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Determine odds ratios for neonatal abstinence syndrome (NAS) and neonatal intensive care unit (NICU) admissions for babies born to women associated with severe mental illness (SMI) and gestational opioid use.A retrospective pharmacoepidemiologic study using Medicaid data included 17,130 mothers with and 170,430 mothers without SMI, and their babies. Odds ratios for NAS and NICU admissions among babies born to mothers associated with SMI diagnoses and associated with varying degrees of gestational opioid use were determined using logistic regression.The adjusted odds ratio for a baby in the methadone or buprenorphine group having NAS was 168.93 [95% confidence interval (CI) 148.78-191.71, P 0.001] and was 9.64 (95% CI 8.74-10.65, P 0.001) for NICU admissions compared to babies with no opioid exposure.Chronicity of prescription maternal opioid use was the strongest factor associated with NAS and NICU admissions.

Background Children with developmental disabilities are at an increased risk of unhealthy eating habits, which may contribute to compromised growth and development. Children with autism spectrum disorder (ASD) exhibit unique risk factors for unhealthy dietary patterns, including sensory issues and cognitive rigidity at mealtimes. Objective This cross-sectional study examined diet quality in a sample of children with ASD in Florida compared to nationally representative National Health and Nutrition Examination Survey (NHANES) 2009–2014/2013-2014 data using the Healthy Eating Index-2015 (HEI-2015). Methods A 24-h food record was completed by 41 parents of children with ASD aged 2–17 years, and food and beverage items consumed by each child were reported per standardized 24-h recall protocol. Two models were used to compare mean total and component HEI-2015 scores to NHANES means: (1) comparing means for our full sample to published NHANES means for children aged 2–18 years and (2) a matched model with subjects matched 1:1 by age, gender, race/ethnicity, and parent education level. Results HEI component scores were significantly lower (poorer) in children with ASD for whole fruit, total vegetables, dairy, total protein foods, and seafood and plant protein. Whole grains, fatty acids, added sugars, and refined grains scores were higher (better) in our sample. However, total HEI scores and HEI scores for all 13 components were similar among children with ASD and the matched cases from the NHANES data. Conclusions There are potential discrepancies in diet quality between children with ASD and general population. Further research with a larger sample size, reporting both total and component HEI scores, is needed.

BACKGROUND/OBJECTIVES: In this report, the National Birth Defects Prevention Network (NBDPN) examines and compares gastroschisis and omphalocele for a recent 5-year birth cohort using data from 30 population-based birth defect surveillance programs in the United States. METHODS: As a special call for data for the 2019 NBDPN Annual Report, state programs reported expanded data on gastroschisis and omphalocele for birth years 2012–2016. We estimated the overall prevalence (per 10,000 live births) and 95% confidence intervals (CI) for each defect as well as by maternal race/ethnicity, maternal age, infant sex, and case ascertainment methodology utilized by the program (active vs. passive). We also compared distribution of cases by maternal and infant factors and presence/absence of other birth defects. RESULTS: The overall prevalence estimates (per 10,000 live births) were 4.3 (95% CI:4.1–4.4) for gastroschisis and 2.1 (95% CI: 2.0–2.2) for omphalocele. Gastroschisis was more frequent among young mothers (40 years). Mothers of infants with gastroschisis were more likely to be underweight/normal weight prior to pregnancy and mothers of infants with omphalocele more likely to be overweight/obese. Omphalocele was twice as likely as gastroschisis to co-occur with other birth defects. CONCLUSIONS: This report highlights important differences between gastroschisis and omphalocele. These differences indicate the importance of distinguishing between these defects in epidemiologic assessments. The report also provides additional data on co-occurrence of gastroschisis and omphalocele with other birth defects. This information can provide a basis for future research to better understand these defects.

Background Many public health surveillance programs utilize hospital discharge data in their estimation of disease prevalence. These databases commonly use the International Classification of Diseases (ICD) coding scheme, which transitioned from the ICD-9 clinical modification (ICD-9-CM) to ICD-10-CM on October 1, 2015. This study examined this transition's impact on the prevalence of major birth defects among infant hospitalizations. Methods Using data from the Agency for Health Care Research and Quality-sponsored National Inpatient Sample, hospitalizations during the first year of life with a discharge date between January 1, 2012 and December 31, 2016 were used to estimate the monthly national hospital prevalence of 46 birth defects for the ICD-9-CM and ICD-10-CM timeframes separately. Survey-weighted Poisson regression was used to estimate 95% confidence intervals for each hospital prevalence. Interrupted time series framework and corresponding segmented regression was used to estimate the immediate change in monthly hospital prevalence following the ICD-9-CM to ICD-10-CM transition. Results Between 2012 and 2016, over 21 million inpatient hospitalizations occurred during the first year of life. Among the 46 defects studied, statistically significant decreases in the immediate hospital prevalence of five defects and significant increases in the immediate hospital prevalence of eight defects were observed after the ICD-10-CM transition. Conclusions Changes in prevalence were expected based on changes to ICD-10-CM. Observed changes for some conditions may result from variation in monthly hospital prevalence or initial unfamiliarity of coders with ICD-10-CM. These findings may help birth defects surveillance programs evaluate and interpret changes in their data related to the ICD-10-CM transition.

Objective:To investigate the relationship between maternal autonomy and various indices of child undernutrition among children aged Design:Population-based, cross-sectional study. Associations between various indices of maternal autonomy and child undernutrition (specifically stunting, underweight and wasting) were determined using weighted bivariate and multivariable logistic regression modelling.Setting:2013 Nigerian Demographic Health Survey.Participants:Children aged between 3 and 24 months (n 7532).Results:Overall, 31·4 % (n 2270), 29·8 % (n 2060) and 25·0 % (n 1755) of children in the sample were stunted, underweight and wasted, respectively. Women with acceptance of domestic violence (low autonomy) were approximately 18 and 14 % less likely to have stunted (OR = 0·82; 95 % CI 0·71, 0·94) and underweight children (OR = 0·86; 95 % CI 0·75, 0·99), respectively. Similarly, women with low power in their couple relations were 17 % less likely to have children who were wasted (OR = 0·83; 95 % CI 0·72, 0·97). Sociodemographic predictors of all indices of undernutrition included maternal education and Hausa ethnicity. Additionally, stunting was predicted by lack of exclusive breast-feeding, low income and being of Fulani ethnicity; wasting by having mothers with low BMI; and underweight by breast-feeding initiation within 1 h hour of birth, polygamous homes, mothers with low BMI and being of Fulani ethnicity.Conclusions:Women with acceptance of domestic violence and low power in couple relations were found to be less likely to have children with indices of undernutrition. This unexpected finding calls for future exploratory research, and policies and interventions that target at-risk subgroups.

BACKGROUND: Congenital diaphragmatic hernia (CDH) is a rare musculoskeletal birth defect with a prevalence of 2.61 per 10,000 in the United States. There is limited evidence for ambient air pollutants in the etiology of CDH in humans. OBJECTIVES: We investigated the role of maternal exposure to ambient cadmium as a risk factor for CDH (overall and stratified by isolated and non-isolated subtypes) in Florida and whether maternal smoking during pregnancy was an effect modifier of this association. METHODS: We conducted a population-based, retrospective cohort study using data from the 1999–2012 Florida Birth Defects Registry linked to the National Air Toxic Assessment database. Analyses included chi–square tests; multilevel Poisson regression models to calculate measures of association between cadmium and CDH; and stratified analyses to examine effect modification by maternal smoking status. RESULTS: The study population consisted of 2,591,395 live births including 840 CDH cases. We did not find evidence for an association between maternal exposure to ambient cadmium concentration and CDH. We observed a 24% increased risk of CDH among isolated cases in the highest quartile of cadmium exposure (95% confidence interval [CI]: 1.00, 1.55). Although we were limited by small sample size for CDH cases, we found that among mothers who smoked during pregnancy, exposure to the highest quartile of cadmium was associated with more than two times higher risk for CDH among overall (95%CI: 1.04, 4.39) and isolated (95%CI: 1.07, 5.57) cases. CONCLUSIONS: Additional research is needed to elucidate the mechanism by which maternal ambient cadmium exposure may increase the risk of CDH in offspring, and the extent to which maternal smoking during pregnancy modifies this association

Background Using the National Birth Defects Prevention Network (NBDPN) annual data report, U.S. national prevalence estimates for major birth defects are developed based on birth cohort 2010-2014. Methods Data from 39 U.S. population-based birth defects surveillance programs (16 active case-finding, 10 passive case-finding with case confirmation, and 13 passive without case confirmation) were used to calculate pooled prevalence estimates for major defects by case-finding approach. Fourteen active case-finding programs including at least live birth and stillbirth pregnancy outcomes monitoring approximately one million births annually were used to develop national prevalence estimates, adjusted for maternal race/ethnicity (for all conditions examined) and maternal age (trisomies and gastroschisis). These calculations used a similar methodology to the previous estimates to examine changes over time. Results The adjusted national birth prevalence estimates per 10,000 live births ranged from 0.62 for interrupted aortic arch to 16.87 for clubfoot, and 19.93 for the 12 critical congenital heart defects combined. While the birth prevalence of most birth defects studied remained relatively stable over 15 years, an increasing prevalence was observed for gastroschisis and Down syndrome. Additionally, the prevalence for atrioventricular septal defect, tetralogy of Fallot, omphalocele, and trisomy 18 increased in this period compared to the previous periods. Active case-finding programs generally had higher prevalence rates for most defects examined, most notably for anencephaly, anophthalmia/microphthalmia, trisomy 13, and trisomy 18. Conclusion National estimates of birth defects prevalence provide data for monitoring trends and understanding the impact of these conditions. Increasing prevalence rates observed for selected conditions warrant further examination.

Background Children with intellectual disability (ID), characterized by impairments in intellectual functioning and adaptive behavior, benefit from early identification and access to services. Previous U.S. estimates used administrative data or parent report with limited information for demographic subgroups. Objective Using empiric measures we examined ID characteristics among 8-year-old children and estimated prevalence by sex, race/ethnicity, geographic area and socioeconomic status (SES) area indicators. Methods We analyzed data for 8-year-old children in 9 geographic areas participating in the 2014 Autism and Developmental Disabilities Monitoring Network. Children with ID were identified through record review of IQ test data. Census and American Community Survey data were used to estimate the denominator. Results Overall, 11.8 per 1,000 (1.2%) had ID (IQ ≤ 70), of whom 39% (n = 998) also had autism spectrum disorder. Among children with ID, 1,823 had adaptive behavior test scores for which 64% were characterized as impaired. ID prevalence per 1,000 was 15.8 (95% confidence interval [95% CI], 15.0–16.5) among males and 7.7 (95% CI, 7.2–8.2) among females. ID prevalence was 17.7 (95% CI, 16.6–18.9) among children who were non-Hispanic black; 12.0 (95% CI, 11.1–13.0), among Hispanic; 8.6 (95% CI, 7.1–10.4), among non-Hispanic Asian; and 8.0 (95% CI, 7.5–8.6), among non-Hispanic white. Prevalence varied across geographic areas and was inversely associated with SES. Conclusions ID prevalence varied substantively among racial, ethnic, geographic, and SES groups. Results can inform strategies to enhance identification and improve access to services particularly for children who are minorities or living in areas with lower SES.

While the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) provides numerous benefits to many enrolled families across the United States, including access to nutritious foods, some recent drops in maternal participation in Kentucky resulted from failures to retrieve those benefits. We explored perceived benefits of and encountered barriers to food benefit retrieval. Journey mapping included direct observations of client appointments, clinic lobby areas, and a shopping experience and was augmented with focus groups conducted in two urban and two rural areas. Major touchpoints before WIC appointments, during those appointments at clinics, and after appointments when redeeming food benefits were identified. Across touchpoints, mothers identified childcare, transportation issues, long waits, confusion regarding eligibility, problems scheduling appointments, and stigma as barriers to their ability to retrieve food instruments. Despite these barriers mothers value the benefits of WIC, especially access to healthy foods, infant formula, and nutrition education. This work demonstrates a method by which WIC mothers’ experiences shed light on client service shortfalls and possible opportunities to improve client services.

We identify women most and least likely to discontinue participation in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) program. Kentucky WIC program management in...

The field of spatial epidemiology has evolved rapidly in the past 2 decades. This study serves as a brief introduction to spatial epidemiology and the use of geographic information systems in applied research in epidemiology. We highlight technical developments and highlight opportunities to apply spatial analytic methods in epidemiologic research, focusing on methodologies involving geocoding, distance estimation, residential mobility, record linkage and data integration, spatial and spatio-temporal clustering, small area estimation, and Bayesian applications to disease mapping. The articles included in this issue incorporate many of these methods into their study designs and analytical frameworks. It is our hope that these studies will spur further development and utilization of spatial analysis and geographic information systems in epidemiologic research.

Background Congenital microcephaly has been linked to maternal Zika virus infection. However, ascertaining infants diagnosed with microcephaly can be challenging. Methods Thirty birth defects surveillance programs provided data on infants diagnosed with microcephaly born 2009 to 2013. The pooled prevalence of microcephaly per 10,000 live births was estimated overall and by maternal/infant characteristics. Variation in prevalence was examined across case finding methods. Nine programs provided data on head circumference and conditions potentially contributing to microcephaly. Results The pooled prevalence of microcephaly was 8.7 per 10,000 live births. Median prevalence (per 10,000 live births) was similar among programs using active (6.7) and passive (6.6) methods; the interdecile range of prevalence estimates was wider among programs using passive methods for all race/ethnicity categories except Hispanic. Prevalence (per 10,000 live births) was lowest among non-Hispanic Whites (6.5) and highest among non-Hispanic Blacks and Hispanics (11.2 and 11.9, respectively); estimates followed a U-shaped distribution by maternal age with the highest prevalence among mothers

Background Once a woman has had a fetus or infant affected with a neural tube defect (NTD), the risk of recurrence is approximately 3%. This risk can be significantly reduced by folic acid supplement consumption during the periconceptional period; however, this requires women at risk to be adequately informed about the appropriate dosage and timing of supplement intake before planning another pregnancy. As birth defects surveillance programs are tasked with identifying and documenting NTD-affected pregnancies and births, they are in a unique position to support recurrence prevention activities. Methods In 2015, we surveyed state and provincial birth defects surveillance programs to assess their NTD recurrence prevention activities. The online survey was sent to programs in 52 United States (U.S.) jurisdictions and all 13 provinces and territories in Canada. Findings were compared with a similar survey conducted in 2005 among U.S. programs. Results In 2015, of the 44 U.S. and Canadian surveillance programs that responded, only 9 programs (7 U.S. and 2 Canadian) reported currently having activities specifically directed toward preventing NTD recurrence. Compared with a 2005 survey of U.S. programs, the number of U.S. programs working on NTD recurrence prevention decreased by almost 50% (from 13 to 7 programs). Conclusion The number of birth defects surveillance programs with NTD recurrence prevention activities has decreased over the past decade due to a range of barriers, most notably a lack of resources. However, while some recurrence prevention activities require part-time staff, other activities could be accomplished using minimal resources. Birth Defects Research (Part A) 106:875–880, 2016.© 2016 Wiley Periodicals, Inc.

The effects of postpartum weight retention on gestational weight gain in successive pregnancies require elucidation. The purpose of the study was (1) to examine the association between postpartum weight retention and subsequent adherence to the Institute of Medicine gestational weight gain guidelines and (2) to determine whether the association varies by body mass index status and affects birth outcomes. Florida vital records for 2005-2010 were analyzed using χ tests and multivariable Poisson regression, adjusted for interpregnancy interval, tobacco use, maternal age, and race/ethnicity. Obese women who gained inadequate weight were more likely to retain weight between pregnancies than obese women who met or exceeded the recommended weight gain. Risks for preterm birth increased among women with inadequate weight and decreased among women with excessive weight gain. Gaining excessive weight was protective for small-for-gestational age infants in all body mass index categories but increased the risks for large-for-gestational age infants. Underweight and normal weight women who gained in excess were 40% more likely to develop hypertension than normal weight women who gained within the recommended amount. Obese women who retain or gain weight postpartum are at increased risk for inadequate weight gain in a successive pregnancy. Achieving Institute of Medicine-recommended gestational weight gain is essential for preventing adverse maternal and infant outcomes.

Spatio-temporal analysis of small area health data often involves choosing a fixed set of predictors prior to the final model fit. In this paper, we propose a spatio-temporal approach of Bayesian model selection to implement model selection for certain areas of the study region as well as certain years in the study time line. Here, we examine the usefulness of this approach by way of a large-scale simulation study accompanied by a case study. Our results suggest that a special case of the model selection methods, a mixture model allowing a weight parameter to indicate if the appropriate linear predictor is spatial, spatio-temporal, or a mixture of the two, offers the best option to fitting these spatio-temporal models. In addition, the case study illustrates the effectiveness of this mixture model within the model selection setting by easily accommodating lifestyle, socio-economic, and physical environmental variables to select a predominantly spatio-temporal linear predictor.

Introduction Cette étude visait à évaluer le biais dans la mesure de l’indice de masse corporelle (IMC) dans l’Enquête canadienne sur l’expérience de la maternité (ECEM) ainsi que les répercussions possibles de ce biais sur l’association entre l’IMC et certaines issues de grossesse. Méthodologie Nous avons évalué la répartition des valeurs de l’IMC en comparant des données autodéclarées et des données mesurées. Nous avons utilisé un échantillon aléatoire de 6 175 participantes à l’ECEM dont l’IMC avait été calculé d’après la taille et le poids autodéclarés et un échantillon aléatoire de 259 participantes à l’Enquête canadienne sur les mesures de santé (ECMS) ayant déjà accouché et dont l’IMC avait été calculé d’après la taille et le poids autodéclarés et mesurés. Nous avons appliqué deux équations de correction à l’IMC fondé sur des valeurs autodéclarées, et nous avons examiné l’impact de ces corrections sur les associations entre l’IMC et un accouchement par césarienne, un faible poids pour l’âge gestationnel (FPAG) et un poids élevé pour l’âge gestationnel (PEAG). Résultats Dans l’ensemble, 86,9 % des femmes du sous-échantillon de l’ECMS appartenaient à la même catégorie d’IMC lorsque ses valeurs étaient autodéclarées et lorsqu’elles étaient mesurées. Cependant, les différences de répartition ont eu un effet considérable sur la proportion de femmes des catégories de poids insuffisant et d’obésité. Par exemple, le pourcentage de femmes classées comme obèses était de 14,5 % avec les données autodéclarées contre 20,8 % avec les données mesurées. Les corrections ont permis d’améliorer les estimations de la prévalence de l’obésité, mais ont surestimé ou sous-estimé les autres catégories d’IMC. Les corrections ont eu un effet non significatif sur les associations entre l’IMC et l’accouchement par césarienne, le FPAG et le PEAG. Conclusion Bien que la concordance pour la répartition des valeurs de l’IMC entre la taille et le poids autodéclarés et la taille et le poids mesurés soit élevée, il existe un biais dans les mesures fondées sur les valeurs autodéclarées susceptible d’entraîner de légères surestimations ou sous-estimations des risques associés à une catégorie d’IMC donnée. La tendance générale des associations reste néanmoins inchangée.

Spatial data are often aggregated from a finer (smaller) to a coarser (larger) geographical level. The process of data aggregation induces a scaling effect which smoothes the variation in the data. To address the scaling problem, multiscale models that link the convolution models at different scale levels via the shared random effect have been proposed. One of the main goals in aggregated health data is to investigate the relationship between predictors and an outcome at different geographical levels. In this paper, we extend multiscale models to examine whether a predictor effect at a finer level hold true at a coarser level. To adjust for predictor uncertainty due to aggregation, we applied measurement error models in the framework of multiscale approach. To assess the benefit of using multiscale measurement error models, we compare the performance of multiscale models with and without measurement error in both real and simulated data. We found that ignoring the measurement error in multiscale models underestimates the regression coefficient, while it overestimates the variance of the spatially structured random effect. On the other hand, accounting for the measurement error in multiscale models provides a better model fit and unbiased parameter estimates.

We investigate uncertainty in estimates of pregnant women's exposure to ambient PM 2.5 and benzene derived from central-site monitoring data. Through a study of live births in Florida during 2000–2009, we discuss the selection of spatial and temporal scales of analysis, limiting distances, and aggregation method. We estimate exposure concentrations and classify exposure for a range of alternatives, and compare impacts. Estimated exposure concentrations were most sensitive to the temporal scale of analysis for PM 2.5 , with similar sensitivity to spatial scale for benzene. Using 1–12 versus 3–8 weeks of gestational age as the exposure window resulted in reclassification of exposure by at least one quartile for up to 37% of mothers for PM 2.5 and 27% for benzene. The largest mean absolute differences in concentration resulting from any decision were 0.78 µg/m 3 and 0.44 ppbC, respectively. No bias toward systematically higher or lower estimates was found between choices for any decision.

This study examined associations between ASD diagnosis retention and non-ASD co-occurring conditions (CoCs) by child sex. The sample included 7077 males and 1487 females who had an ASD diagnosis documented in their school or health records in a population-based ASD surveillance system for 8-year-old children. ASD diagnosis retention status was determined when an initial ASD diagnosis was not later ruled out by a community professional. We found that ASD diagnosis remains fairly stable, with only 9% of children who had an initial documented ASD diagnosis later being ruled-out. Although most of the associations between the ASD diagnosis retention status and CoCs are similar in both sexes, the co-occurrence of developmental diagnoses (e.g., intellectual disability or sensory integration disorder) was predictive of ASD diagnostic changes in males, whereas the co-occurrence of specific developmental (e.g., personal/social delay) and neurological diagnosis (e.g., epilepsy) was associated with ASD diagnostic change in females. More ASD-related evaluations and less ASD-related impairment were associated with later ASD rule outs in both sexes. Our findings highlight that CoCs can complicate the diagnostic picture and lead to an increased likelihood of ambiguity in ASD diagnosis. Using sensitive and appropriate measures in clinical practice is necessary for differential diagnosis, particularly when there are co-occurring developmental conditions.

* Abbreviation: ART — : assisted reproductive technology Assisted reproductive technologies (ARTs), including in vitro fertilization with fresh or frozen embryos as well as intracytoplasmic sperm injection, have come into increasing use in Western nations since the late 1970s. Pregnancies resulting from ART are more likely to result in stillbirth, multiple gestation, preterm delivery, and low birth weight, with higher rates of adverse outcomes after procedures that involve the placing of either a single embryo or multiple embryos.1 Infant mortality rates are higher as well, whereas evidence for an increased risk of specific birth defects is equivocal.2–4 Research on child health and developmental outcomes is more limited, and for this reason, the study by Hansen et al5 is a welcome addition to our literature. Hansen et al5 use population-based data from Western Australia garnered through probabilistic record linkage based … Address correspondence to Russell S. Kirby, PhD, MS, FACE, College of Public Health, University of South Florida, 13201 Bruce B. Downs Blvd, MDC 56, Tampa, FL 33612. E-mail: rkirby{at}health.usf.edu

Background/objectives In this data brief, we examine major eye and ear anomalies (anophthalmia/microphthalmia, anotia/microtia, and congenital cataract) for a recent 5-year birth cohort using data from 30 population-based birth defects surveillance programs in the United States. Methods As a special call for data for the 2018 NBDPN Annual Report, state programs reported expanded data on eye/ear anomalies for birth years 2011-2015. We calculated the combined overall prevalence (per 10,000 live births) and 95% confidence intervals (CI), for the three anomalies as well as by maternal age, maternal race/ethnicity, infant sex, laterality, presence/absence of other major birth defects, and case ascertainment methodology utilized by the program (active vs. passive). Results The overall prevalence estimate (per 10,000 live births) was 1.5 (95% CI: 1.4-1.5) for anophthalmia/microphthalmia, 1.5 (95% CI: 1.4-1.6) for congenital cataract, and 1.8 (95% CI: 1.7-1.8) for anotia/microtia. Congenital cataract prevalence varied little by maternal race/ethnicity, infant sex, or case ascertainment methodology; prevalence differences were more apparent across strata for anophthalmia/microphthalmia and anotia/microtia. Prevalence among active vs. passive ascertainment programs was 50% higher for anophthalmia/microphthalmia (1.9 vs. 1.2) and two-fold higher for anotia/microtia (2.6 vs. 1.2). Anophthalmia/microphthalmia was more likely than other conditions to co-occur with other birth defects. All conditions were more frequent among older mothers (40+ years). Conclusions This data brief provides recent prevalence estimates for anophthalmia/microphthalmia, congenital cataract, and anotia/microtia that address a data gap by examining pooled data from 30 population-based surveillance systems, covering a five-year birth cohort of about 12.4 million births.

Background The World Health Organization (WHO) recommends that women wait at least 24 months after a livebirth before attempting a subsequent pregnancy to reduce the risk of adverse maternal, perinatal, and infant health outcomes. However, the applicability of the WHO recommendations for women in the United States is unclear, as breast feeding, nutrition, maternal age at first birth, and total fertility rate differs substantially between the United States and the low‐ and middle‐resource countries upon which most of the evidence is based. Methods To inform guideline development for birth spacing specific to women in the United States, the Office of Population Affairs (OPA) convened an expert work group meeting in Washington, DC, on 14‐15 September 2017 among reproductive, perinatal, paediatric, social, and public health epidemiologists; obstetrician‐gynaecologists; biostatisticians; and experts in evidence synthesis related to women's health. Results Presentations and discussion topics included the methodological quality of existing studies, evaluation of the evidence for causal effects of short interpregnancy intervals on adverse perinatal and maternal health outcomes, good practices for future research, and identification of research gaps and priorities for future work. Conclusions This report provides an overview of the presentations, discussions, and conclusions from the expert work group meeting.

OBJECTIVES: We examined trends in prevalence rates of smoking and smoking cessation during pregnancy among women in the United States to assess achievement of Healthy People 2020 prevention targets. METHODS: We assessed the smoking habits of 30 667 mothers whose children were born between 1985 and 2014 and who were sampled by the National Health and Nutrition Examination Survey, 1999-2014. Sampled participants were children aged 0-15 at the time of interview; however, an adult proxy—usually the biological mother—responded on the child’s behalf and reported information about maternal tobacco use during pregnancy. We calculated prevalence rates, adjusted odds ratios (aORs), and predicted annual increase or decrease of smoking and quitting smoking during pregnancy, adjusting for mother’s age at delivery and income level and child’s race/ethnicity and sex. RESULTS: The average annual prevalence of smoking at any time during pregnancy decreased from 25.7% (95% confidence interval [CI], 15.3%-36.0%) in 1985 to 10.1% (95% CI, 7.1%-13.0%) in 2014 (P < .001), and quitting smoking at any time during the index pregnancy increased from 36.6% (95% CI, 20.3%-52.9%) in 1985 to 54.9% (95% CI, 44.4%-65.4%) in 2008 (P = .002). The adjusted annual risk of smoking during pregnancy decreased significantly by 3% (aOR = 0.97; 95% CI, 0.95-0.98; P < .001). The prevalence rate of smoking in the year 2020 extrapolated from the current trend would be 6.1%. CONCLUSIONS: Smoking during pregnancy in the United States is declining. However, renewed public health measures are needed to achieve the Healthy People 2020 objectives of preventing smoking among pregnant women in the United States.

Background While there is some evidence that maternal exposure to ambient air pollution is associated with orofacial clefts in offspring, the epidemiologic studies have been largely equivocal. We evaluated whether maternal exposure to elevated county-level ambient fine particulate matter with aerodynamic diameter ≤2.5 µm (PM2.5) and ozone during early gestation was associated with a higher prevalence of orofacial clefts. Methods Birth data consisting of 4.7 million births from 2001 to 2007 were obtained from National Birth Defects Prevention Network for four states — Arizona, Florida, New York (excluding New York City), and Texas. The air pollution exposure assessment for gestational weeks 5–10 was based on county-level average concentrations of PM2.5 and ozone data generated using a Bayesian fusion model available through CDC's Environmental Public Health Tracking Network. Two outcomes were analyzed separately: cleft lip with or without cleft palate, cleft palate alone. In logistic regression analyses, we adjusted for factors that were suspected confounders or modifiers of the association between the prevalence of orofacial clefts and air pollution, i.e., infant sex, race-ethnicity, maternal education, smoking status during pregnancy, whether this was mother's first baby, maternal age. Results Each 10 µg/m3 increase in PM2.5 concentration was significantly associated with cleft palate alone (OR =1.43, 95% CI: 1.11–1.86). There was no significant association between PM2.5 concentration and cleft lip with or without cleft palate. No associations were observed between ozone exposure and the two outcomes of orofacial clefts. Conclusions Our study suggests that PM2.5 significantly increased the risk of cleft palate alone, but did not change the incidence of cleft lip with or without palate. Ozone levels did not correlate with incidence of orofacial clefts.

In Florida prior to 2004, the birth certificate only allowed parents to identify themselves as 1 race. The birth certificate was subsequently revised in 2004, allowing parents to identify with more than 1 race. This inconsistency in data collection methods can greatly impact the results of race-specific time trend analyses. Race-bridging techniques have been developed to reassign multiple race responses to single race categories. This investigation aimed to compare race-specific birth defect rates calculated in 2 ways: (1) the current method: treating those selecting multiple race categories as though they selected Other race, and (2) the bridged method: attempting to classify those selecting multiple categories into the category they would have selected if they could only pick 1 race.Data from the Florida Office of Vital Statistics and the Florida Birth Defects Registry were used to examine rates of selected birth defects by race among births to non-Hispanic mothers from 2005 to 2014. Rates of selected birth defects were calculated and compared for the following race groups: white, black, American Indian/Alaska Native (AIAN), and Asian/Pacific Islander (API) using the following 6 bridging methods: (1) no bridging method, (2) largest group, whole allocation, (3) smallest group, whole allocation, (4) largest group other than white, (5) equal fractions, fractional allocation, and (6) reported fractions, fractional allocation.The differences in birth defect rates comparing the current method to the recalculated bridged-race population depends on the bridging method used. Using largest group, whole-allocation, the total population of white, black, and API races increased, whereas the total number of AIAN remained unaffected. Using the smallest group or largest group other than white, whole-allocation, the total population of black, API, and AIAN increased, resulting in decreased birth defect rates. Lastly, using equal fractions or reported fractions, fractional allocation we found an increase in the live birth count for each race and a corresponding decrease in birth defect rates.Race-bridging techniques may be useful when reviewing race-specific rates over time, or to account for the lack of comparability of race/ethnic classification in birth defect studies, particularly national studies combining data from different states. However, determining the best race-bridging technique warrants further investigation on larger populations and on other health outcomes.

Objective Public health surveillance programs worldwide implement a variety of case-finding strategies, and many rely at least in part on International Classification of Diseases (ICD)-based diagnostic codes in administrative and clinical databases. Over time, state- and national-level hospital discharge databases have been expanding the number of reported diagnosis code fields. This study aimed to evaluate the impact of these expansions on frequencies and rates of major birth defects, and the classification of birth defects as isolated vs multiple. Methods We used state-level 2006-2013 Florida Birth Defects Registry data and 2009-2012 data from a nationally representative database (Kids’ Inpatient Database). We generated data under different scenarios by varying the number of diagnosis code fields available, and comparing counts and rates of major birth defects generated under each scenario. Results The expansion from 10 to 31 diagnosis code fields improved ascertainment by preventing the loss of 1 in every 40 birth defect cases with defect-related diagnoses appearing only in code positions 11 to 31. Although there was variation by birth defect, the largest impact of the expansion tended to occur for less severe birth defects diagnosed in sicker infants. When restricting to fewer codes, not only were fewer cases diagnosed, but more were classified as being isolated due to the inability to capture co-occurring defects. Conclusion Our findings encourage additional research for other health outcomes in patients of all ages. Other disease registries rely at least in part on diagnostic codes documented by healthcare providers in their case-finding activities, irrespective of ascertainment protocols, making routine investigation of these databases essential.

Background Meta‐analyses of observational studies have shown that women with a shorter interpregnancy interval (the time from delivery to start of a subsequent pregnancy) are more likely to experience adverse pregnancy outcomes, such as preterm delivery or small for gestational age birth, than women who space their births further apart. However, the studies used to inform these estimates have methodological shortcomings. Methods In this commentary, we summarise the discussions of an expert workgroup describing good practices for the design, analysis, and interpretation of observational studies of interpregnancy interval and adverse perinatal health outcomes. Results We argue that inferences drawn from research in this field will be improved by careful attention to elements such as: (a) refining the research question to clarify whether the goal is to estimate a causal effect vs describe patterns of association; (b) using directed acyclic graphs to represent potential causal networks and guide the analytic plan of studies seeking to estimate causal effects; (c) assessing how miscarriages and pregnancy terminations may have influenced interpregnancy interval classifications; (d) specifying how key factors such as previous pregnancy loss, pregnancy intention, and maternal socio‐economic position will be considered; and (e) examining if the association between interpregnancy interval and perinatal outcome differs by factors such as maternal age. Conclusion This commentary outlines the discussions of this recent expert workgroup, and describes several suggested principles for study design and analysis that could mitigate many potential sources of bias.

We assessed survival, hospital length of stay (LOS), and costs of medical care for infants with lethal congenital malformations, and also examined the relationship between medical and surgical therapies and survival. Retrospective cohort study including infants born 1998–2009 with lethal congenital malformations, identified using a longitudinally linked maternal/infant database. The cohort included 786 infants: trisomy 18 (T18, n = 350), trisomy 13 (T13, n = 206), anencephaly (n = 125), bilateral renal agenesis (n = 53), thanatophoric dysplasia/achondrogenesis/lethal osteogenesis imperfecta (n = 38), and infants > 1 of the birth defects (n = 14). Compared to infants without birth defects, infants with T18, T13, bilateral renal agenesis, and skeletal dysplasias had longer survival rates, higher inpatient medical costs, and longer LOS. Care practices and survival have changed over time for infants with T18, T13, bilateral renal agenesis, and skeletal dysplasias. This information will be useful for clinicians in counseling families and in shaping goals of care prenatally and postnatally.

Background Higher prevalence of selected birth defects has been reported among American Indian/Alaska Native (AI/AN) newborns. We examine whether known risk factors for birth defects explain the higher prevalence observed for selected birth defects among this population. Methods Data from 12 population-based birth defects surveillance systems, covering a birth population of 11 million from 1999 to 2007, were used to examine prevalence of birth defects that have previously been reported to have elevated prevalence among AI/ANs. Prevalence ratios (PRs) were calculated for non-Hispanic AI/ANs and any AI/ANs (regardless of Hispanic ethnicity), adjusting for maternal age, education, diabetes, and smoking, as well as type of case-finding ascertainment surveillance system. Results After adjustment, the birth prevalence of two of seven birth defects remained significantly elevated among AI/ANs compared to non-Hispanic whites (NHWs): anotia/microtia was almost threefold higher, and cleft lip +/- cleft palate was almost 70% higher compared to NHWs. Excluding AI/AN subjects who were also Hispanic had only a negligible impact on adjusted PRs. Conclusions Additional covariates accounted for some of the elevated birth defect prevalences among AI/ANs compared to NHWs. Exclusion of Hispanic ethnicity from the AI/AN category had little impact on birth defects prevalences in AI/ANs. NHWs serve as a viable comparison group for analysis. Birth defects among AI/ANs require additional scrutiny to identify modifiable risk and protective factors.

Objectives: We identified algorithms to improve the accuracy of passive surveillance programs for birth defects that rely on administrative diagnosis codes for case ascertainment and in situations where case confirmation via medical record review is not possible or is resource prohibitive. Methods: We linked data from the 2009-2011 Florida Birth Defects Registry, a statewide, multisource, passive surveillance program, to an enhanced surveillance database with selected cases confirmed through medical record review. For each of 13 birth defects, we calculated the positive predictive value (PPV) to compare the accuracy of 4 algorithms that varied case definitions based on the number of diagnoses, medical encounters, and data sources in which the birth defect was identified. We also assessed the degree to which accuracy-improving algorithms would affect the Florida Birth Defects Registry’s completeness of ascertainment. Results: The PPV generated by using the original Florida Birth Defects Registry case definition (ie, suspected cases confirmed by medical record review) was 94.2%. More restrictive case definition algorithms increased the PPV to between 97.5% (identified by 1 or more codes/encounters in 1 data source) and 99.2% (identified in >1 data source). Although PPVs varied by birth defect, alternative algorithms increased accuracy for all birth defects; however, alternative algorithms also resulted in failing to ascertain 58.3% to 81.9% of cases. Conclusions: We found that surveillance programs that rely on unverified diagnosis codes can use algorithms to dramatically increase the accuracy of case finding, without having to review medical records. This can be important for etiologic studies. However, the use of increasingly restrictive case definition algorithms led to a decrease in completeness and the disproportionate exclusion of less severe cases, which could limit the widespread use of these approaches.

This study investigates risk of specific structural birth defects associated with ondansetron exposure during the first trimester in a large US commercially-insured population. Medical claims data were obtained from Truven Health Analytics for 864,083 mother-infant pairs from 2000 to 2014. Logistic regression was used to measure the association between first trimester exposure to ondansetron and risk of cardiac defects, orofacial clefts and other specific structural defects in offspring. First trimester exposure to ondansetron was associated with increased risk of cardiac (OR: 1.52 95% CI: 1.35-1.70) and orofacial cleft defects (OR: 1.32 95% CI: 0.76-2.28) in offspring compared to women with no antiemetic exposure during pregnancy. This analysis addresses limitations of prior studies including limited power, exposure misclassification, and generalizability to the US population. In a large, US population we found a statistically significant association between early pregnancy ondansetron exposure and specific structural birth defects in offspring.

One of the main goals in spatial epidemiology is to study the geographical pattern of disease risks. For such purpose, the convolution model composed of correlated and uncorrelated components is often used. However, one of the two components could be predominant in some regions. To investigate the predominance of the correlated or uncorrelated component for multiple scale data, we propose four different spatial mixture multiscale models by mixing spatially varying probability weights of correlated (CH) and uncorrelated heterogeneities (UH). The first model assumes that there is no linkage between the different scales and, hence, we consider independent mixture convolution models at each scale. The second model introduces linkage between finer and coarser scales via a shared uncorrelated component of the mixture convolution model. The third model is similar to the second model but the linkage between the scales is introduced through the correlated component. Finally, the fourth model accommodates for a scale effect by sharing both CH and UH simultaneously. We applied these models to real and simulated data, and found that the fourth model is the best model followed by the second model.

To describe the spatial distribution of diseases, a number of methods have been proposed to model relative risks within areas. Most models use Bayesian hierarchical methods, in which one models both spatially structured and unstructured extra-Poisson variance present in the data. For modelling a single disease, the conditional autoregressive (CAR) convolution model has been very popular. More recently, a combined model was proposed that 'combines' ideas from the CAR convolution model and the well-known Poisson-gamma model. The combined model was shown to be a good alternative to the CAR convolution model when there was a large amount of uncorrelated extra-variance in the data. Less solutions exist for modelling two diseases simultaneously or modelling a disease in two sub-populations simultaneously. Furthermore, existing models are typically based on the CAR convolution model. In this paper, a bivariate version of the combined model is proposed in which the unstructured heterogeneity term is split up into terms that are shared and terms that are specific to the disease or subpopulation, while spatial dependency is introduced via a univariate or multivariate Markov random field. The proposed method is illustrated by analysis of disease data in Georgia (USA) and Limburg (Belgium) and in a simulation study. We conclude that the bivariate combined model constitutes an interesting model when two diseases are possibly correlated. As the choice of the preferred model differs between data sets, we suggest to use the new and existing modelling approaches together and to choose the best model via goodness-of-fit statistics. Copyright © 2016 John Wiley & Sons, Ltd.

Background Research has shown an association between assisted reproductive technology (ART) and adverse birth outcomes. We identified whether birth outcomes of ART-conceived pregnancies vary across states with different maternal characteristics, insurance coverage for ART services, and type of ART services provided. Methods CDC's National ART Surveillance System data were linked to Massachusetts, Florida, and Michigan vital records from 2000 through 2006. Maternal characteristics in ART- and non-ART-conceived live births were compared between states using chi-square tests. We performed multivariable logistic regression analyses and calculated adjusted odds ratios (aOR) to assess associations between ART use and singleton preterm delivery (

Purpose Many types of cancer have an underlying spatial incidence distribution. Spatial model selection methods can be useful when determining the linear predictor that best describes incidence outcomes. Methods In this article, we examine the applications and benefits of using two different types of spatial model selection techniques, Bayesian model selection and Bayesian model averaging, in relation to colon cancer incidence in the state of Georgia, United States. Results Both methods produce useful results that lead to the determination that median household income and percent African American population are important predictors of colon cancer incidence in the Northern counties of the state, whereas percent persons below poverty level and percent African American population are important in the Southern counties. Conclusions Of the two presented methods, Bayesian model selection appears to provide more succinct results, but applying the two in combination offers even more useful information into the spatial preferences of the alternative linear predictors.

Major structural birth defects collectively affect 3 to 5% of births in the United States and contribute substantially to mortality and morbidity (CDC, 2008; TDSHS, 2015). Since 2000, the National Birth Defects Prevention Network (NBDPN) has annually published state-specific data for selected major birth defects affecting a range of organ systems, including central nervous, eye, ear, cardiovascular, orofacial, gastrointestinal, genitourinary, and musculoskeletal, as well as chromosomal and other conditions, such as amniotic bands. While the NBPDN list of birth defects had remained relatively unchanged for two decades, it was recently revised and released with the 2014 NBDPN Annual Report (Mai et al., 2014). Several factors necessitated an in-depth examination of the list of conditions: (1) development of national data quality standards for birth defects surveillance in the United States; (2) transition of the diagnostic coding system from the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) to ICD-10-CM; and (3) inclusion of newborn screening for critical congenital heart defects (CCHD), with 12 primary and secondary CCHD targets, on the national Recommended Uniform Screening Panel. The revision process included a review of each condition in relation to its public health importance, state of current knowledge, and clinical factors, such as accuracy of diagnosis within a child’s first year of life. Table 1 presents the revised list of birth defects and their diagnostic codes [ICD-9-CM and Centers for Disease Control and Prevention/British Pediatric Association Classification of Diseases (CDC/BPA)]. TABLE 1 National Birth Defects Prevention Network (NBDPN) List of Reported Birth Defects by Disease Classification Codes

Objective. We assessed the practices of U.S. population-based birth defects surveillance programs in addressing current and emergent public health needs. Methods. Using the CDC Strategic Framework considerations for public health surveillance (i.e., lexicon and standards, legal authority, technological advances, workforce, and analytic capacity), during 2012 and 2013, we conducted a survey of all U.S. operational birth defects programs ( n=43) soliciting information on legal authorities, case definition and clinical information collected, types of data sources, and workforce staffing. In addition, we conducted semi-structured interviews with nine program directors to further understand how programs are addressing current and emergent needs. Results. Three-quarters of birth defects surveillance programs used national guidelines for case definition. Most birth defects surveillance programs (86%) had a legislative mandate to conduct surveillance, and many relied on a range of prenatal, postnatal, public health, and pediatric data sources for case ascertainment. Programs reported that the transition from paper to electronic formats was altering the information collected, offering an opportunity for remote access to improve timeliness for case review and verification. Programs also reported the growth of pooled, multistate data collaborations as a positive development. Needs identified included ongoing workforce development to improve information technology and analytic skills, more emphasis on data utility and birth defects-specific standards for health information exchange, and support to develop channels for sharing ideas on data interpretation and dissemination. Conclusion. The CDC Strategic Framework provided a useful tool to determine the birth defects surveillance areas with positive developments, such as multistate collaborative epidemiologic studies, and areas for improvement, such as preparation for health information exchanges and workforce database and analytic skills. Our findings may inform strategic deliberations for enhancing the effectiveness of birth defects surveillance programs.

Using geographic information systems (GIS), we examined travel time and distance to access hospital care for infants with spina bifida (SB).This study was a statewide, population-based analysis of Florida-born children with SB, 1998-2007, identified by the Florida Birth Defects Registry and linked to hospitalizations. We geocoded maternal residence at delivery and identified hospital locations for infants (1 year). Using 2007 Florida Department of Transportation road data, we calculated one-way mean travel time and distance to access hospital care. We used Poisson regression to examine selected factors associated with travel time and distance [≤30 vs.30 min/miles (reference)], including presence of hydrocephalus and SB type [isolated (no other major birth defect) versus non-isolated SB].For 612 infants, one-way mean (median) travel time was 45.1 (25.9) min. Infants with both non-isolated SB and hydrocephalus traveled longest to access hospitals (mean 60.8 min/48.5 miles; median 34.2 min/26.9 miles). In adjusted results, infants with non-isolated SB and whose mothers had a rural residence were less likely to travel ≤30 min to hospitals. Infants born to mothers in minority racial/ethnic groups were more likely to travel ≤30 min.Birth defects registry data and GIS-based methods can be used to evaluate geographic accessibility to hospital care for infants with birth defects. Results can help to identify geographic barriers to accessing hospital care, such as travel time and distance, and inform opportunities to improve access to care for infants with SB or other special needs.

This study sought to address underenrollment and late entry to early intervention by identifying factors associated with parental concern and services for developmental delays. The authors analyzed responses from 27,566 parents of children from birth to age 5 from the 2007 National Survey of Children’s Health to quantify and to identify factors associated with developmental concerns and enrollment in public intervention or therapy. Developmental concerns were common among parents from all backgrounds, increasing as children approach preschool age and particularly among children with poor health and those with non-English home language. However, enrollment in intervention is low. Nearly 40% of parents reported one or more concerns, yet 5% of children were enrolled in public intervention or therapy. Multirace or Black race, non-English home language, low income, and private or no insurance were associated with lower odds of services enrollment. Primary health care provider and parent involvement were associated with higher likelihood of parent-reported concern and services.

Information is increasingly digital, creating opportunities to respond to pressing issues about human populations in near real time using linked datasets that are large, complex, and diverse. The potential social and individual benefits that can come from data-intensive science are large, but raise challenges of balancing individual privacy and the public good, building appropriate socio-technical systems to support data-intensive science, and determining whether defining a new field of inquiry might help move those collective interests and activities forward. A combination of expert engagement, literature review, and iterative conversations led to our conclusion that defining the field of Population Data Science (challenge 3) will help address the other two challenges as well. We define Population Data Science succinctly as the science of data about people and note that it is related to but distinct from the fields of data science and informatics. A broader definition names four characteristics of: data use for positive impact on citizens and society; bringing together and analyzing data from multiple sources; finding population-level insights; and developing safe, privacy-sensitive and ethical infrastructure to support research. One implication of these characteristics is that few people possess all of the requisite knowledge and skills of Population Data Science, so this is by nature a multi-disciplinary field. Other implications include the need to advance various aspects of science, such as data linkage technology, various forms of analytics, and methods of public engagement. These implications are the beginnings of a research agenda for Population Data Science, which if approached as a collective field, can catalyze significant advances in our understanding of trends in society, health, and human behavior.

To identify the live-birth prevalence, trends, correlates, and neonatal and 1-year survival rates of congenital diaphragmatic hernia.Using a population-based, retrospective cohort study design, we examined 1,025 cases of congenital diaphragmatic hernia from the 1998-2012 Florida Birth Defects Registry. We used Poisson and joinpoint regression models to compute prevalence ratios and temporal trends, respectively. Kaplan-Meier survival curves and Cox proportional hazards regression were used to describe neonatal and 1-year survival and estimate hazard ratios representing the predictors of infant survival.The birth prevalence of congenital diaphragmatic hernia was 3.19 per 10,000 live births (95% confidence interval [CI]: 3.00-3.39); there was a 4.2% yearly increase among multiple cases only. Among all cases, maternal education less than high school (prevalence ratio: 1.25, 95% CI: 1.02-1.53), high school/associate degree/GED (prevalence ratio: 1.15, 95% CI: 1.01-1.32), multiple birth (prevalence ratio: 1.38, 95% CI: 1.05-1.81), and male sex (prevalence ratio: 1.18, 95% CI: 1.05-1.32) were associated with increased risk for congenital diaphragmatic hernia. The 24-hr, neonatal, and 1-year survival rates were 93.6%, 79.8%, and 71.2%, respectively. The highest hazard ratio of 17.87 (95% CI: 1.49-213.82) was observed for neonatal mortality among cases associated with chromosomal anomalies and born37 weeks at 1,500 g. Among isolated cases, multiple birth (hazard ratio: 0.41, 95% CI: 0.20-0.86) was associated with decreased 1-year mortality.Low maternal education and multiple birth may be linked to congenital diaphragmatic hernia. The trends in prevalence, epidemiologic correlates, and predictors of early survival can differ between congenital diaphragmatic hernia subtypes-isolated, multiple, and chromosomal.© 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.