Glycaemic control of Type 1 diabetes in clinical practice early in the 21st century: an international comparison.

AIMS: Improving glycaemic control in people with Type 1 diabetes is known to reduce complications. Our aim was to compare glycaemic control among people with Type 1 diabetes using data gathered in regional or national registries. METHODS: Data were obtained for children and/or adults with Type 1 diabetes from the following countries (or regions): Western Australia, Austria, Denmark, England, Champagne-Ardenne (France), Germany, Epirus, Thessaly and Thessaloniki (Greece), Galway (Ireland), several Italian regions, Latvia, Rotterdam (The Netherlands), Otago (New Zealand), Norway, Northern Ireland, Scotland, Sweden, Volyn (Ukraine), USA and Wales) from population or clinic-based registries. The sample size with available data varied from 355 to 173 880. Proportions with HbA1c < 58 mmol/mol (< 7.5%) and ≥ 75 mmol/mol (≥ 9.0%) were compared by age and sex. RESULTS: Data were available for 324 501 people. The proportions with HbA1c 58 mmol/mol (< 7.5%) varied from 15.7% to 46.4% among 44 058 people aged < 15 years, from 8.9% to 49.5% among 50 766 people aged 15-24 years and from 20.5% to 53.6% among 229 677 people aged ≥ 25 years. Sex differences in glycaemic control were small. Proportions of people using insulin pumps varied between the 12 sources with data available. CONCLUSION: These results suggest that there are substantial variations in glycaemic control among people with Type 1 diabetes between the data sources and that there is room for improvement in all populations, especially in young adults.

Quality indicators for the prevention of type 2 diabetes in Europe--IMAGE.

BACKGROUND: The marked increase of type 2 diabetes necessitates active development and implementation of efficient prevention programs. A European level action has been taken by launching the IMAGE project to unify and improve the various prevention management concepts, which currently exist within the EU. This report describes the background and the methods used in the development of the IMAGE project quality indicators for diabetes primary prevention programs. It is targeted to the persons responsible for diabetes prevention at different levels of the health care systems. METHODS: Development of the quality indicators was conducted by a group of specialists representing different professional groups from several European countries. Indicators and measurement recommendations were produced by the expert group in consensus meetings and further developed by combining evidence and expert opinion. RESULTS: The quality indicators were developed for different prevention strategies: population level prevention strategy, screening for high risk, and high risk prevention strategy. Totally, 22 quality indicators were generated. They constitute the minimum level of quality assurance recommended for diabetes prevention programs. In addition, 20 scientific evaluation indicators with measurement standards were produced. These micro level indicators describe measurements, which should be used if evaluation, reporting, and scientific analysis are planned. CONCLUSIONS: We hope that these quality tools together with the IMAGE guidelines will provide a useful tool for improving the quality of diabetes prevention in Europe and make different prevention approaches comparable.

Correlation between the prevalence of type 1 diabetes with the daily insulin dose and the autoimmune process against glutamic acid decarboxylase in adults.

In this study, we compared the rate of insulin requirement among adults with type 1 diabetes (T1D) in 24 Ukrainian regions. The glutamic acid decaroxylase 65 antibody (GADA), insulin antibody (IA), and plasma c-peptide levels were investigated. The data included the prevalent cases of T1D in Ukraine at the end of 2006. Only persons aged over 14 years at the time of inclusion into the Ukrainian register and diagnosed with diabetes before 30 years of age were included in this study (n=26796). A total of 86 T1D patients (42 males; 44 females) with a mean age of 27.5 years (0.86) and a mean diabetes duration of 10.3 (0.72) years (SE), were randomly selected from four regional diabetes registers. The GADA, IA, and the plasma c-peptide levels were also determined. The logistic regression model was used, and the odds ratio (OR) and 95% confidence interval (CI) were calculated. Furthermore, the differences in the T1D prevalence among the 24 Ukrainian regions were obtained (p<0.001). In the "minimal" regional cluster (MIC), the prevalence rate was 6 (5-6), and in the "maximal" (MAC) regional cluster, it was -9 (8-9) per 10000 adults. For patients with a disease duration (DD) of up to 15 years (n=13677), the daily insulin dose (DID) was observed to increase linearly with DD (R=0.899, p<0.001). The median insulin doses were standardized according to DD, and the values were lowest in the MIC and highest in the MAC populations: 45.89 (45.28-47.19) and 56.59 (53.33-57.88) U/24 h, respectively (p<0.01). Furthermore, the level of HbA1c in the MAC of T1D patients was observed to be higher than that in the MIC (9.52+/-2.24%, n=240, and 8.57+/-3.29%, n=111, respectively; p<0.01). In addition, the GADA levels and persistence in the MAC patients (n=38) were higher than that in the MIC patients (n=48): 14.1+/-4.6 and 3.2+/-1.2 U/ml, respectively, mean+/-SE; p=0.028; OR=9.66 (3.31-28.17), p<0.001. Adjusting for age, gender, and duration of diabetes affected the results only slightly. Furthermore, the IA and c-peptide levels and their persistence were not observed to be associated with TD1 prevalence.

Body mass index and the risk of total and cardiovascular mortality among patients with type 2 diabetes: a large prospective study in Ukraine.

BACKGROUND: Several prospective studies have evaluated the association between body mass index (BMI) and cardiovascular mortality among patients with type 2 diabetes; however, the results are controversial. OBJECTIVE: To investigate the association of different BMI distributions with total and cardiovascular mortality among diabetic patients. METHODS: A total of 30 534 Ukrainian men and 58 909 women with type 2 diabetes from the nationwide population-based diabetes register were included in this study. RESULTS: During a mean follow-up of 2.7 years, 7804 deaths were recorded, of which 3320 were due to cardiovascular disease. After adjustment for age, smoking and alcohol drinking, the hazard ratios across the five BMI categories (<23, 23-24.9, 25-29.9 (reference group), 30-34.9 and >or=35 kg/m2) among diabetic men were 1.57 (95% CI 1.42 to 1.74), 1.16 (1.05 to 1.28), 1.0, 1.01 (0.91 to 1.12) and 1.24 (1.02 to 1.50) for total mortality, and 1.67 (95% CI 1.42 to 1.95), 1.30 (1.12 to 1.51), 1.0, 1.13 (0.96 to 1.34) and 1.54 (1.16 to 2.05) for cardiovascular mortality, respectively. The respective hazard ratios among diabetic women were 1.34 (95% CI 1.22 to 1.47), 1.00 (0.91 to 1.10), 1.0, 1.04 (0.97 to 1.12) and 1.27 (1.14 to 1.41) for total mortality, and 1.36 (95% CI 1.18 to 1.57), 1.06 (0.92 to 1.21), 1.0, 1.12 (1.01 to 1.25) and 1.35 (1.15 to 1.59) for cardiovascular mortality. Additional adjustment for systolic blood pressure, total cholesterol, history of cardiovascular disease, diabetes treatments and duration of diabetes affected the results only slightly. CONCLUSIONS: This study indicated a U-shaped association between BMI and total and cardiovascular mortality among diabetic men and women.

Seasonality of birth in children and young adults (0-29 years) with type 1 diabetes in Ukraine.

AIMS/HYPOTHESIS: Numerous epidemiological studies have shown differences in seasonality of birth patterns between the general population and the group who develop type 1 diabetes mellitus. This finding indicates that environmental factors operating during pre- and/or postnatal development could be aetiologically important. We examined whether the pattern of month of birth for type 1 diabetes patients in Ukraine differs from that for total live births. METHODS: Data consist of prevalent cases of type 1 diabetes in Ukraine by the end of 2003. Cases are restricted to persons born after 1 January 1960, diagnosed with type 1 diabetes before the age of 30 years (n = 20,117). People born during the same time in the general population (n = 29,105,560) were the reference standard. Seasonal patterns were estimated using logistic regression with harmonic terms. RESULTS: We found a strongly significant seasonal pattern of type 1 diabetes incidence rates (p < 0.001), with the lowest rates in December and the highest in April. The rate ratio between the extremes was 1.32 (95% CI 1.27-1.39). Tests for seasonal patterns in subgroups defined by sex and age or by sex and date of birth were all significant with p values less than 0.02. We found no interactions with sex (p = 0.142) or age at diagnosis (p = 0.207), but found a strong interaction with period of birth (p < 0.0001). CONCLUSIONS/INTERPRETATION: The results obtained indicate that early-life factors linked to seasons may influence type 1 diabetes risk later in life.