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A prospective cohort study of physical activity and time to pregnancy

      Objective

      To investigate the association between leisure-time physical activity (PA) and fecundability.

      Design

      Prospective cohort study.

      Setting

      Internet-based observational study of Danish women who were planning a pregnancy (2007–2009).

      Patient(s)

      A total of 3,628 women aged 18–40 years at baseline.

      Intervention(s)

      None.

      Main Outcome Measure(s)

      Time to pregnancy (TTP). Fecundability ratios (FRs) and 95% confidence intervals (CIs) were derived from discrete-time Cox models, with adjustment for potential confounders, such as body mass index (BMI).

      Result(s)

      We observed an inverse monotonic association between vigorous PA and fecundability (≥5 h/wk vs. none: FR 0.68, 95% CI 0.54–0.85) and a weak positive association between moderate PA and fecundability (≥5 vs. <1 h/wk: FR 1.18, 95% CI 0.98–1.43) after mutual adjustment for both PA types. Inverse associations between high vigorous PA and fecundability were observed within subgroups of age, parity status, and cycle regularity, but not among overweight or obese women (BMI ≥25 kg/m2).

      Conclusion(s)

      There was evidence for a dose-response relationship between increasing vigorous PA and delayed TTP in all subgroups of women with the exception of overweight and obese women. Moderate PA was associated with a small increase in fecundability regardless of BMI. These findings indicate that PA of any type might improve fertility among overweight and obese women, a subgroup at higher risk of infertility. Lean women who substitute vigorous PA with moderate PA may also improve their fertility.

      Key Words

      In 2006, Denmark adopted a national goal of increasing the prevalence of physical activity (PA) in the adult population to ≥75% by the year 2021, with “physically active” defined as moderate intensity activity for ≥30 minutes every day (
      Nordic Council of Ministers
      ). Although PA has been shown to reduce the risk of several chronic health conditions, such as type 2 diabetes, cardiovascular disease, depression, and some cancers (
      • Blair S.N.
      • Morris J.N.
      Healthy hearts and the universal benefits of being physically active: physical activity and health.
      ), its relationship to female fertility is less clear.
      Studies of competitive female athletes have found disturbances in their menstrual cycles, including oligomenorrhea and amenhorrhea (
      • Frisch R.E.
      • Gotz-Welbergen A.V.
      • McArthur J.W.
      • Albright T.
      • Witschi J.
      • Bullen B.
      • et al.
      Delayed menarche and amenorrhea of college athletes in relation to age of onset of training.
      ,
      • Loucks A.B.
      Effects of exercise training on the menstrual cycle: existence and mechanisms.
      ,
      • Dadgostar H.
      • Razi M.
      • Aleyasin A.
      • Alenabi T.
      • Dahaghin S.
      The relation between athletic sports and prevalence of amenorrhea and oligomenorrhea in Iranian female athletes.
      ,
      • Cooper G.S.
      • Sandler D.P.
      • Whelan E.A.
      • Smith K.R.
      Association of physical and behavioral characteristics with menstrual cycle patterns in women age 29–31 years.
      ,
      • De Souza M.J.
      • Toombs R.J.
      • Scheid J.L.
      • O'Donnell E.
      • West S.L.
      • Williams N.I.
      High prevalence of subtle and severe menstrual disturbances in exercising women: confirmation using daily hormone measures.
      ). In addition, high levels of PA have been associated with increased menstrual cycle length (
      • Cooper G.S.
      • Sandler D.P.
      • Whelan E.A.
      • Smith K.R.
      Association of physical and behavioral characteristics with menstrual cycle patterns in women age 29–31 years.
      ), increased follicular phase length (
      • Liu Y.
      • Gold E.B.
      • Lasley B.L.
      • Johnson W.O.
      Factors affecting menstrual cycle characteristics.
      ), and decreased luteal phase length (
      • De Souza M.J.
      • Miller B.E.
      • Loucks A.B.
      • Luciano A.A.
      • Pescatello L.S.
      • Campbell C.G.
      • et al.
      High frequency of luteal phase deficiency and anovulation in recreational women runners: blunted elevation in follicle-stimulating hormone observed during luteal-follicular transition.
      ). Given that previous research shows little effect of moderate-intensity PA on menstrual characteristics, some scientists postulate that the effect of PA on fertility may be positive up to a certain level of activity and then have a deleterious effect above that threshold level of activity (
      • Gudmundsdottir S.L.
      • Flanders W.D.
      • Augestad L.B.
      Physical activity and fertility in women: the North-Trøndelag Health Study.
      ).
      Epidemiologic studies of PA and infertility have been inconclusive, with some showing reduced risk among vigorous exercisers and others showing increased risk at the highest levels of frequency or intensity. Most of these studies have been based on fertility clinic populations (
      • Morris S.N.
      • Missmer S.A.
      • Cramer D.W.
      • Powers R.D.
      • McShane P.M.
      • Hornstein M.D.
      Effects of lifetime exercise on the outcome of in vitro fertilization.
      ,
      • Kucuk M.
      • Doymaz F.
      • Urman B.
      Effect of energy expenditure and physical activity on the outcomes of assisted reproduction treatment.
      ) or have been limited to cases of ovulatory infertility (
      • Chavarro J.E.
      • Rich-Edwards J.W.
      • Rosner B.A.
      • Willett W.C.
      Diet and lifestyle in the prevention of ovulatory disorder infertility.
      ,
      • Rich-Edwards J.W.
      • Spiegelman D.
      • Garland M.
      • Hertzmark E.
      • Hunter D.J.
      • Colditz G.A.
      • et al.
      Physical activity, body mass index, and ovulatory disorder infertility.
      ). In one study based on a fertility clinic population, women who had engaged in PA for ≥4 hours per week for <10 years had a 40% reduced likelihood of live birth, a threefold increased risk of in vitro fertilization (IVF) cycle cancellation (i.e., oocytes not retrieved), and a twofold increased risk of implan-tation failure and pregnancy loss compared with women not regularly engaged in PA (
      • Morris S.N.
      • Missmer S.A.
      • Cramer D.W.
      • Powers R.D.
      • McShane P.M.
      • Hornstein M.D.
      Effects of lifetime exercise on the outcome of in vitro fertilization.
      ). A subsequent study of women undergoing assisted reproduction found that moderate PA was associated with higher implantation and live birth rates (
      • Kucuk M.
      • Doymaz F.
      • Urman B.
      Effect of energy expenditure and physical activity on the outcomes of assisted reproduction treatment.
      ), but none of the women reported high levels of PA. Of the three investigations conducted in the general population, two were limited to the study of ovulatory infertility (
      • Chavarro J.E.
      • Rich-Edwards J.W.
      • Rosner B.A.
      • Willett W.C.
      Diet and lifestyle in the prevention of ovulatory disorder infertility.
      ,
      • Rich-Edwards J.W.
      • Spiegelman D.
      • Garland M.
      • Hertzmark E.
      • Hunter D.J.
      • Colditz G.A.
      • et al.
      Physical activity, body mass index, and ovulatory disorder infertility.
      ). Both of those reports, based on a prospective cohort study of U.S. nurses, found that higher levels of vigorous PA were associated with a decreased risk of ovulatory infertility (
      • Chavarro J.E.
      • Rich-Edwards J.W.
      • Rosner B.A.
      • Willett W.C.
      Diet and lifestyle in the prevention of ovulatory disorder infertility.
      ,
      • Rich-Edwards J.W.
      • Spiegelman D.
      • Garland M.
      • Hertzmark E.
      • Hunter D.J.
      • Colditz G.A.
      • et al.
      Physical activity, body mass index, and ovulatory disorder infertility.
      ). The third report, based on a population-based prospective cohort study of Norwegian women, found an increased risk of infertility (all types) among women reporting the highest levels of PA intensity and frequency (
      • Gudmundsdottir S.L.
      • Flanders W.D.
      • Augestad L.B.
      Physical activity and fertility in women: the North-Trøndelag Health Study.
      ).
      We examined the influence of leisure-time PA on time to pregnancy among Danish women enrolled in a prospective cohort study. We further stratified the results by body mass index (BMI) to assess whether the effect of PA differed according to overweight or obesity, which have been shown to be strong predictors of fecundability in our cohort and other studies (
      • Rich-Edwards J.W.
      • Spiegelman D.
      • Garland M.
      • Hertzmark E.
      • Hunter D.J.
      • Colditz G.A.
      • et al.
      Physical activity, body mass index, and ovulatory disorder infertility.
      ,
      • Wise L.A.
      • Rothman K.J.
      • Mikkelsen E.M.
      • Sorensen H.T.
      • Riis A.
      • Hatch E.E.
      An internet-based prospective study of body size and time-to-pregnancy.
      ,
      • Grodstein F.
      • Goldman M.B.
      • Cramer D.W.
      Body mass index and ovulatory infertility.
      ,
      • Cramer D.W.
      • Barbieri R.L.
      • Xu H.
      • Reichardt J.K.V.
      Determinants of basal follicle stimulating hormone levels in premenopausal women.
      ).

      Materials and methods

       Study Population

      The “Snart Gravid” study is an internet-based prospective cohort study of women planning a pregnancy in Denmark. The study methodology has been described in detail elsewhere (
      • Mikkelsen E.M.
      • Hatch E.E.
      • Wise L.A.
      • Rothman K.J.
      • Riis A.
      • Sorensen H.T.
      Cohort Profile: The Danish web-based pregnancy planning study—“Snart-Gravid.”.
      ,
      • Rothman K.J.
      • Mikkelsen E.M.
      • Riis A.
      • Sørensen H.T.
      • Wise L.A.
      • Hatch E.E.
      Randomized trial of questionnaire length.
      ,
      • Huybrechts K.F.
      • Mikkelsen E.M.
      • Christensen T.
      • Riis A.H.
      • Hatch E.E.
      • Wise L.A.
      • et al.
      A successful implementation of e-Epidemiology: the Danish pregnancy planning study “Snart-Gravid.”.
      ). Briefly, recruitment began in June 2007 with placement of an advertisement on a health-related website (www.netdoktor.dk) and a coordinated media strategy involving radio, print media, online news sites, and television. Enrollment and primary data collection were conducted via a self-administered questionnaire on the study website (www.snart-gravid.dk). Before enrollment, participants read a consent form and completed an online screening questionnaire to confirm eligibility. Eligible women were aged 18–40 years, residents of Denmark, in a stable relationship with a male partner, and not receiving any type of fertility treatment. Participants provided a valid e-mail address and their Civil Personal Registration number—a unique 10-digit personal identification number assigned to every resident by the Central Office of Civil Registration (
      • Frank L.
      When an entire country is a cohort.
      ).
      The baseline questionnaire collected information on demographics, reproductive and medical history, and lifestyle and behavioral factors. During the first 6 months of the study, participants were randomized to receive either a short- or long-form baseline questionnaire, with similar completion frequencies for both versions (
      • Rothman K.J.
      • Mikkelsen E.M.
      • Riis A.
      • Sørensen H.T.
      • Wise L.A.
      • Hatch E.E.
      Randomized trial of questionnaire length.
      ). After the first 6 months, newly enrolled participants received the long-form baseline questionnaire. Follow-up questionnaires evaluated changes in various exposures, frequency of intercourse, and clinically recognized conception. Participants were contacted every 2 months by e-mail for 12 months or until clinically-recognized conception. Women who conceived were asked to complete one questionnaire during early pregnancy to assess changes in exposures, after which active follow-up ceased. Cohort retention after 12 months of follow-up was ∼82% (
      • Huybrechts K.F.
      • Mikkelsen E.M.
      • Christensen T.
      • Riis A.H.
      • Hatch E.E.
      • Wise L.A.
      • et al.
      A successful implementation of e-Epidemiology: the Danish pregnancy planning study “Snart-Gravid.”.
      ). The Snart Gravid study was approved by all appropriate Institutional Review Board committees, and consent was obtained from each of the participants via the internet.

       Assessment of Physical Activity

      On the baseline questionnaire, women reported the average number of hours per week that they engaged in PA during the past year. They were asked to report moderate and vigorous types of activity separately. Categories of response were none, <1, 1, 2, 3–4, 5–6, 7–9, and ≥10 hours per week. Examples were provided for vigorous (“running, fast cycling, aerobics, gymnastics, or swimming”) and moderate (“brisk walking, leisurely cycling, golfing, or gardening”) types of activity. Based on the Compendium of Physical Activities (
      • Jacobs Jr., D.R.
      • Ainsworth B.E.
      • Hartman T.J.
      • Leon A.S.
      A simultaneous evaluation of 10 commonly used physical activity questionnaires.
      ), we estimated total metabolic equivalents (METs) of PA per week by summing the metabolic equivalents from vigorous exercise (h/wk multiplied by 7.0) and moderate exercise (h/wk multiplied by 3.5).

       Assessment of Covariates

      Data on age, weight, height, parity, smoking history, current alcohol consumption, last method of contraception, and frequency of intercourse were self-reported on the baseline questionnaire and were updated every 2 months by follow-up questionnaire. At baseline, women reported whether their cycles were currently regular and, if so, their usual cycle length when not using hormonal contraception (“number of days from the first day of one menstrual period to the first day of the next menstrual period”). We calculated BMI as [weight in kilograms]/[height in meters]2. Self-reported height and weight among women who delivered infants conceived during our study showed excellent agreement with measures provided by the Danish Medical Birth Registry (
      • Wise L.A.
      • Rothman K.J.
      • Mikkelsen E.M.
      • Sorensen H.T.
      • Riis A.
      • Hatch E.E.
      An internet-based prospective study of body size and time-to-pregnancy.
      ).

       Assessment of Pregnancy and Cycles at Risk

      On each follow-up questionnaire, women reported the date of their last menstrual period, whether they were currently pregnant, and whether they had experienced any other pregnancies since the date of their last questionnaire, including miscarriage, induced abortion, or ectopic pregnancy. Total cycles at risk (rounded to the nearest whole number) were calculated as follows: (days of attempt time at study entry/usual cycle length) + ([(last menstrual period date [LMP] from most recent follow-up questionnaire − date of baseline questionnaire completion)/usual cycle length] + 1), with observed cycles at risk defined as those contributed after study entry. For women with irregular cycles, we estimated usual cycle length based on the baseline LMP date, expected date of their next menstrual period, and LMP dates recorded over follow-up. Because we anticipated that the results would be less reliable among women with irregular cycles, we evaluated results separately among women with and without regular cycles.

       Exclusions

      After 30 months of recruitment, 5,460 women registered at the study website. Of these, we excluded 1,063 (19%) women who had been trying to conceive for >6 cycles at study entry: 274 women (5%) with insufficient or implausible information about their LMP date or date of first pregnancy attempt, and 495 women (9%) who did not complete a follow-up survey. After these exclusions, 3,628 women remained in this study. The 601 women (16.6%) who were subsequently lost to follow-up at some point during the year after enrollment (mean follow-up of 5.3 months) had lower parity (28.6% vs. 34.4%), higher BMI (mean 24.7 vs. 24.0 kg/m2), and heavier smoking histories (mean 2.8 vs. 2.0 pack-years) than the 3,027 women who were followed to a study end point. The two groups were similar regarding total PA (mean 24.1 vs. 24.9 MET-h/wk) and other baseline characteristics (e.g., mean age: 28.2 vs. 28.5 years; mean alcoholic drinks per week: 3.0 vs. 2.9; >4 years of higher education: 20.1% vs. 25.0%; gravidity: 43.6% vs. 45.8%; and use of oral contraceptives as last method of contraception: 61.4% vs. 61.6%).

       Data Analysis

      We analyzed vigorous PA in categories of none (reference), <1, 1, 2, 3–4, and ≥5 hours per week, and moderate PA in categories of <1 (reference), 1, 2, 3–4, and ≥5 hours per week. Continuous variables for moderate and vigorous PA were coded as the midpoint of each category (assigning 11 h/wk to the top category). We categorized total MET-h/wk in 10-unit increments, with 20–29 as the reference category (because it was associated with the highest fecundability in our cohort) and ≥60 as the maximum exposure category. We allowed for the possibility of a nonlinear relation or threshold effect of each PA variable on fecundability by fitting a restricted cubic spline model (
      • Li R.
      • Hertzmark E.
      • Louie M.
      • Chen L.
      • Spiegelman D.
      The SAS LGTPHCURV8 macro.
      ,
      • Durrleman S.
      • Simon R.
      Flexible regression models with cubic splines.
      ).
      The fecundability ratio (FR) represents the cycle-specific probability of conception among exposed women divided by that among unexposed women. We used a discrete-time analogue of the Cox proportional hazards model to estimate FRs and 95% confidence intervals (CIs) for moderate, vigorous, and total METs of physical activity in association with time to pregnancy, in cycles (
      • Baird D.D.
      • Wilcox A.J.
      • Weinberg C.R.
      Use of time to pregnancy to study environmental exposures.
      ). We evaluated time to any pregnancy regardless of pregnancy outcome. Women were censored if they did not conceive after 12 cycles, the typical amount of time after which couples seek medical assistance for infertility (
      • Baird D.D.
      • Wilcox A.J.
      • Weinberg C.R.
      Use of time to pregnancy to study environmental exposures.
      ,
      • Bonde J.P.
      • Joffe M.
      • Sallmén M.
      • Kristensen P.
      • Olsen J.
      • Roeleveld N.
      • et al.
      Validity issues relating to time-to-pregnancy studies of fertility.
      ). Women contributed cycles at risk until they reached a study end point: pregnancy, use of fertility treatments, loss to follow-up, or the end of observation (12 cycles), whichever occurred first. The Cox model allowed for “delayed entry” into the risk set, which occurs when women enter the study after having tried to conceive for one or more cycles. Therefore, risk sets were based only on cycles at risk observed after study entry (
      • Wise L.A.
      • Rothman K.J.
      • Mikkelsen E.M.
      • Sorensen H.T.
      • Riis A.
      • Hatch E.E.
      An internet-based prospective study of body size and time-to-pregnancy.
      ).
      We selected potential confounders from a list of variables associated with PA at baseline that met criteria for confounding based on a review of the literature and assessment of a causal graph (
      • Greenland S.
      • Rothman K.J.
      Introduction to stratified analysis: selecting confounders for control.
      ). We then controlled for potential confounders that changed the adjusted FR by >5% relative to the unadjusted FR (
      • Greenland S.
      • Rothman K.J.
      Introduction to stratified analysis: selecting confounders for control.
      ). Based on these criteria, we controlled for female age (<25, 25–29, 30–34, ≥35 y), partner's age (<25, 25–29, 30–34, ≥35 y), BMI (<20, 20–24, 25–29, ≥30 kg/m2), alcohol consumption (drinks per day), pack-years of smoking (never smoked, <5, 5–9, ≥10 pack-y), frequency of intercourse (<1, 1, 2–3, ≥4 times/wk), and last method of contraception (barrier methods, oral contraceptives, other hormonal contraceptives, natural family planning). Alcohol consumption and frequency of intercourse were modeled as time-varying variables. Further control for “doing something to time intercourse” made very little difference in the effect estimates for vigorous or moderate PA (<1% in FRs). To assess the independent effects of vigorous and moderate PA, we further controlled for each type of PA simultaneously in the final multivariable model. The proportion of missing data at baseline ranged from as low as 0.19% (age at menarche) to as high as 4% (pack-years of smoking); proportions were 0.25% and 0.27% for vigorous and moderate PA, respectively. We used multiple imputation methods to impute missing covariate values (
      • Zhou X.H.
      • Eckert G.J.
      • Tierney W.M.
      Multiple imputation in public health research.
      ). In SAS statistical software (version 9.2), we used PROC MI to create five imputed datasets and PROC MIANALYZE to combine results across the five datasets (
      SAS Institute
      SAS/STAT 9.2 user's guide.
      ). All potential confounders were included in the imputation procedure.
      In secondary analyses, we evaluated the extent to which the associations changed when pregnancy losses were excluded from the outcome definition. In these analyses, women who reported an abortion or ectopic pregnancy were censored at their estimated time to pregnancy (
      • Joffe M.
      • Key J.
      • Best N.
      • Keiding N.
      • Scheike T.
      • Jensen T.K.
      Studying time to pregnancy by use of a retrospective design.
      ). We stratified by age, parity status, BMI, cycle regularity, and number of cycle attempts before study entry. We assessed departure from the proportional hazards assumption by plotting the log-log survivor functions for each exposure variable in categoric form, where parallel log-log survivor curves indicated proportional hazards.

      Results

      Baseline characteristics of the study population according to hours of vigorous PA per week are presented in Table 1. Vigorous PA was positively associated with education and higher frequency of intercourse, and was inversely associated with BMI, waist circumference, caffeine intake, current smoking, parity, and the report of “doing something to time intercourse.” Women in the highest category of total MET-h/wk of PA tended to have longer and irregular cycles (data not shown).
      Table 1Baseline characteristics of 3,628 Danish women participating in a prospective cohort study of pregnancy planners, according to level of vigorous physical activity.
      Characteristic
      All characteristics, with exception of participant's age, are age-standardized to cohort at baseline.
      Vigorous physical activity, hours per week
      None<1123–4≥5
      No. of women720821631749513194
      Age, y (mean)28.928.428.528.328.227.8
      Partner's age, y (mean)31.030.730.930.730.731.1
      Age at menarche, y (mean)13.013.012.912.912.913.2
      Regular cycles (%)74.375.675.877.678.374.5
      Cycle length <27 d (%)10.911.911.013.813.111.1
      Cycle length ≥32 d (%)24.024.424.023.822.825.6
      Body mass index, kg/m2 (mean)24.924.623.823.623.622.9
      Waist circumference, cm (mean)84.582.980.979.879.778.0
      Moderate physical activity, h/wk (mean)3.43.64.14.24.45.8
      Total physical activity, MET-h/wk (mean)11.816.121.228.839.965.1
      Higher education >4 y (%)16.321.227.427.428.930.7
      Parous (%)47.640.631.125.222.317.4
      Current regular smoker (%)18.813.710.19.29.07.7
      Pack-y of ever smoking (mean)6.35.55.05.04.55.3
      Alcohol intake, drinks/wk (mean)2.62.72.93.03.33.0
      Caffeine intake, mg/d (mean)148140130136133120
      Intercourse frequency ≥4 times/wk (%)17.215.816.520.025.033.0
      Doing something to time intercourse (%)48.549.544.844.641.041.2
      Last method of contraception (%)
       Barrier methods30.430.527.925.426.620.6
       Hormonal contraceptives59.759.160.865.565.867.8
       Withdrawal, charting, or other9.710.111.39.07.711.0
      a All characteristics, with exception of participant's age, are age-standardized to cohort at baseline.
      In multivariable models that mutually controlled for both types of PA, we observed a monotonic inverse association between vigorous PA and fecundability, and a weak positive association between moderate PA and fecundability (Table 2). When we considered the contribution of both types of PA to total activity levels, we found that higher levels of PA were associated with reduced fecundability (≥60 vs. 20–29 MET-h/wk: FR 0.74, 95% CI 0.56–0.97).
      Table 2Physical activity at baseline and time to pregnancy.
      PregnanciesCyclesUnadjusted model
      Unadjusted model controls for cycle number.
      Adjusted model
      Adjusted for cycle number, age, partner's age, body mass index, alcohol consumption, pack-years of smoking, intercourse frequency, and last method of contraception.
      FR95% CIFR95% CI
      Vigorous physical activity, h/wk
       None5002,8561.00(ref.)1.00(ref.)
       <15663,4920.910.80–1.040.880.77–1.01
       14402,6070.940.81–1.080.870.76–1.01
       25203,1560.930.82–1.070.840.73–0.97
       3–43422,2950.820.70–0.950.730.63–0.86
       ≥51168190.770.61–0.960.680.54–0.85
      Moderate physical activity, h/wk
       <11611,1501.00(ref.)1.00(ref.)
       12271,5431.020.82–1.271.000.80–1.25
       25383,2731.170.96–1.411.150.95–1.40
       3–47204,2831.190.99–1.441.160.95–1.40
       ≥58384,9761.200.99–1.451.180.98–1.43
      Total metabolic equivalents, h/wk
       <103742,4450.870.75–1.090.950.82–1.11
       10–197844,7470.930.82–1.050.960.85–1.09
       20–295333,0951.00(ref.)1.00(ref.)
       30–394042,3450.980.85–1.130.970.84–1.12
       40–492011,3920.820.69–0.980.810.68–0.97
       50–591186880.970.77–1.200.930.75–1.17
       ≥60705130.750.58–0.990.740.56–0.97
      Note: Vigorous activity is adjusted for moderate activity, and vice versa. FR = fecundability ratio; CI = confidence interval.
      a Unadjusted model controls for cycle number.
      b Adjusted for cycle number, age, partner's age, body mass index, alcohol consumption, pack-years of smoking, intercourse frequency, and last method of contraception.
      The effect of vigorous PA was relatively uniform across levels of age, parity, and attempt time at study entry (Table 3). Although we also observed an inverse association between vigorous PA and fecundability among women with BMI <25 kg/m2 (vigorous PA ≥5 vs. 0 h/wk: FR 0.58, 95% CI 0.45–0.75), there was no evidence of an inverse association among overweight and obese women (BMI ≥25 kg/m2) (vigorous PA ≥5 vs. 0 h/wk: FR 1.22, 95% CI 0.74–2.02). In fact, for most categories of vigorous PA above “none” among overweight and obese women, there were weak positive associations between vigorous PA and fecundability (FRs ranged from 1.12 to 1.22, with the exception of FR 0.76 for 3–4 h/wk). The inverse association between vigorous PA and fecundability among lean women (BMI <25 kg/m2) was still apparent after the exclusion of underweight women, defined as BMI <18.5 kg/m2 (data not shown). Within subgroups of selected covariates, increasing levels of moderate PA were either weakly positively associated with fecundability or not associated with fecundability (Supplemental Table 1, available online at www.fertstert.org). Women who engaged in 20–39 MET-h/wk of PA (from all activity sources) had the highest fecundability in our cohort, regardless of BMI (Supplemental Table 2, available online at www.fertstert.org).
      Table 3Vigorous physical activity and time to pregnancy, stratified by selected factors.
      CharacteristicVigorous physical activity, hours per week
      None<1123–4≥5
      Age at baseline, y
       <30
      Pregnancies28735326334023285
      Cycles1,6592,1731,6362,0231,542571
      FR1.00 (ref.)0.90 (0.76–1.07)0.84 (0.69–1.01)0.88 (0.73–1.05)0.75 (0.62–0.91)0.70 (0.53–0.91)
       ≥30
      Pregnancies21321317718011031
      Cycles1,1971,3199711,133753248
      FR1.00 (ref.)0.86 (0.69–1.06)0.93 (0.74–1.17)0.80 (0.64–1.01)0.72 (0.55–0.93)0.61 (0.40–0.93)
      Parity
       Parous
      Pregnancies2752611531358119
      Cycles1,2571,211709705473107
      FR1.00 (ref.)0.92 (0.75–1.12)0.86 (0.68–1.09)0.78 (0.61–0.99)0.66 (0.50–0.89)0.68 (0.39–1.16)
       Nulliparous
      Pregnancies22530528738526197
      Cycles1,5992,2811,8982,4511,822712
      FR1.00 (ref.)0.89 (0.74–1.08)0.96 (0.79–1.17)0.99 (0.82–1.19)0.86 (0.70–1.05)0.80 (0.61–1.04)
      Body mass index (kg/m2)
       <25
      Pregnancies33736531139226793
      Cycles1,7002,1481,7982,3551,627688
      FR1.00 (ref.)0.79 (0.66–0.93)0.79 (0.66–0.94)0.76 (0.64–0.89)0.72 (0.60–0.87)0.58 (0.45–0.75)
       ≥25
      Pregnancies1632011291287523
      Cycles1,1561,344809801668131
      FR1.00 (ref.)1.12 (0.89–1.41)1.15 (0.88–1.48)1.16 (0.89–1.51)0.76 (0.56–1.03)1.22 (0.74–2.02)
      Cycle attempts before study entry
       ≤2
      Pregnancies35342033439127291
      Cycles1,9482,4091,8082,1891,687583
      FR1.00 (ref.)0.91 (0.78–1.07)0.92 (0.77–1.08)0.88 (0.75–1.04)0.77 (0.64–0.92)0.72 (0.55–0.94)
       3–6
      Pregnancies1471461061297025
      Cycles9081,083799967608236
      FR1.00 (ref.)0.80 (0.62–1.03)0.75 (0.56–0.99)0.73 (0.56–0.96)0.64 (0.46–0.88)0.55 (0.35–0.88)
      Moderate physical activity, h/wk
       <5
      Pregnancies36039229734020849
      Cycles2,1842,5911,7442,0721,351307
      FR1.00 (ref.)0.89 (0.76–1.04)0.96 (0.81–1.14)0.91 (0.77–1.08)0.83 (0.69–1.01)0.87 (0.62–1.21)
       ≥5
      Pregnancies14017414318013467
      Cycles6729018631,084944512
      FR1.29 (1.03–1.61)1.09 (0.89–1.34)0.92 (0.74–1.12)0.91 (0.75–1.12)0.75 (0.60–0.94)0.69 (0.52–0.92)
      Note: FR adjusted for cycle number, age, partner's age, body mass index, alcohol consumption, pack-years of smoking, intercourse frequency, last method of contraception, and moderate physical activity (when applicable); 95% CI in parentheses. FR = fecundability ratio; CI = confidence interval.
      Results for vigorous PA within levels of moderate PA (<5 vs. ≥5 h/wk) are shown at the bottom of Table 3, using a single reference category of women engaged in <5 hours of moderate PA and no vigorous PA. Fecundability was lowest for the women engaged in ≥5 h/wk of both moderate and vigorous PA (Table 3). Within each of the two levels of moderate PA, increasing levels of vigorous PA were associated with decreasing fecundability. Notably, women who engaged in ≥5 hours of moderate PA but reported no vigorous PA had increased fecundability compared with the least active women (<5 hours of moderate PA and no vigorous PA).
      The overall results were virtually unchanged when we further controlled for cycle length and cycle irregularity, which are potential mediators of the PA–time to pregnancy association (vigorous PA ≥5 vs. 0 h/wk: FR 0.68, 95% CI 0.54–0.85; total PA ≥60 vs. 20–29 MET-h/wk: FR 0.75, 95% CI: 0.57–0.99). Among women with regular cycles, point estimates were less precise, but they were consistent with the results based on all women (vigorous PA ≥5 vs. 0 h/wk: FR 0.66, 95% CI 0.51–0.86; total PA ≥60 vs. 20–29 MET-h/wk: FR 0.74, 95% CI 0.53–1.02). Similar associations were observed when pregnancy losses were excluded from the outcome definition (data not shown).
      Figure 1 shows the overall association between vigorous PA (h/wk) and fecundability using restricted cubic splines. Results are also presented according to categories of BMI at baseline (Supplemental Figs. 1 and 2, available online at www.fertstert.org). The observed patterns were consistent with the categorical results presented above: Fecundability decreased with increasing hours of vigorous PA per week, in a dose-response fashion, overall and among lean women. In contrast, low levels of vigorous PA were associated with increased fecundability among overweight and obese women up to ∼2 h/wk, after which vigorous PA had little effect on fecundability.
      Figure thumbnail gr1
      Figure 1Association between hours of vigorous physical activity per week and fecundability, fitted by restricted cubic splines. The reference level for the fecundability ratio is 0 hours/week. The curves are adjusted for cycle number, age, partner's age, body mass index, alcohol consumption, pack-years of smoking, intercourse frequency, last method of contraception, and hours of moderate physical activity per week. There were five knot points located at 0.5, 1, 2, 3, and 4 h/wk.

      Discussion

      In this prospective cohort study of Danish women aged 18–40 years, vigorous PA was associated with reduced fecundability in all subgroups of women examined, with the exception of overweight and obese women (BMI ≥25 kg/m2), among whom PA of any type either modestly increased or had little effect on fecundability. In contrast, moderate PA was associated with a modest increase in fecundability overall and did not appear to have any deleterious effect on fertility among lean or overweight/obese women.
      The finding of reduced fecundability among the highest-intensity exercisers agrees with some (
      • Gudmundsdottir S.L.
      • Flanders W.D.
      • Augestad L.B.
      Physical activity and fertility in women: the North-Trøndelag Health Study.
      ,
      • Morris S.N.
      • Missmer S.A.
      • Cramer D.W.
      • Powers R.D.
      • McShane P.M.
      • Hornstein M.D.
      Effects of lifetime exercise on the outcome of in vitro fertilization.
      ) but not all earlier epidemiologic investigations (
      • Chavarro J.E.
      • Rich-Edwards J.W.
      • Rosner B.A.
      • Willett W.C.
      Diet and lifestyle in the prevention of ovulatory disorder infertility.
      ,
      • Rich-Edwards J.W.
      • Spiegelman D.
      • Garland M.
      • Hertzmark E.
      • Hunter D.J.
      • Colditz G.A.
      • et al.
      Physical activity, body mass index, and ovulatory disorder infertility.
      ). Furthermore, the finding that any PA, regardless of type, may be associated with a modest increase in fecundability among overweight/obese women is supported by an intervention study showing that moderate PA coupled with weight loss can enhance fertility in obese women (
      • Clark A.M.
      • Ledger W.
      • Galletly C.
      • Tomlinson L.
      • Blaney F.
      • Wang X.
      • et al.
      Weight loss results in significant improvement in pregnancy and ovulation rates in anovulatory obese women.
      ). The observation that women engaged in moderate PA or intermediate levels of total PA (20–39 MET-h/wk) had higher fecundability agrees with another study based on a fertility clinic population (
      • Kucuk M.
      • Doymaz F.
      • Urman B.
      Effect of energy expenditure and physical activity on the outcomes of assisted reproduction treatment.
      ).
      The conflicting results across studies regarding the effect of high intensity PA on female infertility may be attributable to the type of infertility studied. Two previous studies focused only on ovulatory infertility (
      • Chavarro J.E.
      • Rich-Edwards J.W.
      • Rosner B.A.
      • Willett W.C.
      Diet and lifestyle in the prevention of ovulatory disorder infertility.
      ,
      • Rich-Edwards J.W.
      • Spiegelman D.
      • Garland M.
      • Hertzmark E.
      • Hunter D.J.
      • Colditz G.A.
      • et al.
      Physical activity, body mass index, and ovulatory disorder infertility.
      ). The mechanisms by which high-intensity PA has a deleterious effect on female fertility might involve factors other than ovulation, such as impaired implantation. In support of this hypothesis, the study by Morris et al. of the success of IVF treatment reported a higher rate of implantation failures among women with high levels of PA (
      • Morris S.N.
      • Missmer S.A.
      • Cramer D.W.
      • Powers R.D.
      • McShane P.M.
      • Hornstein M.D.
      Effects of lifetime exercise on the outcome of in vitro fertilization.
      ). Morris et al. also found that associations were stronger among the women who engaged in cardiovascular activities (e.g., running, aerobics, or bicycling) as their primary exercise compare with those who engaged in walking (
      • Morris S.N.
      • Missmer S.A.
      • Cramer D.W.
      • Powers R.D.
      • McShane P.M.
      • Hornstein M.D.
      Effects of lifetime exercise on the outcome of in vitro fertilization.
      ), which agrees with our results for vigorous versus moderate types of PA.
      Not all women entered our study when they were first attempting to conceive, introducing a possibility of both differential and nondifferential misclassification of PA. However, the observation of reduced fecundability among the high-intensity exercisers with ≤2 cycle attempts before study entry suggests that bias due to left truncation did not have a large influence on our results. More than 96% of the women in our cohort with a viable pregnancy reported using home pregnancy tests to confirm their pregnancy, suggesting that bias due to differential recognition of early pregnancy loss (which may be as high as 25% [
      • Wilcox A.J.
      • Weinberg C.R.
      • O'Connor J.F.
      • Baird D.D.
      • Schlatterer J.P.
      • Canfield R.E.
      • et al.
      Incidence of early loss of pregnancy.
      ]) is unlikely to explain our results. Although rates of unintended pregnancy are considerably lower in Denmark than in other developed countries (
      • Jones E.F.
      • Forrest J.D.
      • Henshaw S.K.
      • Silverman J.
      • Torres A.
      Unintended pregnancy, contraceptive practice and family planning services in developed countries.
      ), the study's restriction to pregnancy planners entailed the omission of a nonnegligible fraction of total pregnancies. If pregnancy intention was related both to PA and fertility potential, our results would not apply to women with unplanned pregnancies.
      Another limitation is that we did not validate our measures of physical activity. However, vigorous PA was correlated with other lifestyle and behavioral variables (e.g., education, BMI, and parity) in the expected direction. In addition, we did not ask about specific types of PA, but rather ascertained the number of hours of activity per week for all types of vigorous or moderate PA combined. Given that specific sports with varying intensities may have different effects on fecundability—e.g., an Iranian study showed that endurance and weight-category sports may confer a higher risk of amenorrhea or oligomenorrhea than other sports (
      • Dadgostar H.
      • Razi M.
      • Aleyasin A.
      • Alenabi T.
      • Dahaghin S.
      The relation between athletic sports and prevalence of amenorrhea and oligomenorrhea in Iranian female athletes.
      )—our results may have been influenced by nondifferential misclassification, which most likely would have biased the effect of high PA toward the null. Use of a baseline measure of physical activity, as opposed to one that was updated throughout follow-up, may have resulted in misclassification. For example, women who took longer to conceive could have modified their exercise patterns, thereby introducing differential exposure misclassification. Nevertheless, after stratifying the data by attempt time at entry into the study, we did not find strong evidence of bias in our findings. We were also unable to examine the different causes of subfertility in this study. The time to pregnancy measure represents a combination of different causes contributing to couples' subfertility, and therefore the associations reported in this study are likely to reflect the overall effect of PA on fertility.
      Cohort retention in this study was similar to that reported in other large volunteer cohort studies (
      • Russell C.
      • Palmer J.R.
      • Adams-Campbell L.L.
      • Rosenberg L.
      Follow-up of a large cohort of Black women.
      ,
      • Olsen J.
      • Melbye M.
      • Olsen S.F.
      • Sorensen T.I.
      • Aaby P.
      • Andersen A.M.
      • et al.
      The Danish National Birth Cohort—its background, structure and aim.
      ). PA levels were similar for the small proportion of women lost to follow-up and women followed to a study end point, implying that bias due to selective losses was unlikely. Another consideration is that this study enrolled a self-selected sample of pregnancy planners recruited via the internet; but there is little reason to believe that such women would differ from the general population of women planning a pregnancy in ways that would lead to biased effect estimates. Two Scandinavian birth cohort studies, in which population registry data were used to compare differences between study participants and all women giving birth in the general population, showed that nonparticipation at study outset had a small impact on effect estimates (
      • Nilsen R.M.
      • Vollset S.E.
      • Gjessing H.K.
      • Skjaerven R.
      • Melve K.K.
      • Schreuder P.
      • et al.
      Self-selection and bias in a large prospective pregnancy cohort in Norway.
      ,
      • Nohr E.A.
      • Frydenberg M.
      • Henriksen T.B.
      • Olsen J.
      Does low participation in cohort studies induce bias?.
      ).
      In summary, although the present study found evidence of a dose-response relation between increasing vigorous PA and delayed time to pregnancy, results were equivocal among overweight and obese women. Moderate PA was associated with a small increase in fecundability regardless of BMI. These findings indicate that PA of any type might improve fertility among overweight and obese women, a subgroup at higher risk of infertility. Lean women who substitute vigorous PA with moderate PA may also improve their fertility. Future research investigating individual types of PA in relation to fertility, and whether overweight or obese women might benefit from increased PA when planning a pregnancy, is warranted.

      Acknowledgments

      The authors thank the study staff and all of the women who participated in the Snart Gravid study. The authors also thank Ms. Tina Christensen for her support with data collection and media contact, Dr. Donna Baird for her feedback on questionnaire development, and Mr. Thomas Jensen for his assistance with website design. We also thank Ms. Kristen Hahn, Ms. Rose Radin, and Ms. Kristen Banholzer for their general assistance with the manuscript.

      Appendix.

      Figure thumbnail fx1
      Supplemental Figure 1Association between hours of vigorous physical activity per week and fecundability among women with body mass index (BMI) <25 kg/m2, fitted by restricted cubic splines. The reference level for the fecundability ratio is 0 h/wk. The curves are adjusted for cycle number, age, partner's age, BMI (continuous), alcohol consumption, pack-years of smoking, intercourse frequency, last method of contraception, and hours of moderate physical activity per week. There were four knot points located at 0.5, 1, 2, and 3 h/wk.
      Figure thumbnail fx2
      Supplemental Figure 2Association between hours of vigorous physical activity per week and fecundability among women with body mass index (BMI) ≥25 kg/m2, fitted by restricted cubic splines. The reference level for the fecun-dability ratio is 0 h/wk. The curves are adjusted for cycle number, age, partner's age, BMI (continuous), alcohol consumption, pack-years of smoking, intercourse frequency, last method of con-traception, and hours of moderate physical activity per week. There were 4 knot points located at 0.5, 1, 2, and 3 h/wk.
      Supplemental Table 1Moderate physical activity and time to pregnancy, stratified by selected factors.
      CharacteristicModerate physical activity, hours per week
      <1123–4≥5
      Age at baseline, y
       <30
      Pregnancies94123306485552
      Cycles6508751,9032,8243,352
      FR1.00 (ref.)0.86 (0.64–1.16)1.05 (0.81–1.36)1.11 (0.87–1.43)1.07 (0.84–1.38)
       ≥30
      Pregnancies67104232235286
      Cycles5006681,3701,4591,624
      FR1.00 (ref.)1.22 (0.87–1.72)1.32 (0.97–1.78)1.20 (0.88–1.62)1.34 (0.99–1.81)
      Parity
       Parous
      Pregnancies82101217239285
      Cycles4785401,1501,0511,243
      FR1.00 (ref.)1.13 (0.81–1.58)1.12 (0.84–1.49)1.36 (1.02–1.81)1.37 (1.03–1.83)
       Nulliparous
      Pregnancies79126321481553
      Cycles6721,0032,1233,2323,733
      FR1.00 (ref.)0.98 (0.72–1.33)1.23 (0.94–1.62)1.14 (0.88–1.48)1.15 (0.88–1.49)
      Body mass index (kg/m2)
       <25
      Pregnancies97145364516643
      Cycles6188892,1013,0473,661
      FR1.00 (ref.)1.02 (0.77–1.36)1.11 (0.86–1.43)1.10 (0.86–1.41)1.17 (0.92–1.49)
       ≥25
      Pregnancies6482174204195
      Cycles5326541,1721,2361,315
      FR1.00 (ref.)0.99 (0.69–1.42)1.22 (0.89–1.67)1.27 (0.94–1.77)1.20 (0.87–1.65)
      Cycle attempts before study entry
       ≤2
      Pregnancies125170390551625
      Cycles7831,1152,2473,0153,464
      FR1.00 (ref.)0.88 (0.68–1.15)1.02 (0.81–1.28)1.06 (0.85–1.32)1.06 (0.85–1.32)
       3–6
      Pregnancies4657148169213
      Cycles3674281,0261,2681,512
      FR1.00 (ref.)1.46 (0.92–2.30)1.58 (1.06–2.36)1.45 (0.97–2.15)1.59 (1.08–2.36)
      Note: FR adjusted for cycle number, age, partner's age, BMI, alcohol consumption, pack-years of smoking, intercourse frequency, last method of contraception, and vigorous PA; 95% CI in parentheses. FR = fecundability ratio; CI = confidence interval.
      Supplemental Table 2Total physical activity and time to pregnancy, stratified by selected factors.
      CharacteristicTotal MET-hours of physical activity per week
      <1010–1920–2930–3940–4950–59≥60
      Age at baseline, y
       <30
      Pregnancies2084683332741358854
      Cycles1,3952,8971,8971,611998438368
      FR0.91 (0.75–1.10)0.92 (0.79–1.08)1.00 (ref.)0.95 (0.79–1.14)0.75 (0.60–0.93)1.11 (0.85–1.45)0.78 (0.57–1.07)
       ≥30
      Pregnancies166316200130663016
      Cycles1,0501,8501,198734394250145
      FR1.01 (0.80–1.28)1.00 (0.82–1.23)1.00 (ref.)1.00 (0.78–1.28)0.95 (0.69–1.30)0.60 (0.40–0.92)0.59 (0.34–1.04)
      Parity
       Parous
      Pregnancies201334193110502214
      Cycles1,0271,64183449924012596
      FR0.87 (0.69–1.10)0.86 (0.70–1.06)1.00 (ref.)0.90 (0.68–1.18)0.80 (0.55–1.15)0.67 (0.41–1.10)0.61 (0.33–1.12)
       Nulliparous
      Pregnancies1734503402941519656
      Cycles1,4183,1062,2611,8461,152563417
      FR0.90 (0.74–1.11)0.97 (0.83–1.13)1.00 (ref.)1.01 (0.85–1.20)0.84 (0.69–1.04)1.07 (0.83–1.38)0.81 (0.60–1.11)
      Body mass index (kg/m2)
       <25
      Pregnancies2155373933121619156
      Cycles1,2573,0512,2861,7421,077478425
      FR1.01 (0.84–1.22)1.02 (0.88–1.18)1.00 (ref.)1.02 (0.86–1.20)0.84 (0.68–1.03)1.07 (0.82–1.38)0.71 (0.52–0.96)
       ≥25
      Pregnancies15924714092402714
      Cycles1,1881,69680960331521088
      FR0.76 (0.59–0.99)0.79 (0.63–1.00)1.00 (ref.)0.81 (0.60–1.08)0.75 (0.51–1.11)0.64 (0.40–1.00)0.96 (0.52–1.77)
      Cycle attempts before study entry
       ≤2
      Pregnancies2695983873121469059
      Cycles1,6973,2972,1471,684917513369
      FR0.96 (0.80–1.15)1.02 (0.88–1.18)1.00 (ref.)1.00 (0.85–1.19)0.84 (0.68–1.04)0.91 (0.70–1.18)0.82 (0.61–1.11)
       3–6
      Pregnancies10518614692552811
      Cycles7481,450948661475175144
      FR0.95 (0.72–1.27)0.83 (0.66–1.06)1.00 (ref.)0.90 (0.67–1.21)0.73 (0.52–1.03)1.05 (0.67–1.65)0.48 (0.25–0.93)
      Note: FR adjusted for cycle number, age, partner's age, body mass index, alcohol consumption, pack-years of smoking, intercourse frequency, and last method of contraception; 95% CI in parentheses. FR = fecundability ratio; CI = confidence interval.

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