Gestational Diabetes and Breastfeeding Among Women of Different Races/Ethnicities: Evidence from the Pregnancy Risk Assessment Monitoring Surveys

Incorporating machine learning and statistical methods to address maternal healthcare disparities in US: A systematic review

BACKGROUND

Maternal health disparities are recognized as a significant public health challenge, with pronounced disparities evident across racial, socioeconomic, and geographic dimensions. Although healthcare technologies have advanced, these disparities remain primarily unaddressed, indicating that enhanced analytical approaches are needed.

OBJECTIVES

This review aims to evaluate the impact of machine learning (ML) and statistical methods on identifying and addressing maternal health disparities and to outline future research directions for enhancing these methodologies.

METHODS

Following the PRISMA guidelines, the review of studies employing ML and statistical methods to analyze maternal health disparities within the United States was conducted. Publications between January 1, 2012, and February 2024 were systematically searched through PubMed, Web of Science, and ScienceDirect. Inclusion criteria targeted studies conducted within the U.S., peer-reviewed articles published during the period, research covering the postpartum period up to one year post-delivery, and studies incorporating both maternal and infant health data with a focus primarily on maternal outcomes.

RESULTS

A total of 147 studies met the inclusion criteria for this analysis. Among these, 129 (88 %) utilized statistical methods in health sciences to analyze correlations, treatment effects, and public health initiatives, thus providing vital, actionable insights for policy and clinical decisions. Meanwhile, 18 articles (12 %) applied ML techniques to explore complex, nonlinear relationships in data. The findings indicate that while ML and statistical methods offer valuable insights into the factors contributing to health disparities, there are limitations regarding dataset diversity and methodological precision. Most studies concentrate on racial and socioeconomic inequalities, with fewer addressing the geographical aspects of maternal health. This review emphasizes the necessity for broader dataset utilization and methodology improvements to enhance the findings' predictive accuracy and applicability.

CONCLUSIONS

ML and statistical methods show great potential to transform maternal healthcare by identifying and addressing disparities. Future research should focus on broadening dataset diversity, improving methodological precision, and enhancing interdisciplinary efforts.

Impact of Breastfeeding Barriers on Racial/Ethnic Disparities in Breastfeeding Outcomes in North Dakota

OBJECTIVE

Exclusive breastfeeding is recommended for the first 6 months of life, but there are racial/ethnic disparities in meeting this recommendation.

METHODS

2017-2020 North Dakota Pregnancy Risk Assessment Monitoring System (weighted N = 11,754) data were used to examine racial/ethnic differences in the association between self-reported breastfeeding barriers and breastfeeding duration. Breastfeeding duration was self-reported breastfeeding at 2 and 4 months, and number of weeks until breastfeeding cessation. Self-reported breastfeeding barriers were yes/no responses to 13 barriers (e.g., "difficulty latching," "household duties"). Logistic regression estimated odds ratios and 95% confidence intervals to determine if barriers accounted for breastfeeding disparities by race/ethnicity. Cox proportional hazard models estimated hazard ratios for stopping breastfeeding for American Indian and other race/ethnicity individuals, compared to White individuals. Models were adjusted for birthing parents' demographic and medical factors.

RESULTS

Logistic regression results suggest American Indian birthing parents had similar odds for breastfeeding duration (2-month duration: OR 0.94 (95%CI 0.50, 1.77); 4-month duration: OR 1.24 (95%CI 0.43, 3.62)) compared to White birthing parents, after accounting for breastfeeding barriers. Cox proportional hazard models suggest American Indian birthing parents had a lower hazard of stopping breastfeeding (HR 0.76 (95%CI 0.57, 0.99)) than White parents, after accounting for breastfeeding barriers.

CONCLUSIONS

Accounting for breastfeeding barriers eliminated observed disparities in breastfeeding outcomes between American Indian and White birthing parents. Targeted and culturally safe efforts to reduce barriers to breastfeeding are warranted to reduce racial/ethnic disparities in breastfeeding.

Risk of Gestational Diabetes in Women With PCOS Based on Body Mass Index: The Japan Environment and Children's Study

CONTEXT

Women with polycystic ovary syndrome (PCOS), which is the most common endocrine disorder in women of reproductive age, have a potentially increased risk of gestational diabetes mellitus (GDM).

OBJECTIVE

To examine the impact of PCOS on GDM based on maternal body mass index (BMI) using data from a large birth cohort study in Japan.

DESIGN

Prospective observational study using data from the Japan Environment and Children's Study (JECS).

PARTICIPANTS

Singleton pregnancies in the JECS during 2011-2014 were included. Mothers with HbA1c levels of ≥6.5% in the first trimester and history of diabetes mellitus or steroid use during pregnancy were excluded.

MAIN OUTCOME MEASURES

Participants were categorized according to their prepregnancy BMIs: G1 (<18.5 kg/m2), G2 (18.5-19.99 kg/m2), G3 (20.0-22.99 kg/m2), G4 (23.0-24.99 kg/m2), and G5 (≥25.0 kg/m2). The impact of PCOS on early(Ed) and late-onset(Ld) GDM for each group was estimated using a multiple logistic regression model.

RESULTS

We included 92 774 participants, comprising 2012 PCOS(+) cases. GDM occurrence was higher in women with PCOS (P < .001). PCOS had no effect on GDM in G1, G2, and G3. In G4, PCOS increased the risk of Ed GDM (adjusted odds ratio [aOR]: 3.27; 95% confidence interval [CI], 1.29-8.29). In G5, PCOS increased the risk of both Ed (aOR: 2.48; 95% CI, 1.53-4.02) and Ld GDM (aOR: 1.94; 95% CI, 1.23-3.07).

CONCLUSION

The impact of PCOS on GDM occurrence depended on the prepregnancy BMIs, which may facilitate personalized preconception counseling among women with PCOS.

Gestational Diabetes Mellitus-Induced Milk Fat Globule Membrane Protein Changes of Human Mature Milk Based on TMT Proteomic Analysis

Breastfeeding by mothers with gestational diabetes mellitus (GDM) has been shown to reduce maternal insulin demands and diminish the risks of diabetes in infants, leading to improved long-term health outcomes. Milk fat globule membrane (MFGM) proteins play a crucial role in influencing the immunity and cognitive development of infants. Understanding the alterations in MFGM proteins in breastmilk from mothers with GDM is essential for enhancing their self-efficacy and increase breastfeeding rates. The objective of this study is to investigate and compare MFGM proteins in milk from mothers with GDM and without based on tandem mass tag (TMT) labeling and liquid chromatography tandem mass spectrometry (LC-MS) techniques. A total of 5402 proteins were identified, including 4 upregulated proteins and 24 downregulated proteins. These significantly altered proteins were found to be associated with human diseases, cellular processes, and metabolism pathways. Additionally, the oxidative phosphorylation pathway emerged as the predominant pathway through Gene Set Enrichment Analysis (GSEA) involving all genes.

Pumps: A Possible Tool to Promote More Equitable Lactation Outcomes

Pregnant individuals and infants in the US are experiencing rising morbidity and mortality rates. Breastfeeding is a cost-effective intervention associated with a lower risk of health conditions driving dyadic morbidity and mortality, including cardiometabolic disease and sudden infant death. Pregnant individuals and infants from racial/ethnic subgroups facing the highest risk of mortality also have the lowest breastfeeding rates, likely reflective of generational socioeconomic marginalization and its impact on health outcomes. Promoting breastfeeding among groups with the lowest rates could improve the health of dyads with the greatest health risk and facilitate more equitable, person-centered lactation outcomes. Multiple barriers to lactation initiation and duration exist for families who have been socioeconomically marginalized by health and public systems. These include the lack of paid parental leave, increased access to subsidized human milk substitutes, and reduced access to professional and lay breastfeeding expertise. Breast pumps have the potential to mitigate these barriers, making breastfeeding more accessible to all interested dyads. In 2012, The Patient Protection and Affordable Care Act (ACA) greatly expanded access to pumps through the preventative services mandate, with a single pump now available to most US families. Despite their near ubiquitous use among lactating individuals, little research has been conducted on how and when to use pumps appropriately to optimize breastfeeding outcomes. There is a timely and critical need for policy, scholarship, and education around pump use given their widespread provision and potential to promote equity for those families facing the greatest barriers to achieving their personal breastfeeding goals.