Association between glycaemic outcome and BMI in Danish children with type 1 diabetes in 2000-2018: a nationwide population-based study.

AIM: To describe the development of HbA1c and BMI over time in Danish children with type 1 diabetes; and to investigate the association between HbA1c and BMI including influence of age, gender, diabetes duration, severe hypoglycaemia and treatment method. METHODS: We used the nationwide Danish Registry of Childhood and Adolescent Diabetes, DanDiabKids, including annual registrations of all children with diabetes treated at Danish hospitals. With linear mixed-effects models and splines we analyzed the HbA1c and BMI development over time as well as the association between HbA1c and BMI including effects of gender, age, disease duration, hypoglycaemia and treatment method. BMI z-scores were calculated for these analyses. RESULTS: For the period from 2000 to 2018, 6097 children with type 1 diabetes were identified from the DanDiabKids database. The median (interquartile range) HbA1c level was 65 (57-74) mmol/mol (8.1%) and the median BMI z-score was 0.85 in girls and 0.67 in boys. A non-linear association was found between HbA1c and BMI z-score, with the highest BMI z-score observed for HbA1c values in the range of approximately 60-70 mmol/mol (7.6-6.8%). The association was modified by gender, age and diabetes duration. Severe hypoglycaemia and insulin pump treatment had a small positive impact on BMI z-score. CONCLUSION: The association between HbA1c and BMI z-score was non-linear, with the highest BMI z-score being observed for intermediate HbA1c levels; however, specific patterns depended on gender, age and diabetes duration.

Socioeconomic position and survival after cervical cancer: influence of cancer stage, comorbidity and smoking among Danish women diagnosed between 2005 and 2010.

BACKGROUND: In an attempt to decrease social disparities in cancer survival, it is important to consider the mechanisms by which socioeconomic position influences cancer prognosis. We aimed to investigate whether any associations between socioeconomic factors and survival after cervical cancer could be explained by socioeconomic differences in cancer stage, comorbidity, lifestyle factors or treatment. METHODS: We identified 1961 cases of cervical cancer diagnosed between 2005 and 2010 in the Danish Gynaecological Cancer database, with information on prognostic factors, treatment and lifestyle. Age, vital status, comorbidity and socioeconomic data were obtained from nationwide administrative registers. Associations between socioeconomic indicators (education, income and cohabitation status) and mortality by all causes were analysed in Cox regression models with inclusion of possible mediators. Median follow-up time was 3.0 years (0.01-7.0). RESULTS: All cause mortality was higher in women with shorter rather than longer education (hazard ratio (HR), 1.46; 1.20-1.77), among those with lower rather than higher income (HR, 1.32; 1.07-1.63) and among women aged<60 years without a partner rather than those who cohabited (HR, 1.60; 1.29-1.98). Socioeconomic differences in survival were partly explained by cancer stage and less by comorbidity or smoking (stage- and comorbidity-adjusted HRs being 1.07; 0.96-1.19 for education and 1.15; 0.86-1.52 for income). CONCLUSION: Socioeconomic disparities in survival after cervical cancer were partly explained by socioeconomic differences in cancer stage. The results point to the importance of further investigations into reducing diagnosis delay among disadvantaged groups.

Age-period-cohort modelling of type 1 diabetes incidence rates among children included in the EURODIAB 25-year follow-up study.

AIMS: Specific patterns in incidence may reveal environmental explanations for type 1 diabetes incidence. We aimed to study type 1 diabetes incidence in European childhood populations to assess whether an increase could be attributed to either period or cohort effects. METHODS: Nineteen EURODIAB centres provided single year incidence data for ages 0-14 in the 25-year period 1989-2013. Case counts and person years were classified by age, period and cohort (APC) in 1-year classes. APC Poisson regression models of rates were fitted using restricted cubic splines for age, period and cohort per centre and sex. Joint models were fitted for all centres and sexes, to find a parsimonious model. RESULTS: A total of 57,487 cases were included. In ten and seven of the 19 centres the APC models showed evidence of nonlinear cohort effects or period effects, respectively, in one or both sexes and indications of sex-specific age effects. Models showed a positive linear increase ranging from approximately 0.6 to 6.6%/year. Centres with low incidence rates showed the highest overall increase. A final joint model showed incidence peak at age 11.6 and 12.6 for girls and boys, respectively, and the rate-ratio was according to sex below 1 in ages 5-12. CONCLUSION: There was reasonable evidence for similar age-specific type 1 diabetes incidence rates across the EURODIAB population and peaks at a younger age for girls than boys. Cohort effects showed nonlinearity but varied between centres and the model did not contribute convincingly to identification of environmental causes of the increase.