An association between low education level and an increased risk of metabolic syndrome was recently reported among middle-aged women from Sweden (1). Because the statistics of cardiovascular mortality in Hungary—in sharp contrast to other countries (2)—are discouraging (3), and because metabolic syndrome can contribute to accelerated atherosclerosis (4), it is considered worthwhile to screen subjects to detect early signs of metabolic syndrome in our country. We performed a mass screening to evaluate the clinical features of metabolic syndrome in northwest Hungary (5), and the cohort proved to be large enough to allow subgroup analysis to assess the relationship between education level and clinical characteristics of metabolic syndrome.

Originally, the aim of the screening procedure was to identify subjects with hyperinsulinemia (serum fasting insulin >15 μU/ml and/or postchallenge insulin >45 μU/ml at 120 min after 75 g glucose) because hyperinsulinemia is one of the characteristic features of metabolic syndrome and can contribute to accelerated cardiovascular events (6). In our screening procedure, subjects of both sexes (aged 20–65 years) were referred to our center by general practitioners, and at least one of the following clinical characteristics was applied for inclusion: hypertension (subjects with actual blood pressure ≥140/90 mmHg [mean of three consecutive values] or with antihypertensive treatment irrespective of actual blood pressure measurement); obesity (BMI >30.0 kg/m2); elevated waist-to-hip ratio (WHR; >0.85 in women and >0.90 in men); or positive family history of diabetes, obesity, hypertension, or cardiovascular events. Known diabetic patients were excluded from the study. Anthropometric data and blood pressure values were registered, fasting blood samples were taken, and an oral glucose tolerance test with 75 g glucose was performed. Subjects were classified according to the categories of glucose intolerance (World Health Organization criteria) based on postchallenge 120-min glucose values, and normo- and hyperinsulinemia were based on the plasma insulin values measured. Education levels (low: primary school; middle: high school; high: university) of screened subjects were assessed by questionnaires.

In the total cohort (n = 1,002; 590 women and 412 men), the prevalence of women with lower education level was significantly higher than that of women with high education level, and, in addition, the prevalence of men with lower education level was significantly lower than that of men with high education level. Although the ages of the subjects in the subgroups were comparable, both BMI and the prevalence of hypertension were significantly higher in subjects with low education level compared with those with high education level. The laboratory data and the prevalence of hyperinsulinemia (total 51.3%), different categories of glucose intolerance (total prevalence of impaired glucose tolerance [IGT] = 13.6%; diabetes = 9.1%), and positive family history (total 90.6%) did not differ significantly in subgroups classified according to education level (Table 1). A further analysis regarding sex and education level indicated that women with low education level (n = 223) had significantly higher values (means ± SD) for BMI (32.96 ± 5.79 kg/m2) as well as elevated WHR (0.87 ± 0.06) compared with women with middle education level (n = 281; BMI: 31.35 ± 5.52 kg/m2; WHR: 0.85 ± 0.07; P < 0.001) or high education level (n = 86; BMI: 30.40 ± 5.45 kg/m2; WHR: 0.83 ± 0.07). Men with low education level (n = 114) had significantly higher BMI (32.98 ± 4.79 kg/m2) and elevated WHR (0.97 ± 0.07) compared with men with high education level (n = 86; BMI: 30.35 ± 4.46 kg/m2, P < 0.001; WHR: 0.95 ± 0.08, P < 0.05). Laboratory findings did not differ significantly in subgroups classified according to sex and education level (data not shown).

In summary, a clustering of the clinical features of metabolic syndrome (higher BMI and elevated WHR as well as higher prevalence rate of hypertension) proved to be associated with lower education level in a large cohort of subjects, particularly women in Hungary. Our results are in accordance with others (1,7,8), suggesting that this association could be considered irrespective of the country. Therefore, subjects with low education level and a clustering of clinical characteristics of metabolic syndrome should have priority in efforts aimed at preventing cardiovascular complications. Undoubtedly, lifestyle modification, even in childhood (9), and drug therapy at a later stage (when necessary) should be considered in these subjects.

Table 1—

Clinical and laboratory findings according to the education level in subjects exhibiting at least one of the inclusion criteria (obesity, elevated waist-to-hip ratio, hypertension, positive family history) for screening hyperinsulinemia (n = 1,002)

Education level
LowMiddleHigh
n 337 493 172 
F/M [n (%)] 223*/114* (66.2/33.8) 281/212 (57.0/43.0) 86/86 (50.0/50.0) 
Age of subjects (years) 46.4 ± 7.9 45.4 ± 7.2 46.2 ± 6.7 
BMI (kg/m232.97 ± 5.46* 31.53 ± 5.46 30.37 ± 4.97 
Hypertension 277 (82.2) 386 (78.3) 123 (71.5) 
Positive family history 302 (89.6) 449 (91.1) 157 (91.3) 
Hyperinsulinemia 178 (53.0) 250 (51.0) 84 (48.8) 
Glucose intolerance (IGT/diabetes) 47/28 (14.0/8.3) 69/50 (14.1/10.2) 20/13 (11.6/7.6) 
Fasting blood glucose (mmol/l) 6.47 ± 3.13 5.62 ± 2.00 6.35 ± 3.09 
Fasting plasma insulin (μU/ml) 14.6 ± 9.7 14.1 ± 10.2 12.6 ± 7.4 
HOMA 3.70 ± 2.69 3.61 ± 3.00 3.19 ± 2.20 
Postprandial plasma insulin (μU/ml) 56.2 ± 65.2 57.3 ± 63.6 54.9 ± 65.7 
Serum total cholesterol (mmol/l) 6.00 ± 1.28 6.11 ± 1.31 6.01 ± 1.28 
Serum triglycerides (mmol/l) 2.50 ± 2.53 2.58 ± 2.29 2.64 ± 2.24 
Serum LDL cholesterol (mmol/l) 3.74 ± 1.12 3.81 ± 1.14 3.71 ± 1.21 
Serum HDL cholesterol (mmol/l) 1.19 ± 0.33 1.19 ± 0.33 1.17 ± 0.34 
Serum uric acid (μmol/l) 260 ± 89 256 ± 86 262 ± 81 
Education level
LowMiddleHigh
n 337 493 172 
F/M [n (%)] 223*/114* (66.2/33.8) 281/212 (57.0/43.0) 86/86 (50.0/50.0) 
Age of subjects (years) 46.4 ± 7.9 45.4 ± 7.2 46.2 ± 6.7 
BMI (kg/m232.97 ± 5.46* 31.53 ± 5.46 30.37 ± 4.97 
Hypertension 277 (82.2) 386 (78.3) 123 (71.5) 
Positive family history 302 (89.6) 449 (91.1) 157 (91.3) 
Hyperinsulinemia 178 (53.0) 250 (51.0) 84 (48.8) 
Glucose intolerance (IGT/diabetes) 47/28 (14.0/8.3) 69/50 (14.1/10.2) 20/13 (11.6/7.6) 
Fasting blood glucose (mmol/l) 6.47 ± 3.13 5.62 ± 2.00 6.35 ± 3.09 
Fasting plasma insulin (μU/ml) 14.6 ± 9.7 14.1 ± 10.2 12.6 ± 7.4 
HOMA 3.70 ± 2.69 3.61 ± 3.00 3.19 ± 2.20 
Postprandial plasma insulin (μU/ml) 56.2 ± 65.2 57.3 ± 63.6 54.9 ± 65.7 
Serum total cholesterol (mmol/l) 6.00 ± 1.28 6.11 ± 1.31 6.01 ± 1.28 
Serum triglycerides (mmol/l) 2.50 ± 2.53 2.58 ± 2.29 2.64 ± 2.24 
Serum LDL cholesterol (mmol/l) 3.74 ± 1.12 3.81 ± 1.14 3.71 ± 1.21 
Serum HDL cholesterol (mmol/l) 1.19 ± 0.33 1.19 ± 0.33 1.17 ± 0.34 
Serum uric acid (μmol/l) 260 ± 89 256 ± 86 262 ± 81 

Data are means ± SD or absolute numbers (%). Statistical analysis was made by analysis of variance and χ2. HOMA, homeostasis model assessment test. HOMA = plasma fasting glucose × fasting insulin/22.5.

*

P < 0.001 vs. high education level;

P < 0.05 vs. high education level.

1
Wamala SP, Lynch J, Horsten M, Mittleman MA, Schenck-Gustafsson K, Orth-Gomer K: Education and the metabolic syndrome in women.
Diabetes Care
22
:
1999
–2003,
1999
2
La Vecchia C, Levi F, Lucchini F, Negri E: Trends in mortality from major diseases in Europe, 1980–1993. Eur J Epidemiol
14
:
1
–8,
1998
3
Vargáné HP, Ádány R: Trends of premature mortality from cardiovascular diseases in Hungary and the European Union 1970–1997. Orv Hetil
141
:
601
–607,
2000
4
Reaven GM: Banting Lecture 1988: Role of insulin resistance in human disease.
Diabetes
37
:
1595
–1607,
1988
5
Hídvégi T, Hetyési K, Jermendy Gy: Screening for syndrome-x in Hungary (Abstract).
Diabetes Res Clin Pract
50(Suppl. 1)
:
S140
,
2000
6
Pyörälä M, Miettinen H, Laakso M, Pyörälä K: Hyperinsulinemia predicts coronary heart disease risk in healthy middle-aged men: the 22-year follow-up results of the Helsinki Policemen Study.
Circulation
98
:
398
–404,
1998
7
Brancati FL, Whelton PK, Kuller LH, Klag MJ: Diabetes mellitus, race, and socio-economic status: a population-based study.
Ann Epidemiol
6
:
67
–73,
1996
8
Winkleby MA, Kraemer HC, Ahn DK, Varady AN: Ethnic and socio-economic differences in cardiovascular disease risk factors: findings for women from the Third National Health and Nutrition Examination Survey, 1988–1994. JAMA
280
:
356
–362,
1998
9
Winkleby MA, Robinson TN, Sundquist J, Kraemer HC: Ethnic variation in cardiovascular disease risk factors among children and young adults: findings from the Third National Health and Nutrition Examination Survey, 1988–1994. JAMA
281
:
1006
–1013,
1999

Address correspondence to György Jermendy, MD, PhD, DSC, Bajcsy-Zsilinszky Hospital, 3rd Medical Department, Maglódi út 89-91, Budapest, H-1106, Hungary. E-mail: gyjermendy@mail.datanet.hu.