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Aim To understand the relationship between HbA1c and brain health across the entire glycaemic spectrum. Materials and Methods We used data from the UK Biobank cohort consisting of 500,000 individuals aged 40–69 years. HbA1c and diabetes diagnosis were used to define baseline glycaemic categories. Our outcomes included incident all‐cause dementia, vascular dementia (VD), Alzheimer's dementia (AD), hippocampal volume (HV), white matter hyperintensity (WMH) volume, cognitive function and decline. The reference group was normoglycaemic individuals (HbA1c ≥35 &

Background: Evidence is limited on ethnic differences in associations between kidney function markers and mortality or cardiovascular disease (CVD). Methods: Baseline cross-sectional analysis and longitudinal follow-up study of a UK population-based cohort of 1,116 Europeans and 1,104 South Asians of predominantly Indian descent, age 52 ± 7 years at baseline (1988–1991). Kidney function was estimated using Cystatin C and creatinine-based chronic kidney disease (CKD) Epidemiology Collaboration estimated glomerular filtration rate (eGFR) equations, and urinary albumin-creatinine ratio (ACR). Mortality was captured at 27 years, and incident CVD at 22 years, from death certification, medical records and participant report. Longitudinal associations between eGFR/ACR and mortality/incident CVD were examined using Cox models. Results: eGFRcys was lower and ACR higher in South Asians than Europeans. eGFRcys and ­eGFRcreat were more strongly associated with outcomes in Europeans than South Asians. Conversely, associations between ACR and outcomes were greater in South Asians than Europeans, for example, for CVD mortality: HRs (95% CI) adjusted for CVD risk factors and ACR/eGFRcys as appropriate, p for ethnicity interaction: eGFRcys: Europeans: 0.76 (0.62–0.92), South Asians: 0.92 (0.78–1.07), p = 0.05, eGFRcreat: Europeans 0.81 (0.67–0.99), South Asians 1.18 (0.97–1.41), p = 0.002, ACR: ­Europeans: 1.24 (1.08–1.42), South Asians: 1.39 (1.25–1.57), p= 0.23. Addition of all CKD measures to a standard CVD risk factor model modestly improved prediction capability in ­Europeans; in South Asians only ACR contributed to improvement. Conclusions: Strong associations between ACR and outcomes in South Asians of predominantly Indian origin, and null associations for eGFRcys and eGFRcreat, suggest that ACR may have greater utility in CVD risk prediction in South Asians. Further work is needed to validate these ­findings.

AimsTo investigate the relationship between glycaemia and cognitive function, brain structure and incident dementia using bidirectional Mendelian randomisation (MR).MethodsUK Biobank (n~500,000) individuals, aged 40-69 years at baseline. Our exposures were genetic instruments for type-2 diabetes (163 variants) and HbA1c (52 variants) and our outcomes were reaction time (RT - milliseconds), visual memory (number of incorrect responses), hippocampal and white matter hyperintensity volumes (both mm3), Alzheimer’s disease (AD). To study potential bidirectional effects, we then investigated the associations between genetic variants for RT (43 variants) and clinical type-2 diabetes and measured HbA1c. We used conventional inverse-variance weighted (IVW) MR, alongside standard MR sensitivity analyses.ResultsUsing IVW, genetic liability to type-2 diabetes was not associated with reaction time (exponentiated ß=1.00, 95%CI=1.00; 1.00), visual memory (expß=1.00, 95%CI=0.99; 1.00), white matter hyperintensity volume (expß=0.98, 95%CI=0.93; 1.03), hippocampal volume (coefficient mm3=0.00, 95%CI=-0.01; 0.01) or risk of AD (OR 0.97, 95%CI=0.89; 1.06). HbA1c was not associated with reaction time (expß=1.01, 95%CI=1.00; 1.01), white matter hyperintensity volume (expß=0.88, 95%CI=0.73; 1.07), hippocampal volume (coefficient=-0.02, 95%CI=-0.10; 0.06), risk of AD (OR 0.94, 95%CI=0.47; 1.86), but HbA1c was associated with visual memory (expß=1.06, 95%CI=1.05; 1.07) using a weighted median approach. IVW showed no evidence that reaction time was associated with diabetes (OR 0.96, 95%CI=0.63; 1.46) or HbA1c (coefficient=-0.08, 95%CI=-0.57; 0.42). MR-Egger intercept p-values indicated no major issues with unbalanced horizontal pleiotropy (all p>0.05).ConclusionsOverall, we observed little evidence of causal associations between glycaemia and cognition, structural brain and dementia phenotypes.AbbreviationsAlzheimer’s dementia (AD)Benjamini-Hochberg false discovery rate (BH-FDR)Genome-wide association study (GWAS)Hippocampal volume (HV)Hospital episode statistics (HES)International Classification of Diseases (ICD)Inverse variance weighted (IVW)Magnetic resonance imaging (MRI)Mendelian randomization (MR)Quality control (QC)Reaction time (RT)Simulation extrapolation (SIMEX)UK Biobank (UKB)Visual memory (VM)Weighted median Estimator (WME)White matter hyperintensity volume (WMHV)

The right drug, for the right patient, at the right time. Who wouldn’t want this? For diabetologists, after decades of domination by biguanides and sulfonylureas, only briefly punctuated by thiazolidinediones, the choice of early-stage glucose-lowering agents has recently more than doubled, now including glucagon-like peptide 1 (GLP-1) receptor agonists, and dipeptidyl peptidase 4 (DPP-4) and sodium–glucose cotransporter 2 (SGLT2) inhibitors. Armed with this greater choice, can we now fulfill the promise of precision medicine? Half of the 500 million people in the world with diabetes live in either China or the Indian subcontinent (1). Aside from simple demographics, these huge numbers are largely due to the greater diabetes susceptibility experienced by both populations. In this issue, Gan and associates (2) hypothesize that pathophysiological differences contributing to this greater susceptibility may be associated with different glycemic responses to diabetes medication. This is not unreasonable; 20% of new drug approvals show differences in exposure or response by ethnicity (3). They performed a systematic review and meta-analysis of published randomized clinical trials comparing absolute change in HbA1c from baseline to either 24 or 52 weeks in studies that recruited predominantly (>70%) Asians versus studies that recruited predominantly (>70%) whites. They report that SGLT2 and, possibly, DPP-4 inhibitors are more effective in lowering HbA1c in Asians than in whites. There was no ethnic difference in efficacy of GLP-1 receptor agonists. Their findings are somewhat at odds with previous work. The most striking observation, of an ∼0.3% lower HbA1c in Asians than in whites in response to SGLT2 inhibitors, contrasts with a previous meta-analysis reporting no ethnic difference (4), though an agent-specific analysis did show modest superiority of dapagliflozin (0.16%) in Asians versus non-Asians. Gan et al. …

Aims/hypothesis Excess risks of type 2 diabetes in UK South Asians (SA) and African Caribbeans (AC) compared with Europeans remain unexplained. We studied risks and determinants of type 2 diabetes in first- and second-generation (born in the UK) migrants, and in those of mixed ethnicity. Methods Data from the UK Biobank, a population-based cohort of ~500,000 participants aged 40–69 at recruitment, were used. Type 2 diabetes was assigned using self-report and HbA1c. Ethnicity was both self-reported and genetically assigned using admixture level scores. European, mixed European/South Asian (MixESA), mixed European/African Caribbean (MixEAC), SA and AC groups were analysed, matched for age and sex to enable comparison. In the frames of this cross-sectional study, we compared type 2 diabetes in second- vs first-generation migrants, and mixed ethnicity vs non-mixed groups. Risks and explanations were analysed using logistic regression and mediation analysis, respectively. Results Type 2 diabetes prevalence was markedly elevated in SA (599/3317 = 18%) and AC (534/4180 = 13%) compared with Europeans (140/3324 = 4%). Prevalence was lower in second- vs first-generation SA (124/1115 = 11% vs 155/1115 = 14%) and AC (163/2200 = 7% vs 227/2200 = 10%). Favourable adiposity (i.e. lower waist/hip ratio or BMI) contributed to lower risk in second-generation migrants. Type 2 diabetes in mixed populations (MixESA: 52/831 = 6%, MixEAC: 70/1045 = 7%) was lower than in comparator ethnic groups (SA: 18%, AC: 13%) and higher than in Europeans (4%). Greater socioeconomic deprivation accounted for 17% and 42% of the excess type 2 diabetes risk in MixESA and MixEAC compared with Europeans, respectively. Replacing self-reported with genetically assigned ethnicity corroborated the mixed ethnicity analysis. Conclusions/interpretation Type 2 diabetes risks in second-generation SA and AC migrants are a fifth lower than in first-generation migrants. Mixed ethnicity risks were markedly lower than SA and AC groups, though remaining higher than in Europeans. Distribution of environmental risk factors, largely obesity and socioeconomic status, appears to play a key role in accounting for ethnic differences in type 2 diabetes risk. Graphical abstract

We investigated the relationship between glycemia and cognitive function, brain structure and incident dementia using bidirectional Mendelian randomization (MR). Data were from the UK Biobank (n = ∼500,000). Our exposures were genetic instruments for type 2 diabetes (157 variants) and HbA1c (51 variants) and our outcomes were reaction time (RT), visual memory, hippocampal volume (HV), white matter hyperintensity volume (WMHV), and Alzheimer dementia (AD). We also investigated associations between genetic variants for RT (43 variants) and diabetes and HbA1c. We used conventional inverse-variance–weighted (IVW) MR alongside MR sensitivity analyses. Using IVW, genetic liability to type 2 diabetes was not associated with RT (exponentiated β [expβ] = 1.00 [95% CI 1.00; 1.00]), visual memory (expβ = 1.00 [95% CI 0.99; 1.00]), WMHV (expβ = 0.99 [95% CI 0.97; 1.01]), HV (β-coefficient mm3 = −2.30 [95% CI −12.39; 7.78]) or AD (odds ratio [OR] 1.15 [95% CI 0.87; 1.52]). HbA1c was not associated with RT (expβ = 1.00 [95% CI 0.99; 1.02]), visual memory (expβ = 0.99 [95% CI 0.96; 1.02]), WMHV (expβ = 1.03 [95% CI 0.88; 1.22]), HV (β = −21.31 [95% CI −82.96; 40.34]), or risk of AD (OR 1.09 [95% CI 0.42; 2.83]). IVW showed that reaction time was not associated with diabetes risk (OR 0.94 [95% CI 0.54; 1.65]), or with HbA1c (β-coefficient mmol/mol = −0.88 [95% CI = −1.88; 0.13]) after exclusion of a pleiotropic variant. Overall, we observed little evidence of causal association between genetic instruments for type 2 diabetes or peripheral glycemia and some measures of cognition and brain structure in midlife.

IntroductionDiabetes is observed to increase cancer risk, leading to hypothesized direct effects of either hyperglycemia or medication. We investigated associations between glycosylated hemoglobin (HbA1c) across the whole glycemic spectrum and incidence of 16 cancers in a population sample with comprehensive adjustment for risk factors and medication.Research design and methodsLinked data from the UK Biobank and UK cancer registry for all individuals with baseline HbA1c and no history of cancer at enrollment were used. Incident cancer was based on International Classification of Diseases – 10th Edition diagnostic codes. Age-standardized incidence rates were estimated by HbA1c category. Associations between HbA1c, modeled as a restricted cubic spline, and cancer risk were estimated using Cox proportional hazards models.ResultsAmong 378 253 individuals with average follow-up of 7.1 years, 21 172 incident cancers occurred. While incidence for many of the 16 cancers was associated with hyperglycemia in crude analyses, these associations disappeared after multivariable adjustment, except for pancreatic cancer (HR 1.55, 95% CI 1.22 to 1.98 for 55 vs 35 mmol/mol), and a novel finding of an inverse association between HbA1c and premenopausal breast cancer (HR 1.27, 95% CI 1.00 to 1.60 for 25 vs 35 mmol/mol; HR 0.71, 95% CI 0.54 to 0.94 for 45 vs 35 mmol/mol), not observed for postmenopausal breast cancer. Adjustment for diabetes medications had no appreciable impact on HRs for cancer.ConclusionsApart from pancreatic cancer, we did not demonstrate any independent positive association between HbA1c and cancer risk. These findings suggest that the potential for a cancer-inducing, direct effect of hyperglycemia may be misplaced.

Background Type 2 diabetes mellitus (T2DM) disproportionately affects individuals of nonwhite ethnic origin. Timely and appropriate initiation and intensification of glucose-lowering therapy is key to reducing the risk of major vascular outcomes. Given that ethnic inequalities in outcomes may stem from differences in therapeutic management, the aim of this study was to identify ethnic differences in the timeliness of initiation and intensification of glucose-lowering therapy in individuals newly diagnosed with T2DM in the United Kingdom. Methods and findings An observational cohort study using the Clinical Practice Research Datalink was conducted using 162,238 adults aged 18 and over diagnosed with T2DM between 1990 and 2017 (mean age 62.7 years, 55.2% male); 93% were of white ethnicity (n = 150,754), 5% were South Asian (n = 8,139), and 2.1% were black (n = 3,345). Ethnic differences in time to initiation and intensification of diabetes treatment were estimated at three time points (initiation of noninsulin monotherapy, intensification to noninsulin combination therapy, and intensification to insulin therapy) using multivariable Cox proportional hazards regression adjusted for factors a priori hypothesised to be associated with initiation and intensification: age, sex, deprivation, glycated haemoglobin (HbA1c), body mass index (BMI), smoking status, comorbidities, consultations, medications, calendar year, and clustering by practice. Odds of experiencing therapeutic inertia (failure to intensify treatment within 12 months of HbA1c >7.5% [58 mmol/mol]), were estimated using multivariable logistic regression adjusted for the same hypothesised confounders. Noninsulin monotherapy was initiated earlier in South Asian and black groups (South Asian HR 1.21, 95% CI 1.08–1.36, p < 0.001; black HR 1.29, 95% CI 1.05–1.59, p = 0.017). Correspondingly, no ethnic differences in therapeutic inertia were evident at initiation. Intensification with noninsulin combination therapy was slower in both nonwhite ethnic groups relative to white (South Asian HR 0.80, 95% CI 0.74–0.87, p < 0.001; black HR 0.79, 95% CI 0.70–0.90, p < 0.001); treatment inertia at this stage was greater in nonwhite groups relative to white (South Asian odds ratio [OR] 1.45, 95% CI 1.23–1.70, p < 0.001; black OR 1.43, 95% CI 1.09–1.87, p = 0.010). Intensification to insulin therapy was slower again for black groups relative to white groups (South Asian HR 0.49, 95% CI 0.41–0.58, p < 0.001; black HR 0.69, 95% CI 0.53–0.89, p = 0.012); correspondingly, treatment inertia was significantly higher in nonwhite groups at this stage relative to white groups (South Asian OR 2.68, 95% CI 1.89–3.80 p < 0.001; black OR 1.82, 95% CI 1.13–2.79, p = 0.013). At both stages of treatment intensification, nonwhite groups had fewer HbA1c measurements than white groups. Limitations included variable quality and completeness of routinely recorded data and a lack of information on medication adherence. Conclusions In this large UK cohort, we found persuasive evidence that South Asian and black groups intensified to noninsulin combination therapy and insulin therapy more slowly than white groups and experienced greater therapeutic inertia following identification of uncontrolled HbA1c. Reasons for delays are multifactorial and may, in part, be related to poorer long-term monitoring of risk factors in nonwhite groups. Initiatives to improve timely and appropriate intensification of diabetes treatment are key to reducing disparities in downstream vascular outcomes in these populations., Rohini Mathur and colleagues study disparities in diabetes treatment in the UK., Author summary Why was this study done? In the UK, ethnic minority populations, particularly of South Asian and black African/Caribbean descent, have a higher risk of type 2 diabetes mellitus (T2DM) and related adverse outcomes, such as cardiovascular disease, than the white population. Timely and appropriate diabetes treatment can substantially reduce risk of adverse outcomes associated with T2DM. We sought to quantify ethnic differences in time to initiation and intensification of diabetes treatment among individuals newly diagnosed with T2DM to assess whether these clinically modifiable factors may contribute to ethnic differences in outcomes. What did the researchers do and find? We used routinely recorded data from general practices across the UK to identify people newly diagnosed with T2DM and compared how long it took to initiate and intensify diabetes treatment, comparing people of white, South Asian, and black ethnicity. We found that South Asian and black groups initiated diabetes treatment more quickly than white groups but were slower to intensify to second- and third-line treatment regimes. What do these findings mean? Although time to initial treatment of type 2 diabetes was appropriate, ethnic disparities in subsequent longer-term treatment may contribute to the worse outcomes seen in ethnic minority populations in the UK. Interventions to improve timely and appropriate intensification of diabetes treatment are key to reducing disparities in the downstream adverse outcomes of T2DM.

Objective: To understand the relationship across the glycaemic spectrum with incident dementia, brain structure, and cognitive decline. Research Design and Methods: UK Biobank participants, aged 40-69 at recruitment. HbA1c and diabetes diagnosis define baseline glycaemic categories. Outcomes included incident vascular dementia (VD), Alzheimers dementia (AD), hippocampal volume (HV), white matter hyperintensity (WMH) volume, cognitive function and decline. All results are in reference to normoglycaemic individuals (HbA1c 35

BackgroundType 2 diabetes mellitus (T2DM) risk is markedly higher in UK South Asians (SA) and African Caribbeans (AC) compared to Europeans. Explanations for this excess are unclear. We therefore compared risks and determinants of T2DM in first- and second-generation (born in the UK) migrants, and in those of mixed ethnicity populations.MethodsData from the UK Biobank, a large population-based cohort of volunteers aged 40-69, were used. T2DM was assigned using self-report and glycated haemoglobin. Ethnicity was self-assigned. Using logistic regression and mediation analysis, we compared T2DM between first- and second-generation migrants, and between mixed European/South Asians (MixESA), or mixed European/African Caribbeans (MixEAC) with both Europeans and SA or AC respectively.ResultsT2DM prevalence was three to five times higher in SA and AC compared with Europeans [OR (95%CI): 4·80(3·60,6·40) and 3·30(2·70,4·10) respectively]. T2DM was 20-30% lower in second versus first generation SA and AC migrants [0·78(0·60,1·01) and 0·71(0·57,0·87) respectively]. T2DM in mixed populations was lower than comparator ethnic minority groups [MixESA versus SA 0·29(0·21,0·39), MixEAC versus AC 0·48(0·37,0·62)] and higher than Europeans, in MixESA 1·55(1·11, 2·17), and in MixEAC 2·06 (1·53, 2·78). Improved adiposity patterns in second generation migrants made an important contribution to risk reduction. Greater socioeconomic deprivation accounted for 17% and 42% of the excess risk of T2DM in MixESA and MixEAC compared to Europeans, respectively.ConclusionExcess T2DM risks in South Asians and African Caribbeans compared with Europeans in the UK are attenuated by ∼20% in second-generation migrants, demonstrating the marked benefits of favourable changes in environmental risk factors. T2DM prevalence in people of mixed ethnicity was also raised compared with Europeans, but considerably less than in the ethnic minority group; persistent socioeconomic disadvantage accounted for some of the residual excess.

Background Type 2 diabetes is 2–3 times more prevalent in people of South Asian and African/African Caribbean ethnicity than people of European ethnicity living in the UK. The former 2 groups also experience excess atherosclerotic cardiovascular disease (ASCVD) complications of diabetes. We aimed to study ethnic differences in statin initiation, a cornerstone of ASCVD primary prevention, for people with type 2 diabetes. Methods and findings Observational cohort study of UK primary care records, from 1 January 2006 to 30 June 2019. Data were studied from 27,511 (88%) people of European ethnicity, 2,386 (8%) people of South Asian ethnicity, and 1,142 (4%) people of African/African Caribbean ethnicity with incident type 2 diabetes, no previous ASCVD, and statin use indicated by guidelines. Statin initiation rates were contrasted by ethnicity, and the number of ASCVD events that could be prevented by equalising prescribing rates across ethnic groups was estimated. Median time to statin initiation was 79, 109, and 84 days for people of European, South Asian, and African/African Caribbean ethnicity, respectively. People of African/African Caribbean ethnicity were a third less likely to receive guideline-indicated statins than European people (n/N [%]: 605/1,142 [53%] and 18,803/27,511 [68%], respectively; age- and gender-adjusted HR 0.67 [95% CI 0.60 to 0.76], p < 0.001). The HR attenuated marginally in a model adjusting for total cholesterol/high-density lipoprotein cholesterol ratio (0.77 [95% CI 0.69 to 0.85], p < 0.001), with no further diminution when deprivation, ASCVD risk factors, comorbidity, polypharmacy, and healthcare usage were accounted for (fully adjusted HR 0.76 [95% CI 0.68, 0.85], p < 0.001). People of South Asian ethnicity were 10% less likely to receive a statin than European people (1,489/2,386 [62%] and 18,803/27,511 [68%], respectively; fully adjusted HR 0.91 [95% CI 0.85 to 0.98], p = 0.008, adjusting for all covariates). We estimated that up to 12,600 ASCVD events could be prevented over the lifetimes of people currently affected by type 2 diabetes in the UK by equalising statin prescribing across ethnic groups. Limitations included incompleteness of recording of routinely collected data. Conclusions In this study we observed that people of African/African Caribbean ethnicity with type 2 diabetes were substantially less likely, and people of South Asian ethnicity marginally less likely, to receive guideline-indicated statins than people of European ethnicity, even after accounting for sociodemographics, healthcare usage, ASCVD risk factors, and comorbidity. Underuse of statins in people of African/African Caribbean or South Asian ethnicity with type 2 diabetes is a missed opportunity to prevent cardiovascular events., In a retrospective cohort study, Sophie Eastwood and colleagues investigate the association between ethnicity and statin initiation for people with type 2 diabetes in UK., Author summary Why was this study done? People of South Asian and African/African Caribbean ethnicity living in the UK are more likely to have type 2 diabetes than people of European ethnicity, and have higher rates of cardiovascular complications, e.g., heart attacks and strokes. Lowering blood cholesterol with statin treatment reduces cardiovascular complications, but previous studies suggest ethnic differences exist in statin prescribing for people with diabetes. However, no study has sought explanations for identified ethnic differences, or accounted for changes in prescribing guidelines, so we aimed to provide a timely, representative assessment of ethnic differences in guideline-indicated statin prescribing in type 2 diabetes. What did the researchers do and find? We identified people with newly diagnosed type 2 diabetes in primary care eligible for statin treatment for primary prevention of cardiovascular disease, then compared rates of statin initiation for people of European, South Asian, and African/African Caribbean ethnicity. People of African/African Caribbean ethnicity with type 2 diabetes were 24% less likely to receive guideline-indicated statin treatment than people of European ethnicity, and people of South Asian ethnicity 9% less likely. Ethnic differences remained after allowing for differences in cholesterol levels, other cardiovascular risk factors, demographic factors, deprivation, healthcare usage, comorbidity, and polypharmacy. We estimated that equalising statin prescribing rates across these 3 ethnic groups would prevent up to 12,600 heart attacks and strokes over the lifetimes of people currently affected by type 2 diabetes in the UK. What do these findings mean? People with type 2 diabetes of African/African Caribbean and South Asian ethnicities are less likely to be prescribed a statin for primary prevention of cardiovascular disease in the UK than people of European ethnicity. Policies to increase statin use among people of African/African Caribbean and South Asian ethnicity with type 2 diabetes could substantially reduce the excess burden of cardiovascular events in these groups.

It is unknown whether associations between blood pressure (BP) and stroke vary between Europeans and South Asians, despite higher stroke rates in the latter. We report findings from a UK cohort study of 1375 European and 1074 South Asian men, not receiving antihypertensive medication, aged 40 to 69 years at baseline (1988–1991). Assessment included BP, blood tests, anthropometry, and questionnaires. Incident stroke was established at 20 years from death certification, hospital and primary care records, and participant report. South Asians had higher systolic BP, diastolic BP, and mean arterial pressure than Europeans, and similar pulse pressure. Associations between systolic BP or diastolic BP and stroke were stronger in South Asians than Europeans, after adjustment for age, smoking status, waist/hip ratio, total/high-density lipoprotein-cholesterol ratio, diabetes mellitus, fasting glucose, physical activity, and heart rate (systolic BP: Europeans [odds ratio, 1.22; 95% confidence interval, 0.98–1.51], South Asians [1.56; 1.24–1.95]; ethnic difference P =0.04; diastolic BP: Europeans [0.90; 0.71–1.13], South Asians [1.68; 1.32–2.15]; P

Summary Aims: South Asians in the UK have high cardiovascular disease (CVD) mortality. Therefore, this population is likely to benefit from screening programmes. To address this issue, an initiative was set up between the Royal Free Hampstead NHS Trust, H.E.A.R.T. UK and two Hindu temples in North London to provide screening for CVD risk factors in the community. Methods: A total of 434 individuals of Gujarati Indian origin were screened. Measurements included anthropometry, blood pressure and lipid profiles. Three different scoring systems: Framingham, Joint British Societies’ 2 and QRISK2 were used to estimate CVD risk. Results: At least one modifiable CVD risk factor was present in 92% of the individuals screened; 52% were hypertensive, 40% were obese, 75% had central adiposity and 10% had total cholesterol/high density lipoprotein cholesterol ratio > 6. In addition, 37% of a subset of 104 individuals with a fasting sample fulfilled the diagnostic criteria for metabolic syndrome. Overall, 15% of participants screened had a 10-year CV risk score > 20% using QRISK2. The three risk score calculators showed moderate agreement: QRISK2 and JBS2 (kappa 0.61, 95% CI 0.54–0.67), QRISK2 and Framingham (kappa 0.63, 95% CI 0.57–0.70) and JBS2 and Framingham (kappa 0.70, 95% CI 0.64–0.75). Conclusions: A high prevalence of modifiable risk factors for CVD was detected in the population screened.

OBJECTIVE We examined longitudinal associations between prediabetes and cardiovascular disease (CVD) (coronary heart disease [CHD] and stroke) in Europeans and South Asians. RESEARCH DESIGN AND METHODS This was a U.K. cohort study of 1,336 Europeans and 1,139 South Asians, aged 40–69 years at baseline (1988–1991). Assessment included blood pressure, blood tests, anthropometry, and questionnaires. Prediabetes was determined by OGTT or HbA1c, using either International Expert Committee (IEC) (HbA1c 6.0–6.5% [42–48 mmol/mol]) or American Diabetes Association (ADA) (HbA1c 5.7–6.5% [39–48 mmol/mol]) cut points. Incident CHD and stroke were established at 20 years from death certification, hospital admission, primary care record review, and participant report. RESULTS Compared with normoglycemic individuals, IEC-defined prediabetes was related to both CHD and CVD risk in Europeans but not South Asians (subhazard ratio for CHD 1.68 [95% CI 1.19, 2.38] vs. 1.00 [0.75, 1.33], ethnicity interaction P = 0.008, and for CVD 1.49 [1.08, 2.07] vs. 1.03 [0.78, 1.36], ethnicity interaction P = 0.04). Conversely, IEC-defined prediabetes was associated with stroke risk in South Asians but not Europeans (1.73 [1.03, 2.90] vs. 0.85 [0.44, 1.64], ethnicity interaction P = 0.11). Risks were adjusted for age, sex, smoking, total-to-HDL cholesterol ratio, waist-to-hip ratio, systolic blood pressure, and antihypertensive use. Associations were weaker for OGTT or ADA-defined prediabetes. Conversion from prediabetes to diabetes was greater in South Asians, but accounting for time to conversion did not account for these ethnic differences. CONCLUSIONS Associations between prediabetes and CVD differed by prediabetes diagnostic criterion, type of CVD, and ethnicity, with associations being present for overall CVD in Europeans but not South Asians. Substantiation of these findings and investigation of potential explanations are required.

OBJECTIVE Structured patient education programs can reduce the risk of diabetes-related complications. However, people appear to have difficulties attending face-to-face education and alternatives are needed. This review looked at the impact of computer-based diabetes self-management interventions on health status, cardiovascular risk factors, and quality of life of adults with type 2 diabetes. RESEARCH DESIGN AND METHODS We searched The Cochrane Library, Medline, Embase, PsycINFO, Web of Science, and CINAHL for relevant trials from inception to November 2011. Reference lists from relevant published studies were screened and authors contacted for further information when required. Two authors independently extracted relevant data using standard data extraction templates. RESULTS Sixteen randomized controlled trials with 3,578 participants met the inclusion criteria. Interventions were delivered via clinics, the Internet, and mobile phones. Computer-based diabetes self-management interventions appear to have small benefits on glycemic control: the pooled effect on HbA1c was −0.2% (−2.3 mmol/mol [95% CI −0.4 to −0.1%]). A subgroup analysis on mobile phone–based interventions showed a larger effect: the pooled effect on HbA1c from three studies was −0.50% (−5.46 mmol/mol [95% CI −0.7 to −0.3%]). There was no evidence of improvement in depression, quality of life, blood pressure, serum lipids, or weight. There was no evidence of significant adverse effects. CONCLUSIONS Computer-based diabetes self-management interventions to manage type 2 diabetes appear to have a small beneficial effect on blood glucose control, and this effect was larger in the mobile phone subgroup. There was no evidence of benefit for other biological, cognitive, behavioral, or emotional outcomes.

Proposed as potential mood-enhancing therapy 1, evidence linking statin use with depression remains conflicting 2. Marked ethnic differences exist in rates of cardiovascular disease (CVD), depression and responses to some drugs 3,4, and yet ethnic minority groups (EMGs) have been under-represented in statin trials and no studies have examined ethnic differences in the statin–depression relationship. Cross-sectional data from a population-based tri-ethnic study 5 were available on 638 White Europeans, 487 South Asians and 208 African-Caribbeans. Depression (score of ≥4/10 on the ethnically-validated Geriatric Depression Scale 6), and other psychosocial, behavioural, anthropometric and medication history data were collected. Statin use was identified by prescription from participant/GP records (as were CVD and hypertension). Diabetes was identified from medical records, diagnosis recall or oral glucose tolerance test 5. Statin use was modelled as a predictor for depression in logistic regression analyses, with ethnicity by statin use interaction terms included. Models were also stratified by ethnicity. In a 77% male sample (mean age 70 years), 56% of participants were receiving statins (48% White European, 68% South Asian, 52% African-Caribbean). Of those on statins, South Asian and African-Caribbean participants were significantly more likely to report depression compared with Europeans (OR 2.00, 95% CI 1.25, 3.21 and 2.96, 95% 1.67, 5.24), respectively). The similar relationship between statin use and depression in South Asians and African-Caribbeans (Table​(Table1)1) meant their data were pooled. In ethnically-stratified model 1, statin use was not related to depression in Europeans, whereas among EMGs, depression was significantly higher in people on statins (full sample: ethnicity–statin interaction, P = 0.11). After full adjustment, analyses showed a non-significant trend towards a protective effect of statin use on depression in Europeans and a deleterious effect in EMGs (full sample: ethnicity–statin interaction, P = 0.041). Table 1 Risk of major depression according to statin use across ethnic groups A few explanations could exist for this differential relationship between statin use and depression. ‘Presentation bias’ (different presentation of depression by a particular ethnic group to health care professionals could increase the likelihood of detection/treatment of other conditions) was explored with depression somatization, by correlating depressive symptoms with self-reported health. No group demonstrated elevated depression somatization, with the same strength and direction of relationship observed across all groups. Depression was measured using a screening tool rather than clinical diagnosis; often a study limitation, here it reduced ‘presentation bias’ likelihood, since depression may not have been discussed with GPs. Another possibility is that the statin–depression association was confounded by CVD due to the established bi-directional relationship between depression and CVD. To examine whether, among EMGs, depression is a stronger predictor of CVD or vice versa, we adjusted for CVD in the main models (4–5) and stratified the fully-adjusted model by CVD status in sensitivity analyses. The same results were observed across groups irrespective of CVD prevalence (results not shown), indicating that the statin–depression link did not result from statin use acting as a proxy for CVD. Therefore, our results may reflect a true ethnic difference in the impact of statins on depression. Ethnic differences in response to statins could elicit direct and indirect effects on depression, i.e. across ethnicities, there could be a differential influence of statins on lipid sub-fractions or of statins’ protective effects on cerebrovascular processes, both of which could impact mood. Alternatively, EMGs could be more vulnerable to statin-induced side effects, influencing depression. EMGs receiving statins in this sample were over twice as likely to report depression as Europeans. To our knowledge, this is the first study to examine ethnic differentials in the statin–depression relationship. We acknowledge our dataset's limitations, in particular its cross-sectional nature precluding causal interpretations and limited study power. However our aim was to highlight these findings and we urge others to interrogate existing clinical trial/health care databases, as well as including sufficient EMG numbers in future studies. Given the pervasiveness of statins and predisposition towards CVD and depression among certain groups 3,4, this finding has potentially serious implications for the mental health of thousands of EMGs being treated with statins.

BACKGROUND: Diabetes is one of the commonest chronic medical conditions, affecting around 347 million adults worldwide. Structured patient education programmes reduce the risk of diabetes‐related complications four‐fold. Internet‐based self‐management programmes have been shown to be effective for a number of long‐term conditions, but it is unclear what are the essential or effective components of such programmes. If computer‐based self‐management interventions improve outcomes in type 2 diabetes, they could potentially provide a cost‐effective option for reducing the burdens placed on patients and healthcare systems by this long‐term condition. OBJECTIVES: To assess the effects on health status and health‐related quality of life of computer‐based diabetes self‐management interventions for adults with type 2 diabetes mellitus. SEARCH METHODS: We searched six electronic bibliographic databases for published articles and conference proceedings and three online databases for theses (all up to November 2011). Reference lists of relevant reports and reviews were also screened. SELECTION CRITERIA: Randomised controlled trials of computer‐based self‐management interventions for adults with type 2 diabetes, i.e. computer‐based software applications that respond to user input and aim to generate tailored content to improve one or more self‐management domains through feedback, tailored advice, reinforcement and rewards, patient decision support, goal setting or reminders. DATA COLLECTION AND ANALYSIS: Two review authors independently screened the abstracts and extracted data. A taxonomy for behaviour change techniques was used to describe the active ingredients of the intervention. MAIN RESULTS: We identified 16 randomised controlled trials with 3578 participants that fitted our inclusion criteria. These studies included a wide spectrum of interventions covering clinic‐based brief interventions, Internet‐based interventions that could be used from home and mobile phone‐based interventions. The mean age of participants was between 46 to 67 years old and mean time since diagnosis was 6 to 13 years. The duration of the interventions varied between 1 to 12 months. There were three reported deaths out of 3578 participants. Computer‐based diabetes self‐management interventions currently have limited effectiveness. They appear to have small benefits on glycaemic control (pooled effect on glycosylated haemoglobin A1c (HbA1c): ‐2.3 mmol/mol or ‐0.2% (95% confidence interval (CI) ‐0.4 to ‐0.1; P = 0.009; 2637 participants; 11 trials). The effect size on HbA1c was larger in the mobile phone subgroup (subgroup analysis: mean difference in HbA1c ‐5.5 mmol/mol or ‐0.5% (95% CI ‐0.7 to ‐0.3); P < 0.00001; 280 participants; three trials). Current interventions do not show adequate evidence for improving depression, health‐related quality of life or weight. Four (out of 10) interventions showed beneficial effects on lipid profile. One participant withdrew because of anxiety but there were no other documented adverse effects. Two studies provided limited cost‐effectiveness data ‐ with one study suggesting costs per patient of less than $140 (in 1997) or 105 EURO and another study showed no change in health behaviour and resource utilisation. AUTHORS' CONCLUSIONS: Computer‐based diabetes self‐management interventions to manage type 2 diabetes appear to have a small beneficial effect on blood glucose control and the effect was larger in the mobile phone subgroup. There is no evidence to show benefits in other biological outcomes or any cognitive, behavioural or emotional outcomes.

Background: Stroke risk is greater in South Asians than Europeans. We sought to compare associations between blood pressure (BP) and stroke by ethnicity and determine how BP contributes to ethnic differences in disease. Methods: Population sample of 1510 European and 1195 South Asian men recruited between 1988-1991, mean age 52 7yrs. Incident fatal and nonfatal strokes were captured over 20 years of follow-up. Cox models demonstrated associations between mean arterial BP (MAP) and stroke. Results: South Asians had more incident strokes than Europeans (5.6 (4.7,6.7) versus 4.7 (4.0,5.6) per 1000 person years, age-adjusted hazard ratio:1.40 (1.08,1.76), pZ0.01) and higher MAPs than Europeans (97 12 versus 93 12mmHg, p