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Data System. The Pregnancy Risk Assessment Monitoring System (PRAMS) is an ongoing state-based surveillance system of maternal behaviors, attitudes, and experiences before, during, and shortly after pregnancy. PRAMS is conducted by the Centers for Disease Control and Prevention’s Division of Reproductive Health in collaboration with state health departments. Data Collection/Processing. Birth certificate records are used in each participating jurisdiction to select a sample representative of all women who delivered a live-born infant. PRAMS is a mixed-mode mail and telephone survey. Annual state sample sizes range from approximately 1000 to 3000 women. States stratify their sample by characteristics of public health interest such as maternal age, race/ethnicity, geographic area of residence, and infant birth weight. Data Analysis/Dissemination. States meeting established response rate thresholds are included in multistate analytic data sets available to researchers through a proposal submission process. In addition, estimates from selected indicators are available online. Public Health Implications. PRAMS provides state-based data for key maternal and child health indicators that can be tracked over time. Stratification by maternal characteristics allows for examinations of disparities over a wide range of health indicators.

Postpartum depression is a serious health issue beyond the mental health problems that affect mothers after childbirth. There are no predictive tools available to screen postpartum depression that also allow early interventions. We aimed to develop predictive models for postpartum depression using machine learning (ML) approaches. We performed a retrospective cohort study using data from the Pregnancy Risk Assessment Monitoring System 2012–2013 with 28,755 records (3339 postpartum depression and 25,416 normal cases). The imbalance between the two groups was addressed by a balanced resampling using both random down-sampling and the synthetic minority over-sampling technique. Nine different ML algorithms, including random forest (RF), stochastic gradient boosting, support vector machines (SVM), recursive partitioning and regression trees, naïve Bayes, k-nearest neighbor (kNN), logistic regression, and neural network, were employed with 10-fold cross-validation to evaluate the models. The overall classification accuracies of the nine models ranged from 0.650 (kNN) to 0.791 (RF). The RF method achieved the highest area under the receiver-operating-characteristic curve (AUC) value of 0.884, followed by SVM, which achieved the second-best performance with an AUC value of 0.864. Predictive modeling developed using ML-approaches may thus be used as a prediction (screening) tool for postpartum depression in future studies.

BackgroundHypertensive disorders of pregnancy have lifelong implications on maternal cardiovascular health. Breastfeeding has a variety of maternal benefits, including improved lifelong maternal cardiovascular outcomes, with longer periods of lactation resulting in further improvement. Women with hypertensive disorders of pregnancy encounter many barriers to breastfeeding. Little is known about lactation initiation and duration rates in women with hypertensive disorders of pregnancy. The purpose of this study is to describe lactation patterns in women with HDP, hypertensive disorders of pregnancy, compared to normotensive controls using data from the phase 7 Illinois Pregnancy Risk Assessment Monitoring System (PRAMS).Subjects and MethodsIllinois PRAMS 2012–2015 (Phase 7) data was used to assess lactation patterns as well as rationale for not initiating breastfeeding or earlier cessation. Women who delivered during this time period were eligible to participate in the PRAMS survey, 5285 were included the analysis.ResultsOverall, 17.6% of all women in the study reported their healthcare provider did not speak with them prenatally about breastfeeding. Women who reported they had HDP, were significantly less likely (p ≤ 0.001) to ever breastfeed or pump breast milk to feed their baby, even for a short period, than those women without an HDP. At the time the PRAMS survey was completed, more women without an HDP were still breastfeeding or providing their baby with pumped milk (54.9 v. 48%; p = 0.002). More women with HDP reported stopping breastfeeding because they got sick or had to stop for medical reasons (p = 0.002) and/or because their baby was jaundiced (p = 0.007).ConclusionCardiovascular disease remains the leading cause of death among women and women with a history of HDP are at increased risk for cardiovascular related morbidity and mortality. Obstetrical providers and nurses caring for this high-risk population should ensure they educate women about the increased cardiovascular risk associated with HDP and the maternal cardiovascular benefits associated with lactation in order to promote and support lactation in this population of women.

Exposure to pregnancy during the postpartum period is shaped by biological and behavioral determinants, such as resumption of sexual activity, return of menses, and contraceptive use dynamics. We implement sequence and cluster analyses to generate new insights about exposure to pregnancy during the postpartum period using unique longitudinal data in a low-resource setting. We used population-based data from a sample of 1,935 Ethiopian women who provided reports on factors influencing exposure to pregnancy in the year following childbirth. We used sequence and cluster analyses to characterize patterns of women's reproductive behaviors during the postpartum period. We identified five postpartum trajectories of exposure to pregnancy: (1) no sex; (2) family-planning adopters, no menses; (3) family-planning adopters, return of menses; (4) sex, no menses, no family planning; and (5) sex, menses, no family planning. The 'sex, no menses, no family planning' cluster (50% of the sample) was characterized by resumption of sexual activity around three months postpartum, amenorrhea, and no contraceptive adoption. Women in the two 'family-planning adopters' clusters (39%) resumed sexual activity and adopted contraception around three months postpartum but differ by return of menses. The 'no sex' cluster (5%) was characterized by no sexual activity, contraceptive use, or menses.

Objective To provide a current estimate of the prevalence of prepregnancy obesity in the United States. Methods We analyzed 2004–2005 data from 26 states and New York City ( n  = 75,403 women) participating in the Pregnancy Risk Assessment Monitoring System, an ongoing, population-based surveillance system that collects information on maternal behaviors associated with pregnancy. Information was obtained from questionnaires self-administered after delivery or from linked birth certificates; prepregnancy body mass index was based on self-reported weight and height. Data were weighted to provide representative estimates of all women delivering a live birth in each particular state. Results In this study, about one in five women who delivered were obese; in some state, race/ethnicity, and Medicaid status subgroups, the prevalence was as high as one-third. State-specific prevalence varied widely and ranged from 13.9 to 25.1%. Black women had an obesity prevalence about 70% higher than white and Hispanic women (black: 29.1%; white: 17.4%; Hispanic: 17.4%); however, these race-specific rates varied notably by location. Obesity prevalence was 50% higher among women whose delivery was paid for by Medicaid than by other means (e.g., private insurance, cash, HMO). Conclusion This prevalence makes maternal obesity and its resulting maternal morbidities (e.g., gestational diabetes mellitus) a common risk factor for a complicated pregnancy.

Introduction Screening for specific sexually transmitted diseases (STDs) during pregnancy has been a longstanding public health recommendation. Prior studies have described associations between these infections and socioeconomic factors such as race/ethnicity and education. Objectives We evaluated the prevalence of STDs and the correlation socioeconomic factors have with the presence of these infections among pregnant women in the United States. Methods We conducted an analysis using self-reported data from 12,948 recently pregnant women from the Pregnancy Risk Assessment Monitoring System (PRAMS) in 5 states during 2009–2011. Responses to questions about curable STDs (chlamydia, gonorrhea, syphilis, trichomoniasis) diagnosed during pregnancy were utilized to calculate weighted STD prevalence estimates and 95% confidence intervals (CI). A logistic regression was also conducted to identify maternal socioeconomic characteristics significantly associated with STDs; results are displayed as adjusted prevalence ratios (aPR). The PRAMS protocol was approved at PRAMS participating sites and by CDC’s Institutional Review Board. Results Overall, 3.3% (CI 2.9–3.7) reported ≥ 1 curable STD during her most recent pregnancy. The adjusted STD prevalence was higher among women with younger age (aPR, 2.4; CI 1.8–3.4), non-Hispanic black race/ethnicity (aPR, 3.3; CI 2.4–4.1), unmarried status (aPR, 2.1; CI 1.4–3.0), no college education (aPR, 1.4; CI 1.0–1.9), annual income < $25,000 (aPR, 2.0; CI 1.3–3.2), and no pre-pregnancy health insurance (aPR, 1.4; CI 1.1–1.8). Conclusions for Practice This is the largest study of prevalence of self-reported curable STDs among U.S. pregnant women. Differences in STD prevalence highlight the association between certain socioeconomic factors and the presence of STDs.

BACKGROUND:The 2003 revision of the US Standard Certificate of Live Birth (birth certificate) and Pregnancy Risk Assessment Monitoring System (PRAMS) are important for maternal weight research and surveillance. We examined quality of prepregnancy body mass index (BMI), gestational weight gain, and component variables from these sources. METHODS:Data are from a PRAMS data quality improvement study among a subset of New York City and Vermont respondents in 2009. We calculated mean differences comparing prepregnancy BMI data from the birth certificate and PRAMS (n = 734), and gestational weight gain data from the birth certificate (n = 678) to the medical record, considered the gold standard. We compared BMI categories (underweight, normal weight, overweight, obese) and gestational weight gain categories (below, within, above recommendations), classified by different sources, using percent agreement and the simple κ statistic. RESULTS:For most maternal weight variables, mean differences between the birth certificate and PRAMS compared with the medical record were less than 1 kg. Compared with the medical record, the birth certificate classified similar proportions into prepregnancy BMI categories (agreement = 89%, κ = 0.83); PRAMS slightly underestimated overweight and obesity (agreement = 84%, κ = 0.73). Compared with the medical record, the birth certificate overestimated gestational weight gain below recommendations and underestimated weight gain within recommendations (agreement = 81%, κ = 0.69). Agreement varied by maternal and pregnancy-related characteristics. CONCLUSIONS:Classification of prepregnancy BMI and gestational weight gain from the birth certificate or PRAMS was mostly similar to the medical record but varied by maternal and pregnancy-related characteristics. Efforts to understand how misclassification influences epidemiologic associations are needed.

Background. The 2019 overall breastfeeding initiation rate in the US was 84.1%, yet only 76.6% of American Indian (AI) women initiated breastfeeding. In North Dakota (ND), AI women have greater exposure to interpersonal violence than other racial/ethnic groups. Stress associated with interpersonal violence may interfere with processes important to breastfeeding. We explored whether interpersonal violence partially explains racial/ethnic disparities in breastfeeding in ND. Methods. Data for 2161 women were drawn from the 2017–2019 ND Pregnancy Risk Assessment Monitoring System. Breastfeeding questions in PRAMS have been tested among diverse populations. Breastfeeding initiation was self-report to “Did you ever breastfeed or pump breast milk to feed your new baby, even for a short period?” (yes/no). Breastfeeding duration (2 months; 6 months) was self-reported how many weeks or months of breastmilk feeding. Interpersonal violence for both 12 months before and during pregnancy based on self-report (yes/no) of violence from a husband/partner, family member, someone else, or ex-husband/partner. An “Any violence” variable was created if participants reported “yes” to any violence. Logistic regression models estimated crude and adjusted odds ratios (OR) and 95% confidence intervals (95% CI) for breastfeeding outcomes among AI and Other Race women compared to White women. Sequential models were adjusted for interpersonal violence (husband/partner, family member, someone else, ex-husband/partner, or any). Results. AI women had 45% reduced odds of initiating breastfeeding (OR: 0.55, 95% CI: 0.36, 0.82) compared to white women. Including interpersonal violence during pregnancy did not change results. Similar patterns were observed for all breastfeeding outcomes and all interpersonal violence exposures. Discussion. Interpersonal violence does not explain the disparity in breastfeeding in ND. Considering cultural ties to the tradition of breastfeeding and the role of colonization may provide a better understanding of breastfeeding among AI populations.

IntroductionWith shifting demographics and declining response rates, state and national health surveys are considering mixed mode approaches. Most states field the Pregnancy Risk Assessment Monitoring System (PRAMS) surveillance project, but few have studied the effect of encouraging online responses.MethodsLike PRAMS, the 2016 Ohio Pregnancy Assessment Survey interviewed new mothers 2–4 months after delivery (n = 3382). Fielding included a traditional mailed paper questionnaire with telephone follow-up protocol and two experiments: a rotating web invitation added a web survey link at different points during the mail protocol, and a push-to-web protocol asked women to complete the survey online before mailing a questionnaire. This analysis examined the responses rates and tested for unweighted demographic differences using Pearson’s chi-square.ResultsThe unweighted response rate was highest with the traditional contact protocol (30.0%) and slightly lower among the rotating web invite (27.4%) and the push-to-web (25.5%) groups. Nearly two-thirds (64%) of push-to-web protocol respondents completed the survey online, with 70% of those web surveys submitted before the first paper questionnaire was mailed. Women who responded to the web versus mail surveys were similar on most characteristics, although in both experimental groups, women who completed the web version were more likely to be college educated. Among the push-to-web group, 60% of web and 36% of mail respondents had a 4-year college degree (p < .001).DiscussionGiven the potential for push-to-web to shift respondents to an online survey without greatly impacting response rates, researchers should continue to examine the utility of incorporating a web mode in surveys of new mothers.

Background Excess gestational weight gain (GWG) has adverse short- and long-term effects on the health of mothers and infants. In 2009, the US Institute of Medicine revised its guidelines for GWG and reduced the recommended GWG for women who are obese. There is limited evidence on whether these revised guidelines affected GWG and downstream maternal and infant outcomes. Methods We used data from the 2004–2019 waves of the Pregnancy Risk Assessment Monitoring System, a serial cross-sectional national dataset including over 20 states. We conducted a quasi-experimental difference-in-differences analysis to assess pre/post changes in maternal and infant outcomes among women who were obese, while “differencing out” the pre/post changes among a control group of women who were overweight. Maternal outcomes included GWG and gestational diabetes; infant outcomes included preterm birth (PTB), low birthweight (LBW), and very low birthweight (VLBW). Analysis began in March 2021. Results There was no association between the revised guidelines and GWG or gestational diabetes. The revised guidelines were associated with reduced PTB (− 1.19% points, 95%CI: − 1.86, − 0.52), LBW (− 1.38% points 95%CI: − 2.07, − 0.70), and VLBW (− 1.30% points, 95%CI: − 1.68, − 0.92). Results were robust to several sensitivity analyses. Conclusion The revised 2009 GWG guidelines were not associated with changes in GWG or gestational diabetes but were associated with improvements in infant birth outcomes. These findings will help inform further programs and policies aimed at improving maternal and infant health by addressing weight gain in pregnancy.