Background

Pregnancy anxiety is associated with risk of preterm birth and an array of other birth, infant, and childhood outcomes. However, previous research has not helped identify those pregnant women at greatest risk of experiencing this specific, contextually-based affective condition.

Methods

We examined associations between demographic, medical, and psychosocial factors and pregnancy anxiety at 24-26 weeks of gestation in a prospective, multicentre cohort study of 5271 pregnant women in Montreal, Canada.

Results

Multivariate analyses indicated that higher pregnancy anxiety was independently related to having an unintended pregnancy, first birth, higher medical risk, and higher perceived risk of complications. Among psychosocial variables, higher pregnancy anxiety was associated with lower perceived control of pregnancy, lower commitment to the pregnancy, more stressful life events, higher perceived stress, presence of job stress, lower self-esteem and more social support. Pregnancy anxiety was also higher in women who had experienced early income adversity and those who did not speak French as their primary language. Psychosocial variables explained a significant amount of the variance in pregnancy anxiety independently of demographic and medical variables.

Conclusions

Women with pregnancy-related risk factors, stress of various kinds, and other psychosocial factors experienced higher pregnancy anxiety in this large Canadian sample. Some of the unique predictors of pregnancy anxiety match those of earlier US studies, while others point in new directions. Screening for high pregnancy anxiety may be warranted, particularly among women giving birth for the first time and those with high-risk pregnancies.

For longitudinal studies with multivariate observations, we propose statistical methods to identify clusters of archetypal subjects by using techniques from functional data analysis and to relate longitudinal patterns to outcomes. We demonstrate how this approach can be applied to examine associations between multiple time-varying exposures and subsequent health outcomes, where the former are recorded sparsely and irregularly in time, with emphasis on the utility of multiple longitudinal observations in the framework of dimension reduction techniques. In applications to children's growth data, we investigate archetypes of infant growth patterns and identify subgroups that are related to cognitive development in childhood. Specifically, "Stunting" and "Faltering" time-dynamic patterns of head circumference, body length and weight in the first 12 months are associated with lower levels of long-term cognitive development in comparison to "Generally Large" and "Catch-up" growth. Our findings provide evidence for the statistical association between multivariate growth patterns in infancy and long-term cognitive development.

Background

In 2013, an estimated 2.8 million newborns died and 2.7 million were stillborn. A much greater number suffer from long term impairment associated with preterm birth, intrauterine growth restriction, congenital anomalies, and perinatal or infectious causes. With the approaching deadline for the achievement of the Millennium Development Goals (MDGs) in 2015, there was a need to set the new research priorities on newborns and stillbirth with a focus not only on survival but also on health, growth and development. We therefore carried out a systematic exercise to set newborn health research priorities for 2013-2025.

Methods

We used adapted Child Health and Nutrition Research Initiative (CHNRI) methods for this prioritization exercise. We identified and approached the 200 most productive researchers and 400 program experts, and 132 of them submitted research questions online. These were collated into a set of 205 research questions, sent for scoring to the 600 identified experts, and were assessed and scored by 91 experts.

Results

Nine out of top ten identified priorities were in the domain of research on improving delivery of known interventions, with simplified neonatal resuscitation program and clinical algorithms and improved skills of community health workers leading the list. The top 10 priorities in the domain of development were led by ideas on improved Kangaroo Mother Care at community level, how to improve the accuracy of diagnosis by community health workers, and perinatal audits. The 10 leading priorities for discovery research focused on stable surfactant with novel modes of administration for preterm babies, ability to diagnose fetal distress and novel tocolytic agents to delay or stop preterm labour.

Conclusion

These findings will assist both donors and researchers in supporting and conducting research to close the knowledge gaps for reducing neonatal mortality, morbidity and long term impairment. WHO, SNL and other partners will work to generate interest among key national stakeholders, governments, NGOs, and research institutes in these priorities, while encouraging research funders to support them. We will track research funding, relevant requests for proposals and trial registers to monitor if the priorities identified by this exercise are being addressed.