Carol S Gilbert1, Pamela K Xaverius2,3, Melissa K Tibbits4, William M Sappenfield5. 1. CityMatCH and the Division of Child Health Policy, Department of Pediatrics, University of Nebraska Medical Center, 982155, Nebraska Medical Center, Omaha, NE, USA. cgilbert@unmc.edu. 2. Maternal and Child Health Center of Excellence in Education, Science, and Practice, Department of Epidemiology and Biostatistics, College for Public Health and Social Justice, Saint Louis University, St. Louis, MO, USA. 3. Research and Scholarly Activity, University of Health Sciences and Pharmacy in St. Louis, 1 Pharmacy Place, St. Louis, MO, USA. 4. Health Promotion, College of Public Health, University of Nebraska Medical Center, Omaha, NE, USA. 5. The Chiles Center, College of Public Health, University of South Florida, Tampa, FL, USA.
Abstract
INTRODUCTION: The Perinatal Periods of Risk approach (PPOR) is designed for use by communities to assess and address the causes of high fetal-infant mortality rates using vital records data. The approach is widely used by local health departments and their community and academic partners to inform and motivate systems changes. PPOR was developed and tested in communities based on data years from 1995 to 2002. Unfortunately, a national reference group has not been published since then, primarily due to fetal death data quality limitations. METHODS: This paper assesses data quality and creates a set of unbiased national reference groups using 2014-2016 national vital records data. Phase 1 and Phase 2 analytic methods were used to divide excess mortality into six components and create percentile plots to summarize the distribution of 100 large US counties for each component. RESULTS: Eight states with poor fetal death data quality were omitted from the reference groups to reduce bias due to missing maternal demographic information. There are large Black-White disparities among reference groups with the same age and education restrictions, and these vary by component. PPOR results vary by region, maternal demographics, and county. The magnitude of excess mortality components varies widely across US counties. DISCUSSION: New national reference groups will allow more communities to do PPOR. Percentile plots of 100 large US counties provide an additional benchmark for new communities using PPOR and help emphasize problem areas and potential solutions.
INTRODUCTION: The Perinatal Periods of Risk approach (PPOR) is designed for use by communities to assess and address the causes of high fetal-infant mortality rates using vital records data. The approach is widely used by local health departments and their community and academic partners to inform and motivate systems changes. PPOR was developed and tested in communities based on data years from 1995 to 2002. Unfortunately, a national reference group has not been published since then, primarily due to fetal death data quality limitations. METHODS: This paper assesses data quality and creates a set of unbiased national reference groups using 2014-2016 national vital records data. Phase 1 and Phase 2 analytic methods were used to divide excess mortality into six components and create percentile plots to summarize the distribution of 100 large US counties for each component. RESULTS: Eight states with poor fetal death data quality were omitted from the reference groups to reduce bias due to missing maternal demographic information. There are large Black-White disparities among reference groups with the same age and education restrictions, and these vary by component. PPOR results vary by region, maternal demographics, and county. The magnitude of excess mortality components varies widely across US counties. DISCUSSION: New national reference groups will allow more communities to do PPOR. Percentile plots of 100 large US counties provide an additional benchmark for new communities using PPOR and help emphasize problem areas and potential solutions.
Authors: Samuel H Fishman; Robert A Hummer; Gracia Sierra; Taylor Hargrove; Daniel A Powers; Richard G Rogers Journal: Biodemography Soc Biol Date: 2020 Jan-Mar