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Changes in the state of energy balance owing to changes in physical activity may affect the reproductive system. We evaluated the association between physical activity (PA) and fertility and parity in healthy women. A population-based health survey (HUNT 1) was conducted during 1984-1986 in Nord-Trøndelag county, Norway, with follow-up from 1995 to 1997 (HUNT 2). The study included 3887 women, <45 years old in HUNT 2. PA was assessed by baseline questionnaire, and fertility and parity by questionnaire at follow-up. Data focused on overall occurrence of infertility in the population (without biological confirmation). Increased frequency, duration and intensity of PA were associated with increased subfertility, and frequency of PA was associated with voluntary childlessness (P < 0.01). After adjusting for age, parity, smoking, and marital status, women who were active on most days were 3.2 times more likely to have fertility problems than inactive women. Exercising to exhaustion was associated with 2.3 times the odds of fertility problems versus low intensity. Women with highest intensity of PA at baseline had the lowest frequency of continuing nulliparity and highest frequency of having three or more children during follow-up (P < 0.05). Sensitivity analysis including body mass index as confounder did not alter the results. No associations were found between lower activity levels and fertility or parity. Increased risk of infertility was only found for the small group of women reporting the highest levels of intensity and frequency of PA. Awareness of the possible risks of infertility should be highlighted among non-athletic women who exercise vigorously.
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ORIGINAL ARTICLE Reproductive epidemiology
Physical activity and fertility in women:
the North-Trøndelag Health Study
S.L. Gudmundsdottir1, W.D. Flanders2, and L.B. Augestad1,3
1
Human Movement Science Programme, Faculty of Social Sciences and Technology Management, Norwegian University of Science and
Technology (NTNU), NO-7491 Trondheim, Norway
2
Departments of Epidemiology and Biostatistics, Emory University, Atlanta,
GA 30345, USA
3
Correspondence address. Tel: þ47 7359-1780; Fax: þ47 7359-1770; E-mail: liv.berit.augestad@svt.ntnu.no
background: Changes in the state of energy balance owing to changes in physical activity may affect the reproductive system. We
evaluated the association between physical activity (PA) and fertility and parity in healthy women.
methods: A population-based health survey (HUNT 1) was conducted during 1984– 1986 in Nord-Trøndelag county, Norway, with
follow-up from 1995 to 1997 (HUNT 2). The study included 3887 women, ,45 years old in HUNT 2. PA was assessed by baseline ques-
tionnaire, and fertility and parity by questionnaire at follow-up. Data focused on overall occurrence of infertility in the population (without
biological confirmation).
results: Increased frequency, duration and intensity of PA were associated with increased subfertility, and frequency of PA was associ-
ated with voluntary childlessness (P,0.01). After adjusting for age, parity, smoking, and marital status, women who were active on most
days were 3.2 times more likely to have fertility problems than inactive women. Exercising to exhaustion was associated with 2.3 times the
odds of fertility problems versus low intensity. Women with highest intensity of PA at baseline had the lowest frequency of continuing nulli-
parity and highest frequency of having three or more children during follow-up (P,0.05). Sensitivity analysis including body mass index as
confounder did not alter the results. No associations were found between lower activity levels and fertility or parity.
conclusion: Increased risk of infertility was only found for the small group of women reporting the highest levels of intensity and fre-
quency of PA. Awareness of the possible risks of infertility should be highlighted among non-athletic women who exercise vigorously.
Key words: epidemiology / exercise / infertility / physical activity / women
Introduction
Infertility is defined as the inability of a couple to conceive within
1 year of trying to become pregnant (Kumar et al., 2007). Recent
estimates of the prevalence of infertility range from 3.5 to 16.7% in
more developed nations and from 6.9 to 9.3% in less developed
nations (Boivin et al., 2007). In Norway, the lifetime infertility preva-
lence has been estimated to be 6.6% (Rostad et al., 2006).
A variety of lifestyle factors, such as smoking (Hughes and Brennan
1996; Augood et al., 1998; Hull et al., 2000), psychological stress
(Hjollund et al., 1999), caffeine (Wilcox et al., 1988) and alcohol con-
sumption (Gill, 2000; Eggert et al., 2004) and extremely low or high
body mass index (BMI) (Rich-Edwards et al., 2002; Hassan and
Killick 2004; Norman et al., 2004) have been proposed as causes of
infertility. Consequences of infertility may include psychosocial pro-
blems (Greil, 1997; Boivin, 2003), higher risks of breast and ovarian
cancer (Jensen et al., 2008) and high financial costs for those trying
infertility treatment (Jain and Hornstein 2003). In addition, childless-
ness has been related to mortality disadvantages (Grundy and
Kravdal, 2008). It is suggested that one-third of the incidences of
couple infertility can be related to male reproductive problems
(Meacham et al., 2007).
Reproductive dysfunction is reported to have a higher prevalence in
athletes than non-athletes (Russell et al., 1984; Otis et al., 1997), with
clinical consequences that may include infertility (Warren et al.,
2001). Less is known about the effects of physical activity (PA) on
female fertility in the general population, in contrast to the relatively
well-known beneficial effects of regular PA for numerous undesirable
health outcomes, including the prevention of premature death
(Bouchard and Blair 1999; Warburton et al., 2006). Only a few
studies have focused on the general population. In a cohort study, the
Nurses’ Health Study II, more hours of vigorous exercise were associ-
ated with reduced risk of ovulatory infertility (Rich-Edwards et al., 2002;
Chavarro et al., 2007) while Morris et al. (2006) found that women who
had enrolled on a fertility treatment programme and reported exercis-
ing 4 h or more per week for 1 9 years previously were 40% less likely
to have a live birth, almost three times more likely to experience cycle
cancellation, and twice as likely to have an implantation failure or
&The Author 2009. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved.
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Human Reproduction, Vol.24, No.12 pp. 3196– 3204, 2009
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pregnancy loss than women who had reported not exercising. More
moderate exercise together with weight loss has been found to be posi-
tive in fertility treatment in obese women (Clark et al., 1995). The effect
of PA on fertility may therefore be positive up to a certain level and have
a negative effect above that threshold level of activity. A similar pattern is
suggested for bone health: physically active individuals have been found
to have a lower risk of low bone mineral density and fractures, while the
risk of stress fractures is increased with high-volume training (Kohrt
et al., 2004). This may occur through the direct effects of activity on hor-
mones which stimulate bone formation or indirectly via effects on estro-
gen and menstrual function, a condition often coupled with negative
energy availability in an interrelationship known as the female athlete
triad (Nattiv et al., 2007).
PA plays an important role in maintaining energy balance and it has
been suggested that changes in the status of energy balance due to
changes in PA may affect the reproductive system (Redman, 2006).
In addition, there are some indications that weight loss via PA may
protect ovarian function by increasing insulin resistance and changing
the hormone profile (Norman et al., 2004).
The purpose of this study is to evaluate the association between PA
and fertility status and parity in healthy, premenopausal, Norwegian
women.
Methods
All residents in the county of Nord-Trøndelag, Norway, men and women
aged 20 years, were invited to participate in the Nord-Trøndelag Health
Study in 1984–1986 (HUNT 1) and in the follow-up study in 1995–1997
(HUNT 2).
Among those eligible for HUNT 1, 77 310 (90.8%) returned a
health-related questionnaire and 74 977 (88.1%) participated in the
health examination. At the examination, participants filled out a second
questionnaire, including questions regarding PA.
In HUNT 2, 71.3% of the original cohort from HUNT 1 participated. Par-
ticipants were sent a comprehensive health-related questionnaire by mail.
Assessments at the screening station included measurements of height and
weight. At the examination, participants received a more detailed question-
naire evaluating demographics, medication use, diet, reproductive history,
infertility, menstrual history, history of gynaecological surgery and pregnancy.
In total, 24 837 women participated in both surveys. Of those, 5986
women were ,45 years old at HUNT 2, and therefore considered pre-
menopausal. We excluded women who reported serious conditions or
diagnoses known to affect capability for PA or reproductive function at
baseline, as summarized in Fig. 1, leaving 3887 women in our study.
Weekly frequency, intensity and duration of leisure time PA was
assessed using a self-reported questionnaire in HUNT 1 (http://www.
ntnu.no/eksternwebEN/aboutntnu/facultiesanddepartments/dmf/HUNT/
questionnaires/) (Table I). The questions regarding PA have been vali-
dated for men with good reliability and test and retest validity (Kurtze
et al., 2008). Based on the reported intensity, duration and frequency,
an index of PA was calculated: detailed descriptions are presented in pre-
viously published papers (Augestad et al., 2004; Augestad et al., 2006).
With division at the 33.3th and 66.6th percentiles of the index, leisure
time PA was categorized into low, moderate and high levels. Occupational
PA was assessed by asking the women if they felt physically tired
from occupational work (almost never, seldom, often, almost always).
Age, education, marital status, smoking, and alcohol consumption were
reported at baseline. BMI (kg/m
2
) was computed from measured height
and weight.
Fertility status and reproductive history were assessed by a self-
reported questionnaire in HUNT 2. Questions included inability to con-
ceive within 1 year of trying (and at what age), parity, age at childbirth(s),
contraceptive use and menstruation and pregnancy status.
We classified women as fertile if they conceived within 1 year of
attempting to become pregnant and gave birth, and infertile if they did
not conceive within 1 year, regardless of any subsequent pregnancies
(Kumar et al., 2007). Infertile women were further classified as
subfertile if the time to pregnancy exceeded 1 year of trying, and as
involuntarily childless if they reported problems with conceiving within
1 year and there had been no childbirth. Voluntarily childlessness was
assumed if neither problems with becoming pregnant nor childbirth
were reported.
Fertility status and parity for different levels of baseline variables were
compared using descriptive and chi-square statistics. We modelled the
probability of fertility problems (subfertility or involuntary childlessness)
using unadjusted and adjusted logistic regression. For infertility, odds
ratio (ORs) estimates were obtained by maximum likelihood with associ-
ated 95% confidence intervals (CIs). We were concerned there might be
some link between PA and age and therefore performed subgroup ana-
lyses for young women, ,30 years of age, because of the higher preva-
lence of infertility in this group.
The associations of baseline measurements with parity were examined
in women who were nulliparous in HUNT 1. Comparisons were made
using ordinal regression models, adjusting for potential confounders.
In these analyses parity was treated as a three-level variable: nulliparous,
one to two children and more than two children.
Figure 1 Sequential exclusion of participants in the study of phys-
ical activity and fertility. *No response to questions needed for
classification.
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Table I Baseline characteristics of the healthy Norwegian female study population
Characteristic nwithin
level
Fertile, 3511
(90.3%)
Subfertile, 197
(5.1%)
Involuntary childless,
27 (0.7%)
Voluntary childless,
152 (3.9%)
P-value
Age, n
20–25 years 1247 1048 (84.0) 120 (9.6) 13 (1.0) 66 (5.3) 0.000
26–30 years 1632 1502 (92.0) 62 (3.8) 10 (0.6) 58 (3.6)
31–35 years 1008 961 (95.3) 15 (1.5) 4 (0.4) 28 (2.8)
BMI
,18.5 151 132 (87.4) 10 (6.6) 1 (0.7) 8 (5.3) 0.001
18.5–24.9 3007 2743 (91.2) 138 (4.6) 24 (0.8) 102 (3.4)
25–29.9 579 511 (88.3) 38 (6.6) 1 (0.2) 29 (5.0)
30.0–34.9 114 98 (86.0) 7 (6.1) 0 9 (7.9)
35.0,31 22 (71.0) 4 (12.9) 1 (3.2) 4 (12.9)
Frequency of PA
Never 272 258 (94.9) 6 (2.2) 1 (0.4) 7 (2.6) 0.000
,1 per week 1252 1144 (91.4) 60 (4.8) 8 (0.6) 40 (3.2)
1 per week 1210 1109 (91.7) 55 (4.5) 9 (0.7) 37 (3.1)
2–3 per week 890 778 (87.4) 50 (5.6) 8 (0.9) 54 (6.1)
Nearly every day 263 222 (84.4) 26 (9.9) 1 (0.4) 14 (5.3)
Intensity of PA
Take it easy 1418 1298 (91.5) 57 (4.0) 8 (0.6) 55 (3.9) 0.000
Lose breath 1363 1215 (89.1) 80 (5.9) 11 (0.8) 57 (4.2)
To exhaustion 94 76 (80.9) 14 (14.9) 0 (0.0) 4 (4.2)
Duration of PA
,15 min 440 403 (91.6) 24 (5.5) 2 (0.5) 11 (2.5) 0.001
15–30 min 937 860 (91.8) 30 (3.2) 5 (0.5) 42 (4.5)
30–60 min 1261 1124 (89.1) 71 (5.6) 12 (1.0) 54 (4.3)
.60 min 305 260 (85.2) 30 (9.8) 0 (0.0) 15 (4.9)
PA index
Low 989 916 (92.6) 38 (3.8) 5 (0.5) 30 (3.0) 0.000
Moderate 968 885 (91.4) 39 (4.0) 7 (0.7) 37 (3.8)
High 880 752 (85.5) 72 (8.2) 7 (0.8) 49 (5.6)
Physically tired from work
Never 432 380 (88.0) 22 (5.1) 3 (0.7) 27 (6.2) 0.097
Seldom 1546 1413 (91.4) 74 (4.8) 11 (0.7) 48 (3.1)
Often 1365 1261 (92.4) 54 (4.0) 5 (0.4) 45 (3.3)
Almost always 268 246 (91.8) 13 (4.9) 2 (0.7) 7 (2.6)
Smoking
Never 1563 1388 (88.8) 73 (4.7) 12 (0.8) 90 (5.8) 0.001
Former 761 703 (92.4) 37 (4.9) 4 (0.5) 17 (2.2)
Current 1549 1409 (91.0) 85 (5.5) 11 (0.7) 44 (2.8)
Alcohol consumption prev. 14 days
Never 2038 1857 (91.1) 88 (4.3) 80 (3.9) 13 (0.6) 0.170
1–4 times 1746 1560 (89.3) 102 (5.8) 71 (4.1) 13 (0.6)
5–10 times 35 30 (85.7) 4 (11.4) 0 1 (2.9)
.10 times 55 52 (94.5) 2 (3.6) 1 (1.8) 0
Marital status
Unmarried 1352 1056 (78.1) 134 (9.9) 22 (1.6) 140 (10.4) 0.000
Married 2377 2312 (97.3) 53 (2.2) 5 (0.2) 7 (0.3)
Previously
married
97 90 (92.8) 7 (7.2) 0 (0.0) 0 (0.0)
Continued
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In all of the above analyses, models were run separately for each of the
PA variables (frequency, intensity, duration and index). Full multivariate
models were run at first. Variables were subsequently removed from
the models if their removal did not affect the coefficient estimates of
the remaining variables in the model or the overall significance of the
model.
Based primarily on a priori considerations, we considered the following
baseline measurements as potential confounders: age (5-year categories),
parity, i.e. when assessing the probability of infertility (nulliparous, not nul-
liparous) (Sternfeld et al., 1999; Miller et al., 2002), smoking (never,
former, current), frequency of alcohol consumption during the 14 days
prior to participation in the study (never, 1 4 times, 5–10 times, .10
times) marital status (unmarried, married, previously married) and edu-
cation (,10, 10 12, .12 years).
Women with an unusually high or low BMI tend to have greater risk of
infertility. Because women with high or low BMI may be either less likely or
more likely to be physically active, baseline BMI may be considered a
potential confounder of the relationship between PA and fertility.
However, BMI might also be considered an intermediate variable in that
PA could affect BMI and, in turn, fertility status. We therefore did not
include BMI as an independent variable in the primary (a priori) analyses,
because its inclusion might have biased the estimated association
between PA and fertility status. However, to assess whether inclusion of
BMI affected the estimated association with fertility status, we also con-
ducted additional (sensitivity) analyses that included this variable, treating
it as categorical (World Health Organization categorization of under-,
normal- and overweight, obesity and severe obesity) at baseline. Statistical
significance was set at P,0.05.
The study was approved by the Norwegian Regional Committee for
Ethics in Medical Research and the Norwegian Data Inspectorate and
each subject gave written informed consent prior to participation.
Results
Baseline characteristics and their bivariate relations to fertility status at
follow-up are shown in Table I. The mean baseline age was 27.2 years
(range 20–35) and mean BMI was 22.7 kg/m
2
(range 14.5–44.1).
Overall, 90.1% of the women were classified as fertile, 5.1% as subfer-
tile, 0.7% as involuntary childless and 3.9% as voluntary childless.
A total of 62.4% of infertile women reported having visited a
medical doctor for fertility problems.
The frequency of subfertility decreased with increased age, as did
voluntary childlessness. The relationships of BMI categories with
subfertility and voluntary and involuntary childlessness were approxi-
mately J-shaped, and subfertility was least common in the normal
weight group (BMI: 18.5–24.9). Based on the univariate analyses,
women classified as fertile were more often married and had less
than 10 years of education. Voluntarily childless women were more
often unmarried, non-smokers, with more than 12 years of education.
Subfertility was least common among married women (Table I).
Increased frequency of PA was associated with increased subfertility
and voluntary childlessness. A similar relationship was observed
between intensity and longer duration of PA and subfertility but less
so with voluntary childlessness. In the unadjusted analyses, a high
level of PA, according to our calculated index, was associated with
increased subfertility and voluntary childlessness. Due to missing
answers however, the PA index could not be calculated for just
over 1000 women. Tiredness from occupational activity was not
found to be associated with fertility status (Table I).
The observed relationships between PA variables and fertility status
followed the same trend as those reported above, after controlling for
suspected confounding factors: age, parity, smoking and marital status
(Table II). Additional control for education and alcohol consumption
did not meaningfully affect the ORs. In particular, women who were
active on most days of the week were 3.2 times more likely to be
infertile than inactive women. Exercising to exhaustion was associated
with 2.3 times the odds of infertility compared with lower levels of
intensity. For duration, there was decreased risk of infertility in
those whose exercise was moderate (16 30 and 3060 min) com-
pared with the shortest duration of less than 15 min. Women who,
according to the index of PA, were highly active had an OR of 1.5
for infertility compared women with low or moderate levels of activity.
The alternative analysis, designed to assess the sensitivity of results
to alternative models, in which we included BMI as a potential con-
founding factor, did not result in notably different parameter esti-
mates, consistent with the small differences in BMI across the
groups in the PA variables.
In a subgroup analysis restricted to women up to 30 years of age in
whom subfertility was more common (6.3%) than in the older age
group (1.5%), we found that these younger women were more
likely than older women to exercise every day, exercise to exhaustion
or exercise for more than 60 min. Among the young women, subfer-
tility was reported by 23.7% of those exercising to the level of exhaus-
tion and by 11.1% of those who reported exercising almost every day.
.............................................................................................................................................................................................
Table I Continued
Characteristic nwithin
level
Fertile, 3511
(90.3%)
Subfertile, 197
(5.1%)
Involuntary childless,
27 (0.7%)
Voluntary childless,
152 (3.9%)
P-value
Education
,10 years 1090 1021 (93.7) 33 (3.0) 6 (0.6) 30 (2.8) 0.000
10–12 years 2258 2024 (89.6) 132 (5.8) 15 (0.7) 87 (3.9)
.12 years 510 442 (86.7) 31 (6.1) 5 (1.0) 32 (6.3)
Parity
0 786 510 (64.9) 97 (12.3) 27 (3.4) 152 (19.3) 0.000
13095 2995 (96.8) 100 (3.2)
PA, physical activity. Fertility statusbased on self-reported problems with conceiving within 1 year and childbirths at follow-up. P-values indicate results of the Pearson’s chi-square test. n(%).
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In this subgroup there was a u-shaped relationship between duration
of exercise and subfertility. Among women who reported ,15 min or
.60 min duration, the frequency of subfertility was 12.6 and 12.4%,
respectively, while 3.9% of women exercising for 16 30 min and
7.0% of those exercising for 30 60 min reported subfertility.
In this subgroup, adjusted logistic analysis showed similar but some-
what stronger relationships than in the study group as a whole. The
OR for infertility was 3.5 (CI: 1.3 9.0) for women who exercised
almost every day and women who exercised to the level of exhaustion
had 3.0 (CI: 1.3 6.0) times the risk of infertility compared with those
taking it easy. The trend between the calculated index of PA, occu-
pational activity or other variables did not differ meaningfully from
patterns observed in the analyses that included all age groups.
Women who were nulliparous at baseline were significantly younger
than women who had given birth (24.0 versus 26.5; P,0.001). They
had higher occurrence of frequent PA, higher intensity and longer dur-
ation of activity (P,0.001 for all). Nulliparous women were less likely
to feel tired from occupational activity. They had higher education at
baseline, and were more likely to be non-smokers and unmarried
than women who had given birth (P,0.001 for all). The two
groups did not differ on baseline BMI.
For women who were nulliparous at baseline, the mean number of
children born between baseline and follow-up investigations was 1.5
(range 0–4). A total of 179 women were still nulliparous at follow-up,
of whom 152 (84.9%) reported voluntary childlessness. In descriptive
analyses of this group, continued nulliparity at follow-up was associ-
ated with greater age and with lower or higher than normal BMI.
Parity during follow-up was also related to education. However, it
should be noted that at baseline, 93.7% of women with ,10 years
education had already given birth (Table I). For women who had
not given birth at baseline, we found similar ORs of infertility as for
the whole sample but the 95% CIs were larger and included 1 in all
instances (data not shown).
Women who reported the highest intensity of PA at baseline had
the lowest frequency of continuing nulliparity and highest frequency
of having three or more children during follow-up (P,0.05). In the
unadjusted analysis, there was also a tendency towards less continuing
nulliparity and higher parity among those women with longer durations
of PA and higher scores on the PA index (Table III).
There was a significant tendency towards higher parity among
women with the highest intensity of PA compared with moderate
intensity in an ordinal regression analysis, adjusting for age and edu-
cation. Women reporting low intensity of activity did not significantly
differ from the high intensity group. The model was subsequently run
including BMI but no meaningful changes to the parameter estimates
were observed. In another subgroup analysis excluding those
women who were voluntarily childless in HUNT 2, although the direc-
tion of this association was the same, the relationship was no longer
significant (P¼0.07).
Frequency of PA or tiredness from occupational activity was not
related to parity.
Discussion
In this study we examined the association between PA and fertility
status and parity in healthy premenopausal Norwegian women. We
found that women with the highest levels of frequency or intensity
of PA had increased risk of infertility. We did not, however, see a
trend for increased risk of infertility for the submaximal levels of inten-
sity or frequency of PA. Moreover, the highest level of our index of
PA, indicating the total load of exercise, was related to increased like-
lihood of infertility in adjusted analyses. There was decreased risk of
infertility for women reporting moderate duration of activity in our
adjusted analyses, compared with women reporting activity duration
of less than 15 min. Our estimate of 5.8% prevalence of infertility is
somewhat lower than earlier reports from the same study population
in which lifetime infertility prevalence has been estimated to be 6.6%
(Rostad et al., 2006). The women in our sample were younger than in
the Rostad et al. (2006) study and some may still experience infertility
in their remaining reproductive years.
Although we showed that high intensity of PA was related to
increased risk of infertility, there was also a trend of having three or
more children during the follow-up period among women who
reported the highest level of PA intensity at baseline. A possible expla-
nation may be that women who did high intensity training at baseline
and experienced infertility problems adjusted their activity level to a
lower intensity level. Alternatively, although if intense PA had a nega-
tive effect on the first trial for conception, hormonal changes during
and following pregnancy may have counteracted that negative effect
in later pregnancies. The likelihood of fertility problems in our study
was, however, not notably different for nullipara women compared
with those who had already given birth. This may suggest that the
........................................................................................
Table II Unadjusted and adjusted ORs from logistic
regression for fertility problems (subfertility or
involuntary childlessness)
PA Unadjusted OR
(95% CI)
Adjusted OR
#
(95% CI)
Frequency
Never* 1.0 1.0
,Once a week 2.2 (1.0–4.8) 2.1 (0.9– 4.7)
Once a week 2.1 (1.0– 4.7) 2.0 (0.9– 4.5)
2–3 times a week 2.6 (1.2– 5.9) 2.0 (0.9–4.6)
Almost every day 4.3 (1.9– 10.1) 3.2 (1.3 7.6)
Intensity
Easy* 1.0 1.0
Sweating and out of breath 1.3 (1.1–1.9) 1.1 (0.8 1.6)
Exhaustion 3.3 (1.8–6.2) 2.3 (1.2. 4.5)
Duration
,15 min* 1.0 1.0
16–30 min 0.3 (0.2– 0.6) 0.3 (0.2– 0.5)
30–60 min 0.6 (0.3– 1.0) 0.5 (0.3.– 0.9)
.60 min 0.9 (0.5 1.6) 0.6 (0.3– 1.2)
PA index
Low* 1.0 1.0
Medium 1.0 (0.7–1.7) 0.9 (0.6 1.5)
High 2.1 (1.5– 3.2) 1.5 (1.0– 2.3)
PA, physical activity.
#
Adjusted for age, parity, smoking and marital status.
*Reference category OR, odds ratio; CI, confidence interval.
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Table III Baseline characteristics of women who were nulliparous at baseline (n5786)
No childbirth, 179 (22.8) 1–2 children, 458 (58.3) 3 or more children, 149 (19.0) P-value
Age
20–25 years 561 79 (14.1) 358 (63.8) 124 (22.1) 0.000
26–30 years 179 68 (38.0) 88 (49.2) 23 (12.8)
31–35 years 46 32 (69.6) 12 (26.1) 2 (4.3)
BMI
,18.5 31 9 (29.0) 16 (51.6) 6 (19.4) 0.005
18.5–24.9 616 126 (20.5) 371 (60.2) 119 (19.3)
25–29.9 113 30 (26.5) 59 (52.2) 24 (21.2)
30.0–34.9 15 9 (60.0) 6 (40.0) 0
35.0,9 5 (55.6) 4 (44.4) 0
Frequency of PA
Never 38 8 (21.1) 27 (71.1) 3 (7.9) 0.668
,1 per week 200 48 (24.0) 114 (57.0) 38 (19.0)
1 per week 216 46 (21.3) 126 (58.3) 44 (20.4)
2–3 per week 255 62 (24.3) 142 (55.7) 51 (20.0)
Nearly every day 77 15 (19.5) 49 (63.6) 13 (16.9)
Intensity of PA
Take it easy 222 63 (28.4) 125 (56.3) 34 (15.3) 0.013
Lose breath 361 68 (18.8) 224 (62.0) 69 (19.1)
To exhaustion 30 4 (13.3) 16 (53.3) 10 (33.3)
Duration of PA
,15 min 67 13 (19.4) 46 (68.7) 8 (11.9) 0.151
15–30 min 187 47 (25.1) 101 (54.0) 39 (20.9)
30–60 min 283 66 (23.3) 169 (59.7) 48 (17.0)
.60 min 97 15 (15.5) 58 (59.8) 24 (24.7)
PA index
Low 131 35 (26.7) 80 (61.1) 16 (12.2) 0.256
Moderate 204 44 (21.6) 121 (59.3) 39 (19.1)
High 276 56 (20.3) 163 (59.1) 57 (20.7)
Physically tired from work
Never 120 30 (25.0) 75 (62.5) 15 (12.5) 0.459
Seldom 242 59 (24.4) 138 (57.0) 45 (18.6)
Often 227 50 (22.0) 130 (57.3) 47 (20.7)
Almost always 47 9 (19.1) 32 (68.1) 6 (12.8)
Smoking
Never 411 102 (24.8) 220 (53.5) 89 (21.7) 0.030
Former 108 21 (19.4) 64 (59.3) 23 (21.3)
Current 264 55 (20.8) 172 (65.2) 37 (14.0)
Alcohol consumption prev. 14 days
Never 334 93 (27.8) 183 (54.8) 58 (17.4) 0.044
1–4 times 422 84 (19.9) 252 (59.7) 86 (20.4)
5–10 times 15 1 (6.7) 13 (86.7) 1 (6.7)
.10 times 10 1 (10.0) 7 (70.0) 2 (20.0)
Marital status
Unmarried 717 162 (22.6) 417 (58.2) 138 (19.2) 0.500
Married 40 12 (30.0) 21 (52.5) 7 (17.5)
Continued
Physical activity and fertility 3201
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possible detrimental effects of high intensity exercise are reversible
and not permanent. Unfortunately, our data did not allow further con-
sideration of this matter.
There have only been a few studies regarding the effect of PA on fer-
tility status and parity in the general female population. Our results are
somewhat comparable to results of a retrospective case–control study
which found a 6.2-fold increased risk of infertility in women who exer-
cised vigorously (defined as aerobic activities with estimated energy
requirements of 6 kcal/min) for at least 60 min per day (Green et al.,
1986). There are also reports of lutheal phase alterations, which may
lead to infertility, among recreational runners with at least 2 h per
week of exercise and running 32 km/week (De Souza et al., 2003).
The recreational runners in the De Souze study had lower BMI and
fat mass than sedentary controls and the results were related to short-
term negative energy balance and hypometabolic state, similar to but
not as extensive as seen in amenorrheaic athletes.
Results from the Nurse’s Health Study indicate reduced risk of ovu-
latory infertility in women doing vigorous exercise for at least 30 min
daily (Chavarro et al., 2007). An earlier report of the same cohort indi-
cated a 7% relative risk reduction for ovulatory infertility for each
additional hour of vigorous exercise per week (Rich-Edwards et al.,
2002). Thus, there is a considerable divergence in study results. The
mean age in our study group was approximately 5 years lower than
in the women in the Nurse’s Health Study and this may explain the
difference in results to some extent, as we found younger women
more likely to report both highest intensity of PA and infertility than
older ones.
PA can improve body composition, glucose homeostasis and insulin
sensitivity (Warburton et al., 2006). Exercise-induced weight loss has
been shown to improve metabolic function and hormonal profiles, and
often leads to significant increase in fertility (Clark et al., 1995;
Norman et al., 2004). In our study, adjustment for BMI did not signifi-
cantly alter the increased risk of infertility associated with the highest
intensity or frequency of activity. Thus, the effect of PA may largely act
through a mechanism that does not involve BMI to a significant extent.
It is possible that in normal weight women, high loads of exercise,
not coupled with increased energy intake, lead to negative energy
balance where the energy requirements of reproductive functions
cannot be met (Loucks et al., 1998). This may explain our finding of
increased infertility risk among women doing high intensity training
or very frequent exercise sessions.
Our study is population based, not depending on cases seeking help
from a clinic, and can be viewed as a cohort study. The prospective
assessment of the effect of baseline PA on subsequent fertility problems
hopefully contributes to avoiding selection bias of cases and reporting
bias of activity levels. However, there were possible limitations. We
did not try to identify different causes of infertility with biological
testing but focused on the overall occurrence in the population and
this may have biased our results. Green et al. (1986) found that
among infertile women who had never conceived, high intensity exer-
cise for more than 60 min/day was associated with even higher risk
of infertility after excluding cases with evidence of tubal dysfunction.
Differences in measurement methods for infertility may contribute to
differences in results, to some extent. Also, not all women who partici-
pated in the baseline survey did so in the follow-up survey. If non-
participation at follow-up was jointly associated with PA and infertility,
bias may have resulted. Many women did not answer questions regard-
ing fertility status and we cannot exclude the possibility that those
women differed from women who did answer; this could have affected
our results. Our analysis found, however, that women who did not
answer questions regarding fertility status in the follow-up study had
somewhat lower intensity and duration of PA at baseline than women
who did answer those questions, although this difference was not stat-
istically significant. Because data on fertility status were collected retro-
spectively, recall bias may have occurred. Nevertheless, since fertility
status is of high personal interest, precise recollection of its aspects
may be likely. Other sources of bias may have been spousal infertility
and change of partner, which we could not control for in our data.
PA may affect fertility merely temporary or more permanently in
the reproductive life, but our study did not obtain information at
the time when women tried to conceive. Although we excluded
women who reported infertility at baseline we cannot be certain
whether the level of PA reported at baseline was maintained until
trying to conceive.
In epidemiological studies, the intensity of PA can be assessed as
absolute or relative intensity. Metabolic equivalent task is frequently
used to refer to absolute intensity indicating the energy cost of an
activity. PA-related energy expenditure has been associated with mor-
bidity and mortality (Helmrich et al., 1994; Manini et al., 2006; Mora
et al., 2007). Besides being an important determinant of health, data
on energy expenditure also facilitate study result comparisons and
interpretation of findings into meaningful units, although misreporting
errors have been observed (Mahabir et al., 2006). Relative intensity
can be described by use of the Borg scale (Borg, 1982) or other
measures of how intense the exercise is perceived by each subject.
In the current study, information regarding PA was based on a self-
reported questionnaire that allowed for subjective interpretation of
PA variables. It may therefore suffer from misclassification of activity
by factors such as age, social situations and seasonal variation
(Vanhees et al., 2005). Including a large number of study subjects
and classifying subjects into wide categories, e.g. low, moderate,
high score on activity can compensate for the effects of
.............................................................................................................................................................................................
Table III Continued
No childbirth, 179 (22.8) 1–2 children, 458 (58.3) 3 or more children, 149 (19.0) P-value
Education
,10 years 82 36 (43.9) 39 (47.6) 7 (8.5) 0.000
10–12 years 555 102 (18.4) 341 (61.4) 112 (20.2)
.12 years 140 37 (26.4) 76 (54.3) 27 (19.3)
PA, physical activity. Childbirths during follow-up reported in questionnaire. P-values indicate results of the Pearson’s chi-square test. n(%).
3202 Gudmundsdottir et al.
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misclassification (Shephard, 2003). The questions regarding intensity
and duration of PA in the current study have previously been validated
in a small sample of women and men over a wide age range (Wisloff
et al., 2006). The results indicate a positive association between
reported intensity and the measures of oxygen uptake during exercise.
Taking it easy corresponded to an intensity of approximately 55% of
the maximal oxygen uptake, independent of activity duration up to
90 min. Intensity descriptions of loosing breath and exercising to the
level of exhaustion corresponded to 71–75 and 76 90%, respect-
ively, of the maximum oxygen uptake. Relative intensity decreased
when duration of exercise was increased. A study of reliability and val-
idity of the questions including only men found good reliability and
kappa statistics of 0.69– 0.82 between test and retest (Kurtze et al.,
2008), although these results are not necessarily valid for women. It
seems likely that any measurement error in the assessment of PA
should not depend on fertility status and would tend to bias results
toward the null. In our study, there were many missing responses
on both PA and fertility. For instance, our PA index could not be cal-
culated for just over 1000 women in our study sample. In summary,
we found that women who were active on most days of the week
had a threefold risk of infertility compared with inactive women.
The increased risk of infertility was only found for the most extreme
intensity and frequency of PA, perhaps representing women who
exercised at levels comparable to elite athletes. While we did not
find any associations between lower levels of activity and fertility
status or parity, other studies have found regular moderate PA to
improve reproductive function. It could therefore be suggested that
moderate PA has little or perhaps even a positive direct effect on fer-
tility. This should undoubtedly be confirmed, as it may possibly affect
fertility by other means than biological, for example via positive effects
on self-esteem and improved mental health. Psychosocial interven-
tions, particularly those emphasizing skills training, such as relaxation
training, have been found effective in infertility treatment (Boivin
2003) and the positive psychological effects of regular PA on mental
well-being have been reported in numerous studies (Scully et al.,
1998; Kull 2002). Results on the association between high levels of
PA and fertility status are conflicting. We found increased risk of infer-
tility in women who reported doing PA almost every day and in those
reporting exercising to the level of exhaustion. Although it cannot be
concluded from this study, it seems likely that fertility may be positively
affected by PA up to a certain level after which the energy require-
ments of the activity outweigh the positive effects, resulting in inferti-
lity. It is also possible that this threshold level applies merely at an
individual level, perhaps in combination with energy availability, and
cannot be identified at the population level.
The potential role of regular PA in the prevention and treatment of
infertility needs further investigation. However, awareness of the poss-
ible risks of infertility should be highlighted among non-athletic women
who exercise vigorously.
Funding
The faculty of Social Sciences and Technology Management, The
Norwegian University of Science and Technology (NTNU) supported
this study by a Doctoral Research Fellowship. The HUNT Study is a
collaboration between HUNT Research Centre (Faculty of Medicine,
Norwegian University of Science and Technology NTNU), Nord-
Trøndelag County Council and The Norwegian Institute of Public
Health.
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September 1, 2009
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... Some randomized controlled trials have reported a therapeutic effect of PA on infertility that acts through systemic effects such as increased immune function, insulin resistance, and circulating sex hormones [20]. However, in contrast to the well-known beneficial effects of regular PA on many adverse health outcomes (including prevention of premature death), the effect of PA on fertility in the general population is unclear [21]. ...
... In one study the authors examined male and female samples separately and analyzed the risk of infertility in PA for men and women [23]. We then ultimately included in the present work 10 studies that yielded 12 different relative risk estimates [3,21,[23][24][25][26][31][32][33][34] (Fig. 1). Table 1 shows the principal characteristics of the six cohort studies [3,21,24,26,31,32] and four case-control studies [23,25,33,34] of PA and infertility in our metaanalysis. ...
... We then ultimately included in the present work 10 studies that yielded 12 different relative risk estimates [3,21,[23][24][25][26][31][32][33][34] (Fig. 1). Table 1 shows the principal characteristics of the six cohort studies [3,21,24,26,31,32] and four case-control studies [23,25,33,34] of PA and infertility in our metaanalysis. The studies were conducted in eight countries: two in China [3,31], two in the UK [32,33], and the remaining six in the USA [34], Iran [24], Norway [21], Estonia [26], the Palestinian Territories [25], and France [23]. ...
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Background Physical activity (PA) may protect against infertility by modulating the hypothalamic-pituitary–gonadal axis, thereby reducing gonadotropin levels, elevating immune function, and inhibiting inflammation and circulating sex hormones. However, whether PA reduces the risk of infertility remains largely unknown. We therefore conducted a systematic review and meta-analysis to determine the preventive effects of PA on infertility. Methods We searched PubMed, Cochrane Library, EMBASE, and CINAHL databases to retrieve published epidemiologic studies on the relationship between PA and infertility. Following the PRISMA guidelines, we selected English literature publishedprior to 11 April 2022, and assessed study quality using the Newcastle–Ottawa Scale. Our protocol, including the full methods employed for this review, is available on PROSPERO (ID = CRD42020143344). Results Six cohort studies and four case–control studies based on 708,965 subjects and 12,580 cases were eventually screened and retained. High levels of PA were shown to reduced risk of infertility relative to low levels (cumulative relative risk [RR] = 0.59, with a 95% confidence interval CI 0.49–0.71), and we reported results for cohort studies (RR = 0.63, 95% CI 0.50–0.79) and case–control studies (RR = 0.49, 95% CI 0.35–0.67). Our findings were comparable for men (RR = 0.65, 95% CI 0.41–1.04) and women (RR = 0.56, 95% CI 0.47–0.66). The meta-analysis of six risk estimates from five studies of low, moderate, and high PA levels showed that moderate PA may also reduce the risk of infertility compared with low PA (RR = 0.54, 95% CI 0.38–0.77). However, high PA also appeared to slightly augment the risk of infertility compared with moderate PA (RR = 1.31, 95% CI 1.08–1.59). Conclusions This present systematic review comprehensively reflected an inverse relationship between different levels of PA and infertility, and our meta-analysis showed that a moderate-to-high PA level significantly reduced the overall risk of infertility, and that this level of PA activity was a common protective factor. In addition, limited evidence suggested that compliance with international PA guidelines would greatly lower the risk of infertility (RR = 0.58, 95% CI 0.45–0.74; I ² = 0.0%). Future studies, however, need to be executed to further determine the frequency, optimal dosage, and duration required to effectively attenuate the risk of infertility.
... Fertility, as with other health variables, exhibits an inverted "U" relationship with exercise, indicating there is a certain range that should be minimally met to see a response but there is a limit to when there are diminished returns from the exercise (Clark et al., 1998;Gudmundsdottir et al., 2009;Foucaut et al., 2019;McLean & Wellons, 2012). If a female exercises to an excessive amount, there may be decrements in fertility status depending upon the BMI and current health status of the female. ...
... Similarly, Hakimi et al. (2017) found an increased risk for ovulation problems when a female took part in seven hours or more per week of aerobic exercise while Gaskins et al. (2016) found that strenuous aerobic exercise for four hours or more per week may reduce IVF success. Lastly, Gudmundsdottir et al. (2009) found that there was an increased risk of infertility in women with the highest levels of intensity and frequency of an unspecified mode of physical activity as compared to those with a lower intensity and/or frequency. These studies show that while a lack of exercise increases risk for infertility, there is a threshold volume/intensity of aerobic exercise that will also increase the risk for infertility. ...
... limited, but results have demonstrated an upper limit. Surpassing this upper limit may result in a decreased fertility status (Gudmundsdottir et al., 2009;Hakimi et al., 2016;Wise et al., 2012) Meaning, exercise has a more parabolic, or "inverted-u" relationship with female fertility. Wise et al. (2012) found this relationship to follow suit in an observational study where vigorous exercise for greater than or equal to 5 hours per week caused an increased time to pregnancy (TTP) except in overweight and obese women. ...
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... They emphasised that literature on physical activity and markers of spermatogenesis among athletes may overstate the potential harms of physical activity on testicular function and may not be generalisable to the population at large. In an earlier study on physical activity and fertility in women, Gudmundsdottir et al. (2009) found that women with the highest levels of frequency or intensity of physical activity had an increased risk of infertility. ...
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Introduction: Preconception care practices include physical activity, which is identified as an important indicator of behavioural preconception health. A scoping review was conducted to examine the association between physical activity in preconception health and its long-term effects on the later life of the offspring. Methods: The literature was searched in databases CINAHL, ScienceDirect and PubMed, using keywords determined by the study objective. In total, 755 published manuscripts were identified. Two additional manuscripts were identified through manual searching. A total of 17 manuscripts was selected for the final analysis. The data were extracted and summarized using thematic analysis. Results: The selected studies were summarized in two categories: (1) studies associated with physical activity and preconception health behaviour (n = 8), and (2) studies associated with preconception physical activity, fertility, and pregnancy outcomes (n = 9). Conclusions: Despite limited evidence, other indirect scientific evidence shows that physical activity positively affects health, and is therefore strongly recommended during the preconception period. Policymakers, researchers, and healthcare professionals should join efforts in examining the impact of physical activity on preconception health, fertility and birth outcomes, and effectively translate the findings into preconception health guidelines and public policies.
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... The female athlete triad involves being underweight (often associated with an eating disorder), having a low calorie intake, and engaging in excessive physical activity (Gudmundsdottir et al., 2009). The latter is widespread in professional female athletes combined with being underweight (Nazem and Ackermann, 2012;Weiss and Hecht, 2016 (Hoffman et al., 2011;Howard, 2018). ...
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Metabolic risk factors such as obesity are considered major obstacles to female fertility. Chronic infertility imposes psychological and social burdens on women because infertility violates societal gender roles. Although the prevalence of obesity among women is expected to increase in the future, the relevance of metabolic status for fertility is still underestimated. However, the assessment of metabolic risk factors is highly relevant for understanding fertility disorders and improving infertility treatment. This narrative review discusses the associations of metabolic risk factors (e.g. obesity, female athlete triad, oxidative stress) with significant infertility. An electronic search was conducted for studies published between 2006 and 2020 in Cumulative Index to Nursing and Allied Health Literature, ScienceDirect, PubMed, Scopus, Google Scholar and related databases. In total, this search identified 19,309 results for polycystic ovary syndrome, 28,969 results for endometriosis, and only 1611 results for idiopathic and/or unknown infertility. For the present narrative review, 50 relevant studies were included: 19 studies were on obesity, 24 studies investigated the female athlete triad, and seven studies addressed other risk factors, including reactive oxygen species. This narrative review confirms the direct impact of obesity on female infertility, while the effect of other risk factors needs to be confirmed by large-scale population studies.
... Gudmundsdottir et al. found that women who are active on most days, tended to experience fertility problems 3.2 times more often. In this study exercising to exhaustion also led to 2.3 times more fertility impairments than low intensity PA [90]. Based on the data by Morris et al. on lifetime exercise (level of evidence: II-2), exercising 4 h or more per week indicate 40% less likelihood of having a live birth (OR 0.6, CI 0.4-0.8), it is 3 times more likely to lead to cycle cancellation and 2 times more likely to lead to implantation failure or pregnancy loss (OR 2.8, CI 1.5-5.3; ...
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Chapter
The present chapter deals with the effect of exercise and nutrition intervention for female fertility. It addresses the evidence-based recommendations on exercise training and a physically active lifestyle approach to improving health and fertility. Furthermore, it addresses the critically important issue of the role of sound nutrition practices with regards to macro and micronutrients intake considered important for optimal fertility. While not a primary focus, elements of these points relative to pregnancy are briefly addressed. Other common aspects of daily life, like the exposure to endocrine disruptors, substances that interfere with the proper functioning of the hormonal system, and therefore may alter human reproductive potential, are also addressed.
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