Chronic Disease Risk Factors Among Alaska Native and American Indian People, Alaska, 2004-2006

• Other Authors: Redwood, Diana G., Lanier, Anne P., Johnston, Janet M., Asay, Elvin D., Slattery, Martha L.
• Language: unknown
• Subjects: Original Research; Adult; Aged; Alaska; Cholesterol; HDL; LDL; Chronic Disease; Female; Health Status Disparities; Humans; Hypertension; Indians; North American; Inuits; Lipoproteins; Male; Middle Aged; Nutrition Surveys; Obesity; Prevalence; Risk Factors; Young Adult; Indian; inuits
• Online Access: http://stacks.cdc.gov/view/cdc/20486/

Introduction The Alaska Education and Research Towards Health (EARTH) Study is being conducted to determine the prevalence of clinically measured chronic disease risk factors in a large population of American Indian/Alaska Native people (AI/AN). We report these estimates and compare them with those for the overall US population, as assessed by the National Health and Nutrition Examination Survey (NHANES). Methods We measured blood pressure, height, weight, and fasting serum lipids and glucose in a prospective cohort of 3,822 AI/AN participants who resided in Alaska during 2004 through 2006. We categorized participants as having chronic disease risk factors if their measurements exceeded cutoffs that were determined on the basis of national recommendations. We analyzed the prevalence of risk factors by sex and age and compared the age-adjusted prevalence with 1999-2004 NHANES measurements. Results EARTH participants were significantly more likely than NHANES participants to be overweight or obese and to have impaired fasting glucose, low high-density lipoprotein cholesterol, high low-density lipoprotein cholesterol, and hypertension. The prevalence of high total cholesterol and triglycerides was not significantly different between the 2 study populations. Conclusion We provide baseline clinical measurements for chronic disease risk factors for a larger study sample than any previous study of AI/AN living in Alaska. The prevalence of most risk factors measured exceeded national rates. These data can be used to tailor health interventions and reduce health disparities.