Impact of baseline adipose tissue characteristics on change in adipose tissue volume during a low calorie diet in people with obesity-results from the LION study.


Journal

International journal of obesity (2005)
ISSN: 1476-5497
Titre abrégé: Int J Obes (Lond)
Pays: England
ID NLM: 101256108

Informations de publication

Date de publication:
26 Jun 2024
Historique:
received: 12 01 2024
accepted: 12 06 2024
revised: 04 06 2024
medline: 27 6 2024
pubmed: 27 6 2024
entrez: 26 6 2024
Statut: aheadofprint

Résumé

Weight loss outcomes vary individually. Magnetic resonance imaging (MRI)-based evaluation of adipose tissue (AT) might help to identify AT characteristics that predict AT loss. This study aimed to assess the impact of an 8-week low-calorie diet (LCD) on different AT depots and to identify predictors of short-term AT loss using MRI in adults with obesity. Eighty-one adults with obesity (mean BMI 34.08 ± 2.75 kg/m², mean age 46.3 ± 10.97 years, 49 females) prospectively underwent baseline MRI (liver dome to femoral head) and anthropometric measurements (BMI, waist-to-hip-ratio, body fat), followed by a post-LCD-examination. Visceral and subcutaneous AT (VAT and SAT) volumes and AT fat fraction were extracted from the MRI data. Apparent lipid volumes based on MRI were calculated as approximation for the lipid contained in the AT. SAT and VAT volumes were subdivided into equidistant thirds along the craniocaudal axis and normalized by length of the segmentation. T-tests compared baseline and follow-up measurements and sex differences. Effect sizes on subdivided AT volumes were compared. Spearman Rank correlation explored associations between baseline parameters and AT loss. Multiple regression analysis identified baseline predictors for AT loss. Following the LCD, participants exhibited significant weight loss (11.61 ± 3.07 kg, p < 0.01) and reductions in all MRI-based AT parameters (p < 0.01). Absolute SAT loss exceeded VAT loss, while relative apparent lipid loss was higher in VAT (both p < 0.01). The lower abdominopelvic third showed the most significant SAT and VAT reduction. The predictor of most AT and apparent lipid losses was the normalized baseline SAT volume in the lower abdominopelvic third, with smaller volumes favoring greater AT loss (p < 0.01 for SAT and VAT loss and SAT apparent lipid volume loss). The LCD primarily reduces lower abdominopelvic SAT and VAT. Furthermore, lower abdominopelvic SAT volume was detected as a potential predictor for short-term AT loss in persons with obesity.

Sections du résumé

BACKGROUND/OBJECTIVES OBJECTIVE
Weight loss outcomes vary individually. Magnetic resonance imaging (MRI)-based evaluation of adipose tissue (AT) might help to identify AT characteristics that predict AT loss. This study aimed to assess the impact of an 8-week low-calorie diet (LCD) on different AT depots and to identify predictors of short-term AT loss using MRI in adults with obesity.
METHODS METHODS
Eighty-one adults with obesity (mean BMI 34.08 ± 2.75 kg/m², mean age 46.3 ± 10.97 years, 49 females) prospectively underwent baseline MRI (liver dome to femoral head) and anthropometric measurements (BMI, waist-to-hip-ratio, body fat), followed by a post-LCD-examination. Visceral and subcutaneous AT (VAT and SAT) volumes and AT fat fraction were extracted from the MRI data. Apparent lipid volumes based on MRI were calculated as approximation for the lipid contained in the AT. SAT and VAT volumes were subdivided into equidistant thirds along the craniocaudal axis and normalized by length of the segmentation. T-tests compared baseline and follow-up measurements and sex differences. Effect sizes on subdivided AT volumes were compared. Spearman Rank correlation explored associations between baseline parameters and AT loss. Multiple regression analysis identified baseline predictors for AT loss.
RESULTS RESULTS
Following the LCD, participants exhibited significant weight loss (11.61 ± 3.07 kg, p < 0.01) and reductions in all MRI-based AT parameters (p < 0.01). Absolute SAT loss exceeded VAT loss, while relative apparent lipid loss was higher in VAT (both p < 0.01). The lower abdominopelvic third showed the most significant SAT and VAT reduction. The predictor of most AT and apparent lipid losses was the normalized baseline SAT volume in the lower abdominopelvic third, with smaller volumes favoring greater AT loss (p < 0.01 for SAT and VAT loss and SAT apparent lipid volume loss).
CONCLUSIONS CONCLUSIONS
The LCD primarily reduces lower abdominopelvic SAT and VAT. Furthermore, lower abdominopelvic SAT volume was detected as a potential predictor for short-term AT loss in persons with obesity.

Identifiants

pubmed: 38926461
doi: 10.1038/s41366-024-01568-6
pii: 10.1038/s41366-024-01568-6
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024. The Author(s).

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Auteurs

Daniela Junker (D)

Institute of Diagnostic and Interventional Radiology, School of Medicine and Health, Technical University of Munich, Munich, Germany. daniela.junker@tum.de.

Mingming Wu (M)

Institute of Diagnostic and Interventional Radiology, School of Medicine and Health, Technical University of Munich, Munich, Germany.

Anna Reik (A)

Institute for Nutritional Medicine, School of Medicine and Health, Technical University of Munich, Munich, Germany.

Johannes Raspe (J)

Institute of Diagnostic and Interventional Radiology, School of Medicine and Health, Technical University of Munich, Munich, Germany.

Selina Rupp (S)

Institute of Diagnostic and Interventional Radiology, School of Medicine and Health, Technical University of Munich, Munich, Germany.

Jessie Han (J)

Institute of Diagnostic and Interventional Radiology, School of Medicine and Health, Technical University of Munich, Munich, Germany.

Stella M Näbauer (SM)

Institute of Diagnostic and Interventional Radiology, School of Medicine and Health, Technical University of Munich, Munich, Germany.

Meike Wiechert (M)

Institute for Nutritional Medicine, School of Medicine and Health, Technical University of Munich, Munich, Germany.

Arun Somasundaram (A)

Institute of Diagnostic and Interventional Radiology, School of Medicine and Health, Technical University of Munich, Munich, Germany.

Egon Burian (E)

Institute of Diagnostic and Interventional Radiology, School of Medicine and Health, Technical University of Munich, Munich, Germany.
Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany.

Birgit Waschulzik (B)

Institute of AI and Informatics in Medicine, School of Medicine and Health, Technical University of Munich, Munich, Germany.

Marcus R Makowski (MR)

Institute of Diagnostic and Interventional Radiology, School of Medicine and Health, Technical University of Munich, Munich, Germany.

Hans Hauner (H)

Institute for Nutritional Medicine, School of Medicine and Health, Technical University of Munich, Munich, Germany.
Else Kroener-Fresenius-Center of Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany.

Christina Holzapfel (C)

Institute for Nutritional Medicine, School of Medicine and Health, Technical University of Munich, Munich, Germany.
Department of Nutritional, Food and Consumer Sciences, Fulda University of Applied Sciences, Fulda, Germany.

Dimitrios C Karampinos (DC)

Institute of Diagnostic and Interventional Radiology, School of Medicine and Health, Technical University of Munich, Munich, Germany.
Munich Institute of Biomedical Engineering, Technical University of Munich, Garching, Germany.
Munich Data Science Institute, Technical University of Munich, Garching, Germany.

Classifications MeSH