Berit Filges's research while affiliated with University of Greifswald and other places

Background and aim: Body shape and anthropometrics are well-known risk factors for cardiovascular diseases (CVD) and mortality. Hand-grip strength (HGS) is also a meaningful marker of health and a promising predictor of CVD and mortality. There is a lack of studies that have systematically investigated associations between body shape and anthropometrics with HGS. In a population-based study, we investigated if anthropometric markers derived from 3D body scanning are related to HGS. Methods and results: We used the data of 1,599 individuals aged 36 to 93 years, who participated in the Study of Health in Pomerania. A total of 87 anthropometric markers, determined by a 3D body scanner, were included in the analysis. Anthropometric measurements were standardized and used as exposure variables. HGS was measured with a hand dynamometer and used as outcome. Sex-stratified linear regression models adjusted for age and height were used to relate standard- ized anthropometrics and HGS. Anthropometric markers were ranked according to -log-p-values. In men, left and right forearm circumference, left arm length to neck (C7), left forearm length, and forearm-fingertip length were most strongly related to HGS. In women, right forearm circum- ference, forearm-fingertip length, shoulder breadth, left forearm circumference, and right wrist circumference showed the most significant associations with HGS. The final prediction models contained 13 anthropometric markers in males (R2Z0.54) and eight anthropometric markers in females (R2Z0.37). Conclusions: The identified parameters may help estimate HGS in the clinical setting. However, studies in clinical settings are essential to validating our findings.

The assessment of cardiorespiratory fitness (CRF) is an important tool for prognosis evaluation of cardiovascular events. The gold standard to measure CRF is cardiopulmonary exercise testing (CPET) to determine peak oxygen uptake (VO2peak). However, CPET is not only time consuming but also expensive and is therefore not widely applicable in daily practice. The aim of our study was to analyze, whether and which anthropometric markers derived from a 3D body scanner were related to VO2peak in a general population-based study. We analyzed data (SHIP-START-3) from 3D body scanner and CPET of 1035 subjects (529 women; 51.1%, age range 36–93). A total of 164 anthropometric markers were detected with the 3D body scanner VITUS Smart XXL using the software AnthroScan Professional. Anthropometric measurements were standardized and associated with CRF by sex-stratified linear regression models adjusted for age and height. Anthropometric markers were ranked according to the − log- p values derived from these regression models. In men a greater left and right thigh-knee-ratio, a longer forearm-fingertip length, a greater left thigh circumference and greater left upper arm circumference were most strongly associated with a higher VO2peak. In women a greater left and right thigh circumference, left calf circumference, thigh thickness and right calf circumference were most strongly associated with a higher VO2peak. The detected VO2peak-related anthropometric markers could be helpful in assessing CRF in clinical routine. Commonly used anthropometric markers, e.g. waist and hip circumference, were not among the markers associated with VO2peak.