Identifying Adults at High Risk for Diabetes
and Cardiovascular Disease Using
Hemoglobin A1c
National Health and Nutrition Examination Survey
2005–2006
Ronald T. Ackermann, MD, MPH, Yiling J. Cheng, MD, PhD,
David F. Williamson, PhD, Edward W. Gregg, PhD
Background: The American Diabetes Association (ADA) recently proposed the use of hemoglobin
A1c as a practical and valid strategy to identify high-risk people for whom delivery of an intensive
lifestyle intervention to prevent type 2 diabetes is likely to be cost effective.
Purpose: To estimate composite risks of developing diabetes and cardiovascular disease (CVD) for
adults with different hemoglobin A1c test results and to compare those risks with those of adults who
met the 2003 ADA defınition for prediabetes.
Methods: Cross-sectional data from the 2005–2006 National Health and Nutrition Examination
Survey were analyzed in 2009. The method of Stern and colleagues was used to estimate the 7.5-year
probability of type 2 diabetes, and the Framingham General CVD Risk Engine was used to estimate
the 10-year probability of CVD for adults with different A1c results. Sample weights were used to
account for sampling probability and to adjust for noncoverage and nonresponse.
Results: Among adults meeting the 2003 ADA defınition for prediabetes, the probabilities for
incident type 2 diabetes (over 7.5 years) and CVD (over 10 years) were 33.5% and 10.7%, respectively.
Use of A1c alone, in the range of 5.5% to ⬍6.5%, would identify a population with comparable risks
for diabetes (32.4% [SE⫽1.2%]) and CVD (11.4% [SE⫽0.6%]). A slightly higher cutoff (ⱖ5.7%)
would identify adults with risks of 41.3% (SE⫽1.5%) for diabetes and 13.3% (SE⫽0.8%) for CVD—
risks that are comparable to people enrolled in the Diabetes Prevention Program.
Conclusions: A1c-based testing in clinical settings should be considered as a means to identify
greater numbers of adults at high risk of developing type 2 diabetes and CVD.
(Am J Prev Med 2011;40(1):11–17) © 2011 American Journal of Preventive Medicine
I
ntensive lifestyle interventions and select medications are cost effective for delaying or preventing the
development of type 2 diabetes among high-risk
adults.1 Lifestyle interventions offer benefıt by not only
preventing type 2 diabetes but also reducing the burden
of cardiovascular risk factors.2,3 Identifying people who
are at high risk for both type 2 diabetes and cardiovascu-
From the Department of Medicine, Indiana University School of Medicine
(Ackermann), Indianapolis, Indiana; Division of Diabetes Translation
(Cheng, Gregg), CDC; Hubert Department of Global Health, Rollins School
of Public Health, Emory University (Williamson), Atlanta, Georgia
Address correspondence to: Ronald T. Ackermann, MD, MPH, Indiana
University School of Medicine, 410 West 10th Street, Suite 1140, Indianapolis IN 46202. E-mail: [email protected].
0749-3797/$17.00
doi: 10.1016/j.amepre.2010.09.022
© 2011 American Journal of Preventive Medicine. All rights reserved.
lar disease (CVD) is a pivotal step toward maximizing the
cost effectiveness of services to prevent diabetes in both
clinical practice and the community. However, the selection of a particular test to defıne “high risk” can have
tremendous implications for prevalence estimates, health
policies, costs of care, and for individualized decisions
about preventive therapy.
Recent meta-analyses show that adults with fasting
plasma glucose (FPG) concentrations in the range of
110 –125 mg/dL or 2-hour plasma glucose (2hPG) concentrations in the range of 140 –199 mg/dL are at increased risk for the development of both type 2 diabetes4
and CVD.5 Unfortunately, several practical considerations limit the routine use of FPG and 2hPG tests in
primary care settings. Both tests require a patient to reAm J Prev Med 2011;40(1)11–17 11
12
Ackermann et al / Am J Prev Med 2011;40(1):11–17
To address this issue, the present study used crossturn on a separate day after an overnight fast, which is a
sectional data from the 2005–2006 U.S. National Health
barrier to test completion. In the U.S. today, the FPG test
and Nutrition Examination Survey (NHANES) to exremains underutilized and the 2hPG test is rarely per6
plore the associations of A1c with existing models for
formed. As a result, only ⬃7% of American adults with
estimating the composite risks for future CVD and type 2
prediabetes are actually aware of their status.7
diabetes from multiple traditional risk factors in U.S.
Given these challenges, the hemoglobin A1c (A1c) test
adults.19,20 This analysis provides a comparison between
is an attractive alternative for identifying adults at high
risk for type 2 diabetes. The A1c does not require an
the use of A1c and FPG testing for identifying adults with
overnight fast and is already used routinely in primary
high levels of composite risk, as well as the impact on U.S.
care settings to guide therapeutic decisions for patients
prevalence estimates for prediabetes with different possiwith diagnosed diabetes. Recent studies also have
ble A1c test thresholds to defıne high risk.
strengthened the case for expanding the use of A1c to
Methods
identify high-risk people by demonstrating that higher
levels of A1c across the nondiabetic range (i.e., 5.0% to
Study Design and Sample
6.5%) are associated with both a higher prevalence of
The NHANES 2005–2006 surveyed a nationally representative
cardiovascular risk factors8,9 and greater numbers of insample of the civilian, noninstitutionalized U.S. population using a
10 –12
cident cardiovascular events.
stratifıed, multistage probability sampling design with oversamIn June 2009, the International Expert Committee
pling of older people and minority groups. Detailed descriptions of
(IEC), which represents the American Diathe design may be viewed on the National Cenbetes Association (ADA), the European Aster for Health Statistics (NCHS) website.21
Among NHANES respondents who were aged
sociation for the Study of Diabetes, and the
See
ⱖ18 years, 4751 reported no prior diagnosis of
International Diabetes Federation, recomrelated
diabetes. Of those who attended the mobile exmended adoption of the A1c test for the
Commentary by
amination center, 2188 were randomized to a
13
diagnosis of diabetes. The IEC also stated
Geba and
morning session where blood was drawn for the
that “individuals whose A1c values are close
measurement of FPG and 2hPG following a
Pearson in this
to the 6.5% A1c threshold of diabetes (i.e.,
75-g oral glucose challenge. Among this subissue.
6.0%) should receive demonstrably effective
sample, 1896 participants provided specimens
after a recommended fasting interval of 8 –24
[prevention] interventions.” Unfortunately,
hours. After exclusion of people without an A1c
this recommendation does not appear to
test (n⫽7) or for whom missing data prevented
have considered carefully whether a cutoff
calculation of composite risk scores for CVD
of 6.0% would exclude a large proportion of
(n⫽80) or diabetes (n⫽11), 1798 individuals remained. Written
truly high-risk adults. With concern for this possibility,
informed consents were obtained from all participants, and these
the ADA recently recommended use of a lower A1c test
documents were approved by the IRB of the NCHS.
threshold of ⱖ5.7% to identify adults who are at particuMeasures and Data Collection
larly high risk for developing diabetes.14
Although a handful of prospective studies have evalParticipants were interviewed in their homes, and translators were
uated differences in the future development of diabetes
used for participants with low English profıciency. The examination
included height (recorded to the nearest 0.1 cm) and weight with
associated with different A1c test results, these studies
minimal clothing. BMI was calculated by standard formula. Mean
were largely not population-based, used varying methblood pressure was calculated from up to four readings taken in the
ods to defıne diabetes onset, and did not explore difseated position. Hypertension was defıned as a mean blood pressure
ferences in risk associated with small (e.g., 0.1%) increⱖ140/90 mmHg or current use of medication for hypertension. Blood
ments in A1c across a wide range of subdiabetic levels
samples were collected, processed, stored at –20°C, and shipped to the
(5.0%– 6.5%).12,15–18 Many past studies also focused
laboratory for analysis. Plasma glucose concentrations were measured
by a hexokinase method. A1c was measured using a high-performance
largely on whether A1c is an independent predictor of
liquid chromatography analyzer. High cholesterol was defıned as curincident diabetes or cardiovascular events and not
rent use of a cholesterol-lowering medication or low-density lipoprowhether it has utility as a single test for identifying people
tein cholesterol (LDL-c) ⱖ130 mg/dL (or total cholesterol ⱖ200
in whom composite risk is high because of multiple comg/dL if LDL-c was missing).
occurring risk factors. Because a composite risk score can
be challenging to calculate from multiple clinical variConstructed Variables
ables at the point of care, the validation of a single and
The method of Stern and colleagues20 was used to estimate from
readily available test to guide decisions about whether to
individual clinical and demographic risk factors the average proboffer more intensive resources for lifestyle change could
ability (i.e., composite risk) of developing type 2 diabetes after a
advance diabetes prevention efforts.
mean of 7.5 years. This method was selected because it provides a
www.ajpm-online.net
Ackermann et al / Am J Prev Med 2011;40(1):11–17
risk index that is continuously distributed and does not incorporate use of the A1c test. The Framingham General CVD Risk
Engine was used to predict the average probability of developing
one or more general CVDs (i.e., coronary heart disease, stroke,
peripheral arterial disease, or congestive heart failure) over a 10year period.19 This method does not incorporate use of the A1c test
and has been shown to provide reasonably accurate estimates of
CVD risk among people without type 2 diabetes.9 Details about the
calculations used for incident diabetes and CVD are included in
Appendix A (available online at www.ajpm-online.net).
Data Analysis
Because the Stern and Framingham risk scores were developed to
predict incident type 2 diabetes and CVD, analyses were restricted
to adults without previously diagnosed diabetes or CVD. First, the
percentage of the U.S. population with different mid-range A1c
values (5.0%– 6.5%) was estimated, and the mean risk estimates for
CVD and diabetes for different A1c thresholds across this range
were summarized. Second, mean risk estimates for CVD and diabetes were calculated for people who met the 2003 ADA classifıcation for prediabetes (FPG⫽100 –125 mg/dL or 2hPG⫽140 –199
mg/dL)22 and for people who met the evidence-based glycemic
enrollment criteria (FPG⫽95–125 mg/dL and 2hPG⫽140 –199
mg/dL) for entry into the U.S. Diabetes Prevention Program (DPP)
study.23 Because the Stern and Framingham estimations represent
predicted risks and not actual events (i.e., they cannot be considered criterion standards for incident diabetes or CVD), the analysis
did not include calculation of test sensitivity, specifıcity, or area
under the receiver operator characteristic curve.
13
Third, the frequencies of people who met different A1c test
cutoffs were cross-tabulated with the 2003 ADA or DPP clinical
trial defınitions for high risk. Lastly, each of the analytic steps was
repeated after restricting the sample to only those who were overweight or obese (BMIⱖ25 kg/m2) and had either hypertension or
high cholesterol. This subanalysis was performed because the U.S.
Preventive Services Task Force (USPSTF) currently does not recommend population-wide screening to identify prediabetes but
does recommend periodic screening to identify diabetes among
people with evidence of other conditions for which the management would change if diabetes was identifıed.24,25
Statistical analyses used SAS, version 9.1, for data management
and SUDAAN, version 10.0, to calculate SEs, with the Taylor
linearization method used to account for the complex survey design. Sample weights were used in all analyses to account for the
probability of being sampled and to adjust for noncoverage and
nonresponse.
Results
Nonselective A1c Testing to Identify Adults at
High Risk for Diabetes or Cardiovascular Disease
Among all U.S. adults aged ⱖ18 years without selfreported diabetes or prior CVD, 30.0% (SE⫽1.6%) met the
2003 ADA criteria for prediabetes. Within this large
group, the mean predicted probabilities for incident diabetes (over 7.5 years) and CVD (over 10 years) were
33.5% (SE⫽1.0%) and 10.7% (SE⫽0.8%), respectively. Associations of different
A1c test thresholds
Table 1. Predicted risks of type 2 diabetes and CVD by A1c result among U.S. adults
with predicted risk for
diabetes and CVD in
A1c range
Mean A1c 7.5-year probability of type 10-year probability of general
(%)
n
(% [SE])
2 diabetes (% [SE])a
CVD event (% [SE])a
adults without selfreported diabetes or
⬍5.0
239 5.11 (0.09)
15.2 (2.6)
4.6 (0.6)
prior CVD are shown
5.0 to ⬍6.5 1489 5.45 (0.01)
20.5 (0.9)
7.6 (0.4)
in Table 1. These data
5.1 to ⬍6.5 1365 5.49 (0.01)
21.8 (0.9)
8.1 (0.5)
show a nonlinear,
graded relationship of
5.2 to ⬍6.5 1229 5.53 (0.01)
22.9 (0.9)
8.4 (0.5)
A1c with risk for both
5.3 to ⬍6.5 1062 5.59 (0.01)
24.3 (0.9)
9.0 (0.5)
incident diabetes over
5.4 to ⬍6.5
892 5.65 (0.01)
26.8 (0.9)
9.8 (0.5)
7.5 years and incident
5.5 to ⬍6.5
559 5.78 (0.01)
32.4 (1.2)
11.4 (0.6)
CVD over 10 years.
5.6 to ⬍6.5
410 5.85 (0.01)
36.5 (1.6)
12.6 (0.8)
Use of A1c alone, in
the range of 5.5% to
5.7 to ⬍6.5
287 5.93 (0.02)
41.3 (1.5)
13.3 (0.8)
⬍6.5%, would result
5.8 to ⬍6.5
194 6.02 (0.01)
44.7 (2.3)
14.0 (1.2)
in identifıcation of a
6.0 to ⬍6.5
84 6.16 (0.01)
55.9 (4.2)
12.8 (1.0)
subpopulation with
6.2 to ⬍6.5
33 6.28 (0.01)
64.9 (5.5)
14.5 (1.8)
levels of predicted risk
for incident diabetes
ⱖ6.5
35 7.97 (0.31)
88.7 (4.6)
19.4 (3.3)
(32.4% [SE⫽1.2%])
Overall
1798 5.39 (0.02)
19.6 (1.0)
7.1 (0.4)
and CVD (11.4%
a
Estimates reflect risk levels among U.S. adults (aged ⱖ18 years) with no self-reported diabetes and no
[SE⫽0.6%]) that are
self-reported CVD, regardless of FPG or 2hPG result; derived using the Framingham general cardiovascular risk
comparable to those
21,22
as detailed in Appendix A
equation and a diabetes risk prediction model developed by Stern et al.,
of adults meeting the
(available online at www.ajpm-online.net).
2003 ADA criteria.
CVD, cardiovascular disease; FPG, fasting plasma glucose; 2hPG, 2-hour plasma glucose
January 2011
Ackermann et al / Am J Prev Med 2011;40(1):11–17
14
After excluding people with self-reported
diabetes or prior CVD,
⬃10.2% (SE⫽1.1%) of
U.S. adults met the
more-focused highrisk glycemic criteria
required for enrollment in the DPP.
Within this group, the
mean risks for incident diabetes (over 7.5
years) and CVD (over
10 years) were 42.2%
(SE⫽2.8%) and 13.6%
(SE⫽1.4%), respectively. Use of A1c in
the range of 5.7% to
⬍6.5% (Table 1) would
result in identifıcation
of a population with a
similar predicted risk
for incident diabetes
(41.3% [SE⫽1.5%])
and CVD (13.3% [SE⫽
0.8%]).
Table 2. Predicted risks of type 2 diabetes and CVD by A1c result among overweight or
obese U.S. adults with high blood pressure or high cholesterol
A1c range
(%)
n
Mean A1c
(% [SE])
⬍5.0
65
4.79 (0.02)
18.2 (3.7)
7.1 (1.5)
5.0 to ⬍6.5
572
5.55 (0.02)
31.9 (1.2)
11.1 (0.7)
5.1 to ⬍6.5
547
5.57 (0.01)
32.9 (1.1)
11.4 (0.7)
5.2 to ⬍6.5
505
5.61 (0.02)
33.9 (1.2)
11.7 (0.7)
5.3 to ⬍6.5
455
5.65 (0.01)
34.4 (1.2)
12.0 (0.7)
5.4 to ⬍6.5
414
5.69 (0.02)
36.1 (1.3)
12.4 (0.8)
5.5 to ⬍6.5
289
5.82 (0.02)
41.3 (1.7)
13.9 (0.9)
5.6 to ⬍6.5
229
5.89 (0.02)
44.9 (1.8)
14.7 (1.2)
5.7 to ⬍6.5
171
5.96 (0.02)
48.4 (2.1)
15.3 (0.8)
5.8 to ⬍6.5
121
6.05 (0.01)
51.6 (3.1)
15.2 (1.2)
6.0 to ⬍6.5
62
6.18 (0.01)
60.4 (3.4)
13.8 (1.1)
6.2 to ⬍6.5
27
6.29 (0.01)
68.1 (4.9)
15.2 (1.8)
ⱖ6.5
25
7.84 (0.37)
94.8 (1.2)
22.3 (4.2)
662
5.56 (0.02)
32.8 (1.3)
11.2 (0.7)
Overall
7.5-year probability of type 10-year probability of general
2 diabetes (% [SE])a
CVD event (% [SE])a
Estimates reflect risk levels among U.S. adults (aged ⱖ18 years) in a high risk–factor subgroup (BMIⱖ25 and
evidence of either high blood pressure or high cholesterol) who have no self-reported diabetes and no
self-reported CVD, regardless of FPG or 2hPG result; derived using the Framingham general cardiovascular risk
equation and a diabetes risk prediction model developed by Stern and colleagues,21,22 as detailed in
Appendix A (available online at www.ajpm-online.net).
CVD, cardiovascular disease; FPG, fasting plasma glucose; 2hPG, 2-hour plasma glucose
a
Targeted A1c
Testing to
Identify Adults at
High Risk for Diabetes or Cardiovascular
Disease
Predicted risk levels for incident diabetes and CVD were
higher when testing was applied only to adults with a BMI
ⱖ25 kg/m2 who also had evidence of either high blood
pressure or high cholesterol. After excluding people with
self-reported diabetes or prior CVD, an estimated 42.4%
(SE⫽2.5%) of adults in this targeted subgroup met the
2003 ADA criteria for prediabetes. Among this high-risk
group, the mean predicted risks for incident diabetes
(over 7.5 years) and CVD (over 10 years) were 43.2%
(SE⫽1.1%) and 13.4% (SE⫽1.3%), respectively. Targeted
testing with the use of A1c alone, in the range of 5.5% to
⬍6.5%, would identify people with comparable levels
of predicted risk for incident diabetes (41.3%
[SE⫽1.7%]) and CVD (13.9% [SE⫽0.9%]; Table 2).
Impact of A1c Use on Estimates of High-Risk
Prevalence Among U.S. Adults
Without excluding people with self-report diabetes or
prior CVD, 33.9% (SE⫽1.7%) of the U.S. adult population met the 2003 ADA criteria for prediabetes (Table 3).
If people who have an A1c of 5.5% to ⬍6.5% are also
considered high-risk, the total prevalence would increase
to 47.2% (SE⫽1.7%). This larger group would be made up
of 13.3% of adults meeting only the A1c criteria, 16.9%
meeting only the 2003 ADA criteria, and 17.0% meeting
both. Conversely, if people who have an A1c of 5.7% to
⬍6.5% are considered high-risk, the total prevalence
would increase to 39.1% (SE⫽1.7%). This larger group
would be made up of 5.2% of adults meeting only the A1c
criteria, 23.9% meeting only the 2003 ADA criteria, and
10.0% meeting both.
Conclusion
A large majority of people who would meet the 2003 ADA
classifıcation for prediabetes are unaware of their risk
because of challenges to performing FPG and 2hPG tests
routinely.6,7 A simpler form of high-risk testing could
improve diabetes prevention efforts by substantially increasing the numbers of individuals who complete testing. The current study indicates that the A1c test may
provide a badly needed, clinically practical indicator of
the composite risk for incident diabetes and CVD.
Within a test range of 5.5% to ⬍6.5%, the A1c test identifıes a population with levels of predicted risk for future
www.ajpm-online.net
Ackermann et al / Am J Prev Med 2011;40(1):11–17
Table 3. Percentages of U.S. adults who would be
classified as “high-risk” when using different A1c test
ranges
A1c testing
only
(% [SE])a
Meeting either
the 2003 ADA
criteria for
prediabetesb or
elevation of A1c
(% [SE])
5.0 to ⬍6.5
83.6 (1.0)
85.9 (1.0)
5.1 to ⬍6.5
76.4 (1.0)
80.4 (0.9)
5.2 to ⬍6.5
69.2 (1.3)
75.2 (1.2)
5.3 to ⬍6.5
59.2 (1.3)
67.3 (1.6)
5.4 to ⬍6.5
49.1 (1.3)
60.1 (1.8)
5.5 to ⬍6.5
30.3 (1.3)
47.2 (1.7)
5.6 to ⬍6.5
22.3 (1.0)
42.3 (1.8)
5.7 to ⬍6.5
15.2 (0.6)
39.1 (1.7)
5.8 to ⬍6.5
9.7 (0.8)
37.3 (1.6)
6.0 to ⬍6.5
4.6 (0.7)
35.1 (1.8)
6.2 to ⬍6.5
1.5 (0.2)
34.3 (1.7)
A1c test range (%)
No use of A1c (2003
ADA criteria alone)
N/A
33.9 (1.6)
Note: Values within parentheses are SEs.
a
Estimates reflect the percentage of all U.S. adults aged ⱖ18 years
with an A1c in the specified range, regardless of the FPG or 2hPG
test result.
b
Estimates reflect the percentage of all U.S. adults aged ⱖ18 years
who meet any one of the following criteria: (1) A1c in the specified
range and 2-hour postchallenge plasma glucose ⬍200 mg/dL and
FPG ⬍126 mg/dL; or (2) FPG 100 –125 mg/dL and 2-hour postchallenge plasma glucose ⬍200 mg/dL and A1c⬍6.5% or (3) 2-hour
postchallenge plasma glucose 140 –199 mg/dL and FPG ⬍126
mg/dL and A1c⬍6.5%.
ADA, American Diabetes Association; FPG, fasting plasma glucose;
2hPG, 2-hour plasma glucose
diabetes and CVD that are similar to people identifıed by
the 2003 ADA classifıcation criteria for prediabetes. This
concordance of risk persists regardless of whether casefınding efforts target a general population or focus on
high-risk subgroups that are similar to those recommended by the USPSTF.25
An additional important fınding of the present study is
that A1c testing identifıes some high-risk people who
would not have been identifıed by currently recommended strategies that are based on FPG and 2hPG results alone. The ADA recently recommended a new definition for high-risk individuals that includes everyone
meeting the 2003 ADA defınition for prediabetes or those
with A1c of 5.7% to ⬍6.5%. This defınition increases the
total prevalence of high-risk Americans from 33.9% to an
estimated 39.1% of the U.S. adult population.
January 2011
15
When evaluating strategies to classify people at high
risk, it is important to consider whether those strategies
identify people for whom preventive interventions are
likely to be most cost effective. Although the ADA defıned prediabetes in 2003 to include people with either a
2hPG between 140 and 199 mg/dL or an FPG between
100 and 125 mg/dL, people with elevated FPG alone (i.e.,
2hPG ⬍140 mg/dL) have not been included in most
randomized prevention trials to date26 and are at lower
risk for future diabetes and CVD than participants in
those studies. In this context, a decision regarding the
most appropriate A1c range for identifying high-risk
people should probably not be based on estimates of risk
for people with only modestly elevated FPG 100 –109
mg/dL and no elevation of 2hPG. This analysis found that
an A1c test threshold of ⱖ5.7% identifıes people for
whom the predicted risk for diabetes and CVD are comparable to those who meet the DPP enrollment criteria of
both elevated fasting glucose and IGT.
This research has some limitations. First, crosssectional data were used to predict the probability of
future diabetes and CVD. These predictions should be
interpreted as indicators of the aggregate risk imposed by
multiple co-occurring risk factors among people with
different levels of A1c and not as exact estimates of future
event prevalence. Actual event prevalence may be higher
or lower than predicted. Second, the Stern method was
derived using data from participants in the San Antonio
Heart Study,20 which enrolled a proportionately large
number of Mexican Americans and excluded adults aged
⬍25 years and ⬎64 years. The Framingham Study enrolled a predominantly non-Hispanic white population
and excluded adults aged ⬍30 years and ⬎74 years.19
Both methods may have lower predictive validity in other
population subgroups. Unfortunately, no alternative
published prediction models were identifıed for either
diabetes or CVD that do not incorporate the A1c result in
the estimation and have been validated across a broader
array of population subgroups.
Third, the present study did not evaluate (because of
limited sample sizes) whether the predictive value of A1c
test cutoffs varies across different population subgroups.
One recent study27 found that older adults are more likely
to meet the 2hPG criterion for high risk compared to
younger adults. This suggests that the identifıcation of
high-risk people by only one form of testing can vary by
age and that it would be prudent to encourage FPG or
2hPG testing in adults with multiple risk factors who are
found to have a subthreshold A1c result. In another recent publication,28 average A1c levels at the time of
screening for the DPP were 0.4% higher among AfricanAmerican adults with IGT than in their non-Hispanic
16
Ackermann et al / Am J Prev Med 2011;40(1):11–17
white counterparts, even after adjusting for differences in
other characteristics.
This fınding implies that use of a single A1c cutoff
would identify greater numbers of African Americans
than using only FPG or 2hPG testing. It has been
hypothesized that A1c levels in some racial-minority
groups might be elevated, in part, because of undiagnosed disorders of hemoglobin glycation or red cell
survival. However, it is still unclear whether adults of
minority race/ethnicity are at higher or lower overall
risk for diabetes and CVD events when compared to
non-Hispanic whites with the same level of A1c. Last,
decisions to expand efforts that identify people at high
risk for developing type 2 diabetes presume that those
individuals will benefıt from knowing their risk. However, these efforts may be premature unless parallel
efforts are undertaken to expand the availability of
prevention programs that will support high-risk people in efforts to reduce their risk.
In summary, A1c-based testing appears to have
value for identifying adults who are at high predicted
risk for the future development of type 2 diabetes and
CVD. Because of its practical nature and wide availability, A1c-based testing should be considered as a
means to identify greater numbers of high-risk adults
in clinical settings. If one important goal is to approximate the composite risk for diabetes and CVD among
people who are already included in the 2003 ADA
defınition for prediabetes, then A1c ⱖ5.5% is a suitable
test threshold for defıning high risk. Alternatively, if
the goal is to approximate composite risk levels among
people enrolled in previous prevention trials such as
the DPP, then a test threshold of ⱖ5.7% may be more
appropriate. Recommendations to use A1c in the identifıcation of adults at high risk for type 2 diabetes will
alter the current prevalence estimates for high risk in
the population. Though important, this concern
should remain secondary to the importance of adopting the A1c test as a practical strategy for identifying
the large population of high-risk individuals who remain unidentifıed today and for whom evidencebased preventive interventions are likely to be cost
effective.
Support for this research was provided by the CDC and the
Robert Wood Johnson Foundation Physician Faculty Scholars
Program (Grant 57398). The fındings and conclusions in this
report are those of the authors and do not necessarily represent
the offıcial positions of the CDC.
No fınancial disclosures were reported by the authors of this
paper.
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Appendix
Supplementary data
Supplementary data associated with this article can be found, in the
online version, at doi:10.1016/j.amepre.2010.09.022.
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