Content uploaded by Wolfgang Rathmann
Author content
All content in this area was uploaded by Wolfgang Rathmann on Feb 02, 2017
Content may be subject to copyright.
Prevalence of Polyneuropathy in Pre-
Diabetes and Diabetes Is Associated With
Abdominal Obesity and Macroangiopathy
The MONICA/KORA Augsburg Surveys S2 and S3
DAN ZIEGLER,
MD, PHD, FRCPE
1
WOLFGANG RATHMANN,
MD, MSPH
2
THORSTEN DICKHAUS,
MSC
2
CHRISTA MEISINGER,
MD, MPH
3
ANDREAS MIELCK,
PHD, MPH
4
FOR THE KORA STUDY GROUP
OBJECTIVE — It is controversial whether there is a glycemic threshold above which poly-
neuropathy develops and which are the most important factors associated with polyneuropathy
in the general population. The aim of this study was to determine the prevalence and risk factors
of polyneuropathy in subjects with diabetes, impaired fasting glucose (IFG), impaired glucose
tolerance (IGT), or normal glucose tolerance (NGT).
RESEARCH DESIGN AND METHODS — Subjects with diabetes (n⫽195) and control
subjects matched for age and sex (n⫽198) from the population-based MONICA (Monitoring
Trends and Determinants on Cardiovascular Diseases)/KORA (Cooperative Research in the
Region of Augsburg) Augsburg Surveys 1989/1990 (S2) and 1994/1995 (S3) aged 25–74 years
were contacted again and assessed in 1997/1998 by the Michigan Neuropathy Screening Instru-
ment using a score cut point ⬎2. An oral glucose tolerance test was performed in the control
subjects.
RESULTS — Among the control subjects, 46 (23.2%) had IGT, 71 (35.9%) had IFG, and 81
had NGT. The prevalence of polyneuropathy was 28.0% in the diabetic subjects, 13.0% in those
with IGT, 11.3% in those with IFG, and 7.4% in those with NGT (Pⱕ0.05 for diabetes vs. NGT,
IFG, and IGT). In the entire population studied (n⫽393), age, waist circumference, and diabetes
were independent factors significantly associated with polyneuropathy, whereas in the diabetic
group polyneuropathy was associated with age, waist circumference, and peripheral arterial
disease (PAD) (all P⬍0.05).
CONCLUSIONS — The prevalence of polyneuropathy is slightly increased in individuals
with IGT and IFG compared with those with NGT. The association with waist circumference and
PAD suggests that the latter and abdominal obesity may constitute important targets for strategies
to prevent diabetic polyneuropathy.
Diabetes Care 31:464–469, 2008
D
iabetic polyneuropathy affects 54
per 100,000 people a year in the
community and represents the
third most common neurological disorder,
surpassed only by cerebrovascular events
and shingles (1). Our understanding of
the epidemiology of the distal symmetric
sensory or sensorimotor polyneuropathy,
one of the most frequent diabetes compli-
cations, has been made difficult due to
inconsistency in the selection of diagnos-
tic procedures and referral bias (2). Nu-
merous studies described the prevalence
or incidence in hospital- or clinic-based
populations, which may bias toward
those patients who are more severely af-
fected (3–7). However, it is important
that the populations studied are represen-
tative of the total population being con-
sidered and have not been subjected to
significant selection biases (2).
Previous population-based studies
have reported prevalence rates for poly-
neuropathy ranging from 8 to 54% in type
1 diabetic patients and from 13 to 46% in
type 2 diabetic patients (8–20). Apart
from inherent ethnic differences, these
wide ranges may be explained by the dif-
fering criteria and diagnostic tests used to
define and characterize polyneuropathy.
The risk factors most consistently associ-
ated with polyneuropathy in type 2 dia-
betic patients at the population level were
increasing age, duration of diabetes,
height, and poor glycemic control evi-
denced by A1C as well as presence of ret-
inopathy and nephropathy (21–23).
Divergent or scant data have been re-
ported for the role of diabetes type, insu-
lin treatment, hypoinsulinemia, sex,
hypertension, ethnicity, cigarette smok-
ing, and alcohol use (8–23).
In contrast, frequent comorbidities of
type 2 diabetes such as the further com-
ponents of the metabolic syndrome, i.e.,
abdominal obesity and dyslipidemia,
were not hitherto identified as risk factors
for polyneuropathy in type 2 diabetes. In
type 1 diabetic subjects, low HDL choles-
terol was associated with prevalent poly-
neuropathy (24), and hypertension was a
●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●
From the
1
Institute for Clinical Diabetes Research, German Diabetes Center, Leibniz Institute at the Heinrich
Heine University, Du¨ sseldorf, Germany; the
2
Institute of Biometrics and Epidemiology, German Diabetes
Center, Du¨ sseldorf, Germany; the
3
Institute of Epidemiology, Helmholtz Zentrum Mu¨ nchen - German
Research Center for Environmental Health, Neuherberg, Germany; and the
4
Institute of Health Economics
and Health Care Management, Helmholtz Zentrum Mu¨ nchen - German Research Center for Environmental
Health, Neuherberg, Germany.
Address correspondence and reprint requests to Dr. Dan Ziegler, FRCPE, Institut fu¨ r Klinische Diabe-
tologie, Deutsches Diabetes-Zentrum, Leibniz-Zentrum an der Heinrich-Heine-Universita¨ t, Auf’m Hen-
nekamp 65, 40225 Du¨ sseldorf, Germany. E-mail: dan.ziegler@ddz.uni-duesseldorf.de.
Received for publication 12 September 2007 and accepted in revised form 16 November 2007.
Published ahead of print at http://care.diabetesjournals.org on 26 November 2007. DOI: 10.2337/dc07-
1796.
Abbreviations: CIAP, chronic idiopathic axonal polyneuropathy; IGT, impaired glucose tolerance; IFG,
impaired fasting glucose; KORA, Cooperative Research in the Region of Augsburg; MONICA, Monitoring
Trends and Determinants on Cardiovascular Diseases; MNSI, Michigan Neuropathy Screening Instrument;
NGT, normal glucose tolerance; OGTT, oral glucose tolerance test; PAD, peripheral arterial disease.
© 2008 by the American Diabetes Association.
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.
Epidemiology/Health Services Research
ORIGINAL ARTICLE
464 DIABETES CARE,VOLUME 31, NUMBER 3, MARCH 2008
predictor of incident polyneuropathy
(25). Moreover, in a center-based study in
type 1 diabetic patients, triglycerides,
BMI, and hypertension were identified as
risk factors for incident polyneuropathy
(7).
There is now major interest in pre-
diabetes and the closely related metabolic
syndrome, which are highly prevalent
and enhance the risk of diabetes and ma-
crovascular disease, but controversial dis-
cussion has recently emerged as to
whether impaired glucose tolerance (IGT)
may cause polyneuropathy (26–29).
Some epidemiological studies have re-
ported that the prevalence of polyneurop-
athy is higher in individuals with IGT
compared with those with normal glucose
tolerance (NGT) (10,30), while others
could not confirm such an association
(9,13,31). On the other hand, several un-
controlled observational studies sug-
gested that the chronic idiopathic axonal
polyneuropathy (CIAP) is associated with
IGT (27,32,33). It has been hypothesized
that some components of the metabolic
syndrome may play a causative role in
neuropathy both for those with pre-
diabetes and for those with otherwise id-
iopathic neuropathy (27,33). However,
glucose intolerance is common in the el-
derly population, and the only study in-
cluding a control group could not
confirm an association between CIAP and
IGT (34). The aim of the present study
was to determine the prevalence and risk
factors of polyneuropathy in subjects
with diabetes and those with IGT and
NGT in the general population.
RESEARCH DESIGN AND
METHODS — The independent pop-
ulation-based MONICA (Monitoring
Trends and Determinants on Cardiovas-
cular Diseases)/KORA (Cooperative Re-
search in the Region of Augsburg)
Augsburg surveys were part of the multi-
national World Health Organization
MONICA project (35). The second
MONICA Augsburg Survey 1989/1990
(S2) included 4,940 people (participation
76.9%), while the third MONICA Augs-
burg Survey 1994/1995 (S3) included
4,856 people (participation: 74.9%) aged
25–74 years. The surveys were approved
by the local authorities. All participants
gave written informed consent. Subjects
were classified as having diabetes if they
reported a diagnosis of diabetes or if they
were taking antidiabetes medication. All
diabetic subjects from the S2 and S3 sur-
veys as well as nondiabetic subjects
matched (1:1) for age and sex were in-
vited again in March 1997 and assessed
until July 1998 for the presence of chronic
diabetes complications including poly-
neuropathy. Included in the present
study were cases defined as those who
were invited as diabetic and confirmed as
being diabetic based on self-reports (n⫽
201). Among the diabetic subjects, six
were excluded due to an incomplete data-
set, leaving 195 patients in the final anal-
ysis. An oral glucose tolerance test
(OGTT) was performed in those who had
been invited as nondiabetic control sub-
jects. Age- and sex-matched control sub-
jects were defined as those who were
invited as nondiabetic and confirmed in
the OGTT as nondiabetic (n⫽198).
Thus, the entire population studied in-
cluded 393 subjects, of whom 185 origi-
nated from S2 and 208 from S3. In the
nondiabetic group, 81 individuals had
NGT, 71 had impaired fasting glucose
(IFG), and 46 had IGT. Excluded were
those who were invited as diabetic but
self-confirmed as control subjects (n⫽
16) as well as those invited as control sub-
jects but confirmed as new diabetic (n⫽
23) in the OGTT.
Blood pressure, body height, and
body weight were determined by trained
medical staff (mainly nurses). All mea-
surement procedures have been de-
scribed in detail elsewhere (36–38).
Information concerning sociodemo-
graphic variables and cardiovascular risk
factors was assessed by standardized per-
sonal interviews. BMI was calculated as
weight in kilograms divided by the square
of height in meters. A regular smoker was
defined as a subject who regularly
smoked at least one cigarette per day. Al-
cohol consumption on the previous
workday and during the previous week-
end was calculated in grams per day. High
alcohol intake was defined as ⱖ40 g/day
in men and ⱖ20 g/day in women. The
physical activity level was estimated by
means of two separate four-category in-
terview questions asking about the time
per week spent on sports activities during
leisure time in summer and winter. The
winter and summer responses were com-
bined to define one sport variable,
whereby a participant was considered
physically active if he or she participated
in sports in summer and in winter for
more than 1 h/week in at least one season.
A participant was classified as inactive if
he or she was less active during leisure
time. Prevalent cardiovascular disease
was defined as the need for hospital treat-
ment for myocardial infarction or stroke
(38). Total serum cholesterol and HDL
and LDL cholesterol levels were measured
by enzymatic methods (CHOD-PAP;
Boehringer, Mannheim, Germany). Serum
creatinine was measured by the para-
aminophenazone (PAP) method (Boehr-
inger). Urinary albumin (in milligrams per
liter) was determined in a random morning
urine sample using an immunoturbidimet-
ric test (Tina-quant; Boehringer).
OGTTs were carried out in the morn-
ing (7:00 A.M. to 11:00 A.M.) according to
the World Health Organization protocol
as previously described (39). Participants
were asked to fast for 10 h overnight, to
avoid heavy physical activity on the day
before examination, and to refrain from
smoking before and during the test. Fast-
ing venous blood glucose was sampled,
and 75 g anhydrous glucose was given
(Dextro OGT; Boehringer). IFG was de-
fined using a cut point for plasma glucose
of 100–125 mg/dl according to American
Diabetes Association criteria (40).
The presence or absence of polyneu-
ropathy was determined by the Michigan
Neuropathy Screening Instrument
(MNSI) using a score cut point ⬎2, as
previously described (41). The clinical
examination portion of this tool takes into
account the inspection of the feet (defor-
mities, dry skin, callus, infection), pres-
ence or absence of foot ulceration, ankle
reflexes, and vibration perception thresh-
old at the great toe, which was measured
by the calibrated Rydel Seiffer tuning
fork. In addition, the MNSI questionnaire
consisting of 15 questions addressing
positive symptoms of polyneuropathy
was used.
Peripheral arterial disease (PAD) was
assessed using a Mini Dopplex device
(HNE Healthcare, Hilden, Germany) and
defined by a ankle brachial index ⬍0.9.
This cut point has a sensitivity of 95% for
the presence of PAD documented by an-
giography (42).
Statistical analysis
Continuous data were expressed as the
mean ⫾SD or geometric mean ⫻/⫼stan-
dard deviation factor (SDF). For continu-
ous variables satisfying a normal
distribution assumption, an ANOVA (F
test) for the comparison of the four
groups was performed. For log-normal
variables, the ANOVA was carried out on
the log scale. Binomial proportions were
compared using Fisher’s exact test. The
polyneuropathy score was analyzed
nonparametrically by performing the
Ziegler and Associates
DIABETES CARE,VOLUME 31, NUMBER 3, MARCH 2008 465
Kruskal-Wallis test. Associations be-
tween variables were analyzed both in
the entire population studied and in the
diabetic group using a stepwise proce-
dure with MNSI ⬎2 as the dependent
variable: 1) univariate logistic regres-
sion models where age, sex, height,
weight, BMI, waist and hip circumfer-
ence, systolic blood pressure, smoking,
physical activity, alcohol consumption,
creatinine, albuminuria, myocardial in-
farction, stroke, PAD, total cholesterol,
LDL cholesterol, HDL cholesterol, trig-
lycerides, IGT, diabetes, duration of di-
abetes, A1C, fasting blood glucose, and
2-h blood glucose in the OGTT were
used as independent variables; 2) mul-
tivariate logistic regression models; 3)
stepwise and backward regression mod-
els; and 4) final multivariate logistic re-
gression models including age, sex,
height, weight, waist circumference,
physical activity, creatinine, albumin-
uria, duration of diabetes, A1C, IGT, di-
abetes, and PAD. The level of significance
was set at ␣⫽0.05. The SAS statistical
package version 8.2 TS2M0 was used for
all analyses.
RESULTS — The demographic vari-
ables of the subjects with NGT, IFG, IGT,
and diabetes are shown in Table 1. There
was a significant and steady increase in
the sequence from NGT to IFG, IGT, and
diabetes in BMI, waist circumference, sys-
tolic blood pressure, A1C, albuminuria,
and the prevalence of polyneuropathy,
whereas HDL cholesterol showed a corre-
sponding decrease (all P⬍0.05). More-
over, significant differences between the
four groups studied were noted for age,
height, the proportions of smokers, per-
sons with PAD, and absent ankle reflexes
and in those with high alcohol consump-
tion and low physical activity (all P⬍
0.05). Fasting and 2-h glucose in the
OGTT were significantly different be-
tween those with NGT, IFG, and IGT
(P⬍0.05). No significant differences be-
tween the groups were observed for sex,
LDL cholesterol, creatinine, and the pro-
portion of individuals with stroke, burn-
ing pain, allodynia, and foot ulcers in the
lower limbs.
Among the diabetic subjects, 12 and
135 had type 1 and type 2 diabetes, re-
spectively, and 6 had secondary diabetes,
and in 42 subjects the diabetes type was
not known. Diabetes treatment included
oral antidiabetic agents in 86 (44.1%), in-
sulin in 44 (22.6%), oral antidiabetic
agents and insulin in 42 (21.5%), and diet
only in 23 subjects (11.8%). Cardiovas-
cular medications across the four groups
studied included ACE inhibitors in a
mean 6.6% (range 4.7–8.0), -blocking
agents in 4.6% (2.1–9.1), calcium chan-
nel blockers in 5.2% (3.9–5.8), diuretics
in 5.6% (5.2–6.3), and lipid-lowering
drugs in 2.9% (2.6–3.1) of the subjects.
According to the above definition, the
prevalence (95% CI) of polyneuropathy
was 28.0% (21.5–34.5) in the diabetic
subjects, 11.3% (5.0–31.0) in those with
IFG, 13.0% (4.9 –26.3) in those with IGT,
and 7.4% (2.8–15.4) in those with NGT.
The percentage differences (95% CI) in
prevalence adjusted for multiplicity were:
diabetes minus IGT, 15% (0–30); diabe-
tes minus IFG, 17% (4–29); diabetes mi-
nus NGT, 21% (9–32); IGT minus IFG,
2% (⫺14 to 18); IGT minus NGT, 6%
(⫺9 to 20); and IFG minus NGT, 4% (⫺8
to 16).
In the univariate regression models
including the entire population studied,
significant differences between those with
and without polyneuropathy were noted
for the following variables: age, OR 1.08
(95% CI 1.05–1.12); waist circumfer-
ence, 1.03 (1.01–1.05); low physical ac-
tivity, 0.40 (0.21–0.78); PAD, 3.26
(1.65–6.45); diabetes, 3.99 (1.99–7.99);
Table 1—Demographic and clinical variables of the subjects from the MONICA/KORA Augsburg Surveys (S2 and S3)
NGT IFG IGT Diabetes Overall P
n81 71 46 195 —
Sex (m/f) 43/38 45/26 23/23 110/85 0.47*
Age (years) 63.6 ⫾9.3 66.6 ⫾8.1 69.3 ⫾7.8 66.8 ⫾9.4 0.004†
Height (cm) 166.3 ⫾9.2 169.1 ⫾9.3 165.8 ⫾9.4 164.6 ⫾9.0 0.006†
BMI (kg/m
2
)26.7 ⫾2.9 27.4 ⫾5.2 29.0 ⫾4.4 29.6 ⫾4.6 ⬍0.001†
Waist circumference (cm) 91.9 ⫾10.1 96.0 ⫾11.4 99.0 ⫾12.7 100.0 ⫾12.5 ⬍0.001†
Systolic blood pressure (mmHg) 134 ⫾20.5 140 ⫾21.3 147 ⫾23.7 149 ⫾20.9 ⬍0.001†
Fasting glucose (mg/dl) 92.3 ⫾6.7 107.7 ⫾6.4 107.6 ⫾9.1 — ⬍0.001†
2-h glucose (mg/dl) 98.7 ⫾19.9 104.4 ⫾18.9 160.6 ⫾15.8 — ⬍0.001†
A1C (%) 5.0 ⫾0.3 5.2 ⫾0.6 5.2 ⫾0.4 7.3 ⫾1.8 ⬍0.001†
LDL cholesterol (mg/dl) 143.4 ⫾34.9 151.5 ⫾39.1 145.3 ⫾36.4 141.2 ⫾38.2 0.27†
HDL cholesterol (mg/dl) 59.5 ⫾16.9 58.1 ⫾17.5 56.8 ⫾13.5 48.6 ⫾14.7 ⬍0.001†
Creatinine (mg/dl) 0.81 ⫻/⫼1.21 0.83 ⫻/⫼1.22 0.85 ⫻/⫼1.22 0.88 ⫻/⫼1.36 0.053‡
Albuminuria (mg/l) 6.10 ⫻/⫼3.79 9.13 ⫻/⫼4.36 12.69 ⫻/⫼4.06 30.12 ⫻/⫼8.27 ⬍0.001‡
Smoking (%) 7.4 18.3 2.2 9.7 0.031*
Alcohol (%) 10.0 26.8 8.7 6.7 ⬍0.001*
Low physical activity (%) 45.7 32.4 32.6 20.0 ⬍0.001*
Stroke (%) 5.1 2.8 4.3 10.4 0.143*
PAD (ABI ⬍0.9) (%) 3.7 8.5 2.2 16.2 0.0021*
Polyneuropathy (MNSI ⬎2) (%) 7.4 11.3 13.0 28.0 ⬍0.001§
Burning pain feet/legs (%) 9.9 11.3 10.9 15.5 0.619*
Allodynia feet (%) 2.5 4.2 10.9 10.3 0.063*
Absent ankle reflexes (%) 3.8 4.2 0 20.1 ⬍0.001*
Foot ulcer present (%) 0 0 2.2 4.1 0.089*
Data are means ⫾SD and geometric mean ⫻/⫼SDF (standard deviation factor). ABI, ankle brachial index. *Fisher’s exact test, †F-test, ‡log F-test, §Kruskal-Wallis
test.
Polyneuropathy in pre-diabetes and diabetes
466 DIABETES CARE,VOLUME 31, NUMBER 3, MARCH 2008
fasting glucose, 1.00 (1.00–1.01); A1C,
1.21 (1.06–1.38); log triglycerides, 1.61
(1.09–2.38); log creatinine, 5.78 (2.23–
14.97); and log albuminuria, 1.24 (1.09–
1.42). No differences were observed for
male sex, height, weight, BMI, hip cir-
cumference, systolic blood pressure,
smoking, alcohol intake, myocardial in-
farction, stroke, IGT, 2-h glucose, total
cholesterol, LDL cholesterol, and HDL
cholesterol.
The final mutivariate logistic regres-
sion models included age, male sex,
height, weight, waist circumference, low
physical activity, log creatinine, log albu-
minuria, A1C, IGT, diabetes, and PAD.
The independent variables remaining in
the final multiple logistic regression mod-
els with polyneuropathy (MNSI ⬎2) as
dependent variable are listed in Table 2.
In the entire population studied, age,
waist circumference, and diabetes were
significantly associated with polyneurop-
athy (all P⬍0.05), whereas the relation-
ship with PAD reached borderline
significance (P⫽0.099). In the diabetic
subjects, independent associations with
polyneuropathy were noted for age, waist
circumference, and PAD (all P⬍0.05),
whereas duration of diabetes did not
reach statistical significance (P⫽0.29).
CONCLUSIONS — The results of
this study demonstrate that in the general
population the prevalence of polyneurop-
athy is slightly higher in persons with IGT
than in those with NGT and more than
twofold higher in subjects with diabetes
compared with those with IGT. We fur-
ther show for the first time that the prev-
alence of polyneuropathy is also slightly
higher in individuals with IFG than in those
with NGT and only marginally lower than
in those with IGT. Moreover, both in the
general population and in diabetic patients,
apart from age, waist circumference and
PAD are independently associated with
prevalent polyneuropathy. This is another
novel finding suggesting an interplay be-
tween polyneuropathy and both cardiovas-
cular risk factors and macroangiopathy in
the lower limbs.
The vast majority of previous popula-
tion-based studies did not assess waist cir-
cumference as a potential risk factor of
polyneuropathy but did measure BMI or
weight (13,16,19,21). However, these
studies have not reported any association
between BMI or weight and the preva-
lence of polyneuropathy in diabetic pa-
tients. In the U.S. National Health and
Examination Survey (NHANES), weight
ⱖ92 kg (4th quartile) was associated with
insensate feet as assessed by the 10-g
monofilament, yielding an OR of 2.4
(95% CI 1.8 –3.1) in the nondiabetic pop-
ulation, but this association was not ob-
served in the diabetic population (19). In
the Australian Diabetes Obesity and Life-
style (AusDiab) study (17), including type
2 diabetic patients, neither BMI nor waist
circumference were identified as risk fac-
tors for polyneuropathy in univariate
analyses. Some studies have not taken
measures of obesity into consideration at
all when evaluating the possible risk fac-
tors of polyneuropathy (10,15,18,23).
Moreover, PAD verified by ankle brachial
index has not been previously reported as
a risk modifier for the prevalence of poly-
neuropathy in diabetic patients. Thus, the
present study is the first to report an in-
dependent association of prevalent poly-
neuropathy with both waist circum-
ference and PAD in the diabetic popula-
tion. An increase in waist circumference
by 1 cm was associated with a 4% increase
in the likelihood of polyneuropathy. Due
to the cross-sectional nature of this study,
it can be concluded that visceral obesity is
not a predictor for the development of
polyneuropathy and does not play a
pathogenetic role, but against the back-
ground of the independent association of
polyneuropathy with PAD reported
herein, it is tempting to speculate that vis-
ceral obesity as an important component
and macroangiopathy as a frequent sequel
of the metabolic syndrome may foster the
risk of developing polyneuropathy in di-
abetic subjects. The metabolic syndrome
(visceral obesity, dyslipidemia, hypergly-
cemia, and hypertension) has become one
of the major public health challenges
worldwide. There has been growing inter-
est in this constellation of closely related
cardiovascular risk factors (43–45). In-
deed, central obesity, as assessed by waist
circumference, rather than BMI, was
agreed as essential to define the metabolic
syndrome by different panels because of
the strength of the evidence linking waist
circumference with cardiovascular dis-
ease and the other metabolic syndrome
components and the likelihood that cen-
tral obesity is an early step in the etiolog-
ical cascade leading to full metabolic
syndrome (44,45). However, whether
central obesity is a harbinger of diabetic
polyneuropathy can only be answered by
prospective studies.
This study does not confirm some
previous population-based studies indi-
cating that IGT is associated with an in-
creased prevalence of polyneuropathy
(10,30). While the point estimate indi-
cates an increased prevalence, the differ-
ence did not reach statistical significance,
possibly due to the relatively low sample
size. On the other hand, it is conceivable
that higher age and waist circumference
may contribute to a higher prevalence of
polyneuropathy in individuals with IGT
compared with those with NGT, as these
risk factors were associated with polyneu-
ropathy in the entire population studied.
In the San Luis Valley Diabetes Study (10)
the prevalence of polyneuropathy was
3.9, 11.2, and 25.8% in subjects with
NGT, IGT, and diabetes, respectively. The
OR (95% CI) for the presence of polyneu-
ropathy in individuals with IGT (n⫽89)
was 3.5 (1.5–7.9) compared with those
with NGT (n⫽488) (10). In the Hoorn
Study (30) only the risk of bilateral ab-
sence of ankle reflexes (OR 1.7 [95% CI
1.1–2.8]), but not knee reflexes (1.2
[0.4–4.1]) or vibration sensation at the
big toe (0.8 [0.5–1.3]) or at the medial
malleoli (0.9 [0.4–2.2]), was associated
with IGT as compared with NGT. Other
studies have found no association be-
Table 2—Independent variables remaining in the final multiple logistic regression models
OR (95% CI) P
All subjects (N⫽393)
Age (years) 1.09 (1.05–1.13) ⬍0.0001
Waist circumference (cm) 1.03 (1.00–1.05) 0.0200
Diabetes 2.82 (1.55–5.13) 0.0007
PAD (ABI ⬍0.9) 1.88 (0.89–3.98) 0.0992
Diabetic subjects (n⫽195)
Age (years) 1.09 (1.04–1.14) 0.0007
Waist circumference (cm) 1.04 (1.01–1.07) 0.0183
PAD (ABI ⬍0.9) 2.76 (1.20–6.38) 0.0173
Duration of diabetes (years) 1.02 (0.99–1.05) 0.2852
ABI, ankle brachial index.
Ziegler and Associates
DIABETES CARE,VOLUME 31, NUMBER 3, MARCH 2008 467
tween IGT and prevalent polyneuropathy
(9,13,31,46). In a large sample of individ-
uals with IGT or IFG, the AusDiab Study
(47) recently reported a markedly lower
prevalence of polyneuropathy, as com-
pared with our study reaching only 3.9%
when diagnosed by the Neuropathy Dis-
ability Score and 6.1% when diagnosed
by an overall neuropathy score. However,
the corresponding rates of polyneurop-
athy in a population with NGT were not
reported (47). Thus, the results of the
present study are compatible with the no-
tion that the available evidence does not
generally suggest a significantly elevated
prevalence of polyneuropathy in individ-
uals with IGT.
An interesting aspect in the context of
a presumable “pre-diabetic neuropathy”
(27,33) is the role of IGT in CIAP. Several
uncontrolled observational studies have
recently reported an increased prevalence
of IGT in patients with CIAP (27,32,33).
In the only controlled study hitherto
available, 32% of patients with CIAP and
14% of the control subjects had IGT or
fasting hyperglycaemia, but after adjust-
ing for age and sex the difference was not
significant, even in the painful neuropa-
thy subgroup (34). A recent review has
concluded that despite extensive studies,
it is unclear whether IFG or IGT may
cause diabetic polyneuropathy or CIAP,
as some studies suggest that pre-diabetes
is a common and important cause of
CIAP, whereas others do not. It was
judged that a considerable degree of this
disparity may relate to differences in se-
lection of patients, choice of control sub-
jects, assessment of chronic glycemic
exposure and of diabetes complications,
and statistical power (29). There is gen-
eral agreement that prospective con-
trolled studies are required to definitively
answer the question whether polyneu-
ropathy develops more frequently and
more severely in individuals with pre-
diabetes compared with those with NGT
(26,28,29).
In conclusion, at the population level
the prevalence of polyneuropathy in indi-
viduals with IGT is slightly higher than in
those with NGT. To establish whether
this is a true difference, larger samples are
required. Apart from age, an important
risk factor associated with polyneurop-
athy in diabetic patients is waist circum-
ference, whereas PAD is a relevant
associated disorder. Thus, abdominal
obesity and peripheral macrovascular dis-
ease may represent important targets to
prevent diabetic polyneuropathy.
Acknowledgments— The KORA (Coopera-
tive Research in the Region of Augsburg)
research platform and the MONICA (Monitor-
ing Trends and Determinants on Cardiovascu-
lar Diseases) Augsburg studies were initiated
and financed by the Helmholtz Zentrum
Mu¨nchen - German Research Center for Envi-
ronmental Health, which is funded by the Ger-
man Federal Ministry of Education, Science,
Research and Technology and by the State of
Bavaria.
References
1. MacDonald BK, Cockerell OC, Sander
JW, Shorvon SD: The incidence and life-
time prevalence of neurological disorders
in a prospective community-based study
in the UK. Brain 123:665–676, 2000
2. Shaw JE, Zimmet PZ, Gries FA, Ziegler D:
Epidemiology of Diabetic Neuropathy. In
Textbook of Diabetic Neuropathy. Gries FA,
Cameron NE, Low PA, Ziegler D, Eds.
Thieme, Stuttgart, New York, 2003, p.
64–82
3. Young MJ, Boulton AJ, MacLeod AF, Wil-
liams DR, Sonksen PH: A multicentre
study of the prevalence of diabetic periph-
eral neuropathy in the United Kingdom
hospital clinic population. Diabetologia
36:150–154, 1993
4. Ziegler D, Gries FA, Mu¨ hlen H, Rathmann
W, Spu¨ler M, Lessmann F, the DiaCAN
Multicenter Study Group: Prevalence and
clinical correlates of cardiovascular auto-
nomic and peripheral diabetic neuropa-
thy in patients attending diabetes centers.
Diabete Metab 19:143–151, 1993
5. Fedele D, Comi G, Coscelli C, Cucinotta
D, Feldman EL, Ghirlanda G, Greene DA,
Negrin P, Santeusanio F, the Italian Dia-
betic Neuropathy Committee: A multi-
center study on the prevalence of diabetic
neuropathy in Italy. Diabetes Care
20:836–843, 1997
6. Cabezas-Cerrato J, Neuropathy Spanish
Study Group of the Spanish Diabetes So-
ciety (SDS): The prevalence of clinical di-
abetic polyneuropathy in Spain: a study in
primary care and hospital clinic groups.
Diabetologia 41:1263–1269, 1998
7. Tesfaye S, Chaturvedi N, Eaton SE, Ward
JD, Manes C, Ionescu-Tirgoviste C, Witte
DR, Fuller JH; EURODIAB Prospective
Complications Study Group: Vascular
risk factors and diabetic neuropathy.
N Engl J Med 352:341–350, 2005
8. Knuiman MW, Welborn TA, McCann VJ,
Stanton KG, Constable IJ: Prevalence of
diabetic complications in relation to risk
factors. Diabetes 35:1332–1339, 1986
9. Fujimoto WY, Leonetti DL, Kinyoun JL,
Shuman WP, Stolov WC, Wahl PW: Prev-
alence of complications among second-
generation Japanese-American men with
diabetes, impaired glucose tolerance, or
normal glucose tolerance. Diabetes 36:
730–739, 1987
10. Franklin GM, Kahn LB, Baxter J, Marshall
JA, Hamman RF Sensory neuropathy in
non-insulin-dependent diabetes mellitus:
the San Luis Valley Diabetes Study.AmJ
Epidemiol 131:633–643
11. Dyck PJ, Kratz KM, Karnes JL, Litchy WJ,
Klein R, Pach JM, Wilson DM, O’Brien
PC, Melton LJ 3d, Service FJ: The preva-
lence by staged severity of various types of
diabetic neuropathy, retinopathy, and ne-
phropathy in a population-based cohort:
the Rochester Diabetic Neuropathy
Study. Neurology 43:817–824, 1993
12. Harris M, Eastman R, Cowie C: Symp-
toms of sensory neuropathy in adults with
NIDDM in the U.S. population. Diabetes
Care 16:1446–1452, 1993
13. Shaw JE, Hodge AM, de Courten M,
Dowse GK, Gareeboo H, Tuomilehto J,
Alberti KGMM, Zimmet PZ: Diabetic neu-
ropathy in Mauritius: prevalence and risk
factors. Diabetes Res Clin Prac 42:131–
139, 1998
14. Verhoeven S, van Ballegooie E, Casparie
AF: Impact of late complications in type 2
diabetes in a Dutch population. Diabet
Med 8:435–438, 1991
15. Walters DP, Gatting W, Mullee MA, Hill
RD: The prevalence of diabetic distal sen-
sory neuropathy in an English commu-
nity. Diabet Med 9:349–353, 1992
16. Gregg EW, Sorlie P, Paulose-Ram R, Gu
Q, Eberhardt MS, Wolz M, Burt V, Curtin
L, Engelgau M, Geiss L; 1999–2000 na-
tional health and nutrition examination
survey: Prevalence of lower-extremity dis-
ease in the U.S. adult population ⱖ40
years of age with and without diabetes:
1999–2000 National Health and Nutri-
tion Examination Survey. Diabetes Care
27:1591–1597, 2004
17. Tapp RJ, Shaw JE, de Courten MP, Dun-
stan DW, Welborn TA, Zimmet PZ; Aus-
Diab Study Group: Foot complications in
type 2 diabetes: an Australian population-
based study. Diabet Med 20:105–113,
2003
18. Hanley AJ, Harris SB, Mamakeesick M,
Goodwin K, Fiddler E, Hegele RA, Spence
JD, House AA, Brown E, Schoales B,
McLaughlin JR, Klein R, Zinman B: Com-
plications of type 2 diabetes among Ab-
original Canadians: prevalence and
associated risk factors. Diabetes Care 28:
2054–2057, 2005
19. Cheng YJ, Gregg EW, Kahn HS, Williams
DE, De Rekeneire N, Narayan KM: Pe-
ripheral insensate neuropathy—a tall
problem for US adults? Am J Epidemiol
164:873–880, 2006
20. Koopman RJ, Mainous AG, Liszka HA,
Colwell JA, Slate EH, Carnemolla MA,
Everett CJ: Evidence of nephropathy and
peripheral neuropathy in US adults with
undiagnosed diabetes. Ann Fam Med
4:427–432, 2006
21. Dyck PJ, Davies JL, Wilson DM, Service
Polyneuropathy in pre-diabetes and diabetes
468 DIABETES CARE,VOLUME 31, NUMBER 3, MARCH 2008
FJ, Melton LJ, O’Brien PC: Risk factors for
severity of diabetic polyneuropathy: in-
tensive longitudinal assessment of the
Rochester Diabetic Neuropathy Study co-
hort. Diabetes Care 22:1479–1486, 1999
22. Dyck PJ, Davies JL, Clark VM, Litchy WJ,
Dyck PJ, Klein CJ, Rizza RA, Pach JM,
Klein R, Larson TS, Melton LJ, O’Brien
PC: Modeling chronic glycemic exposure
variables as correlates and predictors of
microvascular complications of diabetes.
Diabetes Care 29:2282–2288, 2006
23. Franklin GM, Shetterly SM, Cohen JA,
Baxter J, Hamman RF: Risk factors for dis-
tal symmetric neuropathy in NIDDM: The
San Luis Valley Diabetes Study. Diabetes
Care 17:1172–1177, 1994
24. Maser RE, Steenkiste AR, Dorman JS,
Kamp Nielsen V, Bass EB, Manjoo Q,
Drash AL, Becker DJ, Kuller LH, Greene
DA, Orchard TJ: Epidemiological corre-
lates of diabetic neuropathy: report from
the Pittsburgh Epidemiology of Diabetes
Complications Study. Diabetes 38:1456–
1461, 1989
25. Forrest KY, Maser RE, Pambianco G,
Becker DJ, Orchard TJ: Hypertension as a
risk factor for diabetic neuropathy: a pro-
spective study. Diabetes 46:665–670,
1997
26. Russell JW, Feldman EL: Impaired glu-
cose tolerance—does it cause neuropa-
thy? Muscle Nerve 24:1109–1112, 2001
27. Singleton JR, Smith AG: Therapy insight:
neurological complications of prediabe-
tes. Nat Clin Pract Neurol 2:276–282,
2006
28. Kissel JT: Peripheral neuropathy with im-
paired glucose tolerance: a sweet smell of
success? Arch Neurol 63:1055–1056,
2006
29. Dyck PJ, Dyck PJ, Klein CJ, Weigand SD:
Does impaired glucose metabolism cause
polyneuropathy? Review of previous
studies and design of a prospective con-
trolled population-based study. Muscle
Nerve 36:536–541, 2007
30. de Neeling JN, Beks PJ, Bertelsmann FW,
Heine RJ, Bouter LM: Peripheral somatic
nerve function in relation to glucose tol-
erance in an elderly Caucasian popula-
tion: the Hoorn study. Diabet Med
13:960–966, 1996
31. Eriksson KF, Nilsson H, Lindga¨ rde F, Os-
terlin S, Dahlin LB, Lilja B, Rose´n I, Sund-
kvist G: Diabetes mellitus but not im-
paired glucose tolerance is associated
with dysfunction in peripheral nerves.
Diabet Med 11:279–285, 1994
32. Hoffman-Snyder C, Smith BE, Ross MA,
Hernandez J, Bosch EP: Value of the oral
glucose tolerance test in the evaluation of
chronic idiopathic axonal polyneurop-
athy. Arch Neurol 63:1075–1079, 2006
33. Smith AG, Singleton JR: Idiopathic neu-
ropathy, prediabetes and the metabolic
syndrome. J Neurol Sci 242:9–14, 2006
34. Hughes RA, Umapathi T, Gray IA, Gregson
NA, Noori M, Pannala AS, Proteggente A,
Swan AV: A controlled investigation of
the cause of chronic idiopathic axonal
polyneuropathy. Brain 127:1723–1730,
2004
35. WHO MONICA Project Principal Investi-
gators, prepared by H. Tunstall-Pedoe:
The World Health Organization
MONICA Project (Monitoring of Trends
and Determinants in Cardiovascular Dis-
ease): a major international collaboration.
J Clin Epidemiol 34:105–114, 1988
36. Keil U, Cairns V, Do¨ ring A: MONICA-
Project, Region Augsburg, manual of op-
erations, survey. In GSF-Bericht 20,
Munich, Germany, Forschungszentrum
fu¨r Gesundheit und Umwelt, 1985
37. Hense HW, Filipiak B, Do¨ ring A: Ten-
year trends of cardiovascular risk factors
in the MONICA Augsburg Region in
Southern Germany: results from the
1984/85, 1989/90 and 1994/1995 sur-
veys. Cardiovasc Dis Prev 1:318–327,
1998
38. Meisinger C, Thorand B, Schneider A,
Stieber J, Doring A, Lo¨wel H: Sex differ-
ences in risk factors for incident type 2
diabetes mellitus: the MONICA Augsburg
cohort study. Arch Intern Med 162:82–89,
2002
39. Rathmann W, Haastert B, Icks A, Lo¨ wel
H, Meisinger C, Holle R, Giani G: High
prevalence of undiagnosed diabetes mel-
litus in Southern Germany: target popu-
lations for efficient screening: the KORA
survey 2000. Diabetologia 46:182–189,
2003
40. Expert Committee on the Diagnosis and
Classification of Diabetes Mellitus: Fol-
low-up report on the diagnosis of diabetes
mellitus. Diabetes Care 26:3160–3167,
2003
41. Feldman EL, Stevens MJ, Thomas PK,
Brown MB, Canal N, Greene DA: A prac-
tical two-step quantitative clinical and
electrophysiological assessment for the
diagnosis and staging of diabetic neurop-
athy. Diabetes Care 17:1281–1289, 1994
42. Bernstein EF, Fronek A: Current status of
noninvasive tests in the diagnosis of pe-
ripheral arterial disease. Surg Clin North
Am 62:473–487, 1982
43. World Health Organization: Report of a
WHO Consultation: Definition, Diagnosis
and Classification of Diabetes Mellitus and
Its Complications. Geneva, World Health
Org., 1999 (Tech. Rep. Ser., no. WHO/
NCD/NCS/99.2)
44. Alberti KG, Zimmet P, Shaw J, IDF Epi-
demiology Task Force Consensus Group:
The metabolic syndrome: a new world-
wide definition. Lancet 366:24–30, 2005
45. Grundy SM, Cleeman JI, Daniels SR, Do-
nato KA, Eckel RH, Franklin BA, Gordon
DJ, Krauss RM, Savage PJ, Smith SC, Sper-
tus JA, Costa F; American Heart Associa-
tion; National Heart, Lung, and Blood
Institute: Diagnosis and management of
the metabolic syndrome: an American
Heart Association/National Heart, Lung,
and Blood Institute Scientific Statement.
Circulation 112:2735–2752, 2005. [Erra-
tum in: Circulation 112:e297–e298]
46. Sosenko JM, Kato M, Soto R, Goldberg
RB: Sensory function at diagnosis and in
early stages of NIDDM in patients de-
tected through screening. Diabetes Care
15:847–852, 1992
47. Barr EL, Wong TY, Tapp RJ, Harper CA,
Zimmet PZ, Atkins R, Shaw JE; AusDiab
Steering Committee: Is peripheral neu-
ropathy associated with retinopathy and
albuminuria in individuals with impaired
glucose metabolism? The 1999–2000
AusDiab Study. Diabetes Care 29:1114–
1116, 2006
Ziegler and Associates
DIABETES CARE,VOLUME 31, NUMBER 3, MARCH 2008 469
