Publications

11 Publications matching the given criteria: (Clear all filters)
Published year: 201711

Abstract (Expand)

INTRODUCTION: A global dementia epidemic is projected for the year 2050 with an ever-rising number of individuals living with the syndrome worldwide. However, increasingly, studies are emerging from high-income countries (HIC) that show a positive trend towards a possible decrease in dementia occurrence. Therefore, we aim to systematically summarise evidence regarding secular trends in the incidence of dementia in HIC. METHODS AND ANALYSIS: We will conduct a systematic review of the literature on secular trends in dementia incidence in HIC according to the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) and the Meta-analysis of Observational Studies in Epidemiology (MOOSE) statements. To do so, we will search the databases MEDLINE (PubMed interface), EMBASE (Ovid interface) and Web of Science (Web of Science interface), as well as the grey literature on unpublished studies. To be eligible, studies must have been published in English or German since 1990 and provide sufficient information on prespecified eligibility criteria regarding outcome measurement and methodological approach. Study selection, data extraction and risk of bias assessment will be performed independently by 2 reviewers. Disagreement will be resolved by discussion and/or the involvement of a third researcher. Data abstraction will include study and participant characteristics, outcomes and methodological aspects. Results will be described and discussed regarding methodology. Depending on the number of studies found and the heterogeneity between the studies, we plan to combine outcome data through meta-analysis in order to get pooled incidence measures. ETHICS AND DISSEMINATION: No primary data will be collected; thus, ethical approval is not required. The results will be disseminated through a peer-reviewed publication and conference presentations. PROSPERO REGISTRATION NUMBER: CRD42016043232.

Authors: S. Roehr, A. Pabst, T. Luck, S. G. Riedel-Heller

Date Published: 7th Apr 2017

Publication Type: Journal article

Human Diseases: dementia, Alzheimer's disease

Abstract (Expand)

BACKGROUND: The Generalized Anxiety Disorder Scales GAD-7 and GAD-2 are instruments for the assessment of anxiety. The aims of this study are to test psychometric properties of these questionnaires, to provide normative values, and to investigate associations with sociodemographic factors, quality of life, psychological variables, and behavioral factors. METHODS: A German community sample (n=9721) with an age range of 18-80 years was surveyed using the GAD-7 and several other questionnaires. RESULTS: Confirmatory factor analyses confirmed the unidimensionality and measurement invariance of the GAD-7 across age and gender. Females were more anxious than males (mean scores: M=4.07 vs. M=3.01; effect size: d=0.33). There was no linear age trend. A total of 5.9% fulfilled the cut-off criterion of 10 and above. Anxiety was correlated with low quality of life, fatigue, low habitual optimism, physical complaints, sleep problems, low life satisfaction, low social support, low education, unemployment, and low income. Cigarette smoking and alcohol consumption were also associated with heightened anxiety, especially in women. When comparing the GAD-7 (7 items) with the ultra-short GAD-2 (2 items), the GAD-7 instrument was superior to the GAD-2 regarding several psychometric criteria. LIMITATIONS: The response rate (33%) was low. Because of the cross-sectional character of the study, causal conclusions cannot be drawn. A further limitation is the lack of a gold standard for diagnosing anxiety. CONCLUSIONS: The GAD-7 can be recommended for use in clinical research and routine.

Authors: A. Hinz, A. M. Klein, E. Brahler, H. Glaesmer, T. Luck, S. G. Riedel-Heller, K. Wirkner, A. Hilbert

Date Published: 1st Mar 2017

Publication Type: Not specified

Human Diseases: generalized anxiety disorder

Abstract (Expand)

The disparity between the chronological age of an individual and their brain-age measured based on biological information has the potential to offer clinically relevant biomarkers of neurological syndromes that emerge late in the lifespan. While prior brain-age prediction studies have relied exclusively on either structural or functional brain data, here we investigate how multimodal brain-imaging data improves age prediction. Using cortical anatomy and whole-brain functional connectivity on a large adult lifespan sample (N=2354, age 19-82), we found that multimodal data improves brain-based age prediction, resulting in a mean absolute prediction error of 4.29 years. Furthermore, we found that the discrepancy between predicted age and chronological age captures cognitive impairment. Importantly, the brain-age measure was robust to confounding effects: head motion did not drive brain-based age prediction and our models generalized reasonably to an independent dataset acquired at a different site (N=475). Generalization performance was increased by training models on a larger and more heterogeneous dataset. The robustness of multimodal brain-age prediction to confounds, generalizability across sites, and sensitivity to clinically-relevant impairments, suggests promising future application to the early prediction of neurocognitive disorders.

Authors: F. Liem, G. Varoquaux, J. Kynast, F. Beyer, S. Kharabian Masouleh, J. M. Huntenburg, L. Lampe, M. Rahim, A. Abraham, R. C. Craddock, S. Riedel-Heller, T. Luck, M. Loeffler, M. L. Schroeter, A. V. Witte, A. Villringer, D. S. Margulies

Date Published: 1st Mar 2017

Publication Type: Journal article

Abstract (Expand)

Background and objectives: Obesity has been associated with increased risk of dementia. Grey and white matter (WM) of the brain are commonly used as biomarkers for early detection of dementia. However, considering WM, available neuroimaging studies had mainly small sample size and yielded less conclusive results (Kullmann et al., 2015). Recently, a positive correlation between obesity and fractional anisotropy (FA) in a middle age group was reported (Birdsill et al. 2017). Furthermore, obesity is related to many medical problems such as diabetes and hypertension. Diabetes and hypertension were found to be correlated with brain structures independently (de Leeuw et al., 2002; Weinstein et al., 2015). Yet, studies rarely investigated non-lesion WM microstructure and its association with diabetes and blood pressure. Therefore we aim to investigate the relation between abdominal obesity, diabetes, blood pressure and WM microstructural variability in a large cohort of community-dwelling healthy adults. Methods: The sample included dementia-free participants (mean age 55 ± 16 years; 50.7% women) of the LIFE cohort with brain MRI scans (n = 1255). WM microstructure was measured with diffusion tensor imaging (DTI). Mean FA was derived from the individual WM skeleton processed by tract-based-spatial-statistic method. Linear regression models were used to assess the relationships between diabetes, blood pressure, waist to hip ratio (WHR) and DTI parameters. Adjustments were made for age, sex, education and Apoe4. Results: The preliminary result indicated diabetes, systolic blood pressure and WHR were independently associated with lower FA, and diabetes explained the most variance besides age. Subgroup analysis revealed both systolic blood pressure and WHR were negatively associated with mean FA in the non-diabetes group (n=1101). Conclusions: The preliminary result of our study indicates that diabetes accelerated brain aging on directional diffusion of WM. Abdominal fat and blood pressure were associated with WM variabilities independently from age, sex and diabetes. With subsequent analysis of additional DTI measures, blood parameters, WM hyperintensity maps and voxel-based microstructural WM “integrity”, we aim to further characterize the associations between obesity, diabetes, blood pressure and WM microstructure. This will contribute to the existing literature and help to disentangle the underlying mechanism.

Authors: Rui Zhang, Frauke Beyer, L. Lampe, T. Luck, S. G. Riedel-Heller, M. Stumvoll, Markus Löffler, M. L. Schroeter, A. Villringer, A. V. Witte

Date Published: 2017

Publication Type: Not specified

Human Diseases: diabetes mellitus, obesity, hypertension

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