Abstract
STUDY QUESTION
Is couples’ body compositions associated with reduced fecundity as measured by a longer time-to-pregnancy (TTP)?
SUMMARY ANSWER
Couples whose BMI are within obese class II (≥35 kg/m2) have a longer TTP in comparison to leaner (BMI < 25 kg/m2) couples, observed only when both partner's BMI was jointly modeled.
WHAT IS KNOWN ALREADY
Extremes of BMI have been associated with a longer TTP and with less successful assisted reproductive technology (ART) outcomes. To our knowledge, the association between measured adiposity in both partners of the couple and prospectively measured TTP has not been investigated despite pregnancy being a couple-dependent outcome.
STUDY DESIGN, SIZE, DURATION
Prospective cohort with preconception recruitment of 501 couples trying for pregnancy and recruited from 16 counties in Michigan and Texas between 2005 and 2009. Couples were followed daily for up to a year of trying or until a hCG pregnancy.
PARTICIPANTS/MATERIALS, SETTING, METHODS
In-home standardized anthropometric assessment of couples upon enrollment included measured height and weight using calibrated stadiometers and scales, and measured waist and hip circumferences. Discrete-time Cox regression was used to estimate fecundability odds ratios (FORs) and 95% CIs, controlling for potential confounders including age, number of days of vigorous physical activity, serum cotinine concentration, race, education, free cholesterol levels for each partner in partner-specific models and for both partners in couple-based models as well as average acts of intercourse per menstrual cycle and menstrual cycle regularity.
MAIN RESULTS AND THE ROLE OF CHANCE
Neither male nor female partner's BMI was associated with TTP when modeled individually. However, obese class II (BMIs ≥ 35.0 kg/m2) couples experienced a reduction in fecundability in both unadjusted (FOR = 0.45; 95% CI: 0.23, 0.89) and adjusted analyses (aFOR = 0.41; 95% CI: 0.17, 0.98) resulting in a longer TTP in comparison to couples with normal BMI (<25 kg/m2). Female partners’ waist circumference ≥88.6 cm was associated with a significant reduction in fecundability in the unadjusted model (FOR = 0.64; 95% CI: 0.48, 0.86) but not in the adjusted model (aFOR = 0.77; 95% CI: 0.55, 1.08) in comparison to females with a smaller (<80 cm) circumference.
LIMITATIONS, REASONS FOR CAUTION
BMI and waist circumference are proxy measures of body composition and residual confounding cannot be eliminated. Findings may not be generalizable to clinical populations.
WIDER IMPLICATIONS OF THE FINDINGS
This is the first cohort study known to us with preconception enrollment of couples who underwent standardized anthropometric assessment and for whom TTP was prospectively measured. The findings underscore the importance of considering both partners’ body composition for fecundity outcomes and preconception guidance.
STUDY FUNDING/COMPETING INTEREST(S)
Supported by the Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (Contracts #N01-HD-3–3355, N01-HD-3–3356 and N01-HD-3–3358). The authors have no competing interests.
TRIAL REGISTRATION NUMBER
N/A.
Keywords: fertility, obesity, body mass index, prospective study, central adiposity
Introduction
Female obesity, as measured by BMI, has been associated with reduced fecundability in several epidemiologic studies (Zaadstra et al., 1993; Jensen et al., 1999; Bolúmar et al., 2000; Hassan and Killick, 2004; Law et al., 2007; Ramlau-Hansen et al., 2007; Wise et al., 2010; McKinnon et al., 2016). Previous investigators also have assessed increased central adiposity (waist-to-hip ratio [WHR] and waist circumference) and fecundability with equivocal results reported (Zaadstra et al., 1993; Wass et al., 1997; Wise et al., 2010; McKinnon et al., 2016). The primary focus of these studies has typically been on the association between female adiposity measures and fecundability, and often relying on self-reported BMI and/or retrospectively reported time-to-pregnancy (TTP). While male BMI has been inversely associated with semen quality (Jensen et al., 2004; Chavarro et al., 2010; Eisenberg et al., 2014) and infertility (Sallmén et al., 2006; Nguyen et al., 2007; Ramlau-Hansen et al., 2007), we are unaware of research where couples’ body compositions inclusive of BMI, waist circumference, waist-to-height ratio (WHtR) and WHR were measured along with prospectively ascertained TTP. Such findings are important given that TTP is a couple-dependent outcome.
Though a few past studies have recognized the importance of studying couples, they have been limited in important ways. In particular, a previous study evaluated the role of male and female obesity on sub-fecundity (TTP > 12 months) and found a higher odds of subfertility when both partners were obese (Ramlau-Hansen et al., 2007). However, this earlier study relied upon self-reported BMI and retrospectively recalled TTP among pregnant women. Among couples undergoing fertility treatment with measured BMI, couple obesity has been associated with poorer outcomes including decreased blastocyst development (Bakos et al., 2011), fewer normally fertilized oocytes (Shah et al., 2011), and decreased likelihood of a clinical pregnancy (Keltz et al., 2010; Bakos et al., 2011; Shah et al., 2011) or live birth (Bakos et al., 2011; Shah et al., 2011; Colaci et al., 2012; Petersen et al., 2013). Still, some authors report no associations (Schliep et al., 2015).
In light of the continuing obesity epidemic in the USA (Ogden et al., 2014) and elsewhere (Berghöfer et al., 2008) and increasing recognition of the importance of male partners for couple fecundity, we sought to evaluate the association between couples’ BMIs and central adiposity in relation to prospectively assessed fecundity, as measured by TTP. This couple-based approach is in keeping with preconception guidance being directed to both partners of the couple (Johnson et al., 2006).
Materials and Methods
Study population
The study population comprises 501 couples who were recruited from 16 counties in Michigan and Texas upon discontinuing contraception given their intentions of trying for pregnancy and enrolled in the Longitudinal Investigation of Fertility and the Environment (LIFE) Study (Louis et al., 2011). By design, enrollment criteria were minimal: (i) females aged 18–40 years with male partner age 18+ years; (ii) married or in a committed relationship; (iii) self-reported menstrual cycle length between 21 and 42 days as required by the fertility monitor; (iv) ability to communicate in English or Spanish; (v) no use of injectable hormonal contraception in the prior 12 months. Couples with a physician diagnosis of infertility were ineligible for participation as were couples off contraception for >2 months. Couples were followed for up to 12 months of trying for pregnancy, with monthly hCG pregnancy tests at the time of expected menses.
Ethical approval
Institutional review board approvals were obtained from all collaborating institutions; couples gave written informed consent prior to study participation and any data collection.
Data collection and operational definitions
The research team met with eligible couples largely in their homes for enrollment and initial data collection purposes. Female partners completed a home pregnancy test to ensure they were not already pregnant at enrollment. Research assistants conducted baseline interviews with each partner of the couple regarding their medical and reproductive history and smoking and alcohol consumption during the past 12 months. Physical activity for both men and women was ascertained at baseline based on their responses to a two-part question asking about whether they followed a regular vigorous exercise program, and if yes, for how many days. Couples completed daily journals on intercourse and women recorded menses and pregnancy test results while trying for pregnancy. Women were instructed in the use of the Clearblue® Easy fertility monitors, SPD Development Co., Switzerland consistent with the manufacturer's guidance commencing on Day 6 of their cycle to help time intercourse to ovulation. The monitor tracks levels of estrone-3-glucoronide (E3G) and LH and gives a visual prompt of low, high and peak fertility. Women were also instructed to use the digital Clearblue® Easy home pregnancy test, SPD Development Co., Switzerland on the day of expected menses and a week later. The fertility monitor has been shown to be highly accurate in detecting the LH surge (99%) and in predicting peak fertility (91%) compared with gold standard ultrasonography (Behre et al., 2000). The Clearblue® Digital home pregnancy test is capable of detecting pregnancy with 99% accuracy (false positive results range from 0 to 0.3%, depending on the pregnancy test lot) when used from the day of expected menses (Tomlinson et al., 2008).
Trained research nurses performed a standardized anthropometric assessment at baseline as proxies of couples’ body composition (Lohman et al., 1988). Anthropometric measurements included height using a portable stadiometer, body weight using calibrated electronic scales and circumferences (waist, hip). Specifically, all study participants were asked to remove shoes, stand erect with their back to the wall and shoulders relaxed at the sides and looking straight ahead for measurement of height. The nurse took two measurements rounded to the nearest ½ inch and a third if the difference was more than ½ inch. The final value for each of the anthropometric measures was based on the average of the two closest measurements. All participants were weighed using the digital self-calibrating Health-O-Meter scale after removing shoes and excessive clothing. The nurse was instructed to take two measurements and record weight to the nearest pound. If the measurements differed by more than one pound, a third measurement was taken. The final weight used was the average of the two closest measurements. Self-reported weights were used for participants with weights in excess of 330 pounds, the upper limit for the accuracy of the weight scale. Waist circumference was taken at the natural waist location (i.e. the narrowest part of the torso) using a standardized cloth tape measure that was placed over the skin or light clothing while the participant was standing. The placement of the tape measure was made with the nurse standing to the right of the participant and after locating the lowest rib on the right side of the iliac crest. With minimal respiration, the participant held the tape measure in place while the nurse ensured the tape measure was in a plane parallel to the floor and was snug without compressing the skin. Two measurements were taken, with a third measurement taken if the difference was ¼ inch or more. Hip circumference was taken at the level of maximum extension of the buttocks.
BMI (kg/m2) was calculated from measured height (converted to centimeters) and weight (converted to kilograms) and categorized as: normal or underweight (<25.0), overweight (25.0–29.9), obese class I (30.0–34.9) and obese class II (≥35) for analysis. In addition to waist circumference, other central adiposity measurements were taken, including WHR for women and WHtR for both men and women. Measures of central adiposity were categorized further using existing cut points for waist circumference (cm) (males: <94, 94 to <101.6, ≥101.6; women: <80, 80 to <88.6, ≥88.6), WHtR (men: ≥0.5; women: ≥0.5) and WHR for women (≥0.80) (Lean et al., 1995; Ashwell and Hsieh, 2005; Consultation, 2011).
Couple fecundity was measured by the number of prospectively observed menstrual cycles required for a couple to become pregnant, conditional on not being pregnant in the previous cycle, i.e. TTP. A menstrual cycle was considered as the first day of bleeding in one cycle to the first day in the next cycle using data prospectively obtained from the fertility monitor and daily journal, both of which tracked menses. Pregnancy was defined as a positive home hCG pregnancy test.
Statistical analysis
Descriptive characteristics of the study population were calculated and compared for both the partners. The Cox model for discrete-time survival analysis was used to estimate the association between various anthropometric proxies of body composition (BMI, waist circumference, WHtR and WHR among females only) and TTP while adjusting for relevant covariates. Specifically, we calculated fecundability odds ratios (FOR) and 95% CIs for each body composition proxy. FORs <1.0 denote decreased fecundability as measured by a longer TTP, while FORs >1.0 reflect enhanced fecundability or a shorter TTP. Couples who withdrew from the study before pregnancy or who were not pregnant after 12 months of trying were censored at the last observed cycle for all analyses. The analyses accounted for left truncation for the time couples were off contraception prior to enrollment. We analyzed anthropometric measurements separately for each partner in individual-based models, as well as together in a couple-based model, and adjusting for a priori selected covariates based on the literature. In the individual-based models, these covariates included: age (in years), number of days of vigorous physical activity per week, active smoking status (serum cotinine concentration ≥10 versus <10 ng/ml [Benowitz et al., 2009]) and free cholesterol levels (log-transformed), as a proxy or global marker for lifestyle and diet (Schisterman et al., 2014). Given the uncertainty about model specification for fecundability-related endpoints in the absence of strong empirical data, we ran additional models adjusting for other potential confounders: race (white or not), education (college level or not), average acts of intercourse per menstrual cycle, and for the female only model, self-reported menstrual cycle regularity (regular or not) at baseline. In couple-based models, we further analyzed the couple's joint profile of their anthropometric measures adjusting for a priori selected covariates based on the literature. The models allowed for a separate regression coefficient for each combination of the couple's BMI profile, allowing the data to dictate the direction of the estimated FORs. These covariates included both partners’ age included as female age and difference between the partners’ ages (in years) to account for their correlatedness, both partners’ number of days of vigorous physical activity, smoking status based on serum cotinine concentration (as mentioned above) and non-fasting free cholesterol levels (log-transformed). Additional joint models were run adjusting for other possible confounders including: both partners’ race, education, average acts of intercourse per menstrual cycle and menstrual cycle regularity. Analyses were conducted using SAS software (version 9.4, SAS Institute, Cary, NC). Significance refers to statistical significance (P < 0.05) throughout the manuscript.
Results
Description of the study cohort by partner is presented in Table I. Specifically, couples tended to be white, college educated and parous. Overall, 27% of women and 41% of men were found to be obese class I or higher (BMIs ≥ 30.0 kg/m2), with 40% of men having a waist circumference of ≥101.6 cm and 47.3% of women with a waist circumference of ≥88.6 cm. The majority of the cohort was inactive with 60% of women and 58% of men reporting engaging in physical activity <1 time/week.
Table I.
Description of Study Cohort by pregnancy status, LIFE Study, 2005–2009.
| Characteristic | Male (n = 501) # (%) |
Female (n = 501) # (%) |
|---|---|---|
| Race | ||
| White | 394 (79) | 393 (78) |
| Education | ||
| ≥College | 452 (90) | 470 (94) |
| Cotinine-based smoking status | ||
| No (Cotinine <10 ng/ml) | 409 (83) | 455 (93) |
| Vigorous activity/week§ | ||
| <1 | 290 (58) | 301 (60) |
| 1–4 | 174 (35) | 156 (31) |
| ≥5 | 37 (7) | 43 (9) |
| History of hypothyroidism | ||
| No | 497 (99) | 462 (92) |
| Female history of polycystic ovarian syndrome | ||
| No | 473 (95) | |
| Female menstrual cycle irregularity | ||
| Regular | 419 (84) | |
| BMI (kg/m2) | ||
| Underweight or normal (<25) | 84 (17) | 228 (46) |
| Overweight (25 to <30) | 206 (42) | 137 (27) |
| Obese class I (30 to <35) | 131 (26) | 66 (13) |
| Obese class II (≥35) | 75 (15) | 69 (14) |
| Male waist circumference | ||
| <94 cm | 165 (33) | |
| 94 to <101.6 cm | 135 (27) | |
| ≥101.6 cm | 197 (40) | |
| Female waist circumference | ||
| <80 cm | 119 (24) | |
| 80 to <88.6 cm | 144 (29) | |
| ≥88.6 cm | 236 (47) | |
| Waist–height ratio | ||
| Regular (<0.5) | 91 (18) | 164 (33) |
| Large (≥0.5) | 405 (82) | 335 (67) |
| Waist–hip ratio | ||
| Regular (<0.8) | 135 (27) | |
| Large (≥0.8) | 361 (73) | |
| Prior male paternity | ||
| Yes | 239 (48) | |
| Female parity, conditional on gravidity | ||
| Never pregnant | 210 (42) | |
| Pregnant, but no live birth | 53 (11) | |
| Pregnant with live birth | 235 (47) | |
| Mean (SD) | ||
| Age (in years) | 31.8 (4.9) | 30.0 (4.1) |
| Average menstrual cycle length | 32.2 (11.2) | |
| Average intercourse/menstrual cycle | 7.4 (4.7) | 7.4 (4.7) |
§Vigorous activity denotes the number of weekly exercise sessions resulting in sweat and increased heart rate during the past year.
Among the anthropometric measurements taken individually on each partner of the couple, only female waist circumference ≥88.6 cm was significantly associated with fecundability, reflecting a ~36% reduction relative to couples whose female partner had a waist circumference of <80 cm (Table II). This association remained significant after adjustment for relevant confounders. However, the association was attenuated after further adjustment for average frequency of intercourse per cycle, menstrual cycle regularity and both partners’ race and education. A dose-response relation was observed between female but not male BMI, and between female but not male waist circumference and fecundability, though the trend was not significant. Both female and male higher WHtR and female WHR showed association with reduced fecundability.
Table II.
Partners’ anthropometric measurements and fecundability odds ratios (FOR), LIFE Study.
| Anthropometric measure | Unadjusted | Adjusted* | Adjusted† |
|---|---|---|---|
| BMI (kg/m2) | FOR (95% CI) | FOR (95% CI) | FOR (95% CI) |
| Females | |||
| <25 | Referent | Referent | Referent |
| 25 to <35 | 0.77 (0.60, 0.99) | 0.82 (0.63, 1.06) | 0.92 (0.70, 1.22) |
| ≥35 | 0.7 (0.48, 1.02) | 0.77 (0.51, 1.16) | 0.83 (0.53, 1.28) |
| Males | |||
| <25 | Referent | Referent | Referent |
| 25 to <35 | 1.07 (0.79, 1.45) | 1.08 (0.79, 1.47) | 0.99 (0.71, 1.37) |
| ≥35 | 0.97 (0.65, 1.46) | 1.03 (0.67, 1.58) | 0.90 (0.57, 1.40) |
| Waist circumference (cm) | |||
| Females | |||
| <80 | Referent | Referent* | Referent† |
| 80 to <88.6 | 0.81 (0.59, 1.11) | 0.88 (0.64, 1.22) | 0.94 (0.66, 1.34) |
| ≥88.6 | 0.64 (0.48, 0.86) | 0.68 (0.50, 0.93) | 0.77 (0.55, 1.08) |
| Males | |||
| <94 | Referent | Referent | Referent |
| 94 to <101.6 | 0.97 (0.72, 1.30) | 0.97 (0.71, 1.31) | 0.97 (0.70, 1.33) |
| ≥101.6 | 1.06 (0.81, 1.39) | 1.17 (0.88, 1.55) | 1.00 (0.74, 1.55) |
| WHtR | |||
| Females | |||
| Regular (<0.5) | Referent | Referent* | Referent† |
| Large (≥0.5) | 0.83 (0.65, 1.06) | 0.86 (0.67, 1.10) | 0.94 (0.72, 1.24) |
| Males | |||
| Regular (<0.5) | Referent | Referent | Referent |
| Large (≥0.5) | 0.89 (0.67, 1.20) | 0.93 (0.69, 1.26) | 0.90 (0.65, 1.24) |
| Female WHR | |||
| Regular (<0.8) | Referent | Referent* | Referent† |
| Large (≥0.8) | 0.91 (0.71, 1.18) | 0.94 (0.72, 1.22) | 0.96 (0.76, 1.29) |
WHtR, Waist-to-height ratio; WHR, Waist-to-hip ratio.
*Adjusted for age (continuous), smoking status (based on cotinine levels ≥10 ng/ml), number of days of vigorous physical activity per week, free cholesterol level (log-transformed).
†Adjusted for age (continuous), smoking status (based on cotinine levels ≥10 ng/ml), number of days of vigorous physical activity per week, free cholesterol level (log-transformed), race (white or not), education (college level or not), average intercourse per cycle and menstrual cycle regularity (regular or not in female model).
When modeling both partners’ body composition in the couple-based model, an interesting pattern emerged for overweight or obese class I female partners whose male partners had normal BMIs (Table III). A 54% reduction in fecundability was observed when the female partner was overweight/obese class I despite the male partner having a normal BMI (aFOR: 0.46, 95% CI: 0.23, 0.95). However, the significance was attenuated with further adjustment for average frequency of intercourse per cycle, menstrual cycle regularity, both partners’ race and education. A comparable reduction in fecundability was observed for couples where both had BMIs categorized in the obese class II range (aFOR: 0.46, 95% CI: 0.21, 1.00). These findings were robust after covariate adjustment. However, in light of the cholesterol measurements being non-fasting and the potential to consider it as an intermediate or confounder as both BMI and cholesterol were measured at the same point in time, we assessed our findings in absence of cholesterol and the results remained consistent. Also, our results for BMI and fecundability remain consistent on additional adjustment for average acts of intercourse to our main model. Of the multiple central adiposity measures assessed in couples, only female partner's waist circumference was associated with diminished fecundability (Tables II and IV). Specifically, female waist circumference >88.6 cm (35 inches) was associated with a 23–36% reduction in fecundability in comparison to smaller waist women (<80 cm) irrespective of the male partner's waist measurement or model. We also found reduced fecundability across all categories of couples’ waist circumferences as compared to the referent group comprising couples where both partners had smaller waists, i.e. female partner's waist circumference <80 cm and male partner's waist circumference <94 cm. The findings were corroborated when considering WHR for the females and waist circumference for the males (Table IV) with FORs <1.0. However, these findings were not consistent. Specifically, couples with male partners having larger waist circumferences between 94 and 101.6 cm but with female partners having smaller WHR (<0.8) showed significant reductions (50%) in fecundability compared to couples with smaller waist circumferences (aFOR: 0.50, 95% CI: 0.27, 0.94). Lastly, we observed no association between couples WHtR and fecundability (results not presented).
Table III.
Couples’ anthropometric measurements and FOR, LIFE Study.
| Female BMI (kg/m2) | |||
|---|---|---|---|
| Male BMI (kg/m2) | <25 | 25 to <35 | ≥35 |
| Unadjusted | FOR (95% CI) | FOR (95% CI) | FOR (95% CI) |
| <25 | Referent | 0.39 (0.20, 0.76) | 0.81 (0.26, 2.48) |
| 25 to <35 | 0.89 (0.61, 1.31) | 0.72 (0.49, 1.07) | 0.77 (0.45, 1.32) |
| ≥35 | 0.77 (0.38, 1.54) | 0.99 (0.58, 1.71) | 0.45 (0.23, 0.89) |
| Adjusted* | FOR (95% CI) | FOR (95% CI) | FOR (95% CI) |
| <25 | Referent* | 0.46 (0.23, 0.95) | 1.29 (0.41, 4.11) |
| 25 to <35 | 0.90 (0.61, 1.34) | 0.83 (0.55, 1.26) | 0.93 (0.53, 1.63) |
| ≥35 | 0.83 (0.39, 1.76) | 1.17 (0.66, 2.05) | 0.46 (0.21, 1.00) |
| Adjusted† | FOR (95% CI) | FOR (95% CI) | FOR (95% CI) |
| <25 | Referent† | 0.50 (0.24, 1.05) | 0.91 (0.25, 3.37) |
| 25 to <35 | 0.80 (0.52, 1.22) | 0.80 (0.51, 1.25) | 1.01 (0.55, 1.85) |
| ≥35 | 0.67 (0.29, 1.51) | 1.37 (0.74, 2.54) | 0.41 (0.17, 0.98) |
*Adjusted for female partner's age (continuous), difference between the male and female age, both partners’ smoking status (based on cotinine levels ≥10 ng/ml), both partners’ number of days of vigorous physical activity per week and both partners’ free cholesterol level (log-transformed).
†Adjusted for female partners’ partners’ age (continuous), difference between male and female age, both partners’ smoking status (based on cotinine levels ≥10 ng/ml), both partners’ number of days of vigorous physical activity per week, both partners’ race (white or not), both partners’ education (college level or not), both partners’ free cholesterol level (log-transformed), average intercourse per cycle and menstrual cycle regularity (regular or not).
Table IV.
Couples’ central adiposity measurements and FOR, LIFE Study.
| Female waist (cm) | Female WHR | ||||
|---|---|---|---|---|---|
| Male waist (cm) | <80 | 80 to <88.6 | ≥88.6 | <0.8 | ≥0.8 |
| Unadjusted | FOR (95% CI) | FOR (95% CI) | FOR (95% CI) | FOR (95% CI) | FOR (95% CI) |
| <94 | Referent | 0.62 (0.38, 1.00) | 0.45 (0.27, 0.73) | Referent | 0.58 (0.38, 0.89) |
| 94 to <101.6 | 0.70 (0.40, 1.25) | 0.60 (0.36, 1.01) | 0.59 (0.37, 0.94) | 0.52 (0.30, 0.93) | 0.73 (0.48, 1.12) |
| ≥101.6 | 0.78 (0.44, 1.38) | 0.88 (0.54, 1.44) | 0.60 (0.39, 0.90) | 0.71 (0.43, 1.18) | 0.75 (0.50, 1.12) |
| Adjusted* | FOR (95% CI) | FOR (95% CI) | FOR (95% CI) | FOR (95% CI) | FOR (95% CI) |
| <94 | Referent | 0.63 (0.39, 1.04) | 0.52 (0.31, 0.88) | Referent | 0.62 (0.40, 0.98) |
| 94 to <101.6 | 0.62 (0.34, 1.14) | 0.66 (0.39, 1.13) | 0.63 (0.39, 1.02) | 0.47 (0.26, 0.86) | 0.76 (0.48, 1.19) |
| ≥101.6 | 0.79 (0.43, 1.45) | 1.08 (0.65, 1.80) | 0.69 (0.44, 1.09) | 0.78 (0.46, 1.34) | 0.87 (0.56, 1.35) |
| Adjusted† | FOR (95% CI) | FOR (95% CI) | FOR (95% CI) | FOR (95% CI) | FOR (95% CI) |
| <94 | Referent | 0.72 (0.42, 1.24) | 0.68 (0.39, 1.18) | Referent | 0.67 (0.41, 1.09) |
| 94 to <101.6 | 0.71 (0.36, 1.36) | 0.70 (0.39, 1.25) | 0.74 (0.44, 1.24) | 0.50 (0.27, 0.94) | 0.80 (0.50, 1.31) |
| ≥101.6 | 0.76 (0.39, 1.51) | 1.17 (0.67, 2.05) | 0.73 (0.44, 1.20) | 0.75 (0.42, 1.34) | 0.87 (0.54, 1.40) |
*Adjusted for female partner's age (continuous), difference between the male and female age, both partners’ smoking status (based on cotinine levels ≥10 ng/ml), both partners’ number of days of vigorous physical activity per week and both partners’ free cholesterol level (log-transformed).
†Adjusted for female partners’ partners’ age (continuous), difference between male and female age, both partners’ smoking status (based on cotinine levels ≥10 ng/ml), both partners’ number of days of vigorous physical activity per week, both partners’ race (white or not), both partners’ education (college level or not), both partners’ free cholesterol level (log-transformed), average intercourse per cycle and menstrual cycle regularity (regular or not)
Discussion
In this prospective cohort study with preconception enrollment of couples without infertility and for whom standardized anthropometric assessments were performed at baseline or before trying for pregnancy, we found diminished fecundability among couples whose female partners were overweight or obese class I, and also for couples whose partners were both obese class II. Fecundability was reduced by ~59%, even after covariate adjustments. Moreover, female but not male central adiposity as measured by waist circumference was associated with reduced fecundability, though not consistently. While BMI provides an estimate of weight for height, it does not differentiate muscle from fat rendering it only a proxy of body composition relative to other measures of body composition. Our findings underscore the importance of including both partners in studies of body composition and obesity when assessing couple fecundity.
Our findings for couple's BMI and reduced fecundability are consistent with previous literature that also observed that the odds of sub-fecundity (TTP > 12 months) were increased for obese couples (Ramlau-Hansen et al., 2007). This earlier study relied upon retrospectively reported dichotomized TTP (≤12 versus >12 months) and BMI among pregnant couples, whereas we recruited couples prior to conception with measured BMI and prospectively observed TTP. As such, our findings are not restricted to couples achieving pregnancy, and may better represent the distribution of fecundability. Our finding that overweight and obese class I women had significantly reduced fecundability even if their male partner was of normal weight supports previous studies evaluating the role of female BMI, though direct comparisons are difficult as these studies tended to rely solely on the female's self-reported BMI (Zaadstra et al., 1993; Jensen et al., 1999; Bolúmar et al., 2000; Law et al., 2007; Wise et al., 2010; McKinnon et al., 2016). Our findings were also consistent with previous reports that obesity was associated with reduced fecundability even among women with regular menstrual cycles (Jensen et al., 1999; Law et al., 2007). These results are also in line with some previous studies among couples seeking fertility treatment that observed lower odds of live birth when both partners were overweight or obese (BMI > 25 kg/m2) (Petersen et al., 2013).
Our lack of a consistent significant negative association between women's waist circumference and fecundability supports findings of a recent prospective pregnancy study, but not all earlier findings. Specifically, reduced fecundability was observed among studies focusing on couples undergoing fertility treatment (Zaadstra et al., 1993; Wass et al., 1997), and among one prospective pregnancy study of female waist circumference and fecundability (McKinnon et al., 2016) though not in another (Wise et al., 2010). Our findings that couples whose male partners’ have larger waist circumferences experience diminished fecundability are consistent with findings focusing on waist circumference and diminished semen quality (Chavarro et al., 2010; Eisenberg et al., 2014), though differences in semen quality do not always translate into associations with couple fecundity (Louis et al., 2014).
Our study has important limitations including the absence of direct measures of body composition (e.g. dual-energy X-ray absorptiometry, skinfolds, impedance), and a relatively crude measure of physical activity. Consistent with this observational design, the potential for possible residual confounding or unmeasured confounders that may account for the findings cannot be ruled out. The measured BMIs for our cohort are skewed toward higher ranges but are consistent with reproductively aged couples in USA (Ogden et al., 2014). Our findings need to be interpreted within the framework of these important limitations along with the study's notable strengths such as preconception enrollment, standard anthropometric assessment of both partners, and prospectively ascertained TTP. In addition, the extent to which our findings are generalizable to study populations recruited from clinical or volunteer settings remain to be established.
Overall, obese couples were found to have approximately half the fecundability as couples with normal BMI. Our findings suggest that couple obesity may be an important ‘reproductive toxicant’. These findings highlight the importance of couples’ body composition for fecundity, and the need for appropriate preconception guidance.
Acknowledgements
None.
Authors’ roles
R.S. assisted in conceptualizing the analytic plan, oversaw the statistical analysis and drafted the paper. S.L.M. assisted in the interpretation of the findings and writing the paper. G.M.B.L. designed the study, conceptualized the paper, and provided critical substantive input and assisted in writing the paper.
Funding
The Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health (contract numbers N01-HD-3–3355; N01-HD-3–3356; N01-HD-3–3358).
Conflict of interest
None declared.
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