It is well recognized that various lifestyle-related factors,
such as obesity, smoking, other substance abuse and
heavy alcohol consumption, have a negative impact on
both male and female fertility, and the success of assisted
reproductive technology (ART) (
Obesity is associated not only with female infertility (
The above-mentioned literature therefore suggests
that infertile people can take non-medical actions, such
as maintaining healthy body weight and lifestyle habits
to improve their chance of conception, spontaneously or
following ART. However, studies have shown that many
women undergoing fertility treatments tend to make poor
lifestyle choices that may affect their chance of conception.
A significant proportion of these women continue to
drink caffeine and alcohol (
In this pilot study, we evaluated the feasibility of conducting a larger prospective cohort study that will aim at determining the independent contribution of male and female lifestyle-related factors to ART success. The study also examined whether couples seeking fertility treatments present unfavorable lifestyle-related factors that may interfere with their reproductive health and evaluated possible differences in these factors between men and women.
Heterosexual couples seeking fertility treatments for the first time and being able to understand, speak and write French were eligible to participate in this prospective pilot study. Recruitment took place at the fertility clinic of the Centre hospitalier affilié universitaire régional (CHAUR) de Trois-Rivières (Qc, Canada) between May 2015 and February 2016. Men and women who agreed to participate in our study were assessed prior to the initiation of infertility treatments. The couples were followed- up for six months to assess ART success, defined as the confirmation of a clinical pregnancy. This project was approved by the Centre intégré universitaire de santé et de services sociaux de la Mauricie et Centre-du-Québec (CIUSSS MCQ) and the Université du Québec à Trois- Rivières Ethics Committes. Written informed consent was obtained from all couples participating in the study.
To assess the feasibility of a larger prospective cohort study, recruitment rates, compliance with the protocol (defined as fulfilling the questionnaires and wearing the accelerometer as requested), as well as retention rate and ART outcomes at six-month follow-up were evaluated.
Height was measured to the nearest millimetre using
a standardized cloth tape measure, and body weight was
measured to the nearest 0.1 kg on a calibrated balance
after removing shoes (UM016 2202, Tanita Corporation,
USA). Body mass index (BMI) was then calculated in
kilograms per meter squared (kg/m2). On the basis of international
BMI cut-off values for adults, the prevalence
of underweight (<18.5 kg/m2), normal weight (18.5-24.9
kg/m2), overweight (25.0-29.9 kg/m2) and obese (=30.0
kg/m2) were calculated. Waist circumference (WC) was
measured using a standardized cloth tape measure according
to standard procedures (
Each partner received an e-mail containing instructions
for completing online questionnaires assessing their eating
and sleeping habits. A web-based self-administered
food frequency questionnaire (web-FFQ), containing a
list of typical foods available in the province of Quebec,
was used to assess dietary intakes over the last month.
The test-retest method showed that this questionnaire has
good reliability (mean R=0.72, 95% confidence interval
0.68; 0.76) (
The pittsburgh sleep quality index (PSQI) was used to
assess sleep quality over a month. PSQI consists of 19
items, each weighted on a 0-3 interval scale, generating
seven “component” scores. The final score can vary from
a minimum of 0 (no sleeping difficulty) to a maximum of
21 (significant sleeping difficulty). A score ≤5 is associated
with good sleep quality, whereas a score >5 is associated
with poor sleep quality (
To objectively assess current physical activity levels
of the partners, we asked them to wear an accelerometer
over their hip on an elastic belt from wake-up time to bedtime,
for seven consecutive days. The participants were
asked to remove the accelerometer when sleeping, showering
or performing water activities. Furthermore, they
received a daily diary to document wear and non-wear
time periods. We used the triaxial ActiGraph GT3X accelerometers
(ActiGraph, Pensacola, FL). The ActiGraph
GT3X measures data in a 60-s epoch and has been widely
used in research for assessing physical activities in adults.
The accelerometer provides measures such as activity intensity
and duration, step counts, and energy expenditure
and has been shown to reasonably correlate with doubly
labeled water-derived, the gold standard to assess energy
A global “reproductive health score” was calculated by attributing 1 point per adverse factor related to women and men reproductive health (for women: age=35 years old, BMI =30 kg/m2, waist circumference =88 cm, consuming alcohol (=1 unit/week), HEI<50, <150 minutes of moderate to vigorous physical activity (MVPA) in bouts of =10 minutes, poor sleep quality (score>5); for men: age=45 years old, BMI=30 kg/m2, waist circumference =102 cm, consuming alcohol (=1 unit/week), HEI<50, <150 minutes of MVPA in bouts of =10 minutes, poor sleep quality (score>5).
Data on sociodemographic status, reproductive history, smoking and drug use, personal and family medical history, as well as causes of infertility, infertility treatments received and biochemical and clinical pregnancy were gathered from patients’ medical records.
Means and standard deviations, as well as percentages, were computed for men and women for socio-demographic and anthropometric characteristics. The normality assumption was tested using the Shapiro-Wilk test. Because several variables were not normally distributed and our sample size was small, we used the Wilcoxon-Mann-Whitney nonparametric test to compare lifestyle-related factors between men and women. For categorical variables, we used the Fisher's exact test. Statistical analyses were performed by using SPSS statistical software (version 23.0) and results were considered to be significant at P≤0.05).
Between May 2015 and February 2016, 130 eligible
couples were approached and asked whether they were
interested in participating in our pilot study. Thirty-two
couples agreed to participate (25% recruitment rate). Reasons
for not agreeing to participate were: not interested in
the study, lack of time or overwhelmed by medical exams
and treatments for infertility. Among the 32 couples, one
left the study before having completed the questionnaires
and worn the accelerometer. Three couples were excluded
from the analyses because of non-compliance with fulfilling
questionnaires by the man, leaving 28 couples for the
These 28 couples had missing data in the data set, especially for objective physical activity measures. Seven participants (12.5%) did not wear the accelerometer for at least four days of monitoring for 10 hours of wear time per day. Incomplete PSQI (n=5, 9%) was also another source of missing data. Seven couples (25%) did not start, or stopped, infertility treatments at six-month follow-up. Thirteen couples (13 out of 21, 62%) achieved a clinical pregnancy whereas 8 couples (8 out of 21, 38%) did not.
A description of the socio-demographic characteristics
of the 28 couples included in the analyses, is provided in
Socio-demographic characteristics of couples who underwent infertility treatments
|Variable||Women n=28||Men n=28|
|Age (Y)||32.0 ± 4.4||35.6 ± 8.4|
|Women≥35 years old||10 (36)||-|
|Men≥45 years old||-||5 (18)|
|No||22 (78)||19 (68)|
|Yes, with actual partner||3 (11)||2 (7)|
|Yes, with ex-partner||3 (11)||6 (21)|
|Yes, with actual and ex-partner||0 (0)||1 (4)|
|No-university degree||13 (46)||11 (39)|
|University degree||15 (54)||17 (61)|
|Cause of infertility|
|Female and male||4 (14.3)|
Data are presented as means ± SD (minimum-maximum) or n (%).
Anthropometric profile and lifestyle habits related
to reproductive health of the 28 couples (56 individuals)
are presented in
When considering the seven lifestyle-related factors associated
with reproductive health (age, BMI, WC, alcohol,
diet, physical activity and sleep) in men and women
for which all the data were available (n=44), we found
that 9% of men and 41% of women presented at least four
adverse factors (P=0.08), with a mean of 3.1 and 2.4 adverse
factors observed in women and men, respectively
Lifestyle-related factors associated with unfavorable reproductive health of couples about to undergo fertility treatments
|BMI (kg/m2)||25.7 ± 4.9||29.9 ± 5.5||26.6 ± 4.3||0.08|
|UW||2 (3.6)||2 (7.1)||0 (0)|
|NW||25 (44.6)||15 (53.6)||10 (35.7)||0.13|
|OW||20 (35.7)||6 (21.4)||14 (50)|
|OB||9 (16.1)||5 (17.9)||4 (14.3)|
|Abdominal obesitya||13 (23.2)||9 (32.2)||4 (14.3)||0.10|
|Yes||3 (5.4)||1 (3.6)||2 (7.1)||0.49|
|Yes||2 (3.6)||0 (0%)||2 (7.1)||0.15|
|Alcohol (unit/week)||6.1 ± 6.7||4.3 ± 3.7||7.9 ± 8.5||0.05|
|≥1 unit/week||47 (84)||23 (82.2)||24 (85.7)||0.57|
|Caffeine (mg/day)||153.8 ± 144.7||112.8 ± 88.0||194.8 ± 177.2||0.11|
|>200 mg/day*||-||6 (21.4)||-|
|Diet quality index||69.2 ± 11.8||72.0 ± 12.4||66.4 ± 10.8||0.10|
|Good diet||11 (19.6)||9 (32.1)||2 (7.1)||0.05|
|Diet needing improvement||41 (73.2)||18 (64.3)||23 (82.2)|
|Poor diet||4 (7.2)||1 (3.6)||3 (10.7)|
|Physical activity habits||n=49||n=25||n=24|
|Time spent at MVPA (minutes/day)||34.2 ± 38.8||24.3 ± 11.8||44.5 ± 52.8||0.05|
|Not achieving≥150 minutes of MVPA per week||16 (32.7)||10 (40)||6 (25)||0.36|
|Time spent at MVPA in bouts≥10 minutes (minutes/day)||13.5 ± 23.5||7.9 ± 6.3||19.3 ± 32.2||0.46|
|Not achieving ≥150 minutes of MVPA in bouts of ≥10 minutes||41 (83.7)||25 (100)||16 (66.7)||0.001|
|Time spent in sedentary activity (hours/day)||9.1 ± 1.7||9.2 ± 1.3||9.0 ±1.9||0.50|
|Sleeping score||5.2 ± 2.7||5.16 ± 3.2||5.23 ± 2.3||0.49|
|Overall poor sleep quality||18 (35.3)||7 (28)||11 (42.3)||0.38|
Data are presented as mean ± SD or n (%). P values indicate differences between women and men. BMI; Body mass index, MVPA; Moderate-to-vigorous intensity physical activity, OB; Obese, OW; Overweight, UW; Underweight, NW; Normal weight, a; Abdominal obesity was defined as: waist circumference>88 cm in women, >102 cm in men, and *; No recommendations regarding caffeine intake are available for men trying to conceive.
Overall number of adverse factors related to women and men reproductive health
|Overall n=44||Women n=22||Men n=22||P value|
|Number of factorsa|
|1||5 (11.4)||1 (4.5)||3 (13.6)|
|2||15 (34.1)||7 (31.8)||9 (41.0)|
|3||13 (29.5)||5 (22.7)||8 (36.4)|
|≥4||11 (25.0)||9 (41.0)||2 (9.0)|
BMI; Body mass index, MVPA; Moderate to vigorous intensity physical activity, HEI; Health eating index, a; Among the following factors: for women: age ≥35 years old, BMI ≥30 kg/m2, waist circumference>88 cm, consuming alcohol (≥1 unit/week), HEI<50, <150 minutes/week of MVPA in bouts of ≥10 minutes, poor sleep quality (score>5). For men: age ≥45 years old, BMI ≥30 kg/m2, waist circumference >102 cm, consuming alcohol (≥1 unit/week), HEI<50, <150 minutes/week of MVPA in bouts of ≥10 minutes, poor sleep quality (score>5), and b; The global score was calculated by attributing 1 point per adverse factor related to women and men reproductive health.
Flow diagram of recruitment, compliance with the protocol and retention of the study population.
This pilot study demonstrated the feasibility of conducting a large prospective cohort study at the fertility clinic of the CHAUR of Trois-Rivières but also highlighted the need for improvement of several aspects of the protocol. First, recruitment rate was 25%. It is not possible to compare our recruitment rate with other similar studies because studies evaluating lifestyle-related factors in both partners, using detailed questionnaires and accelerometers, are inexistent. Nevertheless, recruitment was challenging and different explanations may be given. Men and women were recruited at the same time. Several men declined to participate in our study, which prevented us to recruit the couple. Working in close relationship with the medical team and delivering persuasive message to raise men interest in our study, will be essential to improve recruitment rate. In addition, the couple received a large amount of complex information about the medications, tests and procedures involved in infertility treatments on the day we invited them to participate in our study. They may have been overwhelmed and less inclined to participate in our study. Therefore, a better moment to approach the couples should be considered. Finally, the accelerometer to wear during seven days may have discouraged some couples to participate in our study.
Second, missing data were apparent in the data set in terms of sleeping and physical activity data. It will be essential to emphasize the importance of following the instructions provided in the questionnaires on how to respond to questions as well as wearing the accelerometer for at least 10 hours per day for four days in order to avoid missing data. Finally, at six-month follow-up, seven couples (25%) did not start, or stopped, infertility treatments for medical or personal reasons. This attrition rate will have to be taken into account when designing our larger prospective cohort study.
Our preliminary results also showed that many couples
seeking infertility treatments present unfavourable lifestyle-
related factors that may explain, at least partially, their difficulty
in conceiving and affect future infertility treatment
outcomes. Importantly, 41% of women and 9% of men presented
at least four adverse factors that may have a negative
impact on reproductive health. More specifically, 18% of
women and 14% of men were obese, proportions similar
to those reported by previous studies conducted in infertile
Obesity is a well-known risk factor for female infertility,
as it is related to ovulation and hormonal disorders (
Despite the recommendation that people trying to conceive
should not drink alcohol (
Finally, other lifestyle habits, such as nutrition, physical
activity and sleeping habits may have a negative impact
on fertility and ART outcome, but the currently available
evidence is inconclusive. Ruder et al. (
Physical activity has been associated with improved
ART outcome. Evenson et al. (
Finally, sleeping habits is increasingly recognized as
an important factor of human health and well-being (
While our data are interesting and appear to be feasible to collect, they should be considered preliminary and descriptive. The small sample size should be acknowledged, yet the primary objective of this pilot study was to evaluate the feasibility of a prospective cohort study. Consequently, we did not have the power to detect differences in lifestyle-related factors associated with reproductive health between men and women. Similarly, we did not have the power to compare baseline lifestyle-related factors between couples who achieved a clinical pregnancy and those who did not. Another limitation of our study is that the population was homogenous with respect to race/ ethnicity and educational level, with the majority of recruited couples being highly educated.
We do not know whether lifestyle-related factors of the couples who agreed to participate were any different from those who did not agree to participate. The detailed questionnaires about eating and sleeping habits, as well as the accelerometer to wear during seven days, may have attracted more motivated and healthier couples. But, still, we observed a high proportion of unhealthy anthropometric profile and lifestyle habits despite having well- educated participants. These different factors suggest that a recruitment bias is likely to be present in our larger prospective cohort study, limiting the generalizability of our results to a wider population of infertile couples. Finally, although accelerometers provide a valid and objective measure of physical activity levels, non-waterproof accelerometers underestimate several type of physical activity, such as water activities. It is therefore possible that we underestimated the level of physical activity for some participants who removed the accelerometer to do water activities but the underestimation would be minimal. Only 6 participants (11%) of our subjects reported doing water activities; however, data were considered invalid for three of them because the accelerometer was worn for less than 10 hours. The three other participants reported only one hour of water activities during the wearing period.
The literature shows that a number of lifestyle-related factors have unfavourable effects on reproductive success of infertile men and women; however, further prospective cohort studies assessing both partners’ lifestyle-related factors, especially nutrition, physical activity and sleeping habits, will be needed to fully understand the independent contribution of male and female factors to ART success. Such large prospective cohort studies are essential to develop targeted recommendations to help infertile couples to conceive a child and this pilot study will help us to design such a prospective cohort study.
Though this pilot study had limitations, it provides us with key information that will help us to design a large prospective cohort study. Especially, improvement of recruitment strategies and directives to increase the compliance with the protocol will be essential to ensure its success. It also shows that a considerable proportion of men and women seeking infertility treatments present with several unfavourable lifestyle-related factors that may interfere not only with their fertility but also with future infertility treatment outcome. Conducting a large prospective cohort study will allow us to identify the independent contribution of male and female lifestyle-related factors to ART success. Such a study is essential to help designing interventions aimed at helping infertile couple to conceive a child.