Volitional determinants andage-related decline in fecundability:a general population prospectivecohort study in Denmark

Kenneth J. Rothman, Dr.P.H.,a,b Lauren A. Wise, Sc.D.,a,c Henrik T. Sørensen, D.M.Sc., Ph.D.,d

Anders H. Riis, M.Sc.,d Ellen M. Mikkelsen, Ph.D.,d and Elizabeth E. Hatch, Ph.D.a

a Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts; b RTI International,Research Triangle Park, North Carolina; c Slone Epidemiology Center, Boston University, Boston, Massachusetts; andd Department of Clinical Epidemiology, Institute of Clinical Medicine, Aarhus University Hospital, Aarhus, Denmark

Objective: To quantify the natural decline in fecundability by age and assess the effect of selected volitional factors.Design: Prospective cohort study of women attempting conception.Setting: Not applicable.Participant(s): A total of 2,820 women without infertility, trying to conceive for less than 3 cycles at study entry.Intervention(s): None.Main Outcome Measure(s): Fecundability.Result(s): Age had little effect on fecundability except for women 35–40 years, for whom it was 0.77 relative to women aged 20–24years. Male age showed a similar but smaller decrease, declining to 0.95 for men aged 35–39 years. The effect of age differed for parousand nulliparous women, with the latter experiencing much stronger age-related declines relative to fecundability at age 20 years.Frequency of intercourse, use of nonhormonal birth control as the last method, and timing of intercourse, each had small effects onfecundability. Women who were in the high-fecundability categories for all three of these volitional factors had an estimatedprobability of conceiving of 88% (95% confidence interval 83%–93%). Unlike age, these factors represent individual choices thattogether can offset some of the age-related decline in fecundability.Conclusion(s): Fecundability peaks around age 30 years, slightly earlier for nulliparous than for parous women, and then declines. Thedecline with age is more modest for men. Couples will experience a compounded effect of their separate age-related declines. At age

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40 years, a couple's fecundability would be approximately half of what it was at age 30 years,but some of this decline can be counteracted by volitional factors affecting conception. (FertilSteril� 2013;99:1958–64. �2013 by American Society for Reproductive Medicine.)Key Words: Fecundability, fertility, age, behavioral factors, cohort study

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A ge is a strong determinant offecundability (the probabilityof conception during a single

Received October 31, 2012; revised and accepted FebK.J.R. has nothing to disclose. L.A.W. received travel s

has nothing to disclose. A.H.R. has nothing toNational Institutes of Health. E.E.H. received tra

Supported by the US National Institute of Child Heathe Danish Medical Research Council (271-07-responsibility of the authors and does not necesInstitutes of Health.

Reprint requests: Kenneth J. Rothman, Dr.P.H., DeSchool of Public Health, 715 Albany Street, Bobu.edu).

Fertility and Sterility® Vol. 99, No. 7, June 2013 0015Copyright ©2013 American Society for Reproductivehttp://dx.doi.org/10.1016/j.fertnstert.2013.02.040

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menstrual cycle with unprotected inter-course) (1–5), but it is not modifiable,whereas other strong determinants of

ruary 20, 2013; published online March 18, 2013.upport from National Institutes of Health. H.T.S.disclose. E.M.M. received travel support fromvel support from National Institutes of Health.lth and Human Development (R21-050264) and0338). The content of this article is solely thesarily represent the official views of the National

partment of Epidemiology, Boston Universityston, Massachusetts 02118 (E-mail: krothman@

-0282/$36.00Medicine, Published by Elsevier Inc.

fecundability, such as frequency andtiming of intercourse, are volitionaland may be modified to offsetdeclines in fecundability with age. Tothe extent that this compensatorybehavior occurs, the natural decline infecundability with age may bepartially masked.

The age-related decline in fecund-ability has been studied mostly inwomen receiving donor inseminationor from retrospective data collectedfrom women who have already con-ceived. Schwartz and Mayaux (1) stud-ied fecundability among women with

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azoospermic partners receiving donor insemination with fro-zen semen. They reported a probability of conception of 73%within 12 cycles for women under age 30 years, declining to61% for women 30–34 years of age, and to 54% for womenolder than 34 years. van Noord-Zaadstra et al. (2) found sim-ilar results in a Dutch population of women receiving donorinsemination. Studies in historic populations that did notuse contraception show accelerating decreases in fecundabil-ity as women age from their mid-20s into their 40s (4, 5).Studies based on women who succeed in getting pregnantare subject to selection biases that may distort the agerelation (6).

Couples also appear to experience declining fecundabilitywith increasing age of the male partner. Homan et al. (7)reported a decline in fecundability for couples in which theman is older than 40 years; Baird et al. (8) mention a declinein fertility success in attempts at assisted reproduction whenthe sperm comes from men more than 50 years. Hassan andKillick (9) found increased time to pregnancy with increasingage of the male partner. These studies are reinforced byfindings of declining semen volume, sperm motility, andsperm morphology (but not sperm concentration) withincreasing age of the male partner (10).

No study has examined the age-related decline infecundability in a population-based prospective cohort studyof women trying to conceive, while controlling for volitionalfactors. We therefore examined the pattern of age-relatedfecundability after controlling for several volitional factors,together with other factors that might confound thefecundability estimates. We also examined the decline infecundability in relation to age of the male partner.

MATERIALS AND METHODSStudy Population and Data Collection

The Snart Gravid prospective cohort study enrolled Danishwomen from the general population who stopped usingcontraception because they wished to become pregnant(11, 12). The cohort was recruited and followed for up to1 year by the Internet, beginning in June of 2007. Potentialparticipants learned about the study from an advertisementon a Danish health-related website (www.netdoktor.dk) orthrough other publicity, such as magazine articles. The studywebsite contained an on-line consent form and a screeningquestionnaire. Eligible women were residents of Denmark,aged 18–40 years, in a stable relationship with a male partnerof any age, not using any form of contraception or fertilitytreatment. Participants provided proof of identity and recordlinkage through their Civil Registration Number. They alsogave an e-mail address and completed an extensive baselinequestionnaire. Shorter follow-up questionnaires werecompleted at intervals of 8 weeks to ascertain pregnanciesand to update exposures. Follow-up continued for up to12 months (6 follow-up questionnaires), but ceased if thewoman reported being pregnant, stopped trying to becomepregnant, or began fertility treatment. Of these women 82%were followed for all 12 months, or until a study eventoccurred (13).

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On the baseline and follow-up questionnaires, womenwere asked ‘‘Are you or your partner doing anything to helpyou time intercourse (e.g., keeping a record of basal bodytemperature, monitoring changes in cervical mucus, usingLH or ovulation testing kits)?’’ On the baseline questionnairewomen were also asked to specify which methods they wereusing (indicating all that applied): basal body temperature,monitoring of cervical mucus, LH/ovulation testing kit, orother. The most common response for the ‘‘other’’ categorywas ‘‘counting days of menstrual cycle.’’ At baseline and ateach follow-up, women were asked to report on theirfrequency of sexual intercourse (in the past month) incategories of ‘‘<1 per month, once per month, 2–3 timesper month, once per week, 2–3 times per week, 4–6 timesper week, and daily.’’

After 54 months of recruitment, 5,920 women wereenrolled in the cohort. Many of these women had beentrying to conceive for several months before they entered.For this analysis, we excluded the 1,948 women who hadbeen trying to conceive for >3 cycles at study entry, tofocus on women who were just recently attempting toconceive. We also excluded 38 women who were < 20 yearsat study entry, 2 whose male partners were < 20 years ofage, 236 women with a history of infertility, 296 womenwith insufficient or implausible information about theirlast menstrual period date or length of time trying to con-ceive, and 580 women who completed only the baselinequestionnaire. Thus, our cohort for this analysis comprised2,820 women. Of these, 69% had been trying to becomepregnant for 1 month or less at enrollment.

Data Analysis

We examined the relation between female age at the time ofstudy enrollment and conception during the following12 menstrual cycles by applying life-table methods toestimate the cumulative probability of conception withinfour age categories of women (20–24, 25–29, 30–34, and35–40 years). Within each of these age categories, weexamined cumulative probabilities of conception for threesubsets of women: [1] women with higher frequency ofintercourse (R2 times/wk); [2] women who were timingintercourse to become pregnant; and [3] women who usednonhormonal methods as their last method of contraception,because women using hormonal methods have a short delayin return to fertility (14). We also examined fecundabilty forthe 319 women who met all three criteria. We then fita proportional probabilities regression model to computefecundability ratios and 95% confidence intervals (CIs)by age category, adjusting for cycle at risk usingleft-truncation, and controlling for potential confoundersincluding vigorous physical activity, female body mass index(BMI), education, alcohol consumption, current smoking,pack-years of smoking (ever smokers), male BMI, malesmoking, cycle length, cycle regularity, intercoursefrequency, last method of contraception, parity, and methodsused to time intercourse (15). The fecundability ratiorepresents the average per cycle probability of conceptionfor women (or men) of a given age relative to those ata referent age. A fecundability ratio below one indicates

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TABLE 1

Baseline characteristics of 2,820 Danish women and their male partners participating in a prospective cohort study of pregnancy planners,according to female and male age at baseline.

Characteristic

Female age at baseline (y) Male age at baseline (y)

<25 25–29 30–34 35–40 <25 25–29 30–34 35–39 R40

Number 466 1,355 791 208 198 1,046 1,048 393 135Partner's age (y), mean 26.5 29.6 33.3 37.0 23.1 26.5 29.2 32.0 33.2Regular cycles, % 74.0 75.9 81.3 85.6Cycle length, meana 28.9 28.8 28.6 28.1Cycle length <27 d, %a 9.6 12.9 14.0 16.9Cycle length R32 d, %a 11.0 11.6 7.8 3.4BMI (kg/m2), mean) 24.1 23.8 23.7 24.3 25.1 25.3 25.1 25.4 25.4Vigorous physical activity (h/wk), mean 1.6 1.7 1.4 1.5Higher education (>4 y), % 4.7 23.5 40.5 30.3Parous, % 10.1 22.3 49.3 68.3Current regular smoker (yes), % 15.5 10.4 9.4 9.6 21.7 17.0 16.9 19.1 19.3Pack-years of ever smoking, mean 3.5 4.7 5.6 7.8 2.6 3.3 4.0 4.8 4.7Alcohol intake (drinks/wk), mean 2.3 2.9 3.1 3.2Intercourse frequency (R4 times/wk), % 30.7 20.7 14.8 15.4 30.8 22.8 16.3 17.6 24.4Doing something to time intercourse, % 40.8 40.0 42.2 49.0 43.9 41.0 39.1 43.5 52.6Methods used to time intercourse, %b

Basal body temperature 3.0 2.0 1.9 1.4 1.5 2.7 1.6 2.0 3.0Cervical mucus 17.2 15.8 16.6 21.1 17.2 16.3 15.3 19.3 21.5LH/ovulation test kit 13.9 12.5 14.4 14.9 15.6 14.2 11.6 14.0 16.3Otherc 14.6 17.5 18.1 20.7 16.7 15.8 18.1 18.8 21.5

Last method of contraception, %Barrier methods 21.9 26.3 31.7 33.7 24.7 26.8 27.9 31.3 25.9Hormonal contraceptives 73.1 65.3 54.8 46.6 68.8 66.2 61.0 52.8 58.5Withdrawal, charting, or other 5.0 8.4 13.5 19.7 6.5 7.0 11.1 15.9 15.6

Note: BMI ¼ body mass index; LMP ¼ last menstrual period.a Among women with regular cycles.b Categories are not mutually exclusive.c Most common response to ‘‘other’’ was ‘‘calendar method/counting number of days since LMP.’’

Rothman. Age-related decline in fecundability. Fertil Steril 2013.

ORIGINAL ARTICLE: ENVIRONMENT AND EPIDEMIOLOGY

reduced fecundability of exposed persons relative tounexposed persons.

We usedmenstrual cycles rather than calendar time as thetime metric in the regression model. We asked womenwhether they had regular menstrual cycles (defined as‘‘usually being able to predict from one menstrual period tothe next about when the next menstrual period would start’’).Women with regular cycles were asked to report their usualcycle length. For women with irregular cycles or missingdata, we estimated cycle length from the date of lastmenstrual period (LMP) at the baseline questionnaire, andfrom the actual LMP dates recorded during each follow-upquestionnaire. We estimated time to pregnancy in cyclesbased on the following formula:

{Days of trying at study entry/Cycle length} þ {[(LMPdate frommost recent follow-up questionnaire�Date of base-line questionnaire completion)/Cycle length] þ 1}. We addedone cycle to account for the average woman being at midcyclewhen shefilled out the baseline questionnaire. Observed cyclesat risk were defined as those occurring after study entry.

We censored follow-up if and when participants [1]reported use of fertility treatments or change in intention tobecome pregnant, [2] became lost to follow-up or activelyresigned from the study, or [3] reached the end of theobservation period (no conception after 12 menstrual cycles).Using the same methods, we examined the relation betweenmale age and fecundability in five age categories (20–24,

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25–29, 30–34, 35–39, and R40 years). Finally we fittedsmoothed curves to depict the trend in fecundability ratiowith age, using restricted cubic splines (16, 17). A splinecurve is a concatenated series of polynomial functions withsegments joined at points called ‘‘knots,’’ intended to depictthe underlying trend. The slopes of the polynomialsegments are constrained to fit smoothly at the knots, andthe end segments (in a restricted spline model) are keptlinear to avoid the undue influence of outliers.

We used multiple imputation methods to impute missingdata (18). The proportion of missing data at baseline rangedfrom as low as 0.13% (age of the male partner) to as high as4% (pack-years of smoking); proportions were 0.39% forlast method of contraception, 0.42% for frequency ofintercourse, and 0.58% for actions to improve chances offertility success (e.g., timing intercourse). There were nomissing data for age of female (by design). In SAS statisticalsoftware (version 9.2), we used PROC MI to create fiveimputed datasets and PROC MIANALYZE to combine resultsacross the five datasets (19). All potential confounders wereincluded in the imputation procedure.

Ethical Review

The Snart Gravid study was approved by the Danish DataProtection Board and the Institutional Review Board atBoston University. Consent was obtained from all participantsby the Internet.

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TABLE 2

Number of pregnancies, number of subjects, and cumulative pregnancy proportion within 12 cyclesa by female andmale age at baseline, overall,and by selected volitional factors.

Age (y)

All womenIntercourse R2times per week

Timingintercourse

Nonhormonallast method ofbirth control

Nonhormonal lastbirth control,

intercourse R2/week,and timing intercourse

Preg/total %a Preg/total %a Preg/total %a Preg/total %a Preg/total %a

Women20–24 314/466 78 237/345 79 132/190 78 91/124 81 37/46 9125–29 996/1,355 83 692/917 84 402/542 82 345/467 83 112/143 8730–34 625/791 87 369/460 88 276/334 90 285/356 87 79/93 9035–40 140/208 72 83/123 73 72/102 78 78/111 76 26/37 75

Men20–24 135/198 80 112/151 85 61/87 81 44/61 86 16/20 9025–29 747/1,046 81 535/728 82 312/429 81 260/351 81 89/116 8530–34 817/1,048 86 505/651 85 328/410 87 314/405 85 89/106 8835–39 283/393 81 179/240 83 131/171 83 144/185 86 52/62 90R40 93/135 86 50/75 82 50/71 83 37/56 75 8/15 64

Total 2,075/2,820 83 1,381/1,845 84 882/1,168 84 799/1,058 84 254/319 8895% CI 81%–85% 81%–86% 81%–86% 81%–87% 83%–93%Note: CI ¼ confidence interval.a From life-table analysis that accounts for censoring events (e.g., loss to follow-up).

Rothman. Age-related decline in fecundability. Fertil Steril 2013.

TABLE 3

Modeled fit between age and time to pregnancy, with fecundabilityratios (FR) and 95% confidence intervals (CI), using separatemodels for women and men.

Age (y) Pregnancies Cycles

Unadjusted model Adjusted modela

FR 95% CI FR 95% CI

Women20–24 314 2,035 1.00 (ref.) 1.00 (ref.)25–29 996 5,734 1.12 0.99–1.25 1.03 0.90–1.1830–34 625 3,115 1.26 1.12–1.43 1.05 0.89–1.2335–40 140 948 0.97 0.81–1.16 0.77 0.62–0.97

Men20–24 135 916 1.00 (ref.) 1.00 (ref.)25–29 747 4,453 1.13 0.95–1.33 1.05 0.87–1.2630–34 817 4,186 1.27 1.08–1.50 1.09 0.90–1.3235–39 283 1,680 1.12 0.93–1.36 0.96 0.77–1.19R40 93 597 1.04 0.82–1.33 0.95 0.73–1.25

Note: Unadjusted model controls for cycle number.a Model is adjusted for cycle number, age of the female or male partner (y), vigorous physicalactivity (yes/no), body mass index (BMI), vocational training (yes/no), alcohol consumption(yes/no), current smoking (yes/no), pack-years of smoking (ever smokers), partner smoking(yes/no), partner BMI, parity, cycle length (d), cycle regularity (yes/no), intercourse frequency(no./wk), last method of contraception (barrier/hormonal/other), and methods used to timeintercourse (basal body temp/LH ovulation test kit/other).

Rothman. Age-related decline in fecundability. Fertil Steril 2013.

Fertility and Sterility®

RESULTSCharacteristics of the study population according to femaleand male age at baseline are shown in Table 1. Female agewas positively associated with male partner's age, regularmenstrual cycles, short cycle length, higher education,parity, pack-years of smoking, alcohol intake, use of barriermethods as last method of contraception, and attempting totime intercourse. An intercourse frequency of four or moretimes per week was highest for women less than age 25 yearsand diminished progressively with increasing age. Female agewas not appreciably associated with BMI. Similar patternswere observed for male age.

Among the 2,820 couples in this analysis, 2,075 womenbecame pregnant within 12 menstrual cycles of follow-up,for a crude cumulative probability of conception of 74%.This crudefigure does not adjust for the fact that some coupleshad incomplete follow-up or stopped trying to conceive.When we accounted for these phenomena using life-tablemethods, the estimated probability of becoming pregnantwithin 12 months was 83% (95% CI 81%–85%). Womenbetween 25 and 34 years of age had greater fecundabilitythan women in younger or older age categories when othervariables were not considered. Table 2 shows howage-specific fecundability changed according to variousvolitional factors affecting conception. A frequency ofintercourse of two or more times per week, the last methodof birth control, and whether intercourse timing was used,each had small effects on fecundability, but women whowere in the high-fecundability categories for all three of thesefactors had an estimated probability of conceiving of 88%(95% CI 83%–93%) within 12 cycles, 6% more in absoluteprobability than the value of 82% for women who did noneof the three factors. Overall, these results indicate that voli-tional factors enhance fecundability, although the magnitudedoes not fully offset the age-related decline. Also, the increase

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in fecundability attained by timing of intercourse, use ofnonhormonal methods of birth control, and frequency of in-tercourse appears to be more modest for older women than forwomen under age 30 years.

Table 3 shows the unadjusted and fully adjusted associa-tions for fecundability in relation to female and male age,derived from a proportional probabilities regression model.With adjustment for confounders, a woman's age hadcomparatively little effect except for a marked decline infecundability in the oldest age category, 35–40 yrs, to 0.77(95% CI 0.62–0.97) relative to women aged 20–24 years.

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FIGURE 1

Association between age and fecundability, fitted by restricted cubicsplines. Reference level for fecundability ratio (FR) is 20 years. Allcurves used three knots located at 25, 30, and 35 years, except forthe male curves, which have an additional knot at age 40 years.(A, B) The unadjusted curve controls for cycle number only, and theadjusted curve controls for cycle number, partner's age, vigorousRothman. Age-related decline in fecundability. Fertil Steril 2013.

FIGURE 1 Continued

physical activity, body mass index (BMI), vocational training, alcoholintake, current smoking, pack-years of smoking (ever smokers),partner smoking, partner BMI, cycle length, cycle regularity, parity,intercourse frequency, last method of contraception, and methodsused to time intercourse. (C) Both curves control for cycle number,female age, vigorous physical activity, BMI, vocational training,alcohol intake, current smoking, pack-years of smoking (eversmokers), partner smoking, partner BMI, cycle length, cycleregularity, parity, intercourse frequency, last method ofcontraception, and methods used to time intercourse.Rothman. Age-related decline in fecundability. Fertil Steril 2013.

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Male partner's age showed the same pattern as women withan increase in fecundability from age 20–24 years to age30–34 years, followed by a decrease at older ages, but thedecrease was small, declining to 0.95 for men aged 35–39years (95% CI 0.77–1.19) relative to men aged 20–24 years.We also fit these models after removing terms for cycleregularity and menstrual cycle length, to address the concernthat these variables were mediating factors and thereforeshould not be controlled. The results were essentiallyunchanged when these variables were removed.

These results involve collapsing data into a few relativelybroad age categories. To avoid the loss of information fromcollapsing the data, and to depict the age trend visually, wealso plotted smoothed curves using a restricted cubic splineregression model. Figure 1A shows the trend in fecundabilityby female age with and without adjustment for otherpredictors of fecundability. With adjustment, fecundabilityincreases only slightly until around age 30 years, after whichthere is a gradual decline. The results are shown separatelyfor parous and nulliparous women (Fig. 1C). For parouswomen the curve is an inverted ‘‘U,’’ with fecundability atage 40 years similar to fecundability at age 20 years, andmuch higher between these ages. For nulliparous women,however, fecundability does not appear to increase muchbetween age 20 and 30 years and then declines; therefore,by age 40 years it is substantially below the value at age20 years.

Because nulliparous women comprise gravid andnulligravid women, we also fit the curves examining fecund-ability ratio by age for these two groups separately (notshown). The former group comprised only 306 women ofthe 1,939 nulliparous women, and consequently that curvehad wide confidence bands and the regression model didnot converge with all covariates included. With control fora smaller subset of covariates, we found that the curve forthe nulligravid group moved closer to that for parous womenin Figure 1C, and the nulliparous but gravid group showed anearlier and much steeper decline in fecundability with age,although this finding was based on comparatively fewwomen.

Figure 1B summarizes the data on the relation betweenfecundability and age of the male partner. The changes withage resemble those of women, but when confounders arecontrolled, the change appears much smaller than forwomen, decreasing about 20% from the peak at age 30 years

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to age 45 years. In all of these analyses, age of the partnerhas been controlled. Most couples, however, will experiencethe compounding effect of a simultaneous advance in bothpartners' ages, and therefore the decline in fecundabilityafter age 30 years will be considerably steeper than isdepicted in any of these Figures. We estimated the fecund-ability ratio for couples in which both partners were eitherage 37 years or older or in the age range 27–33 years(essentially comparing couples around age 40 years withcouples around age 30 years), using the same model as inTable 3. The fecundability ratio for the older coupleswas 0.58 compared with the younger couples (95% CI0.42–0.79).

DISCUSSIONWe found that women had slightly higher fecundabilitythan estimates reported in earlier studies (1–5),a difference that may at least partially stem fromdifferences in the populations studied. In our study, peakfecundability was approximately 29–30 years amongparous women and 27–28 years among nulliparouswomen. Among parous women, age was associated withincreasing fecundability until age 30 years, after which itdecreased. Among nulliparous women, there was littleincrease in fecundability after age 20 years and a markeddecline starting around age 28 years. The effect of maleage was more modest, but also was associated witha decline beginning near age 30 years. Our cohort isrelatively young, with few participants from the oldestcategories of reproductive age, and therefore our findingsmay not be applicable for the oldest couples seeking toconceive.

Previous studies have examined fecundability inwomen receiving donor insemination, whereas the currentstudy prospectively followed a cohort of women trying toconceive naturally, and is restricted to women who werejust beginning to attempt pregnancy. Our study mostclosely resembles that of Howe et al. (3), a prospectivecohort study in which data also were stratified by parity.In that study, the effect of age on fecundability was modestamong parous women until age 37 years, after which itdeclined appreciably, but for nulliparous women there wasa strong and consistent decrease in fecundability in eachage category older than 25–27 years (the youngest agegroup in study). Howe et al. (3) reported peak fecundabilityfor parous women at age 28–29 years. Therefore, the resultsfrom these two prospective studies show remarkably similarparity-specific age patterns. Both studies indicate thatthe decline in fecundability with age is stronger innulliparous women.

The validity of our findings depends ultimately on thedata quality and completeness of follow-up. Our studypopulation was recruited from the Internet. Although studyparticipants are volunteers, the same is true for essentiallyall population-based cohort studies and all randomized trials.If the age-related decline that we report differed betweenDanish Internet users and others, our results might havelimited generalizability, but we see no reason whyage-related declines in fecundability would differ according

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to whether a woman had Internet access. Other factors, suchas reproductive history, could have affected participationand be related to fecundability. If these factors were alsoassociated with age, they could have distorted the estimatesof fecundability ratios by age. Because women who wereincluded in this analysis began their attempts to conceiveup to 3 months before we began to follow them, womenwho became pregnant very soon after attempting to conceivewere less likely to be enrolled. This selective enrollment alsocould have distorted our findings.

We found that older women more often used timing ofintercourse to improve their chances for conception, but therewas nevertheless a decreasing frequency of intercourse withincreasing age, even among this population of women whowere trying to conceive. Among women who had botha decreased frequency of intercourse and more careful timingof intercourse, there was only a modest net effect onfecundability, which offset some, but not all, of theage-related decline.

The decline in fecundability that we observed is steeperfor women than for men, but begins at approximately thesame age for both. Thus, for committed couples who are agingtogether, there is a compounded effect of their separateage-related declines. For example, if both partners are thesame age and the declines are considered independent, thentheir fecundability at age 40 years is nearly half of what itis at age 30 years.

Acknowledgments: The authors thank the contributions ofthe study staff and all the women who participated in theSnart Gravid study. We specifically thank Tina Christensenfor her support with data collection and media contact,Dr. Donna Baird for her feedback on questionnaire develop-ment, and Thomas Jensen for his assistance with websitedesign. We also thank Kristen Hahn and Rose Radin for theirgeneral assistance with the manuscript.

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