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1.
Int J Popul Data Sci ; 6(1): 1387, 2021 Apr 15.
Article in English | MEDLINE | ID: mdl-34007896

ABSTRACT

INTRODUCTION: Studies of prevalence and the demographic profile of type 1 diabetes are challenging because of the relative rarity of the condition, however, these outcomes can be determined using routine healthcare data repositories. Understanding the epidemiology of type 1 diabetes allows for targeted interventions and care of this life-affecting condition. OBJECTIVES: To describe the prevalence, incidence and demographics of persons with type 1 diabetes diagnosed in Wales, UK, using the Secure Anonymised Information Linkage (SAIL) Databank. METHODS: Data derived from primary and secondary care throughout Wales available in the SAIL Databank were used to identify people with type 1 diabetes to determine the prevalence and incidence of type 1 diabetes over a 10 year period (2008-18) and describe the demographic and clinical characteristics of this population by age, socioeconomic deprivation and settlement type. The seasonal variation in incidence rates was also examined. RESULTS: The prevalence of type 1 diabetes in 2018 was 0.32% in the whole population, being greater in men compared to women (0.35% vs 0.28% respectively); highest in those aged 15-29 years (0.52%) and living in the most socioeconomically deprived areas (0.38%). The incidence of type 1 diabetes over 10 years was 14.0 cases/100,000 people/year for the whole population of Wales. It was highest in children aged 0-14 years (33.6 cases/100,000 people/year) and areas of high socioeconomic deprivation (16.8 cases/100,000 people/year) and least in those aged 45-60 years (6.5 cases/100,000 people/year) and in areas of low socioeconomic deprivation (11.63 cases/100,000 people/year). A seasonal trend in the diagnoses of type 1 diabetes was observed with higher incidence in winter months. CONCLUSION: This nation-wide retrospective epidemiological study using routine data revealed that the incidence of type 1 diabetes in Wales was greatest in those aged 0-14 years with a higher incidence and prevalence in the most deprived areas. These findings illustrate the need for health-related policies targeted at high deprivation areas to include type 1 diabetes in their remit.


Subject(s)
Diabetes Mellitus, Type 1 , Adolescent , Adult , Child , Child, Preschool , Databases, Factual , Diabetes Mellitus, Type 1/epidemiology , Female , Humans , Incidence , Infant , Infant, Newborn , Male , Middle Aged , Retrospective Studies , Wales/epidemiology , Young Adult
2.
Eur Heart J ; 33(7): 881-8, 2012 Apr.
Article in English | MEDLINE | ID: mdl-21444365

ABSTRACT

AIMS: A sequence variant, rs7025486[A], in DAB2IP on chromosome 9q33 has recently been associated with coronary heart disease (CHD). We sought to replicate this finding and to investigate associations with a panel of inflammatory and haemostatic biomarkers. We also sought to examine whether this variant, in combination with a chromosome 9p21 CHD variant (rs10757278) and the Framingham risk score (FRS), could improve the prediction of events compared with the FRS alone. METHODS AND RESULTS: rs7025486 was genotyped in 1386 CHD cases and 3532 controls and was associated with CHD [odds ratio (OR) of 1.16, 95% confidence interval (CI) 1.05-1.29, P= 0.003]. Meta-analysis, using data from the original report and from genome-wide association studies in both the Wellcome Trust Case Control Consortium and the Cardiovascular Health Study, comprising 9968 cases and 20 048 controls, confirmed the association (OR of 1.10, 95% CI 1.06-1.14, P= 3.2 × 10(-6)). There was no association with a panel of CHD biomarkers, including any lipid, inflammation, or coagulation trait, nor with telomere length. Addition to the FRS of this variant plus rs10757278 on chromosome 9p21 improved the area under the receiver-operating characteristic curve (A(ROC)) from 0.61 to 0.64 (P= 0.03) as well as improving the reclassification (net reclassification index = 11.1%, P= 0.007). CONCLUSION: This study replicates a previous association of a variant in DAB2IP with CHD. Addition of multiple variants improves the performance of predictive models based upon classical cardiovascular risk factors.


Subject(s)
Chromosomes, Human, Pair 9/genetics , Coronary Disease/genetics , Polymorphism, Single Nucleotide/genetics , ras GTPase-Activating Proteins/genetics , Aged , Case-Control Studies , Female , Humans , Kaplan-Meier Estimate , Male , Middle Aged , Prospective Studies , ROC Curve , Risk Factors
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