Search

Objectives: To examine food insecurity and cardiovascular disease-related health outcomes among American Indians (AIs) in rural Oklahoma., Methods: We surveyed a cross-sectional sample of 513 AI adults to assess food insecurity domains (i.e., food quality and quantity) and obesity, diabetes, and hypertension., Results: Among AIs surveyed, 56% reported inadequate food quantity and 62% reported inadequate food quality. The unadjusted prevalence of diabetes (28.4% vs 18.4%), obesity (60.0% vs 48.3%), and hypertension (54.1% vs 41.6%) was higher among participants with inadequate food quantity than among those with adequate food quantity. These associations did not reach statistical significance after adjustment for age, gender, study site, education, and income. The unadjusted prevalence of obesity (60.7% vs 45.8%), diabetes (27.3% vs 18.8%), and hypertension (52.5% vs 42.5%) was higher among those with inadequate food quality than among those with adequate food quality, even after adjustment for age, gender, study site, education, and income., Conclusions: Tribal, federal, and state policymakers, as well as businesses and nonprofit organizations, must collaboratively take aggressive action to address food insecurity and its underlying causes, including improving tribal food environments, reducing barriers to healthy foods, and increasing living wages.

Public health policy relies on accurate data, which are often unavailable for small populations, especially indigenous groups. Yet these groups have some of the worst health disparities in the United States, making it an ethical imperative to explore creative solutions to the problem of insufficient data. We discuss the limits of widely applied methods of data aggregation and propose a mixed-methods approach to data borrowing as a way to augment sample sizes. In this approach, community partners assist in selecting related populations that make suitable "neighbors" to enlarge the data pool. The result will be data that are substantial, accurate, and relevant to the needs of small populations, especially for health-related policy and decision-making at all levels.

We conducted a systematic review of published studies on stroke epidemiology in American Indians and Alaska Natives (AI/ANs). We used MeSH terms and strict inclusion criteria to search PubMed, identifying a relevant sample of 57 refereed publications. We report a consensus view in which prevalent stroke is more common, and estimates of cerebrovascular risk factors are higher, among AI/ANs than among other US populations. Like other minority groups, AI/ANs suffer stroke at younger ages than do non-Hispanic Whites. However, data on AI/AN stroke mortality are significantly compromised by racial misclassification and nonrepresentative sampling. Studies correcting for these problems have found that stroke mortality rates among AI/ANs are among the highest of all US racial and ethnic groups. As with Black and non-Hispanic White stroke mortality, AI/AN stroke mortality varies by geographic region, with the highest rates in Alaska and the Northwest and the lowest in the Southwest. Our results underscore the need for a concerted national effort to collect accurate cross-sectional and longitudinal data on stroke in AI/ANs.