Literature DB >> 33574282

The aging human body shape.

Alexander Frenzel1, Hans Binder1,2, Nadja Walter3, Kerstin Wirkner2,4, Markus Loeffler1,2,4, Henry Loeffler-Wirth5,6.   

Abstract

Body shape and composition are heterogeneous among humans with possible impact for health. Anthropometric methods and data are needed to better describe the diversity of the human body in human populations, its age dependence, and associations with health risk. We applied whole-body laser scanning to a cohort of 8499 women and men of age 40-80 years within the frame of the LIFE (Leipzig Research Center for Civilization Diseases) study aimed at discovering health risk in a middle European urban population. Body scanning delivers multidimensional anthropometric data, which were further processed by machine learning to stratify the participants into body types. We here applied this body typing concept to describe the diversity of body shapes in an aging population and its association with physical activity and selected health and lifestyle factors. We find that aging results in similar reshaping of female and male bodies despite the large diversity of body types observed in the study. Slim body shapes remain slim and partly tend to become even more lean and fragile, while obese body shapes remain obese. Female body shapes change more strongly than male ones. The incidence of the different body types changes with characteristic Life Course trajectories. Physical activity is inversely related to the body mass index and decreases with age, while self-reported incidence for myocardial infarction shows overall the inverse trend. We discuss health risks factors in the context of body shape and its relation to obesity. Body typing opens options for personalized anthropometry to better estimate health risk in epidemiological research and future clinical applications.

Year:  2020        PMID: 33574282     DOI: 10.1038/s41514-020-0043-9

Source DB:  PubMed          Journal:  NPJ Aging Mech Dis        ISSN: 2056-3973


  35 in total

Review 1.  A machine learning approach relating 3D body scans to body composition in humans.

Authors:  James D Pleuss; Kevin Talty; Steven Morse; Patrick Kuiper; Michael Scioletti; Steven B Heymsfield; Diana M Thomas
Journal:  Eur J Clin Nutr       Date:  2018-10-12       Impact factor: 4.016

2.  Waist and hip circumferences have independent and opposite effects on cardiovascular disease risk factors: the Quebec Family Study.

Authors:  J C Seidell; L Pérusse; J P Després; C Bouchard
Journal:  Am J Clin Nutr       Date:  2001-09       Impact factor: 7.045

3.  The effect of age on the association between body-mass index and mortality.

Authors:  J Stevens; J Cai; E R Pamuk; D F Williamson; M J Thun; J L Wood
Journal:  N Engl J Med       Date:  1998-01-01       Impact factor: 91.245

4.  Application of three-dimensional body scanner: observation of prevalence of metabolic syndrome.

Authors:  J D Lin; W K Chiou; H F Weng; J T Fang; T H Liu
Journal:  Clin Nutr       Date:  2004-12       Impact factor: 7.324

5.  The obese without cardiometabolic risk factor clustering and the normal weight with cardiometabolic risk factor clustering: prevalence and correlates of 2 phenotypes among the US population (NHANES 1999-2004).

Authors:  Rachel P Wildman; Paul Muntner; Kristi Reynolds; Aileen P McGinn; Swapnil Rajpathak; Judith Wylie-Rosett; MaryFran R Sowers
Journal:  Arch Intern Med       Date:  2008-08-11

6.  Independent and opposite associations of waist and hip circumferences with diabetes, hypertension and dyslipidemia: the AusDiab Study.

Authors:  M B Snijder; P Z Zimmet; M Visser; J M Dekker; J C Seidell; J E Shaw
Journal:  Int J Obes Relat Metab Disord       Date:  2004-03

7.  Trunk fat and leg fat have independent and opposite associations with fasting and postload glucose levels: the Hoorn study.

Authors:  Marieke B Snijder; Jacqueline M Dekker; Marjolein Visser; Lex M Bouter; Coen D A Stehouwer; John S Yudkin; Robert J Heine; Giel Nijpels; Jacob C Seidell
Journal:  Diabetes Care       Date:  2004-02       Impact factor: 19.112

Review 8.  Overview of Epidemiology and Contribution of Obesity and Body Fat Distribution to Cardiovascular Disease: An Update.

Authors:  Marie-Eve Piché; Paul Poirier; Isabelle Lemieux; Jean-Pierre Després
Journal:  Prog Cardiovasc Dis       Date:  2018-06-28       Impact factor: 8.194

9.  The LIFE-Adult-Study: objectives and design of a population-based cohort study with 10,000 deeply phenotyped adults in Germany.

Authors:  Markus Loeffler; Christoph Engel; Peter Ahnert; Dorothee Alfermann; Katrin Arelin; Ronny Baber; Frank Beutner; Hans Binder; Elmar Brähler; Ralph Burkhardt; Uta Ceglarek; Cornelia Enzenbach; Michael Fuchs; Heide Glaesmer; Friederike Girlich; Andreas Hagendorff; Madlen Häntzsch; Ulrich Hegerl; Sylvia Henger; Tilman Hensch; Andreas Hinz; Volker Holzendorf; Daniela Husser; Anette Kersting; Alexander Kiel; Toralf Kirsten; Jürgen Kratzsch; Knut Krohn; Tobias Luck; Susanne Melzer; Jeffrey Netto; Matthias Nüchter; Matthias Raschpichler; Franziska G Rauscher; Steffi G Riedel-Heller; Christian Sander; Markus Scholz; Peter Schönknecht; Matthias L Schroeter; Jan-Christoph Simon; Ronald Speer; Julia Stäker; Robert Stein; Yve Stöbel-Richter; Michael Stumvoll; Attila Tarnok; Andrej Teren; Daniel Teupser; Francisca S Then; Anke Tönjes; Regina Treudler; Arno Villringer; Alexander Weissgerber; Peter Wiedemann; Silke Zachariae; Kerstin Wirkner; Joachim Thiery
Journal:  BMC Public Health       Date:  2015-07-22       Impact factor: 3.295

10.  Measurement of waist and hip circumference with a body surface scanner: feasibility, validity, reliability, and correlations with markers of the metabolic syndrome.

Authors:  Lina Jaeschke; Astrid Steinbrecher; Tobias Pischon
Journal:  PLoS One       Date:  2015-03-06       Impact factor: 3.240

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