Review about 3D-body scanning in the LIFE sample and their characteristics in anthropometric, actometric and medical context

Abstract Background The shape of the human body was, is and will be a major point of interest in healthcare: Researchers studied the different types of bodies for years, addressing a variety of different questions, but mostly focusing on classic anthropometric parameters like weight, height and index parameters (e.g. body mass index, waist to hip ratio and waist to height ratio). In the following, this view will be extended by utilizing 3D-body scanner data towards a holistic description of the previously defined body types of Leipzig population and with regard to their relation to activity parameters, physiological parameters, and predisposition to selected diseases. Data and methods The LIFE study is a population based cohort study with 10,000 participants (4,766 male and 5,234 female) recruited from the city of Leipzig covering a main age range from 40 to 80 years. The study has been designed to investigate civilization diseases, their risk factors, and potential early onset-markers. In the frame of this study, anthropometry was performed using a 3D-body scanner, and activity data was measured in a smaller subcohort of 2,429 participants using a BodySense Armlet. Anthropometric data were previously utilized to define so-called body types, which collect participants with similar body shapes. Results We figured out that most body types are gender-specific, however two body types lack gender-specifics. Moreover, anthropometric and activity parameters show gender-specific differences and change specifically upon ageing: In general, participants are getting smaller, are gaining weight while aging and are losing weight in higher age again. The index parameters are stagnating with growing age, because incremental changes are getting smaller. Also, the participants are less active with increasing age. For physical activity, we were able to confirm a relation between circumference body measures and activity parameters. In the study anthropometric and activity parameters are evaluated in terms of body type specificity: They reveal similar changes upon ageing as observed in the age strata, but some markedly deviate from these expected developments. We also found health risk body types with potential health issues. Furthermore, we have found that BMI levels are virtually constant in the body types upon ageing, while the activity parameters are steadily decreasing. The prevalence of a number of relevant diseases like hypertension, hyperlipidaemia, myocardial infarction, angina pectoris, arthrosis and diabetes, but not depression and rheumatism, showed clear associations to the parameters age, BMI, and MET. In general, the risk body types revealed highest prevalence among the body types, partly on gender-specifically differing overall prevalence levels. Paradoxically, obese and ‘inactive’ body types do not show increased prevalence of myocardial infarctions for men and, especially, for women. Summary and conclusion This study has presented a comprehensive and detailed characterization of the anthropometric body types of Leipzig population in the context of ageing, physical activity, and prevalence of major diseases. Understanding body type-associated risk profiles opens new options in diagnostics and therapy. In this sense, anthropometric body typing represents another step towards individualized medicine.:Table of content 1 Introduction 1 2 Background 3 2.1 Anthropometry 3 2.1.1 Classic measures 3 2.1.2 Physiological indices 4 2.1.3 Usage of 3D-body scanners in medical applications 5 2.2 Physiological parameters 5 2.2.1 Measurement of physical activity 6 2.2.2 Blood pressure 7 3 Data and Methods 8 3.1 LIFE – the Leipzig population study 8 3.2 Anthropometry using 3D-body scanning 9 3.3 Definition of meta-measures and body types 9 3.4 Methods for measuring the physical activity 10 3.4.1 Body SenseWear Pro Armband 10 3.4.2 IPAQ 11 3.4.3 Comparison of IPAQ and SWA 11 3.5 Units 12 4 General characterization of the study population 13 4.1 Anthropometric parameters vary upon aging 13 4.2 Activity level decreases with age 17 4.3 Body measures associated with activity parameters 20 5 Description of the body types 22 5.3 Physical activity parameters of the body types 26 5.4 Age related development of the body types 29 5.5 Body types of the oldest participants 33 5.6 Distribution widths 34 6 Body types and their prevalence of selected diseases 37 6.1 BMI and MET as risk factors 37 6.2 Hypertension 39 6.4 Hyperlipidaemia 43 6.5 Myocardial infarction 44 6.6 Angina pectoris 46 6.7 Arthrosis 48 6.8 Diabetes 49 6.9 Depression 51 6.10 Rheumatism 53 6.11 Disease prevalence and their relation to the body types 55 7 A holistic review of the body types in the LIFE study population 58 7.1 General aspects 58 7.2 Gender-unspecific body types B1 and B2 58 7.3 Female body types 59 7.4 Male body types 63 8 Summary and Conclusion 66 References 68 Appendix A Regression analysis of body measures towards MET. 77 Appendix B The ageing human body shape 79 Erklärung über die eigenständige Abfassung der Arbeit 114 Danksagung 115 Lebenslau