ArticleNPJ aging and mechanisms of disease2020
The aging human body shape.
Article in NPJ aging and mechanisms of disease, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
11 citing papers in PubMed, 34 citations in OpenAlex.
- 3D body shape-based phenotyping for precision risk stratification of metabolic syndrome.Lipids in health and disease · 2026Article
- Anthropometric indices in older adults with and without Locomotive Syndrome.BMC geriatrics · 2024Article
- Translating digital anthropometry measurements obtained from different 3D body image scanners.European journal of clinical nutrition · 2023Review
- Cohort Profile: The LIFE-Adult-Study.International journal of epidemiology · 2023Article
- AnthropoAge, a novel approach to integrate body composition into the estimation of biological age.Aging cell · 2023Article
- Do Body Composition and Values of Selected Nutritional Status Indices Influence the Glycaemic Index Values of Vegetarian Dishes? A Pilot Study in a Group of Older Women.International journal of environmental research and public health · 2022Article
- Cross-Talk between the Cytokine IL-37 and Thyroid Hormones in Modulating Chronic Inflammation Associated with Target Organ Damage in Age-Related Metabolic and Vascular Conditions.International journal of molecular sciences · 2022Review
- Individualized Biological Age as a Predictor of Disease: Korean Genome and Epidemiology Study (KoGES) Cohort.Journal of personalized medicine · 2022Article
- Article
- Gait Analysis under Spatial Navigation Task in Elderly People-A Pilot Study.Sensors (Basel, Switzerland) · 2021Article
- Differences in the gut Firmicutes to Bacteroidetes ratio across age groups in healthy Ukrainian population.BMC microbiology · 2020Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.