| 1. |
- Lauria, A., et al.
(författare)
-
BMI is an important driver of beta-cell loss in type 1 diabetes upon diagnosis in 10 to 18-year-old children
- 2015
-
Ingår i: European Journal of Endocrinology. - : BioScientifica. - 0804-4643 .- 1479-683X. ; 172:2, s. 107-113
-
Tidskriftsartikel (refereegranskat)abstract
- Objective: Body weight-related insulin resistance probably plays a role in progression to type 1 diabetes, but has an uncertain impact following diagnosis. In this study, we investigated whether BMI measured at diagnosis was an independent predictor of C-peptide decline 1-year post-diagnosis. Design: Multicentre longitudinal study carried out at diagnosis and up to 1-year follow-up. Methods: Data on C-peptide were collected from seven diabetes centres in Europe. Patients were grouped according to age at diagnosis (less than5 years, n = 126; greater than5 years less than10 years, n = 295; greater than10 years less than18 years, n = 421; greater than18 years, n = 410). Linear regression was used to investigate whether BMI was an independent predictor of change in fasting C-peptide over 1 year. Models were additionally adjusted for baseline insulin dose and HbA1c. Results: In individuals diagnosed between 0 and 5 years, 5 and 10 years and those diagnosed greater than18 years, we found no association between BMI and C-peptide decline. In patients aged 10-18 years, higher BMI at baseline was associated with a greater decline in fasting C-peptide over 1 year with a decrease (beta 95% CI; P value) of 0.025 (0.010, 0.041) nM/kg per m(2) higher baseline BMI (P = 0.001). This association remained significant after adjusting for gender and differences in HbA1c and insulin dose (beta = 0.026, 95% CI = 0.0097, 0.042; P = 0.002). Conclusions: These observations indicate that increased body weight and increased insulin demand are associated with more rapid disease progression after diagnosis of type 1 diabetes in an age group 10-18 years. This should be considered in studies of beta-cell function in type 1 diabetes.
|
|
| 3. |
- Patterson, Cc, et al.
(författare)
-
Seasonal variation in month of diagnosis in children with type 1 diabetes registered in 23 European centers during 1989-2008 : little short-term influence of sunshine hours or average temperature
- 2015
-
Ingår i: Pediatric Diabetes. - : Wiley-Blackwell. - 1399-543X .- 1399-5448. ; 16:8, s. 573-580
-
Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The month of diagnosis in childhood type 1 diabetes shows seasonal variation.OBJECTIVE: We describe the pattern and investigate if year-to-year irregularities are associated with meteorological factors using data from 50 000 children diagnosed under the age of 15 yr in 23 population-based European registries during 1989-2008.METHODS: Tests for seasonal variation in monthly counts aggregated over the 20 yr period were performed. Time series regression was used to investigate if sunshine hour and average temperature data were predictive of the 240 monthly diagnosis counts after taking account of seasonality and long term trends.RESULTS: Significant sinusoidal pattern was evident in all but two small centers with peaks in November to February and relative amplitudes ranging from ±11 to ±38% (median ±17%). However, most centers showed significant departures from a sinusoidal pattern. Pooling results over centers, there was significant seasonal variation in each age-group at diagnosis, with least seasonal variation in those under 5 yr. Boys showed greater seasonal variation than girls, particularly those aged 10-14 yr. There were no differences in seasonal pattern between four 5-yr sub-periods. Departures from the sinusoidal trend in monthly diagnoses in the period were significantly associated with deviations from the norm in average temperature (0.8% reduction in diagnoses per 1 °C excess) but not with sunshine hours.CONCLUSIONS: Seasonality was consistently apparent throughout the period in all age-groups and both sexes, but girls and the under 5 s showed less marked variation. Neither sunshine hour nor average temperature data contributed in any substantial way to explaining departures from the sinusoidal pattern.
|
|
