The effects of home visiting on birth outcomes and perinatal health behaviors

Adversity and risk of poor birth and infant outcomes for young mothers: a population-based data-linkage cohort study

Pregnancy is a unique stage of the life course characterized by trade-offs between the nutritional, immune, and metabolic needs of the mother and fetus. The Camden Study was originally initiated to examine nutritional status, growth, and birth outcomes in adolescent pregnancies and expanded to study dietary and molecular predictors of pregnancy complications and birth outcomes in young women. From 1985-2006, 4765 pregnant participants aged 12 years and older were recruited from Camden, NJ, one of the poorest cities in the U.S. The cohort reflects a population under-represented in perinatal cohort studies (45% Hispanic, 38% non-Hispanic Black, 17% White participants; 98% using Medicaid in pregnancy). Study visits, including questionnaires, dietary assessments, and biospecimen collection, occurred in early and late pregnancy as well as at delivery. Medical records were abstracted, and a subset of mothers and infants participated in a six-week postpartum visit. Over the last five decades, the Camden Study has provided data toward the publication of numerous peer-reviewed papers. Results show that adolescent linear growth in pregnancy is associated with smaller birth size, possibly due to impaired hemodynamics. In the context of preterm birth and other perinatal outcomes, analyses of nutritional data have demonstrated the importance of micronutrients (e.g., folate, iron, zinc), as well as glucose/insulin dynamics and prenatal supplement use. More recent analyses have begun to unpack the biochemical pathways in pregnancy that may be shaped by race as an indicator for systemic racism. The Camden Study data and biorepositories are well-positioned to support future research aimed at better understanding perinatal health in under-represented women and infants. Linkages to subsequent health and administrative records and the potential for recontacting participants over 18-39 years after initial participation may provide key insights into the trajectories of maternal and child health across the life course.

Advances in public health and medical care have enabled better pregnancy and birth outcomes. The rates of perinatal health indicators such as maternal mortality and morbidity; fetal, neonatal, and infant mortality; low birthweight; and preterm birth have reduced over time. However, they are still a public health concern, and considerable disparities exist within and between countries. For perinatal researchers who are engaged in unraveling the tangled web of causation for maternal and child health outcomes and for clinicians involved in the care of pregnant women and infants, artificial intelligence offers novel approaches to prediction modeling, diagnosis, early detection, and monitoring in perinatal health. Machine learning, a commonly used artificial intelligence method, has been used to predict preterm birth, birthweight, preeclampsia, mortality, hypertensive disorders, and postpartum depression. Real-time electronic health recording and predictive modeling using artificial intelligence have found early success in fetal monitoring and monitoring of women with gestational diabetes especially in low-resource settings. Artificial intelligence–based methodologies have the potential to improve prenatal diagnosis of birth defects and outcomes in assisted reproductive technology too. In this scenario, we envision artificial intelligence for perinatal research to be based on three goals: (1) availability of population-representative, routine clinical data (rich multimodal data of large sample size) for perinatal research; (2) modification and application of current state-of-the-art artificial intelligence for prediction and classification in health care research to the field of perinatal health; and (3) development of methods for explaining the decision-making processes of artificial intelligence models for perinatal health indicators. Achieving these three goals via a multidisciplinary approach to the development of artificial intelligence tools will enable trust in these tools and advance research, clinical practice, and policies to ensure optimal perinatal health.

While non-Hispanic Black populations tend to be disproportionately affected by adverse reproductive outcomes, Hispanic populations tend to demonstrate healthier birth outcomes, regardless of socioeconomic background. Little is known about birth outcomes for women who are both Black and Hispanic. We examined whether birth outcomes and risk factors for women who are both Black and Hispanic most closely resemble those of women who are only Black or Hispanic and also compared these outcomes to those for Whites. Using the 2013 US natality files, we examined 2,970,315 singleton births to Black Hispanic, Hispanic, Black, and White mothers. We used logistic regression to calculate predicted probabilities of low birth weight (LBW), preterm birth (PTB), or small for gestational age (SGA). Race-stratified regression analysis was used to identify the factors that significantly predicted risk for each outcome for each racial/ethnic group. Black mothers had the highest prevalence and predicted probabilities of experiencing all three outcomes. Black Hispanic mothers were less likely than Black mothers and more likely than Hispanic mothers to experience each of the adverse outcomes. We also found support for racial variation in risk and protective factors for mothers in the different groups. Factors like age and education inconsistently predicted risk of experiencing the birth outcomes for all groups. Overall, Black Hispanic mothers had birth outcomes and risk factor profiles like Hispanic mothers, although they had sociodemographic characteristics and health behaviors like Black mothers. Patterning of birth outcomes among Black Hispanic women suggest an intersection of risk and protective factors associated with their respective racial and ethnic identities. Additional information about sociodemographic context is needed to develop a more complete picture of how factors related to race and ethnic group membership influence Black Hispanic women's birth outcomes.

Changes in population birth outcomes, including increases in low birthweight or preterm births, have been documented after natural and manmade disasters. However, information is limited following the 2011 Fukushima Daiichi Nuclear Power Plant Disaster. In this study, we assessed whether there were long-term changes in birth outcomes post-disaster, compared to pre-disaster data, and whether residential area and food purchasing patterns, as proxy measurements of evacuation and radiation-related anxiety, were associated with post-disaster birth outcomes. Maternal and perinatal data were retrospectively collected for all live singleton births at a public hospital, located 23 km from the power plant, from 2008 to 2015. Proportions of low birthweight (<2500 g at birth) and preterm births (<37 weeks gestation at birth) were compared pre- and post-disaster, and regression models were conducted to assess for associations between these outcomes and evacuation and food avoidance. A total of 1101 live singleton births were included. There were no increased proportions of low birthweight or preterm births in any year after the disaster (merged post-disaster risk ratio of low birthweight birth: 0.98, 95% confidence interval (CI): 0.64–1.51; and preterm birth: 0.68, 95% CI: 0.38–1.21). No significant associations between birth outcomes and residential area or food purchasing patterns were identified, after adjustment for covariates. In conclusion, no changes in birth outcomes were found in this institution-based investigation after the Fukushima disaster. Further research is needed on the pathways that may exacerbate or reduce disaster effects on maternal and perinatal health.

Socioeconomic Disparities in Adverse Birth Outcomes: A Systematic Review

Prenatal bisphenol A and birth outcomes: MOCEH (Mothers and Children's Environmental Health) study

Numerous studies find that socially disadvantaged women are more likely than socially advantaged women to deliver infants that weigh less than normal and/or are born weeks prior to their due date. However, little is known about the pathways that link maternal social disadvantage to birth outcomes. Using data from a prospective cohort study, we examined whether antenatal psychosocial stress, substance use, and maternal health conditions in pregnancy mediated the pathway between maternal social disadvantage and birth outcomes. Analyses used structural equation modeling to examine data from a community clinic-based sample (n=2168) of pregnant women who completed questionnaires assessing psychosocial functioning and health behaviors as well as sociodemographic characteristics, which were matched with subsequent birth outcome data. Analyses revealed maternal social disadvantage predicted poorer birth outcomes through a mediated pathway including maternal health conditions in pregnancy. The findings demonstrate that maternal social disadvantage is associated with poor health status in pregnancy, which in turn adversely affects birth outcomes. Results argue for more systematic attention to the roles of social disadvantage, including life course perspectives that trace social disadvantage prior to and through pregnancy.

Urinary level of triclosan in a population of Chinese pregnant women and its association with birth outcomes

Retrospective studies of preconception health have demonstrated that parents' health conditions and behaviors can impact a newborn's birth outcomes and, subsequently, future health status. This study sought to examine the impact of preconception health, measured prospectively, among both mothers and fathers, on two important birth outcomes: birthweight and gestational age. Data came from Add Health (the National Longitudinal Study of Adolescent Health), which included interviews with original participants and a subsample of their partners in 2001-02. In 2008, the original respondents again completed an interview for Add Health. For 372 eligible infants born to these couples, birth outcomes (measured in 2008) were regressed on preconception health conditions and behaviors among non-pregnant heterosexual partners (measured in 2001-02). Mean birthweight was 3,399 g, and mean gestational age was 39 weeks. Birthweight was higher for infants born to mothers with diabetes or high blood pressure, and for mothers who drank alcohol at least once per month, and lower for infants born to fathers with diabetes (p < 0.05). Infant gestational age was marginally lower for infants born to mothers with higher levels of depression (p < 0.10), and lower for infants born to fathers with diabetes and with higher levels of fast food consumption (p < 0.05). Both maternal and paternal preconception health conditions and behaviors influenced infant birth outcomes. Interventions to promote preconception health should focus on prevention of diabetes and high blood pressure, as well as minimizing consumption of alcohol and fast food.

Perinatal health in Spain during and after the Great Recession: Educational selection into fertility as a protective factor in high unemployment contexts

The interaction of pregnancy, substance use and mental illness on birthing outcomes in Australia

I use Danish survey and administrative data to examine the impact of maternal employment during pregnancy on birth outcomes. As healthier mothers are more likely to work and health shocks to mothers may impact employment and birth outcomes, I combine two strategies: First, I control extensively for time-varying factors that may correlate with employment and birth outcomes, such as pre-pregnancy family income and maternal occupation, pregnancy-related health shocks, maternal sick listing, and health behaviors (smoking and alcohol consumption). Second, to account for remaining time-invariant heterogeneity between mothers, I compare outcomes of mothers' consecutive children. Mothers who work during the first pregnancy trimester have a lower risk of preterm birth. I find no effect on the probability of having a baby of small size for gestational age. To rule out that health selection of mothers between pregnancies drives the results, I focus on mothers whose change in employment status is likely not to be driven by underlying health (mothers who are students in one of their pregnancies and mothers with closely spaced births). Given generous welfare benefits and strict workplace regulations in Denmark, my findings support a residual explanation, namely, that exclusion from employment may stress mothers in countries with high-female employment rates.

BackgroundIn the United States, racial disparities in birth outcomes persist and have been widening. Interpersonal and structural racism are leading explanations for the continuing racial disparities in birth outcomes, but research to confirm the role of racism and evaluate trends in the impact of racism on health outcomes has been hampered by the challenge of measuring racism. Most research on discrimination relies on self-reported experiences of discrimination, and few studies have examined racial attitudes and bias at the US national level.ObjectiveThis study aimed to investigate the associations between state-level Twitter-derived sentiments related to racial or ethnic minorities and birth outcomes.MethodsWe utilized Twitter’s Streaming application programming interface to collect 26,027,740 tweets from June 2015 to December 2017, containing at least one race-related term. Sentiment analysis was performed using support vector machine, a supervised machine learning model. We constructed overall indicators of sentiment toward minorities and sentiment toward race-specific groups. For each year, state-level Twitter-derived sentiment data were merged with birth data for that year. The study participants were women who had singleton births with no congenital abnormalities from 2015 to 2017 and for whom data were available on gestational age (n=9,988,030) or birth weight (n=9,985,402). The main outcomes were low birth weight (birth weight ≤2499 g) and preterm birth (gestational age <37 weeks). We estimated the incidence ratios controlling for individual-level maternal characteristics (sociodemographics, prenatal care, and health behaviors) and state-level demographics, using log binomial regression models.ResultsThe accuracy for identifying negative sentiments on comparing the machine learning model to manually labeled tweets was 91%. Mothers living in states in the highest tertile for negative sentiment tweets referencing racial or ethnic minorities had greater incidences of low birth weight (8% greater, 95% CI 4%-13%) and preterm birth (8% greater, 95% CI 0%-14%) compared with mothers living in states in the lowest tertile. More negative tweets referencing minorities were associated with adverse birth outcomes in the total population, including non-Hispanic white people and racial or ethnic minorities. In stratified subgroup analyses, more negative tweets referencing specific racial or ethnic minority groups (black people, Middle Eastern people, and Muslims) were associated with poor birth outcomes for black people and minorities.ConclusionsA negative social context related to race was associated with poor birth outcomes for racial or ethnic minorities, as well as non-Hispanic white people.

Studies on pregnancy intentions and their consequences have yielded mixed results. Here, we comprehensively analyzed the maternal characteristics, health behaviors before and during pregnancy, as well as pregnancy and birth outcomes, across three different pregnancy planning status in 861 women participating in an ongoing Asian mother-offspring cohort study. At 26-28weeks' gestation, the women's intention and enthusiasm toward their pregnancy were used to classify their pregnancy into planned or unplanned, and unplanned pregnancy was further subdivided into mistimed or unintended. Data on maternal characteristics, health behaviors, and pregnancy outcomes up to that stage were recorded. After delivery, birth outcomes of the offspring were recorded. Linear and logistic regression analyses were performed. Overall, 56% had a planned pregnancy, 39% mistimed, and 5% unintended. Compared to women who planned their pregnancy, women with mistimed pregnancy had higher body mass index and were more likely to have cigarette smoke exposure and less likely to have folic acid supplementation. At 26-28weeks' gestation, unintended pregnancy was associated with increased anxiety. Neonates of mistimed pregnancy had shorter birth length compared to those of planned pregnancy, even after adjustment for maternal baseline demographics. These findings suggest that mothers who did not plan their pregnancy had less desirable characteristics or health behaviors before and during pregnancy and poorer pregnancy and birth outcomes. Shorter birth length in mistimed pregnancy may be attributed to maternal behaviors before or in the early stages of pregnancy, therefore highlighting the importance of preconception health promotion and screening for women of child-bearing age.