Abstract
Objective
To investigate the association of healthy lifestyle factors before conception (BMI=18.5–24.9 kg/m2, non-smoking, ≥150 minutes/week of moderate to vigorous physical activity, healthy eating [top 40% of Dietary Approaches to Stop Hypertension score], none or low-to-moderate alcohol intake [<15 g/day], and use of multivitamins) with risk of adverse pregnancy outcomes (APOs).
Methods
We conducted a secondary analysis of prospectively collected data for women without chronic diseases who are participating in an ongoing cohort in the United States, the Nurses’ Health Study II. Healthy lifestyle factors preceding pregnancy were prospectively assessed every 2–4 years from 1991 to 2009, using validated measures. Reproductive history was self-reported in 2001 and 2009. A composite outcome of APOs including miscarriage, ectopic pregnancy, gestational diabetes, gestational hypertension, preeclampsia, preterm birth, stillbirth, or low birthweight was assessed.
Results
Overall 15,509 women with 27,135 pregnancies were included. The mean maternal age was 35.1±4.2 years. Approximately one in three pregnancies (N=9,702, 35.8%) were complicated with one or more APO. The combination of 6 low-risk factors was inversely associated with risk of APOs, in a dose-dependent manner (P trend<0.001). Compared with women who had 0 or 1 healthy lifestyle factors, those with 6 had a 37% lower risk of APOs (RR=0.63, 95% CI=0.55–0.72), primarily driven by lower risks of gestational diabetes, gestational hypertension, and low birthweight. All prepregnancy healthy lifestyle factors, except avoiding harmful alcohol consumption and regular physical activity, were independently associated with lower risk of APOs after mutual adjustment for each other. Healthy BMI, high-quality diet, and multivitamin supplementation showed the strongest inverse associations with APOs. If the observed relationships were causal, 19% of APOs could have been prevented by the adoption of all 6 healthy lifestyle factors (population attributable risk=19%, 95% CI=13%–26%).
Conclusion
Preconception healthy lifestyle is associated with a substantially lower risk of APOs and could be an effective intervention for the prevention of APOs.
Précis:
Adherence to a prepregnancy healthy lifestyle, including normal body mass index, never smoking, healthy diet, moderate alcohol consumption, regular exercise, and multivitamin supplement, was associated with a significantly lower risk of adverse pregnancy outcomes.
Introduction
Major adverse pregnancy outcomes (APOs), including hypertensive disorders of pregnancy (HDP), preterm delivery, or low birthweight (LBW), affect approximately 20% of pregnancies in the United States.1 APOs are not only associated with higher risk of pregnancy-related mortality in the short-term, but also with the development of chronic non-communicable diseases and premature mortality in the long-term.2-5 Moreover, children born to a pregnancy affected by APOs have higher risk of metabolic, immune, and cognitive disorders.6,7
Based on evidence that several lifestyle factors are associated with a lower risk of one or more APOs,8-10 both the World Health Organization (WHO) and the American College of Obstetricians and Gynecologists (ACOG) recommend the adoption of a healthy lifestyle before conception with the goal of improving pregnancy outcomes.8,9 While specifics differ, recommendations from both organizations include abstinence from substance use (including tobacco and harmful use of alcohol), achieving and maintaining a body mass index (BMI) within a normal range, engaging in ≥150 minutes of moderate exercise per week, adhering to a healthy and balanced diet, and multivitamin supplementation.8,9 However, some of these recommendations are not sufficiently specific or may not be uniformly beneficial across maternal and neonatal outcomes. Moreover, the joint association of these lifestyle factors with pregnancy health is unknown. To fill this knowledge gap, we examined the individual and joint associations of pre-pregnancy lifestyle characteristics with risk of APOs, leveraging data from a large longitudinal cohort, the Nurses’ Health Study II (NHSII).
Methods
The current study is a secondary analysis of a prospective study cohort, the NHSII, which was established in 1989, when 116,429 female nurses aged 25–42 years residing in the United States enrolled.11 Biennial follow-up questionnaires were mailed to update demographic, reproductive, lifestyle, and medical information. Response rate to each follow-up cycle exceeds 85%. The study was approved by the Institutional Review Board of Brigham and Women’s Hospital. Return of questionnaires implied informed consent.
Follow-up for the current study started in 1991, when diet was first assessed, and ended in 2009, when pregnancy history was last assessed because the youngest participants (aged 45 years) had likely completed their reproductive years. Participants who responded to the 2009 pregnancy history questionnaire (n=90,475) were similar to those who did not (n=25,937) in demographics and reproductive factors, but were more likely to be never smokers and had lower levels of BMI and physical activity (Appendix 1, available online at http://links.lww.com/xxx). A total of 20,017 women reported one or more pregnancies between 1991 and 2009 (35,630 pregnancies in total). We excluded pregnancies missing birth year (n=1,035), with implausible or missing gestational weeks (n=65), missing pregnancy outcomes (n=183), ending in induced abortion (n=1,165), or with incomplete information about prepregnancy lifestyle factors (n=4,410). We further excluded 1,637 pregnancies from women with a pre-pregnancy history of diabetes, cancer, hypertension, or other cardiovascular diseases, leaving 15,509 women (27,135 pregnancies, including 513 multi-fetal pregnancies) in the analytic sample.
Healthy lifestyle factors
Six potentially modifiable lifestyle factors were assessed: BMI, smoking, physical activity, diet, alcohol consumption, and multivitamin use. We used the most recent assessment of each lifestyle factor preceding each pregnancy. Height was self-reported at cohort enrollment. Weight was queried every two years and BMI was calculated as weight/(height)2 (kg/m2). Smoking status was updated on each follow-up questionnaire and characterized as current smoking versus not. Self-reported weight, height and smoking have been validated in this cohort.12,13 Physical activity in the past year was assessed using a validated questionnaire in 1989 and every 4 years thereafter, querying the average time spent in moderate to vigorous recreational activities.14 Past-year diet was measured every 4 years since 1991, using a validated semiquantitative food frequency questionnaire (FFQ).15-18 We used the Dietary Approaches to Stop Hypertension (DASH) diet score to characterize prepregnancy diet quality (higher scores indicating healthier diets).19,20 Alcoholic beverage consumption and multivitamin supplementation was also assessed with the FFQ.
Healthy lifestyle score
We defined six healthy lifestyle factors as binary variables: healthy BMI (18.5–24.9 kg/m2), not currently smoking, ≥150 minutes/week of moderate to vigorous physical activity, healthy eating (top 40% of DASH score), no or low-to-moderate alcohol intake (<15 g/day), and use of multivitamins, based on prepregnancy guidelines or prior evidence if cut-offs were not specified in guidelines.8,9,20,21 The healthy lifestyle score was the number of healthy lifestyle factors each participant met (0–6). Because only 8 women had a score of 0, women with 0 or 1 factors were combined in analyses.
Pregnancy outcomes
In 2001 and 2009, women were queried about their lifetime pregnancy history, including year of birth, pregnancy outcome (single live birth, twins/triplets+, miscarriage/stillbirth, induced abortion, tubal or ectopic), gestation length (used to derive preterm birth), birthweight of the newborn(s), and pregnancy related complications after 20 weeks of gestation (“Did you have any of these complications related to pregnancy or lactation? [Mark all that apply]”: gestational diabetes (GDM), pregnancy-related high blood pressure (gestational hypertension, GHTN), preeclampsia/toxemia). Self-report of APOs (e.g., GDM, GHTN, preeclampsia, birthweight, and preterm birth) have been validated against medical records in this cohort.22-26 Miscarriage, ectopic pregnancy, and stillbirth have not been validated in this cohort but external validation studies showed moderate to high validity.27-29 The primary outcome was a composite outcome of any APOs (miscarriage, ectopic pregnancy, GDM, GHTN, preeclampsia, preterm birth, stillbirth, or LBW (<5.5 lbs); the secondary outcomes were individual APO. A pregnancy was considered to be complicated with preeclampsia but not GHTN if both were reported for the same pregnancy.
For primary analyses, to examine the relationship between healthy lifestyle and overall pregnancy health, we included all eligible pregnancies. In an additional analysis, we included only 21,516 pregnancies (from 14,284 women) that lasted for 20 weeks or more, and the composite outcome was restricted to APOs that are usually only diagnosed after 20 weeks’ gestation (GDM, GHTN, preeclampsia, preterm birth, LBW, and stillbirth).
Covariates
Date of birth and race and ethnicity were self-reported at enrollment. Race and ethnicity information was included because its known associations with both the exposure and outcome.10 Gravidity, parity, and interpregnancy intervals were derived from pregnancy history reports. History of infertility (failure to achieve pregnancy after 12 months of attempt) was asked in 1989 and updated biennially. History of ovulation induction treatment (clomiphene and/or gonadotrophins) was queried on biennial questionnaires starting 1993 and in vitro fertilization (IVF) cycles was queried on 2009 questionnaire. Partner’s education attainment was reported in 1999. Census tract median income and tract % with bachelor’s degree or higher was assessed in 2009.
Statistical analysis
We first compared the distribution of prepregnancy maternal characteristics of each pregnancy according to the healthy lifestyle score. In addition, we compared the prevalence of healthy lifestyle factors in our study population with those in the nationally representative National Health and Nutrition Examination Survey (NHANES) in a comparable study period (2003–2004). Missingness of all covariates was <4%. A missing indicator was created for categorical variables.
To estimate the relative risks (RRs) and 95% confidence interval (CIs) for the associations between healthy lifestyle score and risk of APOs, we used generalized estimating equation Poisson models, adjusting for age (years), race and ethnicity (non-Hispanic White, additional races and ethnicities), year of birth (calendar year), history of infertility (yes, no), parity (0, 1, ≥2), and interpregnancy interval (nulligravid, 0–1 year, ≥2 years). An exchangeable covariance structure was specified to account for correlated responses within pregnancies from the same mother. We also examined the RR and 95% CI of APOs in relation to each of the individual healthy lifestyle factors, including a model adjusting for all lifestyle factors. In addition, assuming the observed relationships were causal, we calculated the population attributable risk percentage (PAR) to estimate the proportion of APOs in this study population that could have been prevented if all participants were in the low-risk group using the adjusted RR. To reflect the current trends of lifestyle, we also calculated the PAR using the prevalence of healthy lifestyle factors from recent NHANES data (2017–2018).
To explore potential heterogeneity in the associations between healthy lifestyle score and APOs, we stratified analyses by maternal age, parity, and pre-pregnancy BMI (BMI was excluded from the healthy lifestyle score). We also examined whether the associations differed before and after 1998, when fortification of the US food supply with folic acid came into effect. We conducted seven sensitivity analyses: included 1384 women with preexisting chronic conditions; included 921 pregnancies ending in induced abortion; excluded alcohol intake from the healthy lifestyle score due to concerns of detrimental effects on fetal neurodevelopment;30 further adjusted for total calorie intake; restricted analysis to singleton pregnancies; further adjusted for sociodemographic factors, including partner’s education attainment, census tract median income and tract % with bachelor’s degree or higher; and further adjusted for infertility treatment. Analyses were conducted in SAS 9.4 (SAS Inc.); all statistical tests were two-sided.
Results
The 15,509 women included in the analysis were predominantly non-Hispanic White (95.4%) and the mean maternal age was 34.8±4.2. The median number of healthy prepregnancy lifestyle factors was 4 (interquartile range: 3–5). Greater adherence to healthy prepregnancy lifestyle factors was associated with higher total calorie intake and lower history of infertility (Table 1). Healthy lifestyle factors were weakly correlated with each other (−0.04 < phi coefficient <0.17, Appendix 2 [Appendix 2 is available online at http://links.lww.com/xxx]). In addition, during 2003–2004, the prevalence of low-risk factors was comparable with that from nationally representative data, except that NHSII participants were less likely to be overweight or current smokers and used more multivitamins (Appendix 3, available online at http://links.lww.com/xxx).
Table 1.
Age-standardized pre-pregnancy characteristics by number of healthy lifestyle factors, the Nurses’ Health Study II (NHSII), 1991–2009, 27135 pregnancies from 15509 women
| Characteristics | Healthy lifestyle score | |||||
|---|---|---|---|---|---|---|
| Women | 0 or 1 (n=232, 1.5%) |
2 (n=1573, 10.1%) |
3 (n=4174, 26.9%) |
4 (n=4988, 32.2%) |
5 (n=3362, 21.7%) |
6 (n=1180, 7.6%) |
| Race, n (%) | ||||||
| American Indian/Alaska Native | 1 (0.4) | 4 (0.3) | 16 (0.4) | 15 (0.3) | 10 (0.3) | 3 (0.3) |
| Asian | 0 (0) | 13 (0.8) | 77 (1.8) | 77 (1.5) | 54 (1.6) | 19 (1.6) |
| Black or African American | 3 (1.3) | 15 (1.0) | 40 (1.0) | 36 (0.7) | 20 (0.6) | 7 (0.6) |
| Hispanic | 3 (1.3) | 32 (2.0) | 82 (2.0) | 92 (1.8) | 54 (1.6) | 23 (2.0) |
| Native Hawaiian or Pacific Islander | 0 (0) | 1 (0.1) | 5 (0.1) | 8 (0.2) | 7 (0.2) | 2 (0.2) |
| Non-Hispanic White | 225 (97.0) | 1508 (95.9) | 3954 (94.7) | 4760 (95.4) | 3217 (95.7) | 1126 (95.4) |
| Pregnancies | 0 or 1 (n=280, 1.0%) |
2 (n=2111, 7.8%) |
3 (n=6176, 22.8%) |
4 (n=8811, 32.5%) |
5 (n=6921, 25.5%) |
6 (n=2836, 10.5%) |
| Age, mean±SD, years* | 35.2±4.0 | 35.2±4.3 | 35.1±4.2 | 35±4.1 | 35±4.1 | 35.2±4.2 |
| Body mass index, mean±SD, kg/m2 | 28.1±5.2 | 27.1±5.9 | 24.8±5.1 | 23.2±3.9 | 22.1±2.8 | 21.5±1.7 |
| Smoking status, n (%) | ||||||
| Never | 25 (8.9) | 1125 (53.3) | 4355 (70.5) | 6682 (75.8) | 5286 (76.4) | 2197 (77.5) |
| Past | 13 (4.6) | 359 (17.0) | 1216 (19.7) | 1766 (20.0) | 1564 (22.6) | 639 (22.5) |
| Current | 242 (86.5) | 627 (29.7) | 606 (9.8) | 363 (4.1) | 71 (1.0) | 0 (0.0) |
| Moderate to vigorous physical activity, mean±SD, min/week | 32.2±76.4 | 42.7±82.4 | 68.3±136.8 | 131.9±206.2 | 242.1±287.2 | 386.0±312.0 |
| DASH score, mean±SD | 19.6±3.5 | 20.4±3.6 | 21.7±3.9 | 23.8±4.5 | 26.8±4.3 | 29.4±2.7 |
| Alcohol intake, mean±SD, g/day | 8.7±11.3 | 3.9±7.6 | 2.9±5.5 | 2.6±4.6 | 2.8±4.4 | 2.7±3.5 |
| Multivitamin use, n (%) | 9 (3.3) | 241 (11.4) | 2313 (37.5) | 5954 (67.6) | 5788 (83.6) | 2836 (100.0) |
| Total calorie intake, mean±SD, calories | 1820.7±554.3 | 1731.9±527.7 | 1782.6±544.0 | 1839.6±560.7 | 1936.1±540.4 | 2022.9±511.1 |
| Parity, mean±SD | 1±1 | 1.4±1.2 | 1.3±1.2 | 1.3±1.2 | 1.2±1.1 | 1.1±1.1 |
| History of infertility, n (%)† | 79 (28.2) | 550 (26.1) | 1597 (25.9) | 2116 (24.0) | 1655 (23.9) | 612 (21.6) |
| Infertility treatment, n (%)‡ | 33 (11.8) | 306 (14.5) | 922 (14.9) | 1269 (14.4) | 1027 (14.8) | 374 (13.2) |
| Interpregnancy interval, n (%) | ||||||
| Nulligravid | 58 (20.6) | 314 (14.9) | 971 (15.7) | 1379 (15.7) | 1217 (17.6) | 545 (19.2) |
| 0–1 year | 39 (13.8) | 297 (14.1) | 1029 (16.7) | 1573 (17.8) | 1239 (17.9) | 502 (17.7) |
| ≥ 2 years | 184 (65.6) | 1500 (71.0) | 4176 (67.6) | 5859 (66.5) | 4465 (64.5) | 1789 (63.1) |
| Census tract median household income, mean±SD, USD | 63224±23541 | 66298±23448 | 69496±24689 | 71521±25128 | 74438±26067 | 75731±26589 |
| Census tract % population with bachelor’s degree or higher, mean±SD | 28.5±14.9 | 31.3±16.9 | 33.6±17.7 | 35.6±17.9 | 38.3±17.9 | 40.0±18.2 |
| Partner’s education ≤high school, n (%) | 45 (16.1) | 355 (16.8) | 830 (13.4) | 913 (10.4) | 505 (7.3) | 203 (7.2) |
Healthy lifestyle score includes healthy BMI (18.5–24.9 kg/m2), not currently smoking, ≥150 minutes a week of moderate to vigorous physical activity, healthy diet (top two fifths of Dietary Approaches to Stop Hypertension (DASH) score), low-to-moderate alcohol consumption (<15 g/day), and use of multivitamin.
Values of polytomous variables may not sum to 100% due to rounding.
Value is not age adjusted; all other variables are standardized to the age distribution of the study population.
Defined as failure to get pregnant after 12 months of trying.
Defined as ever receiving treatment including the use of clomiphene, gonadotropin, IUI, and IVF.
About one in three pregnancies (n=9,702, 35.8%) were complicated with one or more APO (Appendix 4, available online at http://links.lww.com/xxx). The most common APO was miscarriage (n=5,228, 19.3%); and among pregnancies ≥20 weeks’ gestation, preterm birth (n=1,862, 8.7%) and GDM (n=1,209, 5.6%). We observed an inverse relationship between healthy prepregnancy lifestyles and risk of APOs (Figure 1, P trend<0.001). Compared with women who adhered to 1 or fewer healthy lifestyle factors, those who engaged in 6 had a 37% lower risk of APOs (RR=0.63, 95% CI=0.55–0.72). The association was somewhat stronger when restricting the analysis to pregnancies ≥20 weeks’ gestation (RR=0.55, 95% CI=0.44–0.69). The corresponding RRs (comparing women with 6 healthy lifestyle factors with those who had 0 or 1) for having two or more APO was 0.44 (95% CI=0.28–0.69). Overall, healthy lifestyle score was inversely related to each APO (all P trend<0.05), with stronger relationships with GDM, GHTN, and LBW (Figure 2).
Figure 1.
Prepregnancy healthy lifestyle score and risk of adverse pregnancy outcomes throughout pregnancy (27,135 pregnancies from 15,509 women) (A) and after gestational week 20 (21,516 pregnancies from 14,284 women) (B), the Nurses’ Health Study II, 1991–2009. Healthy lifestyle score includes healthy body mass index (18.5–24.9 kg/m2), not currently smoking, ≥150 minutes a week of moderate to vigorous physical activity, healthy diet (top two-fifths of Dietary Approaches to Stop Hypertension score), low-to-moderate alcohol consumption (<15 g/day), and use of multivitamin. A. Adverse pregnancy outcomes included miscarriage, ectopic pregnancy, gestational diabetes, hypertensive disorders of pregnancy (gestational hypertension and preeclampsia), preterm birth, stillbirth, and low birthweight. B. Adverse pregnancy outcomes included gestational diabetes, hypertensive disorders of pregnancy (gestational hypertension and preeclampsia), preterm birth, stillbirth, and low birthweight. Multivariable log-Poisson regression models with generalized estimating equations were used to estimate relative risks and 95% CIs, adjusting for maternal age, race and ethnicity, year of birth, history of infertility, parity, and interpregnancy interval. P for trend <.001 for A and B.
Figure 2.
Prepregnancy healthy lifestyle score and risk of common adverse pregnancy outcomes throughout pregnancy, the Nurses’ Health Study II, 1991–2009. Miscarriage (P for trend <.001) (A), gestational hypertension (P for trend <.001) (B), preeclampsia (P for trend <.001) (C), gestational diabetes (P for trend <.001) (D), preterm birth (P for trend =.02) (E), and low birthweight (P for trend =.001) (F). Miscarriage analysis was conducted among all pregnancies (27,135 pregnancies from 15,509 women). Gestational hypertension, preeclampsia, gestational diabetes, preterm birth, and low birthweight analyses were conducted among pregnancies reached 20 weeks of gestation only (21,516 pregnancies from 14,284 women). Only pregnancy complications with a prevalence >2% were presented. Healthy lifestyle score includes healthy body mass index (18.5–24.9 kg/m2), not currently smoking, ≥150 minutes a week of moderate to vigorous physical activity, healthy diet (top two-fifths of Dietary Approaches to Stop Hypertension score), low-to-moderate alcohol consumption (<15 g/day), and use of multivitamin. Multivariable log-Poisson regression models with generalized estimating equations were used to estimate relative risks and 95% CIs, adjusting for maternal age, race and ethnicity, year of birth, history of infertility, parity, and interpregnancy interval.
Each prepregnancy healthy lifestyle factor was associated with lower risk of APOs in a dose-dependent manner (Table 2). After co-adjustment for all other prepregnancy lifestyle factors, physical activity was no longer associated with risk of APOs. Similarly, after co-adjustment, alcohol intake was not associated with risk of APOs for all pregnancies but remained associated with a lower risk of APOs for pregnancies reaching 20 weeks’ gestation, whereas the opposite was observed for multivitamin use (Table 2). A similar pattern was observed when investigating APOs in relation to healthy lifestyle factors as binary variables (Appendixes 5 and 6, available online at http://links.lww.com/xxx). When each healthy prepregnancy lifestyle factor was evaluated in relation to individual APOs (Figure 3), optimal body weight, non-smoking, and healthy diet were associated with lower risk of most APOs, while low-to-moderate alcohol intake was not associated with risk of any APOs. Physical activity was only associated with lower risk of GDM and GHTN. Multivitamin supplementation was protective against miscarriage and LBW.
Table 2.
Pre-pregnancy healthy lifestyle factors and risk of adverse pregnancy outcomes throughout pregnancy and after 20 weeks’ gestation, the Nurses’ Health Study II (NHSII), 1991–2009
| Healthy lifestyle | All pregnancies* (27135 pregnancies from 15509 women) |
Pregnancies ≥20 gestational weeks† (21516 pregnancies from 14284 women) |
||||
|---|---|---|---|---|---|---|
| Cases/ Total pregnancies |
Model 1, multivariable adjusted |
Model 2, with additional mutual adjustment |
Cases/ Total pregnancies |
Model 1, multivariable adjusted |
Model 2, with additional mutual adjustment |
|
| RR (95% CI) | RR (95% CI) | |||||
| Body mass index, kg/m2 | ||||||
| <18.5 | 307/1052 | 0.92 (0.84–1.02) | 0.93 (0.85–1.03) | 120/862 | 0.86 (0.72–1.02) | 0.86 (0.73–1.02) |
| 18.5–24.9 | 6336/19134 | 1.0 [reference] | 1.0 [reference] | 2626/15349 | 1.0 [reference] | 1.0 [reference] |
| 25–29.9 | 1994/4778 | 1.23 (1.18–1.28) | 1.22 (1.17–1.27) | 912/3678 | 1.44 (1.34–1.54) | 1.42 (1.32–1.52) |
| 30–34.9 | 676/1450 | 1.36 (1.28–1.45) | 1.34 (1.26–1.42) | 337/1109 | 1.74 (1.57–1.92) | 1.68 (1.52–1.86) |
| ≥35 | 389/721 | 1.49 (1.39–1.61) | 1.46 (1.35–1.58) | 188/518 | 2.03 (1.79–2.29) | 1.92 (1.69–2.18) |
| P trend | <0.001 | <0.001 | <0.001 | <0.001 | ||
| Smoking | ||||||
| Never | 6875/19668 | 1.0 [reference] | 1.0 [reference] | 3001/15722 | 1.0 [reference] | 1.0 [reference] |
| Past | 2037/5558 | 1.00 (0.96–1.04) | 0.99 (0.95–1.04) | 825/4328 | 0.97 (0.90–1.05) | 0.98 (0.91–1.06) |
| Current | 790/1909 | 1.16 (1.09–1.23) | 1.11 (1.05–1.18) | 357/1466 | 1.20 (1.08–1.33) | 1.15 (1.04–1.28) |
| P trend | <0.001 | 0.01 | 0.02 | 0.04 | ||
| Moderate and vigorous physical activity, min/week | ||||||
| 0–29.9 | 3159/8755 | 1.0 [reference] | 1.0 [reference] | 1395/6952 | 1.0 [reference] | 1.0 [reference] |
| 30–89.9 | 2101/5845 | 1.00 (0.95–1.05) | 1.02 (0.98–1.07) | 903/4623 | 0.96 (0.89–1.04) | 1.00 (0.92–1.08) |
| 90–149.9 | 691/1906 | 1.00 (0.94–1.07) | 1.05 (0.98–1.12) | 302/1510 | 0.97 (0.87–1.09) | 1.05 (0.94–1.17) |
| 150–299.9 | 1868/5262 | 0.97 (0.92–1.02) | 1.02 (0.97–1.07) | 781/4163 | 0.89 (0.82–0.97) | 0.97 (0.90–1.06) |
| ≥300 | 1883/5367 | 0.94 (0.90–0.99) | 1.01 (0.96–1.06) | 802/4268 | 0.87 (0.81–0.95) | 0.98 (0.90–1.07) |
| P trend | 0.008 | 0.66 | <0.001 | 0.51 | ||
| Diet (DASH) | ||||||
| Q1 | 2359/6173 | 1.0 [reference] | 1.0 [reference] | 1080/4877 | 1.0 [reference] | 1.0 [reference] |
| Q2 | 2007/5573 | 0.92 (0.88–0.97) | 0.95 (0.90–0.99) | 865/4413 | 0.88 (0.81–0.95) | 0.91 (0.84–0.99) |
| Q3 | 1379/3996 | 0.88 (0.84–0.93) | 0.91 (0.86–0.97) | 611/3214 | 0.85 (0.78–0.93) | 0.89 (0.81–0.97) |
| Q4 | 1939/5570 | 0.88 (0.84–0.93) | 0.93 (0.88–0.97) | 813/4422 | 0.81 (0.75–0.89) | 0.87 (0.79–0.94) |
| Q5 | 2018/5823 | 0.86 (0.82–0.90) | 0.91 (0.86–0.96) | 814/4590 | 0.78 (0.72–0.85) | 0.85 (0.78–0.93) |
| P trend | <0.001 | <0.001 | <0.001 | <0.001 | ||
| Alcohol consumption, g/day | ||||||
| 0 | 3920/11253 | 1.0 [reference] | 1.0 [reference] | 1801/9095 | 1.0 [reference] | 1.0 [reference] |
| 0.1-4.9 | 3909/10817 | 1.00 (0.97–1.04) | 1.01 (0.97–1.05) | 1643/8498 | 0.93 (0.87–0.99) | 0.96 (0.90–1.02) |
| 5.0-14.9 | 1580/4292 | 0.97 (0.93–1.02) | 0.99 (0.94–1.04) | 629/3335 | 0.86 (0.79–0.94) | 0.92 (0.84–1.00) |
| 15.0-29.9 | 231/594 | 0.97 (0.87–1.08) | 0.98 (0.88–1.10) | 85/447 | 0.82 (0.67–1.00) | 0.87 (0.71–1.06) |
| ≥30 | 62/179 | 0.87 (0.70–1.08) | 0.83 (0.67–1.04) | 25/141 | 0.79 (0.55–1.12) | 0.77 (0.54–1.10) |
| P trend | 0.19 | 0.35 | <0.001 | 0.007 | ||
| Multivitamin use, times/week‡ | ||||||
| 0 | 3733/9992 | 1.0 [reference] | 1.0 [reference] | 1523/7749 | 1.0 [reference] | 1.0 [reference] |
| 1-2 | 719/1869 | 0.97 (0.91–1.03) | 0.99 (0.93–1.05) | 291/1433 | 0.98 (0.88–1.09) | 1.02 (0.91–1.14) |
| 3-5 | 1451/4003 | 0.94 (0.89–0.99) | 0.96 (0.91–1.00) | 590/3123 | 0.96 (0.88–1.04) | 0.99 (0.91–1.07) |
| ≥6 | 3760/11161 | 0.86 (0.83–0.89) | 0.88 (0.85–0.91) | 1758/9119 | 0.93 (0.88–0.99) | 0.97 (0.92–1.03) |
| P trend | <0.001 | <0.001 | 0.02 | 0.29 | ||
DASH, Dietary Approaches to Stop Hypertension (higher score indicates healthier diet). Q, quintile.
Adverse pregnancy outcomes included miscarriage, ectopic pregnancy, gestational diabetes, hypertensive disorders of pregnancy (gestational hypertension and preeclampsia), preterm birth, stillbirth, and low birthweight.
Adverse pregnancy outcomes included gestational diabetes, hypertensive disorders of pregnancy (gestational hypertension and preeclampsia), preterm birth, stillbirth, and low birthweight.
96 participants reported use of multivitamin but did not report frequency of multivitamin use were excluded from this analysis.
Multivariable log-Poisson regression models with generalized estimating equations were used to estimate RRs and 95% CIs. Model 1: adjusted for age, race and ethnicity, year of birth, history of infertility, parity, and interpregnancy interval. Model 2: Model 1 + mutual adjustment for other healthy lifestyle factors in the table.
P trend tests were conducted treating indicator levels as continuous variables.
Figure 3.
Prepregnancy healthy lifestyle factors and risk of common adverse pregnancy outcomes throughout pregnancy, the Nurses’ Health Study II, 1991–2009. Body mass index (BMI) 18.5–24.9 kg/m2 (A), current nonsmoker (B), moderate to vigorous exercise >150 minutes a week (C), healthy diet (D), alcohol intake <15 g/day (E), and multivitamin supplement (F). Miscarriage analysis was conducted among all pregnancies (27,135 pregnancies from 15,509 women). Gestational hypertension, preeclampsia, gestational diabetes, preterm birth, and low birthweight analyses were conducted among pregnancies reached 20 weeks of gestation only (21,516 pregnancies from 14,284 women). Only pregnancy complications with a prevalence >2% were presented. BMI calculated as weight in kilograms divided by height in meters squared, kg/m2. Healthy diet defined as top two-fifths of Dietary Approaches to Stop Hypertension score. Multivariable log-Poisson regression models with generalized estimating equations were used to estimate relative risks and 95% CIs, adjusting for maternal age, race and ethnicity, year of birth, history of infertility, parity, interpregnancy interval, and other lifestyle factors in the figure.
The associations persisted within strata of maternal age (<35, ≥35 years), parity (nulliparous, parous), pre-pregnancy BMI (<25, ≥25 kg/m2), and folic acid fortification (year of birth: 1998 and before, after 1998; Appendix 7 [Appendix 7 is available online at http://links.lww.com/xxx]). Results were also comparable in sensitivity analyses including women with a history of chronic diseases at baseline; including pregnancies that ended in induced abortion; excluding alcohol intake from the healthy lifestyle score; additionally adjusting for total calorie intake; including only singleton pregnancies in the analysis; further adjusting for socioeconomic factors; or additionally adjusting for history of infertility treatment (Appendixes 8 and 9, available online at http://links.lww.com/xxx).
Last, assuming the observed relations are causal, we estimated that, had all women adhered to 6 healthy lifestyle factors prior to pregnancy, 13% (95% CI=9–17%) of APOs in all pregnancies and 19% (95% CI=13–26%) of APOs in pregnancies reaching 20 weeks’ gestation could have been prevented (Appendix 6, http://links.lww.com/xxx) when using current nationally representative estimates for the prevalence of healthy lifestyle factors. The PAR estimates were slightly weaker when using the observed distributions for estimation (Appendix 5. http://links.lww.com/xxx).
Discussion
We found that a healthy lifestyle prior to pregnancy was inversely associated with a substantially lower risk of APOs. The relationship was robust regardless of maternal age, parity, and pre-pregnancy BMI. A healthy lifestyle was broadly protective of APOs, especially miscarriage, GDM, GHTN, and LBW. Healthy weight, tobacco abstinence, and high-quality diet appeared to offer protection for a broader range of APOs. We estimated that adherence to the six lifestyle recommendations during the prepregnancy period may lead to the prevention of nearly 1 in 5 APOs at the population level.
Although consistently recommended by prepregnancy guidelines, evidence of the beneficial associations of a combined healthy lifestyle with APO risk is scarce. Randomized trials have yielded conflicting results of the efficacy of multi-component lifestyle interventions during the prepregnancy period or early pregnancy,31-36 limited by small sample sizes (~100–400 women), low compliance, and interventions that encompass fewer lifestyle factors than those generally endorsed in prepregnancy guidelines.31,32 Trials of interventions during pregnancy are often restricted to high-risk women with varying time of intervention initiation, and their findings may therefore not be generalizable to average risk women or the prepregnancy period.33,34,37 Previous cohort studies have investigated whether prepregnancy healthy lifestyle patterns are associated with lower risk of individual APO. For instance, Zhang et al. found that risk of GDM decreased in a dose-dependent fashion with increasing healthy lifestyle score that include healthy BMI, high-quality diet, regular exercise, and non-smoking.23 A similar association was found with preterm birth in a smaller cohort (n=2,000).38 Comparable evidence regarding other APOs, however, is very limited. In the context of prepregnancy counselling, defining APOs as a composite outcome has particularly practical clinical and public health relevance, especially with respect to informing women about their pregnancy safety and future health related to APO events.
We replicated previously reported lifestyle factor-APO associations while identifying some novel relations. Consistent with prior literature, we found that healthy BMI and abstinence from tobacco are broadly protective of APOs.39-43 The associations of multivitamin supplementation with lower risk of miscarriage, LBW, and stillbirth have been reported in meta-analyses of randomized trials,44,45 conducted in low- or middle-income countries where maternal undernutrition is more prevalent.46 We found that multivitamin supplementation was associated with lower risk of APOs, which suggests that the benefits observed in trials may extend to well-nourished populations. Research from the NHSII has previously shown that adhering to healthy dietary patterns, in the 1 to 3 years preceding pregnancy, is associated with decreased risk of GDM and HDPs, but not miscarriage.20,23,47,48 Considering prior evidence that initiation of dietary interventions during pregnancy provide limited protection against APOs, diet counselling before pregnancy may be exceptionally critical.37 While there is extensive literature supporting the benefits of regular exercise during pregnancy on maternal and fetal health,49-51 the prepregnancy period is less well-studied. Our findings agree with previous prospective studies documenting that moderate to vigorous physical activity prior to pregnancy may be protective for GDM and GHTN,52,53 but not for preterm birth.54 Although pre-pregnancy physical activity was not associated with lower risk of APOs after adjustment for BMI, this lack of association may indeed reflect that BMI may mediate some of the benefits of pre-pregnancy physical activity. Although we did not identify an adverse association between alcohol intake and APOs, women who are contemplating pregnancy should discontinue alcohol use for its well-documented harmful effect on fetal development,30 which was not considered in this study. Furthermore, there were few women (2%) with high alcohol consumption (>15 g/d), further limiting our ability to detect meaningful associations between alcohol intake and risk of APOs.
Limitations of our study include the relative homogeneity in race and ethnicity and socioeconomic status of our study population, limiting generalizability. Second, as an observational study, residual confounding likely remains despite careful control for potential confounders. Third, as APOs were recalled at a relative later stage in reproductive life, misclassification and recall bias may have occurred. However, misclassification should be non-differential with respect to exposure status resulting in bias towards the null. In addition, the validity of self-reported reproductive events in this cohort events is high.22-26 Fifth, some of the lifestyle factors were assessed only once in a few years, which may have introduced measurement error. However, this would have biased our results towards null.
Strengths of the study include the prospective study design with extensive follow-up, a large sample size, and assessment of lifestyle using validated instruments, all of which allow us to study the separate and combined associations of modifiable risk factors on a large number of APOs. In the absence of data from large, randomized trials of multi-component interventions among an average risk population, our study provides valuable evidence for the associations of prepregnancy healthy lifestyle with APOs.
In summary, our results show that a healthy lifestyle as recommended in prepregnancy guidelines is associated with a significantly lower risk of APOs. Our findings highlight the importance of the prepregnancy period as a critical window to implement lifestyle modifications to improve pregnancy health.
Supplementary Material
Funding:
Supported by grants U01 CA176726 and U01 HL145386 from the National Institutes of Health. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Footnotes
Financial Disclosure
Makiko Mitsunami disclosed receiving payment from the Global Scholarship Rotary Foundation. Dr. Mitsunami's institution a grant for soy products research from the Fuji Protein for Research Foundation. The other authors did not report any potential conflicts of interest.
Each author has confirmed compliance with the journal’s requirements for authorship.
Meeting presentation: Presented at the American Heart Association Epi Lifestyle meeting on March 1, 2023, Boston, MA.
References:
- 1.Freaney PM, Harrington K, Molsberry R, et al. Temporal Trends in Adverse Pregnancy Outcomes in Birthing Individuals Aged 15 to 44 Years in the United States, 2007 to 2019. J Am Heart Assoc 2022;11(11):e025050. DOI: 10.1161/JAHA.121.025050. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.O'Sullivan JB. Diabetes mellitus after GDM. Diabetes 1991;40 Suppl 2:131–5. DOI: 10.2337/diab.40.2.s131. [DOI] [PubMed] [Google Scholar]
- 3.Rich-Edwards JW, Fraser A, Lawlor DA, Catov JM. Pregnancy characteristics and women's future cardiovascular health: an underused opportunity to improve women's health? Epidemiol Rev 2014;36:57–70. DOI: 10.1093/epirev/mxt006. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Barrett PM, McCarthy FP, Kublickiene K, et al. Adverse Pregnancy Outcomes and Long-term Maternal Kidney Disease: A Systematic Review and Meta-analysis. JAMA Netw Open 2020;3(2):e1920964. DOI: 10.1001/jamanetworkopen.2019.20964. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Wang YX, Minguez-Alarcon L, Gaskins AJ, et al. Association of spontaneous abortion with all cause and cause specific premature mortality: prospective cohort study. BMJ 2021;372:n530. DOI: 10.1136/bmj.n530. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Pinheiro TV, Brunetto S, Ramos JG, Bernardi JR, Goldani MZ. Hypertensive disorders during pregnancy and health outcomes in the offspring: a systematic review. J Dev Orig Health Dis 2016;7(4):391–407. DOI: 10.1017/S2040174416000209. [DOI] [PubMed] [Google Scholar]
- 7.Damm P, Houshmand-Oeregaard A, Kelstrup L, Lauenborg J, Mathiesen ER, Clausen TD. Gestational diabetes mellitus and long-term consequences for mother and offspring: a view from Denmark. Diabetologia 2016;59(7):1396–1399. DOI: 10.1007/s00125-016-3985-5. [DOI] [PubMed] [Google Scholar]
- 8.ACOG Committee Opinion No. 762: Prepregnancy Counseling. Obstet Gynecol 2019;133(1):e78–e89. DOI: 10.1097/AOG.0000000000003013. [DOI] [PubMed] [Google Scholar]
- 9.World Health Organization. Preconception care to reduce maternal and childhood mortality and morbidity: policy brief. 2013. (https://apps.who.int/iris/bitstream/handle/10665/340533/WHO-FWC-MCA-13.02-eng.pdf?sequence=1). Accessed October 13, 2022. [Google Scholar]
- 10.Wang S, Rexrode KM, Florio AA, Rich-Edwards JW, Chavarro JE. Maternal Mortality in the United States: Trends and Opportunities for Prevention. Annu Rev Med 2023;74:199–216. DOI: 10.1146/annurev-med-042921-123851. [DOI] [PubMed] [Google Scholar]
- 11.Bao Y, Bertoia ML, Lenart EB, et al. Origin, Methods, and Evolution of the Three Nurses' Health Studies. Am J Public Health 2016;106(9):1573–81. DOI: 10.2105/AJPH.2016.303338. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Troy LM, Hunter DJ, Manson JE, Colditz GA, Stampfer MJ, Willett WC. The validity of recalled weight among younger women. Int J Obes Relat Metab Disord 1995;19(8):570–2. (https://www.ncbi.nlm.nih.gov/pubmed/7489028). [PubMed] [Google Scholar]
- 13.Al-Delaimy WK, Willett WC. Measurement of tobacco smoke exposure: comparison of toenail nicotine biomarkers and self-reports. Cancer Epidemiol Biomarkers Prev 2008;17(5):1255–61. DOI: 10.1158/1055-9965.EPI-07-2695. [DOI] [PubMed] [Google Scholar]
- 14.Wolf AM, Hunter DJ, Colditz GA, et al. Reproducibility and validity of a self-administered physical activity questionnaire. Int J Epidemiol 1994;23(5):991–9. DOI: 10.1093/ije/23.5.991. [DOI] [PubMed] [Google Scholar]
- 15.Yuan C, Spiegelman D, Rimm EB, et al. Validity of a Dietary Questionnaire Assessed by Comparison With Multiple Weighed Dietary Records or 24-Hour Recalls. Am J Epidemiol 2017;185(7):570–584. DOI: 10.1093/aje/kww104. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Yuan C, Spiegelman D, Rimm EB, et al. Relative Validity of Nutrient Intakes Assessed by Questionnaire, 24-Hour Recalls, and Diet Records as Compared With Urinary Recovery and Plasma Concentration Biomarkers: Findings for Women. Am J Epidemiol 2018;187(5):1051–1063. DOI: 10.1093/aje/kwx328. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Salvini S, Hunter DJ, Sampson L, et al. Food-based validation of a dietary questionnaire: the effects of week-to-week variation in food consumption. Int J Epidemiol 1989;18(4):858–67. DOI: 10.1093/ije/18.4.858. [DOI] [PubMed] [Google Scholar]
- 18.Rimm EB, Giovannucci EL, Stampfer MJ, Colditz GA, Litin LB, Willett WC. Reproducibility and validity of an expanded self-administered semiquantitative food frequency questionnaire among male health professionals. Am J Epidemiol 1992;135(10):1114–26; discussion 1127-36. DOI: 10.1093/oxfordjournals.aje.a116211. [DOI] [PubMed] [Google Scholar]
- 19.Chobanian AV, Bakris GL, Black HR, et al. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA 2003;289(19):2560–72. DOI: 10.1001/jama.289.19.2560. [DOI] [PubMed] [Google Scholar]
- 20.Arvizu M, Stuart JJ, Rich-Edwards JW, Gaskins AJ, Rosner B, Chavarro JE. Prepregnancy adherence to dietary recommendations for the prevention of cardiovascular disease in relation to risk of hypertensive disorders of pregnancy. Am J Clin Nutr 2020;112(6):1429–1437. DOI: 10.1093/ajcn/nqaa214. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Centers for Disease Control and Prevention. Dietary Guidelines for Alcohol. (https://www.cdc.gov/alcohol/fact-sheets/moderate-drinking.htm). Accessed October 17, 2022. [Google Scholar]
- 22.Troy LM, Michels KB, Hunter DJ, et al. Self-reported birthweight and history of having been breastfed among younger women: an assessment of validity. Int J Epidemiol 1996;25(1):122–7. DOI: 10.1093/ije/25.1.122. [DOI] [PubMed] [Google Scholar]
- 23.Zhang C, Tobias DK, Chavarro JE, et al. Adherence to healthy lifestyle and risk of gestational diabetes mellitus: prospective cohort study. BMJ 2014;349:g5450. DOI: 10.1136/bmj.g5450. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Tomeo CA, Rich-Edwards JW, Michels KB, et al. Reproducibility and validity of maternal recall of pregnancy-related events. Epidemiology 1999;10(6):774–7. (https://www.ncbi.nlm.nih.gov/pubmed/10535796). [PubMed] [Google Scholar]
- 25.Stuart JJ, Tanz LJ, Missmer SA, et al. Hypertensive Disorders of Pregnancy and Maternal Cardiovascular Disease Risk Factor Development: An Observational Cohort Study. Ann Intern Med 2018;169(4):224–232. DOI: 10.7326/M17-2740. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Tanz LJ, Stuart JJ, Williams PL, et al. Preterm Delivery and Maternal Cardiovascular Disease in Young and Middle-Aged Adult Women. Circulation 2017;135(6):578–589. DOI: 10.1161/CIRCULATIONAHA.116.025954. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Kristensen P, Irgens LM. Maternal reproductive history: a registry based comparison of previous pregnancy data derived from maternal recall and data obtained during the actual pregnancy. Acta Obstet Gynecol Scand 2000;79(6):471–7. (https://www.ncbi.nlm.nih.gov/pubmed/10857871). [PubMed] [Google Scholar]
- 28.Hure AJ, Chojenta CL, Powers JR, Byles JE, Loxton D. Validity and reliability of stillbirth data using linked self-reported and administrative datasets. J Epidemiol 2015;25(1):30–7. DOI: 10.2188/jea.JE20140032. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Ellison GT, de Wet T, Matshidze KP, Cooper P. The reliability and validity of self-reported reproductive history and obstetric morbidity amongst Birth to Ten mothers in Soweto. Curationis 2000;23(4):76–80. DOI: 10.4102/curationis.v23i4.753. [DOI] [PubMed] [Google Scholar]
- 30.May PA, Gossage JP. Maternal risk factors for fetal alcohol spectrum disorders: not as simple as it might seem. Alcohol Res Health 2011;34(1):15–26. (https://www.ncbi.nlm.nih.gov/pubmed/23580036). [PMC free article] [PubMed] [Google Scholar]
- 31.Elsinga J, de Jong-Potjer LC, van der Pal-de Bruin KM, le Cessie S, Assendelft WJ, Buitendijk SE. The effect of preconception counselling on lifestyle and other behaviour before and during pregnancy. Womens Health Issues 2008;18(6 Suppl):S117–25. DOI: 10.1016/j.whi.2008.09.003. [DOI] [PubMed] [Google Scholar]
- 32.Lumley J, Donohue L. Aiming to increase birth weight: a randomised trial of pre-pregnancy information, advice and counselling in inner-urban Melbourne. BMC Public Health 2006;6:299. DOI: 10.1186/1471-2458-6-299. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Oteng-Ntim E, Varma R, Croker H, Poston L, Doyle P. Lifestyle interventions for overweight and obese pregnant women to improve pregnancy outcome: systematic review and meta-analysis. BMC Med 2012;10:47. DOI: 10.1186/1741-7015-10-47. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Song C, Li J, Leng J, Ma RC, Yang X. Lifestyle intervention can reduce the risk of gestational diabetes: a meta-analysis of randomized controlled trials. Obes Rev 2016;17(10):960–9. DOI: 10.1111/obr.12442. [DOI] [PubMed] [Google Scholar]
- 35.Legro RS, Hansen KR, Diamond MP, et al. Effects of preconception lifestyle intervention in infertile women with obesity: The FIT-PLESE randomized controlled trial. PLoS Med 2022;19(1):e1003883. DOI: 10.1371/journal.pmed.1003883. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Lan L, Harrison CL, Misso M, et al. Systematic review and meta-analysis of the impact of preconception lifestyle interventions on fertility, obstetric, fetal, anthropometric and metabolic outcomes in men and women. Hum Reprod 2017;32(9):1925–1940. DOI: 10.1093/humrep/dex241. [DOI] [PubMed] [Google Scholar]
- 37.Stephenson J, Heslehurst N, Hall J, et al. Before the beginning: nutrition and lifestyle in the preconception period and its importance for future health. Lancet 2018;391(10132):1830–1841. DOI: 10.1016/S0140-6736(18)30311-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Zhu Y, Hedderson MM, Brown SD, et al. Healthy preconception and early-pregnancy lifestyle and risk of preterm birth: a prospective cohort study. Am J Clin Nutr 2021;114(2):813–821. DOI: 10.1093/ajcn/nqab089. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Vats H, Saxena R, Sachdeva MP, Walia GK, Gupta V. Impact of maternal pre-pregnancy body mass index on maternal, fetal and neonatal adverse outcomes in the worldwide populations: A systematic review and meta-analysis. Obes Res Clin Pract 2021;15(6):536–545. DOI: 10.1016/j.orcp.2021.10.005. [DOI] [PubMed] [Google Scholar]
- 40.Guelinckx I, Devlieger R, Vansant G. Reproductive outcome after bariatric surgery: a critical review. Hum Reprod Update 2009;15(2):189–201. DOI: 10.1093/humupd/dmn057. [DOI] [PubMed] [Google Scholar]
- 41.Perry MF, Mulcahy H, DeFranco EA. Influence of periconception smoking behavior on birth defect risk. Am J Obstet Gynecol 2019;220(6):588 e1–588 e7. DOI: 10.1016/j.ajog.2019.02.029. [DOI] [PubMed] [Google Scholar]
- 42.Hammoud AO, Bujold E, Sorokin Y, Schild C, Krapp M, Baumann P. Smoking in pregnancy revisited: findings from a large population-based study. Am J Obstet Gynecol 2005;192(6):1856–62; discussion 1862-3. DOI: 10.1016/j.ajog.2004.12.057. [DOI] [PubMed] [Google Scholar]
- 43.Wang J, Yang W, Xiao W, Cao S. The association between smoking during pregnancy and hypertensive disorders of pregnancy: A systematic review and meta-analysis. Int J Gynaecol Obstet 2022;157(1):31–41. DOI: 10.1002/ijgo.13709. [DOI] [PubMed] [Google Scholar]
- 44.Haider BA, Bhutta ZA. Multiple-micronutrient supplementation for women during pregnancy. Cochrane Database Syst Rev 2017;4:CD004905. DOI: 10.1002/14651858.CD004905.pub5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Bortolus R, Filippini F, Cipriani S, et al. Efficacy of 4.0 mg versus 0.4 mg Folic Acid Supplementation on the Reproductive Outcomes: A Randomized Controlled Trial. Nutrients 2021;13(12). DOI: 10.3390/nu13124422. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Keats EC, Haider BA, Tam E, Bhutta ZA. Multiple-micronutrient supplementation for women during pregnancy. Cochrane Database Syst Rev 2019;3:CD004905. DOI: 10.1002/14651858.CD004905.pub6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Tobias DK, Zhang C, Chavarro J, et al. Prepregnancy adherence to dietary patterns and lower risk of gestational diabetes mellitus. Am J Clin Nutr 2012;96(2):289–95. DOI: 10.3945/ajcn.111.028266. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Gaskins AJ, Rich-Edwards JW, Hauser R, et al. Prepregnancy dietary patterns and risk of pregnancy loss. Am J Clin Nutr 2014;100(4):1166–72. DOI: 10.3945/ajcn.114.083634. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Meher S, Duley L. Exercise or other physical activity for preventing pre-eclampsia and its complications. Cochrane Database Syst Rev 2006(2):CD005942. DOI: 10.1002/14651858.CD005942. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Magro-Malosso ER, Saccone G, Di Mascio D, Di Tommaso M, Berghella V. Exercise during pregnancy and risk of preterm birth in overweight and obese women: a systematic review and meta-analysis of randomized controlled trials. Acta Obstet Gynecol Scand 2017;96(3):263–273. DOI: 10.1111/aogs.13087. [DOI] [PubMed] [Google Scholar]
- 51.Han S, Middleton P, Crowther CA. Exercise for pregnant women for preventing gestational diabetes mellitus. Cochrane Database Syst Rev 2012(7):CD009021. DOI: 10.1002/14651858.CD009021.pub2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Tobias DK, Zhang C, van Dam RM, Bowers K, Hu FB. Physical activity before and during pregnancy and risk of gestational diabetes mellitus: a meta-analysis. Diabetes Care 2011;34(1):223–9. DOI: 10.2337/dc10-1368. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Arvizu M, Minguez-Alarcon L, Stuart JJ, et al. Physical activity before pregnancy and the risk of hypertensive disorders of pregnancy. Am J Obstet Gynecol MFM 2021;4(2):100556. DOI: 10.1016/j.ajogmf.2021.100556. [DOI] [PubMed] [Google Scholar]
- 54.Aune D, Schlesinger S, Henriksen T, Saugstad OD, Tonstad S. Physical activity and the risk of preterm birth: a systematic review and meta-analysis of epidemiological studies. BJOG 2017;124(12):1816–1826. DOI: 10.1111/1471-0528.14672. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.