- Open Access
- Open Peer Review
The Home Observation of Periconceptional Exposures (HOPE) study, a prospective cohort: aims, design, recruitment and compliance
© The Author(s). 2016
- Received: 2 March 2016
- Accepted: 31 May 2016
- Published: 8 June 2016
To examine transient environmental exposures and their relationship with human fecundity, exposure assessment should occur optimally at the time of conception in both members of the couple.
We performed an observational, prospective cohort study with biomonitoring in both members of a heterosexual couple trying to conceive. Couples collected urine, saliva, and semen specimens for up to two menstrual cycles on days corresponding to the time windows of fertilization, implantation, and early pregnancy, identified based on the woman’s observations of her cervical fluid.
Three hundred nine eligible couples were screened between 2011 and 2015, of which 183 enrolled. Eleven couples (6.0 %) withdrew or were lost to follow up. The most successful and cost effective recruiting strategies were word of mouth (40 % of participating couples), posters and flyers (37 %), and targeted Facebook advertising (13 %) with an overall investment of $37.35 spent on recruitment per couple. Both men and women collected ≥97.2 % of requested saliva samples, and men collected ≥89.9 % of requested semen samples. Within the periovulatory days (±3 days), there was at least one urine specimen collected by women in 97.1 % of cycles, and at least one by men in 91.7 % of cycles. Daily compliance with periovulatory urine specimens ranged from 66.5 to 92.4 % for women and from 55.7 to 75.0 % for men. Compliance was ≥88 % for questionnaire completion at specified time points.
Couples planning to conceive can be recruited successfully for periconceptional monitoring, and will comply with intensive study protocols involving home collection of biospecimens and questionnaire data.
- Endocrine disrupting chemicals
- Research participant recruitment
A growing body of evidence suggests that environmental exposures during the sensitive windows of the periconceptional period are of concern for the reproductive health of mother and embryo [1–3]. Related research demonstrates that environmental contamination by endocrine disrupting chemicals during the fetal period affects virtually all organ systems in fetal development and throughout subsequent life [4–6]. Transient exposures may have critical influences on fertility, spontaneous abortion, and embryonic development, but limitations in exposure assessment hamper our ability to understand these effects. To monitor transient exposures at or near the time of conception, the time of ovulation must be identified prospectively and targeted exposure assessment must occur during the relevant developmental windows [7–9].
Conception (fertilization in vivo) is a highly-timed, couple-based process . A prospective design that follows couples longitudinally beginning prior to conception and through a pregnancy or pregnancy loss, although methodologically challenging, allows the investigator to capture exposure data during the time-sensitive fertile window and to understand the temporal ordering between exposures and outcomes [8, 11, 12]. Home collection of data and biological specimens by study participants can minimize participant burden while still assessing exposure during the most time-sensitive periods of the fertile window, ovulation, and implantation [13, 14]. Women’s self-observation of cervical fluid patterns has been repeatedly validated as an effective approach for identifying the approach and timing of ovulation [15–17] (i.e., the fertile window [18, 19]), but this approach has not been applied to studies assessing environmental exposures in couples trying to conceive.
We designed and successfully implemented a prospective pregnancy study with home-based collection of data and biological specimens to achieve several aims: (1) conduct prospective, periovulational biomonitoring in a preconception cohort using a novel strategy of self-collection of biological specimens timed according to women’s observation of their own fertility signs among couples with normal fertility; (2) evaluate the association between prospectively measured male and female environmental exposures (primarily bisphenol-A (BPA) and disinfection-by-products) and semen quality and time to pregnancy; and (3) quantify the degree of misclassification bias generated by retrospective exposure assessment methods in common use (participant self-report of past exposure using a recall questionnaire and/or archival environmental monitoring data) compared to concurrent periovulational biomonitoring and report of exposures. This paper addresses our first aim and describes design and implementation of the study protocol. We assess the methodological soundness of our approach by evaluating recruitment, cost of recruitment, eligibility, enrollment, and compliance with collection of appropriately timed biospecimens.
Study design, eligibility, and recruitment
The Home Observation of Periconceptional Exposures (HOPE) study is an observational, prospective cohort study designed to accomplish home-collected, individual-level biomonitoring among heterosexual couples during the sensitive windows of conception, implantation, and very early pregnancy. The University of Utah Institutional Review Board approved the study and written informed consent was obtained from all participants prior to enrollment. Couples were recruited and followed for up to 12 months between 2011 and 2015. Screening was conducted with an online questionnaire (Qualtrics, Provo, Utah, USA) with each member of the couple individually screened to ensure that s/he met eligibility criteria. The inclusion criteria were ages 18–35 for women, ages 18–40 for men, both in a heterosexual relationship, and planning to start trying to conceive within three months of study enrollment. Couples needed to reside within one hour of the study office and be able to respond to study questionnaires and instructions in English. Female exclusion criteria included fewer than nine menstrual flows in the previous twelve months (unless due to breastfeeding or use of an intrauterine device (IUD) with a subsequent return to normal menses); use of implantable hormonal contraception in the previous two months; use of injectable medroxyprogesterone acetate (Depo-Provera®) in the last twelve months. Women were also excluded if they had previously performed daily tracking of cervical fluid but had been unable to identify ovulation due to observations of continuous fluid, no fluid, or unchanging fluid patterns. Couples were excluded if either member of the couple had a previous diagnoses of infertility, subfertility, or a condition that might affect fertility such as diagnosed polycystic ovary syndrome (PCOS) or endometriosis without a subsequent pregnancy among women, and low sperm count among men, or had ever been unsuccessful in conceiving a child after a year or more of regular sexual intercourse without contraception. Our recruitment goal was 300 couples, which we estimated would be a feasible target while providing opportunity to detect variation in time to pregnancy.
Several strategies were implemented to recruit participant couples, including newspaper advertisements, flyers placed around the community and on university and college campuses, targeted Facebook advertising, targeted Google AdWords advertising, campus-wide email listservs, and word of mouth. The online screening questionnaire included a question to determine recruitment method for each inquiring individual. Participants were encouraged to refer friends to the study and were compensated $10 for every referred couple successfully enrolled up to three referrals.
Couples who met the inclusion criteria and consented to participate met with a member of the study staff for an in-person enrollment that took place at the couple’s convenience either in their home, or in a mutually convenient location with sufficient privacy. During enrollment the study staff explained the study procedures, demonstrated use of the online data entry system, explained the daily fertility charting, obtained height and weight measurements, collected hair snips, and explained or demonstrated techniques for home collection of biospecimens. Throughout the study, staff communicated with couples on an individualized basis, via their preferred method (e.g. phone, text, or email).
Daily fertility chart
Active and passive observation periods
The active observation period began in the first cycle after enrollment in which the couples planned to try to conceive and continued for up to two menstrual cycles in which the couple continued to report intention to conceive and an EDO/C was observed. If the couple did not achieve pregnancy within the first two active observation cycles, fertility charting (including the daily exposure questions) continued until the completion of the passive observation period. For couples who conceived in the first cycle of active observation, the end of the passive observation period was Cycle 1 EDO/C + 38 weeks. For all other couples the end of the passive observation period was Cycle 2 EDO/C + 38 weeks regardless of pregnancy status.
Concurrent and retrospective online questionnaires
In addition to the exposure questions on the daily fertility charts, concurrent (once at EDO/C +2 days) and retrospective (one time each at EDO/C + 18 days, EDO/C + 6 weeks, and EDO/C + 38 weeks) online exposure assessment questionnaires were completed related to the first two complete cycles of active observation, or only the first cycle if the couple conceived during Cycle 1. Questionnaires were completed through a secure response-interface (Qualtrics, Provo, Utah) and were designed to assess exposure to food, water, and lifestyle factors during the week of the EDO/C. The timing of retrospective assessments were selected to correspond to specific time points during pregnancy when early exposure may be assessed: EDO/C + 18 days corresponds to the day when a woman may notice delayed menses; EDO/C + 6 weeks corresponds to when a woman may have a first prenatal appointment (approximately 8 weeks following her last menstrual period); EDO/C + 38 weeks corresponds to when a woman would be expected to deliver a baby. However, questionnaires were administered to everyone in the study, whether or not they became pregnant within the active observation period (first two cycles).
Women with live births resulting from conceptions that occurred during the study were asked to complete an additional questionnaire 3 weeks after the estimated date of delivery to assess pregnancy outcomes, and to provide medical release of information forms to allow study staff to access the prenatal and obstetrical medical records. Women who did not conceive during the study were contacted six months after study completion and asked to complete a questionnaire designed to ascertain any pregnancy or medical treatment that may have occurred beyond the study observation period .
Participants were instructed to perform biospecimen collection during the first two cycles of active observation. Men and women both were asked to collect daily first-morning urine samples (first void upon waking) from the first day of fertile-quality cervical fluid throughout the fertile window until the EDO/C + 2 days. Men were asked to discontinue collecting after EDO/C + 2 days (the end of the biologically relevant time period for conception), and women were asked to continue to collect for the remainder of the menstrual cycle until the onset of the next menses or until she had a positive home pregnancy test (QuickVue, Quidel, San Diego, CA, USA) at EDO/C + 18 days. In cases where first-morning samples were not collected, participants were instructed to collect later in the day and mark the specimen to indicate that it was not first-morning. Urine was collected in four-ounce polypropylene specimen cups then transferred to 50 mL polypropylene tubes that were placed in the participants’ home freezer until the end of the menstrual cycle. At the end of each cycle, a member of the study staff collected the samples from the participants and transported them to the laboratory.
Both members of the couple completed a saliva specimen using a Quantisal Oral Fluid Collection Device (Immunalysis, Pomona, CA, USA) on EDO/C + 2 days. These specimens were retrieved by study staff at the end of each cycle.
A semen sample from the man was collected at home through intercourse after EDO/C + 2 days but before the onset of menses of EDO/C + 18 days using a Male-FactorPak™ semen collection device (Apex Medical Technologies, Inc., San Diego, CA, USA) . The semen sample was frozen in the participant’s home freezer and picked up by staff at the end of the cycle. Abstinence prior to semen sample collection was not required but acts of intercourse were to be tracked on the daily fertility chart.
Couples were compensated up to $400 USD as follows: $15/cycle for completion of two fertility charts and EDO/C + 2 day questionnaires (women); $20/cycle for semen samples and completion of the EDO/C + 2 day questionnaire (men); $10/cycle/person for saliva samples; $20/cycle/person for urine samples; $7.50/cycle/person for EDO/C + 18 day questionnaires; $12.50/cycle/person for EDO/C + 6 week questionnaires; $15/cycle/person for EDO/C + 38 week questionnaires; $20/person study completion bonus; $10/couple for acquaintance referral up to three. Couples who conceived in the first cycle of study participation were compensated what they would have received had they participated in a second cycle to avoid any incentive to delay conception in order to increase compensation .
Descriptive statistics were calculated to summarize cohort characteristics, biospecimen collection compliance, and questionnaire completion using SAS software (SAS version 9.4, SAS Institute, Inc., Cary, NC, USA).
Reasons for initial ineligibility by sexa
Reason for ineligibility
(n = 76)
(n = 267)
>1 h drive from Salt Lake City
Unable to respond to questionnaires in English
Not planning to conceive within 3 monthsc
Medroxy-progesterone acetate injection in last 12 months
Fewer than 9 menstrual flows in the past yearc
Unable to conceive after a year of regular, unprotected intercourse
Previous infertility or subfertility diagnosis
Continuous or indistinguishable cervical mucus patterns in previous charting
Separated from partner
Efficiency and cost of recruitment by recruitment method
Enrolled (indexe only)
Investment per couple enrolled
Word of Mouth
Email or newsletter
Local news agency websitea
Characteristics of study participants
All participants (n = 366)
Male (n = 183)
Female (n = 183)
mean ± SD, or n (%)
mean ± SD, or n (%)
mean ± SD, or n(%)
27.7 ± 4.0
28.5 ± 3.8
27.1 ± 3.6
26.1 ± 5.6
27.2 ± 5.8
24.9 ± 5.0
Employed for wages
Some college (1–3 years)
College (>4 years, graduate)
Urine collection completion relative to estimated day of ovulation with or without conception (EDO/C)
EDO/C + 1
EDO/C + 2
EDO/C + 3
Concurrent and retrospective questionnaire completion by cycle and sex
EDO/C + 2 days
EDO/C + 18 days
EDO/C + 6 weeks
EDO/C + 38 weeks
Our findings support a growing body of evidence that both women and men planning pregnancy can be recruited and will comply with protocols requiring the collection of biospecimens and questionnaire data in the periconception window [12, 13, 23–27]. Similar to prior studies, the most common reasons for ineligibility were having already become pregnant or subfertility, highlighting the importance of rapid recruitment among couples intending to conceive [23, 27, 28]. We successfully enrolled 59.2 % of couples who screened eligible, a proportion similar to other studies [13, 24, 27]. Participants were self-selected volunteers and thus, no direct denominator is available for the target population at risk of or planning pregnancy. Word of mouth referrals from current participants (with modest recruitment incentives) proved to be the most efficient recruitment tool. Targeted Facebook ads, an innovative recruitment strategy, were productive and highly cost-effective in our study, similar to another recent preconception enrollment study . Facebook allowed us to target our advertisement to appear to select individuals based on marital status, age, sex, and location. Posters and flyers generated nearly one-quarter of our total screenings but were less cost-effective. In terms of strategic planning for recruitment, targeting women had a greater yield in generating screenings.
Participants in our study were predominantly white and well educated. There was a low proportion of current smokers (<2 %), and the mean age for women was 27.1 years. While the lack of racial and ethnic diversity may be a limitation, the absence of smoking allows for less confounding in examining the impact of other environmental and lifestyle exposures on reproductive outcomes.
Retention of participants despite the intensive study protocol was high with a dropout rate of only 6.0 % (11 couples). This rate is lower compared to reported rates from other prospective cohorts of couples trying to conceive in Denmark (8 %) , France (36 %) , Michigan and Texas (26 % and 27.2 %, respectively) , at four centers in the United States (12.2 %) , through internet-based methods (19 %) , and at seven European centers (25 %) , but higher than a study in Washington, DC (4 %) . We believe this high retention rate was related to effective relationships that study staff built with participant couples, flexibility in communication, the convenience of home based visits, and study compensation commensurate with the level of intensity of data collection.
Compliance with collection of semen samples was high over two cycles (89.9 %). Comparatively, 64 % of monthly semen samples for up to six cycles were received in Denmark , and the LIFE Study  reports 94 % compliance with semen collection at baseline and 77 % compliance with semen collection for a second semen sample; both studies collected via masturbation. Investigators may wish to consider the utility of home-based collection of semen samples through intercourse with semen collection devices to increase response rate, depending on the cultural context; although study objectives and analytical limitations of frozen specimens versus fresh specimens must be considered.
Comparison of compliance with collection of urine to other preconception studies is difficult as study designs vary widely. Bonde et al.  report 84 % compliance with women submitting daily urine on days one through ten of each menstrual cycle up to six cycles or until pregnancy, and men with 59 % compliance in submitting one to two pre- or post-shift urines monthly during those cycles. Zinaman et al.  requested women to submit daily morning urine samples for three cycles; compliance was >90 %. Buck-Louis et al.  requested three spot samples per woman with compliance ranging from 77 to 100 %, and two spot urine samples per man with compliance ranging from 94 to 100 %. Wilcox et al.  reported 98 % compliance among 221 women collecting daily samples for up to six months or until pregnancy. In this study, compliance with this collection protocol on periovulatory days (EDO/C ± 3 days) ranged from 67 to 94 % for women and from 56 to 75 % for men. Because men must rely on communication from the woman to start urine collection, it is unclear whether compliance among men is lower than women due to a lack of communication between partners or if men were aware but less motivated. Overall compliance with completion of online concurrent and retrospective questionnaires was high, and females consistently had higher completion rates compared to males.
Possible approaches to obtaining urine and other biospecimens in the fertile window include collecting urine every day, which may be more resource intensive, using fixed calendar days, which is much less accurate due to natural variability in the fertile window , or using indicators of the fertile window to target sample collection accordingly. Targeting biospecimen collection to the fertile window has been done effectively in prior studies using a handheld, home fertility monitor based on urinary hormones of estrone glucuronide and luteinizing hormone [13, 28, 33]. However, use of a fertility monitor may be expensive for larger studies. In this study, women identified the fertile window based on self-observation of fertile-quality cervical fluid, supplemented and confirmed by basal body temperature measurements . This approach is inexpensive, efficient, and resulted in high compliance in our study.
Our findings support a growing body of evidence supporting the feasibility of successful completion of preconception cohort studies for assessing environmental exposures during the earliest critical windows of human development around conception and implantation, with excellent retention and high compliance of detailed exposure monitoring (biospecimens and questionnaires). Our results also confirm the emerging importance of targeted online recruitment strategies. Our study is one of a few that have successfully included all of the male partners, a critical component for studying environmental impacts on fecundity and early human development. Finally, we have demonstrated for the first time the effective implementation of a streamlined, cost-efficient approach of women’s self-observation of fertility symptoms (primarily cervical fluid) applied to periconceptional exposure monitoring.
BMI, Body mass index; BPA, Bisphenol A; EDO/C, Estimated day of ovulation or conception; HOPE, Home observation of periconceptional exposures; IUD, Intrauterine device; LIFE, Longitudinal investigation of fertility and the environment; PCOS, Polycystic ovarian syndrome; USD, United States dollar
The authors acknowledge Allen Wilcox, Carol Sweeney, James A. VanDerslice, Jaewhan Kim, and Douglas Carrell for their contributions to this work.
This study was supported by National Institute of Environmental Health Sciences grant 1R01ES020488-01.
Availability of data and materials
Supporting data can be made available upon request.
CAP served as the Principal Investigator of the study and oversaw all aspects of design, execution, analysis, and writing. K.J.C. participated in design of the study methodology, collected the study data, performed the analyses, and prepared the manuscript. KCS facilitated study protocol and data collection, and assisted with interpretation of data. DGW participated in design of biospecimen collection and supervised all aspects of biospecimen analysis. JBS provided experience with cohort studies and mentorship to the study team through all phases of design, execution, and writing. All authors gave detailed comments on all versions, contributed intellectually to the final version of the manuscript, and approved the final version.
The authors declare that they have no competing interests.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- Barker DJ. Fetal origins of coronary heart disease. BMJ. 1995;311:6998.Google Scholar
- Gluckman PD, Hanson MA, Buklijas T. A conceptual framework for the developmental origins of health and disease. J Dev Orig Health Dis. 2010;1:1.View ArticleGoogle Scholar
- Gillman MW, Barker D, Bier D, Cagampang F, Challis J, Fall C, Godfrey K, Gluckman P, Hanson M, Kuh D, et al. Meeting report on the 3rd international congress on developmental origins of health and disease (DOHaD). Pediatr Res. 2007;61(5 Pt 1):625–9.View ArticleGoogle Scholar
- Rutledge JC, Generoso WM, Shourbaji A, Cain KT, Gans M, Oliva J. Developmental anomalies derived from exposure of zygotes and first-cleavage embryos to mutagens. Mutat Res. 1992;296:1–2.View ArticleGoogle Scholar
- Chapin RE, Robbins WA, Schieve LA, Sweeney AM, Tabacova SA, Tomashek KM. Off to a good start: the influence of pre- and periconceptional exposures, parental fertility, and nutrition on children’s health. Environ Health Perspect. 2004;112:1.Google Scholar
- Hochberg Z, Feil R, Constancia M, Fraga M, Junien C, Carel JC, Boileau P, Le Bouc Y, Deal CL, Lillycrop K, et al. Child health, developmental plasticity, and epigenetic programming. Endocr Rev. 2011;32:2.View ArticleGoogle Scholar
- Chapin RE, Buck GM. Our once-in-a-lifetime opportunity. Environ Health Perspect. 2004;112:1.Google Scholar
- Buck GM, Lynch CD, Stanford JB, Sweeney AM, Schieve LA, Rockett JC, Selevan SG, Schrader SM. Prospective pregnancy study designs for assessing reproductive and developmental toxicants. Environ Health Perspect. 2004;112:1.Google Scholar
- Tingen C, Stanford JB, Dunson DB. Methodologic and statistical approaches to studying human fertility and environmental exposure. Environ Health Perspect. 2004;112:1.Google Scholar
- Louis GM, Cooney MA, Lynch CD, Handal A. Periconception window: advising the pregnancy-planning couple. Fertil Steril. 2008;89(2):e119–21.View ArticleGoogle Scholar
- Baker D, Park C, Sweeney C, McCormack L, Durkin M, Brenner R, Dabelea D, Entwisle B. Recruitment of women in the National Children’s Study initial vanguard study. Am J Epidemiol. 2014;179:11.View ArticleGoogle Scholar
- Stanford JB, Brenner R, Fetterer D, Palmer L, Schoendorf KC. Impact of preconception enrollment on birth enrollment and timing of exposure assessment in the initial vanguard cohort of the U.S. National Children’s Study. BMC Med Res Methodol. 2015;15:75.View ArticleGoogle Scholar
- Buck Louis GM, Schisterman EF, Sweeney AM, Wilcosky TC, Gore-Langton RE, Lynch CD, Boyd Barr D, Schrader SM, Kim S, Chen Z, et al. Designing prospective cohort studies for assessing reproductive and developmental toxicity during sensitive windows of human reproduction and development--the LIFE Study. Paediatr Perinat Epidemiol. 2011;25:5.View ArticleGoogle Scholar
- Rockett JC, Buck GM, Lynch CD, Perreault SD. The value of home-based collection of biospecimens in reproductive epidemiology. Environ Health Perspect. 2004;112:1.Google Scholar
- Zinaman MJ. Using cervical mucus and other easily observed biomarkers to identify ovulation in prospective pregnancy trials. Paediatr Perinat Epidemiol. 2006;20(1):26–9.View ArticleGoogle Scholar
- Fehring RJ, Raviele K, Schneider M. A comparison of the fertile phase as determined by the clearplan easy fertility monitor and self-assessment of cervical mucus. Contraception. 2004;69:1.View ArticleGoogle Scholar
- Ecochard R, Duterque O, Leiva R, Bouchard T, Vigil P. Self-identification of the clinical fertile window and the ovulation period. Fertil Steril. 2015;103:5.View ArticleGoogle Scholar
- Lynch CD, Jackson LW, Buck Louis GM. Estimation of the day-specific probabilities of conception: current state of the knowledge and the relevance for epidemiological research. Paediatr Perinat Epidemiol. 2006;20(1):3–12.View ArticleGoogle Scholar
- Stanford JB. Revisiting the fertile window. Fertil Steril. 2015;103:5.View ArticleGoogle Scholar
- Porucznik C, Cox K, Schliep K, Stanford J. Pilot test and validation of the peak day method of prospective determination of ovulation against a handheld urine hormone monitor. BMC Women’s Health. 2014;14:1.View ArticleGoogle Scholar
- Thomas FS, Stanford JB, Sanders JN, Gurtcheff SE, Gibson M, Porucznik CA, Simonsen SE. Development and initial validation of a fertility experiences questionnaire. Reprod Health. 2015;12:62.View ArticleGoogle Scholar
- Gerris J. Methods of semen collection not based on masturbation or surgical sperm retrieval. Hum Reprod Update. 1999;5:3.View ArticleGoogle Scholar
- Stanford JB, Smith KR, Varner MW. Impact of instruction in the Creighton model fertilitycare system on time to pregnancy in couples of proven fecundity: results of a randomised trial. Paediatr Perinat Epidemiol. 2014;28:5.View ArticleGoogle Scholar
- Bonde JP, Hjollund NH, Jensen TK, Ernst E, Kolstad H, Henriksen TB, Giwercman A, Skakkebaek NE, Andersson AM, Olsen J. A follow-up study of environmental and biologic determinants of fertility among 430 Danish first-pregnancy planners: design and methods. Reprod Toxicol. 1998;12:1.View ArticleGoogle Scholar
- Zinaman MJ, Clegg ED, Brown CC, O’Connor J, Selevan SG. Estimates of human fertility and pregnancy loss. Fertil Steril. 1996;65:3.View ArticleGoogle Scholar
- Wilcox AJ, Weinberg CR, O’Connor JF, Baird DD, Schlatterer JP, Canfield RE, Armstrong EG, Nisula BC. Incidence of early loss of pregnancy. N Engl J Med. 1988;319:4.View ArticleGoogle Scholar
- Wise LA, Rothman KJ, Mikkelsen EM, Stanford JB, Wesselink AK, McKinnon C, Gruschow SM, Horgan CE, Wiley AS, Hahn KA, et al. Design and conduct of an internet-based preconception cohort study in North America: pregnancy study online. Paediatr Perinat Epidemiol. 2015;29:4.Google Scholar
- Schisterman EF, Silver RM, Perkins NJ, Mumford SL, Whitcomb BW, Stanford JB, Lesher LL, Faraggi D, Wactawski-Wende J, Browne RW, et al. A randomised trial to evaluate the effects of low-dose aspirin in gestation and reproduction: design and baseline characteristics. Paediatr Perinat Epidemiol. 2013;27:6.Google Scholar
- de Mouzon J, Spira A, Schwartz D. A prospective study of the relation between smoking and fertility. Int J Epidemiol. 1988;17:2.View ArticleGoogle Scholar
- Colombo B, Masarotto G. Daily fecundability: first results from a new data base. Demogr Res. 2000;3:39.View ArticleGoogle Scholar
- Buck Louis GM, Sundaram R, Schisterman EF, Sweeney A, Lynch CD, Kim S, Maisog JM, Gore-Langton R, Eisenberg ML, Chen Z. Semen quality and time to pregnancy: the Longitudinal Investigation of Fertility and the Environment Study. Fertil Steril. 2014;101(2):453-62. doi: 10.1016/j.fertnstert.2013.10.022. Epub 14 Nov 2013.
- Wilcox AJ, Dunson D, Baird DD. The timing of the “fertile window” in the menstrual cycle: day specific estimates from a prospective study. BMJ. 2000;321:7271.View ArticleGoogle Scholar
- Howards PP, Schisterman EF, Wactawski-Wende J, Reschke JE, Frazer AA, Hovey KM. Timing clinic visits to phases of the menstrual cycle by using a fertility monitor: the BioCycle Study. Am J Epidemiol. 2009;169:1.View ArticleGoogle Scholar