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000291026 1001_ $$aStein, Michael J$$b0
000291026 245__ $$aDifferences in Anthropometric Measures Based on Sex, Age, and Health Status.
000291026 260__ $$aKöln$$bDt. Ärzte-Verl.$$c2024
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000291026 520__ $$aObesity is a worldwide health problem. We conducted detailed analyses of anthropometric measures in a comprehensive, population-based, current cohort in Germany.In the German National Cohort (NAKO), we analyzed cross-sectional data on body mass index (BMI), waist and hip circumference, subcutaneous (SAT) and visceral adipose tissue (VAT) as measured by ultrasound, and body fat percentage. The data were stratified by sex, age, and self-reported physicians' diagnoses of cardiovascular diseases (CVD), metabolic diseases (MetD), cardiometabolic diseases (CMD), and cancer.Data were available from 204 751 participants (age, 49.9 ± 12.8 years; 50.5% women). Body size measures generally increased with age. Men had a higher BMI, larger waist circumference, and more VAT than women, while women had a larger hip circumference, more SAT, and a higher body fat percentage than men. For example, the mean BMI of participants over age 60 was 28.3 kg/m2 in men and 27.6 kg/m2 in women. CVD, MetD, and CMD were associated with higher anthropometric values, while cancer was not. For example, the mean BMI was 25.3 kg/m2 in healthy women, 29.4 kg/m2 in women with CMD, and 25.4 kg/m2 in women with cancer.Obesity is widespread in Germany, with notable differences between the sexes in anthro - pometric values. Obesity was more common in older participants and those with chronic diseases other than cancer. Elevated values were especially common in multimorbid individuals.
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000291026 650_2 $$2MeSH$$aHumans
000291026 650_2 $$2MeSH$$aMale
000291026 650_2 $$2MeSH$$aFemale
000291026 650_2 $$2MeSH$$aMiddle Aged
000291026 650_2 $$2MeSH$$aGermany: epidemiology
000291026 650_2 $$2MeSH$$aAnthropometry: methods
000291026 650_2 $$2MeSH$$aAdult
000291026 650_2 $$2MeSH$$aBody Mass Index
000291026 650_2 $$2MeSH$$aHealth Status
000291026 650_2 $$2MeSH$$aObesity: epidemiology
000291026 650_2 $$2MeSH$$aSex Distribution
000291026 650_2 $$2MeSH$$aAge Distribution
000291026 650_2 $$2MeSH$$aCardiovascular Diseases: epidemiology
000291026 650_2 $$2MeSH$$aAged
000291026 7001_ $$aFischer, Beate$$b1
000291026 7001_ $$aBohmann, Patricia$$b2
000291026 7001_ $$aAhrens, Wolfgang$$b3
000291026 7001_ $$aBerger, Klaus$$b4
000291026 7001_ $$0P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2$$aBrenner, Hermann$$b5$$udkfz
000291026 7001_ $$aGünther, Kathrin$$b6
000291026 7001_ $$aHarth, Volker$$b7
000291026 7001_ $$aHeise, Jana-Kristin$$b8
000291026 7001_ $$aKarch, André$$b9
000291026 7001_ $$aKlett-Tammen, Carolina J$$b10
000291026 7001_ $$0P:(DE-He78)13aa5fe9d9961c9fd67193befb0dcf88$$aKoch-Gallenkamp, Lena$$b11$$udkfz
000291026 7001_ $$aKrist, Lilian$$b12
000291026 7001_ $$aLieb, Wolfgang$$b13
000291026 7001_ $$aMeinke-Franze, Claudia$$b14
000291026 7001_ $$aMichels, Karin B$$b15
000291026 7001_ $$aMikolajczyk, Rafael$$b16
000291026 7001_ $$aNimptsch, Katharina$$b17
000291026 7001_ $$aObi, Nadia$$b18
000291026 7001_ $$aPeters, Annette$$b19
000291026 7001_ $$aPischon, Tobias$$b20
000291026 7001_ $$aSchipf, Sabine$$b21
000291026 7001_ $$aSchmidt, Börge$$b22
000291026 7001_ $$aStang, Andreas$$b23
000291026 7001_ $$aThierry, Sigrid$$b24
000291026 7001_ $$aWillich, Stefan N$$b25
000291026 7001_ $$aWirkner, Kerstin$$b26
000291026 7001_ $$aLeitzmann, Michael F$$b27
000291026 7001_ $$aSedlmeier, Anja M$$b28
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