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Vol 65, No. 2;Feb 2015
2 Jokull Journal
Prevalence Of Prediabetes And Its Association To Cardiovascular Risk Factors
Mohammad Shojaie1, Karamatollah Rahmanian2*, Abdolreza Sotoodeh Jahromi1
1. Research Center For Non-Communicable Diseases, Jahrom University Of
Medical Sciences, Jahrom, Iran.
2. Research Center For Social Determinants Of Health, Jahrom University Of
Medical Sciences, Jahrom, Iran.
*Corresponding author: Karamatollah Rahmanian, Research Center for Social
Determinants of Health, Jahrom University of Medical Sciences, Jahrom, Iran.
Abstract
Introduction: Prediabetes is an important risk factor for the development of diabetes mellitus
and subsequent atherosclerosis. The aim of this study was to determine the prevalence of
prediabetes and established risk factors in a population based sample in Iran.
Methods: In a cross-sectional study, participants aged ≥ 30 years selected using a multistage
cluster sampling method. Firstly, subjects completed a detailed demographic and medical
questionnaire (gender, age, history of diabetes mellitus and hypertension, taking
hypoglycemic and antihypertensive agents and history of smoking). Then all participants
were subjected to physical examination, blood lipid profile, blood glucose, anthropometric,
blood pressure and smoking assessments, during the years 2009 and 2010. We analyzed the
association between prediabetes and other cardiovascular risk factors using SPSS version 11.5
software. P-value <0.05 were considered to indicate statistical significance.
Results: On the whole, prediabetes was observed among 140 (15.7%) subjects, 17.5% for
men and 14.2% for women (p > 0.05). The prediabetic subjects had higher prevalence of
systolic hypertension, hypertension, hypercholesterolemia, high LDL-C and
hypertriglyceridemia than did the normoglycemic group. Multivariate logistic regression
analysis showed that hypertriglyceridemia and high LDL-C level were the strongest
predictors of prediabetes [Odds Ratio (OR) = 2.25, 95% Confidence Interval (CI): 1.44-3.52,
p<0.001; OR= 2.14, CI 95%: 1.19-3.85, p=0.01 respectively).
Conclusion: The major determinants of the prediabetes prevalence were hypertriglyceridemia
and high LDL cholesterol level. Therefore, community-based interventions and primary
prevention strategies should concentrate on reducing serum lipid profiles for diminished in
Iranian adults.
Keywords: prediabetes, cardiovascular risk factor, triglyceride, cholesterol
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Introduction
Type 2 diabetes mellitus is an important risk factor for the development of
atherosclerosis (1, 2), and is a condition with gradual onset and progression (3). The
prevalence of type 2 diabetes has increased considerably during the past few decades,
and the trend is likely to continue through the middle of this century (4). The
prevalence of diabetes is 10.5% in Eastern Mediterranean (EM) population aged
above 20 years (5).
In Iran, a study of 2003 reported a diabetes prevalence of 5% and 14.5% in population
and adults, respectively (6).
Type 2 diabetes is preceded by a long time of prediabetic state (7). Many studies have
identified prediabetic subjects with an IFG (impaired fasting glucose) and/or IGT
(impaired glucose tolerance) increased the risk of cardiovascular disease (8, 9) and
colorectal adenoma (10). Also, prediabetes is a significant risk factor of progression to
type 2 diabetes mellitus (11).
Approximately 25% of individuals with prediabetes will develop type 2 diabetes in
three to five years (12). The mean annual risk of developing diabetes for subjects with
normal blood sugar is nearly 0.7% per year (13), but this risk raise to 10% per year in
prediabetic subjects (14).
The prevalence of prediabetes among Korean adults aged over 20 years was 15.3%
(15), in New Zealanders aged 15 years and above was 18,9% (16) and in Turkish
adults aged ≥ 20 years was 22.9% (17). The investigators suggest that diabetes can be
delayed or prevented by either intensive lifestyle modification and/or a variety of drug
therapies (13).
The aim of study was to assess the prevalence of prediabetes and to identify its
relationship with cardiovascular risk factors in an Iranian adult.
Patients and Methods
Study participants
The participants selected using a multi-stage stratified clustering sample from ten
urban health centers of Jahrom city in the South region of Iran for enrollment to this
cross-sectional study.
Pregnant and lactating women and/or persons with chronic disease and mental
disorders and unable to walk, were excluded. The final sample consisted of 405 males
(aged 51.9 ± 13.9 years) and 487 females (aged 48.5 ± 12.9 years).
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All subjects were asked to answer a demographic and a detailed medical questionnaire
(age, sex, tobacco production and drug use). Then, they were subjected to
anthropometric (weight, height), blood pressure, fasting blood glucose and lipid
profile measurements. All data were collected during 2009-2010.
Signed informed sanction was obtained from all participants and Ethical approval was
obtained from the Ethics Committee of the Jahrom University.
Instruments and measurements
Identical standard protocols were used for each measurement conducted by trained
physician that it explained elsewhere (18).
Body mass index (BMI) was calculated as weight (kilograms) divided by height
(meters) squared. For definitions of obesity were used the definition proposed by the
World Health Organization (WHO), subjects with BMI 25 kg/m2 and <30 kg/m2 were
classified as overweight and those with BMI ≥30 kg/m2 were classified as obese (19).
According to JNC 7 criteria (20), hypertension was defined as an average SBP ≥140
mmHg, an average DBP ≥ 90 mmHg, or use of antihypertensive medications.
Prediabetes was defined as having fasting glucose of 100 mg/dl and less than 126
mg/dl in persons who were not on hypoglycemic medications (21).
We defined high total cholesterol (TC) as ≥ 240 mg/dl; LDL cholesterol (LDL-C) as ≥
160 mg/dl; HDL cholesterol (HDL-C) as < 40 mg/dl in men and < 50 mg/dl in
women; triglycerides (TG) as ≥200 mg/dl (22). Smoking was defined as used at least
one cigarettes or one cup of water pipe per day.
Statistical analysis
Continuous variables were presented as mean values and standard deviation and
categorical variables as frequencies. Associations between categorical variables were
tested by the use of contingency tables and the X2 test.
Comparisons between continuous variables between groups were performed by
analysis of student t test. Finally, we constructed logistic regression models to identify
factors associated with prediabetes. First, all independent variables (age, sex, BMI,
tobacco use, and cholesterol levels) were entered in the model, and then the backward
stepwise selection method was used to remove non significant variables.
Statistical analysis was performed using SPSS version 11.5 software and values of p <
0.05 were considered to indicate statistical significance.
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Results
Among the 892 subjects, 140 (15.7%; 95% CI, 13.3-18.1%) was defined as prediabetes.
Although, the prevalence of prediabetes was more in men (17.5%; CI 13.8% - 21/2%) than in
women (14.2 %; CI 11.1% - 17.3%) but there was no significant difference in the percentage
(p > 0.05).
The epidemiological characteristics of the study participants are shown in table-1.
It appears that age, systolic blood pressure, serum cholesterol and triglyceride mean values
were higher in prediabetic group than in the normoglycemic group, respectively (p < 0.001; p
< 0.001; p < 0.002; p < 0.001).
Table-1: Cardiovascular risk factors among normoglycemic and prediabetic subjects
Variables
Normoglycemic
Prediabetes
p-value
Age group; years
30-39
31.9
9.2
< 0.001
40-49
30.1
32.9
50-59
21.6
25.7
60-69
7.1
14.3
≥ 70
9.3
17.9
Sex; male
50.7
44.9
0.188
Daily smoking
11.1
15.0
0.169
Systolic hypertension
22.6
35.7
0.001
Diastolic hypertension
23.3
30.7
0.060
Hypertension
29.4
42.9
0.002
Total hypercholesterolemia
9.6
16.4
0.018
High LDL level
6.8
14.3
0.003
Low HDL level
42.6
40.0
0.573
Hypertriglyceridemia
13.7
27.1
< 0.001
Body Mass Index
< 25
41.0
34.3
0.331
25-<30
41.8
45.7
≥ 30
17.2
20.0
Figure-1 illustrates an age-group specific pattern concerning the prediabetic prevalence rate.
A steady increment in the prevalence of prediabetes is apparent with an exception for the 50-
59 age group (p<0.001).
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5.17
17.8
17.2
21.7
24
0
5
10
15
20
25
30-39 40-49 50-59 60-69 >=70
age (years)
Figure-1: The prevalence of prediabetes (%) by age group
The prediabetic group exhibited higher prevalence of systolic hypertension (p < 0.001),
hypertension (P < 0.002), hypercholesterolemia (p<0.018), high LDL level (p=0.003) and
hypertriglyceridemia (p < 0.001). Compared with normoglycemic subjects, persons in
prediabetic group were significantly older age group (p < 0.001) table-2.
Table-2: Characteristics of participants: Normoglycemic and Prediabetic groups
Variables
Normoglycemic
Mean ± SD
Prediabetes
Mean ± SD
p-value
Age (years)
47.8 ± 13.0
54.7 ± 13.6
< 0.001
Systolic blood pressure; mmHg
124.4 ± 18.4
133.0 ± 21.6
< 0.001
Diastolic blood pressure; mmHg
79.5 ± 11.3
81.4 ± 10.0
0.076
Cholesterol; mg/dl
188.8 ± 39.7
200.3 ± 44.7
0.002
LDL cholesterol; mg/dl
115.0 ± 29.5
120.3 ± 37.1
0.067
HDL cholesterol; mg/dl
47.9 ± 10.5
47.9 ± 10.6
0.992
Triglyceride; mg/dl
132.7 ± 82.9
168.4 ± 106.1
< 0.001
Weight; kg
68.7 ± 12.8
69.8 ± 11.9
0.387
Height; cm
162.1 ± 9.1
162.4 ± 9.3
0.878
Body Mass Index (kg/m2)
26.1 ± 4.4
26.6 ± 4.3
0.250
Logistic regression analysis showed, hypertriglyceridemia and high LDL cholesterol were the
strongest predictors of prediabetes, with an odds ratio of 2.25 (95% CI, 1.44 to 3.52, p <
0.001) and 2.14 (95% CI, 1.19 to 3.85, p = 0.011), followed by age group (OR=1.48, 95% CI,
1.28 to 1.71, p < 0.001), table-3.
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Table-3: Determinants of prediabetes vs. normal fasting blood sugar from
multivariable logistic regression model
Variables
OR
95% CI
p-value
Age group (age ≥ 70 year)
1.48
1.28-1.71
< 0.001
Sex (male %)
1.13
0.74-1.72
0.567
Daily smoking (%)
1.49
0.86-2.59
0.151
BMI ≥ 25 kg/m2 (%)
1.39
0.93-2.09
0.103
Systolic hypertension (%)
0.83
0.35-1.96
0.676
Diastolic hypertension (%)
0.72
0.87-2.63
0.354
Hypertension (%)
1.09
0.71-1.67
0.690
Hypercholesterolemia (%)
0.69
0.31-1.53
0.370
High LDL level (%)
2.14
1.19-3.85
0.011
Low HDL level (%)
0.98
0.65-1.49
0.956
Hypertriglyceridemia (%)
2.25
1.44-3.52
< 0.001
CI: Confidence Interval, OR: Odds Ratio
Discussion
The results showed that about one sixth of participants had prediabetes. although, men
exhibited a higher prevalence of prediabetes compared to women, but there wasn’t
any significant difference. Also, high triglyceride and LDL-C level had the strongest
association with prediabetes.
The prevalence of prediabetes in our study was more than the prevalence of
prediabetes reported in the Australia (14) and U.S (23). Also, Hosler in his study
found a prevalence of 9.1% self-reported prediabetes among adults aged 18 years or
older (4). The overall prevalence of prediabetes in a study conducted by Johnson et al
was nearly 30% and greater than estimates from our study (24). In a study among
adults aged 20 years and over, the prevalence of prediabetes has been estimated to be
30% (25). Also, the prevalence of prediabetes (impair fasting glucose) among a
sample of Mexican adults aged 30 to 65 years was 24.6% (26). The prevalence rate of
prediabetes in our study was similar (15.7%) to that (18.7%) reported by Phillips et al
and 15.3% by Lee et al in Korea (15, 27).
In our data, there was no significant difference in prevalence of prediabetes by
gender. Also, several studies have failed to show significant gender differences for
prevalence of prediabetes (26, 28, 29). But studies in the U.S (23) and Turkey (17)
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indicated more prevalence of prediabetes in women than in men and in Korea was
more in men than in women (15).
Adversely, Jermendy et al were found more prevalence of impair fasting glucose
(fasting blood glucose: 110-<126 mg/dl) among men than women (30). The
prevalence of prediabetes increased with advancing age except for 50-59 age groups
that was slightly lower than 40-49 age groups. Similar finding were reported by
Hosler (4), Satman et al (17), Rolka et al (23) and Jermendy et al (30). Unlike our
result, Perreault et al found that the age is similar among two groups (normoglycemic
and prediabetic subjects) (31).
Unlike normoglycemic subjects, prediabetes had higher mean age, systolic blood
pressure and serum total cholesterol and triglyceride and high percent of systolic
hypertension, hypertension, hypercholesterolemia, hypertriglyceridemia and abnormal
LDL level. In Australia, increased serum triglyceride levels, decreased high-density
lipoprotein (HDL) cholesterol levels, hypertension and central adiposity are more
common in adults with prediabetes compared with those with normal glucose
tolerance (14). Also in another study the prediabetic state is associated with a
predisposition to lipid disorders, high blood pressure and the metabolic syndrome
(32).
Rolka et al found that prevalence of prediabetes increased with age and body mass
index groups (23). Compared to the group with normoglycemia, the group with
prediabetes had significantly higher fasting serum cholesterol among obese adults
(33). In a study in Taiwan, the impair fasting glucose group (fasting blood glucose:
110-125 mg/dl) showed significantly higher systolic and diastolic blood pressure,
cholesterol level and body mass index than those with normal blood glucose (34).
The stepwise multiple logistic regression analysis indicated that the prediabetic
individuals had higher age group, hyperteriglyceridemia and abnormal LDL
cholesterol level. But Hosler found that the BMI≥ 25 kg/m2 and age 45 years or older
was related with prediabetes (4).
In this present study, we have a number of limitations. First, we used only fasting
blood sugar for definition of prediabetic state. Thus we recommended both fasting
blood sugar and glucose tolerance test for this diagnosis in future studies. Second,
although we used multistage random sampling for selection of population, but the age
and sex of participants were deferred with basic population.
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Limitations
The only fasting blood sugar that was used for our subject classification in the various
blood glucose categories, the higher percentage of the female population compared to
the male one, lack of data on habitual physical activity and the absence of dietary data
could be some limitations that restricted our scientific contribution to the area.
In conclusion, the prevalence of prediabetes in our study was 15.7% that was similar
among men and women. The important factors associated with prediabetes were
hypertriglyceridemia and high LDL-C level. Thus community-based intervention
needs to consider strategies to raise general awareness and decreased the prevalence
of prediabetes in population.
Acknowledgements
This research work was financed by Jahrom University of Medical Sciences. The
authors would like to thank the participants in this study and personnel of Paymanieh
Hospital and urban health center for their help.
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