584 research outputs found

    How old is the Tasmanian cultural landscape? a test of landscape openness using quantitative land-cover reconstructions

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    Aim: To test competing hypotheses about the timing and extent of Holocene landscape opening using pollen-based quantitative land-cover estimates. Location: Dove Lake, Tasmanian Wilderness World Heritage Area, Australia. Methods: Fossil pollen data were incorporated into pollen dispersal models and corrected for differences in pollen productivity among key plant taxa. Mechanistic models (REVEALS-Regional Estimates of VEgetation Abundance from Large Sites) employing different models for pollen dispersal (Gaussian plume and Lagrangian stochastic models) were evaluated and applied in the Southern Hemisphere for the first time. Results: Validation of the REVEALS model with vegetation cover data suggests an overall better performance of the Lagrangian stochastic model. Regional land-cover estimates for forest and non-forest plant taxa show persistent landscape openness throughout the Holocene (average landscape openness similar to 50%). Gymnoschoenus sphaerocephalus, an indicator of moorland vegetation, shows higher values during the early Holocene (11.7-9 ka) and declines slightly through the mid-Holocene (9-4.5 ka) during a phase of partial landscape afforestation. Rain forest cover reduced (from similar to 40% to similar to 20%) during the period between 4.2-3.5 ka. Main conclusions: Pollen percentages severely under-represent landscape openness in western Tasmania and this bias has fostered an over-estimation of Holocene forest cover from pollen data. Treeless vegetation dominated Holocene landscapes of the Dove Lake area, allowing us to reject models of landscape evolution that invoke late-Holocene replacement of a rain forest-dominated landscape by moorland. Instead, we confirm a model of Late Pleistocene inheritance of open vegetation. Rapid forest decline occurred after c.4 ka, likely in response to regional moisture decline.Australian Research Council; AINSE AWARD [ALNGRA16024]; AINSE PGRA scholarship [12039]info:eu-repo/semantics/publishedVersio

    Time Trends in Deaths Before Age 50 Years in People with Type 1 Diabetes:a nationwide analysis from Scotland 2004–2017

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    Acknowledgements We thank the SDRN Epidemiology Group: J. Chalmers (Diabetes Centre, Victoria Hospital, Kirkcaldy, UK), C. Fischbacher (Information Services Division, NHS National Services Scotland, Edinburgh, UK), B. Kennon (Queen Elizabeth University Hospital, Glasgow, UK), G. Leese (Ninewells Hospital, Dundee, UK), R. Lindsay (British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, UK), J. McKnight (Western General Hospital, NHS, UK), J. Petrie (Institute of Cardiovascular & Medical Sciences, University of Glasgow, Glasgow, UK), R. McCrimmon (Division of Molecular and Clinical Medicine, University of Dundee, Dundee, UK), S. Philip (Grampian Diabetes Research Unit, Diabetes Centre, Aberdeen Royal Infirmary, Aberdeen, UK), D. McAllister (Institute of Health & Wellbeing, University of Glasgow, Glasgow, UK), E. Pearson (Population Health and Genomics, School of Medicine, University of Dundee, Dundee, UK) and S. Wild (Usher Institute, University of Edinburgh, Edinburgh, UK). The SDRN Epidemiology Group resource was originally set up under Ethics ref. 11/AL/0225, PAC 33/11 now running under PBPP ref. 1617-0147. Funding This study was supported by funding from Diabetes UK (17/0005627).Peer reviewedPublisher PD

    The association of polypharmacy and high-risk drug classes with adverse health outcomes in the Scottish population with type 1 diabetes

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    This study was supported by funding from the Diabetes UK (17/0005627). The funder had no role in designing the study or in analysing and interpreting data and results.Aims/hypothesis The aim of this work was to map the number of prescribed drugs over age, sex and area-based socioeconomic deprivation, and to examine the association between the number of drugs and particular high-risk drug classes with adverse health outcomes among a national cohort of individuals with type 1 diabetes. Methods Utilising linked healthcare records from the population-based diabetes register of Scotland, we identified 28,245 individuals with a diagnosis of type 1 diabetes on 1 January 2017. For this population, we obtained information on health status, predominantly reflecting diabetes-related complications, and information on the total number of drugs and particular high-risk drug classes prescribed. We then studied the association of these baseline-level features with hospital admissions for falls, diabetic ketoacidosis (DKA), and hypoglycaemia or death within the subsequent year using multivariate Cox proportional hazards models. Results Not considering insulin and treatment for hypoglycaemia, the mean number of prescribed drugs was 4.00 (SD 4.35). The proportion of individuals being prescribed five or more drugs at baseline consistently increased with age (proportion [95% CI]: 0–19 years 2.04% [1.60, 2.49]; 40–49 years 28.50% [27.08, 29.93]; 80+ years 76.04% [67.73, 84.84]). Controlling for age, sex, area-based socioeconomic deprivation and health status, each additional drug at baseline was associated with an increase in the hazard for hospitalisation for falls, hypoglycaemia and death but not for DKA admissions (HR [95% CI]: falls 1.03 [1.01, 1.06]; DKA 1.01 [1.00, 1.03]; hypoglycaemia 1.05 [1.02, 1.07]; death 1.04 [1.02, 1.06]). We found a number of drug classes to be associated with an increased hazard of one or more of these adverse health outcomes, including antithrombotic/anticoagulant agents, corticosteroids, opioids, antiepileptics, antipsychotics, hypnotics and sedatives, and antidepressants. Conclusions Polypharmacy is common among the Scottish population with type 1 diabetes and is strongly patterned by sociodemographic factors. The number of prescribed drugs and the prescription of particular high-risk drug classes are strong markers of an increased risk of adverse health outcomes, including acute complications of diabetes.Publisher PDFPeer reviewe

    Association between renin and atherosclerotic burden in subjects with and without type 2 diabetes.

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    Published onlineJournal ArticleThis is the final version of the article. Available from BioMed Central via the DOI in this record.BACKGROUND: Activation of the renin-angiotensin-aldosterone-system (RAAS) has been proposed to contribute to development of vascular complications in type 2 diabetes (T2D). The aim of the present study was to determine if plasma renin levels are associated with the severity of vascular changes in subjects with and without T2D. METHODS: Renin was analyzed by the Proximity Extension Assay in subjects with (n = 985) and without (n = 515) T2D participating in the SUMMIT (SUrrogate markers for Micro- and Macro-vascular hard endpoints for Innovative diabetes Tools) study and in 205 carotid endarterectomy patients. Vascular changes were assessed by determining ankle-brachial pressure index (ABPI), carotid intima-media thickness (IMT), carotid plaque area, pulse wave velocity (PWV) and the reactivity hyperemia index (RHI). RESULTS: Plasma renin was elevated in subjects with T2D and demonstrated risk factor-independent association with prevalent cardiovascular disease both in subjects with and without T2D. Renin levels increased with age, body mass index, HbA1c and correlated inversely with HDL. Subjects with T2D had more severe carotid disease, increased arterial stiffness, and impaired endothelial function. Risk factor-independent associations between renin and APBI, bulb IMT, carotid plaque area were observed in both T2D and non-T2D subjects. These associations were independent of treatment with RAAS inhibitors. Only weak associations existed between plasma renin and the expression of pro-inflammatory and fibrous components in plaques from 205 endarterectomy patients. CONCLUSIONS: Our findings provide clinical evidence for associations between systemic RAAS activation and atherosclerotic burden and suggest that this association is of particular importance in T2D.Innovative Medicines Initiative (the SUMMIT consortium, IMI-2008/115006, the Swedish Heart-Lung Foundation, the Swedish Research Council and Marianne and Marcus Wallenberg Foundation)

    Cancer incidence in type 2 diabetes patients - first results from a feasibility study of the D2C cohort

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    <p>Abstract</p> <p>Background</p> <p>A large prospective study in patients with type 2 diabetes (T2D), the German D2C cohort, is presently being enumerated to investigate risk factors of incident cancer in diabetic patients.</p> <p>Study setting</p> <p>A disease management program was offered, on a voluntary basis, to all T2D patients who were members of a statutory health insurance fund in Germany. This first feasibility report uses data from 26.742 T2D patients, who were 40 to 79 years old, resided in the Muenster District, and who were enrolled between June 2003 and July 2008. Cancer cases were identified through the regional Cancer Registry.</p> <p>Methods</p> <p>Invasive cancer cases were identified using probabilistic record linkage procedures and pseudonymised personal identifiers. Censoring date was December 31, 2008. We included only first cancers, leaving 12.650 male and 14.092 female T2D with a total of 88.778 person-years (py). We computed standardised incidence ratios (SIR) for external comparisons and we employed Cox regression models and hazard ratios (HR) within the cohort.</p> <p>Results</p> <p>We identified 759 first cancers among male T2D patients (18.7 per 1,000 py) and 605 among females (12.7 per 1,000 py). The risk of any incident cancer in T2D was raised (SIR = 1.14; 95% confidence interval [1.10 - 1.21]), in particular for cancer of the liver (SIR = 1.94 [1.15 - 2.94]) and pancreas (SIR = 1.45 [1.07-1.92]). SIRs decreased markedly with time after T2D diagnosis. In Cox models, adjusting for diabetes duration, body mass index and sex, insulin therapy was related to higher cancer risk (HR = 1.25 [1.17 - 1.33]). No effect was seen for metformin.</p> <p>Discussion</p> <p>Our study demonstrates feasibility of record linkage between DMP and cancer registries. These first cohort results confirm previous reports. It is envisaged to enhance this cohort by inclusion of further regions of the state, expansion of the follow-up times, and collection of a more detailed medication history.</p

    Biomarkers associated with early stages of kidney disease in adolescents with type 1 diabetes

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    Objectives: To identify biomarkers of renal disease in adolescents with type 1 diabetes (T1D) and to compare findings in adults with T1D. Methods: Twenty‐five serum biomarkers were measured, using a Luminex platform, in 553 adolescents (median [interquartile range] age: 13.9 [12.6, 15.2] years), recruited to the Adolescent Type 1 Diabetes Cardio‐Renal Intervention Trial. Associations with baseline and final estimated glomerular filtration rate (eGFR), rapid decliner and rapid increaser phenotypes (eGFR slopes  3 mL/min/1.73m2/year, respectively), and albumin‐creatinine ratio (ACR) were assessed. Results were also compared with those obtained in 859 adults (age: 55.5 [46.1, 64.4) years) from the Scottish Diabetes Research Network Type 1 Bioresource. Results: In the adolescent cohort, baseline eGFR was negatively associated with trefoil factor‐3, cystatin C, and beta‐2 microglobulin (B2M) (B coefficient[95%CI]: −0.19 [−0.27, −0.12], P = 7.0 × 10−7; −0.18 [−0.26, −0.11], P = 5.1 × 10−6; −0.12 [−0.20, −0.05], P = 1.6 × 10−3), in addition to clinical covariates. Final eGFR was negatively associated with osteopontin (−0.21 [−0.28, −0.14], P = 2.3 × 10−8) and cystatin C (−0.16 [−0.22, −0.09], P = 1.6 × 10−6). Rapid decliner phenotype was associated with osteopontin (OR: 1.83 [1.42, 2.41], P = 7.3 × 10−6), whereas rapid increaser phenotype was associated with fibroblast growth factor‐23 (FGF‐23) (1.59 [1.23, 2.04], P = 2.6 × 10−4). ACR was not associated with any of the biomarkers. In the adult cohort similar associations with eGFR were found; however, several additional biomarkers were associated with eGFR and ACR. Conclusions: In this young population with T1D and high rates of hyperfiltration, osteopontin was the most consistent biomarker associated with prospective changes in eGFR. FGF‐23 was associated with eGFR increases, whereas trefoil factor‐3, cystatin C, and B2M were associated with baseline eGFR

    Lack of effect of lowering LDL cholesterol on cancer: meta-analysis of individual data from 175,000 people in 27 randomised trials of statin therapy

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    &lt;p&gt;Background: Statin therapy reduces the risk of occlusive vascular events, but uncertainty remains about potential effects on cancer. We sought to provide a detailed assessment of any effects on cancer of lowering LDL cholesterol (LDL-C) with a statin using individual patient records from 175,000 patients in 27 large-scale statin trials.&lt;/p&gt; &lt;p&gt;Methods and Findings: Individual records of 134,537 participants in 22 randomised trials of statin versus control (median duration 4.8 years) and 39,612 participants in 5 trials of more intensive versus less intensive statin therapy (median duration 5.1 years) were obtained. Reducing LDL-C with a statin for about 5 years had no effect on newly diagnosed cancer or on death from such cancers in either the trials of statin versus control (cancer incidence: 3755 [1.4% per year [py]] versus 3738 [1.4% py], RR 1.00 [95% CI 0.96-1.05]; cancer mortality: 1365 [0.5% py] versus 1358 [0.5% py], RR 1.00 [95% CI 0.93–1.08]) or in the trials of more versus less statin (cancer incidence: 1466 [1.6% py] vs 1472 [1.6% py], RR 1.00 [95% CI 0.93–1.07]; cancer mortality: 447 [0.5% py] versus 481 [0.5% py], RR 0.93 [95% CI 0.82–1.06]). Moreover, there was no evidence of any effect of reducing LDL-C with statin therapy on cancer incidence or mortality at any of 23 individual categories of sites, with increasing years of treatment, for any individual statin, or in any given subgroup. In particular, among individuals with low baseline LDL-C (&#60;2 mmol/L), there was no evidence that further LDL-C reduction (from about 1.7 to 1.3 mmol/L) increased cancer risk (381 [1.6% py] versus 408 [1.7% py]; RR 0.92 [99% CI 0.76–1.10]).&lt;/p&gt; &lt;p&gt;Conclusions: In 27 randomised trials, a median of five years of statin therapy had no effect on the incidence of, or mortality from, any type of cancer (or the aggregate of all cancer).&lt;/p&gt
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