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Table 1
Prevalence of diabetes and impaired glucose regulation according to sex and age
|
Variable
|
Age (years)
|
|
18–30
|
31–45
|
46–60
|
61–75
|
>76
|
|
Men
|
|
n
|
306
|
603
|
578
|
494
|
193
|
|
Isolated IFG
|
0.32 (−0.31, 0.96)
|
2.32 (1.11, 3.52)
|
6.74 (4.70, 8.79)
|
4.85 (2.96, 6.75)
|
6.21 (2.81, 9.62)
|
|
Isolated IGT
|
2.84 (0.59, 5.09)
|
6.28 (3.91, 8.64)
|
10.8 (7.58, 14.1)
|
12.9 (9.02, 16.8)
|
16.9 (10.1, 23.7)
|
|
Combined IFG–IGT
|
0.47 (−0.45, 1.40)
|
2.41 (0.92, 3.91)
|
1.51 (0.23, 2.79)
|
4.22 (1.88, 6.56)
|
3.38 (0.10, 6.66)
|
|
UKDM
|
0.0
|
4.53 (2.87, 6.20)
|
11.9 (9.34, 14.6)
|
17.6 (14.2, 21.0)
|
16.7 (11.4, 22.0)
|
|
KDM
|
0.32 (−0.31, 0.96)
|
2.15 (0.99, 3.31)
|
11.9 (9.29, 14.5)
|
24.8 (21.0, 28.7)
|
20.7 (15.0, 26.4)
|
|
Women
|
|
n
|
369
|
853
|
818
|
608
|
250
|
|
Isolated IFG
|
0.81 (−0.1, 1.72)
|
1.99 (1.05, 2.93)
|
5.74 (4.15, 7.34)
|
5.09 (3.35, 6.84)
|
4.00 (1.57, 6.42)
|
|
Isolated IGT
|
3.89 (1.52, 6.26)
|
3.95 (2.28, 5.62)
|
6.99 (4.83, 9.15)
|
10.9 (7.82, 14.0)
|
20.2 (13.5, 26.9)
|
|
Combined IFG–IGT
|
0.38 (−0.37, 1.15)
|
1.31 (0.34, 2.29)
|
1.74 (0.63, 2.86)
|
2.73 (1.10, 4.36)
|
6.01 (2.07, 9.95)
|
|
UKDM
|
0.31 (−0.2, 0.87)
|
1.28 (0.53, 2.04)
|
4.32 (2.93, 5.71)
|
11.1 (8.60, 13.6)
|
18.1 (13.3, 22.9)
|
|
KDM
|
0.27 (−0.25, 0.80)
|
0.93 (0.29, 1.58)
|
6.60 (4.89, 8.30)
|
18.7 (15.6, 21.8)
|
23.2 (17.9, 28.4)
|
The prevalence of obesity, abdominal obesity and hypertension was significantly higher in all diabetes–IGR phenotypes (Table
). The probability of having raised triacylglycerol or low HDL-cholesterol levels was significantly higher in participants with KDM and UKDM, but the probability of having raised LDL-cholesterol was lower in participants with KDM than in any other group. A low education level was more frequent in participants with KDM.
Table 2
Association between diabetes and impaired glucose regulation categories and various risk factors
|
Variable
|
Normal OGTT
|
IFG
|
IGT
|
IFG + IGT
|
UKDM
|
KDM
|
p
value
|
|
|
3,760
|
198
|
309
|
80
|
244
|
481
|
|
|
Age (years)
|
46.3 ± 16.0
|
57.6 ± 12.6
|
59.7 ± 16.1
|
60.1 ± 15.9
|
62.8 ± 13.7
|
65.6 ± 11.5
|
<0.0001
a
|
|
Obesity (BMI ≥30 kg/m
2
)
|
%
|
23.2
|
51.2
|
48.2
|
53.8
|
60.2
|
50.2
|
<0.0001
b
|
|
OR (95% CI)
|
1
|
2.8 (1.9, 4.1)
|
2.5 (1.9, 3.2)
|
3.4 (2.1, 5.5)
|
4.2 (3.1, 5.5)
|
2.4 (2.0, 3.1)
|
|
|
Abdominal obesity (WHR >1 in men or WHR >0.85 in women)
|
%
|
33.1
|
52.7
|
57.9
|
70.5
|
65.1
|
68.1
|
<0.0001
b
|
|
OR (95% CI)
|
1
|
2.2 (1.4, 3.4)
|
2.2 (1.6, 2.9)
|
4.3 (2.4, 7.7)
|
3.8 (2.7, 5.3)
|
3.5 (2.7, 4.5)
|
|
|
Hypertension (antihypertensive treatment or a systolic BP ≥140 mmHg and/or diastolic BP ≥90 mmHg)
|
%
|
34.3
|
67.8
|
69.5
|
77.2
|
79.1
|
83.3
|
<0.0001
c
|
|
OR (95% CI)
|
1
|
1.9 (1.2, 2.9)
|
1.7 (1.2, 2.3)
|
2.5 (1.3, 4.6)
|
2.2 (1.5, 3.3)
|
2.5 (1.9, 3.4)
|
|
|
High LDL-cholesterol (≥3.9 mmol/l)
|
%
|
6.6
|
9.5
|
8.3
|
11.1
|
8.8
|
4.4
|
0.07
d
|
|
OR (95% CI)
|
1
|
1.3 (0.7, 2.06)
|
0.9 (0.6, 1.4)
|
1.3 (0.6, 2.8)
|
0.8 (0.6, 1.4)
|
0.4 (0.2, 0.7)
|
|
|
High triacylglycerols (≥1.7 mmol/l)
|
%
|
15.4
|
29.6
|
34.2
|
36.1
|
45.6
|
39.4
|
<0.0001
c
|
|
OR (95% CI)
|
1
|
1.4 (0.9, 2.3)
|
2.0 (1.5, 2.6)
|
1.9 (1.1, 3.2)
|
3.0 (2.2, 4.0)
|
2.4 (1.9, 3.1)
|
|
|
Low HDL-cholesterol (<1.0 mmol/l in men or 1.3 mmol/l in women)
|
%
|
29.1
|
38.6
|
34.2
|
34.7
|
39.4
|
48.4
|
<0.0001
c
|
|
OR (95% CI)
|
1
|
1.3 (0.6, 1.5)
|
1.2 (0.9, 1.6)
|
1.1 (0.6, 1.8)
|
1.5 (1.1, 2.0)
|
2.4 (1.8, 2.9)
|
|
|
Low education level (no education or only primary studies)
|
%
|
8.5
|
19.2
|
21.6
|
27.5
|
25.8
|
31.5
|
0.03
c
|
|
OR (95% CI)
|
1
|
1.29 (0.86, 1.95)
|
1.24 (0.88, 1.72)
|
1.74 (0.98, 3.07)
|
1.38 (0.98, 1.95)
|
1.66 (1.29, 2.14)
|
|
|
Smokers (more than one cigarette/day)
|
%
|
28.4
|
25.2
|
15.7
|
23.2
|
29.9
|
15.8
|
0.19
c
|
|
OR (95% CI)
|
1
|
1.34 (0.86, 2.09)
|
0.72 (0.51, 1.02)
|
1.21 (0.67, 2.18)
|
1.16 (0.82, 1.66)
|
0.90 (0.68, 1.19)
|
|
|
Have an active job style
|
%
|
14.1
|
16.5
|
8.9
|
10.0
|
9.1
|
8.2
|
0.06
c
|
|
OR (95% CI)
|
1
|
1.46 (0.87, 2.44)
|
0.70 (0.45, 1.08)
|
0.80 (0.36, 1.78)
|
0.71 (0.44, 1.16)
|
0.67 (0.47, 0.97)
|
|
|
Do leisure exercise at least once a week
|
%
|
39.8
|
33.9
|
32.5
|
32.9
|
35.9
|
30.2
|
0.09
c
|
|
OR (95% CI)
|
1
|
0.91 (0.61, 1.37)
|
0.80 (0.61, 1.05)
|
0.88 (0.52, 1.49)
|
0.96 (0.71, 1.30)
|
0.72 (0.57, 0.90)
|
|
|
Family history of diabetes mellitus (first and/or second degree relative)
|
%
|
47.1
|
53.3
|
45.2
|
46.8
|
49.6
|
62.7
|
<0.0001
c
|
|
OR (95% CI)
|
1
|
1.70 (1.14, 2.53)
|
1.38 (1.06, 1.80)
|
1.37 (0.33, 2.28)
|
1.67 (1.24, 2.26)
|
3.47 (2.76, 4.36)
|
|
The probability of smoking, doing exercise in their free time at least once weekly and the intensity of work activity did not differ significantly between the different metabolic phenotypes (Table
).
The prevalence of a family history of diabetes (first and/or second degree relative) was greater in all diabetes–IGR phenotypes (Table
).
Finally, the multivariate logistic regression analysis showed that the presence of diabetes mellitus was significantly associated with age (OR [95% CI] 1.05 [1.04, 1.06]), sex (less frequent in women [OR 0.34 (0.28, 0.45)]), education level (greater risk in persons without education [OR 1.28 (1.02, 1.62)]), obesity (OR 1.70 [1.37, 2.05]), abdominal obesity (OR 2.20 [1.75, 2.76]), high blood pressure (OR 2.26 [1.77, 2.87]), low HDL-cholesterol (OR 1.54 [1.25, 1.91]), high triacylglycerols (OR 1.99 [1.60, 2.48]) and a family history of diabetes (OR 2.70 [2.21, 3.31]).
Discussion
The present study, using a representative sample of the whole national population, shows that the prevalence of diabetes mellitus in Spain is 13.8%, with 6.8% having UKDM discovered during the study fieldwork.
A total of 13 studies from nine European countries (three from Spain) were included in the Decode Study, involving 7,680 men and 9,251 women aged 30–89 years. The conclusion reached was that in the majority of European countries the prevalence of diabetes and IGR is moderate or low (<10% in people younger than 60 and 10–20% in people aged 60–80 years) [
5
].
Other studies on diabetes mellitus prevalence have been undertaken in other European countries with data obtained from case records or from structured interviews, but with no OGTT. In other cases, local studies are extrapolated to the total national territory, and this may or may not represent the prevalence over the whole country. There may also exist important differences between countries in the prevalence of obesity, physical activity or eating patterns, which might partially explain the variation in diabetes prevalence [
6
].
In a recent Portuguese study using the same methodology as ours, the total prevalence of diabetes mellitus was 11.7%, very similar to that for the Spanish population [
2
]. In both studies diabetes mellitus prevalence was significantly higher in men than women. In our study, the prevalence of KDM was somewhat greater and UKDM somewhat less than that published in earlier studies in Spain [
3
] and Portugal [
2
]. The prevalence of IFG and IGT was also lower than that found in earlier Spanish studies [
3
] or recently in Portugal [
2
], where the prevalence of IFG and IGT was 23%. Different health strategies, different methodologies or a different prevalence of obesity or other metabolic risk factors might explain these differences in contemporary studies in which the overall diabetes mellitus prevalence was very similar.
In our study, diabetes mellitus and IGR were significantly associated with a greater frequency of obesity, high blood pressure, hypertriacylglycerolaemia and low HDL-cholesterol as expected [
7
]. However, people with KDM probably receive statin therapy more frequently, which may explain the lower level of LDL-cholesterol in people with KDM.
Finally, people with a low educational level had a 28% increased risk of having diabetes mellitus after adjustment for other risk factors closely associated with diabetes. A lower socioeconomic level has been associated with a poorer state of health, higher rates of mortality and cardiovascular diseases, and an increase in diabetes prevalence [
8
].
The main strengths of this study are first, the sampling was representative of the whole national territory, and second, the diagnosis of diabetes was made by OGTT in the majority of cases. The study, however, has a few limitations: the participation was relatively low (56%) and there was a greater participation of women and older people, meaning all the prevalence and analysis data were corrected for age and sex. In addition, not all the participants underwent the OGTT, but the prevalence of diabetes mellitus and IGR was calculated taking this into account, as indicated in the
Methods
section. Although, for clinical purposes, an OGTT needs to be reassessed to establish diagnostic status, it is widely accepted that one OGTT is enough in the setting of epidemiological studies. Another limitation is that the information was self-reported, although this, too, is common practice in large epidemiological surveys.
In summary, this study contributes information for the first time on the prevalence of diabetes mellitus and IGR in Spain. The results will provide our public health authorities with data that should encourage the urgent implementation of clinical and preventive intervention programmes to tackle the increasing health and economic burden of diabetes in Spain.
Acknowledgements
We thank P. Zimmet for critically reading the manuscript and making several useful remarks. We wish to acknowledge the kind collaboration of the following entities: the Spanish Diabetes Society, the Spanish Diabetes Federation and the Ministry of Health Quality Agency. Our profound appreciation goes to the primary care managers and personnel of the participating health centres, as well as to L. Forga and F. Casanueva for their inestimable help in the management of the Northern zone. To all the fieldworkers, nurses and dietitians, (I. Alonso, A. Arocas, R. Badia, C.M. Bixquert, N. Brito, D. Chaves, A. Cobo, L. Esquius, I Guillén, E. Mañas, A.M. Megido, N. Ojeda, R.M. Suarep, M.D. Zomeño), without whose work the study would not have been possible to carry out and to all the people who voluntarily participated in the study. Financing: supported by CIBER in Diabetes and Associated Metabolic Disorders–CIBERDEM (ISCIII–Ministerio de Ciencia e Innovación), Ministerio de Sanidad y Consumo and Spanish Society of Diabetes–SED. LifeScan España (Madrid, Spain) kindly donated the glucometers and test strips for capillary glucose measurements.
Contribution statement
All the authors contributed to the interpretation of data, discussion of results and critical review, and gave final approval of the version to be published.
Duality of interest
The authors declare that there is no duality of interest associated with this manuscript.
Open Access
This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
Abbreviations
|
FPG
|
Fasting plasma glucose
|
|
IFG
|
Impaired fasting glucose
|
|
IGR
|
Impaired glucose regulation
|
|
IGT
|
Impaired glucose tolerance
|
|
KDM
|
Known diabetes mellitus
|
|
UKDM
|
Unknown diabetes mellitus
|
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