OBJECTIVE—To compare by region risk factors for cardiovascular disease among American Indian populations with diabetes.

RESEARCH DESIGN AND METHODS—Trained providers from 185 federal, urban, and tribally operated facilities reviewed the records from systematic random samples of the patients included in the local diabetes registries in the 1998 Indian Health Service (IHS) Diabetes Care and Outcomes Audit. Selected measures of cardiovascular risk were aggregated by region and adjusted to calculate regional rates for patients <45 years of age (n = 2,595) and those aged ≥45 years (n = 8,294).

RESULTS—Among the younger group of patients with diabetes, the rates of elevated HbA1c (≥9%) and tobacco use varied significantly among regions. High rates of obesity (78%) and elevated HbA1c (56%) were found in the Southwest. High rates of tobacco use (55%) but the lowest rates of elevated HbA1c (27%) were found in Alaska. Among patients aged ≥45 years, all measures including rates of proteinuria, cholesterol ≥200 mg/dl, and mean blood pressure ≥130/85 varied significantly among all regions. Tobacco use was highest in the Great Lakes (44%) and Great Plains (42%) regions and lowest in the Southwest (14%) and Colorado Plateau (8%) regions. Proteinuria was found most frequently in the Southwest (35%), Colorado Plateau (30%), and Pacific regions (35%). Older individuals with diabetes were more likely than younger individuals to have proteinuria and blood pressure ≥130/85.

CONCLUSIONS—American Indians and Alaska Natives with diabetes carry a large burden of potentially modifiable cardiovascular risk factors, but there is significant regional variation.

Cardiovascular disease (CVD) is now the leading cause of death in American Indians and Alaska Natives (1). According to the Strong Heart Study (SHS) of CVD in Indians in Arizona, Oklahoma, and North and South Dakota, the high and rising mortality rate of CVD has been closely associated with the recent epidemic of diabetes in the native communities (2). The study found diabetes to be the strongest CVD risk factor among individuals aged 45–74 years (3,4). Of all the incident cases of CVD over a mean of 4.2 years of follow-up, 56% of the events occurred in men with diabetes and 78% in women with diabetes (2). The study also described significant regional variations in the rates of CVD and individual risk factors (3,4).

Other studies of CVD risk factors among selected tribes in the southwest and in the northern and central U.S. also have described multiple CVD risk factors, such as obesity and diabetes, in American Indians as well as marked regional variations in smoking rates (5,6). In Montana, Indian adults reported a history of CVD on a telephone survey twice as frequently as non-Indians from the same state (7). Although CVD was reported infrequently by respondents <45 years of age in the survey, younger Indians reported much higher rates of obesity, smoking, and diabetes than similarly aged non-Indians. Because the SHS did not include individuals <45 years of age, risk factor data for this age group is limited.

Among the Pima Indians in Arizona, CVD has replaced kidney disease as the leading cause of death in people with diabetes in the most recent years of an ongoing epidemiological study (8). In addition, greater degrees of hyperglycemia were associated with increasing CVD mortality in individuals with diabetes (9). Thus, to control the increasing cardiovascular morbidity and mortality in Indian communities, it is particularly important to address the risk factors for heart disease in individuals with diabetes. This report describes selected CVD risk factors among American Indians with diabetes collected by the Indian Health Service (IHS) Diabetes Care and Outcomes Audit of 1998 and compares the risk profiles with similar data published for people with diabetes in the general population.

The IHS, an agency of the U.S. Public Health Service, acting through a network of federal, tribal, and urban facilities, has developed and maintained a long-standing clinical and public health focus on diabetes. In 1986, the IHS first formulated standards for diabetes care, and the IHS Diabetes Care and Outcomes Audit has since evolved to measure their implementation. This standardized surveillance system measures both diabetes care and intermediate clinical outcomes (10,11). In recent years, revisions of both the standards of care and the audit measures have increased the emphasis on CVD risk factors. In 1998, the IHS conducted the Diabetes Care and Outcomes Audit at 185 federal, tribal, and urban health care facilities.

As described in a previous published report, participating facilities received written instructions to enable them to draw a random sample of charts of individuals with diabetes and to review selected measures of care and intermediate clinical outcomes (10). The sample was drawn from the community diabetes registries and thus includes patients with diabetes who may not have received diabetes care at the facility in the past year. The instructions enabled facilities to calculate the local sample using a sample size sufficient to provide estimates of ±10% of the true rates of adherence for measures performed at a rate of 60%. Individuals trained by regional diabetes consultants in accordance with written instructions and definitions conducted the actual chart reviews. Where facilities had the ability to abstract variables from the IHS electronic management information system, they were encouraged to do so, and they were also encouraged to supplement the data by chart review.

CVD risk factors included in the 1998 audit were the three most recent blood pressure readings in the past year; the total cholesterol; the most recent HbA1c value in the past year; smoking history; and results of the most recent urinalysis for protein. Blood pressure values were missing in 4% of records (ranging from 3 to 9% in different regions), total cholesterol in 18% (10–32%), HbA1c in 6% (2–20%), BMI in 10% (3–27%), proteinuria in 18% (10–29%), and tobacco use in 28% (10–57%). Other variables collected included age, sex, duration of diabetes, and height and weight. The mean of the last three blood pressure readings and the BMI were calculated from these data. BMI ≥30 kg/m2 was used as the cutoff for obesity.

Data from participating facilities were grouped into the geographic regions shown in Fig. 1. Regional and national benchmarks for each item were constructed using aggregate data from all participating sites for those <45 years of age and for those ≥45 years of age. Data for each age group were weighted by the inverses of the sampling rates. The number of patients in the diabetes registry was divided by the number of patients in the sample for each facility. Weighted prevalence rates, standard errors, and χ2 tests of significance were calculated using PROC Crosstab from the SAS-callable version of SUDAAN, version 7.5 (12).

Of the 10,889 patients with diabetes included in the 1998 IHS Diabetes Care and Outcomes Audit, 24% (n = 2,595) were <45 years of age (ranging from 17 to 31% by region), and 76% (70–83%) were aged 45 years and older (n = 8,294). These patients reflected the experience of ∼66,500 diabetes patients who received care nationwide at participating facilities and were included on the local diabetes registries.

Among patients aged <45 years, selected CVD risk factors are shown in Table 1 by region. The percentage of patients experiencing blood pressures ≥130/85 was lowest in the Pacific region (37%). Obesity rates were higher in the Southwest (78%) and the Pacific (78%). Current tobacco use varied markedly between regions, with the lowest rates in the Southwest (29%) and Colorado Plateau (12%) regions. The percentage with elevated HbA1c was lowest in Alaska (27%). There was no significant regional variation in rates of proteinuria or total cholesterol ≥200 mg/dl.

Among patients aged ≥45 years, there was significant regional variation for all of the measures (Table 2). Patients in the Southern Plains had the highest rates of blood pressures exceeding 130/85 (76%). Rates of cholesterol ≥200 mg/dl were lowest in the Southwest (38%). Obesity rates were lowest in the Colorado Plateau region (44%). As in the younger groups, tobacco use also varied markedly, with the lowest rates again in the Southwest (14%) and Colorado Plateau (8%) regions. Patients from Alaska had the lowest rates of elevated HbA1c (17%) and also had the lowest rates of proteinuria (19%).

In general, the younger patients were more likely to be obese (P < 0.0001), to be current users of tobacco (P < 0.0001), and to have HbA1c values ≥9.0% (P < 0.0001) than the patients aged ≥45 years. Older patients with diabetes were more likely to have blood pressure measurements exceeding 130/85 (P < 0.0001) and to have proteinuria (P < 0.0001). There was no significant difference between the two age groups in the rates of cholesterol ≥200 mg/dl.

The IHS analyses show that American Indians with diabetes carry a substantial burden of modifiable CVD risk factors, but there are differences in patterns of risk factors in regions of the U.S. The SHS investigators described lower smoking rates and lower mean cholesterol values in Arizona than in Oklahoma and the Dakotas (13). Smoking rates found in our study are consistent with this and other studies. The Inter-Tribal Heart Study showed high rates of smoking in the Great Lakes region (5). The Navajo Health and Nutrition Survey found low rates of smoking in the southwestern region of the U.S. (6). The SHS found hypertension to be common among diabetic patients, with the highest rates recorded in Oklahoma (13). Similarly, our analyses found individuals with diabetes in the Southern Plains region to be most likely to have blood pressures exceeding 130/85.

Our study found that the lowest percentage of patients with diabetes, both younger and older, with a total cholesterol of ≥200 mg/dl were in the Southwest. Studies from the Pima showed lipid levels to be lower in this southwestern tribe than in the general U.S. population (14). Total cholesterol values in the SHS were lowest among diabetic participants from Arizona compared with other sites (4).

Obesity rates were high in all regions. Similarly, obesity was highly prevalent in the SHS and among American Indians responding to the Behavioral Risk Factor Surveillance surveys nationwide (4,15). Proteinuria varied by region in our study, and patients aged ≥45 years in the Southwest and Pacific regions had the highest rates. The SHS also described regional differences in rates of albuminuria, with the highest rate found in Arizona (16). As in our study, median HbA1c values were highest in the Southwest cohort of the SHS (17). We do not know what effect staffing patterns, the use of new oral agents, or what other possible explanations contribute to the regional variation in metabolic control, but the observation suggests the need for careful analyses to identify what factors can be associated with the variations.

There are important limitations to this study. The data are based on chart review. Individuals who had not registered for any care at a federal, tribal, or urban facility were not included in the samples. However, because care is available without charge and the facilities are often the only source of care in isolated regions, these data probably reflect the risk factors found clinically among American Indians and Alaska Natives with diabetes residing on or near reservations. We were not able to measure all known risk factors, particularly LDL cholesterol and microalbuminuria. However, these measures have been incorporated into more recent versions of the IHS Diabetes Care and Outcomes audit and are now being measured and recorded frequently enough for the data to be available in the future.

Another limitation of this study was the high rate of missing data about tobacco use in the Southwest and Colorado Plateau regions, which limits comparisons. Providers in these regions may perceive smoking rates to be low and thus chart tobacco history less consistently than others. This could introduce a bias in which patients who are known to smoke have their smoking habits charted, and this would have the effect of falsely elevating the rate. However, the regional tobacco use trends we observed parallel those in studies with more complete ascertainment (46,18). BMI data were missing most frequency from the Great Lakes region because of missing height values (25%), but there was no significant difference in the mean weight values of those with and without height values. Cholesterol data were missing in ∼25% of records from the Southwest and Colorado Plateau regions. Some of the facilities in these regions are very remote from reference labs. Interestingly, these regions were among those with lower rates of elevated cholesterol. The SHS also found lower cholesterol values in the Arizona cohort (19).

Despite the limitations, these findings support the importance of recognizing the public health implications of CVD risk factors among American Indians and Alaska Natives with diabetes in comparison to the U.S. population. Of the 722 adults aged ≥25 years with diabetes reported in the National Health and Nutrition Examination Survey (NHANES) III cohort, only 25% had poor glycemic control (HbA1c value ≥9.0%), compared with 37–51% in this study (20). In addition, only 39% of the NHANES III cohort had uncontrolled blood pressure (≥140/90), a rate lower than the 47–56% in our analysis. Similarly, the 7.6% rate of clinical proteinuria in the NHANES subjects was lower compared with the 29% we observed in the American Indians. Only 22% of those with diabetes in the NHANES III study reported current smoking. Comparisons with the overall rate of “tobacco use” of 31% found in American Indians with diabetes are obviously complicated by the marked variations. Nonetheless, American Indians and Alaska Natives with diabetes from all the regions carry multiple CVD risk factors, and the burden appears to be much greater in these communities than in the general U.S. population.

Because of the large population-attributable risk for diabetes as a CVD risk factor, reducing rates of CVD by focusing on those with diabetes is particularly important for Indian communities. Increased efforts to promote smoking cessation in younger patients with diabetes, and probably youth in general, are especially needed in the Great Lakes, Great Plains, and Alaska regions. Although improving glycemic control is relevant to all regions, special focus on the Southwest is merited. Similarly, the high proportion of patients with poorly controlled blood pressure, elevated cholesterol, and obesity is a concern for all regions, and national programs for hypertension, lipid, and weight control are urgently needed.

Efforts to reduce CVD risk in those with diabetes are not unique to Indian communities (21). Both the American Heart Association and the American Diabetes Association have recently emphasized the necessity of targeting CVD risk reduction efforts toward individuals with diabetes (22). The newly expanded regional/tribal approach to diabetes prevention and control can be enhanced with a focus on preventing heart disease by reducing CVD risk factors (23). Although trends observed in this study can be useful to regional health planners, clinicians at individual facilities should supplement their planning with local data.

Figure 1—

Geographic regions of analysis for IHS Diabetes Care and Outcomes Audit

Figure 1—

Geographic regions of analysis for IHS Diabetes Care and Outcomes Audit

Close modal
Table 1—

Selected cardiovascular risk factors among American Indians and Alaska Natives with diabetes aged, < 45 years by region for 1998

RegionnBlood pressure ≥130/85 (%)Cholesterol ≥200 (%) (SE)BMI ≥30 (%)Tobacco use* (%)HbA1c ≥9.0%* (%)Proteinuria (%)Mean age (years)
All 2,595 47 ± 1.4 48 ± 1.5 73 ± 1.3 37 ± 1.5 51 ± 1.4 26 ± 1.3 35.4 ± 0.7 
Alaska 142 46 ± 4.6 46 ± 5.1 70 ± 4.2 55 ± 5.0 27 ± 4.6 19 ± 4.2 37.4 ± 0.4 
Colorado Plateau 244 51 ± 3.8 43 ± 4.5 67 ± 3.5 12 ± 2.8 52 ± 3.8 27 ± 3.8 35.8 ± 0.7 
Great Lakes 132 60 ± 5.0 53 ± 5.4 79 ± 4.6 53 ± 5.4 34 ± 4.9 17 ± 3.9 35.4 ± 0.3 
Great Plains 549 49 ± 2.7 58 ± 3.0 68 ± 2.6 59 ± 3.0* 52 ± 2.7 24 ± 2.4 36.6 ± 0.4 
Southern ± Plains 261 53 ± 4.0 52 ± 4.1 68 ± 3.7 41 ± 4.0 41 ± 3.8 28 ± 3.6 36.7 ± 0.3 
Pacific 491 37 ± 2.6 54 ± 3.0 78 ± 2.2 35 ± 2.8 51 ± 2.7 30 ± 2.8 35.3 ± 0.2 
Southwest 776 44 ± 2.4 42 ± 2.7 78 ± 2.2* 29 ± 3.1* 56 ± 2.4 25 ± 2.2 36.0 ± 0.1 
RegionnBlood pressure ≥130/85 (%)Cholesterol ≥200 (%) (SE)BMI ≥30 (%)Tobacco use* (%)HbA1c ≥9.0%* (%)Proteinuria (%)Mean age (years)
All 2,595 47 ± 1.4 48 ± 1.5 73 ± 1.3 37 ± 1.5 51 ± 1.4 26 ± 1.3 35.4 ± 0.7 
Alaska 142 46 ± 4.6 46 ± 5.1 70 ± 4.2 55 ± 5.0 27 ± 4.6 19 ± 4.2 37.4 ± 0.4 
Colorado Plateau 244 51 ± 3.8 43 ± 4.5 67 ± 3.5 12 ± 2.8 52 ± 3.8 27 ± 3.8 35.8 ± 0.7 
Great Lakes 132 60 ± 5.0 53 ± 5.4 79 ± 4.6 53 ± 5.4 34 ± 4.9 17 ± 3.9 35.4 ± 0.3 
Great Plains 549 49 ± 2.7 58 ± 3.0 68 ± 2.6 59 ± 3.0* 52 ± 2.7 24 ± 2.4 36.6 ± 0.4 
Southern ± Plains 261 53 ± 4.0 52 ± 4.1 68 ± 3.7 41 ± 4.0 41 ± 3.8 28 ± 3.6 36.7 ± 0.3 
Pacific 491 37 ± 2.6 54 ± 3.0 78 ± 2.2 35 ± 2.8 51 ± 2.7 30 ± 2.8 35.3 ± 0.2 
Southwest 776 44 ± 2.4 42 ± 2.7 78 ± 2.2* 29 ± 3.1* 56 ± 2.4 25 ± 2.2 36.0 ± 0.1 

Data are means ± SEM.

*

P < 0.0001 comparison among regions;

P < 0.01 compared with all others.

Table 2—

Selected cardiovascular risk factors among American Indians and Alaska Natives with diabetes aged ≥45 years by region for 1998

RegionnBlood pressure ≥130/85* (%)Cholesterol ≥200* (%)BMI ≥30* (%)Tobacco Use* (%)HbA1c ≥9.0* (%)Proteinuria* (%)Mean age (years)
All 8,294 66 ± 0.7 45 ± 0.8 56 ± 0.8 24 ± 0.7 37 ± 0.7 30 ± 0.8 62.6 ± 0.4 
Alaska 689 70 ± 1.9 52 ± 2.2 71 ± 2.0 29 ± 2.1 17 ± 1.6 19 ± 1.7 61.8 ± 0.3 
Colorado Plateau 955 63 ± 1.8 44 ± 2.2 44 ± 1.9 8 ± 1.2 39 ± 1.8 30 ± 2.0 59.8 ± 0.5 
Great Lakes 415 68 ± 2.6 48 ± 3.0 58 ± 3.2 44 ± 2.9 36 ± 2.7 24 ± 2.7 59.6 ± 0.2 
Great Plains 1,611 63 ± 1.5 51 ± 1.7 59 ± 1.5 42 ± 1.7 41 ± 1.5 26 ± 1.4 60.2 ± 0.3 
Southern Plains 1,067 76 ± 1.6 43 ± 1.9 60 ± 1.9 28 ± 1.8 31 ± 1.7 28 ± 1.7 60.1 ± 0.2 
Pacific 1,813 60 ± 1.4 56 ± 1.5 69 ± 1.3 24 ± 1.3 33 ± 1.3 35 ± 1.5 59.7 ± 0.2 
Southwest 1,744 64 ± 1.5 38 ± 1.6 57 ± 1.7 14 ± 1.5 42 ± 1.6 35 ± 1.6 60.3 ± 0.1 
RegionnBlood pressure ≥130/85* (%)Cholesterol ≥200* (%)BMI ≥30* (%)Tobacco Use* (%)HbA1c ≥9.0* (%)Proteinuria* (%)Mean age (years)
All 8,294 66 ± 0.7 45 ± 0.8 56 ± 0.8 24 ± 0.7 37 ± 0.7 30 ± 0.8 62.6 ± 0.4 
Alaska 689 70 ± 1.9 52 ± 2.2 71 ± 2.0 29 ± 2.1 17 ± 1.6 19 ± 1.7 61.8 ± 0.3 
Colorado Plateau 955 63 ± 1.8 44 ± 2.2 44 ± 1.9 8 ± 1.2 39 ± 1.8 30 ± 2.0 59.8 ± 0.5 
Great Lakes 415 68 ± 2.6 48 ± 3.0 58 ± 3.2 44 ± 2.9 36 ± 2.7 24 ± 2.7 59.6 ± 0.2 
Great Plains 1,611 63 ± 1.5 51 ± 1.7 59 ± 1.5 42 ± 1.7 41 ± 1.5 26 ± 1.4 60.2 ± 0.3 
Southern Plains 1,067 76 ± 1.6 43 ± 1.9 60 ± 1.9 28 ± 1.8 31 ± 1.7 28 ± 1.7 60.1 ± 0.2 
Pacific 1,813 60 ± 1.4 56 ± 1.5 69 ± 1.3 24 ± 1.3 33 ± 1.3 35 ± 1.5 59.7 ± 0.2 
Southwest 1,744 64 ± 1.5 38 ± 1.6 57 ± 1.7 14 ± 1.5 42 ± 1.6 35 ± 1.6 60.3 ± 0.1 

Data are means ± SEM.

*

P < 0.0001 comparison among regions;

P < 0.01 compared with all others.

1
Indian Health Service:
Trends in Indian Health
. Rockville, MD, Department of Health and Human Services, Public Health Service, Indian Health Service,
1997
2
Howard BV, Lee ET, Cowan LD, Devereux RB, Galloway JM, Go OT, Howard WJ, Rhoades ER, Robbins DC, Sievers ML, Welty TK: Rising tide of cardiovascular disease in American Indians: the Strong Heart Study.
Circulation
99
:
2389
–2395,
1999
3
Howard BV, Lee ET, Cowan LD, Fabsitz RR, Howard WJ, Oopik AJ, Robbins DC, Savage PJ, Yeh JL, Welty TK: Coronary heart disease prevalence and its relation to risk factors in American Indians.
Am J Epidemiol
142
:
254
–268,
1995
4
Welty TK, Lee ET, Yeh Y, Cowan LD, Go O, Fabsitz RR, Le N-A, Oopik AJ, Robbins DC, Howard BV: Cardiovascular Disease Risk Factors in American Indians: the Strong Heart Study.
Am J Epidemiol
142
:
269
–287,
1995
5
CDC Centers for Disease Control and Prevention:
Intertribal Heart Project: Results from the Cardiovascular Health Survey
. Atlanta, GA, Centers for Disease Control and Prevention,
1996
6
Mendlein JM, Freedman DS, Peter DG, Allen B, Percy CA, Ballew C, Mokdad AH, White LL: Risk factors for coronary heart disease among Navajo Indians: findings from the Navajo Health and Nutrition Survey.
J Nutr
127 (Suppl. 10)
:
2099S
–2105S,
1997
7
Harwell TS, Gohdes D, Moore K, McDowall JM, Smilie JG, Helgerson SD: Cardiovascular disease and risk factors in Montana American Indians and non-Indians.
Am J Prev Med
20
:
196
–201,
2001
8
Sievers ML, Nelson RG, Bennett PH: Sequential trends in overall and cause-specific mortality in diabetic and nondiabetic Pima Indians.
Diabetes Care
19
:
107
–111,
1996
9
Sievers ML, Bennett PH, Nelson RG: Effect of glycemia on mortality in Pima Indians with type 2 diabetes.
Diabetes
48
:
896
–902,
1999
10
Mayfield JA, Rith-Najarian SJ, Acton KJ, Schraer CD, Stahn RM, Johnson MH, Gohdes D: Assessment of diabetes care by medical record review: the Indian Health Service model.
Diabetes Care
17
:
918
–923,
1994
11
Acton KJ, Shields R, Rith-Najarian S, Tolbert B, Kelly J, Moore K, Valdez L, Skipper B, Gohdes D: Applying the diabetes quality improvement project indicators in the Indian Health Service primary care setting.
Diabetes Care
24
:
22
–26,
2001
12
Shah BJ, Barnwell BG, Bieler GS.
SUDAAN: Software for the Statistical Analysis of Correlated Data. Version 7.5 Edition
. Research Triangle Park, NC, Research Triangle Institute,
1997
13
Howard BV for the Strong Heart Investigators: Risk factors for cardiovascular disease in individuals with diabetes.
Acta Diabetol
33
:
180
–184,
1996
14
Howard BV, Davis MP, Pettitt DJ, Knowler WC, Bennett PH: Plasma and lipoprotein cholesterol and triglyceride concentrations in the Pima Indians: distributions differing from those of Caucasians.
Circulation
68
:
714
–724,
1983
15
Denny CH, Holtzman D:
Health Behaviors of American Indians and Alaska Natives: Findings from the Behavioral Risk Factor Surveillance System, 1993–1996
. Atlanta, GA, U.S. Department of Health and Human Services, Centers for Disease Control,
1999
16
Robbins DC, Knowler WC, Lee ET, Yeh J, Go OT, Welty T, Fabsitz R, Howard BV: Regional differences in albuminuria among American Indians: an epidemic of renal disease.
Kidney Int
49
:
557
–563,
1996
17
Hu D, Henderson JA, Welty TK, Lee ET, Jablonski KA, Magee ME, Robbins DC, Howard BV: Glycemic control in diabetic American Indians: longitudinal data from the Strong Heart Study.
Diabetes Care
22
:
1802
–1807,
1999
18
Prevalence of selected cardiovascular disease risk factors among American Indians and Alaska Natives—United States, ,
MMWR Morb Mortal Wkly Rep
49
:
461
–465,
1997
19
Howard BV, Robbins DC, Sievers ML, Lee ET, Rhoades D, Devereux RB, Cowan LD, Gray RS, Welty TK, Go OT, Howard WJ: LDL cholesterol as a strong predictor of coronary heart disease in diabetic individuals with insulin resistance and low LDL: the Strong Heart Study.
Arterioscler Thromb Vasc Biol
20
:
830
–835,
2000
20
Harris MI: Health care and health status and outcomes for patients with type 2 diabetes.
Diabetes Care
23
:
754
–758,
2000
21
O’Keefe, JH Miles JM, Harris WH, Moe RM, Mc Callister BD: Improving the adverse cardiovascular prognosis of type 2 diabetes.
Mayo Clinic Proc
74
:
171
–180,
1999
22
Grundy SM, Benjamin IJ, Burke GL, Chait A, Eckel RH, Howard BV, Mitch W, Smith SC Jr, Sowers J: Diabetes and cardiovascular disease: a statement for healthcare professionals from the American Heart Association.
Circulation
100
:
1134
–1146,
1999
23
Interim Report to Congress: Special Diabetes Programs for Indians. Albuquerque, NM, National Diabetes Program, Indian Health Service,
2000

Address correspondence and reprint requests to Stephen Rith-Najarian, Bemidji Area IHS Diabetes Program, Room 115 Federal Building, 522 Minnesota Ave., Bemidji, MN 56601. E-mail: [email protected].

Received for publication 9 May 2001 and accepted in revised form 6 November 2001.

D.M.G. or her immediate family holds stock in Pharmacia and Johnson & Johnson, and she has received honoraria from Bayer, Smith Klein Beecham, Aventis, Novartis, Bristol-Myers Squibb, Takeda, and Novo-Nordisk. At the time of this study, she was a consultant for the Indian Health Service Diabetes Program.

A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.