With sustained growth of diabetes numbers, sustained patient engagement is essential. Using nationally available data, we have shown that the higher mortality associated with a diagnosis of T1DM/T2DM could produces loss of 6.4 million future life years in the current UK population. In the model, the ‘average’ person with T1DM (age 42.8 years) has a life expectancy from now of 32.6 years, compared to 40.2 years in the equivalent age non diabetes mellitus population, corresponding to lost life years (LLYs) of 7.6 years/average person. The ‘average’ person with T2DM (age 65.4 years) has a life expectancy from now of 18.6 years compared to the 20.3 years for the equivalent non diabetes mellitus population, corresponding to LLY of 1.7 years/average person. We estimate that for both T1DM and T2DM, one year with HbA1c >58 mmol/mol loses around 100 life days. Linking glycaemic control to mortality has the potential to focus minds on effective engagement with therapy and lifestyle recommendation adherence.

Objectives We conducted a Pakistan-wide community-based survey on the prevalence of type 2 diabetes using glycated haemoglobin (HbA1c) as the screening test. The aim was to estimate diabetes prevalence across different demographic groups as well as all regions of Pakistan. Design, settings and participants Multistaged stratified cluster sampling was used for the representative selection of people aged ≥20 years, residing in 378 sampled clusters of 16 randomly selected districts, in this cross-sectional study. Eligible participants had blood drawn for HbA1c analyses at field clinics near to their homes. The oral glucose tolerance test (OGTT) was conducted on a subsample of the participants. Overall and stratified prevalence of type 2 diabetes and its association with risk factors were estimated using logistic regression models. Main outcome measures Prevalence of prediabetes and type 2 diabetes. Results Of 18 856 eligible participants the prevalence of prediabetes was 10.91% (95% CI 10.46 to 11.36, n=2057) and type 2 diabetes was 16.98% (95% CI 16.44 to 17.51, n=3201). Overall, the mean HbA1c level was 5.62% (SD 1.96), and among newly diagnosed was 8.56% (SD 2.08). The prevalence was highest in age 51–60 years (26.03%, p<0.001), no formal education (17.66%, p<0.001), class III obese (35.09%, p<0.001), family history (31.29%, p<0.001) and female (17.80%, p=0.009). On multivariate analysis, there was a significant association between type 2 diabetes and older age, increase in body mass index and central obesity, positive family history, and having hypertension and an inverse relation with education as a categorical variable. On a subsample (n=1027), summary statistics for diagnosis of diabetes on HbA1c showed a sensitivity of 84.7%, specificity of 87.2% and area under the receiver operating characteristic curve 0.86, compared with OGTT. Conclusions The prevalence of type 2 diabetes and prediabetes is much higher than previously thought in Pakistan. Comprehensive strategies need to be developed to incorporate screening, prevention and treatment of type 2 diabetes at a community level.

Introduction The COVID‐19 pandemic has transformed lives across the world. In the UK, a public health driven policy of population ‘lockdown’ has had enormous personal and economic impact. Methods We compare UK response and outcomes with European countries of similar income and healthcare resources. We calibrate estimates of the economic costs as different % loss in Gross Domestic Product (GDP) against possible benefits of avoiding life years lost, for different scenarios where current COVID‐19 mortality and comorbidity rates were used to calculate the loss in life expectancy and adjusted for their levels of poor health and quality of life. We then apply a quality‐adjusted life years (QALY) value of £30,000 (maximum under national guidelines). Results There was a rapid spread of cases and significant variation both in severity and timing of both implementation and subsequent reductions in social restrictions. There was less variation in the trajectory of mortality rates and excess deaths, which have fallen across all countries during May/June 2020. The average age at death and life expectancy loss for non‐COVID‐19 was 79.1 and 11.4 years respectively while COVID‐19 were 80.4 and 10.1 years; including adjustments for life‐shortening comorbidities and quality of life plausibly reduces this to around 5 QALY lost for each COVID‐19 death. The lowest estimate for lockdown costs incurred was 40% higher than highest benefits from avoiding the worst mortality case scenario at full life expectancy tariff and in more realistic estimations they were over 5 times higher. Future scenarios showed in the best case a QALY value of £220k (7xNICE guideline) and in the worst‐case £3.7m (125xNICE guideline) was needed to justify the continuation of lockdown. Conclusion This suggests that the costs of continuing severe restrictions are so great relative to likely benefits in lives saved that a rapid easing in restrictions is now warranted.

Cardiometabolic disease is more common in patients with schizophrenia than the general population. The purpose of the study was to assess lifestyle factors, including diet and exercise, in patients with schizophrenia and estimate the prevalence of metabolic syndrome. This is a cross-sectional study of a representative group of outpatients with schizophrenia in Salford, UK. An interview supplemented by questionnaires was used to assess diet, physical activity, and cigarette and alcohol use. Likert scales assessed subjects’ views of diet and activity. A physical examination and relevant blood tests were conducted. Thirty-seven people were included in the study. 92% of men had central adiposity, as did 91.7% of women (International Diabetes Federation Definition). The mean age was 46.2 years and mean illness duration was 11.6 years. 67.6% fulfilled criteria for the metabolic syndrome. The mean number of fruit and vegetable portions per day was 2.8 ± 1.8. Over a third did not eat any fruit in a typical week. 42% reported doing no vigorous activity in a typical week. 64.9% smoked and in many cigarette use was heavy. The Likert scale showed that a high proportion of patients had insight into their unhealthy lifestyles. Within this sample, there was a high prevalence of poor diet, smoking and inadequate exercise. Many did not follow national recommendations for dietary intake of fruit and vegetables and daily exercise. These factors probably contribute to the high prevalence of metabolic syndrome. Many had insight into their unhealthy lifestyles. Thus, there is potential for interventions to improve lifestyle factors and reduce the risk of cardiometabolic disease.