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Background There is a critical need for maternal and child health data at the local level (for example, county), yet most counties lack sustainable resources or capabilities to collect local-level data. In such case, model-based small area estimation (SAE) could be a feasible approach. SAE for maternal or infant health-related behaviors at small areas has never been conducted or evaluated. Methods We applied multilevel regression with post-stratification approach to produce county-level estimates using Pregnancy Risk Assessment Monitoring System (PRAMS) data, 2016–2018 (n = 65,803 from 23 states) for 2 key outcomes, breastfeeding at 8 weeks and infant non-supine sleeping position. Results Among the 1,471 counties, the median model estimate of breastfeeding at 8 weeks was 59.8% (ranged from 34.9 to 87.4%), and the median of infant non-supine sleeping position was 16.6% (ranged from 10.3 to 39.0%). Strong correlations were found between model estimates and direct estimates for both indicators at the state level. Model estimates for both indicators were close to direct estimates in magnitude for Philadelphia County, Pennsylvania. Conclusion Our findings support this approach being potentially applied to other maternal and infant health and behavioral indicators in PRAMS to facilitate public health decision-making at the local level.

Summarize policies on levels of neonatal care designation among 50 states and District of Columbia (DC). Systematic review of publicly available, web-based information on levels of neonatal care designation policies for each state/DC. Information on designating authorities, designation oversight, licensure requirement, and ongoing monitoring for designated levels of care abstracted from 2019 published rules, statutes, and regulations. Thirty-one (61%) of 50 states/DC had designated authority policies for neonatal levels of care. Fourteen (27%) incorporated oversight of neonatal levels of care into the licensure process. Among jurisdictions with designated authority, 25 (81%) used a state agency and 15 (48%) had direct oversight. Twenty-two (71%) of 31 states with a designating authority required ongoing monitoring, 14 (64%) used both hospital reporting and site visits for monitoring with only ten requiring site visits. Limited direct oversight influences regulation of regionalized systems, potentially impacting facility service monitoring and consequent management of vulnerable infants.

Supine sleep positioning (SSP) has been shown to reduce the risk of sudden infant death syndrome (SIDS) and preterm infants are at higher risk for SIDS. Population-based estimates of SSP are lacking for the preterm population. The objectives of this study are: (1) compare the prevalence of SSP after hospital discharge for preterm and term infants in the United States; and (2) assess racial/ethnic disparities in SSP for preterm and term infants.We analyzed the 2000 to 2011 data from the Pregnancy Risk Assessment Monitoring System of Centers for Disease Control and Prevention from 35 states. We measured prevalence of SSP by preterm and term gestational age (GA) categories. We calculated adjusted prevalence ratios (APR) to evaluate the likelihood of SSP for each GA category compared with term infants and the likelihood of SSP for non-Hispanic black (NHB) and Hispanic infants compared with non-Hispanic white (NHW) infants.Prevalence of SSP varied by GA: ⩽27, 59.7%; 28 0/7 to 33 6/7, 63.7%; 34 0/7 to 36 6/7 (late preterm), 63.6%; and 37 0/7 to 42 6/7 (term) weeks, 66.8% (P0.001). In the adjusted analyses, late preterm infants were slightly less likely to be placed in SSP compared with term infants (APR: 0.96, confidence interval: 0.95 to 0.98). There were racial/ethnic disparities in SSP for all GA categories when NHB and Hispanic infants were compared with NHW infants.All infants had suboptimal adherence to SSP indicating a continued need to better engage families about SSP. Parents of late preterm infants and families of NHB and Hispanic infants will also require greater attention given their decreased likelihood of SSP.

To compare fetal and first day outcomes of American Indian and Alaskan Natives (AIAN) with non-AIAN populations. Singleton deliveries to AIAN and non-AIAN populations were selected from live birth–infant death cohort and fetal deaths files from 1995–1998 and 2005–2008. We examined changes over time in maternal characteristics of deliveries and disparities and changes in risks of fetal, first day (

In December 2012, multiple leading agencies in the field of Maternal and Child Health (MCH) partnered to co-host a national MCH Epidemiology Conference. The Conference offered opportunities for peer exchange; presentation of new scientific methodologies, programs, and policies; dialogue on changes in the MCH field; and discussion of emerging MCH issues relevant to the work of MCH professionals. During the Conference, the MCH Epidemiology Program celebrated 25 years of success and partnership, and 16 MCH agencies presented six deserving health researchers and leaders with national awards in the areas of advancing knowledge, effective practice, outstanding leadership, excellence in teaching and mentoring, and young professional achievement. In September 2014, building on knowledge gained and changes in the field of MCH, leading agencies including the Centers for Disease Control and Prevention, the Health Resources and Services Administration, City- MatCH, and the Association of MCH Programs plan to replicate the achievements of 2012 through the implementation of a fully integrated national conference: the CityMatCH Leadership and MCH Epidemiology Conference.

Beginning in the 1980s, there was a growing recognition of the need to quantify the work and contributions of state maternal and child health (MCH) departments [1]. In 1987, the Maternal and Child Health Epidemiology Program (MCHEP) was initiated by the Centers for Disease Control and Prevention (CDC) and the Health Resources and Services Administration’s (HRSA) Maternal and Child Health Bureau (MCHB) to provide epidemiologic leadership for State MCH programs [2, 3]. The success of the MCHEP spawned subsequent initiatives to build MCH data capacity including the development of a National Action Agenda, which was led by the Association of Maternal and Child Health Programs (AMCHP) and CityMatch, and included other national organizations such as the Association of Schools of Public Health, the Association of Teachers of Maternal and Child Health, the Council of State and Territorial Epidemiologists (CSTE), and the National Association of County and City Health Officials [4, 5]. The National Action Agenda focused on increased funding in CDC and HRSA for three areas: better training, stronger data and information systems, and more field-based capacity building. These efforts contributed to a plethora of programs in these areas, including the strengthening of masters, doctoral, and post-doctoral MCH epidemiology training opportunities through programs such as: the MCHB MCH Graduate Student Epidemiology Program for master’s level students; the MCHB MCH Epidemiology Doctoral Fellowship Program; and the CDC/MCHB MCH Epidemiology Master’s and Post-Doctoral Fellows Program, directed by CSTE [6, 7]. Programs to strengthen the analytic skills of the present workforce have included: the MCHB/CDC MCH Epidemiology Methods Training Course; the MCHB MCH Navigator, designed to address and support continuous MCH professional and workforce development needs, including epidemiology; the CDC/MCHB pre-conference trainings at the MCH Epidemiology Conference, administered by the Association of Maternal and Child Health Programs, which have featured such trainings as data linkage, geographic information systems, and needs assessment; pre-conference trainings and focused MCH epidemiology tracks at the CityMatCH and Association of Maternal and Child Health Program Conferences, including trainings on synthetic estimates, small area analysis, and communicating data findings; the CDC evaluation practicum developed to provide a framework for evaluating state MCH programs; and the CDC distance-based course in epidemiologic methods [8–13]. Additionally, the MCH Epidemiology Conference was established in the mid-1990’s, and has served as the focal point for the latest developments in the field [14, 15]. In turn, many factors in maternal and child health data collection and analysis have improved. Since the inception of the program, the capacity of State MCH programs to provide and analyze data has greatly increased [16–19]. Data systems unavailable to states before the late 1980’s, such as linked birth-infant death files, the Pregnancy Risk Assessment Monitoring System (PRAMS), the Youth Risk Behavioral Surveillance System, the Title V Information System, the National Survey of Children’s Health (NSCH), the National Survey of Family Growth, and the National Survey of Children with Special Health Care Needs, are now routinely used. Data systems that are state-based have greatly enhanced our understanding of population-based factors, and have influenced state policies in maternal and child health. For example, data from the Pregnancy Risk Assessment Monitoring System has provided information on state smoking policies on maternal smoking and quit rates [20], breast feeding rates as affected by policy on hospital formula bags [21], and state early discharge policies for newborns [22]. Furthermore, advanced computer software has allowed data systems like vital statistics and Medicaid data to be linked to examine such issues as birth outcomes among Medicaid recipients. A major challenge for leadership in maternal and child health epidemiology was how to increase data and analytic capacity at the State level. In that regard, there has been a great deal of success, as measured by CSTE’s periodic surveys on epidemiologic capacity. From 2004 to 2009, MCH State epidemiologists had the second largest increase in staffing and analytic capacity among all the epidemiologic areas examined, after bioterrorism [23]. As a further measure of success, these assessments also indicated that the percent of states reporting full maternal and child health epidemiologic capacity increased during that time period from 43 to 55 %. Maternal and child health outcomes have also changed since the inception of MCH epidemiology programs. The preterm birth rate and low birth weight rate both rose over 20 % between the early 1990’s and 2006, then began a slight decline [24]. The cesarean section rate climbed almost 50 % between 1996 and 2010 [24]. The Back to Sleep Campaign and the introduction of pulmonary surfactants in the early 1990’s led to a decline in the infant mortality rate through 2000. Infant mortality remained stagnant till 2007, when the decline resumed [25, 26]; yet despite recent declines, the US ranks 34th in the world for infant mortality rates in 2011 [27]. The percent of children with special health care needs has increased, and much of that increase has occurred among developmental conditions such as autism spectrum disorders and attention deficit disorders [28]. The percent of children classified as overweight or obese increased dramatically between 1990 and 2010 [29, 30]. The analytic understanding of these changes in maternal and child health would not have occurred without the work of MCH epidemiologists. But, times have changed, and therefore, the challenges for MCH epidemiology have changed too. The passage of the Affordable Care Act (ACA) in 2010 increased the emphasis of the health care system on prevention and health promotion, as well as increasing coverage for those previously uninsured. Budgetary limitations have meant cutbacks at the local, State, and Federal levels, as well as even greater demands for accountability for dollars and demonstration of impact. It is becoming more difficult and costly to obtain needed data. There has been a decline in the response rates for all types of surveys, whether they are in-person surveys, like the National Health Interview Survey, or telephone surveys such as the National Survey of Children’s Health. It is no longer enough to report simple associations only between a risk factor and an outcome. Theories on life course and fetal origins of adult disease have accelerated the need to account for the complexities that shape the health of children. Prenatal and early life experiences have been seen as having increasing importance on the health of adult populations [31–33]. Advances in communication technology have also affected the speed and mechanisms of MCH information: policy makers and the public expect data and information to be provided more rapidly. What are the challenges that leaders in MCH epidemiology will face in the future?

The purpose of this article is to summarize the methodology, partnerships, and products developed as a result of a distance-based workforce development initiative to improve analytic capacity among maternal and child health (MCH) epidemiologists in state health agencies. This effort was initiated by the Centers for Disease Control's MCH Epidemiology Program and faculty at the University of Illinois at Chicago to encourage and support the use of surveillance data by MCH epidemiologists and program staff in state agencies. Beginning in 2005, distance-based training in advanced analytic skills was provided to MCH epidemiologists. To support participants, this model of workforce development included: lectures about the practical application of innovative epidemiologic methods, development of multidisciplinary teams within and across agencies, and systematic, tailored technical assistance The goal of this initiative evolved to emphasize the direct application of advanced methods to the development of state data products using complex sample surveys, resulting in the articles published in this supplement to MCHJ. Innovative methods were applied by participating MCH epidemiologists, including regional analyses across geographies and datasets, multilevel analyses of state policies, and new indicator development. Support was provided for developing cross-state and regional partnerships and for developing and publishing the results of analytic projects. This collaboration was successful in building analytic capacity, facilitating partnerships and promoting surveillance data use to address state MCH priorities, and may have broader application beyond MCH epidemiology. In an era of decreasing resources, such partnership efforts between state and federal agencies and academia are essential for promoting effective data use.

States can improve pregnancy outcomes by using a standard approach to assess infant mortality. The State Infant Mortality Collaborative (SIMC) developed a series of analyses to describe infant mortality in states, identify contributing factors to infant death, and develop the evidence base for implementing new or modifying existing programs and policies addressing infant mortality. The SIMC was conducted between 2004 and 2006 among five states: Delaware, Hawaii, Louisiana, Missouri, and North Carolina. States used analytic strategies in an iterative process to investigate contributors to infant mortality. Analyses were conducted within three domains: data reporting (quality, reporting, definitional criteria, and timeliness), cause and timing of infant death (classification of cause and fetal, neonatal, and postneonatal timing), and maturity and weight at birth/maturity and birth weight-specific mortality. All states identified the SIMC analyses as useful for examining infant mortality trends. In each of the three domains, SIMC results were used to identify important direct contributors to infant mortality including disparities, design or implement interventions to reduce infant death, and identify foci for additional analyses. While each state has unique structural, political, and programmatic circumstances, the SIMC model provides a systematic approach to investigating increasing or static infant mortality rates that can be easily replicated in all other states and allows for cross-state comparison of results.

The purpose was to examine changes in overall and gestational age-specific proportions and rates of fetal death, first day death (

The purpose of this study was to describe variation among states in designations of hospital neonatal services levels. We systematically searched all 50 states and District of Columbia governmental web sites and extracted definitions and levels terminology, functional and utilization criteria, regulatory compliance and funding measures, and citation of American Academy of Pediatrics (AAP) documents on levels of neonatal care. Thirty-three states designate multiple graduated levels of neonatal services. Two to six levels were designated by numbers, titles, or both. Regulatory sources include hospital licensure, Certificate of Need or State Health Plan (CON/SHP), State Health Department, or an affiliated non-governmental entity (SHD/affiliate). Twenty-four states have a single source and nine have two or more. Functional criteria include population characteristics, respiratory care capabilities, and neonatal and cardiac surgery in 25 states. Utilization criteria include capacity, volume, occupancy, or case mix. Compliance mechanisms include license renewal, CON/SHP approval, and/or SHD/affiliate certification. Thirteen states link funding for the highest level of care through Medicaid, Maternal Child Health Title V funds or regional programs. AAP documents are cited or incorporated by reference in 22 states. All states regulate health care services and facilities. Definitions, criteria, compliance mechanisms, and regulatory source and status of neonatal levels of service vary widely. A consistent national approach would facilitate comparisons in neonatal outcomes and resource use and be informative to parents, providers, and policy makers. AAP documents could serve as a mechanism to foster such consistency.

Objectives To evaluate whether Massachusetts Early Intervention (EI) serves children at risk of developmental delay due to social factors, we identified socio-demographic characteristics associated with program enrollment and examined predictors of participation at each stage from referral to enrollment. Methods The Pregnancy to Early Life Longitudinal (PELL) data system linked birth certificate, hospital discharge, and EI data for all Massachusetts births, 1998–2000. We identified predictors of enrollment among births and predictors of referral, eligibility evaluation among those referred, and enrollment among eligible children using multivariate modified Poisson models to adjust for medical risks. Results Overall, 29,950 children (13.7% of births) enrolled in EI. Most social risk indicators predicted enrollment, including maternal government insurance (RR = 1.32, 95% CI 1.29–1.36) and maternal education ≤10 years (RR = 1.36, 95% CI 1.30–1.42). Having a foreign-born (RR = 0.77, 95% CI 0.74–0.80), non-English speaking (RR = 0.93, 95% CI 0.89–0.97) or Asian (RR = 0.88, 95% CI 0.82–0.94) mother was negatively associated with enrollment. Of births, 18.6% were referred to EI. Similar socio-demographic variables predicted referral as predicted enrollment. Among referrals, 87.7% received an evaluation. Evaluation was negatively associated with young maternal age, black maternal race, and high poverty level. Of eligible children, 93.0% enrolled. Enrollment among eligible children was negatively associated with young maternal age and high poverty level. Conclusion In Massachusetts, children born with social risk factors have high EI participation. Nevertheless, children in immigrant communities may face barriers to initial contact with EI, while children from low socioeconomic environments may be at risk for not enrolling after EI referral.

Objective To identify challenges that women face 2–9 months postpartum using qualitative data gathered by the Pregnancy Risk Assessment Monitoring System (PRAMS). Methods PRAMS is an on-going population-based surveillance system that collects self-reported information on maternal behaviors and experiences before, during, and after the birth of a live infant. We analyzed free text comment data from women in 10 states who answered the PRAMS survey in 2000. Preliminary analysis included a review of the comment data to identify major themes and a demographic comparison of women who commented (n = 3,417) versus women who did not (n = 12,497). Subsequent analysis included systematic coding of the data from 324 women that commented about postpartum concerns and evaluation to ensure acceptable levels of reliability among coders. Results We identified the following major themes, listed in order of frequency: (1) need for social support, (2) breastfeeding issues, (3) lack of education about newborn care after discharge, (4) need for help with postpartum depression, (5) perceived need for extended postpartum hospital stay, and (6) need for maternal insurance coverage beyond delivery. Conclusion The themes identified indicate that new mothers want more social support and education and that some of their concerns relate to policies regarding breastfeeding and medical care. These results can be used to inform programs and policies designed to address education and continuity of postpartum care for new mothers.

Many of the articles in this issue of the Maternal and Child Health (MCH) Journal showcase examples of the high-level applied research currently being conducted by MCH epidemiologists working in state health agencies. This work is in part a product of a collaboration between the MCH Epidemiology Program (MCHEP) at the Centers for Disease Control and Prevention (CDC) and MCH epidemiology faculty at the University of Illinois at Chicago School of Public Health (UIC-SPH)—a collaboration that provided ongoing, distance-based, advanced training and technical assistance in analytic methods for 7 years. For an in-depth description of this collaboration, see the article by Rankin et al. [1] later in this supplement. This collaboration was one of the many workforce development initiatives designed to build analytic capacity in state and local health agencies sponsored by the CDC, HRSA/MCHB, City-MatCH, the Council of State and Territorial Epidemiologists (CSTE) and others over the past 25 years. As discussed in the commentary in this issue by Phillips et al. [2] these capacity building efforts have taken many forms, including face-to-face workshops, distance-based courses, blended trainings, academic degree programs, fellowships, and internships

To evaluate the outcome of an early discharge program regarding the length of stay, hospital expense, maternal satisfaction, and patient safety in a military population.