title: MRI-determined total volumes of visceral and subcutaneous abdominal and trunk adipose tissue are differentially and sex-dependently associated with patterns of estimated usual nutrient intake in a northern German population.
abstract: BACKGROUND
  Visceral (VAT) and subcutaneous abdominal (SAAT) and trunk (STRAT) adipose tissue (AT) have been suggested to be differentially influenced by diet.
  
  
  OBJECTIVE
  We investigated whether and to what extent usual patterns of nutrient intake are associated with VAT, SAAT, and STRAT compared with nondietary predictors in northern German adults (n = 583).
  
  
  METHODS
  AT volumes were quantified by magnetic resonance imaging. Nutrient intake was estimated by a 112-item food-frequency questionnaire linked to the German Food Code and Nutrient Database. Exploratory nutrient patterns were derived by principal components analysis (PCA) and partial least-squares regression (PLS) of 87 nutrients. Cross-sectional associations between nutrient patterns, single nutrients, or total energy intake and AT compartments were analyzed by multiple linear regression.
  
  
  RESULTS
  Next to sex and age, respectively, which were important nondietary predictors and accounted for more of the variation in VAT (∼13% and ∼4%) than in SAAT or STRAT (both 4-7% and <1%), variation in VAT (16.8% or 17.6%) was explained to a greater extent by 9 or 2 nutrient patterns derived by principal components analysis or partial least-squares regression, respectively, than was variation in SAAT (10.6% or 8.2%) or STRAT (11.5% or 8.6%). Whereas VAT (16.6%) was primarily explained by nutrient quality, SAAT (6.9%) and STRAT (7.4%) were mainly explained by total energy intake. VAT was positively associated with nutrients characteristic of animal (except for dairy) products, including arachidonic acid (standardized β: 0.25; 95% CI: 0.15, 0.34; P < 0.0001), but negatively with dietary fiber, including polypentoses (standardized β: -0.17; 95% CI: -0.24, -0.09; P < 0.0001), and nutrients found in milk. The direction and strength of many associations, however, depended strongly on sex and adjustment for BMI.
  
  
  CONCLUSIONS
  VAT may be particularly associated with sex-specific interplays of nutrients found in animal products and fiber, whereas SAAT and STRAT are associated with total energy intake.
authors.affiliation: From the Department of Nutrition and Food Sciences, University of Bonn, Bonn, Germany (KF, DM, and UN); the Institute of Epidemiology, Kiel University, Kiel, Germany (MK and WL); the Department of Neurology, University of Ulm, Ulm, Germany (H-PM and JK); and PopGen Biobank, University Hospital Schleswig-Holstein, Kiel, Germany (GJ).
authors.forename: Karina
authors.initials: K
authors.lastname: Fischer
authors.affiliation: From the Department of Nutrition and Food Sciences, University of Bonn, Bonn, Germany (KF, DM, and UN); the Institute of Epidemiology, Kiel University, Kiel, Germany (MK and WL); the Department of Neurology, University of Ulm, Ulm, Germany (H-PM and JK); and PopGen Biobank, University Hospital Schleswig-Holstein, Kiel, Germany (GJ).
authors.forename: Daniela
authors.initials: D
authors.lastname: Moewes
authors.affiliation: From the Department of Nutrition and Food Sciences, University of Bonn, Bonn, Germany (KF, DM, and UN); the Institute of Epidemiology, Kiel University, Kiel, Germany (MK and WL); the Department of Neurology, University of Ulm, Ulm, Germany (H-PM and JK); and PopGen Biobank, University Hospital Schleswig-Holstein, Kiel, Germany (GJ).
authors.forename: Manja
authors.initials: M
authors.lastname: Koch
authors.affiliation: From the Department of Nutrition and Food Sciences, University of Bonn, Bonn, Germany (KF, DM, and UN); the Institute of Epidemiology, Kiel University, Kiel, Germany (MK and WL); the Department of Neurology, University of Ulm, Ulm, Germany (H-PM and JK); and PopGen Biobank, University Hospital Schleswig-Holstein, Kiel, Germany (GJ).
authors.forename: Hans-Peter
authors.initials: HP
authors.lastname: Müller
authors.affiliation: From the Department of Nutrition and Food Sciences, University of Bonn, Bonn, Germany (KF, DM, and UN); the Institute of Epidemiology, Kiel University, Kiel, Germany (MK and WL); the Department of Neurology, University of Ulm, Ulm, Germany (H-PM and JK); and PopGen Biobank, University Hospital Schleswig-Holstein, Kiel, Germany (GJ).
authors.forename: Gunnar
authors.initials: G
authors.lastname: Jacobs
authors.affiliation: From the Department of Nutrition and Food Sciences, University of Bonn, Bonn, Germany (KF, DM, and UN); the Institute of Epidemiology, Kiel University, Kiel, Germany (MK and WL); the Department of Neurology, University of Ulm, Ulm, Germany (H-PM and JK); and PopGen Biobank, University Hospital Schleswig-Holstein, Kiel, Germany (GJ).
authors.forename: Jan
authors.initials: J
authors.lastname: Kassubek
authors.affiliation: From the Department of Nutrition and Food Sciences, University of Bonn, Bonn, Germany (KF, DM, and UN); the Institute of Epidemiology, Kiel University, Kiel, Germany (MK and WL); the Department of Neurology, University of Ulm, Ulm, Germany (H-PM and JK); and PopGen Biobank, University Hospital Schleswig-Holstein, Kiel, Germany (GJ).
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Lieb
authors.affiliation: From the Department of Nutrition and Food Sciences, University of Bonn, Bonn, Germany (KF, DM, and UN); the Institute of Epidemiology, Kiel University, Kiel, Germany (MK and WL); the Department of Neurology, University of Ulm, Ulm, Germany (H-PM and JK); and PopGen Biobank, University Hospital Schleswig-Holstein, Kiel, Germany (GJ).
authors.forename: Ute
authors.initials: U
authors.lastname: Nöthlings
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D016718:Arachidonic Acid / Q000737:chemistry; D015992:Body Mass Index; D003430:Cross-Sectional Studies; D004032:Diet; D002149:Energy Intake; D005247:Feeding Behavior; D005260:Female; D005858:Germany; D006801:Humans; D016014:Linear Models; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D015596:Nutrition Assessment; D025341:Principal Component Analysis; D011859:Radiography; D012737:Sex Factors; D050507:Subcutaneous Fat, Abdominal / Q000000981:diagnostic imaging*; D011795:Surveys and Questionnaires; D044465:White People
chemical_list: D016718:Arachidonic Acid
keywords: epidemiology; nutrient patterns; nutrients; obesity; visceral and subcutaneous adipose tissue