Publications

8 Publications matching the given criteria: (Clear all filters)
Human disease: obesity8

Abstract (Expand)

3D-body scanning anthropometry is a suitable method for characterization of physiological development of children and adolescents, and for understanding onset and progression of disorders like overweight and obesity. Here we present a novel body typing approach to describe and to interpret longitudinal 3D-body scanning data of more than 800 children and adolescents measured in up to four follow-ups in intervals of 1 year, referring to an age range between 6 and 18 years. We analyzed transitions between body types assigned to lower-, normal- and overweight participants upon development of children and adolescents. We found a virtually parallel development of the body types with only a few transitions between them. Body types of children and adolescents tend to conserve their weight category. 3D body scanning anthropometry in combination with body typing constitutes a novel option to investigate onset and progression of obesity in children.

Authors: H. Loeffler-Wirth, M. Vogel, T. Kirsten, F. Glock, T. Poulain, A. Korner, M. Loeffler, W. Kiess, H. Binder

Date Published: 14th Sep 2018

Publication Type: Not specified

Human Diseases: obesity

Abstract (Expand)

Three-dimensional (3D-) body scanning of children and adolescents allows the detailed study of physiological development in terms of anthropometrical alterations which potentially provide early onset markers for obesity. Here, we present a systematic analysis of body scanning data of 2,700 urban children and adolescents in the age range between 5 and 18 years with the special aim to stratify the participants into distinct body shape types and to describe their change upon development. In a first step, we extracted a set of eight representative meta-measures from the data. Each of them collects a related group of anthropometrical features and changes specifically upon aging. In a second step we defined seven body types by clustering the meta-measures of all participants. These body types describe the body shapes in terms of three weight (lower, normal and overweight) and three age (young, medium and older) categories. For younger children (age of 5-10 years) we found a common 'early childhood body shape' which splits into three weight-dependent types for older children, with one or two years delay for boys. Our study shows that the concept of body types provides a reliable option for the anthropometric characterization of developing and aging populations.

Authors: H. Loeffler-Wirth, M. Vogel, T. Kirsten, F. Glock, T. Poulain, A. Korner, M. Loeffler, W. Kiess, H. Binder

Date Published: 21st Oct 2017

Publication Type: Not specified

Human Diseases: obesity

Abstract (Expand)

Obesity is a complex neurobehavioral disorder that has been linked to changes in brain structure and function. However, the impact of obesity on functional connectivity and cognition in aging humans is largely unknown. Therefore, the association of body mass index (BMI), resting-state network connectivity, and cognitive performance in 712 healthy, well-characterized older adults of the Leipzig Research Center for Civilization Diseases (LIFE) cohort (60-80 years old, mean BMI 27.6 kg/m(2) +/- 4.2 SD, main sample: n = 521, replication sample: n = 191) was determined. Statistical analyses included a multivariate model selection approach followed by univariate analyses to adjust for possible confounders. Results showed that a higher BMI was significantly associated with lower default mode functional connectivity in the posterior cingulate cortex and precuneus. The effect remained stable after controlling for age, sex, head motion, registration quality, cardiovascular, and genetic factors as well as in replication analyses. Lower functional connectivity in BMI-associated areas correlated with worse executive function. In addition, higher BMI correlated with stronger head motion. Using 3T neuroimaging in a large cohort of healthy older adults, independent negative associations of obesity and functional connectivity in the posterior default mode network were observed. In addition, a subtle link between lower resting-state connectivity in BMI-associated regions and cognitive function was found. The findings might indicate that obesity is associated with patterns of decreased default mode connectivity similar to those seen in populations at risk for Alzheimer's disease. Hum Brain Mapp 38:3502-3515, 2017. (c) 2017 Wiley Periodicals, Inc.

Authors: F. Beyer, S. Kharabian Masouleh, J. M. Huntenburg, L. Lampe, T. Luck, S. G. Riedel-Heller, M. Loeffler, M. L. Schroeter, M. Stumvoll, A. Villringer, A. V. Witte

Date Published: 12th Apr 2017

Publication Type: Journal article

Human Diseases: obesity

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

Abstract (Expand)

Midlife obesity has often been associated with accelerated cognitive decline during aging. Obesity leads to changes in multiple physiological factors that could impact neuronal tissue. Numerous studies have linked obesity and higher body mass index (BMI) with differences in cognitive functions and brain structure, including total brain volume, regional gray matter volume and white matter (WM) microstructure. However, regarding to WM, the available neuroimaging studies incorporated mainly small sample sizes that yielded less conclusive results. Thus, we investigated the association of obesity, measured using BMI and waist to hip ratio (WHR), with changes in WM microstructure, as well as variance in cognitive test scores in a large cohort of community-dwelling healthy individuals older than 60 years.

Authors: Rui Zhang, L. Lampe, Frauke Beyer, Sebastian Huhn, S. K. Masouleh, T. Luck, S. G. Riedel-Heller, Markus Löffler, M. L. Schroeter

Date Published: 28th Nov 2016

Publication Type: Not specified

Human Diseases: obesity

Abstract (Expand)

Three-dimensional (3D) whole body scanners are increasingly used as precise measuring tools for the rapid quantification of anthropometric measures in epidemiological studies. We analyzed 3D whole body scanning data of nearly 10,000 participants of a cohort collected from the adult population of Leipzig, one of the largest cities in Eastern Germany. We present a novel approach for the systematic analysis of this data which aims at identifying distinguishable clusters of body shapes called body types. In the first step, our method aggregates body measures provided by the scanner into meta-measures, each representing one relevant dimension of the body shape. In a next step, we stratified the cohort into body types and assessed their stability and dependence on the size of the underlying cohort. Using self-organizing maps (SOM) we identified thirteen robust meta-measures and fifteen body types comprising between 1 and 18 percent of the total cohort size. Thirteen of them are virtually gender specific (six for women and seven for men) and thus reflect most abundant body shapes of women and men. Two body types include both women and men, and describe androgynous body shapes that lack typical gender specific features. The body types disentangle a large variability of body shapes enabling distinctions which go beyond the traditional indices such as body mass index, the waist-to-height ratio, the waist-to-hip ratio and the mortality-hazard ABSI-index. In a next step, we will link the identified body types with disease predispositions to study how size and shape of the human body impact health and disease.

Authors: H. Loffler-Wirth, E. Willscher, P. Ahnert, K. Wirkner, C. Engel, M. Loeffler, H. Binder

Date Published: 29th Jul 2016

Publication Type: Not specified

Human Diseases: obesity

Abstract (Expand)

The 'Fragebogen zum Essverhalten' (FEV) is the German version of the Three-factor-Eating-Questionnaire (TFEQ). This questionnaire covers three domains of eating behaviour ('cognitive restraint', 'disinhibition' and 'hunger') as well as common problems (e.g. craving for sweets). So far, there is a lack of normative data of the FEV especially for the middle-aged and older population. Aim of this study therefore was to provide age- and gender-specific norms of the FEV for the general population aged 40-79 years. We studied 3144 participants of the ongoing large community-based Leipzig Research Center for Civilization Diseases (LIFE) Health Care Study. We provided age- (four age groups: 40-49, 50-59, 60-69, and 70-79 years) and gender-specific percentile ranks and T-scores for the three domains of the FEV as well as age- and gender-specific frequencies of the common problems in eating behaviour. Females scored significantly higher than males in all three domains of the FEV (p < 0.001). Older individuals showed significantly higher mean scores than the younger ones in the domain of cognitive restraint, but lower mean scores in disinhibition and hunger (p < 0.001). 45.1% of the males and 69.9% of the females reported specific problems in eating. The main problem in both genders was craving for sweets (38.6%). Eating in response to stress was mostly reported in younger individuals. The present study offers current normative data for the FEV in the middle-aged and older general population that can be applied in clinical and non-clinical settings. Information on eating behaviour can be helpful in understanding body weight modulation, and thus, may help to improve interventive and preventive programmes for overweight, obesity, and eating disorders.

Authors: A. Loffler, T. Luck, F. S. Then, M. Luppa, C. Sikorski, P. Kovacs, A. Tonjes, Y. Bottcher, J. Breitfeld, A. Horstmann, M. Loffler, C. Engel, J. Thiery, M. Stumvoll, S. G. Riedel-Heller

Date Published: 19th Apr 2015

Publication Type: Not specified

Human Diseases: obesity, eating disorder

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