OBJECTIVE—Hispanics have higher rates of diabetes and diabetes-related complications than do non-Hispanic whites. A meta-analysis was conducted to estimate the difference between the mean values of A1C for these two groups.

RESEARCH DESIGN AND METHODS—We executed a PubMed search of articles published from 1993 through July 2007. Data sources included PubMed, Web of Science, Cumulative Index to Nursing and Allied Health, the Cochrane Library, Combined Health Information Database, and Education Resources Information Center. Data on sample size, age, sex, A1C, geographical location, and study design were extracted. Cross-sectional data and baseline data from clinical trials and cohort studies for Hispanics and non-Hispanic whites with diabetes were included. Studies were excluded if they included individuals <18 years of age or patients with pre-diabetes or gestational diabetes.

RESULTS—A total of 495 studies were reviewed, of which 73 contained data on A1C for Hispanics and non-Hispanic whites, and 11 met the inclusion criteria. Meta-analysis revealed a statistically significant mean difference (P < 0.0001) of −0.46 (95% CI −0.63 to −0.33), correlating to an ∼0.5% higher A1C for Hispanics. Grouping studies by design (cross-sectional or cohort), method of data collection for A1C (chart review or blood sampling), and care type (managed or nonmanaged) yielded similar results.

CONCLUSIONS—In this meta-analysis, A1C was ∼0.5% higher in Hispanic patients with diabetes than in non-Hispanic patients. Understanding the reasons for this disparity should be a focus for future research.

Ethnic minorities in the U.S. are disproportionately affected by diabetes (1). For adults ≥18 years of age, the age-adjusted prevalence of diagnosed diabetes is 10.5% for Hispanic or Latino individuals compared with 6.8% for non-Hispanic whites (1). The Hispanic population is the fastest growing minority group in the U.S., and Hispanics have a higher lifetime risk of diabetes than do non-Hispanic whites (2,3). Diabetes has a major adverse impact on life years and quality-adjusted life years in all U.S. subpopulations, with an even greater impact among minority individuals including Hispanics (3). Specifically, Hispanics have higher rates of many diabetes complications such as retinopathy, neuropathy, and lower leg amputations than do non-Hispanic whites (49).

Improvements in glycemic control have been shown to prevent microvascular complications, and large trials have demonstrated the need for glucose control among patients with diabetes (10,11). Literature reviews have suggested that A1C is higher among minority populations than among nonminority populations, and a previous meta-analysis confirmed higher levels of A1C among African Americans than among non-Hispanic whites (12,13). Factors that may underlie lack of A1C control include language barriers, inadequate access to care, lack of insurance coverage, low socioeconomic status, quality-of-care factors, self-care behaviors, and biological differences (14,15). Variance in A1C between populations may be due to poor control and/or biological differences across ethnic groups.

Although a number of studies varying in size and design have shown ethnic differences in glycemic control between Hispanics and non-Hispanic whites, to date there has not been a systematic analysis of these data. We reviewed the literature (1993–July 2007) for studies in which comparisons between these populations were made and conducted a meta-analysis using standardized statistical methods. This time period was selected because the A1C measurement, a marker of attachment of glucose to the erythrocyte over the previous 3 months, became more standardized over the past 10–15 years. Hispanic refers to populations who trace their origin to Spain or a Spanish-speaking country. We used this criterion for defining Hispanic populations in this article and restricted our focus to such populations residing in the U.S.

Identification of studies

We conducted a MEDLINE search in PubMed, using Medical Subject Heading (MeSH) terms and restricted the search to entries from 1993 through July 2007. We used the search terms “Diabetes Mellitus” (MeSH) or “Diabetes Mellitus, type 2” (MeSH) and “Hemoglobin A, Glycosylated” (MeSH) and “Hispanic Americans” (MeSH) or “Mexican Americans” (MeSH). The MeSH term “Hispanic Americans” when exploded includes Hispanic Americans, Spanish Americans, Cuban Americans, Hispanics, Latinos, and Puerto Ricans. We applied the limits “All Adult, ≥18 years of age,” and “English language.” We initially retrieved 1,271 abstracts and evaluated them for applicability to the project. Publications accepted had to include patients with diabetes and contain comparative data for both Hispanics (of any area) and non-Hispanic whites. We rejected abstracts that included patients with gestational diabetes or pre-diabetes. However, we accepted studies that included both type 1 and type 2 diabetes. We collected additional references from bibliographies of reviews, original research articles, and other articles of interest. Web of Science, Cumulative Index to Nursing and Allied Health, the Cochrane Library, Combined Health Information Database, and Education Resources Information Center were databases that we also searched. A total of 495 abstracts were applicable to the project.

A variety of study designs were found (Table 1). If the SD of the A1C was not reported or could not be obtained from the authors, we did not include the study in the meta-analysis. We accepted author-reported data only if we were assured by written communication that the information was obtained from the original computerized dataset. If a study was an intervention trial, it was excluded because of potential selection bias in patient recruitment. If there was more than one publication from the same database, we accepted the most recent data file that was published.

Data extraction

Two investigators (J.K.K. and R.A.B.) independently reviewed each study for the following data: 1) sample size (N), 2) mean and SD of participants’ age, 3) number of men and women, 4) A1C mean and SD, 5) geographic location of the research, and 6) study design. Figure 1 shows a flow diagram of the literature review. Eleven studies (1626) contained glycemia-related data for Hispanics and non-Hispanic whites including A1C mean value and SD (Table 1). For three of the studies (15,17,18) included in this meta-analysis, the authors personally provided A1C data or SDs.

Statistical analysis

A primary meta-analysis was conducted on the 11 studies (1626). Six individual meta-analyses were conducted on subsets including study type (cohort and cross-sectional studies), method of data collection (chart review and blood sampling), and care type (managed or nonmanaged). Baseline data are summarized in Table 1 for the 11 studies that met the inclusion criteria. Individual meta-analyses were conducted on the subsets to judge the sensitivity of the results and justify the conclusions of the primary analysis. In addition to the meta-analyses performed in the subsets, two additional analyses were done to further examine the effect of age or BMI on A1C differences between Hispanics and non-Hispanic whites. Without patient-level data, the summary meta-analysis could not be adjusted for possible confounding effects of age and BMI. The first of these two additional meta-analyses was done on the subset of studies in which there were no differences in age between the two groups. The second analysis was done on the subset of studies in which there was no difference in BMI between the two groups (Table 1). A mean difference in A1C was calculated between Hispanics and non-Hispanic whites. For each study, a 95% CI was calculated.

Homogeneity of the effect sizes across studies was first assessed using a χ2 test to determine whether a fixed- or random-effects approach should be implemented. A fixed-effects approach treats the set of studies as homogeneous and considers them representative of all potential studies of interest, whereas the random-effects approach treats the studies as heterogeneous and considers them to be a sample from a population of comparable studies. The homogeneity test results indicated the use of random-effects models in five of the seven meta-analyses. As the more conservative approach to meta-analyses, random-effects models were used in all seven cases. All tests of effect were two sided, and P < 0.05 was considered to be statistically significant.

Differences existed in the age of participants across studies, but most included patients >50 of age (Table 1). Four studies designated the population as Hispanic, three as Mexican American, and two as Latino. Four studies were done in a managed care setting; five used chart review, and six used blood sampling to obtain A1C data (Table 1). BMI and age were reported for 10 of the 11 studies. Statistical comparison of mean age between non-Hispanic whites and Hispanics showed no difference in age in five of the studies. The same comparison for BMI resulted in no difference between the groups in six of the studies. Two separate additional meta-analyses were performed including only these five and six studies, respectively.

One of the 11 studies indicated significantly higher A1C levels in Hispanics than in non-Hispanic whites (Fig. 2). Each meta-analysis resulted in statistically significant differences in A1C levels between Hispanics and non-Hispanic whites. The summary mean A1C (%) difference size was −0.46 (95% CI −0.54 to −0.39), which indicated that non-Hispanic whites had A1C values that were ∼0.5% below those of Hispanics (Fig. 3). The mean differences were similar regardless of study design. The estimated mean difference for cross-sectional studies was −0.52 (−0.71 to 0.32) and for prospective cohort studies was −0.40 (−0.42 to −0.37). Similarly, when studies were divided into two groups according to data collection type, the mean A1C (percent) differences were consistent with the results from the summary analysis. Studies in which the A1C values were collected from chart reviews had a mean difference of −0.45 (−0.55 to −0.35), and studies in which the values were obtained from baseline blood sampling had a mean difference of −0.55 (−0.59 to −0.51). For managed care studies the mean difference was −0.38 (0.43 to −0.33), and for nonmanaged care it was −0.57 (−0.78 to −0.36). The supporting analysis, including only studies in which there was no difference in age, had a mean difference of −0.48 (−0.63 to −0.33). Likewise, the analysis including only studies in which there was no difference in BMI had a mean difference of −0.50 (−0.70 to −0.30). Both results support the primary meta-analysis and indicate that despite differences in age or BMI between non-Hispanic whites and Hispanics in some studies included in this analysis, the differences in A1C are persistent.

This meta-analysis shows that, in general, A1C is higher in Hispanics than in non-Hispanic whites with an overall mean A1C difference of 0.5%. The consistency of the findings is notable. This meta-analysis combined 11 studies to evaluate the overall mean difference. For the studies that were excluded but that reported A1C above target thresholds (i.e., >7%), glycemic control was worse among Hispanics than among non-Hispanic whites (2732). The strengths of this analysis are its inclusion of a variety of study designs, the ability to examine A1C differences by study type, data collection methods, and care type, and the use of previously unpublished data (15,17,18).

The reasons for the disparity in A1C found in this meta-analysis are not well established in the literature. Hispanic patients with diabetes have been reported to have a higher prevalence of cardiovascular disease risk factors than non-Hispanic whites (46). Differences in biology, access to care, insurance status, and adherence to diabetes treatment regimens (medication, nutrition, behavior, and others) are all plausible explanations of the disparity. Beliefs about diabetes common among Hispanics may also result in behaviors that limit diabetes self-management (3335). A recent comparison of 2004 Behavioral Risk Factor Surveillance System data for Hispanics and non-Hispanic whites indicates that Hispanics have lower quality of diabetes care (36).

A limitation to the analysis is publication bias. However, we performed numerous searches on this topic and contacted multiple investigators to retrieve unpublished data on A1C means and SDs. The heterogeneity of the studies adds to the limitations of the analysis in that individuals classified as Hispanic have a variety of places of origin. In some studies, Hispanics (20) were likely to be recent migrants from Mexico and Central America, whereas others (17) included Spanish-speaking populations who have been in the U.S. for a considerable length of time. Nevertheless, results are probably generalizable to Hispanic and non-Hispanic white adult patients with type 2 diabetes because the data included a broad range of patient ages, geographic settings, and study types. Another limitation to this meta-analysis is that despite the comprehensive review of abstracts, the potential for omission exists if an abstract initially reviewed through our search process did not specifically address racial disparities.

The results of this meta-analysis, however, depend in part on the accuracy, standardization, and reliability of the A1C measurement across studies. A recent evaluation of ethnic differences in A1C among patients in the Diabetes Prevention Program with impaired glucose tolerance indicated that hemoglobin glycation or red cell survival may differ among ethnic groups (37). Additionally, the relationship between A1C and complications related to medical costs has been investigated using a computer-simulated model in individuals with type 2 diabetes developed by the National Institutes of Health (38). Using this model, Hispanics had the highest predicted complication rates and the highest predicted costs for eye disease, renal disease, and neuropathy/lower extremity amputation.

Although the studies included in our analysis used a variety of designs, a consistency in the degree of disparity of glycemic control was found regardless of study type. Multiple separate meta-analyses were conducted across study types (prospective cohort, cross-sectional, or retrospective chart review). Additional meta-analyses were also performed according to whether A1C data were collected by blood sampling or obtained post hoc from medical chart review and by sex, with all resulting in the same outcome. Hispanics with diabetes have an ∼0.5% higher A1C across studies. Of note is the fact that a 1% reduction in A1C has been correlated with an estimated 21% reduction in vascular complications (39). For this meta-analysis, an estimated reduction would correspond to about a 10.5% decreased risk. The reported findings are significant because ethnic disparities in glycemic control may be directly related to vascular outcomes.

Future researchers should focus not only on discovering the source of disparities in glycemic control that exist between minority populations and non-Hispanic whites but also on reducing these disparities—specifically, how much of these disparities is due to biological differences, types of lifestyles, health care access and utilization, or socioeconomic factors. Although an overall 0.5% difference in A1C among studies between Hispanics and non-Hispanic whites was found, the largest difference in A1C was among the nonmanaged care group of studies. These data suggest that Hispanic patients with diabetes in nonmanaged care settings are different with regard to A1C values. Potential fragmented care, access to care, and quality of care should be further evaluated in this population.

Figure 1—

Flow diagram of systematic review of literature.

Figure 1—

Flow diagram of systematic review of literature.

Close modal
Figure 2—

Mean A1C (%) differences between Hispanics and non-Hispanic whites. *Cross-sectional study; †prospective cohort study; ‡data obtained from chart review; §A1C sample from study-initiated blood draw; ‖managed care; ¶nonmanaged care.

Figure 2—

Mean A1C (%) differences between Hispanics and non-Hispanic whites. *Cross-sectional study; †prospective cohort study; ‡data obtained from chart review; §A1C sample from study-initiated blood draw; ‖managed care; ¶nonmanaged care.

Close modal
Figure 3—

Summary of mean A1C (%) differences between Hispanics and non-Hispanic whites.

Figure 3—

Summary of mean A1C (%) differences between Hispanics and non-Hispanic whites.

Close modal
Table 1—

Characteristics of studies among Hispanics and non-Hispanic whites*

StudyNon-Hispanic whites
Hispanic
SiteStudy design
nAge (years)*BMI (kg/m2)A1C (%)nAge (years)*BMI (kg/m2)A1C (%)
Boltri et al., 2005 (16157 59 ± 1.7 32.8 ± 9.8 7.6 ± 2.5 202 56.5 ± 1.6 31.0 ± 5.16 8.2 ± 4.2 1999–2000 NHANES national sample Cross-sectional 
Bonds et al., 2003 (17)* 144 62 ± 8 30.8 ± 6 7.4 ± 1.8 156 61.4 ± 9.1 30.7 ± 5.7 7.9 ± 2.1 IRAS cohort in CO and TX Prospective cohort 
Brown et al., 2005 (18)* 2,787 61 ± 13 31.6 ± 7.3 7.8 ± 1.7 1,207 60.9 ± 12.7 30.9 ± 6.8 8.2 ± 1.9 TRIAD study of diabetes in managed care (MI, NJ, PA, TX, CA, HI, and IN) Prospective cohort 
Chesla et al., 2000 (19) 116 48.4 ± 8.9 31.0 ± 7.2 8.2 ± 1.6 76 51.7 ± 7.7 31.8 ± 5.3 9.0 ± 2.1 11 private and public health facilities in CA Cross-sectional 
Dunbar et al., 2005 (20599 51 ± 1.9 31.4 ± 7.6 8.7 ± 2.2 257 46 ± 1.9 29.5 ± 5.5 9.3 ± 2.9 Urban outpatient diabetes clinic in GA Cross-sectional 
Harris et al., 1999 (21486 ≥20 NA 7.6 ± 1.9 399 ≥20 NA 8.0 ± 2.0 NHANES III Cross-sectional 
Karter et al., 2002 (22) 40,025 61 ± 13 30.0 ± 6.6 8.4 ± 1.8 6,279 56.7 ± 12.3 30.3 ± 6.1 8.8 ± 2.0 Northern CA Kaiser Permanente patients Prospective cohort 
Lindeman et al., 1998 (23)* 70 72.9 ± 5.5 27.7 ± 4.0 8.4 ± 2.5 118 74.1 ± 5.6 27.8 ± 4.7 8.9 ± 2.9 Medicare recipients from Health Care Financing Authority in NM Cross-sectional 
Sharma and Pavlik, 2001 (24)* 111 63.2 ± 12.7 31.4 ± 8.1 9.4 ± 2.9 132 60.6 ± 13 30.6 ± 6.3 10.2 ± 2.1 Community clinic patients in TX Retrospective chart review 
Wendel et al. 2006 (26)* 226 65,5 ± 9.4 32.3 ± 6.2 7.9 ± 1.4 72 64.9 ± 10.1 30.9 ± 5.7 8.2 ± 1.6 3 Veterans Affairs Medical Centers in Southwest Cross-sectional 
Young et al., 2005 (25) 2,197 60.9 ± 12.3 31.9 ± 7.5 7.8 ± 1.6 98 55.5 ± 11.9 31.1 ± 7.8 8.0 ± 1.8 9 primary care clinics in western WA Cross-sectional 
StudyNon-Hispanic whites
Hispanic
SiteStudy design
nAge (years)*BMI (kg/m2)A1C (%)nAge (years)*BMI (kg/m2)A1C (%)
Boltri et al., 2005 (16157 59 ± 1.7 32.8 ± 9.8 7.6 ± 2.5 202 56.5 ± 1.6 31.0 ± 5.16 8.2 ± 4.2 1999–2000 NHANES national sample Cross-sectional 
Bonds et al., 2003 (17)* 144 62 ± 8 30.8 ± 6 7.4 ± 1.8 156 61.4 ± 9.1 30.7 ± 5.7 7.9 ± 2.1 IRAS cohort in CO and TX Prospective cohort 
Brown et al., 2005 (18)* 2,787 61 ± 13 31.6 ± 7.3 7.8 ± 1.7 1,207 60.9 ± 12.7 30.9 ± 6.8 8.2 ± 1.9 TRIAD study of diabetes in managed care (MI, NJ, PA, TX, CA, HI, and IN) Prospective cohort 
Chesla et al., 2000 (19) 116 48.4 ± 8.9 31.0 ± 7.2 8.2 ± 1.6 76 51.7 ± 7.7 31.8 ± 5.3 9.0 ± 2.1 11 private and public health facilities in CA Cross-sectional 
Dunbar et al., 2005 (20599 51 ± 1.9 31.4 ± 7.6 8.7 ± 2.2 257 46 ± 1.9 29.5 ± 5.5 9.3 ± 2.9 Urban outpatient diabetes clinic in GA Cross-sectional 
Harris et al., 1999 (21486 ≥20 NA 7.6 ± 1.9 399 ≥20 NA 8.0 ± 2.0 NHANES III Cross-sectional 
Karter et al., 2002 (22) 40,025 61 ± 13 30.0 ± 6.6 8.4 ± 1.8 6,279 56.7 ± 12.3 30.3 ± 6.1 8.8 ± 2.0 Northern CA Kaiser Permanente patients Prospective cohort 
Lindeman et al., 1998 (23)* 70 72.9 ± 5.5 27.7 ± 4.0 8.4 ± 2.5 118 74.1 ± 5.6 27.8 ± 4.7 8.9 ± 2.9 Medicare recipients from Health Care Financing Authority in NM Cross-sectional 
Sharma and Pavlik, 2001 (24)* 111 63.2 ± 12.7 31.4 ± 8.1 9.4 ± 2.9 132 60.6 ± 13 30.6 ± 6.3 10.2 ± 2.1 Community clinic patients in TX Retrospective chart review 
Wendel et al. 2006 (26)* 226 65,5 ± 9.4 32.3 ± 6.2 7.9 ± 1.4 72 64.9 ± 10.1 30.9 ± 5.7 8.2 ± 1.6 3 Veterans Affairs Medical Centers in Southwest Cross-sectional 
Young et al., 2005 (25) 2,197 60.9 ± 12.3 31.9 ± 7.5 7.8 ± 1.6 98 55.5 ± 11.9 31.1 ± 7.8 8.0 ± 1.8 9 primary care clinics in western WA Cross-sectional 

Data are means ± SD.

*

t test for differences in age (NS).

t test for differences in BMI (NS).

A1C provided by the author via written communication. IRAS, Insulin Resistance Atherosclerosis Study; NA, not available; NHANES, National Health and Nutrition Examination Survey; TRIAD, Translating Research into Action for Diabetes.

This publication was made possible through a cooperative agreement between the Centers for Disease Control and Prevention and the Association of Teachers of Preventive Medicine (Award TS-0778).

1.
Centers for Disease Control: Early release of selected estimates based on data from January–March 2006 National Health Interview Survey. Available from http://www.cdc.gov/nchs/data/nhis/earlyrelease/200609_14.pdf. Accessed 14 February 2007
2.
Stern PM, Mitchell BD: Diabetes in Hispanics Americans. In
Diabetes in America
. 2nd ed. National Diabetes Data Group, Eds. Bethesda, MD, National Institutes of Health, 1995, p. 631–659
3.
Narayan KM, Boyle JP, Thompson TJ, Sorensen SW, Williamson DF: Lifetime risk for diabetes mellitus in the United States.
JAMA
290
:
1884
–1890,
2003
4.
Hamman RF, Marshall JA, Baxter J, Kahn LB, Mayer EJ, Orleans M, Murphy JR, Lezotte DC: Methods and prevalence of non-insulin-dependent diabetes mellitus in a biethnic Colorado population: the San Antonio Heart Study.
Am J Epidemiol
129
:
295
–311,
1989
5.
Flegal KM, Ezzati TM, Harris MI, Haynes SG, Juarez RZ, Knowler WC, Perez-Stable EJ, Stern MP: Prevalence of diabetes in Mexican Americans, Cubans, and Puerto Ricans from Hispanic Health and Nutrition Survey, 1982–1984.
Diabetes Care
14
:
628
–638,
1991
6.
Haffner SM, Hazuda HP, Mitchell BD, Patterson JK, Stern MP: Increased incidence of type II diabetes in Mexican Americans.
Diabetes Care
14
:
102
–108,
1991
7.
Cowie CC, Port FK, Wolfe RA, Savage PJ, Moll PP, Hawthorne VM: Disparities in incidence of diabetic end-stage renal disease according to race and type of diabetes.
N Engl J Med
321
:
1074
–1079,
1989
8.
Harris MI, Klein R, Cowie CC, Rowland M, Byrd-Holt DD: Is the risk of diabetic retinopathy greater in non-Hispanic blacks and Mexican Americans than in non-Hispanic whites with type 2 diabetes? A U.S. population study.
Diabetes Care
21
:
1230
–1235,
1998
9.
Lavery LA, Ashry HR, van Houtum W, Pugh JA, Harkless LB, Basu S: Variation in the incidence and proportion of diabetes-related amputations in minorities.
Diabetes Care
19
:
48
–52,
1996
10.
Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33): UK Prospective Diabetes Study (UKPDS) Group.
Lancet
352
:
837
–853,
1998
11.
The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes: the Diabetes Control and Complications Trial Research Group.
N Engl J Med
329
:
977
–986,
1993
12.
Kirk JK, Bell RA, Bertoni AG, Arcury TA, Quandt SA, Goff DC Jr, Narayan KM: Ethnic disparities: control of glycemia, blood pressure, and LDL cholesterol among US adults with type 2 diabetes.
Ann Pharmacother
39
:
1489
–1501,
2005
13.
Kirk JK, D'Agostino RA, Bell RA, Passmore LV, Bonds DE, Karter AJ, Narayan KMV: Disparities in HbA1c levels between African Americans and non-Hispanic white adults with diabetes: a meta-analysis.
Diabetes Care
29
:
2130
–2136,
2006
14.
Killilea T: Long-term consequences of type 2 diabetes mellitus: economic impact on society and managed care.
Am J Manag Care
8
:
S441
–S449,
2002
15.
Harris MI: Racial and ethnic differences in health care insurance coverage for adults with diabetes.
Diabetes Care
22
:
1679
–1682,
1999
16.
Boltri JM, Okosun IS, Davis-Smith M, Vogel RL: Hemoglobin A1C levels in diagnosed and undiagnosed black, Hispanic and white persons with diabetes: results from NHANES 1999–2000.
Ethnic Dis
15
:
562
–567,
2005
17.
Bonds DE, Zaccaro DJ, Karter AJ, Selby JV, Saad M, Goff DC Jr: Ethnic and racial differences in diabetes care: the Insulin Resistance Atherosclerosis Study.
Diabetes Care
26
:
1040
–1046,
2003
18.
Brown AF, Gregg EW, Stevens MR, Karter AJ, Weinberger M, Safford MM, Gary TL, Caputo DA, Waitzfelder B, Kim C, Beckles GL: Race, ethnicity, socioeconomic position, and quality of care for adults with diabetes enrolled in managed care: the Translating Research Into Action for Diabetes (TRIAD) study.
Diabetes Care
28
:
2864
–2870,
2005
19.
Chesla CA, Skaff MM, Bartz RJ, Mullan JT, Fisher L: Differences in personal models among Latinos and European Americans.
Diabetes Care
23
:
1780
–1785,
2000
20.
Dunbar VG, King EC, George CD, El-Kebbi IM, Ziemer DC, Gallina DL, Cook CB: Evolving demographics and disparities in an urban diabetes clinic: implications for diabetes education and treatment.
Ethnic Dis
15
:
173
–178,
2005
21.
Harris MI, Eastman RC, Cowie CC, Flegal KM, Eberhardt MS: Racial and ethnic differences in glycemic control of adults with type 2 diabetes.
Diabetes Care
22
:
403
–408,
1999
22.
Karter AJ, Ferrara A, Liu JY, Moffet HH, Ackerson LM, Selby JV: Ethnic disparities in diabetic complications in an insured population.
JAMA
287
:
2519
–2527,
2002
23.
Lindeman RD, Romero LJ, Hundley R, Allen AS, Liang HC, Baumgartner RN, Koehler KM, Schade DS, Garry PJ: Prevalences of type 2 diabetes, the insulin resistance syndrome, and coronary heart disease in an elderly, biethnic population.
Diabetes Care
21
:
959
–966,
1998
24.
Sharma MD, Pavlik VN: Dyslipidaemia in African Americans, Hispanics and whites with type 2 diabetes mellitus and hypertension.
Diabetes Obes Metab
3
:
41
–45,
2001
25.
Young BA, Katon WJ, Korff MV, Simon GE, Lin EHB, Ciechanowski PS, Bush T, Oliver M, Ludman EJ, Boyko EJ: Racial and ethnic difference in microalbuminuria prevalence in a diabetes population: the Pathways Study.
J Am Soc Nephrol
16
:
219
–228,
2005
26.
Wendel CS, Sha JH, Duckworth WC, Hoffman RM, Mohler MJ, Murata GH: Racial and ethnic disparities in the control of cardiovascular disease and risk factors in Southwest American veterans with type 2 diabetes: the Diabetes Outcomes in Veterans Study.
BMC Health Serv Res
6
:
1472
27.
Saaddine JB, Engelgau MM, Beckles GL, Gregg EW, Thompson TJ, Narayan KM: A diabetes report card for the United States: quality of care in the 1990's.
Ann Intern Med
136
:
564
–574,
2002
28.
Harris MI: Racial and ethnic differences in health care access and health outcomes for adults with type 2 diabetes.
Diabetes Care
24
:
454
–459,
2001
29.
Tucker KL, Bermudez OI, Castaneda C: Type 2 diabetes is prevalent and poorly controlled among Hispanic elders of Caribbean origin.
Am J Public Health
90
:
1288
–1303,
2000
30.
Zhang Q, Safford M, Ottenweller J, Hawley G, Repke D, Burgess JF Jr: Performance status of health care facilities changes with risk adjustment of HbA1c.
Diabetes Care
23
:
917
–919,
2000
31.
Baumann LC, Chang MW, Hoebeke R: Clinical outcomes for low-income adults with hypertension and diabetes.
Nurs Res
51
:
191
–198,
2002
32.
Fan T, Koro CE, Fedder DO, Bowlin SJ: Ethnic disparities and trends in glycemic control among adults with type 2 diabetes in the U.S. from 1988 to 2002.
Diabetes Care
29
:
1924
–1925,
2006
33.
Coronado GD, Thompson B, Tejeda S, Godina R: Attitudes and beliefs among Mexican Americans about type 2 diabetes.
J Health Care Poor Underserved
15
:
576
–588,
2004
34.
Hunt LM, Valenzuela MA, Pugh JA: Porque me toco a mi? Mexican American diabetes patients’ causal stories and their relationship to treatment behaviors.
Soc Sci Med
46
:
959
–969,
1998
35.
Arcury TA, Skelly AH, Gesler WM, Dougherty MC: Diabetes meanings among those without diabetes: explanatory models of immigrant Latinos in rural North Carolina.
Soc Sci Med
59
:
2183
–2193,
2004
36.
Mainous AG 3rd, Diaz VA, Koopman RJ, Everett CJ: Quality of care for Hispanic adults with diabetes.
Fam Med
39
:
351
–356,
2007
37.
Herman WH, Ma Y, Uwaifo G, Haffner S, Kahn SE, Horton ES, Lachin JM, Montez MG, Brenneman T, Barrett-Conner E: Racial and ethnic differences in hemoglobin A1C among patients with impaired glucose tolerance in the Diabetes Prevention Program.
Diabetes Care
30
:
2453
–2457,
2007
38.
de Lissovoy G, Ganoczy DA, Ray NF: Relationship of hemoglobin A1c, age of diabetes diagnosis, and ethnicity to clinical outcomes and medical costs in a computer-simulated cohort of persons with type 2 diabetes.
Am J Manag Care
6
:
573
–584,
2000
39.
Stratton IM, Adler AI, Neil HA, Matthews DR, Manley SE, Cull CA, Hadden D, Turner RC, Holman RR: Association of glycaemia with macrovascular and microvascular complications of type 2 diabetes (UKPDS 35): prospective observational study.
BMJ
321
:
405
–412,
2000

Published ahead of print at http://care.diabetesjournals.org on 31 October 2007. DOI: 10.2337/dc07-0382.

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