Low-Carbohydrate and Low-Fat Diet with Metabolic-Dysfunction-Associated Fatty Liver Disease.

low-carbohydrate diet low-fat diet metabolic-dysfunction-associated fatty liver disease quality of macronutrients severe fibrosis

Journal

Nutrients
ISSN: 2072-6643
Titre abrégé: Nutrients
Pays: Switzerland
ID NLM: 101521595

Informations de publication

Date de publication:
13 Nov 2023
Historique:
received: 13 10 2023
revised: 08 11 2023
accepted: 11 11 2023
medline: 27 11 2023
pubmed: 25 11 2023
entrez: 25 11 2023
Statut: epublish

Résumé

This observational cross-sectional study was designed to explore the effects of a low-carbohydrate diet (LCD) and a low-fat diet (LFD) on metabolic-dysfunction-associated fatty liver disease (MAFLD). This study involved 3961 adults. The associations between LCD/LFD scores and MAFLD were evaluated utilizing a multivariable logistic regression model. Additionally, a leave-one-out model was applied to assess the effect of isocaloric substitution of specific macronutrients. Participants within the highest tertile of healthy LCD scores (0.63; 95% confidence interval [CI], 0.45-0.89) or with a healthy LFD score (0.64; 95%CI, 0.48-0.86) faced a lower MAFLD risk. Furthermore, compared with tertile 1, individuals with unhealthy LFD scores in terile 2 or tertile 3 had 49% (95%CI, 1.17-1.90) and 77% (95%CI, 1.19-2.63) higher risk levels for MAFLD, respectively. Healthy LCD and healthy LFD are protective against MAFLD, while unhealthy LFD can increase the risk of MAFLD. Both the quantity and quality of macronutrients might have significant influences on MAFLD.

Sections du résumé

BACKGROUND BACKGROUND
This observational cross-sectional study was designed to explore the effects of a low-carbohydrate diet (LCD) and a low-fat diet (LFD) on metabolic-dysfunction-associated fatty liver disease (MAFLD).
METHODS METHODS
This study involved 3961 adults. The associations between LCD/LFD scores and MAFLD were evaluated utilizing a multivariable logistic regression model. Additionally, a leave-one-out model was applied to assess the effect of isocaloric substitution of specific macronutrients.
RESULTS RESULTS
Participants within the highest tertile of healthy LCD scores (0.63; 95% confidence interval [CI], 0.45-0.89) or with a healthy LFD score (0.64; 95%CI, 0.48-0.86) faced a lower MAFLD risk. Furthermore, compared with tertile 1, individuals with unhealthy LFD scores in terile 2 or tertile 3 had 49% (95%CI, 1.17-1.90) and 77% (95%CI, 1.19-2.63) higher risk levels for MAFLD, respectively.
CONCLUSIONS CONCLUSIONS
Healthy LCD and healthy LFD are protective against MAFLD, while unhealthy LFD can increase the risk of MAFLD. Both the quantity and quality of macronutrients might have significant influences on MAFLD.

Identifiants

pubmed: 38004162
pii: nu15224763
doi: 10.3390/nu15224763
pmc: PMC10674227
pii:
doi:

Substances chimiques

Carbohydrates 0

Types de publication

Observational Study Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Department of Education of Jilin Province
ID : JJKH20231145KJ

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Auteurs

Chengxiang Hu (C)

Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun 130021, China.

Rong Huang (R)

Department of Biostatistics and Epidemiology, School of Public Health, China Medical University, Shenyang 110122, China.

Runhong Li (R)

Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun 130021, China.

Ning Ning (N)

Department of Biostatistics and Epidemiology, School of Public Health, China Medical University, Shenyang 110122, China.

Yue He (Y)

Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun 130021, China.

Jiaqi Zhang (J)

Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun 130021, China.

Yingxin Wang (Y)

Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun 130021, China.

Yanan Ma (Y)

Department of Biostatistics and Epidemiology, School of Public Health, China Medical University, Shenyang 110122, China.

Lina Jin (L)

Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun 130021, China.

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