62 research outputs found

    Prevalence of macrovascular disease amongst type 2 diabetic patients detected by targeted screening and patients newly diagnosed in general practice: the Hoorn Screening Study

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    Prevalence of macrovascular disease amongst type 2 diabetic patients detected by targeted screening and patients newly diagnosed in general practice: the Hoorn Screening Study. Spijkerman AM, Henry RM, Dekker JM, Nijpels G, Kostense PJ, Kors JA, Ruwaard D, Stehouwer CD, Bouter LM, Heine RJ. Institutes for Research in Extramural Medicine, VU University Medical Center, Amsterdam, The Netherlands. [email protected] OBJECTIVES: Screening for type 2 diabetes has been recommended and targeted screening might be an efficient way to screen. The aim was to investigate whether diabetic patients identified by a targeted screening procedure differ from newly diagnosed diabetic patients in general practice with regard to the prevalence of macrovascular complications. DESIGN: Cross-sectional population-based study. SETTING: Population study, primary care. SUBJECTS: Diabetic patients identified by a population-based targeted screening procedure (SDM patients), consisting of a screening questionnaire and a fasting capillary glucose measurement followed by diagnostic testing, were compared with newly diagnosed diabetic patients in general practice (GPDM patients). Ischaemic heart disease and prior myocardial infarction were assessed by ECG recording. Peripheral arterial disease was assessed by the ankle-arm index. Intima-media thickness of the right common carotid artery was measured with ultrasound. RESULTS: A total of 195 SDM patients and 60 GPDM patients participated in the medical examination. The prevalence of MI was 13.3% (95% CI 9.3-18.8%) and 3.4% (1.0-11.7%) in SDM patients and GPDM patients respectively. The prevalence of ischaemic heart disease was 39.5% (95% CI 32.9-46.5%) in SDM patients and 24.1% (15.0-36.5%) in GPDM patients. The prevalence of peripheral arterial disease was similar in both groups: 10.6% (95% CI 6.9-15.9%) and 10.2% (4.7-20.5%) respectively. Mean intima-media thickness was 0.85 mm (+/-0.17) in SDM patients and 0.90 mm (+/-0.20) in GPDM patients. The difference in intima-media thickness was not statistically significant. CONCLUSIONS: Targeted screening identified patients with a prevalence of macrovascular complications similar to that of patients detected in general practice, but with a lower degree of hyperglycaemi

    Autoimmunity plays a role in the onset of diabetes after 40 years of age

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    AIMS/HYPOTHESIS: Type 1 and type 2 diabetes differ with respect to pathophysiological factors such as beta cell function, insulin resistance and phenotypic appearance, but there may be overlap between the two forms of diabetes. However, there are relatively few prospective studies that have characterised the relationship between autoimmunity and incident diabetes. We investigated associations of antibodies against the 65 kDa isoform of GAD (GAD65) with type 1 diabetes and type 2 diabetes genetic risk scores and incident diabetes in adults in European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct, a case-cohort study nested in the EPIC cohort. METHODS: GAD65 antibodies were analysed in EPIC participants (over 40 years of age and free of known diabetes at baseline) by radioligand binding assay in a random subcohort (n = 15,802) and in incident diabetes cases (n = 11,981). Type 1 diabetes and type 2 diabetes genetic risk scores were calculated. Associations between GAD65 antibodies and incident diabetes were estimated using Prentice-weighted Cox regression. RESULTS: GAD65 antibody positivity at baseline was associated with development of diabetes during a median follow-up time of 10.9 years (HR for GAD65 antibody positive vs negative 1.78; 95% CI 1.43, 2.20) after adjustment for sex, centre, physical activity, smoking status and education. The genetic risk score for type 1 diabetes but not type 2 diabetes was associated with GAD65 antibody positivity in both the subcohort (OR per SD genetic risk 1.24; 95% CI 1.03, 1.50) and incident cases (OR 1.97; 95% CI 1.72, 2.26) after adjusting for age and sex. The risk of incident diabetes in those in the top tertile of the type 1 diabetes genetic risk score who were also GAD65 antibody positive was 3.23 (95% CI 2.10, 4.97) compared with all other individuals, suggesting that 1.8% of incident diabetes in adults was attributable to this combination of risk factors. CONCLUSIONS/INTERPRETATION: Our study indicates that incident diabetes in adults has an element of autoimmune aetiology. Thus, there might be a reason to re-evaluate the present subclassification of diabetes in adulthood

    Alcoholic beverage preference and diabetes incidence across Europe the Consortium on Health and Ageing Network of Cohorts in Europe and the United States (CHANCES) project

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    It is unknown if wine, beer and spirit intake lead to a similar association with diabetes. We studied the association between alcoholic beverage preference and type 2 diabetes incidence in persons who reported to consume alcohol.Ten European cohort studies from the Consortium on Health and Ageing: Network of Cohorts in Europe and the United States were included, comprising participant data of 62 458 adults who reported alcohol consumption at baseline. Diabetes incidence was based on documented and/or self-reported diagnosis during follow-up. Preference was defined when ⩾70% of total alcohol consumed was either beer, wine or spirits. Adjusted hazard ratios (HRs) were computed using Cox proportional hazard regression. Single-cohort HRs were pooled by random-effects meta-analysis.Beer, wine or spirit preference was not related to diabetes risk compared with having no preference. The pooled HRs were HR 1.06 (95% confidence interval (CI) 0.93, 1.20) for beer, HR 0.99 (95% CI 0.88, 1.11) for wine, and HR 1.19 (95% CI 0.97, 1.46) for spirit preference. Absolute wine intake, adjusted for total alcohol, was associated with a lower diabetes risk: pooled HR per 6 g/day was 0.96 (95% CI 0.93, 0.99). A spirit preference was related to a higher diabetes risk in those with a higher body mass index, in men and women separately, but not after excluding persons with prevalent diseases.This large individual-level meta-analysis among persons who reported alcohol consumption revealed that the preference for beer, wine, and spirits was similarly associated with diabetes incidence compared with having no preference

    Autoimmunity plays a role in the onset of diabetes after 40 years of age

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    AIMS/HYPOTHESIS: Type 1 and type 2 diabetes differ with respect to pathophysiological factors such as beta cell function, insulin resistance and phenotypic appearance, but there may be overlap between the two forms of diabetes. However, there are relatively few prospective studies that have characterised the relationship between autoimmunity and incident diabetes. We investigated associations of antibodies against the 65 kDa isoform of GAD (GAD65) with type 1 diabetes and type 2 diabetes genetic risk scores and incident diabetes in adults in European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct, a case-cohort study nested in the EPIC cohort. METHODS: GAD65 antibodies were analysed in EPIC participants (over 40 years of age and free of known diabetes at baseline) by radioligand binding assay in a random subcohort (n = 15,802) and in incident diabetes cases (n = 11,981). Type 1 diabetes and type 2 diabetes genetic risk scores were calculated. Associations between GAD65 antibodies and incident diabetes were estimated using Prentice-weighted Cox regression. RESULTS: GAD65 antibody positivity at baseline was associated with development of diabetes during a median follow-up time of 10.9 years (HR for GAD65 antibody positive vs negative 1.78; 95% CI 1.43, 2.20) after adjustment for sex, centre, physical activity, smoking status and education. The genetic risk score for type 1 diabetes but not type 2 diabetes was associated with GAD65 antibody positivity in both the subcohort (OR per SD genetic risk 1.24; 95% CI 1.03, 1.50) and incident cases (OR 1.97; 95% CI 1.72, 2.26) after adjusting for age and sex. The risk of incident diabetes in those in the top tertile of the type 1 diabetes genetic risk score who were also GAD65 antibody positive was 3.23 (95% CI 2.10, 4.97) compared with all other individuals, suggesting that 1.8% of incident diabetes in adults was attributable to this combination of risk factors. CONCLUSIONS/INTERPRETATION: Our study indicates that incident diabetes in adults has an element of autoimmune aetiology. Thus, there might be a reason to re-evaluate the present subclassification of diabetes in adulthood

    Cardiovascular comorbidities among public health clinic patients with diabetes: the Urban Diabetics Study

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    BACKGROUND: We sought to determine the frequency and distribution of cardiovascular comorbidities in a large cohort of low-income patients with diabetes who had received primary care for diabetes at municipal health clinics. METHODS: Outpatient data from the Philadelphia Health Care Centers was linked with hospital discharge data from all Pennsylvania hospitals and death certificates. RESULTS: Among 10,095 primary care patients with diabetes, with a mean observation period of 4.6 years (2.8 after diabetes diagnosis), 2,693 (14.3%) were diagnosed with heart disease, including 270 (1.4%) with myocardial infarction and 912 (4.8%) with congestive heart failure. Cerebrovascular disease was diagnosed in 588 patients (3.1%). Over 77% of diabetic patients were diagnosed with hypertension. Incidence rates of new complications ranged from 0.6 per 100 person years for myocardial infarction to 26.5 per 100 person years for hypertension. Non-Hispanic whites had higher rates of myocardial infarction, and Hispanics and Asians had fewer comorbid conditions than African Americans and non-Hispanic whites. CONCLUSION: Cardiovascular comorbidities were common both before and after diabetes diagnosis in this low-income cohort, but not substantially different from mixed-income managed care populations, perhaps as a consequence of access to primary care and pharmacy services

    A multivariate logistic regression equation to screen for dysglycaemia: development and validation

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    Aims  To develop and validate an empirical equation to screen for dysglycaemia [impaired fasting glucose (IFG), impaired glucose tolerance (IGT) and undiagnosed diabetes]. Methods  A predictive equation was developed using multiple logistic regression analysis and data collected from 1032 Egyptian subjects with no history of diabetes. The equation incorporated age, sex, body mass index (BMI), post-prandial time (self-reported number of hours since last food or drink other than water), systolic blood pressure, high-density lipoprotein (HDL) cholesterol and random capillary plasma glucose as independent covariates for prediction of dysglycaemia based on fasting plasma glucose (FPG) ≥ 6.1 mmol/l and/or plasma glucose 2 h after a 75-g oral glucose load (2-h PG) ≥ 7.8 mmol/l. The equation was validated using a cross-validation procedure. Its performance was also compared with static plasma glucose cut-points for dysglycaemia screening. Results  The predictive equation was calculated with the following logistic regression parameters: P  = 1 + 1/(1 + e −X ) = where X = −8.3390 + 0.0214 (age in years) + 0.6764 (if female) + 0.0335 (BMI in kg/m 2 ) + 0.0934 (post-prandial time in hours) + 0.0141 (systolic blood pressure in mmHg) − 0.0110 (HDL in mmol/l) + 0.0243 (random capillary plasma glucose in mmol/l). The cut-point for the prediction of dysglycaemia was defined as a probability ≥ 0.38. The equation's sensitivity was 55%, specificity 90% and positive predictive value (PPV) 65%. When applied to a new sample, the equation's sensitivity was 53%, specificity 89% and PPV 63%. Conclusions  This multivariate logistic equation improves on currently recommended methods of screening for dysglycaemia and can be easily implemented in a clinical setting using readily available clinical and non-fasting laboratory data and an inexpensive hand-held programmable calculator. Diabet. Med. 22, 599–605 (2005)Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75603/1/j.1464-5491.2005.01467.x.pd

    Interplay between genetic predisposition, macronutrient intake and type 2 diabetes incidence: analysis within EPIC-InterAct across eight European countries

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    AIMS/HYPOTHESIS: Gene-macronutrient interactions may contribute to the development of type 2 diabetes but research evidence to date is inconclusive. We aimed to increase our understanding of the aetiology of type 2 diabetes by investigating potential interactions between genes and macronutrient intake and their association with the incidence of type 2 diabetes. METHODS: We investigated the influence of interactions between genetic risk scores (GRSs) for type 2 diabetes, insulin resistance and BMI and macronutrient intake on the development of type 2 diabetes in the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct, a prospective case-cohort study across eight European countries (N = 21,900 with 9742 incident type 2 diabetes cases). Macronutrient intake was estimated from diets reported in questionnaires, including proportion of energy derived from total carbohydrate, protein, fat, plant and animal protein, saturated, monounsaturated and polyunsaturated fat and dietary fibre. Using multivariable-adjusted Cox regression, we estimated country-specific interaction results on the multiplicative scale, using random-effects meta-analysis. Secondary analysis used isocaloric macronutrient substitution. RESULTS: No interactions were identified between any of the three GRSs and any macronutrient intake, with low-to-moderate heterogeneity between countries (I2range 0-51.6%). Results were similar using isocaloric macronutrient substitution analyses and when weighted and unweighted GRSs and individual SNPs were examined. CONCLUSIONS/INTERPRETATION: Genetic susceptibility to type 2 diabetes, insulin resistance and BMI did not modify the association between macronutrient intake and incident type 2 diabetes. This suggests that macronutrient intake recommendations to prevent type 2 diabetes do not need to account for differences in genetic predisposition to these three metabolic conditions

    Interaction between genes and macronutrient intake on the risk of developing type 2 diabetes: systematic review and findings from (EPIC)-InterAct

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    Background: Gene-diet interactions have been reported to contribute to the development of type 2 diabetes (T2D). However, to our knowledge, few examples have been consistently replicated to date. Objective: We aimed to identify existing evidence for gene-macronutrient interactions and T2D and to examine the reported interactions in a large-scale study. Design: We systematically reviewed studies reporting gene-macronutrient interactions and T2D. We searched the MEDLINE, Human Genome Epidemiology Network, and WHO International Clinical Trials Registry Platform electronic databases to identify studies published up to October 2015. Eligibility criteria included assessment of macronutrient quantity (e.g., total carbohydrate) or indicators of quality (e.g., dietary fiber) by use of self-report or objective biomarkers of intake. Interactions identified in the review were subsequently examined in the EPIC (European Prospective Investigation into Cancer)-InterAct case-cohort study (n = 21,148, with 9403 T2D cases; 8 European countries). Prentice-weighted Cox regression was used to estimate country-specific HRs, 95% CIs, and P-interaction values, which were then pooled by random-effects meta-analysis. A primary model was fitted by using the same covariates as reported in the published studies, and a second model adjusted for additional covariates and estimated the effects of isocaloric macronutrient substitution. Results: Thirteen observational studies met the eligibility criteria (n < 1700 cases). Eight unique interactions were reported to be significant between macronutrients [carbohydrate, fat, saturated fat, dietary fiber, and glycemic load derived from self-report of dietary intake and circulating n–3 (ω-3) polyunsaturated fatty acids] and genetic variants in or near transcription factor 7–like 2 (TCF7L2), gastric inhibitory polypeptide receptor (GIPR), caveolin 2 (CAV2), and peptidase D (PEPD) (P-interaction < 0.05). We found no evidence of interaction when we tried to replicate previously reported interactions. In addition, no interactions were detected in models with additional covariates. Conclusions: Eight gene-macronutrient interactions were identified for the risk of T2D from the literature. These interactions were not replicated in the EPIC-InterAct study, which mirrored the analyses undertaken in the original reports. Our findings highlight the importance of independent replication of reported interactions

    Estimated substitution of tea or coffee for sugar-sweetened beverages was associated with lower type 2 diabetes incidence in case-cohort analysis across 8 European countries in the epic-interact study.

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    INTRODUCTION: Beverage consumption is a modifiable risk factor for type 2 diabetes (T2D), but there is insufficient evidence to inform the suitability of substituting 1 type of beverage for another. OBJECTIVE: The aim of this study was to estimate the risk of T2D when consumption of sugar-sweetened beverages (SSBs) was replaced with consumption of fruit juice, milk, coffee, or tea. METHODS: In the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct case-cohort study of 8 European countries (n = 27,662, with 12,333 cases of incident T2D, 1992-2007), beverage consumption was estimated at baseline by dietary questionnaires. Using Prentice-weighted Cox regression adjusting for other beverages and potential confounders, we estimated associations of substituting 1 type of beverage for another on incident T2D. RESULTS: Mean ± SD of estimated consumption of SSB was 55 ± 105 g/d. Means ± SDs for the other beverages were as follows: fruit juice, 59 ± 101 g/d; milk, 209 ± 203 g/d; coffee, 381 ± 372 g/d; and tea, 152 ± 282 g/d. Substituting coffee for SSBs by 250 g/d was associated with a 21% lower incidence of T2D (95% CI: 12%, 29%). The rate difference was -12.0 (95% CI: -20.0, -5.0) per 10,000 person-years among adults consuming SSBs ≥250 g/d (absolute rate = 48.3/10,000). Substituting tea for SSBs was estimated to lower T2D incidence by 22% (95% CI: 15%, 28%) or -11.0 (95% CI: -20.0, -2.6) per 10,000 person-years, whereas substituting fruit juice or milk was estimated not to alter T2D risk significantly. CONCLUSIONS: These findings indicate a potential benefit of substituting coffee or tea for SSBs for the primary prevention of T2D and may help formulate public health recommendations on beverage consumption in different populations

    Prevalence of diabetes mellitus and the performance of a risk score among Hindustani Surinamese, African Surinamese and ethnic Dutch: a cross-sectional population-based study

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    <p>Abstract</p> <p>Background</p> <p>While the prevalence of type 2 diabetes mellitus (DM) is high, tailored risk scores for screening among South Asian and African origin populations are lacking. The aim of this study was, first, to compare the prevalence of (known and newly detected) DM among Hindustani Surinamese, African Surinamese and ethnic Dutch (Dutch). Second, to develop a new risk score for DM. Third, to evaluate the performance of the risk score and to compare it to criteria derived from current guidelines.</p> <p>Methods</p> <p>We conducted a cross-sectional population based study among 336 Hindustani Surinamese, 593 African Surinamese and 486 Dutch, aged 35–60 years, in Amsterdam. Logistic regressing analyses were used to derive a risk score based on non-invasively determined characteristics. The diagnostic accuracy was assessed by the area under the Receiver-Operator Characteristic curve (AUC).</p> <p>Results</p> <p>Hindustani Surinamese had the highest prevalence of DM, followed by African Surinamese and Dutch: 16.7, 8.1, 4.2% (age 35–44) and 35.0, 19.0, 8.2% (age 45–60), respectively. The risk score included ethnicity, body mass index, waist circumference, resting heart rate, first-degree relative with DM, hypertension and history of cardiovascular disease. Selection based on age alone showed the lowest AUC: between 0.57–0.62. The AUC of our score (0.74–0.80) was higher than that of criteria from guidelines based solely on age and BMI and as high as criteria that required invasive specimen collection.</p> <p>Conclusion</p> <p>In Hindustani Surinamese and African Surinamese populations, screening for DM should not be limited to those over 45 years, as is advocated in several guidelines. If selective screening is indicated, our ethnicity based risk score performs well as a screening test for DM among these groups, particularly compared to the criteria based on age and/or body mass index derived from current guidelines.</p
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