The prevalence of type 2 diabetes is increasing rapidly, particularly among younger age groups. Estimates suggest that people with diabetes die, on average, 6 years earlier than people without diabetes. We aimed to provide reliable estimates of the associations between age at diagnosis of diabetes and all-cause mortality, cause-specific mortality, and reductions in life expectancy.
A method to automatically segment cerebrospinal fluid, gray matter, white matter and white matter lesions is presented. The method uses magnetic resonance brain images from proton density, T1-weighted and fluid-attenuated inversion recovery sequences. The method is based on an automatically trained k-nearest neighbour classifier extended with an additional step for the segmentation of white matter lesions. On six datasets, segmentations are quantitatively compared with manual segmentations, which have been carried out by two expert observers. For the tissues, similarity indices between method and observers approximate those between manual segmentations. Reasonably good lesion segmentation results are obtained compared to interobserver variability.
One of the global targets for non-communicable diseases is to halt, by 2025, the rise in the age-standardised adult prevalence of diabetes at its 2010 levels. We aimed to estimate worldwide trends in diabetes, how likely it is for countries to achieve the global target, and how changes in prevalence, together with population growth and ageing, are affecting the number of adults with diabetes.
Methods
We pooled data from population-based studies that had collected data on diabetes through measurement of its biomarkers. We used a Bayesian hierarchical model to estimate trends in diabetes prevalence—defined as fasting plasma glucose of 7·0 mmol/L or higher, or history of diagnosis with diabetes, or use of insulin or oral hypoglycaemic drugs—in 200 countries and territories in 21 regions, by sex and from 1980 to 2014. We also calculated the posterior probability of meeting the global diabetes target if post-2000 trends continue.
Findings
We used data from 751 studies including 4 372 000 adults from 146 of the 200 countries we make estimates for. Global age-standardised diabetes prevalence increased from 4·3% (95% credible interval 2·4–7·0) in 1980 to 9·0% (7·2–11·1) in 2014 in men, and from 5·0% (2·9–7·9) to 7·9% (6·4–9·7) in women. The number of adults with diabetes in the world increased from 108 million in 1980 to 422 million in 2014 (28·5% due to the rise in prevalence, 39·7% due to population growth and ageing, and 31·8% due to interaction of these two factors). Age-standardised adult diabetes prevalence in 2014 was lowest in northwestern Europe, and highest in Polynesia and Micronesia, at nearly 25%, followed by Melanesia and the Middle East and north Africa. Between 1980 and 2014 there was little change in age-standardised diabetes prevalence in adult women in continental western Europe, although crude prevalence rose because of ageing of the population. By contrast, age-standardised adult prevalence rose by 15 percentage points in men and women in Polynesia and Micronesia. In 2014, American Samoa had the highest national prevalence of diabetes (>30% in both sexes), with age-standardised adult prevalence also higher than 25% in some other islands in Polynesia and Micronesia. If post-2000 trends continue, the probability of meeting the global target of halting the rise in the prevalence of diabetes by 2025 at the 2010 level worldwide is lower than 1% for men and is 1% for women. Only nine countries for men and 29 countries for women, mostly in western Europe, have a 50% or higher probability of meeting the global target.
Interpretation
Since 1980, age-standardised diabetes prevalence in adults has increased, or at best remained unchanged, in every country. Together with population growth and ageing, this rise has led to a near quadrupling of the number of adults with diabetes worldwide. The burden of diabetes, both in terms of prevalence and number of adults affected, has increased faster in low-income and middle-income countries than in high-income countries.
Abstract Funding Acknowledgements Type of funding sources: Public hospital(s). Main funding source(s): - Erasmus MC MRace grant- The Netherlands Organization for the Health Research and Development (ZonMw) Background Atrial fibrillation (AF) is a highly prevalent cardiac tachyarrhythmia. Recent literature suggests that AF induces a prothrombotic state, ultimately leading to thrombotic events. It is also hypothesized that coagulation underlies AF development through coagulation. Purpose We aimed to assess the associations between selected coagulation factors with AF in both longitudinal and cross-sectional studies, to give further insight on the interaction of coagulation and AF. Methods Through a systematic search of large databases, including Embase, Medline ALL, and Web of Science Core Collection, all longitudinal cohort studies and cross-sectional studies published before 25th of May, 2021 were reviewed. For longitudinal studies, pooled hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated through log-transformed HRs and 95% CIs using the generic inverse variance method. For cross-sectional studies the pooled standardized mean differences (SMD) were calculated through inverse variance weighting. Results 16 longitudinal studies and 44 cross-sectional studies were included. In the longitudinal studies, using complex multivariable models, we found significant associations between fibrinogen (HR1.06, 95% CI 1.01-1.12), Plasminogen activator inhibitor 1 (PAI-1) (HR 1.06, 95% CI 1.00-1.12), and D-dimer (HR 1.10, 95% CI 1.02-1.19), with AF incidence. In cross-sectional studies, we found significant differences between AF patients and controls for fibrinogen (SMD 0.47), D-dimer (SMD 1.74), P-selectin (SMD 0.31), von Willebrand factor (SMD 0.96), PAI-1 (SMD 1.73), ß-thromboglobulin (SMD 0.82), and Platelet Factor 4 (SMD 0.42). Conclusions Atrial fibrillation is associated with higher levels of coagulation factors. These associations are most pronounced in cross-sectional analyses, but limited studies are available investigating a prothrombotic state underlying AF initiation. These results further support the hypothesis of "AF begets AF".
Abstract Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, Netherlands Organization for the Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. This study is further supported by the Senior Scientist Grant from Dutch Heart Foundation (03-004-2021-T050). Background The (shape of the) association and sex-differences between electrocardiographic parameters and new-onset atrial fibrillation (AF) remain incompletely understood. Purpose To investigate the association between electrocardiographic parameters and new-onset atrial fibrillation among men and women in the general population. Methods 12,212 participants free of AF from a large population-based cohort study were included. Up to five repeated measurements of electrocardiographic parameters including PR, QRS, QT, QT corrected for heart rate (QTc), JT, RR interval, and heart rate were assessed at baseline and follow-up examinations. Cox proportional hazards models and joint models, both adjusted for cardiovascular risk factors, were used to determine the (shape of) association between baseline and longitudinal electrocardiographic parameters with new-onset AF. Additionally, we evaluated potential sex-differences. Results During a median follow-up of 9.3 years, 1,282 incident AF cases occurred among 12,212 participants (mean age 64.9 years, 58.2% women). Penalized cubic splines revealed that associations between baseline electrocardiographic measures and risk of new-onset AF were generally U-shaped (Figure 1). Sex-differences in terms of the shape of the various associations were most apparent for baseline PR, QT, QTc, RR, and heart rate in relation to new-onset AF. Longitudinal measures of PR (hazard ratio (HR), 95% confidence interval (CI), 1.43, 1.02-2.04, p=0.0393), and QTc interval (HR, 95% CI, 5.23, 2.18-12.45, p=0.0002) were significantly associated with new-onset AF. Sex-stratified analyses showed that the longitudinal associations were more prominent among men. Conclusions Baseline electrocardiographic measures and risk of new-onset AF were generally U-shaped. Longitudinal electrocardiographic measures of PR, and QTc interval were significantly associated with new-onset AF, more pronounced in men. Our findings imply that different thresholds of electrocardiographic parameters might translate to a differential risk of AF among men and women, and that treatment options targeting specific electrocardiographic parameters might prevent AF in the general population, in particular in men.
Introduction Late-onset Alzheimer’s disease (LOAD, onset age > 60 years) is the most prevalent dementia in the elderly 1 , and risk is partially driven by genetics 2 . Many of the loci responsible for this genetic risk were identified by genome-wide association studies (GWAS) 3–8 . To identify additional LOAD risk loci, the we performed the largest GWAS to date (89,769 individuals), analyzing both common and rare variants. We confirm 20 previous LOAD risk loci and identify four new genome-wide loci ( IQCK , ACE , ADAM10 , and ADAMTS1 ). Pathway analysis of these data implicates the immune system and lipid metabolism, and for the first time tau binding proteins and APP metabolism. These findings show that genetic variants affecting APP and Aβ processing are not only associated with early-onset autosomal dominant AD but also with LOAD. Analysis of AD risk genes and pathways show enrichment for rare variants ( P = 1.32 × 10 −7 ) indicating that additional rare variants remain to be identified.
Abstract Funding Acknowledgements Type of funding sources: None. Background. Arterial stiffness/remodeling results in impaired blood flow and, eventually, decreased glucose disposal in peripheral tissues and increased blood glucose. Besides, increased arterial stiffness/remodeling may lead to hypertension, as a potential reciprocal risk factor for type 2 diabetes mellitus (T2D). We, therefore, hypothesized that increased arterial stiffness/remodeling is associated with an increased risk of T2D. Purpose. To study the associations between arterial stiffness/remodeling and incident T2D. Methods. We used the prospective population-based Rotterdam Study. Common carotid arterial properties were ultrasonically determined in plaque-free areas. Aortic stiffness was estimated by carotid-femoral pulse wave velocity (cf_PWV), carotid stiffness was estimated by the carotid distensibility coefficient (carDC). Arterial remodeling was estimated by carotid artery lumen diameter (carDi), carotid intima-media thickness (cIMT), mean circumferential wall stress (CWSmean), and pulsatile circumferential wall stress (CWSpuls). Cox proportional hazard regression analysis was used to estimate the associations between arterial stiffness/remodeling and the risk of incident T2D, adjusted for age, sex, cohort, mean arterial pressure (MAP), antihypertensive medications, heart rate, non- high-density lipoprotein (HDL)-cholesterol, lipid-lowering medications, and smoking. We included interaction terms in the fully adjusted models to study whether any significant associations were modified by sex, age, blood glucose, or MAP. Spearman correlation analyses were applied to examine the correlations between measurements of arterial stiffness/remodeling and glycemic traits. Results. We included 3,055 individuals free of T2D at baseline (mean (SD) age, 67.2 (7.9) years). During a median follow-up of 14.0 years, 395 (12.9%) T2D occurred. After adjustments, higher cf_PWV (hazard ratio (HR),1.18; 95%CI:1.04-1.35), carDi (1.17; 1.04-1.32), cIMT (1.15; 1.01-1.32), and CWSpuls (1.28; 1.12-1.47) were associated with increased risk of incident T2D. After further adjustment for the baseline glucose, the associations attenuated but remained statistically significant. Sex, age, blood glucose, or MAP did not modify the associations between measurements of arterial stiffness/remodeling, and incident T2D. Among the population with prediabetes at baseline (n = 513) compared to the general population, larger cIMT was associated with a greater increase in the risk of T2D. Most measurements of arterial stiffness/remodeling significantly but weakly correlated with baseline glycemic traits, particularly with blood glucose. Conclusions. Our study suggests that greater arterial stiffness/remodeling is independently associated with an increased risk of T2D development. Blood glucose and hypertension do not seem to play significant roles in these associations. Further studies should disentangle the underlying mechanism that links arterial stiffness/remodeling and T2D.
Abstract Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, Netherlands Organization for the Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. This study is further supported by the Gender and prevention grant (555003017) from ZonMw. Background Sex-differences and the causality of the association between heart rate variability (HRV) and atrial fibrillation (AF) remain unclear. Purpose To investigate the sex-differences and the causality of the association between heart rate variability and atrial fibrillation. Methods 12,334 participants free of AF from a large population-based cohort study were included. Measures of HRV including the standard deviation of normal RR-intervals (SDNN), SDNN corrected for heart rate (SDNNc), RR-interval differences (RMSSD), RMSSD corrected for heart rate (RMSSDc), and heart rate were assessed at baseline and follow-up examinations. Joint models, adjusted for cardiovascular risk factors, were used to determine the association between longitudinal measures of HRV with new-onset AF. Additionally, we evaluated sex-differences. Genetic variants for HRV were used as instrumental variables in a Mendelian randomization (MR) analysis using GWAS summary-level data. Results During a median follow-up of 9.4 years, 1,302 incident AF cases occurred. In joint models, higher SDNN (hazard ratio (HR), 95% confidence interval (CI), 1.24, 1.04-1.47, p=0.0213), and higher RMSSD (HR, 95% CI, 1.33, 1.13-1.54, p=0.0010) were significantly associated with new-onset AF. Sex-stratified analyses showed that the associations were mostly prominent among women. In MR analyses, genetically determined decreases in SDNN (odds ratio (OR), 95% CI, 1.60, 1.27-2.02, p=8.36x10-05), and RMSSD (OR, 95% CI, 1.56, 1.31-1.86, p= 6.32x10-07) were significantly associated with increased AF risk. Conclusions Longitudinal measures of uncorrected HRV were significantly associated with new-onset AF, in particular among women. MR analyses supported the causal relationship between uncorrected measures of HRV with AF. Our findings indicate that measures to modulate HRV might prevent AF in the general population, especially among women.
Diabetes has been defined on the basis of different biomarkers, including fasting plasma glucose (FPG), 2-h plasma glucose in an oral glucose tolerance test (2hOGTT), and HbA1c. We assessed the effect of different diagnostic definitions on both the population prevalence of diabetes and the classification of previously undiagnosed individuals as having diabetes versus not having diabetes in a pooled analysis of data from population-based health examination surveys in different regions.We used data from 96 population-based health examination surveys that had measured at least two of the biomarkers used for defining diabetes. Diabetes was defined using HbA1c (HbA1c ≥6·5% or history of diabetes diagnosis or using insulin or oral hypoglycaemic drugs) compared with either FPG only or FPG-or-2hOGTT definitions (FPG ≥7·0 mmol/L or 2hOGTT ≥11·1 mmol/L or history of diabetes or using insulin or oral hypoglycaemic drugs). We calculated diabetes prevalence, taking into account complex survey design and survey sample weights. We compared the prevalences of diabetes using different definitions graphically and by regression analyses. We calculated sensitivity and specificity of diabetes diagnosis based on HbA1c compared with diagnosis based on glucose among previously undiagnosed individuals (ie, excluding those with history of diabetes or using insulin or oral hypoglycaemic drugs). We calculated sensitivity and specificity in each survey, and then pooled results using a random-effects model. We assessed the sources of heterogeneity of sensitivity by meta-regressions for study characteristics selected a priori.Population prevalence of diabetes based on FPG-or-2hOGTT was correlated with prevalence based on FPG alone (r=0·98), but was higher by 2-6 percentage points at different prevalence levels. Prevalence based on HbA1c was lower than prevalence based on FPG in 42·8% of age-sex-survey groups and higher in another 41·6%; in the other 15·6%, the two definitions provided similar prevalence estimates. The variation across studies in the relation between glucose-based and HbA1c-based prevalences was partly related to participants' age, followed by natural logarithm of per person gross domestic product, the year of survey, mean BMI, and whether the survey population was national, subnational, or from specific communities. Diabetes defined as HbA1c 6·5% or more had a pooled sensitivity of 52·8% (95% CI 51·3-54·3%) and a pooled specificity of 99·74% (99·71-99·78%) compared with FPG 7·0 mmol/L or more for diagnosing previously undiagnosed participants; sensitivity compared with diabetes defined based on FPG-or-2hOGTT was 30·5% (28·7-32·3%). None of the preselected study-level characteristics explained the heterogeneity in the sensitivity of HbA1c versus FPG.Different biomarkers and definitions for diabetes can provide different estimates of population prevalence of diabetes, and differentially identify people without previous diagnosis as having diabetes. Using an HbA1c-based definition alone in health surveys will not identify a substantial proportion of previously undiagnosed people who would be considered as having diabetes using a glucose-based test.Wellcome Trust, US National Institutes of Health.
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