Recent studies using 2016–2017 National Health Interview Survey data reported that the prevalence of type 1 diabetes (T1D) and type 2 diabetes (T2D) in U.S. adults was 0.5% and 8.5%, respectively (1). However, little is known about the prevalence of diabetes subtypes among American Indian and Alaska Native (AI/AN) peoples. The SEARCH for Diabetes in Youth (SEARCH) study investigators examined the prevalence of T1D versus T2D among youth in various racial/ethnic groups (2), but AI/AN participants of these studies were primarily Indian Health Service (IHS) users in Arizona and New Mexico, which may not be representative of all IHS users across the country.
We extracted data from the IHS Improving Health Care Delivery Data Project data set, which represents nearly 30% of AI/AN individuals who use IHS services. The study population included AI/AN individuals with diabetes who lived in 1 of 15 locations throughout the nation and were IHS active users in October 2012–September 2013. Diabetes was identified by one inpatient diagnosis or two of the following events occurring within 24 months: 1) HbA1c ≥6.5%; 2) an outpatient diagnosis; and 3) antidiabetes medication use (3).
Patients were categorized as having T1D if they used insulin as their only antidiabetes prescription and received 1) more than five T1D-related codes; 2) two to five T1D-related codes, and ≥50% of the diabetes-related codes were for T1D; and 3) one T1D-related code and no T2D-related code. Patients were also categorized as having T1D if they used both insulin and oral antidiabetes medication and received more than five T1D-related codes and if ≥50% of diabetes-related codes were for T1D. Patients were classified as having T2D if they received 1) three or more T2D-related codes, and ≥50% of diabetes-related codes were for T2D; 2) two T2D-related codes and no T1D-related codes; and 3) one T2D-related code, no T1D codes, and no insulin use. The prevalence of both T1D and T2D was calculated and reported for the overall study population as well as for subpopulations stratified by demographic characteristics and geographic locations.
A total of 55,049 AI/AN individuals were identified as T1D or T2D patients in 2012–2013, which is 11.51% of the total population. Among them, 1.32% were classified as T1D patients, and 98.06% were T2D patients (Table 1). Among adults, T1D and T2D prevalence was 0.18% and 16.53%, respectively. T1D prevalence was about 1.5 times that of T2D (0.03% vs. 0.02%) among children under 10 years old. Starting from age 10, the prevalence of T2D surpassed that of T1D. T1D prevalence reached its peak in individuals who were 20–29 years old, while T2D prevalence reached its peak in the 70- to 74-year-old age-group. Consistent with the SEARCH study (2), T1D was found to be rare among AI/AN individuals, even among AI/AN youth. Conversely, T2D prevalence among AI/AN youth aged 10–19 years was 0.42% (95% CI 0.38–0.46) in 2012–2013, higher than that in most other U.S. racial/ethnic groups at that age (e.g., prevalence for White individuals was 0.02% [95% CI 0.017–0.023] in 2017) (2). These findings suggest that, in addition to the well-known disparities of T2D prevalence suffered by adult AI/AN individuals, young AI/AN individuals also experience disparities in T2D prevalence.
Prevalence of diagnosed diabetes among AI/AN peoples by diabetes subtype and demographic subgroups, 2012–2013
| Characteristic . | No. of patients with diabetesa . | Total population . | Prevalence of Diabetes Subtype, % (95% CI) . | ||
|---|---|---|---|---|---|
| T1D . | T2D . | All subtypesa . | |||
| Overall N | 55,049 | 478,212b | 727 | 53,982 | 55,049 |
| Overall % | 0.15 (0.14, 0.16) | 11.29 (11.20, 11.38) | 11.51 (11.42, 11.60) | ||
| Age (years) | |||||
| Youth (<18) | 399 | 152,998 | 0.08 (0.07, 0.10) | 0.15 (0.13, 0.17) | 0.26 (0.24, 0.29) |
| Adults (≥18) | 54,650 | 325,214 | 0.18 (0.17, 0.20) | 16.53 (16.40, 16.66) | 16.80 (16.68, 16.93) |
| <10 | 55 | 87,544 | 0.03 (0.02, 0.04) | 0.02 (0.01, 0.02) | 0.06 (0.05, 0.08) |
| 10–19 | 536 | 82,870 | 0.18 (0.15, 0.21) | 0.42 (0.38, 0.46) | 0.65 (0.59, 0.70) |
| 20–29 | 2,267 | 89,444 | 0.20 (0.17, 0.23) | 2.25 (2.16, 2.35) | 2.54 (2.43, 2.64) |
| 30–49 | 17,674 | 120,972 | 0.20 (0.18, 0.23) | 14.29 (14.10, 14.49) | 14.61 (14.41, 14.81) |
| 50–69 | 25,745 | 76,819 | 0.14 (0.11, 0.17) | 33.29 (32.95, 33.62) | 33.51 (33.18, 33.85) |
| 70–74 | 3,858 | 8,548 | 0.07 (0.01, 0.13) | 44.96 (43.90, 46.01) | 45.13 (44.08, 46.19) |
| ≥75 | 4,914 | 12,015 | 0.05 (0.01, 0.09) | 40.80 (39.92, 41.68) | 40.90 (40.02, 41.78) |
| Sex | |||||
| Female | 30,202 | 251,713 | 0.12 (0.11, 0.14) | 11.80 (11.68, 11.93) | 12.00 (11.87, 12.13) |
| Male | 24,847 | 226,499 | 0.18 (0.17, 0.20) | 10.72 (10.59, 10.85) | 10.97 (10.84, 11.10) |
| Female youth | 218 | 75,364 | 0.08 (0.06, 0.10) | 0.18 (0.15, 0.21) | 0.29 (0.25, 0.33) |
| Male youth | 181 | 77,634 | 0.09 (0.07, 0.11) | 0.12 (0.10, 0.15) | 0.23 (0.20, 0.27) |
| Female adults | 29,984 | 176,349 | 0.14 (0.12, 0.16) | 16.77 (16.59, 16.94) | 17.00 (16.83, 17.18) |
| Male adults | 24,666 | 148,865 | 0.23 (0.21, 0.26) | 16.24 (16.06, 16.43) | 16.57 (16.38, 16.76) |
| Regionc | |||||
| Alaska | 2,732 | 61,874 | 0.13 (0.10, 0.15) | 4.26 (4.10, 4.41) | 4.42 (4.25, 4.58) |
| East | 2,061 | 10,879 | 0.12 (0.05, 0.18) | 18.71 (17.97, 19.44) | 18.95 (18.21, 19.68) |
| Northern Plains | 6,079 | 52,462 | 0.13 (0.10, 0.16) | 11.33 (11.06, 11.60) | 11.59 (11.31, 11.86) |
| Pacific Coast | 1,771 | 17,734 | 0.16 (0.10, 0.22) | 9.78 (9.35, 10.22) | 9.99 (9.55, 10.43) |
| Southern Plains | 19,327 | 162,182 | 0.26 (0.23, 0.28) | 11.60 (11.44, 11.76) | 11.92 (11.76, 12.08) |
| Southwest | 20,824 | 152,728 | 0.06 (0.04, 0.07) | 13.50 (13.32, 13.68) | 13.64 (13.46, 13.81) |
| Characteristic . | No. of patients with diabetesa . | Total population . | Prevalence of Diabetes Subtype, % (95% CI) . | ||
|---|---|---|---|---|---|
| T1D . | T2D . | All subtypesa . | |||
| Overall N | 55,049 | 478,212b | 727 | 53,982 | 55,049 |
| Overall % | 0.15 (0.14, 0.16) | 11.29 (11.20, 11.38) | 11.51 (11.42, 11.60) | ||
| Age (years) | |||||
| Youth (<18) | 399 | 152,998 | 0.08 (0.07, 0.10) | 0.15 (0.13, 0.17) | 0.26 (0.24, 0.29) |
| Adults (≥18) | 54,650 | 325,214 | 0.18 (0.17, 0.20) | 16.53 (16.40, 16.66) | 16.80 (16.68, 16.93) |
| <10 | 55 | 87,544 | 0.03 (0.02, 0.04) | 0.02 (0.01, 0.02) | 0.06 (0.05, 0.08) |
| 10–19 | 536 | 82,870 | 0.18 (0.15, 0.21) | 0.42 (0.38, 0.46) | 0.65 (0.59, 0.70) |
| 20–29 | 2,267 | 89,444 | 0.20 (0.17, 0.23) | 2.25 (2.16, 2.35) | 2.54 (2.43, 2.64) |
| 30–49 | 17,674 | 120,972 | 0.20 (0.18, 0.23) | 14.29 (14.10, 14.49) | 14.61 (14.41, 14.81) |
| 50–69 | 25,745 | 76,819 | 0.14 (0.11, 0.17) | 33.29 (32.95, 33.62) | 33.51 (33.18, 33.85) |
| 70–74 | 3,858 | 8,548 | 0.07 (0.01, 0.13) | 44.96 (43.90, 46.01) | 45.13 (44.08, 46.19) |
| ≥75 | 4,914 | 12,015 | 0.05 (0.01, 0.09) | 40.80 (39.92, 41.68) | 40.90 (40.02, 41.78) |
| Sex | |||||
| Female | 30,202 | 251,713 | 0.12 (0.11, 0.14) | 11.80 (11.68, 11.93) | 12.00 (11.87, 12.13) |
| Male | 24,847 | 226,499 | 0.18 (0.17, 0.20) | 10.72 (10.59, 10.85) | 10.97 (10.84, 11.10) |
| Female youth | 218 | 75,364 | 0.08 (0.06, 0.10) | 0.18 (0.15, 0.21) | 0.29 (0.25, 0.33) |
| Male youth | 181 | 77,634 | 0.09 (0.07, 0.11) | 0.12 (0.10, 0.15) | 0.23 (0.20, 0.27) |
| Female adults | 29,984 | 176,349 | 0.14 (0.12, 0.16) | 16.77 (16.59, 16.94) | 17.00 (16.83, 17.18) |
| Male adults | 24,666 | 148,865 | 0.23 (0.21, 0.26) | 16.24 (16.06, 16.43) | 16.57 (16.38, 16.76) |
| Regionc | |||||
| Alaska | 2,732 | 61,874 | 0.13 (0.10, 0.15) | 4.26 (4.10, 4.41) | 4.42 (4.25, 4.58) |
| East | 2,061 | 10,879 | 0.12 (0.05, 0.18) | 18.71 (17.97, 19.44) | 18.95 (18.21, 19.68) |
| Northern Plains | 6,079 | 52,462 | 0.13 (0.10, 0.16) | 11.33 (11.06, 11.60) | 11.59 (11.31, 11.86) |
| Pacific Coast | 1,771 | 17,734 | 0.16 (0.10, 0.22) | 9.78 (9.35, 10.22) | 9.99 (9.55, 10.43) |
| Southern Plains | 19,327 | 162,182 | 0.26 (0.23, 0.28) | 11.60 (11.44, 11.76) | 11.92 (11.76, 12.08) |
| Southwest | 20,824 | 152,728 | 0.06 (0.04, 0.07) | 13.50 (13.32, 13.68) | 13.64 (13.46, 13.81) |
Numbers of patients with diabetes include numbers of patients with T1D, T2D, and unknown subtypes. Patients with at least one T1D or T2D diagnostic code but who do not belong to any of the scenarios for T1D or T2D were classified as having an unknown type of diabetes (N = 340).
Total population for the overall prevalence was the number of AI/AN individuals who lived in 1 of the 15 project sites and were IHS active users between 1 October 2012 and 30 September 2013 (fiscal year 2013). The IHS definition of an active user during a fiscal year is a person who used services at least once during the specified fiscal year or the preceding two fiscal years.
The six IHS regions are defined as the following: Alaska: Alaska; East: Alabama, Arkansas, Connecticut, Delaware, Florida, Georgia, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Mississippi, Missouri, New Hampshire, New Jersey, New York, North Carolina, Ohio, Pennsylvania, Rhode Island, South Carolina, Tennessee, Vermont, Virginia, Washington, DC, and West Virginia; Northern Plains: Illinois, Indiana, Iowa, Michigan, Minnesota, Montana, Nebraska, North Dakota, South Dakota, Wisconsin, and Wyoming; Pacific Coast: California, Hawaii, Idaho, Oregon, and Washington; Southern Plains: Kansas, Oklahoma, and Texas; and Southwest: Arizona, Colorado, Nevada, New Mexico, and Utah.
There were large regional variations in T1D and T2D prevalence across IHS regions (Table 1). The Southern Plains had the highest T1D prevalence (0.26% [95% CI 0.23–0.28]), while the Southwest region had the lowest T1D prevalence (0.06% [95% CI 0.04–0.07]). Meanwhile, the East region had the highest T2D prevalence (18.71% [95% CI 17.91–19.44]), and the Alaska region had the lowest T2D prevalence (4.26% [95% CI 4.10–4.41]). Based on a recent publication using national IHS data (4), among AI/AN adults, the Southwest had the highest diabetes prevalence followed by the East region, while the Alaska region had the lowest prevalence. Those findings are consistent with our findings.
Our study has several limitations. We do not have access to data more recent than 2012–2013 or to data that would allow us to validate the accuracy of the algorithm we used to distinguish T1D and T2D. Additionally, only around 30% of the IHS users were included in our sample. Thus, our findings may not be generalizable to the IHS users in nonincluded sites and AI/AN individuals who were not IHS users.
Our study is the first to estimate the prevalence of diabetes subtypes among AI/AN individuals of all ages. We found that AI/AN individuals had markedly higher prevalence of T2D, but not T1D, than the U.S. general population across all ages beginning at 10 years. These findings highlight the necessity of enhancing existing diabetes prevention interventions that address the population-level environmental conditions and individual health risks underlying the exacerbation of the diabetes epidemic among AI/AN individuals and many other underserved communities across the life span, such as addressing risk factors in early life (5).
Data Availability
The data from the IHS Improving Health Care Delivery Data Project used to support the findings of this study have not been made available because of IHS and tribal regulations regarding data confidentiality and security.
Retired
Article Information
Acknowledgments. The data used in this secondary analysis are from the IHS Health Care Delivery Data Project. The data set includes information for many AI/AN communities. This work was conducted with the guidance and advice of IHS and tribal health program colleagues as well as members of the project’s steering, project site, and patient committees. Members of tribal and IHS National institutional review boards, tribal councils, and tribal authorities educate us about the health concerns they have for their tribal members and how they hope this project will inform their work. This project relies on their support and approval.
The findings and conclusions in this article are those of the authors and do not necessarily represent the official position of the IHS or the funding agencies.
Funding. This study was supported by the National Institute on Aging (R01AG061189), National Institute of Diabetes and Digestive and Kidney Diseases (P30DK092923), and National Institute on Minority Health and Health Disparities (U54MD000507). Funding for the development of the data infrastructure was supported by the Patient-Centered Outcomes Research Institute (AD-1304-6451) and Agency for Healthcare Research and Quality (290-2006-00020-I).
Duality of Interest. No potential conflicts of interest relevant to this article were reported.
Author Contributions. J.D. and X.N. researched the data, contributed to the discussion, and wrote the manuscript. A.B., S.M.M., and J.O. contributed to the discussion and reviewed and edited the manuscript. L.J. designed the study, contributed to the discussion, and reviewed and edited the manuscript. L.J. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Prior Presentation. Parts of this study were presented in abstract form at the American Public Health Association Annual Meeting and Expo, Atlanta, GA, 12 November 2023.
