948 resultados para predicting diabetes behaviour
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In order to build dynamic models for prediction and management of degraded Mediterranean forest areas was necessary to build MARIOLA model, which is a calculation computer program. This model includes the following subprograms. 1) bioshrub program, which calculates total, green and woody shrubs biomass and it establishes the time differences to calculate the growth. 2) selego program, which builds the flow equations from the experimental data. It is based on advanced procedures of statistical multiple regression. 3) VEGETATION program, which solves the state equations with Euler or Runge-Kutta integration methods. Each one of these subprograms can act as independent or as linked programs.
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Aims: To investigate the utility of an extended Theory of Planned Behaviour (TPB), including descriptive norms and anticipated regret, in predicting binge-drinking intentions and behaviour. Methods: A total of178 undergraduates completed a questionnaire containing measures of TPB variables, descriptive norms, anticipated regret, and previous binge-drinking behaviour. One week later, 104 students completed a measure of binge-drinking behaviour. Results: Hierarchical regression demonstrated that attitudes (beta = 0.30, P < 0.001) and anticipated regret (beta = 0.47, P < 0.001) were significant predictors of intentions, with the final equation accounting for 58% of the variance. Hierarchial regression found that intentions (beta = -0.21, P < 0.05) and previous binge-drinking behaviour (beta = 0.36, P < 0.01) predicted current drinking behaviour, accounting for 33% of the variance. Conclusions: The study suggests that modifying attitudes and inducing regret may be effective strategies for reducing binge-drinking intentions among undergraduates, which should reduce subsequent binge-drinking behaviour. © The Author 2006. Published by Oxford University Press on behalf of the Medical Council on Alcohol. All rights reserved.
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Chlamydia is a common sexually transmitted infection that has potentially serious consequences unless detected and treated early. The health service in the UK offers clinic-based testing for chlamydia but uptake is low. Identifying the predictors of testing behaviours may inform interventions to increase uptake. Self-tests for chlamydia may facilitate testing and treatment in people who avoid clinic-based testing. Self-testing and being tested by a health care professional (HCP) involve two contrasting contexts that may influence testing behaviour. However, little is known about how predictors of behaviour differ as a function of context. In this study, theoretical models of behaviour were used to assess factors that may predict intention to test in two different contexts: self-testing and being tested by a HCP. Individuals searching for or reading about chlamydia testing online were recruited using Google Adwords. Participants completed an online questionnaire that addressed previous testing behaviour and measured constructs of the Theory of Planned Behaviour and Protection Motivation Theory, which propose a total of eight possible predictors of intention. The questionnaire was completed by 310 participants. Sufficient data for multiple regression were provided by 102 and 118 respondents for self-testing and testing by a HCP respectively. Intention to self-test was predicted by vulnerability and self-efficacy, with a trend-level effect for response efficacy. Intention to be tested by a HCP was predicted by vulnerability, attitude and subjective norm. Thus, intentions to carry out two testing behaviours with very similar goals can have different predictors depending on test context. We conclude that interventions to increase self-testing should be based on evidence specifically related to test context.
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Type 2 diabetes mellitus (T2DM) increases in prevalence in the elderly. There is evidence for significant muscle loss and accelerated cognitive impairment in older adults with T2DM; these comorbidities are critical features of frailty. In the early stages of T2DM, insulin sensitivity can be improved by a “healthy” diet. Management of insulin resistance by diet in people over 65 years of age should be carefully re-evaluated because of the risk for falling due to hypoglycaemia. To date, an optimal dietary programme for older adults with insulin resistance and T2DM has not been described. The use of biomarkers to identify those at risk for T2DM will enable clinicians to offer early dietary advice that will delay onset of disease and of frailty. Here we have used an in silico literature search for putative novel biomarkers of T2DM risk and frailty. We suggest that plasma bilirubin, plasma, urinary DPP4-positive microparticles and plasma pigment epithelium-derived factor merit further investigation as predictive biomarkers for T2DM and frailty risk in older adults. Bilirubin is screened routinely in clinical practice. Measurement of specific microparticle frequency in urine is less invasive than a blood sample so is a good choice for biomonitoring. Future studies should investigate whether early dietary changes, such as increased intake of whey protein and micronutrients that improve muscle function and insulin sensitivity, affect biomarkers and can reduce the longer term complication of frailty in people at risk for T2DM.
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Purpose: To assess the compliance of Daily Disposable Contact Lenses (DDCLs) wearers with replacing lenses at a manufacturer-recommended replacement frequency. To evaluate the ability of two different Health Behavioural Theories (HBT), The Health Belief Model (HBM) and The Theory of Planned Behaviour (TPB), in predicting compliance. Method: A multi-centre survey was conducted using a questionnaire completed anonymously by contact lens wearers during the purchase of DDCLs. Results: Three hundred and fifty-four questionnaires were returned. The survey comprised 58.5% females and 41.5% males (mean age 34. ±. 12. years). Twenty-three percent of respondents were non-compliant with manufacturer-recommended replacement frequency (re-using DDCLs at least once). The main reason for re-using DDCLs was "to save money" (35%). Predictions of compliance behaviour (past behaviour or future intentions) on the basis of the two HBT was investigated through logistic regression analysis: both TPB factors (subjective norms and perceived behavioural control) were significant (p. <. 0.01); HBM was less predictive with only the severity (past behaviour and future intentions) and perceived benefit (only for past behaviour) as significant factors (p. <. 0.05). Conclusions: Non-compliance with DDCLs replacement is widespread, affecting 1 out of 4 Italian wearers. Results from the TPB model show that the involvement of persons socially close to the wearers (subjective norms) and the improvement of the procedure of behavioural control of daily replacement (behavioural control) are of paramount importance in improving compliance. With reference to the HBM, it is important to warn DDCLs wearers of the severity of a contact-lens-related eye infection, and to underline the possibility of its prevention.
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This work presents a method for predicting resource availability in opportunistic grids by means of use pattern analysis (UPA), a technique based on non-supervised learning methods. This prediction method is based on the assumption of the existence of several classes of computational resource use patterns, which can be used to predict the resource availability. Trace-driven simulations validate this basic assumptions, which also provide the parameter settings for the accurate learning of resource use patterns. Experiments made with an implementation of the UPA method show the feasibility of its use in the scheduling of grid tasks with very little overhead. The experiments also demonstrate the method`s superiority over other predictive and non-predictive methods. An adaptative prediction method is suggested to deal with the lack of training data at initialization. Further adaptative behaviour is motivated by experiments which show that, in some special environments, reliable resource use patterns may not always be detected. Copyright (C) 2009 John Wiley & Sons, Ltd.
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A risk score model was developed based in a population of 1,224 individuals from the general population without known diabetes aging 35 years or more from an urban Brazilian population sample in order to select individuals who should be screened in subsequent testing and improve the efficacy of public health assurance. External validation was performed in a second, independent, population from a different city ascertained through a similar epidemiological protocol. The risk score was developed by multiple logistic regression and model performance and cutoff values were derived from a receiver operating characteristic curve. Model`s capacity of predicting fasting blood glucose levels was tested analyzing data from a 5-year follow-up protocol conducted in the general population. Items independently and significantly associated with diabetes were age, BMI and known hypertension. Sensitivity, specificity and proportion of further testing necessary for the best cutoff value were 75.9, 66.9 and 37.2%, respectively. External validation confirmed the model`s adequacy (AUC equal to 0.72). Finally, model score was also capable of predicting fasting blood glucose progression in non-diabetic individuals in a 5-year follow-up period. In conclusion, this simple diabetes risk score was able to identify individuals with an increased likelihood of having diabetes and it can be used to stratify subpopulations in which performing of subsequent tests is necessary and probably cost-effective.
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As survival of patients with CF increases,glucose intolerance and cystic fibrosisrelated diabetes (CFRD),ar e increasingly recognised common complications. CFRD may be preceded by a pre-diabetic state. Using markers identified as being associated with CFRD may improve targeted screening. Aim: To identify features consistently predicting CFRD in paediatric patients. Patients diagnosed with CFRD between January 1997–January 2002 were compared with age and sex matched controls. Clinical,micr obiological, and hospitalisation data was collected at time of CFRD diagnosis,and at six monthly intervals for 3 yr prior to diagnosis. Eight patients with CFRD were identified,mean age 13.7 yr (S.D. 3.49) at time of diagnosis. Control patients underwent OGTT to ensure normal glucose tolerance. Patients with CFRD had a lower FEV1 up to 12 months prior to diagnosis however, this was only significant at diagnosis. There was no difference in weight and height z scores between the 2 groups; however,the decrease in weight and height z scores in the CFRD group over 3 yr prior to diagnosis was significant. Mean number of days in hospital and admissions per patient significantly increased in the CFRD group,6 months prior to diagnosis. No other significant differences were observed between the 2 groups. Conclusions: This study has shown a difference in lung function,gr owth parameters and frequency of hospital admissions between patients with CFRD and controls. These differences may be utilised as tools for targeted screening in the paediatricyadolescent population. Further larger scale studies are required to improve guidelines for targeted screening in this population.
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Asurvey-based field study was conducted with 232 members and nonmembers of the National Tertiary Education Union to investigate the psychological processes underpinning union support. Drawing on value-expectancy models and social identity/self-categorisation theory, this study investigated the role that both individual and grouprelated factors play in predicting attitudinal and behavioural support for the union. Variables investigated included instrumental and ideological attitudes, perceptions of a normative climate of union-support, and perceptions of higher education being under threat. Further to support for previous findings for the role of instrumental and ideological attitudes it was found that the perceived workplace norm had the anticipated direct effect on behaviour and evaluation and also moderated the behavioural expression of ideological and instrumental attitudes. The perception of threat to employment and higher education also directly impacted on behaviour and moderated the behavioural expression of ideological beliefs. The implications of these findings for collective action research will he discussed.
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Objective: To measure the prevalence of obesity in Australian adults and to examine the associations of obesity with socioeconomic and lifestyle factors. Design: AusDiab, a cross-sectional study conducted between May 1999 and December 2000, involved participants from 42 randomly selected districts throughout Australia. Participants: Of 20 347 eligible people aged greater than or equal to 25 years who completed a household interview, 11247 attended the physical examination at local survey sites (response rate, 55%). Main outcome measures: Overweight and obesity defined by body mass index (BMI; kg/m(2)) and waist circumference (cm); sociodemographic factors (including smoking, physical activity and television viewing time). Results: The prevalence of overweight and obesity (BMI greater than or equal to 25.0 kg/m(2); waist circumference greater than or equal to 80.0 cm [women] or greater than or equal to 94.0 cm [men]) in both sexes was almost 60%, defined by either BMI or waist circumference. The prevalence of obesity was 2.5 times higher than in 1980. Using waist circumference, the prevalence of obesity was higher in women than men (34.1% v 26.8%; P < 0.01). Lower educational status, higher television viewing time and lower physical activity time were each strongly associated with obesity, with television viewing time showing a stronger relationship than physical activity time. Conclusions: The prevalence of obesity in Australia has more than doubled in the past 20 years. Strong positive associations between obesity and each of television viewing time and lower physical activity time confirm the influence of sedentary lifestyles on obesity, and underline the potential benefits of reducing sedentary behaviour, as well as increasing physical activity, to curb the obesity epidemic.
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Objective: Limited information is available on the quantitative relationship between family history and the corresponding underlying traits. We analyzed these associations for blood pressure, fasting blood glucose, and cholesterol levels. Methods: Data were obtained from 6,102 Caucasian participants (2,903 men and 3,199 women) aged 35-75 years using a population-based cross-sectional survey in Switzerland. Cardiovascular disease risk factors were measured, and the corresponding family history was self-reported using a structured questionnaire. Results: The prevalence of a positive family history (in first-degree relatives) was 39.6% for hypertension, 22.3% for diabetes, and 29.0% for hypercholesterolemia. Family history was not known for at least one family member in 41.8% of participants for hypertension, 14.4% for diabetes, and 50.2% for hypercholesterolemia. A positive family history was strongly associated with higher levels of the corresponding trait, but not with the other traits. Participants who reported not to know their family history of hypertension had a higher systolic blood pressure than participants with a negative history. Sibling histories had higher positive predictive values than parental histories. The ability to discriminate, calibrate, and reclassify was best for the family history of hypertension. Conclusions: Family history of hypertension, diabetes, and hypercholesterolemia was strongly associated with the corresponding dichotomized and continuous phenotypes.
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CONTEXT: Several genetic risk scores to identify asymptomatic subjects at high risk of developing type 2 diabetes mellitus (T2DM) have been proposed, but it is unclear whether they add extra information to risk scores based on clinical and biological data. OBJECTIVE: The objective of the study was to assess the extra clinical value of genetic risk scores in predicting the occurrence of T2DM. DESIGN: This was a prospective study, with a mean follow-up time of 5 yr. SETTING AND SUBJECTS: The study included 2824 nondiabetic participants (1548 women, 52 ± 10 yr). MAIN OUTCOME MEASURE: Six genetic risk scores for T2DM were tested. Four were derived from the literature and two were created combining all (n = 24) or shared (n = 9) single-nucleotide polymorphisms of the previous scores. A previously validated clinic + biological risk score for T2DM was used as reference. RESULTS: Two hundred seven participants (7.3%) developed T2DM during follow-up. On bivariate analysis, no differences were found for all but one genetic score between nondiabetic and diabetic participants. After adjusting for the validated clinic + biological risk score, none of the genetic scores improved discrimination, as assessed by changes in the area under the receiver-operating characteristic curve (range -0.4 to -0.1%), sensitivity (-2.9 to -1.0%), specificity (0.0-0.1%), and positive (-6.6 to +0.7%) and negative (-0.2 to 0.0%) predictive values. Similarly, no improvement in T2DM risk prediction was found: net reclassification index ranging from -5.3 to -1.6% and nonsignificant (P ≥ 0.49) integrated discrimination improvement. CONCLUSIONS: In this study, adding genetic information to a previously validated clinic + biological score does not seem to improve the prediction of T2DM.
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Executive summaryThe increasing prevalence of chronic diseases is one of the major causes of rising health expenditure, as stated by the WHO. Not only chronic diseases are very costly, but they are by far the leading cause of mortality in the world, representing 60% of all deaths. Diabetes in particular is becoming a major burden of disease. In Switzerland around 5% of the population suffer of type 2 diabetes and 5 to 10% of the annual health care budget is attributable to diabetes. If the predictions of WHO do realise, the prevalence of diabetes will double until 2030 and so is expected the attributable health expenditure.The objective of this thesis is to provide policy recommendations as to slow down the disease progression and its costly complication. We study the factors that influence diabetes dynamics and the interventions that improve health outcomes while decreasing costs according to different time horizon and use systems thinking and system dynamic.Our results show that managing diabetes requires using integrated care interventions that are effective on three fronts: (1) delaying the onset of complications, (2) slowing down the disease progression and (3) accelerating the time to diagnosis of diabetes and its complications. We recommend firstly the implementation of those interventions targeted at changing patients' behaviour which are also less expensive, but require a change in the delivery of care and medical practices. Then policies targeted at an earlier diagnosis of diabetes, its prevention and the diagnosis of complications are to be considered. This sequence of interventions allows saving money, as total costs decrease, even including the costs of interventions and result in longer life expectancy of diabetics in the long term.In diabetes management there is therefore a trade-off between medical costs and patients' benefits on the one hand and between the objectives of obtaining results in the short or long term on the other hand. Decision makers need to deliver acceptable outcomes in the short term. Considering this criterion, the preferred policy may be to focus only on diagnosed diabetics, thus attempting to slow down the progression of their disease, compared to an integrated care approach addressing all the aspects of the disease. Such a policy also yields desirable results in terms of costs and patients' benefits.
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INTRODUCTION: Several studies have shown an increased risk of type 2 diabetes among smokers. Therefore, the aim of this analysis was to assess the relationship between smoking, cumulative smoking exposure and nicotine dependence with pre-diabetes. METHODS: We performed a cross-sectional analysis of healthy adults aged 25-41 in the Principality of Liechtenstein. Individuals with known diabetes, Body Mass Index (BMI) >35 kg/m² and prevalent cardiovascular disease were excluded. Smoking behaviour was assessed by self-report. Pre-diabetes was defined as glycosylated haemoglobin between 5.7% and 6.4%. Multivariable logistic regression models were done. RESULTS: Of the 2142 participants (median age 37 years), 499 (23.3%) had pre-diabetes. There were 1,168 (55%) never smokers, 503 (23%) past smokers and 471 (22%) current smokers, with a prevalence of pre-diabetes of 21.2%, 20.9% and 31.2%, respectively (p <0.0001). In multivariable regression models, current smokers had an odds ratio (OR) of pre-diabetes of 1.82 (95% confidential interval (CI) 1.39; 2.38, p <0.0001). Individuals with a smoking exposure of <5, 5-10 and >10 pack-years had an OR (95% CI) for pre-diabetes of 1.34 (0.90; 2.00), 1.80 (1.07; 3.01) and 2.51 (1.80; 3.59) (p linear trend <0.0001) compared with never smokers. A Fagerström score of 2, 3-5 and >5 among current smokers was associated with an OR (95% CI) for pre-diabetes of 1.27 (0.89; 1.82), 2.15 (1.48; 3.13) and 3.35 (1.73; 6.48) (p linear trend <0.0001). DISCUSSION: Smoking is strongly associated with pre-diabetes in young adults with a low burden of smoking exposure. Nicotine dependence could be a potential mechanism of this relationship.
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QUESTIONS UNDER STUDY: To describe a population-based sample of patients with diabetes and the quality of their care in the canton of Vaud, Switzerland, as a baseline measure for the evaluation of the "Programme cantonal Diabète". METHODS: We conducted a self-administered paper-based questionnaire survey. Non-institutionalised adult (aged ≥18 years) patients with diabetes diagnosed for at least 1 year and residing in the canton of Vaud were recruited by community pharmacies. Women with gestational diabetes, people with obvious cognitive impairment or people not sufficiently fluent in French were excluded. Primary outcomes were recommended processes-of-care and outcomes of care (glycosylated haemoglobin [HbA1c], generic and disease-specific health-related quality of life (HRQoL), overall care score in relation to the Chronic Care Model). Other measures included diabetes education, self-management support and self-efficacy, health status, health behaviour and demographics. RESULTS: A total of 519 patients with diabetes were included. Whereas the mean HbA1c level was 7.3% (n = 177, 95% confidence interval 7.1-7.5), diabetes-specific processes-of-care and influenza vaccination were reported by less than two-thirds of the patients. Physical activity and diet recommendations results mirrored patients' difficulties with their management in daily life and diabetes-specific HRQoL was worst in the dimensions relative to diet (eating and drinking) and sex life. A minority of patients reported ever having participated in diabetes education courses (32.8%). Overall, patients were satisfied with their care and the support they received. CONCLUSIONS: This study provides a broad picture of the experiences of people living with diabetes in the canton of Vaud. It shall guide the development of targeted interventions within the "Programme cantonal Diabète".