Producing Feedstock for Biofuels: Land-Use and Local Environmental Impacts

This report covers Chalmers responsibilities for subtask 1.3 - land-use patterns as well as parts of subtask 3.4 – data for other environmental impacts, in the EU Biofuel Baseline projec

Trends in the incidence of dementia: design and methods in the Alzheimer Cohorts Consortium.

Several studies have reported a decline in incidence of dementia which may have large implications for the projected burden of disease, and provide important guidance to preventive efforts. However, reports are conflicting or inconclusive with regard to the impact of gender and education with underlying causes of a presumed declining trend remaining largely unidentified. The Alzheimer Cohorts Consortium aggregates data from nine international population-based cohorts to determine changes in the incidence of dementia since 1990. We will employ Poisson regression models to calculate incidence rates in each cohort and Cox proportional hazard regression to compare 5-year cumulative hazards across study-specific epochs. Finally, we will meta-analyse changes per decade across cohorts, and repeat all analysis stratified by sex, education and APOE genotype. In all cohorts combined, there are data on almost 69,000 people at risk of dementia with the range of follow-up years between 2 and 27. The average age at baseline is similar across cohorts ranging between 72 and 77. Uniting a wide range of disease-specific and methodological expertise in research teams, the first analyses within the Alzheimer Cohorts Consortium are underway to tackle outstanding challenges in the assessment of time-trends in dementia occurrence

Trends in the incidence of dementia: design and methods in the Alzheimer Cohorts Consortium

Several studies have reported a decline in incidence of dementia which may have large implications for the projected burden of disease, and provide important guidance to preventive efforts. However, reports are conflicting or inconclusive with regard to the impact of gender and education with underlying causes of a presumed declining trend remaining largely unidentified. The Alzheimer Cohorts Consortium aggregates data from nine international population-based cohorts to determine changes in the incidence of dementia since 1990. We will employ Poisson regression models to calculate incidence rates in each cohort and Cox proportional hazard regression to compare 5-year cumulative hazards across study-specific epochs. Finally, we will meta-analyse changes per decade across cohorts, and repeat all analysis stratified by sex, education and APOE genotype. In all cohorts combined, there are data on almost 69,000 people at risk of dementia with the range of follow-up years between 2 and 27. The average age at baseline is similar across cohorts ranging between 72 and 77. Uniting a wide range of disease-specific and methodological expertise in research teams, the first analyses within the Alzheimer Cohorts Consortium are underway to tackle outstanding challenges in the assessment of time-trends in dementia occurrence

Dementia risk prediction in the population: are screening models accurate?

Early identification of individuals at risk of dementia will become crucial when effective preventative strategies for this condition are developed. Various dementia prediction models have been proposed, including clinic-based criteria for mild cognitive impairment, and more-broadly constructed algorithms, which synthesize information from known dementia risk factors, such as poor cognition and health. Knowledge of the predictive accuracy of such models will be important if they are to be used in daily clinical practice or to screen the entire older population (individuals aged 65 years). This article presents an overview of recent progress in the development of dementia prediction models for use in population screening. In total, 25 articles relating to dementia risk screening met our inclusion criteria for review. Our evaluation of the predictive accuracy of each model shows that most are poor at discriminating at-risk individuals from not-at-risk cases. The best models incorporate diverse sources of information across multiple risk factors. Typically, poor accuracy is associated with single-factor models, long follow-up intervals and the outcome measure of all-cause dementia. A parsimonious and cost-effective consensus model needs to be developed that accurately identifies individuals with a high risk of future dementia. © 2010 Macmillan Publishers Limited. All rights reserved

Adherence to multidomain interventions for dementia prevention: Data from the FINGER and MAPT trials

Introduction: Multidomain interventions, targeting multiple risk factors simultaneously, could be effective dementia prevention strategies, but may be burdensome and not universally acceptable. Methods: We studied adherence rates and predictors in the Finnish Geriatric Intervevntion Study to Prevent Cognitive Impairment and Disability and Multidomain Alzheimer Preventive Trial prevention trials, for all intervention components (separately and simultaneously). Finnish Geriatric Intervevntion Study to Prevent Cognitive Impairment and Disability participants received a 2-year multidomain lifestyle intervention (physical training, cognitive training, nutritional counseling, and cardiovascular monitoring). Multidomain Alzheimer Preventive Trial participants received a 3-year multidomain lifestyle intervention (cognitive training, physical activity counseling, and nutritional counseling) with either an omega-3 supplement or placebo. Results: Adherence decreased with increasing intervention complexity and intensity: it was highest for cardiovascular monitoring, nutritional counseling, and the omega-3 supplement, and lowest for unsupervised computer-based cognitive training. The most consistent baseline predictors of adherence were smoking and depressive symptoms. Discussion: Reducing participant burden, while ensuring that technological tools are suitable for older individuals, maintaining face-to-face contacts, and taking into account participant characteristics may increase adherence in future trials