Background: The prevalence of nonalcoholic fatty liver disease (NAFLD) is high among subjects with type 2 diabetes (T2D). However, the prevalence and outcomes of NAFLD among individuals with pre-diabetes (PreD) and metabolically healthy and metabolically unhealthy individuals without T2D are not known. Our aim was to assess prevalence and mortality of NAFLD among these four groups.
Methods: The Third National Health and Nutrition Examination Survey (NHANES) III (1988-1994) with mortality data (follow up to 2019) via linkage to the National Death Index was utilized. NAFLD was defined by ultrasound and absence of other liver diseases and excess alcohol use. Pre-D was defined as fasting plasma glucose values of 100-125 mg/dL and/or HbA1c level between 5.7 %-6.4 % in the absence of established diagnosis of T2D. Metabolically healthy (MH) was defined if all of the following criteria were absent: waist circumference of ≥102 cm (men) or ≥ 88 cm (women) or BMI of ≥30; blood pressure (BP) ≥ 130/85 mmHg or using BP-lowering medication; triglyceride level ≥ 150 mg/dL or using lipid-lowering medication; lipoprotein cholesterol level of <40 mg/dL (men) or < 50 mg/dL (women); homeostasis model assessment of insulin resistance (HOMA-IR) score ≥ 2.5; C-reactive protein (CRP) level of >2 mg/L; Pre-D and T2D. Metabolically unhealthy (MU) individuals were defined as the presence of any component of metabolic syndrome but not having Pre-D and T2D. Competing risk analyses of cause-specific mortality were performed.
Findings: 11,231 adults (20-74y) were included: mean age 43.4 years; 43.9 % male; 75.4 % white, 10.8 % Black, and 5.4 % Mexican American, 18.9 % NAFLD, 7.8 % T2D; 24.7 % PreD; 44.3 % MU; and 23.3 % in MH individuals. In multivariable adjusted logistic model, as compared to MH individuals, the highest risk of having NAFLD were in T2D individuals (Odd Ratio [OR] = 10.88 [95 % confidence interval: 7.33-16.16]), followed by Pre-D (OR = 4.19 [3.02-5.81]), and MU (OR = 3.36 [2.39-4.71]). During a median follow up of 26.7 years (21.2-28.7 years), 3982 died. NAFLD subjects had significantly higher age-adjusted mortality than non-NAFLD (32.7 % vs. 28.7 %, p < .001). Among subjects with NAFLD, the highest age-standardized cumulative mortality was observed among those with T2D (41.3 %), followed by with Pre-D (35.1 %), MU subjects (30.0 %), and MH subjects (21.9 %) (pairwise p-values<.04 vs. MH). Multivariable adjusted cox models showed that NAFLD with T2D had a higher risk of all-causes and cardiac-specific deaths (Hazard Ratio [HR] = 4.71 [2.23-9.96] and HR = 20.01 [3.00-133.61]), followed by NAFLD with Pre-D (HR = 2.91 [1.41-6.02] and HR = 10.35 [1.57-68.08]) and metabolically unhealthy NAFLD (HR = 2.59 [1.26-5.33] and HR = 6.74 [0.99-46.03]) compared to metabolically healthy NAFLD. In addition to older age, independent predictors of mortality among NAFLD with T2D included high CRP, CVD, CKD, high FIB-4, and active smoking. Similarly, among NAFLD with PreD, high CRP, CKD, CVD, hypertension, and active smoking were associated with mortality. Finally, CVD and active smoking were predictors of mortality among metabolically unhealthy NAFLD, and active smoking was the only mortality risk among metabolically healthy NAFLD subjects.
Interpretation: Metabolic abnormality impacts both prevalence and outcomes of subjects with NAFLD.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.metabol.2023.155642 | DOI Listing |
Inflamm Res
January 2025
Laboratório de Virologia Básica E Aplicada, Departamento de Microbiologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais-UFMG, Belo Horizonte, MG, Brazil.
Introduction: The present study aimed at evaluating the systemic profile and network connectivity of immune mediators during acute chikungunya fever (CHIKF) according to days of symptoms onset and ageing.
Methods: A total of 161 volunteers (76 CHIKF patients and 85 non-infected healthy controls) were enrolled.
Results And Discussion: Data demonstrated that a massive and polyfunctional storm of serum immune mediators was observed in CHIKF.
Inflamm Res
January 2025
Department of Otolaryngology, Peking University Third Hospital, Haidian District, No. 49 Huayuan North Road, Beijing, 100191, People's Republic of China.
Background: Dysbiosis of the nasal microbiome is considered to be related to the acute exacerbation of chronic rhinosinusitis (AECRS). The microbiota in the nasal cavity of AECRS patients and its association with disease severity has rarely been studied. This study aimed to characterize nasal dysbiosis in a prospective cohort of patients with AECRS.
View Article and Find Full Text PDFFASEB J
January 2025
Department of Radiology, C.J. Gorter MRI Center, Leiden University Medical Center, Leiden, The Netherlands.
Brown adipose tissue (BAT) is a metabolically highly active tissue that dissipates energy stored within its intracellular triglyceride droplets as heat. Others have previously utilized MRI to show that the fat fraction of human supraclavicular BAT (scBAT) decreases upon cold exposure, compared with baseline (i.e.
View Article and Find Full Text PDFClin Transl Sci
January 2025
NIMML Institute, Blacksburg, Virginia, USA.
NIM-1324 is an oral investigational new drug for autoimmune disease that targets the Lanthionine Synthetase C-like 2 (LANCL2) pathway. Through activation of LANCL2, NIM-1324 modulates CD4+ T cells to bias signaling and cellular metabolism toward increased immunoregulatory function while providing similar support to phagocytes. In primary human immune cells, NIM-1324 reduces type I interferon and inflammatory cytokine (IL-6, IL-8) production.
View Article and Find Full Text PDFClin Transl Sci
January 2025
Clinical Pharmacology, Translational Medicine and Clinical Pharmacology, Boehringer-Ingelheim Pharma, Ingelheim, Germany.
Hepatic impairment (HI) trials are traditionally part of the clinical pharmacology development to assess the need for dose adaptation in people with impaired metabolic capacity due to their diseased liver. This review aimed at looking into the data from dedicated HI studies, cluster these data into various categories and connect the effect by HI with reported pharmacokinetics (PK) properties in order to identify patterns that may allow waiver, extrapolations, or adapted HI study designs. Based on a ratio ≥ 2 or ≤ 0.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!