covariates at multiple time points, and minimize potential information biases (e.g., recall bias) (Adams 2001; Andersson et al. 2000; Reichman and Hade 2001; Werler et al. 1989). A recent example of recall bias in retrospective design is in a study that found poor reliability and recall bias in women's retrospective reports of exposure to chemicals during pregnancy (Till et al. 2002).
Several cohort studies have followed human development by studying pregnant women (Golding et al. 2001; Niswander and Gordon 1972). These studies, however, could not ascertain exposures (or collect biospecimens) at critical periconceptional windows and could not assess early reproductive outcomes (before clinically recognized pregnancy).
The most comprehensive and informative observational design is a prospective cohort study that measures exposures longitudinally (on both parents) beginning prior to pregnancy and continuing throughout pregnancy (if it occurs) and beyond. This study design, which we call a prospective pregnancy study with preconception enrollment, allows for the assessment of early exposures and a complete range of reproductive and developmental outcomes, key information for avoiding bias in evaluating effect(s) of potential toxicants (Tingen et al. 2004).
Prospective pregnancy studies are often described as difficult, intensive, and expensive to conduct, with limited overall yield, in this article, we examine the empirical evidence on the utility and feasibility of prospective pregnancy study designs for identifying reproductive and developmental toxicants. Although most prospective pregnancy studies focus on the determinants of sensitive end points (e.g., time to pregnancy and early pregnancy loss), a review of these issues is beyond the scope of this article. Our work is based on a systematic literature review to summarize relevant information on the planning, implementation, and relative success of this design.
We conducted a MEDLINE (http://www.ncbi.nlm.nih.gov/entrez/query.fcgl) search in May 2002 to locate published prospective pregnancy studies using the following search terms: prospective studies [MeSH term] AND (fertility OR fecundity OR time to pregnancy OR urine OR pregnancy). We sought to identify all large epidemiologic prospective pregnancy studies with preconception enrollment and at least a 3-month follow-up period. We reviewed the references cited by each study investigator to ensure that all relevant published works had been identified. Our initial search yielded 18 studies, of which 13 were selected for review. Five studies were excluded for the following reasons: a) clinical study focusing on postimplantation pregnancy (Miller et al. 1980); b) small sample size (n = 24, 13, and 13, respectively) (Hilgers et al. 1978; Li et al. 2002b; Sanders and Bruce 1997), and c) prospective study comprising only women with clinically recognized pregnancies (Li et al. 2002a). We later added two studies, published while we were finalizing this work (Buck et al. 2002; Wang et al. 2003), which resulted in a total of 15 studies available for review.
We developed a standardized data abstraction form that included author and year of primary (or methodologically oriented) publication; size of the target population; number of individuals contacted; number of eligible individuals; number of study participants; length of follow-up; type(s) of data collection, specifically, use of daily diaries and biospecimen collection (namely, urine and blood); semen collection; number of people dropping out of the study; and type(s) of incentives offered for participation.
Requests for specific information were sent to all primary authors in June 2002, with 100% response. The authors were asked to review and approve our summaries of their work and to provide missing information if possible. Both published and unpublished data obtained from the authors were summarized for our review. Several investigators were unsure or unable to enumerate the exact size of the target population, given the sampling strategy employed. Thus, the eligibility and participation percentages presented here should be regarded as best estimates.
Table 1 summarizes the sampling and recruitment strategies of the 15 selected prospective pregnancy studies. The first prospective pregnancy study with preconception recruitment was published in 1984 (France et al. 1984). By definition and selection, all studies used a prospective design with women/couples recruited prior to becoming pregnant. All but four studies (Brown et al. 1997; Ellish et al. 1996; Hakim et al. 1995; Zinaman et al. 1996) required that women/couples enroll prior to discontinuing contraception to ensure that the first ovarian cycle, measured in terms of the menstrual cycle, was at risk for pregnancy. Six authors estimated the size of their target population (Bonde et al. 1998; Brown et al. 1997; Buck et al. 2002; Ellish et al. 1996; Eskenazi et al. 1995; Hakim et al. 1995). Nine studies did not enumerate a denominator became of their reliance on community volunteers responding to recruitment advertisements or other such attempts to solicit participation (Colombo and Masarotto 2000; de Mouzon et al. 1988; France et al. 1984; Sweeney et al. 1988, 1989; Vartiainen et al. 1994; Wang et al. 2003, Wilcox et al. 1988; Zinaman et al. 1996).
Participants have been recruited from a number of diverse referent populations (general or medical communities, job sites, population-based registries), and on the basis of recreational exposures (e.g., anglers). Most investigators studied women, with only four studies focusing on couples (Bonde et al. 1998; Colombo and Masarotto 2000; de Mouzon et al. 1988; Zinaman et al. 1996). All but three studies (Hakim et al. 1995; Sweeney et al. 1988, 1989) were restricted to presumably fecund women, leaving us with limited understanding of the exposure profiles of couples with impaired fecundity. One author specifically addressed the yield of mixed recruitment strategies, with targeted letters being the most successful (72%), followed by health care providers (12%), health maintenance organization (HMO) newsletters (9%), clinic posters (4%), radio and television announcements (1%), and other methods (2%) (Brown et al. 1997).
When recruitment details were available (Table 2), the percentage of women/couples who were successfully contacted ranged from 2% in a population-based study of first pregnancy planners (Bonde et al. 1998) to 67% in a study of women working in the semiconductor industry (Eskenazi et al. 1995). Of particular note is the high percentage of contacts (46%) achieved by one group of investigators by mailing questionnaires to women of reproductive age who were listed in the New York State registry of licensed drivers (Ellish et al. 1996). The percentage of women/couples successfully contacted or eligible for enrollment could not be determined for every study because of the lack of available denominator information.
The percentage of eligible women/couples among those who were contacted ranged from 4% in a population-based study that targeted women of reproductive age (Ellish et al. 1996) to 95% in a volunteer community-based sample of couples desiring pregnancy (Zinaman et al. 1996) and 97% in a group of newly married textile workers in China (Wang et al. 2003). It should be noted that the number of women contacted and deemed eligible appeared to vary according to the recruitment strategy (i.e., those who publicized their eligibility criteria during the recruitment process contacted fewer women, but more of their contacts were eligible for participation).
Participation rates seemed to be influenced by both the recruitment strategy and the study design features, with rates ranging from 42% of women originally enrolled in a larger cohort study with a less intense protocol to 100% of community volunteers meeting eligibility criteria at one urban medical center. One group of investigators examined the degree to which pregnancy intentions influenced a woman's decision to participate (Sweeney et al. 1989). They found that only 2% of enrolled women reported actively trying to conceive during the 3-month study period, 46% reported using oral contraceptives or intrauterine devices, 24% reported using barrier methods or monitoring their cervical mucus and basal body temperature (BBT) to avoid pregnancy, 18% reported being sexually inactive, 8% reported being sexually active but not using contraception, and 2% reported being infertile.
Table 3 summarizes the follow-up and specimen collection details for each selected study. The length of follow-up varied by study purpose and intensity of the data collection. Study durations ranged from 3 to 12 months. The least intensive protocols included a minimum of baseline interviews with some prospective recording of relevant study factors with or without the collection of biologic specimens.
Daily diaries were used by 12 (80%) studies for varying periods of time ranging from 1 month to 12 at-risk menstrual cycles. The type of data collected with these diaries varied but typically included exposure(s) of interest, menstruation, fecundity signs (namely, vaginal mucus discharge and/or BBT), sexual intercourse, lifestyle behaviors (e.g., cigarette smoking, alcohol, caffeine, or vitamin/mineral consumption, illnesses, medications), and home pregnancy test results. Among those studies in which compliance rates were available, rates ranged from 80 to 98%, with the exception of one study that reported a 38% completion rate for the entire study protocol (France et al. 1984).
Four types of biospecimens have been collected in prospective pregnancy studies: urine, blood, semen, and breast milk. Biospecimen compliance rates were quite high among the studies for which information was available, ranging from 57 to 98% for urine, 86 to 93% for blood, 94 to 100% for semen, and 97% for a single postpartum breast milk sample. Our review suggests that once enrolled, women (and male partners, if applicable) will provide a variety of specimens for study purposes.
The reported study dropout rates varied widely, in part depending on how withdrawals were handled. (Some authors counted withdrawals as ineligible.) Moreover, some investigators requested that women/couples participate as long as possible, while others asked a priori for participation for a set period of time (e.g., 6 months). The lowest dropout rate (3%) was reported by one group of investigators in their 6-month prospective pregnancy study of community volunteers desiring pregnancy (Wilcox et al. 1988). France and associates reported the highest dropout rate (62%) in their study of couples desiring pregnancy who wished to preselect the sex of their child (France et al. 1984). Of the 148 women who dropped out of that study, 28% cited a change in pregnancy plans, 18% stated that the study was too demanding, 12% felt the study was too stressful, and 7% failed to become pregnant. Among other studies reporting reasons for dropout, the most common reasons were changes in pregnancy plans or health status (Bonde et al. 1998; Brown et al. 1997; Buck et al. 2002; Ellish et al. 1996; Sweeney et al. 1988).
Prospective pregnancy studies have offered varying levels of incentives for study participation. Notably, four (27%) authors reported offering no incentives for participation (Colombo and Masarotto 2000; Sweeney et al. 1988, 1989; Vartiainen et al. 1994). The largest incentive was US$500, which was given to couples upon completion of a protocol that required multiple clinic visits and sensitive procedures such as midcycle postcoital tests (Zinaman et al. 1996). Among U.S. studies reporting the use of incentives, the smallest was US$10, which was given either weekly (Wilcox et al. 1988) or every 2 months (Ellish et al. 1996) to women who participated in a protocol that included daily diaries and urine collection (the former had an attrition rate of 3% and the latter 7%). A recent study conducted in China paid women US$1 per three urine samples provided (Wang et al. 2003). Only two studies reported providing feedback to participants in the form of summarized menstrual cycle information (Buck et al. 2002; Hakim et al. 1995).
This review suggests that prospective pregnancy studies are a relatively new, powerful, and feasible design for examining the relation between biological, environmental, and lifestyle exposures and various reproductive and developmental outcomes. The utility of prospective pregnancy studies has greatly furthered our understanding of human reproduction and development, including notable advances such as estimates of the incidence of early [i.e., human chorionic gonadotrophin (hCG) identified] pregnancy loss and the elucidation of daily and cumulative probabilities of conception. Such information is crucial for accurately measuring the reproductive effects of exposures along the continuum of susceptible windows of human development.
Although more contacts may be required to identify a woman eligible for preconception enrollment in a prospective pregnancy study, the participation rates of eligible women are comparable to those seen in prospective studies of pregnant women. For example, 60% of eligible women enrolled in the Pregnancy, Infection, and Nutrition study, a prospective cohort study of the risk factors for preterm birth in North Carolina (Siega-Riz et al. 2001). In a captured HMO population, 39% of the eligible pregnant women were successfully recruited to participate in a population-based prospective cohort study in the Kaiser Permanente Medical Care Program in Northern California (Li et al. 2002a).
To address the lack of a sampling frame for women at risk of pregnancy, one investigator employed commercially available telephone directories (Lobdell et al. 2003). These inexpensive (< US$100) computerized directories contain the names, addresses, and telephone numbers of U.S. households, with each entry linked to basic census information. The census information enables investigators to assess sociodemographic differences between respondents and nonrespondents, as well as those that could not be reached because of inaccurate contact information. Targeted sampling is also possible by weighting or stratifying on ZIP or area code, if a specific subpopulation is desired.
An often-cited concern regarding the utility of prospective pregnancy studies is that participants are not representative of pregnant women as a whole because approximately half of all pregnancies in the United States are unintended (Henshaw 1998). Approximately 46% of unintended pregnancies result in live births (many are electively terminated) (Kannitz and Schnare 2001). Little empirical evidence exists to assess whether the prospective pregnancy study design results in a biased estimate of effect because of differing exposure scenarios among women with intended versus unintended pregnancies. However, the possibility of differing exposure profiles should always be given careful consideration, as women who plan their pregnancies are healthier, smoke and drink less, and have better diets than women who do not (Brown and Eisenberg 1995). Similarly, women who change unhealthy or risky behaviors are reported to be more educated, more likely to be employed, and from higher socioeconomic backgrounds than women who do not change behaviors (Beck et al. 2002; Joyce et al. 2000b; Kost et al. 1998).
Though yet unproven, the xenobiotic exposure profiles of women may also vary by pregnancy intention status. For example, hazardous waste sites and industrial sources of environmental pollution are often located in low-income communities (Farber and Krieg 2002; Morello-Frosch et al. 2002; Wilson et al. 2002) whose residents typically do not participate in research studies in the absence of targeted recruiting. Further, lifestyle factors such as cigarette smoking, alcohol use, and medications can influence the effects of environmental chemical exposures in humans (Anwar 1993; McCauley 1998). Given the potential for differing exposure profiles among pregnant women, coupled with the likelihood that some behaviors will be modified during pregnancy, the possible interactive effects of toxic agents and divergent lifestyle profiles during the peri-conceptional period (including those that are paternally mediated) must be evaluated. Prospective pregnancy study designs are the only reliable approach for such inquiry.
Additional concerns have been raised regarding the generalizability of prospective pregnancy studies because of research suggesting that women with intended pregnancies have fewer adverse pregnancy outcomes compared with mothers with unintended pregnancies (Piccinino and Mosher 1998). However, data from the National Longitudinal Survey of Youth suggest that differences in pregnancy outcomes by pregnancy intentions might be explained by the women's socioeconomic status rather than by planning status per se (Joyce et al. 2000a).
The conceptualization and measurement of intended or planned pregnancies has recently come under intense scrutiny, with many researchers in the field suggesting that more accurate measures are needed (Klerman 2000; Luker 1999; Sable 1999; Stanford et al. 2002; Trussell et al. 1999). For example, one study reported that 25% of women gave discordant responses to questions designed to assess pregnancy intentions in two large population-based surveys (Kaufmann et al. 1997). Discrepancies in pregnancy intention responses were associated with age, marital status, income, education, parity, time since pregnancy, and pregnancy outcome.
As with any epidemiologic investigation, researchers must weigh the relative importance of external validity in relation to internal validity (Grimes and Schulz 2002; Rothman and Greenland 1998). Given the difficulty in defining the exact size of the population from which participants in prospective pregnancy studies are recruited, empirical evaluation of external validity is often not possible. Although results from prospective pregnancy studies may not be generalizable to all women of reproductive age, they are likely to yield important observations that prompt additional studies.
As demonstrated in other pregnancy-related studies (Wyatt et al. 2002), prospective pregnancy studies with semen collection were successful in obtaining specimens from most male participants (Bonde et al. 1998; Vartiainen et al. 1994; Zinaman et al. 2000). Couple-based studies permit exploration of developmental toxicants that may be mediated through exposure of the embryo or fetus to the components of seminal fluid via intracanicular exposure or by absorbance of seminal fluid components into the bloodstream of the mother (Benziger and Edelson 1983; Sandberg et al. I968). Semen collection provides the opportunity to measure biological and chemical components of the seminal fluid (Lay et al. 2001; Younglai et al. 2002), perform standard sperm analyses, and even examine spermatozoal gene expression profiles (Ostermeier et al. 2002). The routine collection of semen specimens would further the assessment of human reproductive function, as these data could identify paternally mediated developmental effects. Semen analyses afford an opportunity to identify biomarkers that could delineate causal mechanisms of paternal toxicant exposure and/or fertility.
Our review suggests that study participants were generally willing to participate in studies even when they included time-consuming and/or invasive protocols for extended periods of time. Future studies may yield even higher rates of participation as technologic advances are incorporated into study protocols. Examples of relatively inexpensive technologies that could be implemented include specially programmed handheld devices to record menstrual cycle symptoms (Wyatt et al. 2002), home fertility monitors based on daily urine dipsticks (Behre et al. 2000) or salivary or vaginal probes (Fehring and Schlaff 1998), one-step luteinizing hormone tests (Nielsen et al. 2001), fingerprick blood spots (Worthman and Stallings 1997), home semen collection (Royster et al. 2000), and mouthwash methods for collecting genomic DNA (Lum and Le Marchand 1998). These technologies will be a useful addition to the biomarkers of fecundity and ovulation currently in use (e.g., vaginal mucus and BBT) (Stanford et al. 2002). For example, one recent study suggests early pregnancies can be detected with home pregnancy test kits (Buck et al. 2002). These kits have high sensitivity and specificity for detecting hCG concentrations of 25 mIU/mL, the level anticipated on the day following expected menstruation when conception has occurred (Ehrenkranz 2002). Because the timing of ovulation can vary in healthy women, this approach would be most accurate if used with a marker for ovulation (Wilcox et al. 2001).
Our assessment of the utility and feasibility of prospective pregnancy studies has several limitations. Only published prospective pregnancy studies were summarized for review. Though we made every effort to learn of all large-scale prospective pregnancy studies undertaken to dare, both published and unpublished, the possibility remains that we may have missed some studies. Further, although it would have been valuable to be able to include estimates of study costs and personnel, most investigators were unable to provide us with that information.
In summary, recruiting women/couples for prospective pregnancy studies prior to conception is feasible for both those planning pregnancy and those at risk of pregnancy. Among the population-based studies of women of reproductive age examined in this review (Bonde et al. 1998; Brown et al. 1997; Ellish et al. 1996), the number of participants divided by the size of the target population ranged from 0.8 to 4%. Using a conservative estimate, it therefore appears that about 120 women of reproductive age would need to be approached to identify one eligible woman/ couple planning pregnancy who might be willing to participate in a study of this type. Our review suggests that once recruited, women/ couples are often willing to complete very intensive protocols, even if only a modest incentive is provided. In one study, when an urban sample of women was presented with the choice of four protocols that ranged in intensity, 74% opted to participate in the most intense protocol (Sweeney et al. 1989).
As previously noted, individuals from underrepresented minority or economically disadvantaged groups should be targeted for recruitment, given their potentially higher risk of exposure to toxicants and possibly greater susceptibility (Sexton 1997). In so doing, investigators should consider factors reported to enhance participation, such as building trust with community participants (Shavers et al. 2002). Finally, couples experiencing fecundity-related impairments, including those undergoing assisted reproductive technologies, might represent another group suitable for study, in that exposure(s) to toxicants may be impairing their ability to conceive or carry a pregnancy to term.
Table 1. Target population, sampling unit, and recruitment strategy among the selected prospective pregnancy studies. Primary author Sampling (year) Target population unit Recruitment strategy Bonde (1998) Trade union Couples Letters members Brown (1997) HMO women of Women Letters to female reproductive HMO members (also age media and health providers) Buck (2002) Anglers and Women Letters partners Colombo (2000) Women seeking Couples Fertility awareness medical care teaching centers de Mouzon Community Couples Media and letters (1988) Ellish (1996) Motor vehicle Women Letters registry Eskenazi Semiconductor Women Letters (also (1995) workers informational meetings) France (1984) Women seeking Women Media and fertility medical care awareness teachers Hakim (1995) Semiconductor Women (a) Outreach talks and workers posters Sweeney (1988) Community Women (a) Media and letters Sweeney (1989) Motor vehicle Women (a) Letters registry and telephone directory Vartiainen Community Women Media (1994) Wang (2003) Newly wed Women Letters textile workers Wilcox (1988) Community Women (b) Media Zinaman (1996) Community Couples (c) Media, physician, and acquaintance referral (a) The sampling units were not required to be free of known fecundity or fertility impairments. Media include television, radio, and newspaper/poster announcements. (b) Men were enrolled after study was implemented; baseline questionnaire data available from approximately two-thirds of husbands. (Personal communication with authors.) (c) Female partner of couple had to be free of fecundity impairments. Table 2. Recruitment details for the selected prospective pregnancy studies. (a) Primary author (country) Year Context Eligibility criteria Bonde 1998 Couples recruited from No children (Denmark) Danish trade unions, Cohabiting office workers, nurses, Age 20-35 (nurses 23-39) and daycare workers years Planning to discontinue contraception Access to a telephone Working home freezer Partner within [+ or -] 10 years Excluded if either partner had previous reproductive experience Brown 1997 Participants recruited Female HMO member (United from Group Health, Age 18-35 years States) Inc., a large HMO in Planning to attempt Minneapolis and St. pregnancy in < 3 months Paul, Minnesota Nulliparas were recruited first, multiparas included later Multiparas excluded if planned attempt was within 12 months of most recent delivery Excluded if history of > 1 loss at less than 20 weeks, history of > 2 abortions, history of infertility, hypertension, diabetes, heart or kidney disease, or if pregnancy plans changed or pregnancy occurred before planned Buck 2002 Female members of the Indicated that they had (United New York State Angler not yet started or States) Cohort Study who completed childbearing indicated at enrollment Age 18-35 years in 1991 that they had Absence of infertility not yet completed or fecundity problems childbearing (self-reported) Colombo 2000 782 women recruited at Women experienced in the (Europe) seven European centers use of natural family (Milan, Verona, Lugano, planning Duesseldorf, Paris, Married or in a stable London, Brussels); most relationship were trying to avoid Age 18-40 years pregnancy In multiparas, must have had at least one menses after delivery/ breastfeeding Excluded if women were taking hormonal meds that could affect fertility or if either partner was sterile or had an endocrine disorder de Mouzon 1988 Couples in France Absence of contraception (France) without a history of during the study infertility who desired Existence of at least pregnancy one eligible menstrual cycle Interpretable cycles Knowledge of smoking status Ellish 1996 Women randomly selected Off contraception for (United from the 1987-1988 New [less than or equal to] States) York State Department 12 months of Motor Vehicles Planning to discontinue database of licensed contraception within 6 drivers who were living months in Albany County when Residence within the they applied for or prescribed area renewed their license Regular menstrual cycle length ([+ or -] 5 days) Eskenazi 1995 Women were recruited Not currently pregnant (United from seven silicon Menstruated within the States) wafer fabrication sites past 2 months in five U.S. companies Intercourse within the past 2 months Working home freezer No plan to leave the company within the next 3 months Ability to speak in English, Spanish, Vietnamese, or Tagalog Excluded if sterilized, using oral contraceptives, IUDs, had a sterilized partner, or using hormonal steroids that might affect fertility France 1984 Couples contemplating Proven fertility (New pregnancy in Auckland, Zealand) New Zealand, from 1979 to 1985 who had the desire to preselect the sex of their child Hakim 1995 Female employees at two Proven fertility (United semiconductor Women desiring pregnancy States) facilities in Vermont 42 years of age or and New York from May younger 1989 to August 1991 Excluded if using oral contraceptives, using an IUD, or surgically sterilized Sweeney 1988 University of Pittsburgh Women trying to become United employees and other pregnant States) area volunteers who were trying to become pregnant from October 1985 to October 1986 Sweeney 1989 Women were recruited Age 16-44 years (United from a particular Not currently pregnant States) section of Pittsburgh, Not menopausal Pennsylvania, in which Excluded if woman had a 89% of people were history of hysterectomy employed in service-oriented and blue-collar jobs Vartiainen 1994 First-time pregnancy Healthy couples without (Finland) planners were recruited a history of from the Kuopio area in infertility Eastern Finland Planning to have a baby Wang 2003 Newly married female Full-time employment (China) textile workers in Newly married China who intended to Age 20-34 years conceive Had permission to conceive Wilcox 1988 Women in the Research Age 18 years or older (United Triangle Park, North Not currently pregnant States) Carolina, area who were Excluded if they had a planning to discontinue history of fertility contraception problems or chronic illness Zinaman 1996 Couples discontinuing Women age 21-37 years (United contraception to become Men age 21-60 years States) pregnant Regular menstrual cycles (25-33 days) Men willing to provide semen samples Excluded if couples had been without contraception for > 3 months or if either partner had a history of infertility early pregnancy loss Primary author (country) Target (n) Contacts Eligible Participants Bonde 52,255 1,113 (2%) 851 (76%) 430 (51%) (Denmark) Brown 28,000 2,840 (10%) 1,649 (58%) 1,152 (70%) (United States) Buck 2,637 1,031 (39%) 244 (24%) 102 (42%) (United States) Colombo (b) (b) (b) 782 (Europe) de Mouzon (b) 4,200 (b) 1,887 (France) Ellish 16,800 7,649 (46%) 293 (4%) 227 (77%) (United States) Eskenazi 3,915 2,639 (67%) 739 (28%) 481 (65%) (United States) France (b) (b) (b) 239 (New Zealand) Hakim Over 5,000 (c) (b) (b) 148 (United States) Sweeney (b) 88 (b) 82 United States) Sweeney (b) (b) (b) 104 (United States) Vartiainen (b) 443 (c) (b) 191 (Finland) Wang (b) 1,006 (c) 971 (97%) 961 (99%) (China) Wilcox (b) (b) (b) 221 (c) (United States) Zinaman (b) 210 200 (95%) 200 (100%) (United States) Abbreviations: HMO, health maintenance organization; IUD, intrauterine device. (a) Cycles refer to menstrual cycles, whereas months refer to calendar time. (b) Information not available. (c) Personal communication with author(s). Table 3. Follow-up and specimen collection details for the selected prospective pregnancy studies. (a) Primary author (country) Year Participants Length of follow-up Daily diaries Bonde 1998 430 (51%) 6 cycles or until 1,329/1,657 (Denmark) pregnancy occurred completed (80%) Brown 1997 1,152 (70%) 12 cycles, second N/A (United miscarriage, or States) delivery if pregnancy occurred (b) Buck 2002 102 (42%) 12 cycles, or until 7 women (United first postpartum missing 1+ States) visit or cessation weekly of breastfeeding cards (b) (if nursing) Colombo 2000 782 Average of 8.6 80.6% included (Europe) cycles per woman BBT, 85.2% included cervical mucus score (b) de Mouzon 1988 1,887 12 cycles or until (c) (France) delivery if pregnancy occurred Ellish 1996 227 (77%) 12 cycles or until 1,304/1,516 (United pregnancy occurred (86%) States) completed (b) Eskenazi 1995 481 (65%) 6 cycles or 403 (84%) (United clinical pregnancy completed at States) least one cycle (b) France 1984 239 6 months oruntil 91 (38%) (New pregnancy occurred completed the Zealand) entire protocol (b) Hakim 1995 148 At least 6 months Near 100% (b) (United or until pregnancy States) occurred (mean = 7 cycles) Sweeney 1988 82 12 months or until (c) (United pregnancy occurred States) Sweeney 1989 104 3 cycles or until 81% (United the end of the States) first trimester if pregnancy occurred Vartiainen 1994 191 6 months or until 88% first f/u; (Finland) pregnancy occurred 59% second f/u; 39% third f/u (b) Wang 2003 961 (99%) 12 months or 545 (57%) (China) clinically completed at confirmed pregnancy least one after stopping cycle (b) contraception Wilcox 1988 221 (b) 6 months or until 98% (b) (United pregnancy occurred States) Zinaman 1996 200 (100%) 12 months or until Over 90% (b) (United pregnancy occurred States) Primary author Urine Blood Semen (country) samples sample(s) sample(s) Bonde Women: Women: 418/430 (Denmark) 9,671 (83%) 288/317 (91%) (97%) Men: Men: 820 (59%) 350/376 (93%) Brown N/A N/A N/A (United States) Buck N/A 88/102 (86%) N/A (United States) Colombo N/A N/A N/A (Europe) de Mouzon N/A N/A N/A (France) Ellish 95% N/A N/A (United States) Eskenazi 84% N/A N/A (United completed States) at least one cycle (b) France (c) N/A N/A (New Zealand) Hakim 90% N/A N/A (United States) Sweeney Among those N/A N/A (United conceiving, States) 84% provided daily urines (88% weekly urines) Sweeney 80% N/A N/A (United States) Vartiainen N/A N/A 180 (94%) (b) (Finland) Wang 545 (57%) N/A N/A (China) completed at least one cycle (b) Wilcox 98% N/A N/A (United States) Zinaman Over 90% (b) (c) 100% (United (participation States) requirement) Primary author Dropped out (country) of the study Incentive(s) to participate Bonde 35 (8%) $200 for specimens; (Denmark) participants entered in a lottery for $3,000 (b) Brown 510 (44%) $100 for completion and (United small gifts (e.g., pencils) States) with newsletters Buck 20 (20%) $50 for completion (United through postpartum States) blood and breast milk (97% of women provided a postpartum breast milk; 74% provided a second sample upon weaning) (b) Colombo 300 (25%) None (b) (Europe) 84 of these women re-entered (b) de Mouzon 687 (36%) (c) (France) Ellish 7% $10 for every 2 months of (United participation; lab results States) were forwarded to physicians (b) Eskenazi 78 (16%) $35 for each month of (United participation; eligible for States) a prize drawing for a trip to Hawaii or other local resort France 148 (62%) Personal instruction (New regarding fertility Zealand) awareness and the Shettles theory of sex selection (b) Hakim 24 (16%) (b) $100 for completion of (United the study, feedback on States) menstrual cycles Sweeney 45 (55%) None (b) (United States) Sweeney (c) None (b) (United States) Vartiainen 11 (6%) None (b) (Finland) Wang 35 (4%) $1 per three urine (China) samples (b) Wilcox 6 (3%) $10/week for urine (United collection States) Zinaman 8 (4%) $500 for completion of (United the study States) Abbreviations: f/u, follow-up; N/A, information not applicable. (a) Cycles refer to menstrual cycles, whereas months refer to calendar time. (b) Personal communication with author(s). (c) Information not available.
We thank the principal investigators of the prospective pregnancy studies included in this review for their pioneering work and generous time devoted to answering our many inquiries. In addition, we acknowledge members of the Fertility and Early Pregnancy Working Group, National Children's Study, for their critical review of this work.
This article is part of the mini-monograph "Understanding the Determinants of Children's Health."
The views in this article reflect those of the authors and not necessarily those of their affiliated institutions. The information in this document has been subjected to review by the National Health and Environmental Effects Research Laboratory (U.S. EPA) and approved for publication. Approval does not signify that the contents reflect the views of the Agency, nor does mention of trade names or commercial products constitute endorsement or recommendation for use.
The authors declare they have no competing financial interests.
Adams M. 2001. Validity of birth certificate data for the outcome of the previous pregnancy, Georgia, 1999-1995. Am J Epidemiol 154:883-888.
Andersson SW, Niklasson A, Lapidus L, Hallberg L, Bengtsson C, Hulthen L. 2000. Poor agreement between self-reported birth weight and birth weight from original records in adult women. Am J Epidemiol 152:609-616.
Anwar WA. 1993. Chemical interaction: enhancement and inhibition of clastogenicity. Environ Health Perspect 101(suppl 3):203-206.
Beck LF, Morrow B, Lipscomb LE, Johnson CH, Gaffield ME, Rogers M, et al. 2002. Prevalence of selected maternal behaviors and experiences, Pregnancy Risk Assessment Monitoring System (PRAMS). 1999. MMWR Surveill Summ 51:1-27.
Behre HM, Kuhlage J, Gassner C, Sonntag B, Schem C, Schneider HP, et al. 2000. Prediction of ovulation by urinary hormone measurements with the home use ClearPlan Fertility Monitor: comparison with transvaginal ultrasound scans and serum hormone measurements. Hum Reprod 15: 478-2482.
Benziger DP, Edelson J. 1983. Absorption from the vagina. Drug Metab Rev 14:137-168.
Bonde JP, Hjollund NH, Jensen TK, Ernst E, Kolstad H, Henriksen TB, et al. 1998. A follow up study of environmental and biologic determinants of fertility among 430 Danish first pregnancy planners: design and methods. Reprod Toxicol 12:19-27.
Brown JE, Jacobs DRJ, Barosso GM, Potter JD, Hannan PJ, Kopher RA, et al. 1997. Recruitment, retention and characteristics of women in a prospective study of preconceptional risks to reproductive outcomes: experience of the Diana Project. Paediatr Perinat Epidemiol 11:345-358.
Brown SS, Eisenberg L. 1995. Unintended Pregnancy and the Well-being of Children and Family. Washington, DC: National Academy Press.
Buck G, Vena JE, Greizerstein HB, Weiner JM, McGuinness B, Mendola P, et al. 2002. PCB congeners and pesticides and female fecundity, New York State Angler Prospective Pregnancy Study. Environ Toxicol Pharmacol 12:83-82.
California Environmental Protection Agency. 1991. Draft Guidelines for Hazard Identifications and Dose-Response Assessment of Agents Causing Developmental and/or Reproductive Toxicity. Sacramento, CA:California Department of Health Services, Health Hazard Assessment Division, Reproductive and Cancer Hazard Assessment Section.
Chapin RE, Robbins WA, Schieve LA, Sweeney AM, Tabacova SA, Tomashek KM. 2004. Off to a good start: the influence of pre-and periconceptional exposures, parental fertility, and nutrition on children's health. Environ Health Perspect Environ Health Perspect 112:69-78.
Colombo B, Masarotto G. 2000. Daily fecundability: first results from a new data base. Demogr Res 3.
de Mouzon J, Spira A, Schwartz D. 1988. A prospective study of the relation between smoking and fertility. Int J Epidemiol 17:378-384.
Ehrenkranz JR. 2002. Home and point of-care pregnancy tests: a review of the technology. Epidemiology 13:S15-S18.
Ellish NJ, Saboda K, O'Connor J, Nasca PC, Stanek EJ, Boyle C. 1996, A prospective study of early pregnancy loss. Hum Reprod 11:406-412.
Eskenazi B, Gold EB, Samuels SJ, Wight S, Lasley BL, Hammond SK, et al. 1995. Prospective assessment of fecundability of female semiconductor workers, Am J Ind Med 28:817-831.
European Commission. 2002. 7th Amendment: Toxic to Reproduction, Guidance to Classification. Technical Report 47. Brussels:European Commission.
Farber DR, Krieg EJ. 2002. Unequal exposure to ecological hazards: environmental injustices in the Commonwealth of Massachusetts. Environ Health Perspect 110(suppl 2): 277-280.
Fehring RJ, Schlaff WD. 1998. Accuracy of the Ovulon fertility monitor to predict and detect ovulation. J Nurse Midwifery 43:117-120.
France JT, Graham FM, Gosling L, Hair PI. 1984. A prospective study of the preselection of the sex of offspring by timing intercourse relative to ovulation. Fertil Steril 41:894-900.
Golding J, Pembrey M, Jones R. 2001, ALSPAC--the Avon Longitudinal Study of Parents and Children. I. Study methodology. Paediatr Perinat Epidemiol 15:74-87.
Grimes DA, Schulz KF. 2002. Bias and causal associations in observational research. Lancet 359:248-252.
Hakim RB, Gray RH, Zacur H. 1995. Infertility and early pregnancy loss. Am J Obstet Gynecol 172:1510-1517.
Henshaw SK. 1998. Unintended pregnancy in the United States, Fam Plann Perspect 30:24-29, 46.
Hilgers TW, Abraham GE, Cavanagh D. 1978. Natural family planning. I. The peak symptom and estimated time of ovulation. Obstet Gynecol 52:575-582.
International Programme on Chemical Safety. 2001. Environmental Health Criteria 225. Principles for Evaluating Health Risks to Reproduction Associated with Exposure to Chemicals. Geneva:World Health Organization.
Joyce TJ, Kaestner R, Korenman S. 2000a. The effect of pregnancy intention on child development. Demography 37:83-94.
--.2000b. The stability of pregnancy intentions and pregnancy-related maternal behaviors. Matern Child Health J 4:171-178.
Kaufmann RB, Morris L, Spitz AM. 1997. Comparison of two question sequences for assessing pregnancy intentions. Am J Epidemiol 145:810-816.
Kaunitz AM, Schnare SM. 2001. Unintended pregnancies: cause, consequences, and prevention. Clin Courier 19:1-11.
Klerman LV. 2000. The intendedness of pregnancy: a concept in transition. Matern Child Health J 4:155-162.
Kost K, Landry DJ, Darroch JE. 1998. Predicting maternal behaviors during pregnancy: does intention status matter? Fam Plann Perspect 30:79-88.
Lay MF, Richardson ME, Boone WR, Bodine AB, Thurston RJ. 2001. Seminal plasma and IVF potential. Biochemical constituents of seminal plasma of males from in vitro fertilization couples. J Assist Regrod Genet 18:144-150.
Li D-K, Odouli R, Wi S, Janevic T, Golditch I, Bracken TD, et al. 2002a. A population-based prospective cohort study of personal exposure to magnetic fields during pregnancy and the risk of miscarriage. Epidemiology 13:9-20.
Li H, Chen J, Overstreet JW, Nakajima ST, Lasley BL. 2002b. Urinary follicle-stimulating hormone peak as a biomarker for estimating the day of ovulation. Fertil Steril 77:961-966.
Lobdell DT, Buck GM, Weiner JM, Mendola P. 2003. Using commercial telephone directories to obtain a population-based sample for mail survey of women of reproductive age. Paediatr Perinat Epidemiol 17:1-8.
Luker KC. 1999. A reminder that human behavior frequently refuses to conform to models created by researchers. Fam Plann Perspect 31:248-249.
Lum A, Le Marchand L. 1998. A simple mouthwash method for obtaining genomic DNA in molecular epidemiological studies. Cancer Epidemiol Biomarkers Prev 7:719-724.
McCauley LA. 1999. Chemical mixtures in the workplace. Research and practice. AAOHN J 46:29-40.
Miller JF, Williamson E, Glue J, Gordon YB, Grudzinskas JG, Sykes A. 1980. Fetal loss after implantation. A prospective study. Lancet 2:554-556.
Moore JA, Daston GP, Faustman E, Golub MS, Hart WL, Hughes C Jr., et al. 1995. An evaluative process for assessing human reproductive and developmental toxicity of agents, Reprod Toxicol 9:61-95.
Morello-Frosch R, Pastor M Jr, Porras C, Sadd J. 2002. Environmental justice and regional inequality in southern California: implications for future research. Environ Health Perspect 110(suppl 2):149-54.
Nielsen MS, Barton SD, Hatasaka HH, Stanford JB. 2001. Comparison of several one-step home urinary luteinizing hormone detection test kits to OvuQuick. Fertil Steril 76:384-387.
Niswander KR, Gordon M. 1972. The Women and Their Pregnancies. Philadelphia:W.B. Saunders.
Ostermeier GC, Dix DJ, Miller B, Khatri P, Krawetz SA. 2002. Spermatozoal RNA profiles of normal fertile men. Lancet 360:772-77.
Piccinino LJ, Mosher WD. 1998. Trends in contraceptive use in the United States: 1982-1995. Faro Plann Perspect 30:4-10, 46.
Reichman NE, Hade EM. 2001, Validation of birth certificate data. A study of women in New Jersey's HealthStart program. Ann Epidemiol 11:186-193.
Rothman KJ, Greenland S, eds. 1998. Modern Epidemiology. 2nd ed. Philadelphia:Lippincott-Raven Publishers.
Royster MO, Lobdell DT, Mendola P, Perreault SD, Selevan SG, Rothmann SA, et al. 2000. Evaluation of a container for collection and shipment of semen with potential uses in population-based, clinical, and occupational settings. J Androl 21:478-484.
Sable MR. 1999. Pregnancy intentions may not be a useful measure for research on maternal and child health outcomes. Fam Plann Perspect 31:249-250.
Sandberg F, Ingelman-Sundberg A, Ryden G, Joelsson I. 1968. The absorption of tritium-labelled prostaglandin E1 from the vagina of non-pregnant women, Acta Obstet Gynecol Scand 47:22-26.
Sanders KA, Bruce NW. 1997. A prospective study of psychosocial stress and fertility in women. Hum Reprod 12:2324-2329.
Selevan SG, Kimmel CA, Mendola p. 2000. Identifying critical windows of exposure for children's health. Environ Health Perspect 108(suppl 3):451-155.
Sexton K, 1997. Sociodemographic aspects of human susceptibility to toxic chemicals: do class and race matter for realistic risk assessment? Environ Toxicol Pharmacol 4:261-269.
Shavers VL, Lynch CF, Burmeister LE. 2002. Racial differences in factors that influence the willingness to participate in medical research studies. Ann Epidemiol 12:248-256.
Siega-Riz AM, Herrmann TS, Savitz DA, Thorp JM. 2001. Frequency of eating during pregnancy and its effect on preterm delivery. Am J Epidemiol 153:647-652.
Stanford JB, White G, Hatasaka H. 2002. Timing intercourse to achieve pregnancy: current evidence. Obstet Gynecol 100:1333-1341.
Subcommittee on Reproductive and Developmental Toxicology. 2001. Evaluating Chemical and Other Agent Exposures for Reproductive and Developmental Toxicity. Washington, DC:National Academy Press.
Sweeney AM, Meyer MR, Aarons JH, Mills JL, LaPorte RE. 1988. Evaluation of methods for the prospective identification of early fetal losses in environmental epidemiology studies. Am J Epidemiol 127:843-850.
Sweeney AM, Meyer MR, Mills JL, Aarons JH, LaPorte RE. 1989. Evaluation of recruitment strategies for prospective studies of spontaneous abortion. J Occup Meal 31:980-985.
Till C, Koren G, Rovet JF. 2002. Agreement between prospective and retrospective reports of maternal exposure to chemicals during pregnancy. J Occup Environ Med 44:708-713.
Tingen C, Stanford JB, Dunson DB. 2004. Methodologic and statistical approaches to studying human fertility and environmental exposure. Environ Health Perspect 112:97-93.
Trussell J, Vaughan B, Stanford J. 1999. Are all contraceptive failures unintended pregnancies? Evidence from the 1995 National Survey of Family Growth. Fam Plann Perspect 31:246-247, 260.
U.S. Environmental Protection Agency. 1991. Guidelines for developmental toxicity risk assessment. Fed Reg 56:63797-63826.
--.1996. Reproductive toxicity risk assessment guidelines. Fed Reg 61:56273-56322.
Vartiainen H, Saarikoski S, Halonen P, Rimon R. 1994. Psychosocial factors, female fertility and pregnancy: a prospective study--part I. Fertility. J Psychosom Obstet Gynaecol 15:67-75.
Wang X, Chen C, Wang L, Chen D, Guang W, French J. 2003. Conception, early pregnancy loss, and time to clinical pregnancy: a population-based prospective study. Fertil Steril 79:577-504.
Werler MM, Pober BR, Nelson K, Holmes LB. 1989. Reporting accuracy among mothers of malformed and nonmalformed infants. Am J Epidemiol 129:415-421.
Wilcox AJ, Baird DD, Dunson D, McChesney R, Weinberg CR. 2001. Natural limits of pregnancy testing in relation to the expected menstrual period. JAMA 286:1759-1761.
Wilcox AJ, Weinberg CR, O'Connor JF, Baird DD, Schlatterer JP, Canfield RE, et al. 1988. Incidence of early loss of pregnancy, N Engl J Med 319:180-194.
Wilson SM, Howell F, Wing S, Sobsey M. 2002, Environmental injustice and the Mississippi hog industry. Environ Health Perspeet 110(suppl 2):195-201.
Worthman CM, Stallings JF. 1997. Hormone measures in fingerprick blood spot samples: new field methods for reproductive endocrinology. Am J Phys Anthropol 104:1-21.
Wyatt KM, Dimmock PW, Hayes-Gill B, Crowe J, O'Brien PM. 2002. Menstrual symptometrics: a simple computer-aided method to quantify menstrual cycle disorders, Fertil Steril 78:96-101.
Younglai EV, Foster WG, Hughes EG, Trim K, Jarrell JE. 2002, Levels of environmental contaminants in human follicular fluid, serum, and seminal plasma of couples undergoing in vitro fertilization. Arch Environ Contam Toxicol 43:121-126.
Zinaman MJ, Brown CC, Selevan SG, Clegg ED. 2000. Semen quality and human fertility: a prospective study with healthy couples. J Androl 21:145-153.
Zinaman MJ, Clegg ED, Brown CC, O'Connor J, Selevan SG. 1995. Estimates of human fertility and pregnancy loss. Fertil Steril 65:503-509.
Germaine M. Buck, (1) Courtney D. Lynch, (1) Joseph B. Stanford, (2) Anne M. Sweeney, (3) Laura A. Schieve, (4) John C. Rockett, (5) Sherry G. Selevan, (6) and Steven M. Schrader (7)
(1) Epidemiology Branch, National Institute of Child Health and Human Development, National Institutes of Health, Department of Health and Human Services, Rockville, Maryland, USA; (2) Department of Family Preventive Medicine, Health Research Center, University of Utah, Salt Lake City, Utah, USA; (3) Department of Epidemiology, Texas A&M University Health Science Center, School of Rural Public Health, Bryan, Texas, USA; (4) Division of Reproductive Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia, USA; (5) Gamete and Early Embryo Research Branch, Reproductive Toxicology Division, National Health and Environmental Effects Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA; (6) National Center for Environmental Assessment, Office of Research and Development, U.S. Environmental Protection Agency, Washington, DC, USA; (7) Reproductive Health Assessment Section, Division of Applied Research and Technology, National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Cincinnati, Ohio, USA
Address correspondence to G. Buck, Epidemiology Branch, NICHD, NIH, DHHS, 6100 Executive Blvd., Rm. 7B03, Rockville, MD 20852 USA. Telephone: (301) 496-6155. Fax: (301) 402-2084. E-mail: email@example.com
Received 6 February 2003; accepted 2 September 2003.
|Printer friendly Cite/link Email Feedback|
|Author:||Schrader, Steven M.|
|Publication:||Environmental Health Perspectives|
|Date:||Jan 1, 2004|
|Previous Article:||Off to a good start: the influence of pre- and periconceptional exposures, parental fertility, and nutrition on children's health.|
|Next Article:||Methodologic and statistical approaches to studying human fertility and environmental exposure.|