Dataset Information

US county-level prevalence and spatial distribution of optimal birth outcomes 2018-2019.

ABSTRACT: A shift in focus towards healthy reproductive outcomes may reveal opportunities for novel interventions and strategies to promote optimal health. Using variables from the National Center for Health Statistics restricted use natality files, we calculated Empirical Bayes smoothed (EBS) rates of optimal birth for the all live births-both overall and by maternal race/ethnicity-by applying the smoothing tool in GeoDa version 1.18.0.10 We defined counties achieving greater racial birth equity as those where the overall EBS optimal birth rate was greater than the national 75th percentile and the absolute difference between maternal racial/ethnic categories was smaller than the national 25th percentile difference. During the study period, 49.80% of overall births could be classified as an optimal birth according to the study definition. Of the 3140 US counties, only 282 (8.98%) appeared to advance White-Black equity in optimal births, and 205 (6.53%) appeared to advance White-Hispanic equity in optimal births. In the effort improve maternal health, we should focus not only on the absence of negative outcomes, but also the occurrence of positive outcomes. Our analytic results suggest that optimal births can be measured and that geographic inequities by race occur.

SUBMITTER: Dyer L

PROVIDER: S-EPMC9529881 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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US county-level prevalence and spatial distribution of optimal birth outcomes 2018-2019.

Dyer Lauren L Bell Caryn C Perez Susan S Crear-Perry Joia J Theall Katherine K Wallace Maeve M

Scientific reports 20221003 1

A shift in focus towards healthy reproductive outcomes may reveal opportunities for novel interventions and strategies to promote optimal health. Using variables from the National Center for Health Statistics restricted use natality files, we calculated Empirical Bayes smoothed (EBS) rates of optimal birth for the all live births-both overall and by maternal race/ethnicity-by applying the smoothing tool in GeoDa version 1.18.0.10 We defined counties achieving greater racial birth equity as those ...[more]

PMID: 36192415

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Project description:ImportancePreterm birth is a leading cause of preventable neonatal morbidity and mortality. Preterm birth rates at the national level may mask important geographic variation in rates and trends at the county level.ObjectiveTo estimate age-standardized preterm birth rates by US county from 2007 to 2019.Design, setting, and participantsThis serial cross-sectional study used data from the National Center for Health Statistics composed of all live births in the US between 2007 and 2019. Data analyses were performed between March 22, 2022, and September 29, 2022.Main outcomes and measuresAge-standardized preterm birth (<37 weeks' gestation) and secondarily early preterm birth (<34 weeks' gestation) rates by county and year calculated with a validated small area estimation model (hierarchical bayesian spatiotemporal model) and percent change in preterm birth rates using log-linear regression models.ResultsBetween 2007 and 2019, there were 51 044 482 live births in 2383 counties. In 2007, the national age-standardized preterm birth rate was 12.6 (95% CI, 12.6-12.7) per 100 live births. Preterm birth rates varied significantly among counties, with an absolute difference between the 90th and 10th percentile counties of 6.4 (95% CI, 6.2-6.7). The gap between the highest and lowest counties for preterm births was 20.7 per 100 live births in 2007. Several counties in the Southeast consistently had the highest preterm birth rates compared with counties in California and New England, which had the lowest preterm birth rates. Although there was no statistically significant change in preterm birth rates between 2007 and 2019 at the national level (percent change, -5.0%; 95% CI, -10.7% to 0.9%), increases occurred in 15.4% (95% CI, 14.1%-16.9%) of counties. The absolute and relative geographic inequalities were similar across all maternal age groups. Higher quartile of the Social Vulnerability Index was associated with higher preterm birth rates (quartile 4 vs quartile 1 risk ratio, 1.34; 95% CI, 1.31-1.36), which persisted across the study period. Similar patterns were observed for early preterm birth rates.Conclusions and relevanceIn this serial cross-sectional study of county-level preterm and early preterm birth rates, substantial geographic disparities were observed, which were associated with place-based social disadvantage. Stability in aggregated rates of preterm birth at the national level masked increases in nearly 1 in 6 counties between 2007 and 2019.

Project description:ImportanceAppreciation for the effects of neighborhood conditions and community factors on perinatal health is increasing. However, community-level indices specific to maternal health and associations with preterm birth (PTB) have not been assessed.ObjectiveTo examine the association of the Maternal Vulnerability Index (MVI), a novel county-level index designed to quantify maternal vulnerability to adverse health outcomes, with PTB.Design, setting, and participantsThis retrospective cohort study used US Vital Statistics data from January 1 to December 31, 2018. Participants included 3 659 099 singleton births at 22 plus 0/7 to 44 plus 6/7 weeks of gestation born in the US. Analyses were conducted from December 1, 2021, through March 31, 2023.ExposureThe MVI, a composite measure of 43 area-level indicators, categorized into 6 themes reflecting physical, social, and health care landscapes. Overall MVI and theme were stratified by quintile (very low to very high) by maternal county of residence.Main outcomes and measuresThe primary outcome was PTB (gestational age <37 weeks). Secondary outcomes were PTB categories: extreme (gestational age ≤28 weeks), very (gestational age 29-31 weeks), moderate (gestational age 32-33 weeks), and late (gestational age 34-36 weeks). Multivariable logistic regression quantified associations of MVI, overall and by theme, with PTB, overall and by PTB category.ResultsAmong 3 659 099 births, 298 847 (8.2%) were preterm (male, 51.1%; female, 48.9%). Maternal race and ethnicity included 0.8% American Indian or Alaska Native, 6.8% Asian or Pacific Islander, 23.6% Hispanic, 14.5% non-Hispanic Black, 52.1% non-Hispanic White, and 2.2% with more than 1 race. Compared with full-term births, MVI was higher for PTBs across all themes. Very high MVI was associated with increased PTB in unadjusted (odds ratio [OR], 1.50 [95% CI, 1.45-1.56]) and adjusted (OR, 1.07 [95% CI, 1.01-1.13]) analyses. In adjusted analyses of PTB categories, MVI had the largest association with extreme PTB (adjusted OR, 1.18 [95% CI, 1.07-1.29]). Higher MVI in the themes of physical health, mental health and substance abuse, and general health care remained associated with PTB overall in adjusted models. While the physical health and socioeconomic determinant themes were associated with extreme PTB, physical health, mental health and substance abuse, and general health care themes were associated with late PTB.Conclusions and relevanceThe findings of this cohort study suggest that MVI was associated with PTB even after adjustment for individual-level confounders. The MVI is a useful measure for county-level PTB risk that may have policy implications for counties working to lower preterm rates and improve perinatal outcomes.

Project description:BackgroundAdverse pregnancy outcomes jointly account for a high proportion of mortality and morbidity among pregnant women and their infants. Furthermore, the burden attributed to adverse pregnancy outcomes remains high and inadequately characterised due to the intricate interplay of its etiology and shared set of important risk factors. This study sought to quantify and map the underlying risk of multiple adverse pregnancy outcomes in Kenya at sub-county level using a shared component space-time modelling framework.MethodsReported sub-county level adverse pregnancy outcomes count from January 2016 - December 2019 were obtained from the Kenyan District Health Information System. A Bayesian hierarchical spatio-temporal model was used to estimate the joint burden of adverse pregnancy outcomes in space (sub-county) and time (year). To improve the precision of our estimates over time and space, information across the outcomes were combined via the shared and the outcome-specific components using a shared component model with spatio-temporal interactions.ResultsOverall, the total number of adverse outcomes in pregnancy increased by 14.2% (95% UI: 14.0-14.5) from 88,816 cases in 2016 to 101,455 cases in 2019. Between 2016 and 2019, the estimated low birth weight rate and the pre-term birth rate were 4.5 (95% UI: 4.4-4.7) and 2.3 (95% UI: 2.2-2.5) per 100 live births. The stillbirth and neonatal death rates were estimated to be 18.7 (95% UI: 18.0-19.4) and 6.9 (95% UI: 6.4-7.4) per 1000 live births. The magnitude of the spatio-temporal variation attributed to shared risk was high for pre-term births, low birth weight, neonatal deaths, stillbirths and neonatal deaths, respectively. The shared risk patterns were dominant in sub-counties located along the Indian ocean coastline, central and western Kenya.ConclusionsThis study demonstrates the usefulness of a Bayesian joint spatio-temporal shared component model in exploiting specific and shared risk of adverse pregnancy outcomes sub-nationally. By identifying sub-counties with elevated risks and data gaps, our estimates not only assert the need for bolstering maternal health programs in the identified high-risk sub-counties but also provides a baseline against which to assess the progress towards the attainment of Sustainable Development Goals.

Dataset Information

US county-level prevalence and spatial distribution of optimal birth outcomes 2018-2019.

Publications

US county-level prevalence and spatial distribution of optimal birth outcomes 2018-2019.

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