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  5. Identifying systemic inequities in maternal and child health among the American Indian and Alaska Native population

Identifying systemic inequities in maternal and child health among the American Indian and Alaska Native population

Project profile

Institution: Regents of the University of California, San Francisco
Principal Investigator: Martha Decker
Project Number: R42MC49148
Project Date: 07-01-2023

Age Group(s)

  • Women/Maternal
  • Prenatal
  • Perinatal/Infancy (0-12 months)
  • Adolescence (12-18 years)
  • Young Adulthood (19-25 years)

Targeted/Underserved Population

  • Native American/Alaskan Native

Abstract

While the impact of systemic inequities and racism on health has gained recent attention few studies have focused on these issues among the American Indian and Alaska Native (AI/AN) population. The AI/AN population experiences substantial disparities in access to health services and in maternal and child health (MCH) outcomes compared to the general U.S. population. Persistent disparities in social determinants of health are also reported for AI/AN populations however examinations of the relationship between these factors and MCH outcomes are limited. Moreover AI/AN health statistics consistently are omitted from public health surveillance data and reports or collapsed into an 'Other' racial category a practice called 'data genocide' by researchers raising awareness about this ongoing issue. Our proposed study aligns with the Maternal and Child Health Bureau's principles of incorporating health equity and a holistic view of health and improving the quality/accessibility of services for underserved populations. Structural and social determinants of health are strongly influenced by centuries of colonialism racism and unhealed intergenerational trauma and are key drivers of inequitable health outcomes for AI/AN people. Our study will advance health equity by using a lens that considers historical context and incorporates structural/societal-level inequities to fill a gap in needed information to advance health care programs and policies for the AI/AN population. DATA SET AND TARGET POPULATION: The National Survey of Family Growth (NSFG) supplies key MCH statistics by race/ethnicity but suppresses AI/AN data in public datasets and reports. Our study will complete secondary analyses of NSFG 2011-2019 data (N=38 669) to: 1) Examine access to/ use of MCH services family planning intentions sexual violence and maternal and infant health outcomes among the AI/AN sample compared to the general population; 2) Examine indicators of systemic inequities among NSFG AI/ AN respondents compared to the general population including housing and food insecurity school discipline and exposure to foster care; and 3) Explore associations between our MCH outcomes and indicators of systemic inequities among NSFG AI/AN respondents compared to the general population. GOALS: Our overarching goal is to improve the health and well-being of AI/AN populations. Specifically our study goals are to: 1) Promote utilization of public health data to address MCH inequities among AI/AN populations and an emerging research focus on systemic factors; 2) Consult an AI/AN Advisory Group to guide the research; 3) Support AI/AN mentees to focus on and advance in MCH research; and 4) Expand the evidence-base on the relationship between MCH outcomes and systemic inequities among AI/AN populations.

Products:

We will pursue our fourth goal through submission of at least three manuscripts to peer-reviewed journals; preparation of issue/policy briefs; and presentation of study findings at national conferences and other relevant settings.

Evaluation:

UCSF is committed to conducting a performance evaluation to ensure achievement of the study's goals. Prior to award UCSF will pursue access to the data and is prepared to develop the analysis files immediately post-award. The partnership between the University of California San Francisco and Native scholars helps ensure our research represents AI/AN values; accounts for the context of AI/AN communities; and minimizes potential harmful effects for AI/AN communities. Our Research Advisory Group including AI/AN experts in MCH clinical services policy tribal law and public health research will support data interpretation and promote the impact and utilization of study results.