Dataset Information

Association between fast eating speed and metabolic dysfunction-associated steatotic liver disease: a multicenter cross-sectional study and meta-analysis.

ABSTRACT:

Background

With the fast pace of modern life, people have less time for meals, but few studies have examined the association between the habit of fast eating and metabolic diseases.

Objective

Combining the results of the current study and the prior ones, we aimed to investigate the possible relationship between fast eating and the risk of metabolic dysfunction-associated steatotic liver disease (MASLD).

Methods

This is a sub-analysis of a multicenter cross-sectional study of 1965 participants investigated the association between fast eating and MASLD in Chinese. Fast eating was defined as meal time less than five minutes and participants were divided into three categories based on their self-reported frequency of fast eating: ≤1 time/month, ≤1 time/week and ≥2 times/week. We further conducted a literature search for available studies published before November, 2023 as well as a meta-analysis to investigate the association between fast eating and MASLD.

Results

The proportion of MASLD was 59.3%, 50.5%, and 46.2% in participants with fast eating ≥2 times/week, ≤1 time/week and ≤1 time/month, respectively (P for trend <0.001). The frequency of fast eating was independently associated with risk of MASLD after multiple adjustment for sex, age, demographics, smoking and drinking status, BMI and clinical metabolic parameters (OR, 1.29; 95%CI, 1.09-1.53). Participants who ate fast frequently (≥2 times/week) had 81% higher risk of MASLD (P = 0.011). A meta-analysis of five eligible studies confirmed that frequent fast eating was associated with increased risk of MASLD (pooled OR, 1.22; 95%CI, 1.07-1.39).

Conclusions

Frequent fast eating was associated with an increased risk of MASLD.

SUBMITTER: Zhang M

PROVIDER: S-EPMC11324733 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Association between fast eating speed and metabolic dysfunction-associated steatotic liver disease: a multicenter cross-sectional study and meta-analysis.

Zhang Miao M Sun Xiaoyang X Zhu Xiaopeng X Zheng Lili L Bi Yufang Y Li Qiang Q Sun Lirong L Di Fusheng F Xu Yushan Y Zhu Dalong D Gao Yanyan Y Bao Yuqian Y Wang Yao Y He Lanjie L Fan Chenmin C Gao Xin X Gao Jian J Xia Mingfeng M Bian Hua H

Nutrition & diabetes 20240814 1

<h4>Background</h4>With the fast pace of modern life, people have less time for meals, but few studies have examined the association between the habit of fast eating and metabolic diseases.<h4>Objective</h4>Combining the results of the current study and the prior ones, we aimed to investigate the possible relationship between fast eating and the risk of metabolic dysfunction-associated steatotic liver disease (MASLD).<h4>Methods</h4>This is a sub-analysis of a multicenter cross-sectional study o ...[more]

PMID: 39143072

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Project description:BackgroundsAdherence to the Planetary Health Diet Index (PHDI) has been shown to benefit both individual health and the planet. However, its impact on Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) remains unclear. This study aimed to investigate the relationship between PHDI adherence and the MASLD risk.MethodsWe analyzed a cohort of 15,865 adults (aged ≥18 years) using data from the National Health and Nutrition Examination Survey (NHANES, 2005-2018). The PHDI was derived from 24-h dietary assessments and comprised the scores of 15 food groups. Multivariate logistic regression was used to investigate the association between PHDI and MASLD, while restricted cubic spline (RCS) regression and threshold analysis were employed to explore potential non-linear relationship. Subgroup analyses were conducted to assess the influence of various demographic and clinical characteristics on the observed associations. Mediation analysis was performed to evaluate the indirect effect of PHDI on MASLD, and weighted quantile sum (WQS) regression was used to assess the influence of individual PHDI nutrients on MASLD.ResultsAmong the cohort, 6,125 individuals were diagnosed with MASLD. Multivariate logistic regression revealed that a higher quintile of PHDI was significantly associated with reduced MASLD risk in the fully adjusted model (OR = 0.610, 95%CI 0.508-0.733, p < 0.001). Notably, nonlinear relationships between PHDI and MASLD risk were observed through RCS analysis (p = 0.002). Subgroup analyses indicated that PHDI was particularly effective in reducing MASLD risk among females, those with higher education attainment, and those living with a partner. WQS regression identified saturated fatty acids as the most significant factor contributing to MASLD risk (weight = 0.313). Additionally, BMI and waist circumference (81.47 and 87.66%, respectively) partially mediated the association between PHDI and MASLD risk, suggesting that the effect of PHDI on MASLD operates, in part, through its impact on BMI and waist circumference. The association between PHDI and MASLD remained robust across multiple sensitivity analyses.ConclusionOur findings indicate that adherence to PHDI is linked to a lower risk of MASLD, providing crucial insights for strategies aimed at mitigating the MASLD epidemic while simultaneously fostering environmental sustainability.

Project description:ObjectiveNumerous studies emphasize the pivotal role of inflammation in metabolic dysfunction-associated steatotic liver disease (MASLD) development. Some link specific systemic immune biomarkers (e.g., systemic immuno-inflammatory index [SII], neutrophil-to-albumin ratio [NPAR] and neutrophil-to-lymphocyte ratio [NLR]) to hepatic steatosis risk. However, the relevance of other markers like systemic immune-inflammation index [SIRI], platelet-to-lymphocyte ratio [PLR] and lymphocyte/monocyte ratio [LMR] in MASLD remains unclear. Limited literature covers all six markers together. This study aims to investigate the association between SII, SIRI, LMR, NLR, PLR, and NPAR and MASLD, assessing their predictive value.MethodsIn this cross-sectional analysis of adults from NHANES (2007-2018), we investigated the relationship between six systemic immune biomarkers, stratified by quartiles: quartile1 (Q1), quartile2 (Q2), quartile3 (Q3) and quartile4 (Q4), and the outcome of MASLD assessed by Fatty Liver Index (FLI) and United States Fatty Liver Index (USFLI). Logistic regression and restricted cubic splines (RCS) were employed to assess the association between systemic immune biomarkers and MASLD risks. Propensity score matching controlled for potential confounders, and receiver operating characteristic (ROC) curve analysis evaluated the biomarkers' predictive performances for MASLD. Subgroup and interaction analysis were conducted to explore the effects of systemic immune biomarkers on MASLD risks. Multicollinearity was quantified using the variance inflation factor.ResultsIn total, 14,413 participants were included and 6,518 had MASLD. Compared with non-MASLD, participants with MASLD had higher SII, SIRI, NLR, PLR, and NPAR (p < 0.001). SII, SIRI, NLR, and NPAR were further validated in the restricted cubic splines (RCS) regression model and identified as positive linear relationships (p for nonlinear >0.05). The prevalence of MASLD increased with the Q4 of SII [OR = 1.47, 95%CI (1.24, 1.74)], SIRI [OR = 1.30, 95%CI (1.09, 1.54)], NLR [OR = 1.25, 95%CI (1.04, 1.49)], PLR [OR = 1.29, 95%CI (1.09, 1.53)] and NPAR [OR = 1.29, 95%CI (1.09, 1.54)] compared to the Q1 after adjusting for the bias caused by potential confounders. However, the propensity score matching analysis only supported an association between the highest SII, SIRI, NLR NPAR and the risk of MASLD. The results of the subgroup analysis showed considerable robustness in the relationship.ConclusionHigher SII, SIRI, NLR and NPAR were positively associated with a heightened risk of MASLD. NPAR showed the superior predictive value, followed by SII, SIRI and NLR. This needs to be validated in additional longitudinal studies and clinical trials.

Project description:ImportanceIn the US, hepatocellular carcinoma (HCC) has been the most rapidly increasing cancer since 1980, and metabolic dysfunction-associated steatotic liver disease (MASLD) is expected to soon become the leading cause of HCC.ObjectiveTo develop a prediction model for HCC incidence in a cohort of patients with MASLD.Design, setting, and participantsThis prognostic study was conducted among patients aged at least 18 years with MASLD, identified using diagnosis of MASLD using International Classification of Diseases, Ninth Revision (ICD-9) or International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) diagnosis codes; natural language processing of radiology imaging report text, which identified patients who had imaging evidence of MASLD but had not been formally diagnosed; or the Dallas Steatosis Index, a risk equation that identifies individuals likely to have MASLD with good precision. Patients were enrolled from Kaiser Permanente Northern California, an integrated health delivery system with more than 4.6 million members, with study entry between January 2009 and December 2018, and follow-up until HCC development, death, or study termination on September 30, 2021. Statistical analysis was performed during February 2023 and January 2024.ExposureData were extracted from the electronic health record and included 18 routinely measured factors associated with MASLD.Main outcome and measuresThe cohort was split (70:30) into derivation and internal validation sets; extreme gradient boosting was used to model HCC incidence. HCC risk was divided into 3 categories, with the cumulative estimated probability of HCC 0.05% or less classified as low risk; 0.05% to 0.09%, medium risk; and 0.1% or greater, high risk.ResultsA total of 1 811 461 patients (median age [IQR] at baseline, 52 [41-63] years; 982 300 [54.2%] female) participated in the study. During a median (range) follow-up of 9.3 (5.8-12.4) years, 946 patients developed HCC, for an incidence rate of 0.065 per 1000 person-years. The model achieved an area under the curve of 0.899 (95% CI, 0.882-0.916) in the validation set. At the medium-risk threshold, the model had a sensitivity of 87.5%, specificity of 81.4%, and a number needed to screen of 406. At the high-risk threshold, the model had a sensitivity of 78.4%, a specificity of 90.1%, and a number needed to screen of 241.Conclusions and relevanceThis prognostic study of more than 1.8 million patients with MASLD used electronic health record data to develop a prediction model to discriminate between individuals with and without incident HCC with good precision. This model could serve as a starting point to identify patients with MASLD who may need intervention and/or HCC surveillance.

Dataset Information

Association between fast eating speed and metabolic dysfunction-associated steatotic liver disease: a multicenter cross-sectional study and meta-analysis.

Background

Objective

Methods

Results

Conclusions

Publications

Association between fast eating speed and metabolic dysfunction-associated steatotic liver disease: a multicenter cross-sectional study and meta-analysis.

Similar Datasets

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