Poverty, urban-rural classification and term infant mortality: a population-based multilevel analysis

Safe sleep crib clinics: Promoting risk reduction strategies for sudden unexpected infant death

Objectives

Safe Sleep Community Baby Showers (CBS) provide group education to reduce risk factors of sudden unexpected infant death (SUID). Based on CBS success, Safe Sleep Crib Clinics were developed to provide individual education. This study assessed Crib Clinic outcomes and differences in Crib Clinics compared to CBSs.

Methods

Certified Safe Sleep Instructors facilitated CBSs and/or Crib Clinics in their communities and collected participant data related to safe sleep, tobacco avoidance and breastfeeding. Crib Clinic data was compared pre- to post-test; post-test results were compared between Crib Clinics and CBSs.

Results

Crib Clinic attendees exhibited significant increases in intention to have infant follow safe sleep recommendations, avoid secondhand smoke and breastfeed (all p < 0.001). Significant differences between Crib Clinic and CBS participants related to marital status, language, tobacco, education and insurance (all p < 0.01). CBS and Crib Clinic participants differed on items related to sleep environment, breastfeeding and tobacco (all p = 0.05).

Conclusions

Overall Crib Clinics appear to be effective in increasing knowledge, intentions and confidence related to safe sleep, tobacco avoidance and breastfeeding. Crib Clinics may offer flexibility (e.g., time, format) that increases accessibility to safe sleep education for families.

Innovation

Results suggest the ability to shift education delivery method based on group size was important in both rural and urban settings.

Preventing Infant Mortality Through Medicaid-Administered Prenatal Care Coordination: Evidence From Wisconsin

OBJECTIVE

To estimate associations between Wisconsin Medicaid's Prenatal Care Coordination (PNCC) program and infant mortality.

DATA SOURCES AND STUDY SETTING

We analyzed birth records, Medicaid claims, and infant death records for all resident and in-state Medicaid-paid live deliveries during 2010-2018.

STUDY DESIGN

We measured PNCC exposure during pregnancy dichotomously (none; any) and categorically (none; assessment/care plan only; service receipt). Our outcome was infant mortality (death at age < 365 days). Adjusted binary logit regressions and propensity score weighted regressions tested associations between PNCC receipt and infant mortality, and we estimated probabilities and average marginal effects of infant mortality. We also executed regressions with interactions on maternal race/ethnicity to determine if associations varied across Black non-Hispanic (NH), Hispanic, and White NH births.

DATA COLLECTION/EXTRACTION METHODS

Our sample consisted of 231,540 Medicaid-paid births during 2010-2018. PNCC is only available to pregnant Medicaid beneficiaries.

PRINCIPAL FINDINGS

Infant mortality was lower among PNCC assessment/care plan only births (5.0 deaths/1000 births) and PNCC service receipt births (6.1 deaths/1000 births) relative to non-PNCC births (6.8 deaths/1000 births). This pattern was consistent in Black NH and Hispanic subgroups, but infant mortality did not vary by PNCC among White NH deliveries. Overall, adjusted binary logit regressions indicated that the probabilities of infant mortality were 0.70% for no PNCC and 0.53% for any PNCC, yielding an average marginal effect of -0.17 percentage points (95% confidence interval -0.22 percentage points, -0.11 percentage points). This association did not vary by PNCC exposure level. PNCC-infant mortality associations were significantly stronger for Black NH births relative to White NH births. Results were consistent in propensity score weighted regressions.

CONCLUSIONS

PNCC during pregnancy is associated with a lower probability of infant mortality, particularly in Black NH families. The benefit of PNCC on infant mortality may not depend on receiving services beyond care planning.

An explanation of the stagnant under-5 mortality rate in Bangladesh using multilevel, multivariable analysis of three Demographic and Health Surveys

Despite remarkable success in the Millennium Development Goal era, Bangladesh experienced a sluggish reduction in the under-5 mortality rate (U5MR) between 2014 and 2017-18. Our study aimed to explain this stagnancy by examining the variation in the key predictor-specific mortality risks over time, using the Bangladesh Demographic and Health Survey 2011, 2014 and 2017-18 data. We applied multilevel mixed effects logistic regression to examine the extent to which the under-5 mortality (U5M) risks were associated with the key sociodemographic and health service-specific predictors. We found that the rise in mortality risks attributable to maternal age 18 years or below, low maternal education, mother's overweight or obesity and the absence of a handwashing station within the household were the key contributors to the stagnant U5MR between 2014 and 2017-18. Poverty and low education aggravated the mortality risks. Besides, antenatal care (ANC) and postnatal care (PNC) did not impact U5M risks as significantly as expected. Compulsory use of ANC and PNC cards and strict monitoring of their use may improve the quality of these health services. Leveraging committees like the Upazila Hospital Management Committee can bring harmony to implementing policies and programmes in the sectors related to U5M.

The risk factors of infant mortality in Somalia: evidence from the 2018/2019 Somali health & demographic survey

BACKGROUND

Globally, infant mortality is one of the major public health threats, especially in low-income countries. The infant mortality rate of Somalia stands at 73 deaths per 1000 live births, which is one of the highest infant death rates in the region as well as in the world. Therefore, the aim of this study was to ascertain the risk factors of infant mortality in Somalia using national representative data.

METHOD

In this study, data from the Somali Health and Demographic Survey (SHDS), conducted for the first time in Somalia in 2018/2019 and released in 2020, were utilized. The analysis of the data involved employing the Chi-square test as a bivariate analysis. Furthermore, a multivariate Cox proportional hazard model was applied to accommodate potential confounders that act as risk factors for infant death.

RESULTS

The study found that infant mortality was highest among male babies, multiple births, and those babies who live in rural areas, respectively, as compared to their counterparts. Those mothers who delivered babies with small birth size and belonged to a poor wealth index experienced higher infant mortality than those mothers who delivered babies with average size and belonged to a middle or rich wealth index. Survival analysis indicated that mothers who did use ANC services (HR = 0.740; 95% CI = 0.618-0.832), sex of the baby (HR = 0.661; 95% CI = 0.484-0.965), duration of pregnancy (HR = 0.770; 95% CI = 0.469-0.944), multiple births (HR = 1.369; 1.142-1.910) and place of residence (HR = 1.650; 95% CI = 1.451-2.150) were found to be statistically significantly related to infant death.

CONCLUSION

The study investigated the risk factors associated with infant mortality by analyzing data from the first Somali Health and Demographic Survey (SHDS), which included a representative sample of the country's population. Place of residence, gestational duration, infant's gender, antenatal care visits, and multiple births were identified as determinants of infant mortality. Given that infant mortality poses a significant public health concern, particularly in crisis-affected countries like Somalia, intervention programs should prioritize the provision of antenatal care services, particularly for first-time mothers. Moreover, these programs should place greater emphasis on educating women about the importance of receiving antenatal care and family planning services, in order to enhance their awareness of these vital health services and their positive impact on infant survival rates.

A greater nurse and midwife density protects against infant mortality globally

PURPOSE

As the largest profession within the health care workforce, nurses and midwives play a critical role in the health and wellness of families especially children and infants. This study suggests those countries with higher nurse and midwife densities (NMD) had lower infant mortality rates (IMR).

DESIGN AND METHODS

With affluence, low birthweight and urbanization incorporated as potential confounders, this ecological study analyzed the correlations between NMD and IMR with scatterplots, Pearson r correlation, partial correlation and multiple linear regression models. Countries were also grouped for analysing and comparing their Pearson's coefficients.

RESULTS

NMD inversely and significantly correlated to IMR worldwide. This relationship remained significant independent of the confounders, economic affluence, low birthweight and urbanization. Explaining 57.19% of IMR variance, high NMD was implicated in significantly reducing the IMR.

PRACTICE IMPLICATIONS

Countries with high NMD had lower IMRs both worldwide and with special regard to developing countries. This may interest healthcare policymakers, especially those from developing countries, to consider the impacts of global nursing and midwifery staffing shortages. Nurses and midwives are the group of healthcare professionals who spend most with infants and their carers. This may be another alert for the health authorities to extend nurses and midwives' practice scope for promoting infant health.

Early neonatal mortality and determinants in sub-Saharan Africa: Findings from recent demographic and health survey data

INTRODUCTION

Neonatal mortality during the first week of life is a global issue that is responsible for a large portion of deaths among children under the age of five. There are, however, very few reports about the issue in sub-Saharan Africa. For the sake of developing appropriate policies and initiatives that could aid in addressing the issue, it is important to study the prevalence of mortality during the early neonatal period and associated factors. Thus, the aim of this study was to ascertain the prevalence of and pinpoint the contributing factors to early neonatal mortality in sub-Saharan Africa.

METHOD

Data from recent demographic and health surveys in sub-Saharan African countries was used for this study. The study included 262,763 live births in total. The determinants of early newborn mortality were identified using a multilevel mixed-effects logistic regression model. To determine the strength and significance of the association between outcome and explanatory variables, the adjusted odds ratio (AOR) at a 95% confidence interval (CI) was computed. Independent variables were deemed statistically significant when the p-value was less than the significance level (0.05).

RESULT

Early neonatal mortality in sub-Saharan Africa was 22.94 deaths per 1,000 live births. It was found to be significantly associated with maternal age over 35 years (AOR = 1.77, 95% CI: 1.34-2.33), low birth weight (AOR = 3.27, 95% CI: 2.16, 4.94), less than four ANC visits (AOR = 1.12, 95% CI: 1.01, 1.33), delivery with caesarean section (AOR = 1.81, 95% CI: 1.30-2.5), not having any complications during pregnancy (AOR = 0.76, 95% CI: 0.61, 94), and community poverty (AOR = 1.32, 95% CI: 1.05-1.65).

CONCLUSION

This study found that about twenty-three neonates out of one thousand live births died within the first week of life in sub-Saharan Africa. The age of mothers, birth weight, antenatal care service utilization, mode of delivery, multiple pregnancy, complications during pregnancy, and community poverty should be considered while designing policies and strategies targeting early neonatal mortality in sub-Saharan Africa.

Social Determinants of Premature Birth

Social determinants of health have received increasing attention in public health, leading to increased understanding of how social factors-individual and contextual-shape the health of the mother and infant. However, racial differences in birth outcomes persist, with incomplete explanation for the widening disparity. Here, we highlight the social determinants of preterm birth, with special attention to the social experiences among African American women, which are likely attributed to structural racism and discrimination throughout life.

An Application of Social Vulnerability Index to Infant Mortality Rates in Ohio Using Geospatial Analysis- A Cross-Sectional Study

BACKGROUND

Ohio ranks 43rd in the nation in infant mortality rates (IMR); with IMR among non-Hispanic black infants is three times higher than white infants.

OBJECTIVE

To identify the social factors determining the vulnerability of Ohio counties to IMR and visualize the spatial association between relative social vulnerability and IMR at county and census tract levels.

METHODS

The social vulnerability index (SVICDC) is a measure of the relative social vulnerability of a geographic unit. Five out of 15 social variables in the SVICDC were utilized to create a customized index for IMR (SVIIMR) in Ohio. The bivariate descriptive maps and spatial lag model were applied to visualize the quantitative relationship between SVIIMR and IMR, accounting for the spatial autocorrelation in the data.

RESULTS

Southeastern counties in Ohio displayed highest IMRs and highest overall SVIIMR; specifically, highest vulnerability to poverty, no high school diploma, and mobile housing. In contrast, extreme northwestern counties exhibited high IMRs but lower overall SVIIMR. Spatial regression showed five clusters where vulnerability to low per capita income in one county significantly impacted IMR (p = 0.001) in the neighboring counties within each cluster. At the census tract-level within Lucas county, the Toledo city area (compared to the remaining county) had higher overlap between high IMR and SVIIMR.

CONCLUSION

The application of SVI using geospatial techniques could identify priority areas, where social factors are increasing the vulnerability to infant mortality rates, for potential interventions that could reduce disparities through strategic and equitable policies.

Maternal opioid use disorder and infant mortality in Wisconsin, United States, 2010-2018

OBJECTIVE

The difference in infant health outcomes by maternal opioid use disorder (OUD) status is understudied. We measured the association between maternal OUD during pregnancy and infant mortality and investigated whether this association differs by infant neonatal opioid withdrawal syndrome (NOWS) or maternal receipt of medication for OUD (MOUD) during pregnancy.

METHODS

We sampled 204,543 Medicaid-paid births from Wisconsin, United States (2010-2018). The primary exposure was any maternal OUD during pregnancy. We also stratified this exposure on NOWS diagnosis (no OUD; OUD without NOWS; OUD with NOWS) and on maternal MOUD receipt (no OUD; OUD without MOUD; OUD with <90 consecutive days of MOUD; OUD with 90+ consecutive days of MOUD). Our outcome was infant mortality (death at age <365 days). Demographic-adjusted logistic regressions measured associations with odds ratios (OR) and 95% confidence intervals (CI).

RESULTS

Maternal OUD was associated with increased odds of infant mortality (OR 1.43; 95% CI 1.02-2.02). After excluding infants who died <5 days post-birth (i.e., before the clinical presentation of NOWS), regression estimates of infant mortality did not significantly differ by NOWS diagnosis. Likewise, regression estimates did not significantly differ by maternal MOUD receipt in the full sample.

CONCLUSIONS

Maternal OUD is associated with an elevated risk of infant mortality without evidence of modification by NOWS nor by maternal MOUD treatment. Future research should investigate potential mechanisms linking maternal OUD, NOWS, MOUD treatment, and infant mortality to better inform clinical intervention.

Social fund and infant mortality: Evidence from an anti-poverty policy in Northeast Brazil

This paper evaluates the effects of a social fund that meets the needs of the poor in Northeast Brazil, the Fundos Estaduais de Combate e Erradicação da Pobreza (FECEP). The program could have improved infant health by reducing poverty and improving access to health care, sanitation, food, and housing. Using a difference-in-differences approach robust to heterogeneous treatment effects, we confirm that the program has effectively reduced poverty in treated areas. Furthermore, we document that this poverty reduction is associated with a significant decline in infant mortality. These findings provide consistent evidence that targeted public investments can improve living conditions in vulnerable regions.

Perinatal health effects of herbicides exposures in the United States: the Heartland Study, a Midwestern birth cohort study

BACKGROUND

The objective of the Heartland Study is to address major knowledge gaps concerning the health effects of herbicides on maternal and infant health. To achieve this goal, a two-phased, prospective longitudinal cohort study is being conducted. Phase 1 is designed to evaluate associations between biomarkers of herbicide concentration and pregnancy/childbirth outcomes. Phase 2 is designed to evaluate potential associations between herbicide biomarkers and early childhood neurological development.

METHODS

People (target enrollment of 2,000) who are seeking prenatal care, are ages 18 or older, and are ≤ 20 + 6 weeks gestation will be eligible for recruitment. The Heartland Study will utilize a combination of questionnaire data and biospecimen collections to meet the study objectives. One prenatal urine and buccal sample will be collected per trimester to assess the impact of herbicide concentration levels on pregnancy outcomes. Infant buccal specimens will be collected post-delivery. All questionnaires will be collected by trained study staff and clinic staff will remain blinded to all individual level research data. All data will be stored in a secure REDCap database. Hospitals in the agriculturally intensive states in the Midwestern region will be recruited as study sites. Currently participating clinical sites include Indiana University School of Medicine- affiliated Hospitals in Indianapolis, Indiana; Franciscan Health Center in Indianapolis, Indiana; Gundersen Lutheran Medical Center in La Crosse, Wisconsin, and University of Iowa in Iowa City, Iowa. An anticipated 30% of the total enrollment will be recruited from rural areas to evaluate herbicide concentrations among those pregnant people residing in the rural Midwest. Perinatal outcomes (e.g. birth outcomes, preterm birth, preeclampsia, etc.) will be extracted by trained study teams and analyzed for their relationship to herbicide concentration levels using appropriate multivariable models.

DISCUSSION

Though decades of study have shown that environmental chemicals may have important impacts on the health of parents and infants, there is a paucity of prospective longitudinal data on reproductive impacts of herbicides. The recent, rapid increases in herbicide use across agricultural regions of the United States necessitate further research into the human health effects of these chemicals, particularly in pregnant people. The Heartland Study provides an invaluable opportunity to evaluate health impacts of herbicides during pregnancy and beyond.

TRIAL REGISTRATION

The study is registered at clinicaltrials.gov, NCT05492708 with initial registration and release 05 August, 2022.

Health insurance coverage and poverty status of postpartum women in the United States in 2019: an ACS-PUMS population-based cross-sectional study

BACKGROUND

A quarter of United States (US) postpartum women still report unmet health care needs and health care unaffordability. We aimed to study associations between receipt of health insurance coverage and poverty status/receipt of government financial support and determine coverage gaps overall and by social factors among US postpartum women in poverty.

METHODS

This study design is a cross-sectional study using secondary data. We included women who gave birth within the last 12 months from 2019 American Community Survey Public Use Microdata Sample. Poverty was defined as having an income-to-poverty ratio of less than 100%. We explored Medicaid/government medical assistance gaps among women in poverty. To examine the associations between Medicaid/government medical assistance (exposures) and poverty/government financial support (outcomes), we used age-, race-, and multivariable-adjusted logistic regression models. We also evaluated the associations of state, race, citizenship status, or language other than English spoken at home (exposures) with receipt of Medicaid/government medical assistance (outcomes) among women in poverty through multivariable-adjusted logistic regression.

RESULTS

It was notable that 35.6% of US postpartum women in poverty did not have Medicaid/government medical assistance and only a small proportion received public assistance income (9.8%)/supplementary security income (3.1%). Women with Medicaid/government medical assistance, compared with those without the coverage, had statistically significantly higher odds of poverty [adjusted odds ratio (aOR): 3.15, 95% confidence interval (95% CI): 2.85-3.48], having public assistance income (aOR: 24.52 [95% CI: 17.31-34.73]), or having supplementary security income (aOR: 4.22 [95% CI: 2.81-6.36]). Also, among postpartum women in poverty, women in states that had not expanded Medicaid, those of Asian or other race, non-US citizens, and those speaking another language had statistically significantly higher odds of not receiving Medicaid/government medical assistance [aORs (95% CIs): 2.93 (2.55-3.37); 1.30 (1.04-1.63); 3.65 (3.05-4.38); and 2.08 (1.86-2.32), respectively].

CONCLUSIONS

Our results showed that the receipt of Medicaid/government medical assistance is significantly associated with poverty and having government financial support. However, postpartum women in poverty still had Medicaid/government medical assistance gaps, especially those who lived in states that had not expanded Medicaid, those of Asian or other races, non-US citizens, and other language speakers.

Disparities Contributing to Late-Stage Diagnosis of Lung, Colorectal, Breast, and Cervical Cancers: Rural and Urban Poverty in Florida

Despite advances in cancer screening, late-stage cancer diagnosis is still a major cause of morbidity and mortality in the United States. In this study, we aim to understand demographic and geographic factors associated with receiving a late-stage diagnosis (LSD) of lung, colorectal, breast, or cervical cancer. (1) Methods: We analyzed data of patients with a cancer diagnosis between 2016 and 2020 from the Florida Cancer Data System (FCDS), a statewide population-based registry. To investigate correlates of LSD, we estimated multi-variable logistic regression models for each cancer while controlling for age, sex, race, insurance, and census tract rurality and poverty. (2) Results: Patients from high-poverty rural areas had higher odds for LSD of lung (OR = 1.23, 95% CI (1.10, 1.37)) and breast cancer (OR = 1.31, 95% CI (1.17,1.47)) than patients from low-poverty urban areas. Patients in high-poverty urban areas saw higher odds of LSD for lung (OR = 1.05 95% CI (1.00, 1.09)), breast (OR = 1.10, 95% CI (1.06, 1.14)), and cervical cancer (OR = 1.19, 95% CI (1.03, 1.37)). (3) Conclusions: Financial barriers contributing to decreased access to care likely drive LSD for cancer in rural and urban communities of Florida.

Increasing Access: Telehealth and Rural Obstetric Care

Parturients in rural areas face many barriers in access to care, including distance to maternity care sites and lack of maternity providers. Expanding telehealth modalities is recommended to help expand access to care. Although there is increasing evidence in support of telehealth in rural America, the success of telehealth lies in infrastructure (broadband network availability), regional support, and funding.

Spatial spillover impact of determinants on child mortality in Pakistan: evidence from Spatial Durbin Model

BACKGROUND

Child mortality is a major challenge to public health in Pakistan and other developing countries. Reduction of the child mortality rate would improve public health and enhance human well-being and prosperity. This study recognizes the spatial clusters of child mortality across districts of Pakistan and identifies the direct and spatial spillover effects of determinants on the Child Mortality Rate (CMR).

METHOD

Data of the multiple indicators cluster survey (MICS) conducted by the United Nations International Children's Emergency Fund (UNICEF) was used to study the CMR. We used spatial univariate autocorrelation to test the spatial dependence between contiguous districts concerning CMR. We also applied the Spatial Durbin Model (SDM) to measure the spatial spillover effects of factors on CMR.

RESULTS

The study results showed 31% significant spatial association across the districts and identified a cluster of hot spots characterized by the high-high CMR in the districts of Punjab province. The empirical analysis of the SDM confirmed that the direct and spatial spillover effect of the poorest wealth quintile and MPI vulnerability on CMR is positive whereas access to postnatal care to the newly born child and improved drinking water has negatively (directly and indirectly) determined the CMR in Pakistan.

CONCLUSION

The instant results concluded that spatial dependence and significant spatial spillover effects concerning CMR exist across districts. Prioritization of the hot spot districts characterized by higher CMR can significantly reduce the CMR with improvement in financial statuses of households from the poorest quintile and MPI vulnerability as well as improvement in accessibility to postnatal care services and safe drinking water.

Disparities in Neonatal Outcomes: Past, Present, and Our Future?

Neonatal outcomes and infant mortality rates have improved significantly in the past century. However, the disparities in outcomes linked to racial and ethnic variations have persisted and actually increased. Those differences in outcomes have been acknowledged for years as care providers strive to improve care for all of our most vulnerable and youngest individuals. Trends in neonatal outcomes are summarized.

Infant Mortality Trends and Determinants in Kazakhstan

Infant mortality rate (IMR) is a crucial indicator of healthcare performance and a reflection of a country's socioeconomic development. We analyzed the trends of IMR in Central Asia (CA) countries and its determinants in Kazakhstan, which is a middle-income country. Linear regression was used for IMR trend analysis in CA countries from 2000 to 2020 and for exploring associations between IMR and socioeconomic factors, health service-related factors, and population health indicators-related factors. A gamma generalized linear model was applied to define associations with various determinants. Our analysis revealed that IMR has decreased in all CA countries, with Kazakhstan having the lowest rate in 2000 and 2020. Our results suggest that socioeconomic indicators, such as total unemployment, Gini index, current health expenditure, gross domestic product (GDP), proportion of people living in poverty, and births by 15-19-year-old mothers, were associated with increased infant mortality rates. Improving socioeconomic conditions, investing in healthcare systems, reducing poverty and income inequality, and improving access to education, are all potential issues for further development. Addressing these factors may be critical for improving maternal and child health outcomes in the region.

What is the impact of national public expenditure and its allocation on neonatal and child mortality? A machine learning analysis

BACKGROUND

Understanding the impact of national public expenditure and its allocation on child mortality may help governments move towards target 3.2 proposed in the 2030 Agenda. The objective of this study was to estimate the impacts of governmental expenditures, total, on health, and on other sectors, on neonatal mortality and mortality of children aged between 28 days and five years.

METHODS

This study has an ecological design with a population of 147 countries, with data between 2012 and 2019. Two steps were used: first, the Generalized Propensity Score of public spending was calculated; afterward, the Generalized Propensity Score was used to estimate the expenditures' association with mortality rates. The primary outcomes were neonatal mortality rates (NeoRt) and mortality rates in children between 28 days and 5 years (NeoU5Rt).

RESULTS

The 1% variation in Int$ Purchasing Power Parity (Int$ PPP) per capita in total public expenditures, expenditure in health, and in other sectors were associated with a variation of -0.635 (95% CI -1.176, -0.095), -2.17 (95% CI -3.051, -1.289) -0.632 (95% CI -1.169, -0.095) in NeoRt, respectively The same variation in public expenditures in sectors other than health, was associates with a variation of -1.772 (95% CI -6.219, -1.459) on NeoU5Rt. The results regarding the impact of total and health public spending on NeoU5Rt were not consistent.

CONCLUSION

Public investments impact mortality in children under 5 years of age. Likely, the allocation of expenditures between the health sector and the other social sectors will have different impacts on mortality between the NeoRt and the NeoU5Rt.

County-level jail incarceration, community economic distress, rurality, and preterm birth among women in the US South

Introduction

The USA has higher rates of preterm birth and incarceration than any other developed nation, with rates of both being highest in Southern states and among Black Americans, potentially due to rurality and socioeconomic factors. To test our hypothesis that prior-year county-level rates of jail admission, economic distress, and rurality were positively associated with premature birth rates in the county of delivery in 2019 and that the strength of these associations is greater for Black women than for White or Hispanic women, we merged five datasets to perform multivariable analysis of data from 766 counties across 12 Southern/rural states.

Methods

We used multivariable linear regression to model the percentage of babies born premature, stratified by Black (Model 1), Hispanic (Model 2), and White (Model 3) mothers. Each model included all three independent variables of interest measured using data from the Vera Institute, Distressed Communities Index, and Index of Relative Rurality.

Results

In fully fitted stratified models, economic distress was positively associated with premature births among Black (F = 33.81, p < 0.0001) and White (F = 26.50, p < 0.0001) mothers. Rurality was associated with premature births among White mothers (F = 20.02, p < 0.0001). Jail admission rate was not associated with premature births among any racial group, and none of the study variables were associated with premature births among Hispanic mothers.

Conclusions

Understanding the connections between preterm birth and enduring structural inequities is a necessary scientific endeavor to advance to later translational stages in health-disparities research.

Emission of Industrial Air Pollution and Mortality Due to Respiratory Diseases: A Birth Cohort Study in Poland

BACKGROUND

Air pollution is a major risk factor for public health worldwide, but evidence linking this environmental problem with the mortality of children in Central Europe is limited.

OBJECTIVE

To investigate the relationship between air pollution due to the emission of industry-related particulate matter and mortality due to respiratory diseases under one year of age.

METHODS

A retrospective birth cohort analysis of the dataset including 2,277,585 children from all Polish counties was conducted, and the dataset was matched with 248 deaths from respiratory diseases under one year of age. Time to death during the first 365 days of life was used as a dependent variable. Harmful emission was described as total particle pollution (TPP) from industries. The survival analysis was performed using the Cox proportional hazards model for the emission of TPP at the place of residence of the mother and child, adjusted individual characteristics, demographic factors, and socioeconomic status related to the contextual level.

RESULTS

Infants born in areas with extremely high emission of TPP had a significantly higher risk of mortality due to respiratory diseases: hazard ratio (HR) = 1.781 [95% confidence interval (CI): 1.175, 2.697], p = 0.006, compared with those born in areas with the lowest emission levels. This effect was persistent when significant factors were adjusted at individual and contextual levels (HR = 1.959 [95% CI: 1.058, 3.628], p = 0.032). The increased risk of mortality was marked between the 50th and 150th days of life, coinciding with the highest exposure to TPP.

CONCLUSIONS

The emission of TPP from industries is associated with mortality due to respiratory diseases under one year of age. A considerable proportion of children's deaths could be prevented in Poland, especially in urban areas, if air pollution due to the emission of particle pollution is reduced.

Influence of maternal age on birth and infant outcomes at 6 months: a cohort study with quantitative bias analysis

BACKGROUND

Maternal age is increasingly recognized as a predictor of birth outcomes. Given the importance of birth and growth outcomes for children's development, wellbeing and survival, this study examined the effect of maternal age on infant birth and growth outcomes at 6 months and mortality. Additionally, we conducted quantitative bias analysis (QBA) to estimate the role of selection bias and unmeasured confounding on the effect of maternal age on infant mortality.

METHODS

We used data from randomized-controlled trials (RCTs) of 21 555 neonates in Burkina Faso conducted in 2019-2020. Newborns of mothers aged 13-19 years (adolescents) and 20-40 years (adults) were enrolled in the study 8-27 days after birth and followed for 6 months. Measurements of child's anthropometric measures were collected at baseline and 6 months. We used multivariable linear regression to compare child anthropometric measures at birth and 6 months, and logistic regression models to obtain the odds ratio (OR) of all-cause mortality. Using multidimensional deterministic analysis, we assessed scenarios in which the difference in selection probability of adolescent and adult mothers with infant mortality at 6 months increased from 0% to 5%, 10%, 15% and 20% if babies born to adolescent mothers more often died during the first week or were of lower weight and hence were not eligible to be included in the original RCT. Using probabilistic bias analysis, we assessed the role of unmeasured confounding by socio-economic status (SES).

RESULTS

Babies born to adolescent mothers on average had lower weight at birth, lower anthropometric measures at baseline, similar growth outcomes from enrolment to 6 months and higher odds of all-cause mortality by 6 months (adjusted OR = 2.17, 95% CI 1.35 to 3.47) compared with those born to adult mothers. In QBA, we found that differential selection of adolescent and adult mothers could bias the observed effect (OR = 2.24, 95% CI 1.41 to 3.57) towards the null [bias-corrected OR range: 2.37 (95% CI 1.49 to 3.77) to 2.84 (95% CI 1.79 to 4.52)], whereas unmeasured confounding by SES could bias the observed effect away from the null (bias-corrected OR: 2.06, 95% CI 1.31 to 2.64).

CONCLUSIONS

Our findings suggest that delaying the first birth from adolescence to adulthood may improve birth outcomes and reduce mortality of neonates. Babies born to younger mothers, who are smaller at birth, may experience catch-up growth, reducing some of the anthropometric disparities by 6 months of age.

Food environment index and preterm birth rate in the counties of the United States

OBJECTIVES

To determine the relationship between Food Environment Index (FEI) and Preterm Birth (PTB) rate at the county level of the United States of America (USA) (primary), while evaluating the interaction of multiple factors within a framework of sociodemographic, maternal health, maternal behavioral, and environmental factors.

METHODS

This is a population-based retrospective cohort ecological study from 2015-2018. The study compares the characteristics of the population of the counties of the USA. All counties with complete data on their PTB rate and the independent variables were included in the study. Independent variables with greater than 20% missing data were excluded from the study. Purposive sampling technique was applied. A total of 2983/3142 counties were included in the study.

RESULTS

The median PTB rate of all counties was 9.90%. The highest PTB rate (23.3%) was in Tallapoosa County, Alabama and the lowest (3.4%) in San Juan County, Washington State. After adjusting for variables, PTB rate had a significant association with FEI (coefficient of correlation - 0.36, p < 0.01, 95% CI - 0.19 to - 0.04). Increase in the rate of unemployment, African American race, adult smoking, obesity, uninsured rate, sexually transmitted diseases (STD), high school education and air pollution was associated with an increase in PTB rate, while an increase in FEI and alcohol abuse rates was associated with a decrease in PTB rate.

CONCLUSIONS

FEI can predict the PTB rate in USA counties after adjusting for sociodemographic, health, behavioral and environmental factors. Future studies are needed to confirm these associations and consider them when making policies to reduce PTBs.

Double Impact: A Dyadic Discrimination Model for Poor, Minority, and Pregnant Couples

Frequent daily discrimination compounds the negative health impacts of those with multiple marginalized identities, including pregnant mothers and their children. We used a dyadic, moderated, mediated model of 296 young, expectant, poor, urban, primarily minority couples. In this study, we explored if a multiple pathway discrimination model explained the relationship between multiple marginalized identities and health (depression and stress). We also examined if a mediated (discrimination moderated by gender) model, within a minority-stress and intersectional framework explained the relationship with depression and stress for couples. We observed that frequent daily discrimination was associated with negative health outcomes (depression and stress). Women reported significantly more depression than men. Frequent daily discrimination mediated the relationship between multiple marginalized identities and depression and stress and having a partner with multiple marginations increased one's personal depression and stress. Our observations suggest that discrimination's impact on health is experienced during pregnancy and the more marginalized identities one carries, the more impact it may have. Further, having a partner with multiple marginalized identities also impacts the depression and stress reported by women. Inventions to address depression and stress outcomes may be strengthened by considering multiple marginalized identities and include couples.

An assessment of random forest technique using simulation study: illustration with infant mortality in Bangladesh

We aimed to assess different machine learning techniques for predicting infant mortality (<1 year) in Bangladesh. The decision tree (DT), random forest (RF), support vector machine (SVM) and logistic regression (LR) approaches were evaluated through accuracy, sensitivity, specificity, precision, F1-score, receiver operating characteristics curve and k-fold cross-validation via simulations. The Boruta algorithm and chi-square ( χ 2 ) test were used for features selection of infant mortality. Overall, the RF technique (Boruta: accuracy = 0.8890, sensitivity = 0.0480, specificity = 0.9789, precision = 0.1960, F1-score = 0.0771, AUC = 0.6590; χ 2 : accuracy = 0.8856, sensitivity = 0.0536, specificity = 0.9745, precision = 0.1837, F1-score = 0.0828, AUC = 0.6480) showed higher predictive performance for infant mortality compared to other approaches. Age at first marriage and birth, body mass index (BMI), birth interval, place of residence, religion, administrative division, parents education, occupation of mother, media-exposure, wealth index, gender of child, birth order, children ever born, toilet facility and cooking fuel were potential determinants of infant mortality in Bangladesh. Study findings may help women, stakeholders and policy-makers to take necessary steps for reducing infant mortality by creating awareness, expanding educational programs at community levels and public health interventions.

Associations between maternal residential rurality and maternal health, access to care, and very low birthweight infant outcomes

OBJECTIVE

Infant mortality is increased in isolated rural areas. This study compares prenatal factors, access to care, and health outcomes for very-low birthweight (VLBW) infants by degree of maternal residential rurality.

METHODS

This descriptive population-based retrospective cohort study used the California Perinatal Quality Care Collaborative registry to study VLBW infants. Rurality was assigned as urban, large rural, and small rural/isolated using the Rural Urban Commuting Area codes. We used hierarchical random effect models to test the association of rurality with survival without major morbidity.

RESULTS

The study included 38 614 dyads. VLBW survival without major morbidity decreased with increasing rurality and the relationship remained significant for small rural/isolated areas (OR 0.79, p = 0.03) after adjustment. Birth weight, gestational age, and infant sex were similar across geographic groups.

CONCLUSION

A rural urban disparity exists for VLBW survival without major morbidity. Our findings generate hypotheses about factors that may be driving these disparities.

Planetary health and health education in Brazil: Facing inequalities

Brazil has the world's fifth-largest population and seventh-largest economy. However, it also has many inequalities, especially in health education, which impacts health sector services. Thus, this article aims to describe the situation of planetary health and health education in Brazil, identifying how current policies support the cause of planetary health. This study had a qualitative approach characterised as exploratory research based on an integrative review and documentary research. The results show that, in recent decades, there have been positive improvements to achieve collective and planetary health, which advocates empathy and pro-environmental and humanitarian attitudes. However, the pursuit of planetary health in Brazil is being influenced by various challenges, ranging from the need for a sound policy framework to provisions of education and training on planetary health. Based on the need to address these deficiencies, the paper suggests some measures which should be considered as part of efforts to realise the potential of planetary health in the fifth largest country in the world.

Spatio-temporal variations in neonatal mortality rates in Ghana: An application of hierarchical Bayesian methods

Ghana might not meet the SDGs target 3.2 of reducing neonatal mortality to 12 deaths per 1000 live births by 2030. Identifying core determinants of neonatal deaths provide policy guidelines and a framework aimed at mitigating the effect of neonatal deaths. Most studies have identified household and individual-level factors that contribute to neonatal mortality. However, there are relatively few studies that have rigorously assessed geospatial covariates and spatiotemporal variations of neonatal deaths in Ghana. This study focuses on modeling and mapping of spatiotemporal variations in the risk of neonatal mortality in Ghana using Bayesian Hierarchical Spatiotemporal models. This study used data from the Ghana Demographic and Health Surveys (GDHS) conducted in 1993, 1998, 2003, 2008, and 2014. We employed Bayesian Hierarchical Spatiotemporal regression models to identify geospatial correlates and spatiotemporal variations in the risk of neonatal mortality. The estimated weighted crude neonatal mortality rate for the period under consideration was 33.2 neonatal deaths per 1000 live births. The results obtained from Moran's I statistics and CAR model showed the existence of spatial clustering of neonatal mortality. The map of smooth relative risk identified Ashanti region as the most consistent hot-spot region for the entire period under consideration. Small body size babies contributed significantly to an increased risk of neonatal mortality at the regional level [Posterior Mean: 0.003 (95% CrI: 0.00,0.01)]. Hot spot GDHS clusters exhibiting high risk of neonatal mortality were identified by LISA cluster map. Rural residents, small body size babies, parity, and aridity contributed significantly to a higher risk of neonatal mortality at the GDHS cluster level. The findings provide actionable and insightful information to prioritize and distribute the scarce health resources equitably to tackle the menace of neonatal mortality. The regions and GDHS clusters with excess risk of neonatal mortality should receive optimum attention and interventions to reduce the neonatal mortality rate.

Out-of-hospital births and infant mortality in the United States: Effect measure modification by rural maternal residence

BACKGROUND

Out-of-hospital births have been increasing in the United States, and home births are almost twice as common in rural vs. urban counties. Planned home births and births in rural areas have each been associated with an increased risk of infant mortality.

OBJECTIVES

To estimate the effect of birth setting on infant mortality in the United States and how this is modified by rural-urban county of maternal residence.

METHODS

We conducted a population-based cohort study of infants born in the United States during 2010-2017 using the National Center for Health Statistics' period-linked birth-infant death files. Unadjusted and adjusted Poisson regression models were used to calculate infant mortality rate ratios and 95% confidence intervals for out-of-hospital births vs. hospital births stratified by maternal residence. Relative excess risk due to interaction (RERI) was calculated to assess effect measure modification on the additive scale.

RESULTS

The study included 25,210,263 live births. Of rural births, 97.8% was in hospitals, 0.5% was in birth centres, and 1.5% was planned home births; of urban births, 98.6% was in hospitals, 0.5% was in birth centres, and 0.7% was planned home births. After adjusting for maternal demographics and markers of high-risk pregnancy and stratifying by maternal residence, infant mortality rates were generally higher for out-of-hospital as compared to hospital births (e.g. rural planned home births aRR 1.62, 95% confidence interval [CI] 1.42, 1.85, and rural birth centre aRR 1.33, 95% CI 1.05, 1.68). There were positive additive effects of rural residence on infant mortality for planned home births and birth centre births.

CONCLUSIONS

Within both rural and urban areas, out-of-hospital births generally had higher rates of infant mortality than hospital births after accounting for maternal demographics and markers of high-risk pregnancy. The risks associated with planned home births and birth centre births were more pronounced for women in rural counties.

Does a Rising Median Income Lift All Birth Weights? County Median Income Changes and Low Birth Weight Rates Among Births to Black and White Mothers

Policy Points Policies that increase county income levels, particularly for middle-income households, may reduce low birth weight rates and shrink disparities between Black and White infants. Given the role of aggregate maternal characteristics in predicting low birth weight rates, policies that increase human capital investments (e.g., funding for higher education, job training) could lead to higher income levels while improving population birth outcomes. The association between county income levels and racial disparities in low birth weight is independent of disparities in maternal risks, and thus a broad set of policies aimed at increasing income levels (e.g., income supplements, labor protections) may be warranted.

CONTEXT

Low birth weight (LBW; <2,500 grams) and infant mortality rates vary among place and racial group in the United States, with economic resources being a likely fundamental contributor to these disparities. The goals of this study were to examine time-varying county median income as a predictor of LBW rates and Black-White LBW disparities and to test county prevalence and racial disparities in maternal sociodemographic and health risk factors as mediators.

METHODS

Using national birth records for 1992-2014 from the National Center for Health Statistics, a total of approximately 27.4 million singleton births to non-Hispanic Black and White mothers were included. Data were aggregated in three-year county-period observations for 868 US counties meeting eligibility requirements (n = 3,723 observations). Sociodemographic factors included rates of low maternal education, nonmarital childbearing, teenage pregnancy, and advanced-age pregnancy; and health factors included rates of smoking during pregnancy and inadequate prenatal care. Among other covariates, linear models included county and period fixed effects and unemployment, poverty, and income inequality.

FINDINGS

An increase of $10,000 in county median income was associated with 0.34 fewer LBW cases per 100 live births and smaller Black-White LBW disparities of 0.58 per 100 births. Time-varying county rates of maternal sociodemographic and health risks mediated the association between median income and LBW, accounting for 65% and 25% of this estimate, respectively, but racial disparities in risk factors did not mediate the income association with Black-White LBW disparities. Similarly, county median income was associated with very low birth weight rates and related Black-White disparities.

CONCLUSIONS

Efforts to increase income levels-for example, through investing in human capital, enacting labor union protections, or attracting well-paying employment-have broad potential to influence population reproductive health. Higher income levels may reduce LBW rates and lead to more equitable outcomes between Black and White mothers.

Association between maternal smoking and survival among infants with trisomy 21

BACKGROUND

Trisomy 21 (T21) is common, with affected infants having an increased risk of infant mortality (5.9-7.1%). Maternal smoking is associated with infant mortality in the general population, and we evaluated if similar associations were present among infants with T21.

METHODS

We identified infants with T21 from the Texas Birth Defects Registry, and maternal smoking and infant vital status were obtained from linked birth and death certificate data, respectively. Cox proportional hazards regression models were used to calculate hazard ratios between maternal smoking and death between 0 to ≤ 364 days, 28-364 days, and 0-27 days.

RESULTS

We found a significant association between maternal smoking and death between 0 to ≤ 364 (unadjusted HR 1.72, 95% CI 1.07, 2.77), which was no longer statistically significant after adjustment for covariates (adjusted HR 1.55, 95% CI 0.94, 2.56). A similar pattern was observed for death between 28-364 days (adjusted HR: 1.68, 95% CI 0.93, 3.03), whereas the association for 0-27 days (adjusted HR: 1.30, 95% CI 0.51, 3.29) was not statistically significant before and after adjustment.

CONCLUSIONS

The observed magnitudes of associations were similar to previous estimates among the general population. Further work considering the role of other maternal and infant risk factors and social determinants of health is necessary to better understand the observed results.

Improving Sexual Health in U.S. Rural Communities: Reducing the Impact of Stigma

Sexually transmitted infections (STI), including HIV, are among the most reported diseases in the U.S. and represent some of America's most significant health disparities. The growing scarcity of health care services in rural settings limits STI prevention and treatment for rural Americans. Local health departments are the primary source for STI care in rural communities; however, these providers experience two main challenges, also known as a double disparity: (1) inadequate capacity and (2) poor health in rural populations. Moreover, in rural communities the interaction of rural status and key determinants of health increase STI disparities. These key determinants can include structural, behavioral, and interpersonal factors, one of which is stigma. Engaging the expertise and involvement of affected community members in decisions regarding the needs, barriers, and opportunities for better sexual health is an asset and offers a gateway to sustainable, successful, and non-stigmatizing STI prevention programs.

Maternal Age, the Disparity across Regions and Their Correlation to Sudden Infant Death Syndrome in Taiwan: A Nationwide Cohort Study

Sudden infant death syndrome (SIDS) has always been a regrettable issue for families. After sleeping in the supine position was proposed, the incidence of SIDS declined dramatically worldwide. However, SIDS still accounts for the top 10 causes of infant deaths in Taiwan. Recognizing the risk factors and attempting to minimize these cases are imperative. We obtained information on cases with SIDS from the National Health Insurance Research Database in Taiwan and interconnected it with the Taiwan Maternal and Child Health Database to acquire infant-maternal basal characteristics between 2004 and 2017. The SIDS subjects were matched 1:10 considering gestational age to normal infants. After case selection, a total of 953 SIDS cases were included. Compared with healthy infants, SIDS infants had younger parents, lower birth weight, and lower Apgar scores. After adjusting for potential confounders, infants with mothers aged <20 years had 2.81 times higher risk of SIDS. Moreover, infants in the non-eastern region had a significantly lower risk of SIDS than those in the eastern region. We concluded that infants of young mothers (especially maternal age <20 years) and infants in the eastern region of Taiwan had a higher risk of SIDS than their counterparts.

Infant mortality among native-born children of immigrants in France, 2008-17: results from a socio-demographic panel survey

BACKGROUND

Within Europe, France stands out as a major country that lacks recent and reliable evidence on how infant mortality levels vary among the native-born children of immigrants compared with the native-born children of two parents born in France.

METHODS

We used a nationally representative socio-demographic panel consisting of 296 400 births and 980 infant deaths for the period 2008-17. Children of immigrants were defined as being born to at least one parent born abroad and their infant mortality was compared with that of children born to two parents born in France. We first calculated infant mortality rates per 1000 live births. Then, using multi-level logit models, we calculated odds ratios of infant mortality in a series of models adjusting progressively for parental origins (M1), core demographic factors (M2), father's socio-professional category (M3) and area-level urbanicity and deprivation score (M4).

RESULTS

We documented a substantial amount of excess infant mortality among those children born to at least one parent from Eastern Europe, Northern Africa, Western Africa, Other Sub-Saharan Africa and the Americas, with variation among specific origin countries belonging to these groups. In most of these cases, the excess infant mortality levels persisted after adjusting for all individual-level and area-level factors.

CONCLUSIONS

Our findings, which can directly inform national public health policy, reaffirm the persistence of longstanding inequality in infant mortality according to parental origins in France and add to a growing body of evidence documenting excess infant mortality among the children of immigrants in Europe.

County Poverty, Urban-Rural Classification, and the Causes of Term Infant Death : United States, 2012-2015

OBJECTIVE

Higher mortality among full-term infants (term infant deaths) contributes to disparities in infant mortality between the United States and other developed countries. We examined differences in the causes of term infant deaths across county poverty levels and urban-rural classification to understand underlying mechanisms through which these factors may act.

METHODS

We linked period birth/infant death files for 2012-2015 with US Census poverty estimates and county urban-rural classifications. We grouped the causes of term infant deaths as sudden unexpected death in infancy (SUDI), congenital malformations, perinatal conditions, and all other causes. We computed the distribution and relative risk of overall and cause-specific term infant mortality rates (term IMRs) per 1000 live births and 95% CIs for county-level factors.

RESULTS

The increase in term IMR across county poverty and urban-rural classification was mostly driven by an increase in the rate of SUDI. The relative risk of term infant deaths as a result of SUDI was 1.6 (95% CI, 1.5-1.8) times higher in medium-poverty counties and 2.3 (95% CI, 1.2-2.5) times higher in high-poverty counties than in low-poverty counties. Cause-specific IMRs of congenital malformations, perinatal conditions, and death from other causes did not differ by county poverty level. We found similar trends across county urban-rural classification. Sudden infant death syndrome was the main cause of SUDI across both county poverty levels and urban-rural classifications, followed by unknown causes and accidental suffocation and strangulation in bed.

CONCLUSIONS

Interventions aimed at reducing SUDI, particularly in high-poverty and rural areas, could have a major effect on reducing term IMR disparities between the United States and other developed countries.

Delivering Perinatal Health Information via a Voice Interactive App (SMILE): Mixed Methods Feasibility Study

BACKGROUND

Perinatal health care is critically important for maternal health outcomes in infants. The United States fares considerably worse than comparable countries for maternal and infant mortality rates. As such, alternative models of care or engagement are warranted. Ubiquitous digital devices and increased use of digital health tools have the potential to extend the reach to women and infants in their everyday lives and make a positive impact on their health outcomes. As voice technology becomes more mainstream, research is prudent to establish evidence-based practice on how to best leverage voice technology to promote maternal-infant health.

OBJECTIVE

The aim of this study is to assess the feasibility of using voice technology to support perinatal health and infant care practices.

METHODS

Perinatal women were recruited from a large Midwest Children's Hospital via hospital email announcements and word of mouth. Owing to the technical aspects of the intervention, participants were required to speak English and use an iPhone. Demographics, patterns of technology use, and technology use specific to perinatal health or self-care practices were assessed at baseline. Next, participants were onboarded and asked to use the intervention, Self-Management Intervention-Life Essentials (SMILE), over the course of 2 weeks. SMILE provided users with perinatal health content delivered through mini podcasts (ranging from 3 to 8 minutes in duration). After each podcast, SMILE prompted users to provide immediate verbal feedback to the content. An exit interview was conducted with participants to gather feedback on the intervention and further explore participants' perceptions of voice technology as a means to support perinatal health in the future.

RESULTS

In total, 19 pregnant women (17 to 36 weeks pregnant) were consented. Themes identified as important for perinatal health information include establishing routines, expected norms, and realistic expectations and providing key takeaways. Themes identified as important for voice interaction include customization and user preferences, privacy, family and friends, and context and convenience. Qualitative analysis suggested that perinatal health promotion content delivered by voice should be accurate and succinctly delivered and highlight key takeaways. Perinatal health interventions that use voice should provide users with the ability to customize the intervention but also provide opportunities to engage family members, particularly spouses. As a number of women multitasked while the intervention was being deployed, future interventions should leverage the convenience of voice technology while also balancing the influence of user context (eg, timing or ability to listen or talk versus nonvoice interaction with the system).

CONCLUSIONS

Our findings demonstrate the short-term feasibility of disseminating evidence-based perinatal support via podcasts and curate voice-captured data from perinatal women. However, key areas of improvement have been identified specifically for perinatal interventions leveraging voice technology. Findings contribute to future content, design, and delivery considerations of perinatal digital health interventions.

Structural racism, racial inequities and urban-rural differences in infant mortality in the US

Background

While evidence shows considerable geographic variations in county-level racial inequities in infant mortality, the role of structural racism across urban–rural lines remains unexplored. The objective of this study was to examine the associations between county-level structural racism (racial inequity in educational attainment, median household income and jail incarceration) and infant mortality and heterogeneity between urban and rural areas.

Methods

Using linked live birth/infant death data provided by the National Center for Health Statistics, we calculated overall and race-specific 2013–2017 5-year infant mortality rates (IMRs) per 1000 live births in every county. Racially stratified and area-stratified negative binomial regression models estimated IMR ratios and 95% CIs associated with structural racism indicators, adjusting for county-level confounders. Adjusted linear regression models estimated associations between structural racism indicators and the absolute and relative racial inequity in IMR.

Results

In urban counties, structural racism indicators were associated with 7%–8% higher black IMR, and an overall structural racism score was associated with 9% greater black IMR; however, these findings became insignificant when adjusting for the region. In white population, structural racism indicators and the overall structural racism score were associated with a 6% decrease in urban white IMR. Both absolute and relative racial inequity in IMR were exacerbated in urban counties with greater levels of structural racism.

Conclusions

Our findings highlight the complex relationship between structural racism and population health across urban–rural lines and suggest its contribution to the maintenance of health inequities in urban settings.

The Association Between Area Deprivation Index and Patient-Reported Outcomes in Patients with Advanced Cancer

Background: This analysis describes associations between area deprivation and patient-reported outcomes among patients with advanced cancer. Methods: This is a cross-sectional analysis of baseline data from a multisite primary palliative care intervention trial. Participants were adult patients with advanced cancer. Patient-level area deprivation scores were calculated using the Area Deprivation Index (ADI). Quality of life and symptom burden were measured. Uni- and multivariate regressions estimated associations between area deprivation and outcomes of interest. Results: Among 672 patients, ∼0.5 (54%) were women and most (94%) were Caucasian. Mean age was 69.3±10.2 years. Lung (36%), breast (13%), and colon (10%) were the most common malignancies. Mean ADI was 64.0, scale of 1 (low)-100 (high). In unadjusted univariate analysis, Functional Assessment of Cancer Therapy-Palliative (p=0.002), Edmonton Symptom Assessment Scale (p=0.025) and the Hospital Anxiety and Depression Scale anxiety (p=0.003) and depression (p=0.029) scores were significantly associated with residence in more deprived areas (p=0.003). In multivariate analysis, controlling for patient-level factors, living in more deprived areas was associated with more anxiety (p=0.019). Conclusion: Higher ADI was associated with higher levels of anxiety among patients with advanced cancer. Geographic information could assist clinicians with providing geographically influenced social support strategies.

Infant Mortality in Rural and Nonrural Counties in the United States

BACKGROUND AND OBJECTIVES

Rural counties have the highest infant mortality rates across the United States when compared with rates in more urban counties. We use a social-ecological framework to explain infant mortality disparities across the rural-urban continuum.

METHODS

We created a cohort of all births in the United States linked to infant death records for 2014 to 2016. Records were linked to county-level data from the Area Health Resources File and the American Community Survey and classified using the National Center for Health Statistics Urban-Rural Classification Scheme. Using multilevel generalized linear models, we investigated the association of infant mortality with county urban-rural classification, considering county health system resources and measures of socioeconomic advantage, net of individual-level characteristics, and controlling for US region and county centroid.

RESULTS

Infant mortality rates were highest in noncore (odds ratio [OR] = 1.32, 95% confidence interval [CI]: 1.26-1.39) and micropolitan counties (OR = 1.26, 95% CI: 1.20-1.32) when compared with large metropolitan fringe counties, controlling for geospatial measures. Inclusion of county health system characteristics did little to attenuate the greater odds of infant mortality in rural counties. Instead, a composite measure of county-level socioeconomic advantage was highly protective (adjusted OR = 0.84; 95% CI: 0.82-0.86) and eliminated any difference between the micropolitan and noncore counties and the large metropolitan fringe counties.

CONCLUSIONS

Higher infant mortality rates in rural counties are best explained by their greater socioeconomic disadvantage than more-limited access to health care or the greater prevalence of mothers' individual health risks.

Regional variation in Black infant mortality: The contribution of contextual factors

BACKGROUND

Compared to other racial/ethnic groups, infant mortality rates (IMR) are persistently highestamong Black infants in the United States, yet there is considerable regional variation. We examined state and county-level contextual factors that may explain regional differences in Black IMR and identified potential strategies for improvement.

METHODS AND FINDINGS

Black infant mortality data are from the Linked Birth/Infant Death files for 2009-2011. State and county contextual factors within social, economic, environmental, and health domains were compiled from various Census databases, the Food Environment Atlas, and the Area Health Resource File. Region was defined by the nine Census Divisions. We examined contextual associations with Black IMR using aggregated county-level Poisson regression with standard errors adjusted for clustering by state. Overall, Black IMR varied 1.5-fold across regions, ranging from 8.78 per 1,000 in New England to 13.77 per 1,000 in the Midwest. In adjusted models, the following factors were protective for Black IMR: higher state-level Black-White marriage rate (rate ratio (RR) per standard deviation (SD) increase = 0.81, 95% confidence interval (CI):0.70-0.95), higher state maternal and child health budget per capita (RR per SD = 0.96, 95% CI:0.92-0.99), and higher county-level Black index of concentration at the extremes (RR per SD = 0.85, 95% CI:0.81-0.90). Modeled variables accounted for 35% of the regional variation in Black IMR.

CONCLUSIONS

These findings are broadly supportive of ongoing public policy efforts to enhance social integration across races, support health and social welfare program spending, and improve economic prosperity. Although contextual factors accounted for about a third of regional variation, further research is needed to more fully understand regional variation in Black IMR disparities.

Factors affecting infant mortality in the general population: evidence from the 2016 Ethiopian demographic and health survey (EDHS); a multilevel analysis

Background

Infant mortality is one of the leading public health problems globally; the problem is even more staggering in low-income countries. In Ethiopia seven in ten child deaths occurred during infancy in 2016. Even though the problem is devastating, updated information about the major determinants of infant mortality which is done on a countrywide representative sample is lacking. Therefore, this study was aimed to identify factors affecting infant mortality among the general population of Ethiopia, 2016.

Methods

A Community-based cross-sectional study was conducted in all regions of Ethiopia from January 18 to June 27, 2016. A total of 10,641 live births were included in the analysis. Data were analyzed and reported with both descriptive and analytic statistics. Bivariable and multivariable multilevel logistic regression models were fitted by accounting correlation of individuals within a cluster. Adjusted odds ratio (AOR) with 95% confidence interval was reported to show the strength of the association and its significance.

Results

A total of 10,641 live-births from the Ethiopian demographic and health survey (EDHS) data were included in the analysis. Being male infant (AOR = 1.51; 1.25, 1.82), Multiple birth (AOR = 5.49; 95% CI, 3.88–7.78), Preterm (AOR = 8.47; 95% CI 5.71, 12.57), rural residents (AOR = 1.76; 95% CI; 1.16, 2.67), from Somali region (AOR = 2.07; 1.29, 3.33), Harari (AOR = 2.14; 1.22, 3.75) and Diredawa (AOR = 1.91; 1.04, 3.51) were found to be statistically significantly associated with infant mortality.

Conclusion

The study has assessed the determinants of infant mortality based on EDHS data. Sex of the child, multiple births, prematurity, and residence were notably associated with infant mortality. The risk of infant mortality has also shown differences across different regions. Since infant mortality is still major public health problem interventions shall be done giving more attention to infants who were delivered multiple and who are preterm.

Urban-Rural Infant Mortality Disparities by Race and Ethnicity and Cause of Death

INTRODUCTION

Infant mortality rates are higher in nonmetropolitan areas versus large metropolitan areas. Variation by race/ethnicity and cause of death has not been assessed. Urban-rural infant mortality rate differences were quantified by race/ethnicity and cause of death.

METHODS

National Vital Statistics System linked birth/infant death data (2014-2016) were analyzed in 2019 by 3 urban-rural county classifications: large metropolitan, medium/small metropolitan, and nonmetropolitan. Excess infant mortality rates (rate differences) by urban-rural classification were calculated relative to large metropolitan areas overall and for each racial/ethnic group. The number of excess deaths, population attributable fraction, and proportion of excess deaths attributable to underlying causes of death was calculated.

RESULTS

Nonmetropolitan areas had the highest excess infant mortality rate overall. Excess infant mortality rates were substantially lower for Hispanic infants than other races/ethnicities. Overall, 7.4% of infant deaths would be prevented if all areas had the infant mortality rate of large metropolitan areas. With more than half of births occurring outside of large metropolitan areas, the population attributable fraction was highest for American Indian/Alaska Natives (20.3%) and whites, non-Hispanic (14.3%). Excess infant mortality rates in both nonmetropolitan and medium/small metropolitan areas were primarily attributable to sudden unexpected infant deaths (42.3% and 31.9%) and congenital anomalies (30.1% and 26.8%). This pattern was consistent for all racial/ethnic groups except black, non-Hispanic infants, for whom preterm-related and sudden unexpected infant deaths accounted for the largest share of excess infant mortality rates.

CONCLUSIONS

Infant mortality increases with rurality, and excess infant mortality rates are predominantly attributable to sudden unexpected infant deaths and congenital anomalies, with differences by race/ethnicity regarding magnitude and cause of death.

Pediatric Complex Chronic Conditions: Does the Classification System Work for Infants?

BACKGROUND

One widely accepted approach to identify children with life-limiting health problems is the complex chronic conditions (CCCs) classification system. Although considered the "gold standard" for classifying children with serious illness, little is known about its performance, especially among infants.

OBJECTIVE/HYPOTHESIS

This research examined the prevalence of CCCs and the infant characteristics related to a CCC classification.

METHODS

Multivariate regression analysis was conducted with 2012 Kids' Inpatient Database, Healthcare Cost and Utilization Project data files, using a national sample of infant decedents less than 1 year.

RESULTS

Our findings showed that 40% of the infants were classified with a CCC. African Americans were negatively associated with a CCC classification (adjusted odds ratio [aOR] = 0.63; 95% confidence interval [CI] = 0.543-0.731). When infants had other insurance coverage, they were less likely (aOR = 0.63; 95% CI = 0.537-0.748) to have a CCC classification. Infants who resided in nonurban areas (aOR = 1.21; 95% CI =1.034-1.415) and had comorbidities (aOR = 38.19; 95% CI = 33.12-44.04) had greater odds of having a CCC classification.

CONCLUSIONS

The findings suggested that the infants are not commonly classified with a CCC and highlighted the significant variation in race with African American infants exhibiting different CCC classifications than Caucasian infants. Given the importance of reducing disparities in palliative care, critical attention to using CCC classifications in research is warranted.