Full Title: Perinatal Periods of Risk Analyses: Using Data to Mobilize the Community and to Guide Prevention and Intervention Strategies
Susan M. Wolfe, Ph.D.
CEO, Susan Wolfe and Associates, LLC
Nobody wants to read, hear, or think about babies dying. Yet, in the United States, the estimated infant mortality rate for 2011 is 6.06 per 1,000 births. In comparison, the infant mortality rate in Japan is 2.78, in the Czech Republic it is 3.73, and in the United Kingdom it is 4.62 per 1,000 babies born.1 These rates are not the same for everyone in the United States and there are large disparities in racial and ethnic groups, with rates for Black infants more than twice those of White infants.
Perinatal Periods of Risk (PPOR) is an analytic framework that provides urban communities with valuable tools to investigate and develop prevention and intervention strategies to combat feto-infant mortality and other adverse birth outcomes.2 This framework uses a 2-phase approach. Phase 1 estimates the excess mortality for specific groups compared to a reference group with optimal outcomes. Phase 2 consists of a more in-depth community investigation of risk and preventive factors that contribute to the excess mortality rates. I recently had the opportunity to participate in Phase 1 of this process in one community and Phase 2 in another, and I am continuing participation in efforts to engage and mobilize the communities to address the identified disparities.
During Phase I analyses are performed to determine at which stage the rates are highest using the framework presented below. Each cell in this model represents a different age of infant and birth weight, and each is associated with different implications for prevention and/or intervention. For example, the "Maternal Care" cell consists of infants that weighed at least 1500 grams that died prior to birth. Intervention to reduce this rate would focus on prenatal care.
(24 + weeks)
(28 + days)
1500 + grams
We recently presented the rates for each of these periods and birth weights at a community forum with approximately 300 social service, education, and health care professionals in the audience.3 The audience size was approximately the same number as the total number of potentially preventable infant deaths during a five year period. When the speaker asked everyone to stand and look around, and then pointed out that the number of infants that died unnecessarily was the same as the number of people standing in the room, the data were humanized. Each loss of life is not just a single infant, but a loss of potential talent and of potential significant contributions to society. The follow-up to this presentation is a scheduled meeting to engage community based organizations to begin developing community wide strategies to address these disparities.
I attended another forum in a different community a few days later where results of Phase 2 analyses were presented, pointing out the specific maternal and social factors that predicted very low birth weight (which is associated with infant mortality). They included race (Black), low maternal education, inadequate prenatal care, previous preterm birth, previous infant death, and maternal chronic health conditions. When analyses were performed specifically for Black women, community economic disadvantage was also a predictor, although marginally.4 In this community, these data are being used to develop a Local Health Systems Action Plan specifically targeting infant mortality, low birth weight and very low birth weight. A community wide consortium is in place to facilitate implementation of this plan.
These are examples of how data can be presented to communities to mobilize them and to guide their actions. Phase 1 data were useful in demonstrating that there is a problem, and specifically where that problem resides. Phase 2 provided the detailed information needed to show the community where to start to target prevention and interventions. The level of the data speaks not only to individual interventions, but suggests avenues for more systemic changes, such as improving access to prenatal care and developing strategies to reduce community economic disadvantage.
ADDENDUM: An hour after I wrote and submitted this blog I learned that the State of Texas issued a request for applications for communities to utilize PPOR data to develop or enhance local coalitions to implement evidence-based interventions to reduce the incidence of preterm birth and infant mortality.
1 Central Intelligence Agency (2011). The World Factbook. Accessed at: https://www.cia.gov/library/publications/the-world-factbook/rankorder/2091rank.html on October 15, 2011.
2 Sappenfield, W.M., Peck, M.G., Gilbert, C.S., Haynatzka, V.R., & Bryant, T. (2010). Perinatal Periods of Risk: Analytic Preparation and Phase 1 Analytic Methods for Investigating Feto-Infant Mortality. Maternal Child Health Journal, Published online 20 June 2010.
3 Bellinger, K., & Wolfe, S.M. (2011, September). The State of Infant Mortality. Presented at the Voices for Children of San Antonio 13th annual Congress on Children. San Antonio, TX