The attitude of healthcare professionals plays an important role in the uptake of diabetes self-management education: analysis of the Barriers to Uptake of Type 1 Diabetes Education (BUD1E) study survey.

AIM: To explore reasons for the poor uptake of accredited diabetes self-management education (DSME) in adults with Type 1 diabetes. METHODS: The study was set in an urban population in South London, UK. A cross sectional survey gathered demographic, diabetes service-use data, psychological scores and reasons for non-attendance at locally-available DSME. In addition, 56 healthcare professionals were surveyed. RESULTS: Responses to surveys were returned by 496 adults with Type 1 diabetes (33% response rate), of whom 263 had attended DSME (53%). Multivariable analysis adjusted for significant variables identified four key variables influencing attendance. Non-attendance was associated with men (OR 0.55 CI 0.37-0.84, p = 0.005), lower educational attainment (OR 0.45 CI 0.28-0.73, p = 0.001), higher glycated haemoglobin (OR 1.74 CI 1.03-2.94, p = 0.04) and healthcare professional encouragement to attend (OR 1.7 CI 1.28-2.3, p = 0.001). The most frequently reported barriers to attendance were work (37%) and time (14%) commitments. Only 49% of healthcare professionals (HCPs) correctly identified the most likely barriers. Those HCPs who had observed courses believed more in their efficacy, with higher uptake within their clinic population. CONCLUSIONS: Social determinants of health, particularly educational attainment and gender, increase health inequalities by influencing decisions to attend evidence-based education courses. Healthcare professional communication is paramount to encourage attendance, and observation of a course may facilitate this.

Factors influencing attendance at structured education for Type 1 diabetes in south London.

AIM: To investigate the factors influencing uptake of structured education for people with Type 1 diabetes in our local population in order to understand why such uptake is low. METHODS: We conducted a cross-sectional database study of adults with Type 1 diabetes in two south London boroughs, analysed according to Dose Adjustment For Normal Eating (DAFNE) attendance or non-attendance. Demographics, glycaemic control and service use, with subset analysis by ethnicity, were compared using univariate analysis. An exploratory regression model was used to identify influencing factors. RESULTS: The analysis showed that 73% of adults had not attended the DAFNE programme. For non-attenders vs attenders, male gender (59 vs 48%; P = 0.002), older age (39 vs 35 years; P < 0.001), non-white ethnicity (30 vs 20%; P = 0.001) and coming from an area of social deprivation (index of multiple deprivation score 31 vs 28; P < 0.001) were associated with non-attendance. The difference in gender (88% men vs 70% women; P < 0.001) and age (43 vs 34 years) persisted in the non-white group. Regression analysis showed that higher baseline HbA1c level (odds ratio 1.96; P = 0.004), younger age (odds ratio 0.98; P = 0.001) and lower social deprivation (odds ratio 0.52; P = 0.001) was associated with attendance. CONCLUSION: Socio-economic status and factors perceived as indicating greater severity of disease (HbA1c ) influence attendance at DAFNE. More work is necessary to understand the demography of non-attenders to aid future service design and alternative engagement strategies for these groups.

Miscoding, misclassification and misdiagnosis of diabetes in primary care.

AIMS: To determine the effectiveness of self-audit tools designed to detect miscoding, misclassification and misdiagnosis of diabetes in primary care. METHODS: We developed six searches to identify people with diabetes with potential classification errors. The search results were automatically ranked from most to least likely to have an underlying problem. Eight practices with a combined population of 72,000 and diabetes prevalence 2.9% (n = 2340) completed audit forms to verify whether additional information within the patients' medical record confirmed or refuted the problems identified. RESULTS: The searches identified 347 records, mean 42 per practice. Pre-audit 20% (n = 69) had Type 1 diabetes, 70% (n = 241) had Type 2 diabetes, 9% (n = 30) had vague codes that were hard to classify, 2% (n = 6) were not coded and one person was labelled as having gestational diabetes. Of records, 39.2% (n = 136) had important errors: 10% (n = 35) had coding errors; 12.1% (42) were misclassified; and 17.0% (59) misdiagnosed as having diabetes. Thirty-two per cent (n = 22) of people with Type 2 diabetes (n = 69) were misclassified as having Type 1 diabetes; 20% (n = 48) of people with Type 2 diabetes (n = 241) did not have diabetes; of the 30 patients with vague diagnostic terms, 50% had Type 2 diabetes, 20% had Type 1 diabetes and 20% did not have diabetes. Examples of misdiagnosis were found in all practices, misclassification in seven and miscoding in six. CONCLUSIONS: Volunteer practices successfully used these self-audit tools. Approximately 40% of patients identified by computer searches (5.8% of people with diabetes) had errors; misdiagnosis is commonest, misclassification may affect treatment options and miscoding in omission from disease registers and the potential for reduced quality of care.

Risk of myocardial infarction in men and women with type 2 diabetes in the UK: a cohort study using the General Practice Research Database.

AIMS/HYPOTHESIS: Our primary aim was to establish reliable and generalisable estimates of the risk of myocardial infarction (MI) for men and women with type 2 diabetes in the UK compared with people without diabetes. Our secondary aim was to investigate how the MI risk associated with diabetes differs between men and women. METHODS: A cohort study using the General Practice Research Database (1992-1999) was carried out, selecting 40,727 patients with type 2 diabetes and 194,913 age and sex-matched patients without diabetes. Rates of MI in men and women with and without diabetes were derived, as were hazard ratios for MI adjusted for known risk factors. RESULTS: The rate of MI in men with type 2 diabetes was 19.74 (95% CI 18.83-20.69) per 1,000 person-years compared with 16.18 (95% CI 15.33-17.08) per 1,000 person-years in women with type 2 diabetes. The overall adjusted relative risk of MI in diabetes versus no diabetes was 2.13 (95% CI 2.01-2.26) in men and 2.95 (95% CI 2.75-3.17) in women and decreased with age in both sexes. Women with type 2 diabetes aged 35 to 54 years were at almost five times the risk of MI compared with women of the same age without diabetes (HR 4.86 [95% CI 2.78-8.51]). CONCLUSIONS/INTERPRETATION: This study has demonstrated that women with type 2 diabetes are at a much greater relative risk of MI than men even when adjusted for risk factors.

Risk of stroke in people with type 2 diabetes in the UK: a study using the General Practice Research Database.

AIMS/HYPOTHESIS: Risk estimates for stroke in patients with diabetes vary. We sought to obtain reliable risk estimates for stroke and the association with diabetes, comorbidity and lifestyle in a large cohort of type 2 diabetic patients in the UK. MATERIALS AND METHODS: Using the General Practice Research Database, we identified all patients who had type 2 diabetes and were aged 35 to 89 years on 1 January 1992. We also identified five comparison subjects without diabetes and of the same age and sex. Hazard ratios (HRs) for stroke between January 1992 and October 1999 were calculated, and the association with age, sex, body mass index, smoking, hypertension, atrial fibrillation and duration of diabetes was investigated. RESULTS: The absolute rate of stroke was 11.91 per 1,000 person-years (95% CI 11.41-12.43) in people with diabetes (n = 41,799) and 5.55 per 1,000 person-years (95% CI 5.40-5.70) in the comparison group (n = 202,733). The age-adjusted HR for stroke in type 2 diabetic compared with non-diabetic subjects was 2.19 (95% CI 2.09-2.32) overall, 2.08 (95% CI 1.94-2.24) in men and 2.32 (95% CI 2.16-2.49) in women. The increase in risk attributable to diabetes was highest among young women (HR 8.18; 95% CI 4.31-15.51) and decreased with age. No investigated comorbidity or lifestyle characteristic emerged as a major contributor to risk of stroke. CONCLUSIONS/INTERPRETATION: This study provides risk estimates for stroke for an unselected population from UK general practice. Patients with type 2 diabetes were at an increased risk of stroke, which decreased with age and was higher in women. Additional risk factors for stroke in type 2 diabetic patients included duration of diabetes, smoking, obesity, atrial fibrillation and hypertension.

Mortality in people with type 2 diabetes in the UK.

AIMS: Under-reporting of diabetes on death certificates contributes to the unreliable estimates of mortality as a result of diabetes. The influence of obesity on mortality in Type 2 diabetes is not well documented. We aimed to study mortality from diabetes and the influence of obesity on mortality in Type 2 diabetes in a large cohort selected from the General Practice Research Database (GPRD). Methods A cohort of 44 230 patients aged 35-89 years in 1992 with Type 2 diabetes was identified. A comparison group matched by year of birth and sex with no record of diabetes at any time was identified (219 797). Hazards ratios (HRs) for all-cause mortality during the period January 1992 to October 1999 were calculated using the Cox Proportional Hazards Model. The effects of body mass index (BMI), smoking and duration of diabetes on all-cause mortality amongst people with diabetes was assessed (n = 28 725). Results The HR for all-cause mortality in Type 2 diabetes compared with no diabetes was 1.93 (95% CI 1.89-1.97), in men 1.77 (1.72-1.83) and in women 2.13 (2.06-2.20). The HR decreased with increasing age. In the multivariate analysis in diabetes only, the HR for all-cause mortality amongst smokers was 1.50 (1.41-1.61). Using BMI 20-24 kg/m(2) as the reference range, for those with a BMI 35-54 kg/m(2) the HR was 1.43 (1.28-1.59) and for those with a BMI 15-19 kg/m(2) the HR was 1.38 (1.18-1.61). CONCLUSIONS: Patients with Type 2 diabetes have almost double the mortality rate compared with those without. The relative risk decreases with age. In people with Type 2 diabetes, obesity and smoking both contribute to the risk of all-cause mortality, supporting doctrines to stop smoking and lose weight.

All-cause mortality rates in patients with type 1 diabetes mellitus compared with a non-diabetic population from the UK general practice research database, 1992-1999.

AIMS/HYPOTHESIS: We compiled up to date estimates of the absolute and relative risk of all-cause mortality in patients with type 1 diabetes in the UK. MATERIALS AND METHODS: We selected patients with type 1 diabetes (n=7,713), and for each of these diabetic subjects five age- and sex-matched control subjects without diabetes (n=38,518) from the General Practice Research Database (GPRD). Baseline was 1 January 1992; subjects were followed until 1999. The GPRD is a large primary-care database containing morbidity and mortality data of a large sample representative of the UK population. Deaths occurring in the follow-up period were identified. RESULTS: The study comprised 208,178 person-years of follow-up. The prevalence of type 1 diabetes was 2.15/1,000 subjects in 1992 (mean age 33 years, SD 15). Annual mortality rates were 8.0 per 1,000 person-years (95% CI 7.2-8.9) in type 1 diabetic subjects compared with 2.4 per 1,000 person-years (95% CI 2.2-2.6) in those without diabetes (hazard ratio [HR]=3.7, 95% CI 3.2-4.3). The increased mortality rates in patients with type 1 diabetes were apparent across all age-bands. The HR was higher in women (HR=4.5, 95% CI 3.5-5.6 compared with non-diabetic women) than men (HR=3.3, 95% CI 2.7-4.0), such that the sex difference (p<0.0001) in mortality in the non-diabetic population was abolished (p=0.3) in the type 1 diabetic patients. The predominant cause of death in patients with type 1 diabetes was cardiovascular disease. CONCLUSIONS/INTERPRETATION: Despite advances in care, UK mortality rates in the past decade continue to be much greater in patients with type 1 diabetes than in those without diabetes.

Breathlessness in humans activates insular cortex.

Dyspnea (shortness of breath, breathlessness) is a major and disabling symptom of heart and lung disease. The representation of dyspnea in the cerebral cortex is unknown. In the first study designed to explore the central neural structures underlying perception of dyspnea, we evoked the perception of severe 'air hunger' in healthy subjects by restraining ventilation below spontaneous levels while holding arterial oxygen and carbon dioxide levels constant. PET revealed that air hunger activated the insular cortex. The insula is a limbic structure also activated by visceral stimuli, temperature, taste, nausea and pain. Like dyspnea, such perceptions underlie behaviors essential to homeostasis and survival.