Objectives

To examine the relationships between pre-pregnancy diabetes mellitus (DM), gestational diabetes mellitus (GDM), pre-pregnancy body mass index (BMI) and county-level social determinants of health, with infant macrosomia within a sample of American Indian/Alaska Native (AI/AN) women receiving Indian Health Service (IHS) care.

Methods

The sample included women-infant dyads representing 1,136 singleton births from fiscal year 2011 (10/1/2019-9/30/2011). Data stemmed from the IHS Improving Health Care Delivery Data Project. Multivariate generalized linear mixed models were fitted to assess the association of macrosomia with pre-pregnancy health status and social determinants of health.

Results

Nearly half of the women in the sample were under age 25 years (48.6%), and most had Medicaid health insurance coverage (76.7%). Of those with a pre-pregnancy BMI measure, 66.2% were overweight or obese. Although few women had pre-pregnancy DM (4.0%), GDM was present in 12.8% of women. Most women had a normal term delivery (85.4%). Overweight, obesity, pre-pregnancy DM, and county-level rurality were all significantly associated with higher odds of infant macrosomia.

Objective

To explore the prevalence of obesity among American Indian and Alaska Native (AIAN) adolescents aged 12-19 years in association with social determinants of health (SDOH), and mental health and substance use disorders.

Methods

Guided by the World Health Organization's Social Determinants of Health Framework, we examined data from the Indian Health Service (IHS) Improving Health Care Delivery Data Project from Fiscal Year 2013, supplemented by county-level data from the U.S. Census and USDA. Our sample included 26,226 AIAN adolescents ages 12-19 years. We described obesity prevalence in relationship to SDOH and adolescents' mental health and substance use disorder status. We then fit a multivariable logit generalized linear mixed model to estimate the relationships after adjusting for other individual and county level characteristics.

Results

We observed a prevalence of 32.5% for obesity, 13.8% for mental health disorders, and 5.5% for substance use disorders. Females had lower odds of obesity than males (OR = 0.76, p < 0.001), which decreased with age. Having Medicaid coverage (OR = 1.09, p < 0.01), residing in a county with lower education attainment (OR = 1.17, p < 0.05), and residing in a county with higher rates of poverty (OR = 1.51, p < 0.001) were each associated with higher odds of obesity. Residing in a county with high access to a grocery store (OR = 0.73, p < 0.001) and residing in a county with a higher proportion of AIANs (OR = 0.83, p < 0.01) were each associated with lower odds of obesity. Those with mental health disorders had higher odds of obesity (OR = 1.26, p < 0.001); substance use disorders were associated with decreased odds of obesity (OR = 0.73, p < 0.001).

Conclusions

Our findings inform future obesity prevention and treatment programs among AIAN youth; in particular, the need to consider mental health, substance use, and SDOH.

Objective

American Indian and Alaska Native peoples (AI/ANs) have a disproportionately high rate of obesity, but little is known about the social determinants of obesity among older AI/ANs. Thus, our study assessed social determinants of obesity in AI/ANs aged ≥ 50 years.

Design

We conducted a cross-sectional analysis using multivariate generalized linear mixed models to identify social determinants associated with the risk of being classified as obese (BMI ≥ 30.0 kg/m2). Analyses were conducted for the total study population and stratified by median county poverty level.

Setting

Indian Health Service (IHS) data for AI/ANs who used IHS services in FY2013.

Participants

27,696 AI/ANs aged ≥ 50 years without diabetes.

Results

Mean BMI was 29.8 ± 6.6 with 43% classified as obese. Women were more likely to be obese than men, and younger ages were associated with higher obesity risk. While having Medicaid coverage was associated with lower odds of obesity, private health insurance was associated with higher odds. Living in areas with lower rates of educational attainment and longer drive times to primary care services were associated with higher odds of obesity. Those who lived in a county where a larger percentage of people had low access to a grocery store were significantly less likely to be obese.

Conclusions

Our findings contribute to the understanding of social determinants of obesity among older AI/ANs and highlight the need to investigate AI/AN obesity, including longitudinal studies with a life course perspective to further examine social determinants of obesity in older AI/ANs.

Objective: To examine the associations between social determinants of health (SDOH) and prevalent overweight/obesity status and change in adiposity status among American Indian and Alaska Native (AI/AN) children. Methods: The study sample includes 23,950 AI/AN children 2-11 years of age, who used Indian Health Service (IHS) from 2010 to 2014. Multivariate generalized linear mixed models were used to examine the following: (1) cross-sectional associations between SDOH and prevalent overweight/obesity status and (2) longitudinal associations between SDOH and change in adiposity status over time. Results: Approximately 49% of children had prevalent overweight/obesity status; 18% had overweight status and 31% had obesity status. Prevalent severe obesity status was 20% in 6-11-year olds. In adjusted cross-sectional models, children living in counties with higher levels of poverty had 28% higher odds of prevalent overweight/obesity status. In adjusted longitudinal models, children 2-5 years old living in counties with more children eligible for free or reduced-priced lunch had 15% lower odds for transitioning from normal-weight status to overweight/obesity status. Conclusions: This work contributes to accumulating knowledge that economic instability, especially poverty, appears to play a large role in overweight/obesity status in AI/AN children. Research, clinical practice, and policy decisions should aim to address and eliminate economic instability in childhood.

Multilevel interventions (MLIs) are appropriate to reduce health disparities among Indigenous peoples because of their ability to address these communities' diverse histories, dynamics, cultures, politics, and environments. Intervention science has highlighted the importance of context-sensitive MLIs in Indigenous communities that can prioritize Indigenous and local knowledge systems and emphasize the collective versus the individual. This paradigm shift away from individual-level focus interventions to community-level focus interventions underscores the need for community engagement and diverse partnerships in MLI design, implementation, and evaluation. In this paper, we discuss three case studies addressing how Indigenous partners collaborated with researchers in each stage of the design, implementation, and evaluation of MLIs to reduce health disparities impacting their communities. We highlight the following: (1) collaborations with multiple, diverse tribal partners to carry out MLIs which require iterative, consistent conversations over time; (2) inclusion of qualitative and Indigenous research methods in MLIs as a way to honor Indigenous and local knowledge systems as well as a way to understand a health disparity phenomenon in a community; and (3) relationship building, maintenance, and mutual respect among MLI partners to reconcile past research abuses, prevent extractive research practices, decolonize research processes, and generate co-created knowledge between Indigenous and academic communities.