Extreme maternal education and preterm birth: time-to-event analysis of age and nativity-dependent risks

Determinants of preterm birth among reproductive age women in sub-Saharan Africa: Evidence from the most recent Demographic and Health Survey data-2019-2022

INTRODUCTION

Preterm birth is the leading cause of both infant and neonatal mortality. It also had long-term consequences for the physical and neurological development of a growing child. The majority of these and related problems occur in low- and middle-income countries, particularly in sub-Saharan Africa, due to resource scarcity to sustain the lives of premature babies. Despite this, there is a paucity of recent information on the pooled prevalence and factors associated with preterm birth in sub-Saharan Africa. Therefore, this study aimed to update the pooled prevalence and determinants of preterm birth in sub-Saharan Africa based on the most recent Demographic and Health Survey data.

METHODS

A cross-sectional study design using the most recent demographic and health survey data from eight sub-Saharan African countries was used. We included a total weighted sample of 74,871 reproductive-aged women who gave birth in the five years preceding the survey. We used a multilevel logistic regression model to identify associated factors of preterm birth in sub-Saharan Africa. The adjusted odds ratio at 95% Cl was computed to assess the strength and significance of the association between explanatory and outcome variables. Factors with a p-value of <0.05 are declared statistically significant.

RESULTS

In this study, the pooled prevalence of preterm birth among reproductive-aged women in eight sub-Saharan African countries was 3.11% (95% CI: 2.98-3.25). Working mothers (AOR = 0.61; 95% CI: 0.38-0.97), being married (AOR = 0.63; 95% CI: 0.40-0.99), and having media exposure (AOR = 0.59; 95% CI: 0.36-0.96) decrease the odds of preterm birth. On the other hand, being low birth weight (AOR = 17.7; 95% CI: 10.7-29.3), having multiple pregnancies (AOR = 3.43; 95% CI: 1.82-6.45), having a history of terminated pregnancies (AOR = 1.56; 95% CI: 1.01-2.41), being un-educated (AOR = 3.16; 95% CI: 1.12-8.93), being of a maternal age above 35 (AOR = 1.63; 95% CI: 1.08-2.45), maternal alcohol use (AOR = 19.18; 95% CI: 13.6-38.8), and being in the low socio-economic status (AOR = 1.85; 95% CI: 1.11-3.07) of the community increase the odds of preterm birth.

CONCLUSION

The burden of preterm birth among reproductive-age women in sub-Saharan Africa showed improvements as compared to previous findings. To further lessen the burden, policymakers and other pertinent organizations must prioritize maternal health, expand media access, educate and empower women, and promote a healthy lifestyle for reproductive-age women.

Cervical length distribution among Brazilian pregnant population and risk factors for short cervix: A multicenter cross-sectional study

Objective

Since there are populational differences and risk factors that influence the cervical length, the aim of the study was to construct a populational curve with measurements of the uterine cervix of pregnant women in the second trimester of pregnancy and to evaluate which variables were related to cervical length (CL) ≤25 mm.

Materials and methods

This was a multicenter cross-sectional study performed at 17 hospitals in several regions of Brazil. From 2015 to 2019, transvaginal ultrasound scan was performed in women with singleton pregnancies at 18 0/7 to 22 6/7 weeks of gestation to measure the CL. We analyzed CL regarding its distribution and the risk factors for CL ≤25 mm using logistic regression.

Results

The percentage of CL ≤ 25mm was 6.67%. Shorter cervices, when measured using both straight and curve techniques, showed similar results: range 21.0–25.0 mm in straight versus 22.6–26.0 mm in curve measurement for the 5^th percentile. However, the difference between the two techniques became more pronounced after the 75^th percentile (range 41.0–42.0 mm straight x 43.6–45.0 mm in curve measurement). The risk factors identified for short cervix were low body mass index (BMI) (OR: 1.81 CI: 1.16–2.82), higher education (OR: 1.39 CI: 1.10–1.75) and personal history ([one prior miscarriage OR: 1.41 CI: 1.11–1.78 and ≥2 prior miscarriages OR: 1.67 CI: 1.24–2.25], preterm birth [OR: 1.70 CI: 1.12–2.59], previous low birth weight <2500 g [OR: 1.70 CI: 1.15–2.50], cervical surgery [OR: 4.33 CI: 2.58–7.27]). By contrast, obesity (OR: 0.64 CI: 0.51–0.82), living with a partner (OR: 0.76 CI: 0.61–0.95) and previous pregnancy (OR: 0.46 CI: 0.37–0.57) decreased the risk of short cervix.

Conclusions

The CL distribution showed a relatively low percentage of cervix ≤25 mm. There may be populational differences in the CL distribution and this as well as the risk factors for short CL need to be considered when adopting a screening strategy for short cervix.

Maternal preterm birth prediction in the United States: a case-control database study

Background

Preterm birth is serious public health worldwide, and early prediction of preterm birth in pregnant women may provide assistance for timely intervention and reduction of preterm birth. This study aimed to develop a preterm birth prediction model that is readily available and convenient for clinical application.

Methods

Data used in this case-control study were extracted from the National Vital Statistics System (NVSS) database between 2018 and 2019. Univariate and multivariate logistic regression analyses were utilized to find factors associated with preterm birth. Odds ratio (OR) and 95% confidence interval (CI) were used as effect measures. The area under the curve (AUC), accuracy, sensitivity, and specificity were utilized as model performance evaluation metrics.

Results

Data from 3,006,989 pregnant women in 2019 and 3,039,922 pregnant women in 2018 were used for the model establishment and external validation, respectively. Of these 3,006,989 pregnant women, 324,700 (10.8%) had a preterm birth. Higher education level of pregnant women [bachelor (OR = 0.82; 95%CI, 0.81–0.84); master or above (OR = 0.82; 95%CI, 0.81–0.83)], pre-pregnancy overweight (OR = 0.96; 95%CI, 0.95–0.98) and obesity (OR = 0.94; 95%CI, 0.93–0.96), and prenatal care (OR = 0.48; 95%CI, 0.47–0.50) were associated with a reduced risk of preterm birth, while age ≥ 35 years (OR = 1.27; 95%CI, 1.26–1.29), black race (OR = 1.26; 95%CI, 1.23–1.29), pre-pregnancy underweight (OR = 1.26; 95%CI, 1.22–1.30), pregnancy smoking (OR = 1.27; 95%CI, 1.24–1.30), pre-pregnancy diabetes (OR = 2.08; 95%CI, 1.99–2.16), pre-pregnancy hypertension (OR = 2.22; 95%CI, 2.16–2.29), previous preterm birth (OR = 2.95; 95%CI, 2.88–3.01), and plurality (OR = 12.99; 95%CI, 12.73–13.24) were related to an increased risk of preterm birth. The AUC and accuracy of the prediction model in the testing set were 0.688 (95%CI, 0.686–0.689) and 0.762 (95%CI, 0.762–0.763), respectively. In addition, a nomogram based on information on pregnant women and their spouses was established to predict the risk of preterm birth in pregnant women.

Conclusions

The nomogram for predicting the risk of preterm birth in pregnant women had a good performance and the relevant predictors are readily available clinically, which may provide a simple tool for the prediction of preterm birth.

Identifying the Early Signs of Preterm Birth from U.S. Birth Records Using Machine Learning Techniques

Preterm birth (PTB) is the leading cause of infant mortality in the U.S. and globally. The goal of this study is to increase understanding of PTB risk factors that are present early in pregnancy by leveraging statistical and machine learning (ML) techniques on big data. The 2016 U.S. birth records were obtained and combined with two other area-level datasets, the Area Health Resources File and the County Health Ranking. Then, we applied logistic regression with elastic net regularization, random forest, and gradient boosting machines to study a cohort of 3.6 million singleton deliveries to identify generalizable PTB risk factors. The response variable is preterm birth, which includes spontaneous and indicated PTB, and we performed a binary classification. Our results show that the most important predictors of preterm birth are gestational and chronic hypertension, interval since last live birth, and history of a previous preterm birth, which explains 10.92, 5.98, and 5.63% of the predictive power, respectively. Parents' education is one of the influential variables in predicting PTB, explaining 7.89% of the predictive power. The relative importance of race declines when parents are more educated or have received adequate prenatal care. The gradient boosting machines outperformed with an AUC of 0.75 (sensitivity: 0.64, specificity: 0.73) for the validation dataset. In this study, we compare our results with seminal and most related studies to demonstrate the superiority of our results. The application of ML techniques improved the performance measures in the prediction of preterm birth. The results emphasize the importance of socioeconomic factors such as parental education as one of the most important indicators of preterm birth. More research is needed on these mechanisms through which socioeconomic factors affect biological responses.

Comparing Birth Outcomes in Hawai'i between US- and Foreign-Born Women

The objective of this study is to examine the relationship between maternal nativity status and preterm birth (PTB) or low birth weight (LBW) for Hawai'i resident mothers, to compare these relationships across different maternal race/ethnicity groups, and to identify other potential risk and protective factors related to PTB and LBW. Using the 2004 Natality Birth Data from the National Vital Statistic System of the National Center for Health Statistics, crude and adjusted odds ratios were calculated using logistic regression to determine maternal racial/ethnic-specific nativity effects on PTB and LBW. Other Asian or Pacific Islander foreign-born mothers had higher unadjusted rates of PTB, and Samoan foreign-born mothers had lower rates of LBW after adjusting for the socio-demographic covariates compared to their native-born counterparts. Given the limitation of this study particularly relating to data quality, further research is needed to identify socio-contextual factors that are involved in the relationship between nativity status and PTB/LBW.

Are immigrants healthier than native-born Canadians? A systematic review of the healthy immigrant effect in Canada

OBJECTIVES

Immigrants are typically healthier than the native-born population in the receiving country and also tend to be healthier than non-migrants in the countries of origin. This foreign-born health advantage has been referred to as the healthy immigrant effect (HIE). We examined evidence for the HIE in Canada.

DESIGN

We employed a systematic search of the literature on immigration and health and identified 78 eligible studies. We used a narrative method to synthesize the HIE across different stages of the life-course and different health outcomes within each stage. We also examined the empirical evidence for positive selection and duration effects - two common explanations of migrants' health advantage and deterioration, respectively.

RESULTS

We find that the HIE appears to be strongest during adulthood but less so during childhood/adolescence and late life. A foreign-born health advantage is also more robust for mortality but less so for morbidity. The HIE is also stronger for more recent immigrants but further research is needed to determine the critical threshold for when migrants' advantage disappears. Positive selection as an explanation for the HIE remains underdeveloped.

CONCLUSIONS

There is an absence of a uniform foreign-born health advantage across different life-course stages and health outcomes in Canada. Nonetheless, it remains the case that the HIE characterizes the majority of contemporary migrants since Canada's foreign-born population consists mostly of core working age adults.

Scoping Review on Maternal Health among Immigrant and Refugee Women in Canada: Prenatal, Intrapartum, and Postnatal Care

The last fifteen years have seen a dramatic increase in both the childbearing age and diversity of women migrating to Canada. The resulting health impact underscores the need to explore access to health services and the related maternal health outcome. This article reports on the results of a scoping review focused on migrant maternal health within the context of accessible and effective health services during pregnancy and following delivery. One hundred and twenty-six articles published between 2000 and 2016 that met our inclusion criteria and related to this group of migrant women, with pregnancy/motherhood status, who were living in Canada, were identified. This review points at complex health outcomes among immigrant and refugee women that occur within the compelling gaps in our knowledge of maternal health during all phases of maternity. Throughout the prenatal, intrapartum, and postnatal periods of maternity, barriers to accessing healthcare services were found to disadvantage immigrant and refugee women putting them at risk for challenging maternal health outcomes. Interactions between the uptake of health information and factors related to the process of immigrant settlement were identified as major barriers. Availability of appropriate services in a country that provides universal healthcare is discussed.

Maternal and neonatal factors related to prematurity

ABSTRACT OBJECTIVE To identify maternal and neonatal factors associated with prematurity in the municipality of Porto Alegre. METHOD This was a population-based case-control study. The cases were newborns under 37 weeks of gestation and the controls were newborns over 37 weeks. The data came from the records of 19,457 births in the city of Porto Alegre in the year 2012 from the Information System on Live Births of the Municipal Health Department. The analysis was carried outand adjusted by a Logistic Regression according to a hierarchical model. The variables studied were allocated into three hierarchy levels: sociodemographic variables; reproductive history; and gestational and birth factors. RESULTS There were 767 cases allocated and 1,534 controls in a design of a case for two controls (1:2) by simple randomization. In the final model, a statistically significant association was found for prematurity for the following variables: mother's age under 19 years old (OR=1.32; CI 95%: 1.02-1.71) or over 34 years old (OR=1.39; CI 95%: 1.12-1.72); inadequate maternal schooling for age (OR=2.11; CI 95%: 1.22-3.65); multiple pregnancies (OR=1.14; CI 95%: 1.01-1.29); C-section (OR=1.15; CI 95%: 1.03-1.29); birth weights under 2,500g (OR=4.04; CI 95%: 3.64-4.49); Apgar score at five minutes between zero and three (OR=1.47; CI 95%: 1.12-1.91); and inadequate prenatal care (OR=1.18; CI 95%: 1.02-1.36). CONCLUSION The present study showed the most immediate consequence of prematurity for newborns by evidencing its association with worse Apgar scores and low birth weight. The following factors were also shown as possible more distal determinants of prematurity: mother's age; inadequate maternal education; multiple gestation; inadequate prenatal care; and C-section.

Preterm birth and social inequality: assessing the effects of material and psychosocial disadvantage in a UK birth cohort

OBJECTIVE

To examine the association between social inequalities and preterm birth, testing both psychosocial and material determinants.

DESIGN

Retrospective cohort study with linked hospital data.

SETTING AND POPULATION

17 285 women in England, Scotland, Northern Ireland and Wales giving birth to singletons included in wave 1 of the UK Millennium Cohort Study.

METHODS

Social inequalities were measured with material (household income, housing tenure) and psychosocial (education, occupational class, employment, social support) indicators. Analysis using multivariable logistic regression assessed odds of preterm birth, adjusting for demographics, health and health-related behaviors, pregnancy and delivery conditions, and pregnancy complications.

MAIN OUTCOME MEASURE

Preterm birth between 24 and 36 weeks, 6 days' gestation.

RESULTS

Initial bivariable analysis suggested associations between preterm birth and household income, housing tenure, and education. These effects were largely explained by adjustment for other social determinants in multivariable models. Following full adjustment, effects of unemployment [OR = 1.52, 95% confidence interval (CI) 1.21-1.90, p < 0.001] and one indicator of poor social support (OR = 1.17, 95% CI 1.01-1.35, p = 0.04) remained significant.

CONCLUSION

Unemployment and lack of social support are associated with higher risk of preterm birth, supporting the hypothesis that poor psychosocial circumstances elevate a woman's risk of this adverse perinatal outcome. Further research is needed to examine the causal pathways through which social inequalities affect preterm birth.

Constructing inverse probability weights for continuous exposures: a comparison of methods

Inverse probability-weighted marginal structural models with binary exposures are common in epidemiology. Constructing inverse probability weights for a continuous exposure can be complicated by the presence of outliers, and the need to identify a parametric form for the exposure and account for nonconstant exposure variance. We explored the performance of various methods to construct inverse probability weights for continuous exposures using Monte Carlo simulation. We generated two continuous exposures and binary outcomes using data sampled from a large empirical cohort. The first exposure followed a normal distribution with homoscedastic variance. The second exposure followed a contaminated Poisson distribution, with heteroscedastic variance equal to the conditional mean. We assessed six methods to construct inverse probability weights using: a normal distribution, a normal distribution with heteroscedastic variance, a truncated normal distribution with heteroscedastic variance, a gamma distribution, a t distribution (1, 3, and 5 degrees of freedom), and a quantile binning approach (based on 10, 15, and 20 exposure categories). We estimated the marginal odds ratio for a single-unit increase in each simulated exposure in a regression model weighted by the inverse probability weights constructed using each approach, and then computed the bias and mean squared error for each method. For the homoscedastic exposure, the standard normal, gamma, and quantile binning approaches performed best. For the heteroscedastic exposure, the quantile binning, gamma, and heteroscedastic normal approaches performed best. Our results suggest that the quantile binning approach is a simple and versatile way to construct inverse probability weights for continuous exposures.

Gestational age-dependent risk factors for preterm birth: associations with maternal education and age early in gestation

OBJECTIVES

Preterm birth (PTB) before 37 weeks can occur over a wide range of gestational ages, but few studies have assessed if associations between risk factors and PTB vary over the duration of gestation. We sought to evaluate if associations between two major risk factors (maternal education and age) and PTB depend on gestational age at delivery.

STUDY DESIGN

We estimated hazard ratios of PTB for education and age in a time-to-event analysis using a retrospective cohort of 223,756 live singleton births from the province of Québec, Canada for the years 2001-2005. Differences in hazards of maternal education and age with PTB were assessed over gestational age in a Cox proportional hazards model using linear and nonlinear time interaction terms, adjusting for maternal characteristics.

RESULTS

Associations of PTB with lower (vs. higher) education and older (vs. younger) age strengthened progressively at earlier gestational ages, such that the risk of PTB for maternal education and age was not constant over the course of gestation.

CONCLUSIONS

Associations of PTB with risk factors such as maternal low education and older age may be stronger early in gestation. Models that capture the time-dependent nature of PTB may be useful when the goal is to assess associations at low gestational ages, and to avoid masked or biased associations early in gestation.