We sought to prospectively measure women’s daily cigarette, alcohol, and caffeine use, while attempting pregnancy in relation to intentions to change.
This was a cohort comprising 90 women enrolled upon discontinuing contraception and followed up prospectively until pregnant. Women reported number of daily cigarettes, and alcoholic and caffeinated beverages for 459 menstrual cycles while attempting pregnancy.
A significant mean reduction in daily caffeinated drinks (estimate [EST] = −0.52; 95% confidence interval [CI], −0.70 to −0.33) was observed when compared to baseline usage. Intention to change was associated with a reduction in caffeinated drinks (EST = −0.32; 95% CI, −0.64 to 0.00), and with alcohol and cigarette usage from the first menstrual cycle (EST = −0.15; 95% CI, −0.28 to −0.02 and EST = −1.65; 95% CI, −3.12 to −0.19, respectively).
A reduction in daily caffeine intake while attempting pregnancy was observed, but not in alcohol or cigarette use, underscoring the need for preconception guidance.
Healthy lifestyles during pregnancy are recognized to be positively associated with pregnancy outcomes for both mothers and offspring, and have become embedded in effective prenatal care guidance. Of late, discussion has arisen about the need for preconception guidance in light of growing recognition regarding the importance of environmental exposures including lifestyle during the preconception window for a spectrum of sensitive reproductive and developmental endpoints. Despite little prospective information on what women actually do while attempting to become pregnant possibly reflecting the limited number of prospective cohort studies conducted worldwide, support for preconception guidance continues to grow. With the possible exception of folate supplementation or care of diabetic women, there has been little systematic implementation into clinical practice. A recent Cochrane Review noted the absence of randomized trials to assess the effect of preconception advice on fertility outcomes.
At the population level, the US Centers for Disease Control and Prevention released preconception recommendations to increase awareness of healthy lifestyles and to cease risky behaviors (eg, use of alcohol, caffeine, and cigarettes). While some observational studies have shown that women adopt healthy behaviors during pregnancy, only a few have examined women’s behaviors while trying to become pregnant and these relied upon retrospective reporting by women after delivery despite the modest validity of such information. In response to these critical data gaps, we prospectively assessed women’s use of cigarettes, alcohol, and caffeine during the preconception period, particularly in relation to their intentions to modify behavior given their interest in becoming pregnant. We focused on these specific lifestyle behaviors because of their purported role in increasing the time required for conception and other adverse perinatal outcomes.
Materials and Methods
Investigators targeted women who had participated in a cohort focusing on fish consumption and adverse pregnancy outcomes to identify those planning pregnancy, consistent with the intention to recruit women who would be trying to become pregnant. Eligibility criteria included aged 18-34 years and no self-reported history of fecundity impairments or infertility. Of the 244 eligible women, 113 (46%) agreed to participate in this prospective pregnancy study and discontinued contraception with the intention of becoming pregnant in the next 6 months. Fourteen (12%) women were excluded because they were found to be pregnant during enrollment.
A research nurse conducted a standardized interview in the women’s homes to ascertain sociodemographic information; reproductive and medical history; and average usage of alcohol, cigarettes, and caffeine during the past 12 months or prior to attempting pregnancy along with intentions to change each of these 3 behaviors while trying to become pregnant. We calculated body mass index (BMI) (kg/m 2 ) from self-reported height and weight. For baseline consumption, participants reported the daily average number of cigarettes smoked and daily average number of servings of caffeinated (coffee, tea, and soft drinks) drinks over the past year. Alcohol use was ascertained in a 2-part question comprising how many occasions per month the participant drank on average in the past year, and how many alcoholic beverages (beer, wine, wine coolers, and liquor) per occasion. For consistency in scale, we converted these answers to the daily number of alcoholic drinks by multiplying the number of occasions per month by the number of drinks per occasion and dividing by 28, as the women were likely approximating a month by 4 weeks. To measure baseline intentions for changing (or not) each behavior, the nurse asked participants, “Have you changed (or do you plan to change) your (cigarettes/alcohol/caffeine) consumption (type of beverage, frequency, or amount) in anticipation of becoming pregnant?” Participants were given the following response options: “yes, abstain now,” “yes, drink less now,” “plan to change but haven’t yet,” “no,” or “never (smoked/drank).” In this analysis, we dichotomized intent by grouping the former 3 responses into “intend to change” and the latter 2 responses into “do not intend to change.” Not all abstainers, defined as such by baseline consumption or intention, refrained from consumption while attempting pregnancy, thereby necessitating their inclusion in the latter category.
Women completed daily diaries and recorded the number of cigarettes smoked and the number of alcoholic and caffeinated beverages consumed while trying to become pregnant. The women were followed up prospectively until a positive home pregnancy test conducted on the expected date of menstruation or up to 12 menstrual cycles at risk for pregnancy. A few couples informed the study that they had paused trying for reasons such as unemployment or birth month preference. These non-at risk cycles were excluded irrespective of reason. Full human subject approval was awarded, and all participants gave informed consent prior to enrollment.
We defined menstrual cycles using bleeding reported in the daily diaries, with the first day of menses corresponding to the first day of the cycle. The first day of menses was designated by a day of bleeding or spotting followed within 1 day by at least 2 additional days of bleeding or spotting. We calculated average daily consumption for each cycle by summing the number of cigarettes smoked or the number of alcoholic or caffeinated beverages consumed as recorded for the cycle and then dividing by the number of diary entries in that cycle. The primary outcome, change in consumption relative to baseline, was calculated as the difference between the average daily consumption in a cycle and the daily baseline consumption. This continuous value was computed for each cycle, with up to 12 measurements (menstrual cycles) per woman for a total of 459 cycles. To assess the effects of reporter bias at baseline, change in consumption was also determined relative to average daily consumption observed in the first trying cycle. For the women who completed at least 2 cycles, this value was calculated for each cycle with a maximum of 11 measurements (menstrual cycles) per woman for a total of 369 cycles. Once a woman withdrew or conceived, the values of change in consumption for subsequent cycles were missing. For both measurements, a negative value of change indicated a decrease in consumption whereas a positive value denoted an increase; 95% confidence intervals (CIs) were calculated for assessing statistical significance.
We compared baseline characteristics by intention to change using χ 2 or Fisher’s exact test when cell counts were small. We modeled the mean change in consumption and the association between mean change and determinants including intent to change using linear regression with the generalized estimating equations method for correlated outcomes via PROC GENMOD in SAS software (version 9.1; SAS Institute Inc, Cary, NC). We assumed that the correlation between outcomes from the same woman was a function of time between observations; thus, we chose an M-dependent or autoregressive working correlation structure, and we used robust SE for inference. Since the women did not record daily consumption following pregnancy, we conducted a sensitivity analysis to assess the effects of dropout bias. In this analysis, we used a last observation carried forward (LOCF) approach, replacing the missing values due to attrition with the last observed change in consumption and repeating the analysis.
The women were highly compliant with 91% submitting daily diaries, resulting in a final cohort of 90 women contributing 459 cycles for analysis. The cohort comprised mostly college-educated (66%), employed (76%), married (98%), parous (70%) women self-defined as of white non-Hispanic ethnicity (100%). Seventy-three percent of the women conceived during the study while 14% withdrew after submitting some diary data and 12% did not conceive. At baseline, the majority of women reported consuming alcohol (84%) and caffeinated beverages (94%), although few smoked cigarettes (17%). Most women reported planning to change or refrain from these behaviors while attempting to become pregnant.
For the purpose of determining what risk factors were important to consider in later analyses, Table 1 demonstrates subgroups of women who were more likely to report intentions to change usage at baseline. Overall, few differences in distribution of intent between strata were observed save for overweight women who reported fewer intentions to change any behavior. Nulliparous women were more likely to report intentions to change alcohol and caffeine use than parous women. Intent to change also seemed to be dependent upon baseline consumption; medium to heavier users were more likely to report intending to change than women abstaining or engaging less frequently in a behavior. For cigarette consumption, a difference in education was observed with college-educated women less likely to report an intention to change than women with lower educational attainments. This difference is possibly due to the large amount of abstainers who reported no intention to change.
|Intend to change alcohol use||Intend to change cigarette use||Intend to change caffeine use|
|Characteristic||No %||Yes %||No %||Yes %||No %||Yes %|
|BMI, kg/m 2|
|Underweight (BMI <18.5)||25||75 a||50||50||25||75|
|Normal (18.5 ≤ BMI <25)||24||76||84||16||40||60|
|Overweight (BMI ≥25)||45||55||84||16||48||52|
|No||15||85 a||95||5 a||25||75 a|
|Previous spontaneous pregnancy loss|
|Previous live birth|
|No||11||89 b||81||19||19||81 b|
|Baseline alcohol (no. monthly drinks)|
|0||93||7 c||100||0||36||64 c|
|Baseline cigarettes (no. daily)|
|Baseline caffeinated drinks (no. daily)|