Exploring Food Insecurity as a Social Determinant of Health Among American Indian and Alaska Native Adolescents at Risk for Gestational Diabetes

项目总结/摘要 美国印第安人和阿拉斯加原住民（AI/AN）女性患妊娠糖尿病的可能性是女性的两倍 (GDM)以及随后诊断为2型糖尿病的非西班牙裔白色女性。GDM和肥胖可以 对母婴造成严重的围产期并发症。通过健康饮食管理体重 和体力活动是降低GDM风险的关键因素。然而，健康饮食存在障碍 在许多AI/AN社区中。粮食不安全，定义为缺乏持续获得足够食物的机会， 积极、健康的生活，是不必要的体重增加的危险因素。生活在粮食无保障的家庭， 孕前和怀孕可能会增加体重增加和围产期并发症的风险， 母亲和婴儿。我们的团队最近开发并进行了一项随机对照试验， 创新的GDM风险降低和孕前咨询计划，为AI/AN青春期女孩谁是在 GDM风险高。这个部落支持的，在线的，理论和证据为基础的计划，题为停止GDM， 重点关注健康的GDM风险降低行为，如体重管理，通过健康饮食， 身体活动，怀孕前。我们从这项工作中得出的形成性发现表明，AI/AN女性认为， 粮食不安全是孕前和孕期健康饮食的主要障碍。然而，目前， 制止GDM并没有将粮食不安全作为一个重点内容领域。在此提出的 项目，我们将采用混合方法的研究设计，以审查粮食不安全与 通过二次分析，AI/AN青春期女孩（n=149）的健康饮食自我效能和行为 现有的Stopping GDM数据集。我们假设生活在粮食不安全环境中的AI/AN青春期女孩 家庭对健康饮食的自我效能感和健康饮食行为较差，两者都是 与GDM风险增加有关。在此二次定量数据分析之后，我们将使用定性 通过个别访谈方法进行调查，以使主要利益攸关方协助口译， 这些发现的影响。通过电话会议或电话面试，我们将招募AI/AN 青春期女孩的母亲，AI/AN青春期女孩，和AI/AN女性从停止GDM的历史， 在两个合作的AI/AN社区（Akwesasne的Saint Regis Mohawk，NY和一个多部落社区）进行的GDM试验 波特兰市中心）。此外，我们还将在全国范围内招募AI/AN食品等领域的专家。 不安全，传统的AI/AN食物，传统的AI/AN食物获取习惯，以及 为人工智能/人工智能女孩提供服务，如注册营养师。使用这种定性的方法，我们将重新引入的声音， AI/AN社区成员告知适应停止GDM以有效解决食物问题的下一步措施 通过创新的多系统方法，消除不安全感作为GDM健康差距的一个因素。这项工作 对于打破AI/AN社区糖尿病的代际循环至关重要， 怀孕前期

PROJECT SUMMARY / ABSTRACT American Indian and Alaska Native (AI/AN) women are twice as likely to have gestational diabetes mellitus (GDM) and subsequent diagnosis of type 2 diabetes as non-Hispanic White females. GDM and obesity can cause severe perinatal complications for both mother and baby. Weight management through healthy diet and physical activity are key factors in decreasing risk for GDM. However, there are barriers to healthful eating in many AI/AN communities. Food insecurity, defined as the lack of consistent access to enough food for an active, healthy life, is a risk factor for unwanted weight gain. Living in a food insecure household during preconception and pregnancy may increase risk of greater weight gain and perinatal complications for both mother and baby. Our team recently developed and conducted a randomized controlled trial evaluation of an innovative GDM risk reduction and preconception counseling program for AI/AN adolescent girls who are at high risk for GDM. This tribally-supported, online, theory-and evidence-based program, entitled Stopping GDM, focuses on healthy GDM risk reduction behaviors, such as weight management, through healthy eating and physical activity, prior to pregnancy. Our formative findings from this work suggest that AI/AN women view food insecurity as a key barrier to healthful eating, both before and during pregnancy. Currently, however, Stopping GDM does not specifically address food insecurity as a content area of focus. In this proposed project, we will employ a mixed-methods study design to examine the relationship between food insecurity with healthy eating self-efficacy and behaviors among AI/AN adolescent girls (n=149) through secondary analysis of the existing Stopping GDM dataset. We hypothesize that AI/AN adolescent girls who live in food insecure households will have poorer self-efficacy for healthy eating and poorer healthy eating behaviors, both of which are related to increased risk of GDM. After this secondary quantitative data analysis, we will use qualitative inquiry through individual interview methods to engage key stakeholders to assist with the interpretation and implications of these findings. Through teleconference or phone-based interviews, we will recruit AI/AN mothers of adolescent girls, AI/AN adolescent girls, and AI/AN women with a history of GDM from the Stopping GDM trial in two collaborating AI/AN communities (Saint Regis Mohawk of Akwesasne, NY and a multi-tribal urban center in Portland, OR). Additionally, we will recruit nationwide experts on topics such as: AI/AN food insecurity, traditional AI/AN foods, traditional AI/AN food acquisition habits, and health care providers who serve AI/AN girls such as registered dietitians. Using this qualitative method we will reintroduce the voice of AI/AN community members to inform next steps in the adaptation of Stopping GDM to effectively address food insecurity as a contributor to GDM health disparities through innovative, multi-systems approaches. This work is critical to break the intergenerational cycle of diabetes in AI/AN communities, starting during the preconception period.