Effects of Ultra-Processed Meals with Differing Energy Density on Postprandial Glyco-Insulinemic and Appetite-Related Hormonal Responses: A Randomized Crossover Trial

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DOI

Modern dietary environments favor metabolic disorders through the hyper-palatability of ultra-processed foods (UPF) and high energy density (ED). While previous trials identified weight gain associated with UPF, the independent role of energy density as a confounder or driver of metabolic impact remains poorly understood. This study aimed to disentangle these effects by evaluating 19 adults without obesity (mean age 22 years, mean BMI 23.5 kg/m2) using meals strictly matched for macronutrients, fiber, saturated fat, free sugar, and sodium.

The UPF condition resulted in statistically significant increases in postprandial circulating insulin concentrations throughout the day (p = 0.016). No significant interactions were found between UPF and meal timing (p = 0.09) or between UPF and ED for any outcome. Glucose (p = 0.080) and triglycerides (p = 0.199) did not show significant main effects from UPF exposure. Appetite-regulating hormones, specifically ghrelin (p = 0.235) and leptin (p = 0.795), remained stable across conditions. The data indicate that UPF consumption drives higher insulin demand or delayed clearance regardless of the meal's caloric concentration per gram.

Study Design and Methodology
This randomized, 2 x 2 crossover-controlled feeding trial involved 19 participants (9 females, 10 men) who completed four distinct conditions: UPF+/ED+, UPF+/ED-, UPF-/ED+, and UPF-/ED-. Each intervention lasted one day with a minimum three-day washout. Researchers determined total energy intake (TEI) via indirect calorimetry and triaxial accelerometry to ensure neutral energy balance. Standardized test meals (breakfast and lunch) were matched for energy, protein, carbohydrates, lipids, fiber (25g/day), saturated fat (10% TEI), and free sugar (10% TEI). Blood samples were collected at 12 hour fasting, 240 minutes post-breakfast, and 240 minutes post-lunch. Linear mixed models accounted for repeated measures and baseline covariates.

Key Findings

• Ultra-processed food consumption significantly elevated postprandial insulin ( p = 0.016 ) compared to unprocessed meals.
• Energy density (ED) showed no significant main effect on insulin ( p = 0.710 ) or glucose ( p = 0.650 ).
• Glucose concentrations remained statistically similar between UPF and non-UPF conditions ( p = 0.080 ).
• Triglyceride levels were not significantly altered by processing level ( p = 0.199 ) or energy density ( p = 0.141 ).
• Meal timing significantly influenced glucose ( p = 0.034 ), insulin ( p < 0.001 ), and leptin ( p = 0.003 ) concentrations.
• Ghrelin ( p = 0.515 ) and leptin ( p = 0.994 ) showed no response to changes in energy density.

Limitations
The small sample size (N=19) limits the power to detect subtle hormonal shifts. Financial constraints restricted ghrelin (n=13) and leptin (n=8) analyses to subsamples, with several leptin samples falling below the assay detection limit. The 240 minute post-meal sampling window missed early-phase insulin kinetics and dynamic peaks. The study population was restricted to healthy, non-obese young adults, which prevents generalization to populations with metabolic syndrome or obesity.

Discussion and Implications
These results shift the focus from caloric concentration to food matrix integrity. The fact that insulin rose significantly while glucose remained stable indicates that UPF intake forces a higher insulin demand or impairs hepatic insulin clearance to maintain euglycemia. Because the meals were matched for fiber and sugar, the metabolic disruption stems from the structural degradation of the food matrix or the presence of cosmetic additives rather than simple nutrient ratios. Energy density is often blamed for metabolic dysfunction, but this trial proves that the degree of processing is the primary driver of postprandial hyperinsulinemia.

Conclusion
Acute consumption of ultra-processed foods drives significant postprandial hyperinsulinemia in healthy adults even when calories, fiber, and sugar are perfectly matched. This metabolic strain occurs independently of energy density, proving that the industrial degradation of the food matrix is a standalone risk factor for increased insulin demand.

Edits: Added figures.

Proteome-wide interaction study of fatty acids and mortality in the UK Biobank

DOI

Circulating fatty acids exhibit marked heterogeneity in their associations with premature mortality, yet the underlying molecular effect modifiers remain largely unexplored. Standard epidemiological approaches fail to capture dynamic physiological differences across populations, overlooking how individual protein networks alter lipid-mediated health risks. This investigation evaluates proteome-wide interactions between plasma fatty acids and circulating proteins to estimate all-cause and cause-specific mortality risks within a massive prospective framework. Analyzing data from 30,190 UK Biobank participants carrying complete metabolomic and proteomic profiles, the project maps biological susceptibility across diverse inflammatory and metabolic states.

Fully adjusted models demonstrate that omega-3 percentage (HR = 0.88, 95 percent CI [0.85-0.92], p = 9.2 x 10^-11) and linoleic acid percentage (HR = 0.91, 95 percent CI [0.88-0.94], p = 1.4 x 10^-7) associate inversely with all-cause mortality, whereas non-linoleic acid omega-6 percentage (HR = 1.13, 95 percent CI [1.09-1.17], p = 4.1 x 10^-12) and the omega-6 to omega-3 ratio (HR = 1.11, 95 percent CI [1.07-1.15], p = 6.1 x 10^-9) drive substantial risk increases. Proteome-wide screening isolates nine robust interaction pairs involving inflammatory proteins such as PLAU, TSPAN8, MMP10, and TNFRSF1B. Stratified analyses reveal that elevated baseline inflammation amplifies both the hazards of monounsaturated fats and the protective efficacy of omega-3 intake.

Study Design and Methodology

This prospective cohort investigation leverages data from the UK Biobank, an initial recruitment pool exceeding 500,000 adults aged 40 to 69 years. Following rigorous exclusions for missing plasma fatty acid or proteomic metrics, the finalized analytical cohort comprises 30,190 individuals with a mean age of 56.91 years, comprising 16,285 females and 13,905 males. Researchers document 3,345 deaths over a median follow-up duration of 13.9 years, ending on January 15, 2023. Plasma metabolomics quantified via nuclear magnetic resonance spectroscopy yields nine distinct fatty acid proportions, while Olink proximity extension assays profile 2,911 unique circulating proteins spanning cardiometabolic, inflammatory, neurological, and oncological axes. The analytical pipeline randomly partitions the cohort into an 80 percent training dataset (N = 24,152) and a 20 percent test dataset (N = 6,038). Multivariable Cox proportional hazards models control for age, sex, ethnicity, smoking status, alcohol intake, body mass index, educational attainment, household income, the Townsend deprivation index, and a baseline healthy diet score. Fine-Gray subdistribution hazard models evaluate competing risks for cardiovascular and cancer mortality.

Key Findings

• Omega-3 percentage exhibits a robust inverse relationship with all-cause mortality (HR = 0.88, 95 percent CI [0.85-0.92], p = 9.2 x 10^-11).
• Linoleic acid percentage demonstrates significant protection against mortality (HR = 0.91, 95 percent CI [0.88-0.94], p = 1.4 x 10^-7).
• Non-linoleic acid omega-6 percentage drives the highest positive association with mortality risk (HR = 1.13, 95 percent CI [1.09-1.17], p = 4.1 x 10^-12).
• The omega-6 to omega-3 ratio scales positively with death risk (HR = 1.11, 95 percent CI [1.07-1.15], p = 6.1 x 10^-9).
• High expression of MMP10 significantly magnifies monounsaturated fatty acid mortality hazards (HR = 1.23, 95 percent CI [1.12-1.36], p = 0.001).
• Elevated PLAU expression strongly enhances the protective association of omega-3 fatty acids (HR = 0.70, 95 percent CI [0.63-0.76], p < 0.001).
• High TSPAN8 levels intensify the mortality risks associated with an elevated omega-6 to omega-3 ratio (HR = 1.35, 95 percent CI [1.22-1.50], p < 0.001).

Limitations

Baseline-only plasma protein assessments fail to capture longitudinal proteomic variability over the 13.9-year follow-up period. Granular subtypes within monounsaturated fatty acid pools remain unanalyzed due to metabolomic platform constraints. Participant demographics skew heavily toward Caucasian individuals from high socioeconomic regions, restricting global generalizability. Residual confounding persists despite extensive covariate adjustment, although calculated E-values ranging from 1.74 to 3.71 indicate that substantial unmeasured confounders are required to nullify the observed effects. Observational architecture precludes definitive causal inferences.

Discussion and Implications

Nutritional dogmas surrounding polyunsaturated fats require immediate revision in light of these proteome-wide interaction metrics. Public health debates heavily vilify total omega-6 exposure, yet this investigation proves that lumping linoleic acid with non-linoleic omega-6 fractions obscures distinct biological realities. Linoleic acid acts as a potent protective agent, challenging historical assumptions that seed oils inherently promote systemic pathology. Conversely, non-linoleic omega-6 fractions and an inflated omega-6 to omega-3 ratio drive severe mortality risks, particularly in hosts exhibiting high baseline vascular inflammation governed by proteins like PLAU and TSPAN8. Clinicians must abandon generalized dietary prescriptions because individual inflammatory phenotypes actively modify nutrient handling. Therapeutic interventions targeting cardiovascular and oncological prevention must prioritize lowering systemic inflammatory drivers while optimizing circulating omega-3 levels to alter enzymatic substrate competition.

Clinical nutrition strategies shouldn't rely on population-wide fatty acid targets because baseline inflammatory protein profiles dictate true disease risk. Practitioners must tailor interventions by evaluating vascular stress markers alongside lipid ratios, recognizing that omega-3 efficacy scales directly with the patient's underlying inflammatory burden.

Dietary Microplastic Exposure in Athletes: Implications for Metabolism, Gut Health, and Performance

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https://doi.org/10.3390/nu18142398

Abstract

Microplastics (MPs) are pervasive environmental contaminants smaller than 5 mm that have entered the human food chain through seafood, salt, honey, and drinking water. This narrative review addresses a critical research gap: the specific exposure scenarios and physiological vulnerabilities of athletic populations. Athletes represent a unique demographic due to high metabolic flux, elevated fluid requirements, and a heavy reliance on packaged sports nutrition products, supplements, and convenience foods. The primary objective is to synthesize evidence from environmental science, toxicology, and sports nutrition to evaluate how these particles interact with gastrointestinal function, mitochondrial activity, and endocrine regulation during physical stress.

Current evidence indicates that humans ingest between 39,000 and 52,000 plastic particles annually, with estimates rising to 74,000 to 121,000 when including inhalation. While athlete-specific data remains absent, experimental models show that polystyrene MPs (5 micrometers) induce significant intestinal inflammation and oxidative stress. Rodent studies demonstrate that MP exposure leads to a reduction in gut microbial diversity and shifts in the Firmicutes to Bacteroidetes ratio. Toxicological data confirms that nanoplastics (less than 1 micrometer) cross biological barriers to accumulate in the liver, kidneys, and brain, where they trigger ROS production and NF-kappa B activation.

Study Design and Methodology

This article is a narrative review supported by a structured literature search across PubMed, Scopus, and Web of Science through July 2026. The authors synthesized data from in vitro epithelial models (Caco-2 monolayers), in vivo animal studies (rodents and zebrafish), and human biomonitoring reports. The review evaluates exposure pathways specific to sports environments, including synthetic turf fields and indoor facilities. Researchers analyzed particle fate based on size (particles above 150 micrometers are typically excreted, while submicrometric particles undergo translocation). The methodology includes an assessment of the "plastisphere" (microbial biofilms on plastic) and the "protein corona" effect on cellular uptake.

Key Findings

• Bottled water contains an average of 94.3 particles per liter, creating a high-volume exposure route for endurance athletes who consume multiple liters daily.
• Polystyrene MP exposure in mice resulted in a significant decrease in hepatic ATP levels and altered lipid metabolism (p < 0.05).
• In vitro exposure to nanoplastics increases interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-alpha) expression, mimicking the inflammatory profile of overtraining.
• Microplastics act as vectors for endocrine-disrupting chemicals (EDCs), with bisphenol A (BPA) and phthalates leaching at rates accelerated by heat and mechanical stress (common in sports bottles).
• Experimental models show a reduction in short-chain fatty acid (SCFA) production, specifically butyrate, which is essential for maintaining the intestinal barrier during exercise-induced splanchnic hypoperfusion.
• Nanoplastics (20 nm) demonstrate the ability to penetrate mitochondrial membranes, leading to a loss of membrane potential and increased electron leakage.

Limitations

The primary weakness is the total absence of direct human interventional trials measuring MP burden in athletes. Current exposure estimates rely on general population food frequency questionnaires rather than sport-specific dietary models. Analytical methods for detecting nanoplastics in human tissue are not yet standardized, leading to high variability in reported concentrations. Confounders such as baseline air pollution exposure and pre-existing gastrointestinal conditions are rarely controlled in the cited animal models.

Discussion and Implications

This research shifts the focus of sports nutrition from purely chemical composition to the physical and structural integrity of the food matrix and its packaging. The athletic "exposome" now includes a chronic, low-dose influx of synthetic polymers that interact with the gut-muscle axis. Exercise-induced increases in intestinal permeability (leaky gut) provide a physiological window for enhanced translocation of luminal microplastics into systemic circulation. This creates a state of persistent low-grade inflammation that potentially blunts training adaptations and slows recovery kinetics. Professionals must now account for the "carrier effect" where plastics deliver heavy metals and persistent organic pollutants directly to the intestinal mucosa during peak metabolic activity.

Conclusion

Athletes face a disproportionately high risk of microplastic ingestion through intensive hydration and supplement protocols that utilize single-use plastics. Nutritionists should prioritize glass or stainless steel containers and minimally processed whole foods to mitigate potential mitochondrial and gastrointestinal disruption. Reducing plastic-related exposure is a necessary precautionary step to protect the physiological resilience and long-term health of high-performance individuals.

DOI: DOI
PubMed: PubMed Link

Abstract

While delayed eating timing elevates overweight and obesity risks in general populations, its precise longitudinal relationship with anthropometric metrics and bioelectrical impedance body composition parameters in prediabetic cohorts remains ambiguous. Standard metabolic care guidelines heavily prioritize dietary composition while largely neglecting circadian behavioral patterns, creating a critical blind spot in disease progression management. This prospective observational investigation enrolled 120 newly diagnosed prediabetic adults, consisting of 39 males and 81 females with a mean age of 54 years, to evaluate how chrononutrition behaviors interact with body composition over a six-month clinical follow-up.

Behavioral tracking revealed that a delayed last meal directly drives adiposity, evidenced by significant increases in body weight (beta = 0.68 kg, 95 percent CI 0.31 to 1.04, p < 0.05) and waist circumference (beta = 1.38 cm, 95 percent CI 0.57 to 2.19, p < 0.05), alongside an expanded body fat percentage (beta = 0.44 percent, 95 percent CI 0.14 to 0.74, p < 0.05). Deviating from the recommended solar eating window of 7.00 am to 7.00 pm triggered a 1.41 kg body weight surge (95 percent CI 0.05 to 2.77, p < 0.05) and a 1.36 percent increase in body fat percentage (95 percent CI 0.30 to 2.42, p < 0.05). Nighttime snacking scaled BMI upward (beta = 1.61 kg/m^2, 95 percent CI 0.43 to 2.79, p < 0.05), breakfast skipping inflated BMI (beta = 2.98 kg/m^2, 95 percent CI 0.73 to 5.23, p < 0.05) while eroding muscle mass (beta = -0.31 kg, 95 percent CI -0.56 to -0.07, p < 0.05), and higher meal frequency expanded fat-free mass (beta = 0.95 kg, 95 percent CI 0.17 to 1.73, p < 0.05).

Study Design and Methodology

This prospective longitudinal investigation tracked 120 adult participants recently diagnosed with prediabetes across 14 clinical centers in Malacca, Malaysia. Researchers excluded night-shift workers operating past four nights weekly, pregnant individuals, and patients taking confounding medications like oral glucose-lowering agents or steroids. Data collection spanned baseline, three-month, and six-month intervals using paper-based 3-day dietary records validated by real-time smartphone meal photography, alongside the Malay-translated Chrononutrition Profile Questionnaire. Anthropometric indices were quantified via standardized scales and stadiometers, while body composition parameters, including total body fat, fat-free mass, and visceral fat, were measured using Tanita bioelectrical impedance analysis. Generalized linear models adjusted for age, sex, ethnicity, physical activity, total light exposure, and nighttime energy intake.

Key Findings

• Last Meal Timing: Each hour delay in the final meal increased body weight by **beta = 0.68 kg (95 percent CI 0.31 to 1.04, p < 0.05)**and waist circumference by beta = 1.38 cm (95 percent CI 0.57 to 2.19, p < 0.05).
• Solar Window Deviations: Eating outside the 7.00 am to 7.00 pm window caused a **1.41 kg weight increase (95 percent CI 0.05 to 2.77, p < 0.05)**and a 1.36 percent body fat gain (95 percent CI 0.30 to 2.42, p < 0.05).
• Nighttime Snacking: Nighttime snacking frequency escalated BMI by beta = 1.61 kg/m^2 (95 percent CI 0.43 to 2.79, p < 0.05).
• Breakfast Skipping: Skipping breakfast drove a BMI increase of **beta = 2.98 kg/m^2 (95 percent CI 0.73 to 5.23, p < 0.05)**while pulling muscle mass down by beta = -0.31 kg (95 percent CI -0.56 to -0.07, p < 0.05).
• Meal Frequency: Higher daily meal frequency scaled fat-free mass upward by beta = 0.95 kg (95 percent CI 0.17 to 1.73, p < 0.05).

Limitations

• Single-clinic recruitment and a predominantly female cohort limit broad demographic generalization.
• Reliance on self-reported 3-day dietary records introduces potential underreporting and misclassification biases.
• Standard clinical lifestyle care delivered concurrently introduces uncontrolled behavioral modifications that obscure independent chrononutrition effects.
• Bioelectrical impedance analysis remains vulnerable to hydration fluctuations and recent ingestion timing.

Discussion and Implications

Traditional nutritional counseling focuses exclusively on macronutrient splits and total caloric deficits while ignoring the biological clock. Circadian misalignment disrupts satiety hormones, suppresses diet-induced thermogenesis, and impairs lipid oxidation during biological nights. Preclinical and clinical models demonstrate that nutrients processed outside daylight windows shift metabolic pathways toward adiposity storage rather than oxidation. Practitioners must integrate meal timing parameters into standard metabolic protocols because clock-based eating behaviors exert independent control over body composition outcomes in prediabetic populations.

Conclusion

Clinical nutrition protocols for prediabetes must mandate strict adherence to a solar eating window between 7.00 am and 7.00 pm while eliminating late-night caloric intake. Prescribing precise meal timing parameters protects lean muscle mass, prevents central adiposity accumulation, and halts metabolic disease progression far more effectively than caloric restriction alone

Link: DOI

Abstract

Comprehensive biological profiling comparing non-essential and essential trace element excretion across distinct dietary spectrums remains noticeably sparse in nutritional literature. This cross-sectional investigation evaluates spot urine excretion profiles of 20 trace elements across 115 healthy adults in southwest Germany, categorized into strict vegans (n = 38, 55.3% female, median age 27.5 years), lacto-ovo-vegetarians (LOV, n = 37, 67.6% female, median age 27.0 years), and omnivores (OMN, n = 40, 60.0% female, median age 30.5 years). Dietary adherence averaged 4.0 years for vegans, 5.8 years for LOV, and 28.0 years for omnivores. Multivariable linear regression models adjusted for age, sex, education, subjective social status, and physical activity scores to evaluate dietary group variance.

Eight elements (silver, gold, bismuth, indium, iridium, palladium, platinum, zirconium) were undetected or present in negligible samples. Unadjusted linear models revealed 54.4% lower arsenic (p = 0.009) and 47.6% lower mercury (p = 0.028) in vegans alongside 54.1% lower arsenic in LOV (p = 0.009) compared to omnivores. Raw cadmium concentrations were 41.7% higher in vegans (p = 0.023). Normalizing values to urinary creatinine confirmed 59.4% lower arsenic in vegans and 63.4% lower arsenic in LOV (p < 0.001), while revealing 17.3% higher copper in vegans (p = 0.040) and 52.5% higher cobalt in LOV (p = 0.035). Creatinine adjustment eliminated significant group differences for mercury and cadmium. No significant differences existed between vegans and LOV across any measured elements (p >= 0.207).

Study Design and Methodology

Investigators recruited 115 healthy, normal-weight (BMI 18.6 to 29.9 kg/m2) participants in Freiburg, Germany. Confirmation of dietary adherence relied on four-day weighed food protocols covering two weekdays and two weekend days. Morning spot urine samples (10 mL) collected between December 2021 and May 2022 underwent inductively coupled plasma mass spectrometry (ICP-MS) using an Agilent 8900 ICP-MS/MS system in July 2024. Laboratory staff and the primary statistician were fully blinded to dietary group identities.

Urinary creatinine concentrations were quantified using the Jaffé method on a Cobas c501 analyzer. Single fixed-value imputation resolved measurements below the limit of quantification (LOQ), affecting elements from 0% (molybdenum) up to 81% (aluminium). Covariate controls in the primary multivariable linear regression models included age, sex, educational attainment, MacArthur subjective social status scale, and binarized physical activity scores from the International Physical Activity Questionnaire. Sensitivity analyses incorporated serum cystatin C as an extra covariate, and pairwise p-values underwent Benjamini-Hochberg false discovery rate correction.

Key Findings

• Non-creatinine-adjusted arsenic levels dropped by 54.4% in vegans and 54.1% in LOV compared to omnivores (p = 0.009), with absolute ranges spans of 1 to 17 ug/L in vegans, 1 to 55 ug/L in LOV, and 1 to 71 ug/L in omnivores.
• Creatinine-normalized arsenic concentrations declined by 59.4% in vegans and 63.4% in LOV relative to omnivores (p < 0.001), establishing total fish exclusion as the primary driver of reduced body burden.
• Unadjusted mercury levels were 47.6% lower in vegans relative to omnivores (p = 0.028, ranges: 0.1 to 0.5 ug/L vs 0.1 to 1.2 ug/L), though creatinine normalization attenuated this difference to non-significance (p > 0.05).
• Raw cadmium excretion was 41.7% higher in vegans compared to omnivores (p = 0.023, ranges: 0.2 to 1.0 ug/L vs 0.2 to 0.7 ug/L), but creatinine-adjusted models negated statistical significance (p > 0.05).
• Creatinine-normalized copper rose by 17.3% in vegans compared to omnivores (p = 0.040), reflecting high copper density in unrefined plant foods.
• Creatinine-adjusted cobalt increased by 52.5% in LOV (p = 0.035), while vegans displayed a +42.6% trend (p = 0.054 post-FDR correction) driven by high vitamin B12 supplementation rates (92.1% in vegans vs 27.5% in omnivores).
• Urinary creatinine concentrations showed no significant differences between vegans (median 0.89 g/L), LOV (median 0.96 g/L), and omnivores (median 0.73 g/L) after covariate adjustment (p >= 0.912).
• Bivariate correlations between dietary or supplemental intakes of zinc, copper, or vitamin B12 and their corresponding urinary elements were negligible (r <= |0.06|). Supplemental intake overall showed weak correlations with urinary trace element levels (r <= |0.33|).

Limitations

• The cross-sectional design prevents drawing direct causal inferences regarding dietary intakes and internal tissue accumulation.
• Utilizing single morning spot urine samples introduces potential dilution variance compared to 24-hour collection standards, though creatinine adjustment counteracted hydration fluctuations.
• High proportions of values fell below the limit of quantification for specific elements like aluminium (81%) and mercury (76%), requiring single-value statistical imputation.
• Spot urine matrixes do not represent ideal biomarkers for cadmium and lead, which concentrate predominantly in red blood cells.
• Nutrient database constraints prevented direct food-group correlation analyses, such as linking specific rice or seaweed consumption protocols to urinary arsenic spikes.

Discussion and Implications

These findings reframe environmental toxicant profiles across plant-based paradigms. Excluding seafood dramatically slashes systemic arsenic exposure by more than half without inducing deficiencies in essential trace minerals like molybdenum or copper. Fears regarding severe heavy metal toxicity from plant-heavy diets prove unfounded: elevated raw cadmium and lower mercury signals in vegans dissolve once controlling for urinary dilution parameters. High vitamin B12 supplementation rates in vegans increase excreted cobalamin-bound cobalt, yet this molecule remains biologically inert and fails to yield free toxic cobalt ions. Plant-based diets deliver an advantageous toxicological trade-off by limiting marine pollutant accumulation while sustaining adequate essential ultratrace element homeostasis.

Conclusion

Strict plant-based diets significantly lower exposure to toxic environmental arsenic by over 50% through seafood exclusion while maintaining essential trace element profiles comparable to omnivorous diets. Observed variations in cadmium and mercury depend heavily on urine dilution correction methods, confirming that plant-based dietary choices do not elevate heavy metal burden. Clinical nutritionists can confidently advocate well-planned vegan diets without fearing ultratrace mineral imbalances or heightened environmental toxicant accumulation.

Trans fatty acids from dairy foods do not affect risk of cardiometabolic diseases: Systematic review and meta-analysis of evidence from randomized controlled trials and systematic review of prospective cohort studies

https://doi.org/10.1016/j.nutres.2026.03.009

Abstract

Global health initiatives like the WHO REPLACE action plan focus on eliminating industrially produced trans fatty acids (iTFA), yet ruminant-derived trans fatty acids (rTFA) remain a natural component of dairy and meat. Scientific uncertainty persists regarding whether rTFA share the same pathogenic profile as iTFA or if their typical low intake levels mask potential risks. This systematic review addressed this gap by evaluating the cardiometabolic effects of dairy-sourced TFA through a dual-lens approach: a meta-analysis of 10 randomized controlled trials (RCTs) and a systematic review of 12 prospective cohort studies (PCS). The study populations spanned healthy adults, overweight individuals, and those with mild hypercholesterolemia across North America and Europe, focusing on biomarkers like blood lipids and hard clinical endpoints including cardiovascular disease (CVD) and type 2 diabetes (T2D).

Pooled meta-analysis of the RCT data demonstrated that dairy foods naturally enriched with TFA (ranging from 1.3 to 13.2 g/d) do not adversely impact the lipid profile. Primary outcomes showed no significant differences in mean difference for total cholesterol (TC), LDL-C, triacylglycerols (TG), ApoB, or ApoA1. A slight decrease was observed in HDL-C with a mean difference of -0.05 mmol/L (95% CI: -0.10 to -0.00, p = 0.04), though this significance disappeared in sensitivity analyses by food type. Prospective cohort data confirmed these findings: circulating concentrations of trans palmitoleic acid (TPA) and vaccenic acid (VA) showed no association with CVD incidence or mortality. Notably, multiple cohorts reported an inverse relationship with metabolic risk, including a 52% lower risk of incident diabetes (p trend = 0.02) in the MESA cohort and a significant reduction in sudden cardiac death (p trend = 0.015) in the LURIC study.

Study Design and Methodology

This investigation utilized a systematic literature search in PubMed and EMBASE through December 2024 following PRISMA guidelines. The RCT arm included 10 trials (N = 10 to 61 per study) with durations of 3 to 12 weeks. These trials utilized modified dairy fat (butter, cheese, or milk) where cows were fed plant oils or oilseeds to naturally increase rTFA content. Controls consisted of conventional dairy products. Most RCTs used crossover designs with washout periods, while others were parallel interventions. The PCS arm evaluated 12 high-quality cohorts (N = 407 to 3,333) with follow-up periods reaching 22 years. Researchers measured TFA exposure through objective biomarkers in plasma phospholipids, serum, or erythrocyte membranes rather than self-reported intake.

Key Findings

• Lipid Biomarkers: Meta-analysis of 13 experimental groups showed no significant pooled effect on LDL-C (p = 0.069) or Total Cholesterol (p = 0.026), with the latter showing a decrease after trim-and-fill recomputation (mean difference = -0.19 mmol/L).
• Cardiovascular Ratios: Ratios for TC/HDL-C and LDL-C/HDL-C remained stable across all interventions with no significant pooled effect (p = 0.996 and p = 0.999, respectively).
• Diabetes Risk: High circulating TPA was associated with a 48% to 52% lower risk of incident T2D in the NHS, HPFS, and MESA cohorts (p trend < 0.001 and p trend = 0.02).
• CVD Mortality: Analysis of the CHS cohort (22-year follow-up) found no association between TPA and CVD death (HR = 0.95, 95% CI: 0.75-1.21) or stroke (HR = 1.13, 95% CI: 0.84-1.52).
• Specific Isomers: Trans vaccenic acid (VA) levels in the NHANES cohort showed no correlation with CVD mortality (p = 0.711) over 11.6 years.

Limitations

The RCTs often featured small sample sizes and "some concerns" regarding bias due to lack of pre-specified analysis plans. Altering cow diets to increase rTFA naturally decreases saturated fatty acids (SFA) and increases MUFA/PUFA, which introduces confounding variables in lipid outcomes. Most prospective cohorts relied on a single baseline measurement of fatty acid biomarkers, which doesn't account for dietary changes over decades of follow-up.

Discussion and Implications

The data challenge the long-standing practice of grouping all trans fats into a single "harmful" category. Ruminant TFA behave differently than their industrial counterparts, likely due to the specific isomers present (VA and TPA) and the complex dairy food matrix. While industrial TFA are clearly linked to CHD, natural dairy TFA at current consumption levels (up to 13g/d in experimental settings) don't degrade the lipid profile. The consistent inverse association between TPA and type 2 diabetes suggests that dairy fat biomarkers are indicators of a protective metabolic effect or a healthy dietary pattern. Professionals should distinguish between hydrogenated oils and natural dairy fats when providing cardiovascular risk counseling.

Conclusion

Dairy-derived trans fatty acids do not increase cardiometabolic risk and are not associated with adverse lipid changes or cardiovascular events. High circulating levels of these fats correlate with a reduced risk of type 2 diabetes, confirming that naturally occurring ruminant trans fats are distinct from industrially produced variants. Nutrition professionals don't need to restrict full-fat dairy based on its natural trans-fat content.

Micronutrient Deficiencies and Cardiovascular Disease: A Binational Analysis of NHANES and CHARLS

DOI: https://doi.org/10.1017/S0007114526107661

Abstract

Micronutrient deficiencies represent modifiable risk factors for cardiovascular disease (CVD), yet the relative importance of specific biomarkers and their cumulative impact across diverse global populations remains insufficiently characterized. This study addressed a critical research gap by performing a binational analysis to compare nutritional landscapes in the United States and China. The researchers integrated cross-sectional data from the National Health and Nutrition Examination Survey (NHANES, 2007-2018) and prospective longitudinal data from the China Health and Retirement Longitudinal Study (CHARLS, 2011-2018). The objective was to evaluate the associations between specific micronutrient biomarkers (vitamin D, folate, vitamin B12, calcium, and iron) and dietary patterns with CVD prevalence and incidence.

In the NHANES cohort, iron deficiency emerged as a potent independent risk factor for prevalent CVD with an odds ratio (OR) of 1.49 (95% CI: 1.09-2.01). While vitamin D deficiency was the most prevalent at 33.1%, it didn't show an independent association in multivariable-adjusted models. Nonlinear spline analysis revealed a U-shaped relationship for iron (p-nonlinearity = 0.003) and an inverse association for vitamin D (p-nonlinearity < 0.001). Cumulative risk was evident as participants with two or more deficiencies exhibited 91% higher CVD odds (OR 1.91, 95% CI: 1.20-2.99). Prospective data from CHARLS confirmed that frequent intake of fruits and vegetables (aHR 0.81, 95% CI: 0.70-0.93), nuts (aHR 0.82, 95% CI: 0.71-0.95), and fish (aHR 0.85, 95% CI: 0.74-0.98) significantly reduced incident CVD risk.

Study Design and Methodology

This research utilized a dual-design approach. The US component (NHANES) used a cross-sectional design with a population of N = 3,848 adults. The Chinese component (CHARLS) utilized a prospective cohort design following N = 11,391 participants from 2011 to 2018. Researchers used multivariable-adjusted logistic regression for cross-sectional prevalence and Cox proportional hazards models for longitudinal incidence. Measurement tools included standardized laboratory assays for serum biomarkers and validated food frequency questionnaires. Statistical controls accounted for age, sex, BMI, smoking status, and comorbid conditions. No metabolic ward or blinding was applicable given the observational nature of the datasets.

Key Findings

• Iron deficiency prevalence reached 23.4% in the US cohort and was independently linked to CVD (OR 1.49, p < 0.05).
• Cumulative micronutrient deficiency score (MDS) showed a clear dose-response effect where MDS ≥ 2 nearly doubled CVD risk (OR 1.91).
• Vitamin D showed a significant nonlinear relationship with CVD risk (p-nonlinearity < 0.001) despite lacking independent linear association.
• Plant-based dietary components provided consistent protection: Fruit and vegetable consumption reduced hazard by 19% (aHR 0.81).
• Nut consumption was associated with an 18% reduction in incident CVD (aHR 0.82).
• Fish intake resulted in a 15% lower risk of developing CVD over the follow-up period (aHR 0.85).

Limitations

The study relies on cross-sectional data for the biomarker analysis, which prevents the establishment of direct causality for iron and vitamin D. Dietary data in the CHARLS cohort was self-reported, introducing potential recall bias. While the models adjusted for major confounders, residual confounding from unmeasured socioeconomic or genetic factors can't be entirely ruled out.

Discussion and Implications

These results signal a shift in how we prioritize nutritional interventions for heart health. We've spent decades focusing on macronutrients and lipids, but these data prove that micronutrient status (specifically iron) is a primary driver of cardiovascular pathology. The synergistic effect of multiple deficiencies suggests that treating a single nutrient in isolation is less effective than addressing total nutritional status. Iron deficiency is an underrecognized independent risk factor that requires mandatory screening in cardiovascular clinical practice. The protective effects of plant-based patterns and fish across different geographic populations reinforce the universality of these dietary requirements.

Conclusion

Iron deficiency is a major independent predictor of cardiovascular disease that demands routine clinical screening alongside standard lipid panels. Clinicians should prioritize a holistic approach to micronutrient status because cumulative deficiencies synergistically double the risk of heart disease.

Evidence for a protein leverage effect on food intake in a Norwegian population

DOI: https://doi.org/10.1016/j.appet.2026.108581

https://preview.redd.it/9n2hy8t14r0h1.png?width=2765&format=png&auto=webp&s=dbcd53c0258f7919ec8700531c799e4ec1e38217

Abstract

The global obesity epidemic is often attributed to multifactorial causes, yet the protein leverage hypothesis offers a specific mechanism involving the dilution of dietary protein in modern food environments. This hypothesis suggests that humans prioritize a specific protein target, leading to excess energy consumption when the protein proportion of the diet decreases. While several randomized controlled trials and pediatric studies have supported this, few large scale observational studies have examined these effects in adult European populations. This pre-registered study aimed to explore the relationship between habitual dietary protein, total energy intake (TEI), and BMI within a general population. The researchers utilized cross-sectional data from the seventh survey of the Tromsø Study (2015-2016), focusing on a cohort of 11,152 Norwegian adults aged 40 to 99 years.

The analysis provided strong support for a partial protein leverage effect on energy intake. Total energy intake was negatively associated with the proportion of dietary protein (L = -0.36, p < .001) and positively associated with dietary fat (L = 0.33, p < .001). While the researchers intended to test the link between protein and BMI, the data showed a weak negative relationship between total energy intake and BMI (p < .001), rendering the sample unsuitable for testing protein's effect on BMI. Ultra-processed food (UPF) consumption was positively associated with total energy intake (b = 554, p < .001) and negatively associated with the proportion of dietary protein (b = -2.0, p < .001). Additionally, a subsample analysis (n = 880) revealed that plasma FGF21 levels were negatively associated with percent protein in the diet (b = -0.05, p = .001).

Study Design and Methodology

This cross-sectional study analyzed data from the Tromsø7 survey (2015-2016) in Tromsø, Norway. The total sample size included 11,152 participants after exclusions for pregnancy, extreme BMI values, or incomplete dietary data. Researchers used a validated 261-item Food Frequency Questionnaire (FFQ) to assess habitual intake over the previous year. Height and weight were measured by trained personnel using standardized scales. Food items were categorized using the NOVA classification system to determine UPF intake. A randomly selected subsample of 1,144 participants provided non-fasting blood samples for FGF21 analysis via Proximity Extension Assay technology. Statistical models controlled for age, sex, physical activity, education, smoking status, and chronic health conditions.

Key Findings

• Protein exerted a significant negative leverage on energy intake with an L-value of -0.36 (p < .001).
• Fat intake showed a positive leverage effect on total energy consumption with an L-value of 0.33 (p < .001).
• Carbohydrate proportion had no significant control over energy intake with an L-value of 0.00 (p = .966).
• The highest quintile of UPF consumption was associated with a lower protein proportion (16.4% vs 18.5% in the lowest quintile).
• UPF intake was a significant predictor of higher energy intake, showing an increase of 554 kJ per day (p < .001).
• Protein leverage was significantly stronger in low UPF consumers (L = -0.40) compared to high UPF consumers (L = -0.29, p = .009).
• FGF21 levels increased as dietary protein percentage decreased (b = -0.05, p = .001), supporting its role as a biomarker for protein restriction.

Limitations

The study relies on self-reported dietary data from an FFQ, which is susceptible to underreporting, particularly in participants with higher BMI. The cross-sectional nature prevents the establishment of a causal link between protein leverage and long term weight gain. The lack of a positive correlation between energy intake and BMI in this specific cohort limits the ability to draw conclusions regarding obesity development.

Discussion and Implications

These results confirm that the protein leverage mechanism is active in middle aged and older European adults. The data show that as the protein density of the diet drops, individuals increase their total energy intake to reach a physiological protein target. This effect is particularly relevant in the context of ultra-processed foods, which appear to dilute protein and drive passive overconsumption of fats and carbohydrates. The negative correlation between protein and FGF21 suggests a biological signaling pathway that monitors protein status and potentially modulates appetite. The positive leverage effect of fat indicates that high fat diets exacerbate the energy surplus created by protein seeking behavior.

Conclusions

Dietary protein proportion is a primary driver of total energy intake in adults, where even small dilutions in protein density lead to significant caloric overconsumption. Nutrition professionals should prioritize protein density to leverage satiety and mitigate the passive overconsumption of energy associated with ultra-processed, high fat diets.

The Effect of Including 1 Avocado Daily in a Habitual Diet on the Glycemic Index and Glycemic Load in Free-Living Adults with Overweight/Obesity

Link to study.

Abstract

High glycemic index (GI) and glycemic load (GL) diets are established drivers of type 2 diabetes and cardiovascular disease risk. While avocados are nutrient-dense and low in available carbohydrates, evidence is sparse regarding how adding a single food to a Western habitual diet influences these specific glycemic metrics over the long term. This secondary analysis of the Habitual Diet and Avocado Trial (HAT) aimed to determine if daily consumption of one large avocado (168 g) for six months would lower dietary GI and GL. The study population consisted of 1008 free-living adults with abdominal obesity (elevated waist circumference) who typically consumed fewer than two avocados per month.

The intervention group demonstrated a significant reduction in dietary GL compared to the control group. After adjusting for age, sex, BMI, energy intake, and other confounders, the avocado-supplemented group showed a reduction in dietary GL by 13.7 points (95% CI: -17.0, -10.4; p < 0.001). No significant differences were observed in dietary GI between the groups (p = 0.123 in unadjusted models; p = 0.043 when adjusted for kcal, but p = 0.063 in the fully adjusted model). Nutrient analysis revealed that the avocado group had significantly higher intakes of fiber, monounsaturated fatty acids (MUFA), and several micronutrients, alongside a lower percentage of energy from carbohydrates and animal protein.

Study Design and Methodology

This was a multicenter, randomized, parallel-arm controlled trial conducted over 26 weeks. The study enrolled 1008 adults (961 included in final analysis) with elevated waist circumference (over 35 inches for women, 40 inches for men). Participants were randomized to either the avocado group (1 large avocado/day) or the control group (habitual diet, <2 avocados/month). Dietary intake was measured using three unannounced 24-hour dietary recalls at weeks 8, 16, and 26 via the Nutrition Data System for Research (NDSR) software. The study utilized a free-living design without a metabolic ward setting or caloric restriction, providing a high degree of ecological validity. No specific nutritional counseling was provided to either group beyond avocado preparation instructions.

Key Findings

• Dietary Glycemic Load (GL) decreased by 13.7 points in the intervention group (beta = -13.73, p < 0.001).
• Total dietary fiber intake increased from 17.8 g/d to 28.0 g/d in the avocado group (p < 0.001).
• Soluble fiber intake rose significantly from 5.7 g/d to 9.3 g/d (p < 0.001).
• Monounsaturated fatty acid (MUFA) intake increased from 13.2% to 18.1% of total energy (p < 0.001).
• Carbohydrate intake as a percentage of energy decreased from 43.1% to 40.1% (p < 0.001).
• Animal protein intake was significantly lower in the avocado group (47.4 g/d vs 51.5 g/d, p = 0.003).
• Avocado consumption resulted in an 87% displacement of non-avocado carbohydrate sources.

Limitations

The study relied on self-reported 24-hour dietary recalls, which are susceptible to underreporting or memory bias. The secondary analysis nature of the study means it wasn't originally powered for GI/GL as primary endpoints. While the sample was large and diverse, the free-living design introduces potential variability in adherence that isn't present in controlled feeding trials.

Discussion and Implications

These results demonstrate that a simple, single-food addition can meaningfully alter the glycemic profile of a habitual diet without requiring complex counseling or restrictive patterns. The 14-point reduction in GL is clinically relevant, as similar magnitudes of change are associated with improved HbA1c and reduced hepatic fat in existing literature. The mechanism appears to be a combination of the avocado's low-glycemic matrix (high fiber and MUFA) and the natural displacement of higher-glycemic carbohydrate sources. This study shifts the focus from "dietary restriction" to "nutrient-dense addition" as a viable public health strategy for managing glycemic response in populations with obesity.

Conclusion

Adding one avocado daily to a habitual diet reduces dietary glycemic load by approximately 14 points, primarily through carbohydrate displacement and increased fiber intake. This single-food intervention offers a sustainable, non-restrictive method for clinicians to improve the glycemic profile of patients with overweight or obesity.

Edit: Link updated.

Marine n-3 fatty acid treatment for carotid plaques in patients with type 2 diabetes
https://doi.org/10.1186/s12933-026-03082-7

Abstract

Patients with type 2 diabetes (T2D) face a significantly elevated risk of atherosclerotic cardiovascular disease, often driven by residual dyslipidemia even when LDL cholesterol is well managed. While marine n-3 polyunsaturated fatty acids (PUFAs) are known to modulate lipid metabolism, their direct impact on subclinical atherosclerosis like carotid plaques remains controversial, especially within diabetic populations. This study addressed this gap through a 14 month double blind, randomized controlled trial involving 415 Chinese T2D patients aged 40 to 75. The primary objective was to evaluate whether high dose (3.0 g/day) or low dose (1.5 g/day) fish oil supplementation could reduce carotid plaque prevalence or improve NMR derived lipoprotein subclasses compared to a refined olive oil placebo.

The 14 month intervention showed that fish oil supplementation did not significantly reduce carotid plaque prevalence, with a p trend of 0.111. Compared to the placebo, the adjusted odds ratios (OR) for plaque risk were 1.05 (95% CI 0.51 to 2.14) for the low dose group and 0.49 (95% CI 0.23 to 1.04) for the high dose group (p trend = 0.071). No significant effects were observed for the incidence of new plaques (p trend = 0.304) or the regression of existing ones (p trend = 0.390). High dose fish oil significantly improved the lipoprotein profile, reducing remnant cholesterol (median change -14.00 mg/dL vs -0.50 mg/dL in placebo, FDR < 0.001) and lowering triglycerides across VLDL, IDL, and specific LDL/HDL subfractions. A significant gene treatment interaction was found where high dose fish oil reduced plaque risk only in patients with low genetic risk for remnant cholesterol (p interaction = 0.008, FDR = 0.056).

Study Design and Methodology

This was a 14 month, double blind, placebo controlled, randomized clinical trial (NCT03708887) conducted in China. The study enrolled 415 T2D patients who were randomized 1:1:1 into three groups: high dose (3.0 g/day EPA+DHA), low dose (1.5 g/day EPA+DHA), or a refined olive oil placebo. Researchers used carotid ultrasonography at baseline and month 14 to assess plaque status and intima media thickness (CIMT). Plasma lipoprotein subclasses were quantified using a high throughput 600.13 MHz proton NMR spectrometer. Compliance was verified via gas chromatography of plasma EPA and DHA levels and monthly capsule counts. Genetic risk scores (GRS) were constructed using Illumina Infinium Asian Screening Array genotyping to explore gene nutrient interactions.

Key Findings

• High dose fish oil reduced serum triglycerides: median change -0.405 mmol/L vs -0.085 mmol/L in placebo (p < 0.001).
• Remnant cholesterol reduction in high dose group: median change -14.00 mg/dL (FDR < 0.001).
• Adjusted OR for carotid plaque in high dose group: 0.49 (95% CI 0.23 to 1.04, p = 0.071).
• New plaque incidence OR (high dose): 0.54 (95% CI 0.22 to 1.32, p = 0.191).
• Interaction between high dose and remnant cholesterol GRS: p interaction = 0.008.
• Plaque risk reduction in low genetic risk subgroup: significant benefit observed (FDR = 0.056).
• Maximum CIMT change: -0.010 mm in high dose vs 0.000 mm in placebo (p = 0.075).

Limitations

• The 14 month duration might be too short to observe structural regression of established atherosclerotic plaques.
• The study used a mix of EPA and DHA, which may have different or opposing effects on specific LDL subfractions.
• The sample size, while large for this demographic, was underpowered to detect smaller relative risk reductions in the primary outcome.
• The population was statin naive or had low statin usage (13.5%), which limits generalizability to patients on intensive lipid lowering therapy.
• Plaque stability and composition were not assessed via advanced imaging.

Discussion and Implications

These results indicate that marine n-3 PUFA supplementation doesn't provide a broad "one size fits all" reduction in carotid atherosclerosis for T2D patients within a 14 month window. The clear, dose dependent improvement in remnant cholesterol and triglyceride rich lipoprotein subfractions confirms the metabolic efficacy of high dose fish oil, yet these biochemical shifts don't immediately translate to structural plaque changes. The discovery of a significant interaction with genetic risk for remnant cholesterol is a major step toward precision nutrition. It suggests that a patient's genetic architecture dictates their vascular response to n-3 fatty acids. Clinical practice should move away from routine supplementation for all diabetic patients and instead focus on identifying responsive subgroups through genetic and advanced lipid profiling.

Elevated remnant cholesterol is linked to non-alcoholic fatty liver disease in patients with type 2 diabetes mellitus

https://doi.org/10.3389/fnut.2026.1782646

https://preview.redd.it/r9xp50rphbzg1.png?width=1417&format=png&auto=webp&s=d827bdf16a6aa38bc4e539f935a133ec3772f0e6

Abstract

Non-alcoholic fatty liver disease (NAFLD) and type 2 diabetes mellitus (T2DM) are closely interrelated metabolic conditions that significantly increase the risk of cardiovascular and hepatic complications. While traditional lipid parameters like LDL-C are standard in clinical assessments, the role of remnant cholesterol (RC), which represents the cholesterol content of triglyceride-rich lipoproteins, remains poorly defined in diabetic populations. This study aimed to investigate the independent association between RC levels and the presence of NAFLD in patients diagnosed with T2DM. The researchers utilized a cross-sectional cohort of 308 hospitalized patients to address the gap in identifying simple, cost-effective biomarkers for liver disease risk stratification in high-risk metabolic groups.

The primary analysis revealed a robust positive correlation between elevated RC and NAFLD presence. In the fully adjusted multivariable logistic regression model, each 1 mmol/L increase in RC was associated with a 4.23-fold increase in the odds of NAFLD (OR = 4.23, 95% CI: 1.73 to 12.04, p = 0.004). Restricted cubic spline analysis confirmed a linear dose-response relationship (p overall = 0.006, p nonlinear = 0.399), showing that the predicted probability of NAFLD increased from 65.7% at an RC of 0.2 mmol/L to 85.8% at 1.0 mmol/L. Sensitivity analyses using RC tertiles further validated these findings: patients in the highest tertile (T3) exhibited significantly higher odds of NAFLD compared to the lowest (T1) after full adjustment (OR = 2.05, 95% CI: 1.06 to 4.03, p trend = 0.035).

Study Design and Methodology

This cross-sectional study involved 308 patients with T2DM admitted to Hebei General Hospital between 2023 and 2025. Participants underwent an 8-hour overnight fast before venous blood collection for biochemical analysis. RC was calculated as total cholesterol minus LDL-C minus HDL-C. NAFLD was diagnosed using hepatic ultrasound imaging after strictly excluding secondary causes such as excessive alcohol consumption, viral hepatitis, or autoimmune liver disease. The statistical framework employed multivariable logistic regression across three models, with the final model adjusting for age, diabetes duration, BMI, uric acid, and albumin. Model performance was verified through the Hosmer-Lemeshow test for calibration and the DeLong method for AUC discrimination.

Key Findings

• NAFLD prevalence in the diabetic cohort: 69.0% (211 patients).
• Median RC levels in NAFLD vs. non-NAFLD: 0.6 mmol/L vs. 0.4 mmol/L (p < 0.001).
• Adjusted odds ratio (Model 3) per 1 mmol/L RC increase: 4.23 (95% CI: 1.73 to 12.04, p = 0.004).
• AUC for NAFLD discrimination using Model 3: 0.778 (95% CI: 0.723 to 0.834).
• Predicted probability of NAFLD at RC 0.8 mmol/L (75th percentile): 80.0%.
• Interaction tests for age (p = 0.772), sex (p = 0.231), and BMI (p = 0.221) showed consistent effects across all subgroups.
• Post-hoc power calculation: 99.4% power to detect the observed association.

Limitations

• The cross-sectional nature of the study prevents the determination of a causal relationship between RC and NAFLD.
• Ultrasound diagnosis lacks the precision to differentiate between simple steatosis and non-alcoholic steatohepatitis (NASH) or to quantify fibrosis stages.
• The sample size is relatively small, which may have limited the statistical power in specific subgroup analyses, such as the female population.
• Potential residual confounding exists from unmeasured variables including dietary habits, physical activity, and the use of specific lipid-lowering or antidiabetic medications.

Discussion and Implications

These findings establish remnant cholesterol as a potent and independent indicator of NAFLD risk in diabetic patients. The results support the integration of RC into standard metabolic screenings, as it provides a simple calculation from existing lipid panels without additional cost. This study shifts the focus from traditional LDL-C toward triglyceride-rich lipoprotein remnants as critical drivers of hepatic lipid accumulation and inflammation. Clinicians should recognize that even in non-obese diabetic patients, elevated RC remains a significant threat to liver health. Prioritizing RC management may offer a dual benefit in reducing both cardiovascular risk and the progression of metabolic liver disease.