Associations between three diet quality indices, genetic risk and body composition: A prospective cohort study.

Absorptiometry, Photon Adult Body Composition Body Mass Index Bone Density / genetics Cohort Studies Diet, Mediterranean Humans Obesity Prospective Studies Risk Factors
Body composition Bone mineral content Diet quality Fat mass Lean mass Polygenic risk score

Journal

Clinical nutrition (Edinburgh, Scotland)
ISSN: 1532-1983
Titre abrégé: Clin Nutr
Pays: England
ID NLM: 8309603

Informations de publication

Date de publication:
09 2022
Historique:
received: 27 02 2022
revised: 03 06 2022
accepted: 07 07 2022
pubmed: 11 8 2022
medline: 9 9 2022
entrez: 10 8 2022
Statut: ppublish

Résumé

Diet and genetic predisposition to adiposity are independent predictors of body composition, yet few cohort studies have examined the association between overall diet quality indices, genetic risk and body composition. This study examined the prospective association of three diet quality indices and a polygenic risk score (PRS) with trunk fat mass, total fat mass, lean mass and bone mineral content. Adults from UK Biobank cohort were included. Dietary intake was assessed using the Oxford WebQ and three diet quality indices calculated: Recommended Food Score (RFS); Mediterranean Diet Score (MDS); Healthy Diet Indicator (HDI). Bioimpedance data were available for trunk fat, total fat and lean mass (kg). Trunk fat mass (kg), total fat mass (kg) and lean mass (kg) were assessed using bioelectrical impedance (BIA) in 17,478 adults. Bone mineral content (g) was available from dual energy x-ray absorptiometry (DXA) scans in 11,887 participants. Linear regression analyses, adjusted for demographic and lifestyle confounders, were used to estimate prospective associations between each diet quality index and body composition outcomes. A PRS created from 97 adiposity-related single nucleotide polymorphisms was used to examine interaction effects. A total of 17,478 adults (M = 55.9, SD 7.5 years) were followed up for up to 10 years. RFS, HDI and MDS were inversely associated with trunk fat (RFS: B -0.29; 95% CI: -0.33, -0.25; HDI: -0.23; -0.27, -0.19; MDS: -0.22; -0.26, -0.18), total fat (RFS: B -0.49; 95% CI: -0.56, -0.42; HDI: -0.38; -0.45, -0.32; MDS: -0.38; -0.44, -0.32) and lean (RFS: B -0.10; 95% CI: -0.14, -0.06; HDI: -0.07; -0.11, -0.03; MDS: -0.07; -0.11, -0.04) mass. Diet quality was positively associated with bone mineral content (RFS: B 8.23; 95% CI: 2.14, 14.3; HDI: 6.77; 1.00, 12.5). There was evidence of non-linear associations between diet quality (RFS and HDI only) and trunk fat (p < 0.01) and total fat mass (p < 0.05). There was limited evidence PRS was associated with body composition, with interaction effects of PRS and HDI (p-interaction = 0.039) and MDS (p-interaction = 0.031) on total fat mass. Higher diet quality was associated with lower trunk fat, total fat and lean mass, regardless of the diet quality index examined (RFS, HDI or MDS), while higher diet quality (RFS and HDI only) was associated with higher bone mineral content. The benefit of higher diet quality on reducing total fat mass was most evident in individuals with higher generic risk of adiposity. These findings underscore the importance of a high-quality diet for maintaining optimal body composition, particularly in individuals with genetic pre-disposition to adiposity.

Sections du résumé

BACKGROUND & AIMS
Diet and genetic predisposition to adiposity are independent predictors of body composition, yet few cohort studies have examined the association between overall diet quality indices, genetic risk and body composition. This study examined the prospective association of three diet quality indices and a polygenic risk score (PRS) with trunk fat mass, total fat mass, lean mass and bone mineral content.
METHODS
Adults from UK Biobank cohort were included. Dietary intake was assessed using the Oxford WebQ and three diet quality indices calculated: Recommended Food Score (RFS); Mediterranean Diet Score (MDS); Healthy Diet Indicator (HDI). Bioimpedance data were available for trunk fat, total fat and lean mass (kg). Trunk fat mass (kg), total fat mass (kg) and lean mass (kg) were assessed using bioelectrical impedance (BIA) in 17,478 adults. Bone mineral content (g) was available from dual energy x-ray absorptiometry (DXA) scans in 11,887 participants. Linear regression analyses, adjusted for demographic and lifestyle confounders, were used to estimate prospective associations between each diet quality index and body composition outcomes. A PRS created from 97 adiposity-related single nucleotide polymorphisms was used to examine interaction effects.
RESULTS
A total of 17,478 adults (M = 55.9, SD 7.5 years) were followed up for up to 10 years. RFS, HDI and MDS were inversely associated with trunk fat (RFS: B -0.29; 95% CI: -0.33, -0.25; HDI: -0.23; -0.27, -0.19; MDS: -0.22; -0.26, -0.18), total fat (RFS: B -0.49; 95% CI: -0.56, -0.42; HDI: -0.38; -0.45, -0.32; MDS: -0.38; -0.44, -0.32) and lean (RFS: B -0.10; 95% CI: -0.14, -0.06; HDI: -0.07; -0.11, -0.03; MDS: -0.07; -0.11, -0.04) mass. Diet quality was positively associated with bone mineral content (RFS: B 8.23; 95% CI: 2.14, 14.3; HDI: 6.77; 1.00, 12.5). There was evidence of non-linear associations between diet quality (RFS and HDI only) and trunk fat (p < 0.01) and total fat mass (p < 0.05). There was limited evidence PRS was associated with body composition, with interaction effects of PRS and HDI (p-interaction = 0.039) and MDS (p-interaction = 0.031) on total fat mass.
CONCLUSION
Higher diet quality was associated with lower trunk fat, total fat and lean mass, regardless of the diet quality index examined (RFS, HDI or MDS), while higher diet quality (RFS and HDI only) was associated with higher bone mineral content. The benefit of higher diet quality on reducing total fat mass was most evident in individuals with higher generic risk of adiposity. These findings underscore the importance of a high-quality diet for maintaining optimal body composition, particularly in individuals with genetic pre-disposition to adiposity.

Identifiants

DOI: 10.1016/j.clnu.2022.07.005 PMID: 35947896
pubmed: 35947896
pii: S0261-5614(22)00241-2
doi: 10.1016/j.clnu.2022.07.005
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1942-1949

Informations de copyright

Copyright © 2022 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Déclaration de conflit d'intérêts

Conflicts of Interest None.

Auteurs

Katherine M Livingstone (KM)

Deakin University, Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Geelong, VIC 3220, Australia. Electronic address: k.livingstone@deakin.edu.au.

Catherine Milte (C)

Deakin University, Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Geelong, VIC 3220, Australia. Electronic address: catherine.milte@deakin.edu.au.

Steven J Bowe (SJ)

Deakin University, Deakin Biostatistics Unit, Geelong, VIC 3220, Australia. Electronic address: s.bowe@deakin.edu.au.

Rachel L Duckham (RL)

Deakin University, Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Geelong, VIC 3220, Australia; Australian Institute for Musculoskeletal Science (AIMSS), The University of Melbourne and Western Health, St Albans, Victoria, Australia. Electronic address: r.duckham@deakin.edu.au.

Joey Ward (J)

University of Glasgow, Institute of Health and Wellbeing, Glasgow, UK. Electronic address: Joey.Ward@glasgow.ac.uk.

Michelle A Keske (MA)

Deakin University, Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Geelong, VIC 3220, Australia. Electronic address: michelle.keske@deakin.edu.au.

Mark McEvoy (M)

The University of Newcastle, Centre for Clinical Epidemiology & Biostatistics, Hunter Medical Research Institute, School of Medicine and Public Health, Australia; La Trobe Rural Health School, College of Science, Health and Engineering, La Trobe University, VIC, Australia. Electronic address: mark.mcevoy@newcastle.edu.au.

Barbara Brayner (B)

Deakin University, Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Geelong, VIC 3220, Australia. Electronic address: bvitorinoalenca@deakin.edu.au.

Gavin Abbott (G)

Deakin University, Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Geelong, VIC 3220, Australia. Electronic address: gavin.abbott@deakin.edu.au.

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Classifications MeSH

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