Literature DB >> 19808920

Comparison of A1C and fasting glucose criteria to diagnose diabetes among U.S. adults.

April P Carson1, Kristi Reynolds, Vivian A Fonseca, Paul Muntner.   

Abstract

OBJECTIVE: To compare A1C and fasting glucose for the diagnosis of diabetes among U.S. adults. RESEARCH DESIGN AND METHODS: This study included 6,890 adults (> or =20 years of age) from the 1999-2006 National Health and Nutrition Examination Survey without a self-reported history of diabetes who had fasted > or =9 h. A1C > or =6.5% and fasting glucose > or =126 mg/dl were used, separately, to define diabetes.
RESULTS: Overall, 1.8% of U.S. adults had A1C > or =6.5% and fasting glucose > or =126 mg/dl, 0.5% had A1C > or =6.5% and fasting glucose <126 mg/dl, and 1.8% had A1C <6.5% and fasting glucose > or =126 mg/dl. Compared with individuals with A1C <6.5% and fasting glucose > or =126 mg/dl, individuals with A1C > or =6.5% and fasting glucose <126 mg/dl were younger, more likely to be non-Hispanic black, had lower Hb levels, and had higher C-reactive protein.
CONCLUSIONS: A1C > or =6.5% demonstrates reasonable agreement with fasting glucose for diagnosing diabetes among U.S. adults.

Entities:  

Mesh:

Substances:

Year:  2009        PMID: 19808920      PMCID: PMC2797994          DOI: 10.2337/dc09-1227

Source DB:  PubMed          Journal:  Diabetes Care        ISSN: 0149-5992            Impact factor:   19.112


In June 2009, the International Expert Committee released a report that recommended the use of A1C to diagnose diabetes (1). Previously, A1C had been used primarily to monitor glycemic control among individuals with diabetes. However, over the last decade, the A1C measurement has become standardized (2,3), facilitating its recognition as an acceptable diagnostic method for diabetes. Before the release of this report, diabetes was mainly defined using a fasting plasma glucose ≥126 mg/dl (≥7.0 mmol/l) in the U.S (4). Using A1C (≥6.5%) to diagnose diabetes may identify different individuals than fasting plasma glucose because the two methods assess different elements of glucose metabolism (1). The purpose of this study was to compare A1C ≥6.5% and fasting plasma glucose ≥126 mg/dl for the identification of undiagnosed diabetes among participants in the U.S. National Health and Nutrition Examination Survey (NHANES). Additionally, we calculated the demographic characteristics and cardiovascular risk profile for individuals diagnosed with diabetes by each of these methods.

RESEARCH DESIGN AND METHODS

NHANES 1999–2000, 2001–2002, 2003–2004, and 2005–2006 are serial cross-sectional surveys including nationally representative samples of the noninstitutionalized civilian U.S. population identified through a stratified, multistage probability sampling design. Methods for pooling these datasets have been published (5). The current analysis was limited to 6,890 participants without self-reported diabetes who attended a morning examination, fasted for ≥9 h at the time of their blood collection, and had valid plasma glucose and A1C values. Data were collected through questionnaires (demographics, medical history), a physical examination (blood pressure), and blood collection (lipids, plasma glucose, A1C). Plasma glucose was measured using a modified hexokinase enzymatic method and A1C using high-performance liquid chromatography. The coefficient of variation was <3% in each 2-year period for glucose and <2% for A1C. Participants were categorized into one of four mutually exclusive groups by the presence or absence of fasting plasma glucose ≥126 mg/dl and A1C ≥6.5%. The distribution of the population into these groupings was determined. The κ statistic was calculated as a measure of agreement. Characteristics of the study population were calculated for each group with the statistical significance of differences determined using least squares and maximum likelihood estimation for continuous and categorical variables, respectively. In secondary analyses, the distribution of U.S. adults by fasting glucose and different A1C cut-points (6.0–6.7%) were calculated. Also, sensitivity, specificity, positive and negative predictive values, and number of U.S. adults misclassified were calculated using different A1C cut-points. Analyses were weighted to represent the U.S. population and conducted using SUDAAN (version 9; Research Triangle Institute) to account for the complex survey design.

RESULTS

Among U.S. adults, the prevalence of undiagnosed diabetes was 2.3% using A1C and 3.6% using fasting glucose. Moderate agreement existed for A1C and fasting glucose diagnoses (κ = 0.60; 95% CI 0.55–0.64). Diabetes classification was consistent for the majority of the study participants, with 95.9% classified as not having diabetes by both A1C and fasting glucose and 1.8% classified as having diabetes by both A1C and fasting glucose (Table 1). Discordant classifications occurred for 0.5% of participants who had an A1C ≥6.5% and fasting glucose <126 mg/dl and for 1.8% who had an A1C <6.5% and fasting glucose ≥126 mg/dl. Among individuals with an A1C ≥6.5% and fasting glucose <126 mg/dl, 82% had impaired fasting glucose (100–125 mg/dl). Among individuals with an A1C <6.5% and a fasting glucose ≥126 mg/dl, 45% had an A1C value ≥6.0% but <6.5% (i.e., elevated risk for diabetes using the new A1C guidelines).
Table 1

Characteristics of NHANES participants (1999–2006) without self-reported diabetes, by A1C and fasting plasma glucose

A1C <6.5%
A1C ≥6.5%
FPG <126 mg/dlFPG ≥126 mg/dlFPG <126 mg/dlFPG ≥126 mg/dl
n6,54114245162
Prevalence (95% CI)95.9 (95.3–96.5)1.8 (1.5–2.2)0.5 (0.4–0.7)1.8 (1.5–2.1)
Age (years)44.7 ± 0.460.0 ± 1.6*53.1 ± 2.757.2 ± 1.5
Women (%)52.936.339.838.7
Race/ethnicity
    Non-Hispanic white (%)76.2*81.964.959.5
    Non-Hispanic black (%)10.77.425.914.9
    Hispanic (%)13.010.69.325.6
Current smoker (%)23.815.116.522.8
Systolic blood pressure (mmHg)121.3 ± 0.3137.6 ± 1.9130.0 ± 4.5132.3 ± 2.6
Diastolic blood pressure (mmHg)71.1 ± 0.372.0 ± 1.475.8 ± 3.771.2 ± 1.7
Hypertension (%)25.365.252.756.7
BMI (kg/m2)27.9 ± 0.1*31.2 ± 0.634.1 ± 2.532.7 ± 0.8
Waist circumference (cm)95.5 ± 0.3*107.5 ± 1.2112.9 ± 6.5110.1 ± 1.6
Total cholesterol (mg/dl)200.9 ± 0.8198.8 ± 4.8196.5 ± 6.7215.2 ± 5.7
HDL cholesterol (mg/dl)53.4 ± 0.349.1 ± 1.347.7 ± 3.744.3 ± 1.1
Triglycerides (mg/dl)§112 (78–164)147 (106–214)127 (88–151)178 (128–257)
Estimated glomerular filtration rate
    <60 ml/min per 1.73 m27.421.617.015.6
Microalbuminuria (%)7.024.214.729.6
Hb (g/dl)14.6 ± 0.115.0 ± 0.214.3 ± 0.215.1 ± 0.1
Serum albumin (g/dl)4.29 ± 0.014.25 ± 0.044.17 ± 0.084.18 ± 0.03
Ferritin (ng/ml)§67 (31–136)137 (77–253)122 (57–139)219 (96–293)*
Aspartate aminotransferase (units/l)24.9 ± 0.228.3 ± 1.830.0 ± 3.327.7 ± 1.8
Alanine aminotransferase (unites/l)25.6 ± 0.330.7 ± 2.036.2 ± 3.733.6 ± 2.6
C-reactive protein (mg/l)§1.9 (0.7–4.4)2.2 (1.2–6.2)*4.2 (2.1–12.9)4.1 (2.5–9.0)
FPG (mg/dl)95.5 ± 0.3136.9 ± 1.1110.6 ± 2.2199.9 ± 7.7
A1C (%)5.26 ± 0.015.82 ± 0.056.92 ± 0.148.34 ± 0.19

§Data are means ± SE or percent, except variables denoted by §, which are medians (25th to 75th percentiles).

*P < 0.05;

†P < 0.01;

‡P < 0.001 compared with individuals with A1C ≥6.5% and fasting plasma glucose (FPG) <126 mg/dl (after age adjustment).

Characteristics of NHANES participants (1999–2006) without self-reported diabetes, by A1C and fasting plasma glucose §Data are means ± SE or percent, except variables denoted by §, which are medians (25th to 75th percentiles). *P < 0.05; †P < 0.01; ‡P < 0.001 compared with individuals with A1C ≥6.5% and fasting plasma glucose (FPG) <126 mg/dl (after age adjustment). The demographic and cardiovascular profile differed for participants with A1C ≥6.5% and fasting glucose <126 mg/dl compared with individuals with A1C <6.5% and fasting glucose ≥126 mg/dl. Specifically, participants with A1C ≥6.5% and fasting glucose <126 mg/dl were younger, more likely to be non-Hispanic black, had lower Hb, and higher C-reactive protein values. The distribution of adults by fasting glucose and different A1C cut points are available in Table S1 (which is located in an online-only appendix at http://care.diabetesjournals.org/cgi/content/full/dc09-1227/DC1). Overall, lower A1C cut points resulted in higher sensitivity and lower specificity (Table S2).

CONCLUSIONS

The results of the current study indicate the new recommendation by the International Expert Committee to use A1C to diagnose diabetes would result in the same classification as fasting glucose for 97.7% of U.S. adults. For those with discordant results, 0.5% of U.S. adults had A1C ≥6.5% and fasting glucose <126 mg/dl, whereas 1.8% had A1C <6.5% and fasting glucose ≥126 mg/dl. Discordance in the diagnosis of diabetes using A1C and fasting glucose was expected and is likely due to the assessment of different aspects of glucose metabolism (1). For example, participants with an A1C ≥6.5% and fasting glucose <126 mg/dl may have been diagnosed by an oral glucose tolerance test, which was not available for the majority of participants in this study. About 1.8% of U.S. adults had A1C <6.5% and fasting glucose ≥126 mg/dl and would not be classified as having diabetes using the new recommendation. However, as defined using the report's guidelines, almost half of these individuals would be identified as high risk for diabetes based on A1C values between 6.0 and 6.4%. Although these adults would not satisfy the new A1C recommendation for the diagnosis of diabetes, they would be targeted for preventive therapy to reduce diabetes risk, which may also prompt a fasting glucose measurement. Using a lower A1C cut point would result in more diabetes diagnoses among this group; however, there would also be a tradeoff with substantially more diabetes diagnoses among individuals who would have previously been classified as not having diabetes using fasting glucose alone. Subgroup differences were noted in this study, with a higher percentage of individuals diagnosed with diabetes via A1C versus with fasting glucose being non-Hispanic black and of younger age. These differences are similar to previous reports (6–8), but caution should be used when comparing estimates across subgroups because of the limited sample size in this study. In summary, A1C may be an appropriate method for diagnosing diabetes, although clinical implications for using different A1C cut points warrant further investigation.
  7 in total

1.  Report of the expert committee on the diagnosis and classification of diabetes mellitus.

Authors: 
Journal:  Diabetes Care       Date:  2003-01       Impact factor: 19.112

2.  Trends in A1C concentrations among U.S. adults with diagnosed diabetes from 1999 to 2004.

Authors:  Earl S Ford; Chaoyang Li; Randie R Little; Ali H Mokdad
Journal:  Diabetes Care       Date:  2007-10-12       Impact factor: 19.112

Review 3.  Glycated hemoglobin standardization--National Glycohemoglobin Standardization Program (NGSP) perspective.

Authors:  Randie R Little
Journal:  Clin Chem Lab Med       Date:  2003-09       Impact factor: 3.694

4.  International Expert Committee report on the role of the A1C assay in the diagnosis of diabetes.

Authors: 
Journal:  Diabetes Care       Date:  2009-06-05       Impact factor: 17.152

5.  Consensus statement on the worldwide standardization of the hemoglobin A1C measurement: the American Diabetes Association, European Association for the Study of Diabetes, International Federation of Clinical Chemistry and Laboratory Medicine, and the International Diabetes Federation.

Authors: 
Journal:  Diabetes Care       Date:  2007-09       Impact factor: 19.112

6.  Differences in A1C by race and ethnicity among patients with impaired glucose tolerance in the Diabetes Prevention Program.

Authors:  William H Herman; Yong Ma; Gabriel Uwaifo; Steven Haffner; Steven E Kahn; Edward S Horton; John M Lachin; Maria G Montez; Tina Brenneman; Elizabeth Barrett-Connor
Journal:  Diabetes Care       Date:  2007-05-29       Impact factor: 19.112

7.  Elevated A1C in adults without a history of diabetes in the U.S.

Authors:  Elizabeth Selvin; Hong Zhu; Frederick L Brancati
Journal:  Diabetes Care       Date:  2009-02-05       Impact factor: 19.112

  7 in total
  65 in total

1.  Low hemoglobin A1c and risk of all-cause mortality among US adults without diabetes.

Authors:  April P Carson; Caroline S Fox; Darren K McGuire; Emily B Levitan; Martin Laclaustra; Devin M Mann; Paul Muntner
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2010-10-05

2.  Epidemiological ramifications of diagnosing diabetes with HbA1c levels.

Authors:  Mayer B Davidson; Deyu Pan
Journal:  J Diabetes Complications       Date:  2014-04-02       Impact factor: 2.852

3.  Muscle mass index as a predictor of longevity in older adults.

Authors:  Preethi Srikanthan; Arun S Karlamangla
Journal:  Am J Med       Date:  2014-02-18       Impact factor: 4.965

Review 4.  Management of critically ill patients with type 2 diabetes: The need for personalised therapy.

Authors:  Palash Kar; Karen L Jones; Michael Horowitz; Adam M Deane
Journal:  World J Diabetes       Date:  2015-06-10

5.  Implications of the new definition of diabetes for health disparities.

Authors:  Anusha M Vable; Melinda L Drum; Hui Tang; Marshall H Chin; Stacy T Lindau; Elbert S Huang
Journal:  J Natl Med Assoc       Date:  2011-03       Impact factor: 1.798

6.  Community screening for pre-diabetes and diabetes using HbA1c levels in high-risk African Americans and Latinos.

Authors:  Mayer B Davidson; Petra Duran; Martin L Lee
Journal:  Ethn Dis       Date:  2014       Impact factor: 1.847

7.  A1C between 5.7 and 6.4% as a marker for identifying pre-diabetes, insulin sensitivity and secretion, and cardiovascular risk factors: the Insulin Resistance Atherosclerosis Study (IRAS).

Authors:  Carlos Lorenzo; Lynne E Wagenknecht; Anthony J G Hanley; Marian J Rewers; Andrew J Karter; Steven M Haffner
Journal:  Diabetes Care       Date:  2010-06-23       Impact factor: 19.112

8.  Differences in cardiovascular risk profile of diabetic subjects discordantly classified by diagnostic criteria based on glycated hemoglobin and oral glucose tolerance test.

Authors:  Mauro Boronat; Pedro Saavedra; Laura López-Ríos; Marta Riaño; Ana M Wägner; Francisco J Nóvoa
Journal:  Diabetes Care       Date:  2010-08-31       Impact factor: 19.112

9.  Screening for diabetes and pre-diabetes with proposed A1C-based diagnostic criteria.

Authors:  Darin E Olson; Mary K Rhee; Kirsten Herrick; David C Ziemer; Jennifer G Twombly; Lawrence S Phillips
Journal:  Diabetes Care       Date:  2010-07-16       Impact factor: 19.112

10.  Investigating concordance in diabetes diagnosis between primary care charts (electronic medical records) and health administrative data: a retrospective cohort study.

Authors:  Stewart B Harris; Richard H Glazier; Jordan W Tompkins; Andrew S Wilton; Vijaya Chevendra; Moira A Stewart; Amardeep Thind
Journal:  BMC Health Serv Res       Date:  2010-12-23       Impact factor: 2.655

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.