Abstract
Background:
Although pregnancy planners are a priority group for influenza vaccination in the United States, little is known about the extent to which influenza vaccination affects fecundability.
Methods:
We analyzed data from Pregnancy Study Online (PRESTO), an ongoing preconception cohort study of North American pregnancy planners. During June 2013 to August 2019, 8,654 female participants and 2,137 of their male partners completed a baseline questionnaire and were followed until reported pregnancy, fertility treatment initiation, loss to follow-up, or 12 menstrual cycles of attempt time, whichever came first. At baseline, male and female participants reported whether they received an influenza vaccination in the past year and the date of vaccination. We used proportional probabilities regression models to estimate fecundability ratios (FR) and 95% confidence intervals (CI) comparing those who did and did not report influenza vaccination, adjusting for demographics, anthropometrics, behavioral factors, and medical history.
Results:
Influenza vaccination in the past year was more common among female participants than male participants (47% vs. 37%). FRs were 1.04 (95% CI: 0.98-1.10) for female vaccination and 1.03 (95% CI: 0.93-1.14) for male vaccination. Among the 2,137 couples with complete data on both partners, for 40% neither partner was vaccinated, 23% had female-only vaccination, 9% had male-only vaccination, and in 28% both partners were vaccinated. Compared with couples in which neither participant was vaccinated, FRs were 1.13 for female-only vaccination (95% CI: 0.99-1.29), 0.94 for male-only vaccination (95% CI: 0.78-1.12), and 1.07 when both partners were vaccinated (95% CI: 0.94-1.21). When restricted to recent vaccination before peak influenza season, results were similar.
Conclusions:
Our data indicate no adverse effect of influenza vaccination on fecundability.
1. Introduction
Influenza is a viral contagion that causes mild to severe respiratory illness (1). Preliminary burden estimates for the U.S. 2018-2019 influenza season include 37-43 million influenza-like illnesses, 17-20 million medical visits, 531,000-647,000 hospitalizations, and 36,400-61,200 deaths (2). To help mitigate such outcomes, the U.S. recommends routine annual influenza vaccination for persons aged six months or older who do not have contraindications (3). Since pregnant individuals have a higher chance of hospitalization due to respiratory illness that can result in adverse perinatal and neonatal outcomes (4-6), some countries consider individuals who are (or will be) pregnant during the influenza season a high priority group for influenza vaccination (3, 7, 8). Recent reports show no adverse association between prenatal influenza vaccination and infant outcomes (9, 10). However, little is known about the extent to which influenza vaccination is associated with fecundability.
Influenza viruses are detected year-round but are considerably more common during the fall and winter months, peaking in the northern hemisphere during December, January and February (11). In order to provide protection for a year’s anticipated influenza strains, the antigenic composition of influenza vaccinations differs annually. The match between the antigenic composition of a season’s influenza vaccination and that season’s circulating viruses influences its effectiveness, and can also vary from year to year (12). In the U.S., influenza vaccine effectiveness generally ranges from 40-60% in the overall population (12, 13). Vaccine effectiveness can also wane over the course of a single season (14). Intramuscular or subcutaneous administration is the most common route of administration, resulting in a systemic immunologic response. Antibodies that protect against influenza can be detected in serum as early as 2 days post-vaccination, peaking around 2-3 weeks post-vaccination, and are 50% lower six months post-vaccination (15). The severity of influenza seasons, and vaccination uptake, can also vary from year to year and by region (16, 17).
Given such inter- and intra-seasonal variations, influenza vaccination may influence fecundability in multiple ways. First, vaccinated individuals (female and male) for whom the vaccine was effective in preventing influenza-related sickness may then subsequently be healthier than unvaccinated individuals in a given season, making them more likely to engage in regular intercourse and increasing the probability of conception. Second, since immunological benefits of the influenza vaccination are highest in the weeks following vaccination (15), influenza vaccination may help induce immunological tolerance among vaccinated females and improve embryo implantation, although this theory is controversial (18). We know of no studies reporting on the association between preconception influenza vaccination and fecundability, and a prospective cohort enrolling pregnancy planners provides an important opportunity for such investigations.
In a prospective preconception cohort study of pregnancy planners, we examined the association between preconception influenza vaccination and fecundability, the per-cycle probability of conception.
2. Methods
2.1. Study population
We analyzed data from Pregnancy Study Online (PRESTO), an ongoing internet-based preconception cohort study of pregnancy planners in the U.S. and Canada. Details are described elsewhere (19). Briefly, recruitment began in June 2013 and was conducted primarily through banner advertisements on social media and health-related websites. Eligible participants were aged 21-45 years, not using contraception or fertility treatments, and not pregnant at study entry. From June 2013 through August 2019, 10,988 eligible participants completed a baseline questionnaire and were followed via bimonthly follow-up questionnaires until reported pregnancy or 12 months, whichever came first. After enrollment, we asked female participants to invite their male partners to participate (optional). We excluded 129 female participants whose baseline date of last menstrual period (LMP) was more than 6 months before study entry and 24 with insufficient or missing LMP data. We further excluded couples with more than 6 cycles of attempt time at entry (n=2,181), in an effort to minimize selection bias and reverse causation, since couples who have been attempting to conceive longer may have modified their behavior due to subfertility. After exclusions, 8,654 female participants were retained for analysis. Of these, 54% invited their male partners to participate and 46% of these partners completed the survey, resulting in 2,137 male participants and couples. The Boston University Medical Center’s Institutional Review Board approved this study protocol and online informed consent was obtained from all participants.
2.2. Assessment of influenza vaccination and covariates
At baseline, both female and male participants reported whether they received an influenza vaccination in the past year and the date of that vaccination (month/year). The majority of vaccinated individuals provided a date of vaccination (99%). Because antibodies that protect against influenza are 50% lower six months post-vaccination (15), we might expect protective associations to decrease with time since vaccination. We created the following categories of time since influenza vaccination at baseline: 0-3, 4-6, 7-9, and 10-12 months. We treated vaccinated participants as unvaccinated if they did not provide a date of vaccination (29 females and 0 males) or if they provided a date of vaccination >12 months since baseline (72 females and 33 males). On bimonthly follow-up questionnaires, female participants updated their data on influenza vaccination (“did you receive a flu vaccination in the past 2 months?”). We used these data in time-varying analyses, which updated female influenza vaccination exposure over follow-up. Male participants did not complete bimonthly follow-up questionnaires. Baseline questionnaires from both partners collected detailed data on socio-demographics, lifestyle factors, medical and reproductive history, and medication use.
2.3. Assessment of time to pregnancy (TTP)
We estimated TTP using data from the baseline and follow-up questionnaires. On the baseline questionnaire, female participants reported the first day of their LMP, usual menstrual cycle length, and the number of menstrual cycles they attempted pregnancy before study entry. In our data, we compared LMP dates from FertilityFriend.com vs. baseline questionnaire data and found very high agreement (19). On each follow-up questionnaire, participants reported their most recent LMP date and whether they conceived since the prior questionnaire. Among female participants who reported irregular cycles, cycle length was estimated based on the LMP date at baseline and the consecutive LMP dates reported during follow-up. TTP was estimated based on the total discrete cycles at risk, calculated as: cycles of attempt at study entry + [(LMP date from most recent follow-up questionnaire – date of baseline questionnaire completion)/usual cycle length] +1 (Supplemental Figure).
2.4. Data analysis
Vaccination in the past year (yes/no), and categories of time since vaccination (0-3, 4-6, 7-9, and 10-12 months), were evaluated separately for female and male participants. In the subset of 2,137 couples with complete data, we evaluated past-year vaccination using the following categories: neither partner vaccinated, female-only vaccinated, male-only vaccinated, and both partners vaccinated. Couples contributed observed menstrual cycles at risk from study enrollment until reported pregnancy (regardless of the outcome), fertility treatment initiation, loss to follow-up, cessation of pregnancy attempt, or 12 menstrual cycles of attempt time, whichever came first.
We used proportional probabilities regression models to estimate fecundability ratios (FR), the ratio of the per-cycle probability of conception comparing vaccinated with unvaccinated participants, and 95% confidence intervals (CI). A FR of <1 indicates a longer TTP comparing vaccinated with unvaccinated participants. For example, a FR of 0.85 would indicate that vaccinated participants have a 15% reduced probability of conception in any given cycle of attempt time compared with the unvaccinated referent group. The proportional probabilities model included indicator variables for each cycle at risk to account for the baseline decline in fecundability with increasing pregnancy attempt time. We used an Andersen-Gill data structure, which includes a single menstrual cycle per observation and accounts for left truncation from delayed entry into the study (20, 21).
Selection of potential confounders was determined a priori and guided by the literature and a causal directed acyclic graph. In models for female influenza vaccination, we adjusted for the following baseline variables: female age (<25, 25-29, 30-34, 35-39, ≥40 years), years of education (≤12, 13-15, 16, ≥17 years), annual household income (<50,000, 50,000-99,000, 100,000-149,000, ≥150,000 US dollars), body mass index (BMI) (<18.5, 18.5-24, 25-29, 30-34, ≥35 kg/m2), asthma diagnosis (ever vs. never), diabetes diagnosis (ever vs. never), smoking status (current, past, never), marital status with current partner (no vs. yes), number of previous births (0, 1, ≥2 births), last method of contraceptive use (oral contraceptives, other hormonal contraceptives, barrier methods, withdrawal/rhythm/other methods), intercourse frequency (1, 2-3, ≥4 times/week), and geographic region of residence (Canada, U.S. Northeast, Midwest, South, West, and other). To assess the role of health-seeking behaviors, we further adjusted for health insurance from government, private, or work (no vs. yes), number of times visited primary care physician (0, 1, 2-3, ≥4 times in the last year), and prenatal and multivitamin use (no vs. yes). Models for male influenza vaccination were adjusted for the male covariate equivalencies, as well as female partner’s age and BMI, given their strong association with fecundability (22-25). We did not have information on male participant’s health insurance status. Models reporting on couple exposure to influenza vaccination adjusted for both female and male covariates.
We used multiple imputation methods to impute missing data for exposure, covariates, and outcome (26). We generated five imputation datasets with over 200 covariates to predict missing values. We then pooled effect estimates across the five datasets to account for variation within and across imputation datasets. We were missing data on vaccination status for 0.1% of females and 0.1% of males. Questions assessing health insurance at baseline was added to the baseline questionnaire in 2018 and was missing for 52% of participants. With the exception of health insurance, covariate missingness ranged from 0% (e.g., age) to 3% (e.g., annual household income), and was similar when comparing female and male participants. For women who did not complete any follow-up questionnaires (15%), we assigned them one cycle of follow-up and imputed their pregnancy status (pregnant vs. not pregnant) at that cycle.
We report the agreement of influenza vaccination among couples using the weighted kappa coefficient, which takes into account random agreement. We also evaluated time-varying exposure to influenza vaccination (in two-month intervals) using the female bimonthly questionnaires. Since influenza vaccination antigenic composition, effectiveness, and population uptake can vary from year to year (27), we stratified female influenza vaccination findings by year (2013-2019) of the baseline questionnaire. Sensitivity analyses excluded the 101 female participants and the 33 male participants who reported influenza vaccination in the past 12-months but were assigned non-vaccinated status due to lack of dates or implausible dates.
Since the immunological response to the influenza vaccine is strongest in the first few weeks, we hypothesized that influenza vaccination may result in improved fecundability through greater immune system activation. To evaluate this hypothesis, we assessed fecundability by categories of time since vaccination.
Since influenza vaccination and TTP have seasonal variation (28), we also hypothesized that influenza vaccination may result in improved fecundability through improved health status during influenza season. To assess this hypothesis, we restricted analyses to evaluate influenza vaccination occurring before cycles at highest risk of influenza infection in the Northern hemisphere. In this analysis, we restricted data to the 2,373 female participants and 544 male participants who completed the baseline questionnaire in the fall (September 22-December 21). The exposure in these analyses was further defined as influenza vaccination in the past 3 months (yes vs. no), which is consistent with vaccination during the fall when the vaccination becomes newly available in the Northern hemisphere, and presumably when that season’s vaccination was best “matched” to that season’s anticipated virus strains. We then truncated follow-up time in our analyses to include: 1) up to 3 menstrual cycles, and 2) up to 6 menstrual cycles, thereby approximating the menstrual cycles at greatest risk of infection from the influenza virus and the peak of the influenza season (approximately December-February). For example, an individual who completed the baseline questionnaire in October and reported an influenza vaccination in September would be considered exposed to the influenza vaccination at baseline, and then followed for pregnancy for 3 cycles (until January) and 6 cycles (until April).
3. Results
Overall, 8,654 female participants contributed 5,103 pregnancies and 33,087 menstrual cycles of attempt time. At baseline, the mean age was 29.9 years (standard deviation (SD)=4.1), the mean BMI was 28.0 kg/m2 (SD=7.5), and the majority had a college education or higher (71.9%). 15.3% had a household income >150,000 U.S. dollars and participants were predominately non-Hispanic White (84.4%). The majority did not currently smoke, were married, and nulliparous (Table 1). Nearly all participants had some form of health insurance and many reported taking either a prenatal or multivitamin at baseline. Similar characteristics were observed among their male partners.
Table 1:
Baseline characteristics of 8,654 female pregnancy planners and 2,137 of their male partners bv influenza vaccination status (past year), PRESTO* (June 2013-August 2019)
| Female Influenza Vaccination |
Male Influenza Vaccination |
|||
|---|---|---|---|---|
| Characteristic | Yes | No | Yes | No |
| N (%) | 4060 (46.9) | 4594 (53.1) | 797 (37.3) | 1340 (62.7) |
| Age at baseline (years), mean (SD) | 30.4 (4.0) | 29.4 (4.2) | 32.1 (4.9) | 31.4 (5.4) |
| Education, years, % | ||||
| ≤12 | 3.1 | 7.4 | 5.2 | 13.2 |
| 13-15 | 17.7 | 27.2 | 17.7 | 25.9 |
| 16 | 34.3 | 34.8 | 36.0 | 37.2 |
| >16 | 44.9 | 30.6 | 41.1 | 23.8 |
| Household income ≥150,000 U.S. dollars/year , % | 19.1 | 11.4 | 22.4 | 14.2 |
| Race/ethnicity, % | ||||
| White, non-Hispanic | 84.7 | 84.0 | 84.6 | 85.6 |
| Black, non-Hispanic | 2.4 | 3.6 | 1.6 | 2.2 |
| Hispanic | 6.5 | 6.4 | 4.8 | 5.5 |
| Asian, non-Hispanic | 2.4 | 1.6 | 4.5 | 2.1 |
| Mixed race/other race | 4.0 | 4.4 | 4.6 | 4.7 |
| Body mass index (kg/m2), mean | 27.6 | 28.3 | 28.0 | 28.3 |
| Current smoker, % | 7.0 | 13.9 | 6.7 | 16.0 |
| Ever diagnosed with asthma, % | 18.5 | 15.0 | 14.0 | 12.1 |
| Ever diagnosed with diabetes, % | 1.9 | 1.5 | 2.3 | 2.0 |
| Married, % | 92.4 | 87.8 | 96.8 | 91.8 |
| Relationship duration (years), mean | 5.9 | 5.3 | 6.2 | 5.5 |
| Intercourse frequency at baseline (times/week) ≥4, % | 13.9 | 18.6 | 11.3 | 14.5 |
| Cycles of attempt at study entry, mean | 1.9 | 2.2 | 1.7 | 2.0 |
| Health insurance (government, private, or work), % | 98.0 | 96.6 | - | - |
| Prenatal vitamin or multivitamin use, % | 81.0 | 71.1 | 36.4 | 32.6 |
| Times visited primary care physician in past year ≥4, % | 17.0 | 16.3 | 8.3 | 6.7 |
| Fall or winter season at baseline, % | 52.9 | 55.1 | 51.1 | 50.5 |
| Canadian residence, % | 11.8 | 20.4 | 8.7 | 17.1 |
| United States region of residence, % | ||||
| Northeast | 24.8 | 19.5 | 31.0 | 21.9 |
| Midwest | 23.9 | 18.6 | 19.9 | 21.3 |
| South | 23.0 | 25.5 | 22.8 | 23.0 |
| West | 16.5 | 16.0 | 17.6 | 16.7 |
| Other region | 0.0 | 0.1 | 0.0 | 0.0 |
| Among males, ever impregnated a partner, % | - | - | 48.7 | 43.9 |
| Among females, nulliparous, % | 65.1 | 67.7 | ||
| Among females, last method of contraception, % | ||||
| Oral contraceptives | 34.6 | 31.7 | - | - |
| Other hormonal methods | 5.3 | 5.2 | - | - |
| Barrier methods | 43.0 | 38.4 | - | - |
| Withdraw/other | 17.1 | 24.8 | - | - |
Pregnancy Study Online
All characteristics except for age are standardized to age distribution of the cohort at baseline.
Among the 2,137 female participants with male partner data (couples), 1,379 pregnancies and 8,670 menstrual cycles of attempt time were contributed. Compared with all female participants, female participants with available male partner data were more likely to have been vaccinated at baseline, married, have health insurance, take a prenatal or multivitamin, and have higher annual household incomes (Supplemental Table 1). They were also less likely to report current smoking.
Vaccination was positively associated with never smoking and education (Table 1). We also saw some evidence of greater vaccination among individuals with asthma and diabetes. The prevalence of influenza vaccination in the past year was higher among females than males (47% vs. 37%) and highest in the fall/winter months (>80% among those who were vaccinated). Vaccinated individuals were less likely to be Canadian and more likely to reside in the northeastern U.S. Among the 4,060 vaccinated females, 34.8% reported vaccination within three months of baseline, 20.6% 4-6 months from baseline, 23.8% 7-9 months from baseline, and 20.8% 10-12 months from baseline. Among the 797 vaccinated males, we observed a similar distribution (34.6%, 23.2%, 23.0%, and 19.2%, respectively).
Among the 2,137 couples with vaccination information available, for 39.6% neither partner was vaccinated, for 23.1% only the female partner was vaccinated, for 9.3% only the male partner was vaccinated, and for 28.0% both partners were vaccinated. The weighted kappa coefficient for this agreement was 0.36. Female influenza vaccination in the past 2 months ranged from 8-11% at each follow-up questionnaire.
FRs were 1.04 (95% CI: 0.98-1.10) for female influenza vaccination at baseline and 1.03 (95% CI: 0.93, 1.14) for male influenza vaccination at baseline (Table 2). Compared with couples in which neither participant was vaccinated, FRs were 1.13 when only the female partner was vaccinated (95% CI: 0.99-1.29), 0.94 when only the male partner was vaccinated (95% CI: 0.78-1.12), and 1.07 when both partners were vaccinated (95% CI: 0.94-1.21) (Table 2). Results did not differ meaningfully by months since vaccination (Table 2). Compared with no vaccination at baseline, FR’s among female participants for 0-3, 4-6, 7-9, and 10-12 months since vaccination were 1.08, 1.01, 1.01, and 1.03 respectively. We also observed no trend among male participants (1.03, 1.12, 0.97, and 1.01 respectively).
Table 2:
Fecundability ratios (FR) and 95% confidence intervals (CI) for self-reported influenza vaccination at baseline among the 8,654 female pregnancy planners and 2,137 of their male partners, PRESTO* (June 2013-August 2019)
| Exposure | No. of pregnancies |
No. of cycles |
Unadjusted | Adjusteda | Adjustedb | |||
|---|---|---|---|---|---|---|---|---|
| FR | 95% CI | FR | 95% CI | FR | 95% CI | |||
| Female influenza vaccination at baseline (past year) | ||||||||
| No | 2570 | 17984 | 1.00 | Referent | 1.00 | Referent | 1.00 | Referent |
| Yes | 2533 | 15103 | 1.11 | 1.06, 1.17 | 1.05 | 1.00, 1.11 | 1.04 | 0.98, 1.10 |
| 0-3 months since vaccination at baseline | 887 | 5195 | 1.14 | 1.06, 1.23 | 1.10 | 1.02, 1.18 | 1.08 | 1.00, 1.16 |
| 4-6 months since vaccination at baseline | 523 | 3181 | 1.10 | 1.00, 1.19 | 1.03 | 0.94, 1.13 | 1.01 | 0.92, 1.11 |
| 7-9 months since vaccination at baseline | 608 | 3630 | 1.09 | 1.01, 1.18 | 1.02 | 0.94, 1.11 | 1.01 | 0.93, 1.10 |
| 10-12 months since vaccination at baseline | 515 | 3097 | 1.12 | 1.02, 1.22 | 1.04 | 0.95, 1.13 | 1.03 | 0.95, 1.12 |
| Female influenza vaccination (past 2-months), time-varying | ||||||||
| No | 3043 | 21880 | 1.00 | Referent | 1.00 | Referent | 1.00 | Referent |
| Yes | 2060 | 11207 | 1.09 | 0.94, 1.15 | 1.05 | 1.00, 1.11 | 1.05 | 1.00, 1.11 |
| Male influenza vaccination at baseline (past year) | ||||||||
| No | 843 | 5466 | 1.00 | Referent | 1.00 | Referent | 1.00 | Referent |
| Yes | 536 | 3204 | 1.05 | 0.95, 1.16 | 1.03 | 0.93, 1.13 | 1.03 | 0.93, 1.14 |
| 0-3 months since vaccination at baseline | 181 | 1160 | 1.02 | 0.89, 1.18 | 1.02 | 0.89, 1.18 | 1.03 | 0.89, 1.19 |
| 4-6 months since vaccination at baseline | 132 | 725 | 1.15 | 0.99, 1.35 | 1.11 | 0.94, 1.31 | 1.12 | 0.95, 1.32 |
| 7-9 months since vaccination at baseline | 121 | 729 | 1.00 | 0.84, 1.19 | 0.97 | 0.81, 1.15 | 0.97 | 0.81, 1.16 |
| 10-12 months since vaccination at baseline | 102 | 590 | 1.04 | 0.87, 1.25 | 1.00 | 0.83, 1.21 | 1.01 | 0.84, 1.22 |
| Couple influenza vaccination at baseline (past year) | ||||||||
| Neither | 514 | 3616 | 1.00 | Referent | 1.00 | Referent | 1.00 | Referent |
| Female only | 329 | 1850 | 1.16 | 1.02, 1.31 | 1.12 | 0.98, 1.28 | 1.13 | 0.99, 1.29 |
| Male only | 121 | 867 | 0.98 | 0.82, 1.18 | 0.94 | 0.78, 1.12 | 0.94 | 0.78, 1.12 |
| Both | 415 | 2337 | 1.15 | 1.03, 1.29 | 1.07 | 0.94, 1.21 | 1.07 | 0.94, 1.21 |
Pregnancy Study Online
Adjusted for the following baseline variables: age, education, household income, body mass index, asthma, diabetes, smoking status, marital status, number of previous births, last method of contraceptive, intercourse frequency, history of infertility, and geographic region of residence.
Additionally adjusted for health insurance, number of times visited primary care physician in last year, and prenatal and multivitamin use.
Results did not differ when we analyzed female influenza vaccination as a time-varying exposure (Table 2). With the exception of 2015 (FR=1.13), results stratified by year at baseline were similar (Supplemental Table 2). Sensitivity analyses excluding the 101 female participants and the 33 male participants assigned as “non-vaccinated” in the past 12-months due to implausible dates did not meaningfully differ from the main analyses (data not shown).
In analyses restricted to fall baseline questionnaire completion, the prevalence of influenza vaccination over the past year at baseline was similar to that of the larger cohort (46.0% for female participants and 37.6% for male participants). Among participants who completed baseline in the fall, vaccination in the past 3 months was 61.5% for female participants and 58.8% for male participants. Vaccination profiles for the couples who enrolled in the study in the fall were nearly identical to the larger cohort. FRs for female vaccination before peak influenza season were similar to the main findings (1.04 vs. 1.03) and were similar when restricted to 3 and 6 cycles of follow-up at risk (1.06 and 1.04, respectively) (Supplemental Table 3). We saw little difference for male vaccination in the fall compared to main analyses (1.03 vs. 0.97). The exclusion of female participants with no follow-up data (15%) produced similar findings (data not shown).
4. Discussion
Our findings indicate, with reasonable precision, that there is no adverse effect of influenza vaccination, for either female or male partner, on fecundability. We observed little or no effect of the time since influenza vaccination, or when restricting to influenza vaccination just before peak influenza season, when a potential protective effect would be most evident. We also observed that influenza vaccination was more commonly reported among female than male participants (47% vs. 37%), and that influenza vaccination was moderately concordant within couples (weighted kappa coefficient=0.4).
The absence of patterns for time since influenza vaccination on fecundability in our data does not support the hypothesis that influenza vaccination primes the immune system to aid with conception. In sensitivity analyses restricted to cycles at greatest risk of influenza infection, we saw no evidence to support the hypothesis that potential protective benefits offered from the vaccination improved fecundability. Our observation of 13% increased fecundability among female participants in 2015 only (FR=1.13, 95% CI: 0.89-1.17), and not in other years, is likely a chance finding.
During the 2016-2017 U.S. influenza season, 34% of individuals of reproductive age (18-49 years) reported influenza vaccination (29) and, consistent with our study findings, was more common among females than males (37% vs. 30%). Although the prevalence of vaccination was higher among our study participants than the general population, such a difference by itself would not necessarily bias the fecundability estimates (30). If participation in our study was related to both influenza vaccination and probability of pregnancy, then our findings may be influenced by selection bias (31). Hatch et al. evaluated the potential for selection bias in a web-based prospective cohort study design by comparing findings in a volunteer cohort of pregnancy planners with those obtained from nationwide data in Denmark (32); effect estimates for several established perinatal associations were similar.
Our study has limitations. First, although self-report of influenza vaccination in the prior and current season has been validated (33), we did not confirm influenza vaccination using medical records. Exposure misclassification of influenza vaccination is likely to have been non-differential with respect to the outcome (TTP), which we assessed prospectively. Such misclassification would generally result in bias towards the null. Second, although we attempted to control for confounding in a number of ways, and because vaccination is often associated with health-seeking behaviors, social capital, higher income, and access to health insurance (34-36), vaccinated participants may be healthier overall and thus more likely to conceive. A healthy-vaccinee effect can bias results (37), however, this does not explain why there was no evidence of such an upward bias seen for male vaccination. We also saw some evidence that individuals with chronic health conditions were more likely to be vaccinated. If other unreported chronic health conditions impacted vaccination and fertility, our results may be influenced by residual confounding. Third, we were not able to determine the participant’s actual influenza status or symptoms, or the effectiveness of vaccination. Lastly, we did not collect data regularly on frequency of intercourse after baseline.
5. Conclusions
Our findings are compatible with either no effect of influenza vaccination in the past year on fecundability or a slight improvement, and inconsistent with a meaningful adverse effect. As influenza vaccination is recommended for pregnancy planners, the apparent lack of adverse effect on fecundability should be reassuring to those individuals considering vaccination around the time of conception.
Supplementary Material
Highlights.
Pregnancy planners are a priority group for influenza vaccination.
The extent to which influenza vaccination affects fecundability is unclear.
Influenza vaccination was common (47% of females and 37% of males).
Our data indicate no adverse effect of influenza vaccination on fecundability.
7. Acknowledgments
We acknowledge funding from NICHD grants R21-HD072326 and R01-HD086742, and the contributions of PRESTO participants and staff. We are thankful to Michael Bairos for his development of the web-based infrastructure for the study. We acknowledge Alina Chaiyasarikul and Jessica Levinson for their assistance with participant recruitment and follow-up. PRESTO receives in-kind donations for data collection from Swiss Precision Technologies, Sandstone Diagnostics, FertilityFriend.com, and Kindara.com. Birth records were obtained from selected states (CA, FL, MA, MI, OH, PA, and TX) to incorporate additional data on pregnancy outcomes; the data presented herein do not reflect the views of these registries.
Footnotes
Declaration of Competing Interests
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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