A1C is formed when glucose reacts nonenzymatically with amino acids on hemoglobin. Its concentration represents an integrated measure of glucose concentration during hemoglobin's lifespan, which is about 2–3 months (1). Because A1C concentration predicts the risk for microvascular and macrovascular complications (2,3), it is used in the clinical setting to assess longer-term glycemic control among people with diabetes. Generally, A1C concentrations <7% are regarded as acceptable glycemic control (4).

Approximately 44% of U.S. adults with diagnosed diabetes had a concentration of A1C <7% during 1988–1994 compared with ∼36–37.0% during 1999–2000 (5,6). More recently, data from the National Committee for Quality Assurance showed steady increases in the percentage of patients receiving annual testing for A1C and decreases in the percentage of patients with poor glycemic control from 2000 to 2006 (7). Our objective was to examine trends in glycemic control among U.S. adults with diagnosed diabetes from 1999 to 2004.

The National Health and Nutrition Examination Survey (NHANES) 1999–2004 included nationally representative samples of the noninstitutionalized, civilian U.S. population, selected using a multistage, stratified sampling design (8). Participants were asked the following: “Other than during pregnancy, have you ever been told by a doctor or health professional that you have diabetes or sugar diabetes?” In addition to answering “yes” or “no,” participants could report having “borderline” diabetes. Individuals with borderline diabetes were excluded from further analysis.

Concentrations of A1C were determined by using boronate affinity high-performance liquid chromatography on Primus CLC330 and Primus CLC385 instruments (Primus, Kansas City, MO). Interassay coefficients of variation were <3% (9). All measurements were performed at the Diabetes Diagnostic Laboratory at the University of Missouri-Columbia. The method was standardized to the reference method of the Diabetes Control and Complications Trial. A plot of the mean concentrations of two levels of A1C control subjects from 1999 to 2004 shows no evidence of drift.

Analyses, performed using SUDAAN to account for the complex sampling design, were limited to participants aged ≥20 years who attended the mobile examination center. Prevalence ratios were estimated using log-binomial regression analysis (10).

A total of 1,334 participants with diagnosed diabetes had a measurement of A1C. Of all patients with diabetes, the percentage of participants whose diabetes had been diagnosed was 70.2% in 1999–2000, 68.5% in 2001–2002, and 74.6% in 2003–2004. The mean age, sex, and racial or ethnic composition of the samples were similar for the three 2-year cycles.

In 2003–2004, the geometric mean concentration of A1C was significantly lower than in 1999–2000 (Table 1). The unadjusted percentage of participants with diagnosed diabetes who had a concentration of A1C <7% increased significantly, from 37.0% (95% CI 28.4–45.7) in 1999–2000 to 56.8% (49.6–64.0) in 2003–2004 (Table 1). These percentages were little affected by adjustment for age, sex, ethnicity, educational status, smoking status, hypertension, concentrations of total cholesterol, BMI, waist circumference, treatment (oral glucose-lowering medications only, insulin only, both, or no oral glucose-lowering medications or insulin), and duration of diabetes in logistic regression (1,160 participants with complete data). Compared with participants from NHANES 1999–2000, the adjusted prevalence ratios for having a concentration of A1C <7% were 1.32 (0.98–1.79) for participants from NHANES 2001–2002 and 1.46 (1.08–1.97) for participants from NHANES 2003–2004 (P for linear trend = 0.010). Trends did not differ significantly between men and women.

Improvements in A1C were steadiest among whites but occurred primarily from 1999–2000 to 2001–2002 among African Americans and Mexican Americans. Despite these apparent differences, no significant differences in trends among the ethnic groups were found, possibly as a result of limited statistical power. For the entire 6-year period, glycemic control was similar in men and women (P = 0.235). However, white participants exhibited better control than African-American (P = 0.001) or Mexican-American (P < 0.001) participants.

Although glycemic control as determined by a concentration of A1C <7% did not change significantly from 1988–1994 to 1999–2000 (5,6), it is encouraging that a significant improvement appears to have occurred from 1999–2000 to 2003–2004. After controlling for factors known to be associated with A1C (1114), we still found a substantial increase in glycemic control, suggesting that other factors must have been at work during the study period. A trend toward earlier detection of diabetes could have explained the improvement in glycemic control. However, we did not find evidence of such a trend during the study period. Therefore, it is conceivable that the concerted efforts of professional organizations and clinicians at improving glycemic control are bearing fruit. A variety of approaches can improve glycemic control (1520). Learning whether these approaches or other factors may have positively impacted the recent trends in glycemic control could provide important lessons for effecting further improvements in glycemic control in the future.

Significant ethnic disparities in glycemic control were noted and are consistent with previous findings (21). The disparity in glycemic control stands in contrast to the results from some studies that showed no or little ethnic difference in annual testing for A1C (22,23).

Some limitations should be considered. We were unable to provide separate estimates of glycemic control for type 1 and type 2 diabetes. Sample sizes were inadequate to provide detailed estimates when the sociodemographic variables were considered simultaneously.

In conclusion, our results are consistent with other data suggesting that improvements in glycemic control have occurred among patients with diabetes in the U.S. As welcome as the recent favorable trends in glycemic control are, additional efforts are needed to help the ∼40% of patients with diabetes who do not have adequate glycemic control.

1.
Reynolds TM, Smellie WS, Twomey PJ: Glycated haemoglobin (A1C) monitoring.
BMJ
333
:
586
–588,
2006
2.
The Diabetes Control and Complications Trial Research Group: The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus.
N Engl J Med
329
:
977
–986,
1993
3.
UK Prospective Diabetes Study (UKPDS) Group: Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33).
Lancet
352
:
837
–853,
1998
4.
American Diabetes Association: Tests of glycemia in diabetes.
Diabetes Care
25(Suppl. 1)
:
S97
–S99,
2002
5.
Saydah SH, Fradkin J, Cowie CC: Poor control of risk factors for vascular disease among adults with previously diagnosed diabetes.
JAMA
291
:
335
–342,
2004
6.
Koro CE, Bowlin SJ, Bourgeois N, Fedder DO: Glycemic control from 1988 to 2000 among U.S. adults diagnosed with type 2 diabetes: a preliminary report.
Diabetes Care
27
:
17
–20,
2004
7.
National Committee for Quality Assurance: The state of health care quality 2006 [article online]. Washington, DC, National Committee for Quality Assurance. Available from http://web.ncqa.org/Default.aspx?tabid=447. Accessed 25 September 2007
8.
National Center for Health Statistics: 1999–2000 National Health and Nutrition Examination Survey (NHANES) [article online]. Atlanta, GA, Centers for Disease Control and Prevention. Available from http://www.cdc.gov/nchs/about/major/nhanes/currentnhanes.htm. Accessed 30 May 2007
9.
Centers for Disease Control and Prevention: MEC laboratory component: glycohemoglobin [article online]. Atlanta, GA, Centers for Disease Control and Prevention. Available from http://www.cdc.gov/nchs/data/nhanes/nhanes_03_04/l10_c.pdf. Accessed 30 May 2007
10.
Barros AJ, Hirakata VN: Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the prevalence ratio.
BMC Med Res Methodol
3
:
21
,
2003
11.
de Vegt F, Dekker JM, Ruhe HG, Stehouwer CD, Nijpels G, Bouter LM, Heine RJ: Hyperglycaemia is associated with all-cause and cardiovascular mortality in the Hoorn population: the Hoorn Study.
Diabetologia
42
:
926
–931,
1999
12.
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
13.
Carter JS, Gilliland SS, Perez GE, Skipper B, Gilliland FD: Public health and clinical implications of high hemoglobin A1c levels and weight in younger adult Native American people with diabetes.
Arch Intern Med
160
:
3471
–3476,
2000
14.
Gulliford MC, Ukoumunne OC: Determinants of glycated haemoglobin in the general population: associations with diet, alcohol and cigarette smoking.
Eur J Clin Nutr
55
:
615
–623,
2001
15.
Brown SA: Meta-analysis of diabetes patient education research: variations in intervention effects across studies.
Res Nurs Health
15
:
409
–419,
1992
16.
Coster S, Gulliford MC, Seed PT, Powrie JK, Swaminathan R: Self-monitoring in type 2 diabetes mellitus: a meta-analysis.
Diabet Med
17
:
755
–761,
2000
17.
Montani S, Bellazzi R, Quaglini S, d'Annunzio G. Meta-analysis of the effect of the use of computer-based systems on the metabolic control of patients with diabetes mellitus.
Diabetes Technol Ther
3
:
347
–356,
2001
18.
Gary TL, Genkinger JM, Guallar E, Peyrot M, Brancati FL: Meta-analysis of randomized educational and behavioral interventions in type 2 diabetes.
Diabetes Educ
29
:
488
–501,
2003
19.
Deakin T, McShane CE, Cade JE, Williams RD: Group based training for self-management strategies in people with type 2 diabetes mellitus.
Cochrane Database Syst Rev
18
:
CD003417
,
2005
20.
Shojania KG, Ranji SR, McDonald KM, Grimshaw JM, Sundaram V, Rushakoff RJ, Owens DK: Effects of quality improvement strategies for type 2 diabetes on glycemic control: a meta-regression analysis.
JAMA
296
:
427
–440,
2006
21.
Kirk JK, D'Agostino RB Jr, Bell RA, Passmore LV, Bonds DE, Karter AJ, Narayan KM: Disparities in A1C levels between African-American and non-Hispanic white adults with diabetes: a meta-analysis.
Diabetes Care
29
:
2130
–2136,
2006
22.
Trivedi AN, Zaslavsky AM, Schneider EC, Ayanian JZ: Trends in the quality of care and racial disparities in Medicare managed care.
N Engl J Med
353
:
692
–700,
2005
23.
Sequist TD, Adams A, Zhang F, Ross-Degnan D, Ayanian JZ: Effect of quality improvement on racial disparities in diabetes care.
Arch Intern Med
166
:
675
–681,
2006

Published ahead of print at http://care.diabetesjournals.org on 12 October 2007. DOI: 10.2337/dc07-0565.

The findings and conclusions in this article are those of the authors and do not represent the views of the Centers for Disease Control and Prevention.

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

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C Section 1734 solely to indicate this fact.