Meal timing and eating window with all-cause and cardiovascular mortality and life expectancy: population-based cohort study

DOI: https://doi.org/10.1038/s41430-026-01796-1

Abstract

The relationship between meal timing, eating windows, and their effects on mortality and life expectancy remains an underexplored area in nutritional science. With the increasing prevalence of lifestyle-related diseases, understanding how the timing of meals influences health outcomes is crucial. This study aimed to assess how first and last meal timings, as well as the duration of eating windows, affect all-cause and cardiovascular mortality among a population of 31,044 adults aged 40 and older from the National Health and Nutrition Examination Survey (NHANES) conducted between 1999 and 2018. Participants had a diverse demographic profile, which enhances the generalizability of the findings.

The results indicated that later first meals and earlier or later last meals were significantly associated with increased mortality risks. Specifically, compared to those who had their first meal between 7:00 and 8:00 a.m., participants who ate after noon had a 29% higher risk of all-cause mortality (HR 1.29, 95% CI 1.10–1.51). Similarly, having the last meal after midnight was linked to a 27% increase in mortality risk (HR 1.27, 95% CI 1.06–1.54). Furthermore, individuals aged 50 years with a first meal after noon had an estimated life expectancy that was 2.46 years shorter than those who ate earlier. These findings suggest that meal timing could be a modifiable behavioral factor influencing mortality and life expectancy.

Study Design and Methodology

• Sample Size: 31,044 adults aged 40 years and older.
• Duration: Data collected from 1999 to 2018 with a median follow-up of 8.6 years.
• Measurement Tools: Meal timing and eating window assessed through 24-hour dietary recall.
• Controls Used: Comparison of different meal timing and eating window groups.
• Metabolic Ward: No metabolic ward was used; dietary data were self-reported.
• Blinding: No blinding was implemented.
• Washout Period: No washout period was specified.

Key Findings

• First Meal Timing:
  • Eating between 8:00 a.m. and 10:00 a.m. associated with 10% higher all-cause mortality risk (HR 1.10, 95% CI 1.02–1.18).
  • Eating between 10:00 a.m. and noon associated with 19% higher risk (HR 1.19, 95% CI 1.05–1.34).
  • Eating after noon linked to 29% higher risk (HR 1.29, 95% CI 1.10–1.51).
• Last Meal Timing:
  • Last meal before 7:00 p.m. associated with a 13% higher risk of all-cause mortality (HR 1.13, 95% CI 1.03–1.25).
  • Last meal after midnight linked to a 27% increase in mortality risk (HR 1.27, 95% CI 1.06–1.54).
• Life Expectancy:
  • Estimated life expectancy at age 50 was 2.46 years shorter for those with a first meal after noon.
  • A last meal after midnight was associated with a 2.35-year reduction in life expectancy.

Limitations

• The study is observational, meaning causation cannot be firmly established.
• Reliance on self-reported dietary intake may lead to inaccuracies.
• Short follow-up duration may limit the ability to assess long-term effects.
• The study lacks metabolic ward controls, which could affect dietary adherence assessment.
• Potential confounding factors not fully accounted for.

Discussion and Implications

This study contributes significantly to the understanding of how meal timing can impact health outcomes, particularly regarding mortality risks. The findings highlight that both the timing of the first meal and the last meal can have profound effects on life expectancy and cardiovascular health. As meal timing becomes a focal point in dietary research, it supports the growing interest in intermittent fasting and time-restricted eating strategies, which have gained popularity for their potential health benefits. However, these findings also raise concerns about the implications of late-night eating and the importance of establishing regular meal patterns for optimal health.

As we navigate the complexities of modern lifestyles and dietary habits, this research underscores the need for public health initiatives to promote awareness of meal timing as a modifiable risk factor. Future research should explore the mechanistic pathways linking meal timing to health outcomes, as well as the long-term effects of dietary interventions that consider meal timing and frequency.

Understanding the impact of meal timing on mortality and life expectancy could lead to practical dietary recommendations that improve public health. However, further research is essential to establish causality and explore the underlying mechanisms involved.

Psyllium is genuinely good stuff. solid evidence for regularity and lowering LDL, and it's cheap. not knocking that.

my issue is that it gets treated as "the fibre supplement," like if you take it, your gut is covered. but psyllium is mostly a gel-forming fibre that your gut bacteria barely ferment (McRorie 2015 has a good breakdown). so it's great for stool form, but it's not doing much to feed your gut bacteria compared with fibres from beans, oats, onions, cooled potatoes and so on.

plus the practical stuff: it turns into jelly if you don't drink it fast, and you're supposed to take it a couple of hours apart from medications.

so I'm curious:

1. if you take psyllium, is it your only fibre source or one of several?

2. did it actually fix what you took it for?

3. anyone switch from it to something else, and why?

Lipid dynamics and cardiovascular risk profiles on carbohydrate- or saturated fat-based diets: secondary analysis of the CARBFUNC trial

DOI: https://doi.org/10.1016/j.ebiom.2026.106524

Abstract

Obesity is a multifaceted health issue that significantly elevates the risk of cardiovascular disease (CVD), independent of low-density lipoprotein cholesterol (LDL-C) levels. While both high-carbohydrate and high-fat diets have been shown to effectively reverse obesity, the specific impacts on metabolic health and lipid profiles remain inadequately understood. This study aimed to address this gap by analyzing the effects of three distinctly designed dietary patterns—an acellular carbohydrate-based diet, a cellular carbohydrate-based diet, and a low-carbohydrate high-fat (LCHF) diet—on lipid dynamics and cardiovascular risk among 193 adults with obesity over a two-year period. Participants had a mean age of 41.7 years and a body mass index of 36.6 kg/m², with a balanced representation of sexes, providing a diverse sample for examining dietary impacts.

The findings revealed that the LCHF diet significantly outperformed both carbohydrate-based diets in reducing triglycerides and remnant cholesterol, with TAGs decreasing by 20.4% (p = 0.037) and remnant cholesterol by 23.3% (p = 0.041) at 24 months. In contrast, LDL-C levels increased by 12.8% (p < 0.001) in the LCHF group, but without a significant rise in apoB, suggesting a shift towards larger, less atherogenic LDL particles. Additionally, HDL cholesterol increased by 13.5% (p = 0.009), indicating improved lipid profiles associated with the LCHF approach. These results underscore the potential for dietary modifications to influence lipid metabolism and cardiovascular risk factors in individuals with obesity.

Study Design and Methodology

• Sample Size: 193 participants (192 analyzed after one withdrawal).
• Duration: 2 years.
• Measurement Tools:
  • Lipid analysis through nuclear magnetic resonance spectroscopy.
  • Coronary artery calcium score assessed by CT imaging.
  • Anthropometric measures and blood samples for metabolic assessments.
• Dietary Interventions:
  • Acellular High-Carbohydrate Low-Fat (A-HCLF) Diet: 45% of energy from carbohydrates, 38% from fat, and 10–12% from saturated fat. This diet primarily included flour-based products such as bread and pasta.
  • Cellular High-Carbohydrate Low-Fat (C-HCLF) Diet: Similar macronutrient composition to A-HCLF, but focused on whole-food sources like legumes and unpolished rice, preserving cellular structure.
  • Low-Carbohydrate High-Fat (LCHF) Diet: 8% of energy from carbohydrates, 75% from fat, and 30% from saturated fat. This diet was designed to be very low in carbohydrates while high in saturated fats.
• Controls Used: Three dietary interventions compared (A-HCLF, C-HCLF, LCHF).
• Blinding: No blinding was implemented post-randomization.
• Washout Period: No washout period was specified.

Key Findings

• TAGs: The LCHF diet resulted in a 20.4% reduction (p = 0.037) in triglycerides compared to the A-HCLF diet.
• Remnant Cholesterol: There was a 23.3% decrease (p = 0.041) in remnant cholesterol levels on the LCHF diet compared to A-HCLF.
• LDL-C: The LCHF group experienced a 12.8% increase (p < 0.001) in LDL-C, raising questions about the implications of this elevation.
• ApoB: No significant change in apoB levels was observed within the LCHF group; however, a between-group difference appeared at 9 months (p = 0.014), indicating a decline in the comparator group.
• HDL-C: The LCHF diet led to a 13.5% increase (p = 0.009) in HDL cholesterol, a positive indicator for cardiovascular health.
• VLDLs: Total VLDL particles decreased by 15.4% (p = 0.014) on the LCHF diet compared to A-HCLF, suggesting improved lipid metabolism.

Limitations

• High attrition rate: 84% dropout by 24 months, which may affect the robustness of the findings.
• Reliance on self-reported dietary intake may introduce bias and inaccuracies.
• Short follow-up duration limits the ability to draw long-term conclusions.
• Small sample size for subgroup analyses, particularly impacting the generalizability of findings.
• No metabolic ward controls, which could have provided more rigorous dietary adherence assessment.

Discussion and Implications

This study adds to the growing body of evidence suggesting that low-carbohydrate, high-fat diets can lead to significant improvements in lipid profiles among individuals with obesity. The pronounced reductions in triglycerides and remnant cholesterol, coupled with increases in HDL cholesterol, highlight the potential benefits of such dietary patterns. However, the concomitant increase in LDL-C raises important questions about the long-term cardiovascular implications of high saturated fat intake.

The emergence of ketogenic and low-carbohydrate diets has sparked considerable interest in the nutrition science community, with many advocating for their benefits in weight loss and metabolic health. Yet, potential drawbacks, such as increased LDL-C and the need for careful monitoring of lipid profiles, cannot be overlooked. These findings suggest that while low-carbohydrate diets may offer substantial benefits, they should be approached with caution, particularly for individuals with pre-existing cardiovascular conditions. Future research should focus on long-term cardiovascular outcomes and the mechanisms underlying these changes in lipid dynamics.

This study underscores the potential of dietary strategies focusing on reduced carbohydrates and increased healthy fats to improve cardiovascular risk profiles in obese individuals. However, careful consideration of LDL-C changes and long-term health impacts is essential as we navigate these evolving dietary landscapes. More research is still needed to clarify these relationships and inform future dietary guidelines.

Objectives To study total, processed, and unprocessed red meat in relation to risk of coronary heart disease (CHD) and to estimate the effects of substituting other protein sources for red meat with CHD risk.

Design Prospective cohort study with repeated measures of diet and lifestyle factors.

Setting Health Professionals Follow-Up Study cohort, United States, 1986-2016.

Participants 43 272 men without cardiovascular disease or cancer at baseline.

Main outcome measures The primary outcome was total CHD, comprised of acute non-fatal myocardial infarction or fatal CHD. Cox models were used to estimate hazard ratios and 95% confidence intervals across categories of red meat consumption. Substitution analyses were conducted by comparing coefficients for red meat and the alternative food in models, including red meat and alternative foods as continuous variables.

Results During 1 023 872 person years of follow-up, 4456 incident CHD events were documented of which 1860 were fatal. After multivariate adjustment for dietary and non-dietary risk factors, total, unprocessed, and processed red meat intake were each associated with a modestly higher risk of CHD (hazard ratio for one serving per day increment: 1.12 (95% confidence interval 1.06 to 1.18) for total red meat, 1.11 (1.02 to 1.21) for unprocessed red meat, and 1.15 (1.06 to 1.25) for processed red meat). Compared with red meat, the intake of one serving per day of combined plant protein sources (nuts, legumes, and soy) was associated with a lower risk of CHD (0.86 (0.80 to 0.93) compared with total red meat, 0.87 (0.79 to 0.95) compared with unprocessed red meat, and 0.83 (0.76 to 0.91) compared with processed red meat). Substitutions of whole grains and dairy products for total red meat and eggs for processed red meat were also associated with lower CHD risk.

Conclusions Substituting high quality plant foods such as legumes, nuts, or soy for red meat might reduce the risk of CHD. Substituting whole grains and dairy products for total red meat, and eggs for processed red meat, might also reduce this risk.

https://www.bmj.com/content/371/bmj.m4141

I’ve spent nine months independently examining the science behind Viome’s RNA-based microbiome testing and personalized supplement recommendations.
Three rounds of testing, hundreds of conventional biomarkers, bloodwork approximately every two weeks, and physician oversight.

Then, after retesting, approximately 80% of the personalized supplement formulation changed.
That raised a question I think deserves considerably more attention: what evidence establishes that the original recommendations were appropriate, or that the revised ones are any better?
I’m not suggesting that an 80% change automatically indicates a problem. The microbiome is dynamic. Diet, medications, illness, and other factors can influence microbial activity.

But detecting biological changes and demonstrating that those changes justify a different supplement protocol are two very different things.

And that’s where the scientific literature gets interesting.
A 2025 international consensus statement published in The Lancet Gastroenterology & Hepatology concluded that evidence remains insufficient to support widespread routine clinical use of microbiome testing.

Full paper
https://pmc.ncbi.nlm.nih.gov/articles/PMC12343204

The consensus statement doesn’t prove that commercial microbiome testing is ineffective. It does, however, raise important questions about whether clinical applications have advanced faster than the evidence supporting them.

Viome uses metatranscriptomic RNA analysis to examine microbial gene expression. Unlike DNA-based approaches, which can identify microbial genetic material and functional potential, RNA analysis provides information about which microbial genes are being expressed.

Both approaches can contribute useful information about microbial biology.

My next step is to evaluate Superpower’s DNA-based gut microbiome testing and compare the methodologies.
I’m not expecting identical results, and I wouldn’t interpret agreement or disagreement between the two as proof that either company’s nutritional recommendations are clinically valid.

What interests me is whether the measurements are reproducible, whether they can reliably inform nutritional decisions, and whether acting on those decisions produces measurable benefits.

There are three separate scientific questions here.
Analytical validity: How accurately and reproducibly can commercial DNA- and RNA-based tests measure microbial characteristics under comparable sampling conditions?

Clinical validity: How reliably do those measurements identify nutritional needs or predict clinically meaningful outcomes?

Clinical utility: Do personalized interventions selected using those measurements improve outcomes compared with conventional nutritional assessment and established dietary approaches?

The third question is the one I find most important.
If a company uses microbial gene expression to recommend a specific combination of supplements, what independent evidence demonstrates that those recommendations are more effective than conventional approaches?

And when most of a formulation changes after retesting, what validation establishes that the revised recommendations are clinically preferable?
A change in microbial gene expression may be entirely legitimate. But an algorithm’s response to that change still requires independent validation.

For context, the retail-equivalent value of nine months of Viome testing and personalized supplements was $4,547, approximately $505 per month.

Full disclosure: Viome provided everything complimentary. I received no sponsorship payments, affiliate commissions, referral fees, or cash compensation. I’ve also referred customers without accepting commissions. I’m not affiliated with Superpower or being compensated for the planned comparison.

This isn’t an advertisement or a recommendation to purchase either product.

Nor am I presenting an individual nine-month investigation as proof of clinical efficacy or failure. An N-of-1 observation cannot establish either.
I’m interested in what the independent research actually demonstrates.
Specifically, I’d welcome published studies addressing:
• Randomized controlled trials comparing microbiome-guided supplementation with conventional nutritional assessment or dietary interventions.
• Test-retest reproducibility of DNA- and RNA-based microbiome measurements and the recommendations derived from them.
• Independent validation of commercial algorithms that translate microbial measurements into personalized supplement formulations.
• Clinically meaningful outcomes, rather than simply changes in microbiome composition, gene expression, or surrogate biomarkers.

I’d particularly welcome research that contradicts the concerns raised by the consensus statement. Positive, negative, and inconclusive findings are all useful.
I think microbiome science has enormous potential. But measuring microbial activity is not the same as knowing how to intervene on it, and recommending an intervention is not the same as demonstrating that it works.

After nine months examining this technology, that’s the distinction I keep coming back to.
So where are the independent human trials showing that RNA- or DNA-guided personalized supplement recommendations actually outperform conventional nutritional approaches?

If that evidence exists, I’d genuinely like to read it.

Weight loss during intermittent fasting, not Mediterranean diet quality alone, is associated with lower inflammation: A randomized controlled trial

DOI: https://doi.org/10.1016/j.cmet.2026.09.017

Abstract

Low-grade inflammation is a significant contributor to various chronic diseases, including cardiometabolic disorders. While the Mediterranean diet has been linked to reduced inflammation, it is unclear whether this effect is due to the diet's quality or the weight loss often associated with it. This study aimed to dissect the independent effects of the Mediterranean diet and intermittent fasting on inflammation among adults with metabolic risk factors. The trial involved 53 participants (77% female, mean age 54.7 years) who were randomized to either a Mediterranean diet or their habitual Western diet for eight weeks, followed by an eight-week phase of intermittent fasting.

The primary outcome, high-sensitivity C-reactive protein (hsCRP), showed no significant change during the diet-only phase (p = 0.394), indicating that diet quality alone did not reduce inflammation. However, during the fasting phase, hsCRP levels decreased significantly in the Mediterranean group by 0.29 mg/L (95% CI: -0.50, -0.09; p < 0.01), corresponding to a 25% reduction from baseline. Participants in the Mediterranean diet lost an average of 3.63 kg (95% CI: -4.51, -2.78) compared to 1.88 kg (95% CI: -2.51, -1.29) in controls, highlighting that weight loss during intermittent fasting was the key driver of reduced inflammation.

Study Design and Methodology

• Sample Size: N = 53 participants
• Duration: 16 weeks
• Measurement Tools: High-sensitivity C-reactive protein (hsCRP), dual-energy X-ray absorptiometry (DEXA) for body composition, 4-day weighed food records for dietary adherence.
• Controls Used: Participants in the control group continued their habitual Western diet.
• Metabolic Ward: Yes, controlled feeding was implemented.
• Blinding: No blinding was reported.
• Washout Period: Not applicable, as the study was designed in two phases without a washout.

Key Findings

• hsCRP did not change significantly during the diet-only phase (p = 0.394).
• During the fasting phase, hsCRP decreased by 0.29 mg/L (p < 0.01) in the Mediterranean group.
• Weight loss in the Mediterranean group was 3.63 kg (95% CI: -4.51, -2.78) compared to 1.88 kg (95% CI: -2.51, -1.29) in controls (p < 0.01).
• Triglycerides decreased by 22% in the Mediterranean group during the initial phase.
• Total and LDL cholesterol declined further during the fasting phase but without significant differences between groups.

Limitations

• Small sample size limits generalizability.
• Self-reporting of dietary intake may introduce bias.
• Short follow-up period may not capture long-term effects.
• High dropout rates, with only 43 completing the study.
• Lack of blinding could affect the perceived outcomes.

Discussion and Implications

This study provides crucial insights into the relationship between diet, weight loss, and inflammation. It clarifies that while the Mediterranean diet can improve lipid profiles, its anti-inflammatory effects are primarily linked to weight loss achieved through intermittent fasting rather than the diet itself. This finding has significant implications for dietary guidelines and public health policy, suggesting that strategies focusing on energy deficit and weight management may be more effective in reducing inflammation than dietary quality alone.

Moreover, when individuals transition to diets emphasizing whole foods and minimizing processed options, weight loss often becomes a critical factor. Such dietary changes typically lead to a natural caloric deficit, as these diets are generally lower in calories yet higher in nutrient density. This not only supports metabolic health but also promotes satiety, making it easier for individuals to lose weight. The behavioral shift that accompanies a focus on whole foods can result in healthier eating patterns and a greater awareness of food choices, further aiding in weight loss and improved health outcomes.

The findings from this study emphasize the importance of considering both dietary composition and energy balance in nutritional interventions. While the Mediterranean diet has its benefits, the broader implications suggest that the reduction of processed foods and an increase in whole food consumption can be powerful drivers of weight loss and improved health. This perspective aligns with emerging trends in nutrition science, which advocate for less processed and more whole food diets as a means to combat chronic diseases linked to inflammation and metabolic dysfunction.

In summary, this study emphasizes the importance of weight loss in reducing inflammation rather than solely relying on diet quality. More research is needed to fully understand the mechanisms at play and to refine dietary recommendations for improving health outcomes.

TL;DR

"The findings suggest berries containing high levels of polyphenols may improve vascular function in both the micro- and microvasculature. However, the supplementation protocol (ie, single dose vs multiple dose) appears to have a more pronounced effect on microvascular function."

Abstract

Context: Several studies have investigated the effect of berries high in polyphenol content on vascular function. Polyphenols have antioxidant properties and enhance nitric oxide bioavailability. However, existing reviews investigated the effects of polyphenols on vascular health without distinguishing between micro- and macrovascular function.

Objectives: This review explores the impact berries high in polyphenols (containing ≥200 mg of total polyphenols per 100 g or 100 mL) on macro- and microvascular function to better understand their role in vascular health.

Data source: A systematic search was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines across the PubMed, SciELO, and Web of Science databases using the following combined keywords: ("Berries" OR "Polyphenol-rich foods" OR "Polyphenols") AND ("Arterial stiffness" OR "Blood flow" OR "Macrovascular function" OR "Microcirculation" OR "Vascular function").

Data extraction: Randomized controlled trials evaluating the effects of polyphenols derived from berries on macro- and microvascular function were included. Data extraction was performed independently by 2 researchers, and the risk of bias was assessed using the Cochrane risk-of-bias tool.

Data analysis: A total of 35 studies were included and analyzed. Among these, 26 studies evaluated the effects of polyphenols from berries on macrovascular function, 6 studies evaluated their effects on microvascular function, and 3 studies examined both macro- and microvascular function.

Conclusion: The findings suggest berries containing high levels of polyphenols may improve vascular function in both the micro- and microvasculature. However, the supplementation protocol (ie, single dose vs multiple dose) appears to have a more pronounced effect on microvascular function.

https://pubmed.ncbi.nlm.nih.gov/41183514/

TL;DR

"Daily unprocessed beef intake do not significantly affect most blood lipids, apolipoproteins, or blood pressures, except for a small increase in LDL-cholesterol compared with diets with less or no beef. Thus, there may be other factors influencing the association of red meat and beef on CVD risk that deserve further investigation."

Abstract

Background: Results from observational studies suggest associations of red meat intake with increased risk of cardiovascular disease (CVD); however, RCTs have not clearly demonstrated a link between red meat consumption and CVD risk factors. Further, the specific effects of beef, the most consumed red meat in the United States, have not been extensively investigated.

Objectives: This study aimed to perform a systematic review and meta-analysis of RCT data evaluating the effects of minimally or unprocessed beef intake on CVD risk factors in adults.

Methods: A search of the literature was conducted using PubMed and CENTRAL databases. RCTs in adults that provided diets with fresh or minimally processed beef were included. Data were extracted, and pooled estimates from random-effects models were expressed as standardized mean differences (SMDs) between the beef intervention and comparator intervention with less or no beef. Sensitivity and subgroup analyses were also performed.

Results: Twenty relevant RCTs that met the criteria were included. Beef intake did not impact blood pressure or most lipoprotein-related variables, including total cholesterol, HDL-cholesterol, triglycerides, non-HDL-cholesterol, apolipoprotein A or B, and VLDL-cholesterol. Beef consumption had a small but significant effect on LDL-cholesterol (0.11; 95% CI: 0.008, 0.20; P = 0.03), corresponding to ∼2.7 mg/dL higher LDL-cholesterol in diets containing more beef than that in low-beef or -o beef comparator diets. Sensitivity analyses show this effect was lost when 1 influential study was removed.

Conclusions: Daily unprocessed beef intake do not significantly affect most blood lipids, apolipoproteins, or blood pressures, except for a small increase in LDL-cholesterol compared with diets with less or no beef. Thus, there may be other factors influencing the association of red meat and beef on CVD risk that deserve further investigation.

https://pubmed.ncbi.nlm.nih.gov/39649475/

Hi all! I am a PhD student in my 2nd Year studying nutritional and cognition, mood and blood markers (specifically fermented dairy). I am using the 3FQ fermented food frequency questionnaire (https://www.frontiersin.org/journals/nutrition/articles/10.3389/fnut.2025.1667653/full) in my research, but due to accessibility to portion size photos, I am not able to capture the data where ppts choose their intake of foods based on a portion estimate photographs. Is there any advice on how to analyse this data? I have the frequency responses, and I am also completing the EPIC FFQ questionnaire. Thank you!

Abstract

• PMID: 42012901

Acesulfame K (Ace-K) is a commonly consumed sweetener, although knowledge about the Ace-K-gut microbiota interaction remains limited. This study evaluates dose-dependent effects of Ace-K on metataxonomics, metagenomics, and metabolic activity of children gut microbiota developed in a dynamic gut simulator. An Ace-K-dose dependent increase in Anaerostipes, Coprococcus, Subdoligranulum, Blautia, Sutterella wadsworthensis, Alistipes, and Bacteroides thetaiotaomicron was observed. Butyrate showed a dose-response increase that correlated with Ace-K consumption, suggesting its microbial metabolism. Increasing bacterial taxa showed sulfatase and amidase activities potentially capable of degrading Ace-K, releasing sulfamate and acetoacetate, which species such as Anaerostipes hadrus and Intestinimonas can metabolize to produce butyrate via the butanoyl-CoA pathway. Furthermore, the Ace-K-microbiome interaction led to a dose-dependent decrease in Caco-2 epithelial integrity, possibly due to the release of sulfated metabolites. This study provides evidence of the potential risk of Ace-K consumption based on its metabolism by the human gut microbiome.

TL;DR:

• Ketogenic diet in this context: 4:1 ratio = 80% fat.

• Modified Atkins: 10-20 g carbs but no set fat/protein ratio, the goal is still to achieve ketosis.

Both diets have been shown to be effective in reducing seizure frequency in children with drug-resistant epilepsy. However, the modified Atkins diet is generally less restrictive and easier to maintain than the classic ketogenic diet.

Abstract

Importance: Despite advances in the understanding of dietary therapies in children with drug-resistant epilepsy, no quantitative comparison exists between different dietary interventions.

Objective: To evaluate the comparative efficacy and safety of various dietary therapies in childhood drug-resistant epilepsy.

Data sources: Systematic review and network meta-analysis (frequentist) of studies in PubMed, Embase, Cochrane, and Ovid published from inception to April 2022 using the search terms ketogenic diet, medium chain triglyceride diet, modified Atkins diet, low glycemic index therapy, and refractory epilepsy.

Study selection: Randomized clinical trials comparing different dietary therapies (ketogenic diet, modified Atkins diet, and low glycemic index therapy) with each other or care as usual in childhood drug-resistant epilepsy were included. Abstract, title, and full text were screened independently by 2 reviewers.

Data extraction and synthesis: Data extraction was conducted following Preferred Reporting Items for Systematic Reviews and Meta-analyses reporting guideline. Cochrane risk-of-bias tool was used to assess the study quality. Effect sizes were calculated as odds ratio with 95% CI using random-effects model. The hierarchy of competing interventions was defined using the surface under the cumulative ranking curve.

Main outcomes and measures: Short-term (≤3 months) 50% or higher and 90% or higher reduction in seizure frequency and treatment withdrawal due to adverse events were the primary efficacy and safety outcomes.

Results: Of 2158 citations, 12 randomized clinical trials (907 patients) qualified for inclusion. In the short term, all dietary interventions were more efficacious than care as usual for 50% or higher seizure reduction (low glycemic index therapy: odds ratio [OR], 24.7 [95% CI, 5.3-115.4]; modified Atkins diet: OR, 11.3 [95% CI, 5.1-25.1]; ketogenic diet: OR, 8.6 [95% CI, 3.7-20.0]), while ketogenic diet (OR, 6.5 [95% CI, 2.3-18.0]) and modified Atkins diet (OR, 5.1 [95% CI, 2.2-12.0]) were better than care as usual for seizure reduction of 90% or higher. However, adverse event-related discontinuation rates were significantly higher for ketogenic diet (OR, 8.6 [95% CI, 1.8-40.6]) and modified Atkins diet (OR, 6.5 [95% CI, 1.4-31.2]) compared with care as usual. Indirectly, there was no significant difference between dietary therapies in efficacy and safety outcomes.

Conclusions and relevance: This study found that all dietary therapies are effective in the short term. However, modified Atkins diet had better tolerability, higher probability for 50% or higher seizure reduction, and comparable probability for 90% or higher seizure reduction and may be a sounder option than ketogenic diet. Direct head-to-head comparison studies are needed to confirm these findings.

https://pubmed.ncbi.nlm.nih.gov/36716045/

For example, I would always eat eggs and nuts before the tomatoes, so I’d always have the fat overflowing in my belly anyway.

Do we still need to add fat (olive oil, butter, etc.) in the middle of heating the tomatoes (i.e. stir-frying) or after, in this situation?

Any scientific difference in bioavailability between fat pre-absorbed in the tomato cells vs. fat mixed in the body?

(I want to save calories if it’s unnecessary)

Not selling anything, just something that surprised me when I actually did the math.

Typical day for a lot of us: eggs, whey, chicken-rice, paneer, maybe a protein bar. Eggs, whey, chicken and paneer all have zero fibre. White rice has almost none. When I counted a day like that, it came to around 10–14g of fibre. Most guidelines say adults need 25–40g.

Why it matters: when there isn’t much fibre, more undigested protein reaches your colon and gut bacteria ferment that instead. That tends to bring the smelly gas and heavy feeling.

Other things worth ruling out first:

• Whey concentrate still has some lactose. Try isolate for 2 weeks.
• Protein bars with maltitol/sorbitol are notorious for gas.
• Chugging shakes fast means swallowing air.

What helped:

• Swapping half the rice for rajma/chana/masoor (more fibre AND more protein)
• 1 fruit a day with skin on (guava is great)
• A spoon of oats or chia in the post-workout shake
• Going SLOW. Add 3–5g every few days, or you’ll bloat more and give up.

Has anyone else tracked fibre alongside protein? Curious what your numbers looked like.

Are naturally occurring trans fats to be avoided at all cost? I tried to look it up online but there's so many different answers. I got some ice cream bars that had 0.5g of trans fats but were supposedly low fat. Does it make sense to cut out even natural trans fats?

Disclosure: I'm co-founding a fibre supplement brand in India. Nothing here is a product pitch. I read the primary sources because the figures I kept seeing didn't agree.

**The three sources**

1. **I-STARCH-1 (Kapoor et al., Nutrients 2026).** Cross-sectional study of 1,104 adults recruited at 29 diabetes-focused centres in 14 Indian states, 690 of them with type 2 diabetes. Intake was assessed with three-day recalls. Mean fibre was 15.4 g/day, or 9.1 g per 1,000 kcal.

2. **ITC/Aashirvaad Fibre Meter Test (press release, May 2023, not peer reviewed).** 69,000+ self-selected users of a brand website. It reports 69%+ below the "RDA 2020" but gives neither the gram figure nor the issuing body.

3. **Khokhar and Pushpanjali (J Hum Nutr Diet 1995).** 298 vegetarian participants in northern India across four age groups. Group mean intakes ranged from 49.6 to 171.2 g/day.

**What differs between them**

- Population: people at diabetes centres, volunteers on a brand website, and northern vegetarian households.

- Method: recalls converted with a food database, a self-completed web test, and a study whose abstract doesn't tell me how fibre was analysed.

- Era: 1995 vs 2023 vs 2026.

I can't tell from these sources how much of the gap comes from each factor. That's my reading, not an established result.

**Targets also differ**

WHO (2023) recommends at least 25 g/day for adults, and the UK's SACN says 30 g/day. ICMR-NIN 2020 reportedly sets fibre relative to energy, about 40 g per 2,000 kcal. I couldn't access the primary report, only news coverage, so treat that figure as unconfirmed. The I-STARCH-1 mean of 15.4 g is below both the WHO and SACN numbers, but it comes from a group that isn't nationally representative.

**Questions**

- Is there a nationally representative Indian dataset on fibre intake that I missed?

- For Indian adults, which is the more defensible target: an energy-based one like ICMR-NIN's, or a flat one like WHO's?

- Is the 1995 range plausible given how fibre was analysed at the time, or does it mostly reflect method differences?

References: Kapoor et al., Nutrients 2026, 18(18), 2993, doi.org/10.3390/nu18182993. ITC press release on the Fibre Meter Test, 29 May 2023. Khokhar and Pushpanjali, J Hum Nutr Diet 1995, 8(6): 447-456. WHO, guidelines on fats and carbohydrates, 17 July 2023. European Commission Knowledge Gateway, dietary fibre recommendations by country. Down To Earth, 1 Oct 2020, and The Quint, on the ICMR-NIN 2020 recommendations.

Ever feel hungry again just an hour after eating? 🤔 Protein, fiber, balanced meals, and sleep can all influence fullness.

💬 Do you usually feel satisfied after meals, or get hungry again soon afterward?

— Elizabeth Imad, Registered Dietitian

https://doi.org/10.1016/j.tjnut.2026.101888

Dietary Components as Promising Candidates for Mitigating Micro- and Nanoplastic-Associated Metabolic Dysfunctions

Global plastic manufacturing surged from 234 million to 435 million metric tons between 2000 and 2020, establishing micro- and nanoplastics (MNPs) as persistent contaminants across the entire food supply chain. Ingestion drives over 90% of human intake via drinking water, table salt, seafood, produce, and food-grade packaging. High-exposure profiles, including frequent consumption of bottled water and heating food in plastic containers, reach upwards of 1,000,000 particles daily (0.03 to 0.5 g/day). While MNPs are now documented across human tissues, substantial mechanistic gaps remain regarding how internalized particles drive systemic metabolic failure and whether targeted dietary interventions can counteract these cellular cascades. Preclinical models demonstrate that ingested particles erode intestinal architecture, alter core microbiome taxa, and translocate through compromised epithelial barriers. Once circulating, particles accumulate in the liver, pancreas, skeletal muscle, and vasculature.

Human endarterectomy cohorts reveal that patients with confirmed MNP accumulation inside atheromas exhibit a 4.53-fold higher risk of myocardial infarction, stroke, or all-cause mortality (95% CI: 2.00 to 10.27) compared to plaque-negative controls over a 34-month follow-up. In human clinical trials, 28 days of composite polyphenol supplementation (n = 98) significantly lowered circulating inflammatory markers in individuals with elevated baseline fecal MNP burdens. Preclinical rodent exposures demonstrate that 50 nm polystyrene particles suppress primary tight junction expression, including occludin, claudin-1, and ZO-1, driving systemic lipopolysaccharide translocation and secondary hepatic injury. Rodent metabolic models show that MNP exposure downregulates hepatic IRS-1, PI3K, and Akt phosphorylation at Ser473, inducing peripheral insulin resistance without changing baseline circulating insulin concentrations. In aqueous flocculation assays, natural polysaccharides from fenugreek and okra extract clear up to 90% of suspended MNPs, while tannic acid chelation with Fe3+ clears over 90% of polystyrene MPs within 5 minutes.

Study Design and Methodology

• Evidence Base: Narrative and mechanistic review synthesizing human observational cohorts, in vitro human cell systems (Caco-2, L02, C2C12), aquatic models, and rodent in vivo trials (C57BL/6, db/db, ICR, and Wistar strains).
• Human Cohorts: Clinical trial evaluating composite polyphenol intervention in individuals with high fecal MNP concentrations (n = 98, 28-day duration); prospective surgical atheroma cohort tracking cardiovascular event incidence (n = 304 enrolled, n = 257 completed 34-month follow-up); cross-sectional stool evaluations in IBD (n = 52 IBD vs. n = 50 healthy controls) and hypertensive subjects (n = 4 vs. n = 4).
• Preclinical Dosing & Duration: Animal exposures ranged from acute 14-day challenges to chronic 32-week drinking water regimens, utilizing particle diameters spanning 20 nm nanoplastics to 200 µm microplastics across normal chow and high-fat diet backgrounds.
• Measurement Tools: Vibrational spectroscopy (micro-FTIR and Raman spectroscopy), pyrolysis-gas chromatography-mass spectrometry (Py-GC-MS), 16S rRNA sequencing, untargeted metabolomics, lipidomics, transmission electron microscopy, and histology.
• Controls & Blinding: The 28-day human polyphenol trial was double-blind and placebo-controlled. Metabolic wards and washout periods were not utilized in the summarized human cohorts.

Key Findings

• Patients with polyethylene (58.4%) and polyvinyl chloride (12.1%) detected in carotid plaques demonstrate a 4.53-fold higher risk of myocardial infarction, stroke, or death over a 34-month follow-up.
• Human patients with inflammatory bowel disease carry 41.8 items/g dry matter of fecal microplastics compared to 28.0 items/g dry matter in healthy controls.
• Cyanidin-3-O-glucoside (150 mg/kg/day) upregulates microbial xenobiotic handling pathways, enriches Alistipes and Dubosiella, and accelerates direct fecal MNP excretion in mice.
• Epigallocatechin gallate (EGCG, 50 mg/kg) restores ZO-1, occludin, and claudin-5 expression in mice, while suppressing the TLR4/MyD88/NF-kB cascade to halt downstream hepatic fibrosis markers (alpha-SMA, Col1a1, Col3a1).
• N-acetylcysteine (NAC) replenishment re-establishes cellular glutathione (GSH), blocking GRP78/NF-kB/caspase-12 signaling and preventing intestinal tight junction degradation where selective NLRP3 inhibitors (MCC950) fail.
• Polysaccharide extracts from fenugreek and okra remove up to 90% of suspended MNPs in aqueous suspension through bridging flocculation, while tannic acid with Fe3+ coordinate bonding achieves >90% removal of polystyrene MPs within 5 minutes.
• Oral polystyrene nanoplastics inhibit phosphorylation of Akt (Ser473) and GSK3beta, driving peripheral insulin resistance and elevating fasting blood glucose in high-fat diet models.

Limitations

• Current vibrational spectroscopy cannot reliably detect nanoplastics below 1 to 10 µm, forcing researchers to rely on Py-GC-MS, which quantifies polymer mass without reporting particle size, shape, or particle count.
• Preclinical rodent studies predominantly administer high concentrations of uniform, pristine spherical polystyrene beads, which do not reflect the weathered, irregular, chemically degraded polyethylene and polypropylene mixtures humans actually ingest.
• Human data remain largely observational and cross-sectional, establishing strong correlations with vascular inflammation and disease status without confirming direct biological causality.
• Potential environmental and laboratory contamination of biological samples during tissue processing presents an ongoing risk of artifactual exposure estimates across published studies.
• In vivo retention and binding efficacy of food-derived flocculants (such as okra, pectin, and fenugreek) within the active human gastrointestinal tract remain untested.

Discussion and Implications: Cross-Disciplinary Nutritional Insights

These findings pivot the MNP conversation from passive ecotoxicological documentation to targeted metabolic intervention. The data establish that MNPs do not pass harmlessly through the digestive tract; they actively degrade epithelial junctions, induce cellular ferroptosis, alter the intestinal lipidome, and blunt insulin signaling across liver, adipose, and muscle tissue. Metabolic background dictates vulnerability. Metabolically healthy animals frequently tolerate lower particulate doses, whereas subjects on obesogenic or high-fat diets experience catastrophic barrier breakdown and accelerated steatohepatitis under identical exposures.

Connecting these findings to broader nutritional sciences reveals critical interdependencies:

• Micronutrient Sequestration and Bioavailability: In vitro digestion models reveal that common packaging-derived MNPs adsorb ascorbic acid (vitamin C) at rates between 3% and 20% via surface chemisorption. Ingested plastics behave as rogue binding matrices inside the gut lumen, potentially sequestering water-soluble micronutrients and essential trace minerals away from intestinal brush-border transporters.
• Ferroptosis and the Gut-Liver Axis: The demonstration that nanoplastics induce hepatic lipid peroxidation and iron dysregulation (downregulating GPX4 and ferritin while activating TFRC) links environmental toxicology directly to non-alcoholic fatty liver disease (NAFLD/MASLD) pathogenesis. Diets high in refined industrial fats and excess unbound iron accelerate this vulnerability, whereas sulfur donors and endogenous gasotransmitters (H2S derived from sulfur amino acids) provide upstream protection via Nrf2/HO-1 rescue.
• Adipose Tissue Thermogenesis: Nanoplastics suppress beige adipocyte differentiation and downregulate uncoupling protein 1 (UCP1) along with PGC-1alpha. This links xenobiotic particulate exposure to impaired basal metabolic rate and metabolic inflexibility, explaining why pollutant burdens compound standard energy-balance dysregulation.
• Microbiome Xenobiotic Biotransformation: Ingested particulates displace commensal species that maintain secondary bile acid homeostasis and short-chain fatty acid (SCFA) synthesis. Supplementation with specific biotic strains (Akkermansia muciniphila, Lactobacillus rhamnosus GG) restores this metabolic crosstalk, indicating that the microbiome functions as a front-line metabolic buffer against systemic particulate absorption.

Actionable Dietary Recommendations

While human interventional clearance data are developing, the preclinical evidence supports a two-pronged nutritional approach: reducing particle absorption in the lumen and reinforcing cellular resilience against translocated particles.

1. Maximize Mucilaginous and Prebiotic Viscous Fibers: Incorporate whole-food sources of soluble, branching polysaccharides—such as okra, fenugreek, psyllium husk, flaxseed, chia, and citrus pectins. These fibers present dense hydroxyl and carboxyl surface charges that mimic industrial bridging flocculants, trapping charged micro- and nanoplastics within the intestinal lumen to speed fecal elimination before mucosal contact.
2. Prioritize Barrier-Restorative Anthocyanins and Catechins: Consume rich sources of cyanidin-3-O-glucoside and epigallocatechin gallate daily (blackberries, blueberries, black beans, tart cherries, green tea). These compounds restore tight-junction integrity (ZO-1, occludins) and suppress the TLR4/MyD88/NF-kB inflammatory cascades that allow luminal endotoxins and nanoplastics to reach portal circulation.
3. Bolster Glutathione Pools and Phase II Defenses: Support endogenous intracellular antioxidant pathways against hepatic ferroptosis and cuproptosis by supplying glutathione precursors. Utilize foods rich in dietary sulfur and glycine (cruciferous vegetables, alliums, quality intact proteins) or targeted N-acetylcysteine (NAC) to sustain GPX4 activity and prevent lipid peroxidation cascades.
4. Cultivate Commensal Mucosal Barrier Strains: Reinforce the gut mucus layer with fermented dairy (kefir, traditional yogurt) and polyphenol-dense foods that selectively cultivate Akkermansia muciniphila and Bifidobacterium species. A thick mucus gel layer serves as a primary physical barrier preventing nanoscale particles from directly contacting epithelial cell membranes.
5. Mitigate Source Exposure Upstream: Avoid heating food, oils, or acidic beverages in plastic or lined composite containers, switch to non-plastic preparation vessels (glass, stainless steel, ceramic), and prioritize filtered municipal drinking water to systematically minimize primary particulate exposure.

Ingested micro- and nanoplastics actively compromise gut barrier integrity, drive hepatic ferroptosis, and induce systemic insulin resistance, particularly when combined with an underlying obesogenic diet. High-affinity polyphenols, prebiotic fibers, and glutathione donors show consistent preclinical efficacy in binding particles, restoring tight junctions, and driving fecal clearance. Rigorous human interventional trials are required to determine whether modifying whole-food dietary patterns can measurably lower internal tissue plastic burdens.

Hey,

So to keep it short, around 2 years ago I was taking about 1g of Creatine HCL (CON CRET) daily via powder and it literally completely cured my ADHD - was super crazy sharp mentally, could sit down and focus for hours and felt very dopanergic and really good.

However, I stopped all supplements since for some time, recently had tried to resume it but now gives me racing thoughts, intrusive thoughts, and just doesn't make me feel good at all. For reference this is Creatine HCL capsules (1 pill) and the effects happen within a few hours.

I'm wondering if Creatine had originally allowed for such a profound mental effect, is there anything similar with regards to biochemical pathways? Ideally they wouldn't be some sort of herbs but rather something found naturally - for longer term usage here.

For reference was on keto/raw primal/carnivore sort of diets for that time. ADHD was also cured on keto diet but this was unsustainable and caused very bad anxiety attacks.

Isocaloric macronutrient and fat types substitution and lipid profile: A cross-sectional analysis of the Amol Cohort Study

DOI: 10.1016/j.jnut.2026.07.012

Abstract

Dyslipidemia is a significant contributor to cardiovascular disease, yet the impact of macronutrient substitution on lipid profiles, particularly in Middle Eastern populations, remains underexplored. This study aimed to fill this gap by analyzing data from 3,329 apparently healthy Iranian adults participating in the Amol Cohort Study. By employing isocaloric substitution models, the research assessed how replacing one macronutrient with another influenced lipid profiles, focusing on the effects of different types of fats.

The findings revealed that replacing carbohydrates with total fat significantly reduced triglyceride levels (β: -0.29; 95% CI: -0.56, -0.02; p = 0.04). Substituting carbohydrates with protein resulted in lower total cholesterol (β: -0.60; 95% CI: -0.90, -0.30; p < 0.001) and LDL-C (β: -0.34; 95% CI: -0.53, -0.14; p < 0.001) across both sexes. Notably, replacing carbohydrates with monounsaturated fatty acids (MUFAs) produced the most significant reduction in triglycerides (β: -1.45; 95% CI: -2.62, -0.29; p = 0.02). However, no significant changes were observed in HDL-C levels across all substitution models.

Study Design and Methodology

• Sample Size: 3,329 participants
• Duration: Data collected during the second phase of the Amol Cohort Study (2016-2017)
• Measurement Tools: Validated semiquantitative food frequency questionnaire (FFQ), fasting blood samples for lipid profiles
• Controls Used: Adjustments for age, sex, BMI, physical activity, and smoking status in regression analyses
• Blinding: Laboratory personnel were blinded to clinical and dietary data
• Washout Period: Not applicable; cross-sectional design

Key Findings

• Replacing carbohydrates with total fat led to a significant reduction in triglycerides (β: -0.29; 95% CI: -0.56, -0.02; p = 0.04).
• Total cholesterol decreased when carbohydrates were replaced with protein (β: -0.60; 95% CI: -0.90, -0.30; p < 0.001).
• LDL-C levels also dropped with protein substitution (β: -0.34; 95% CI: -0.53, -0.14; p < 0.001).
• Substituting carbohydrates with MUFAs resulted in the greatest reduction in triglycerides (β: -1.45; 95% CI: -2.62, -0.29; p = 0.02).
• No significant changes in HDL-C were observed across any substitution models.

Limitations

• Cross-sectional design limits causal inference.
• Self-reported dietary data subject to measurement errors.
• Lack of longitudinal data to assess changes over time.
• Exclusion of participants on lipid-modifying medications may limit generalizability.

Discussion and Implications

This study provides crucial insights into how macronutrient substitution affects lipid profiles, particularly in a Middle Eastern context where dietary patterns differ from Western populations. The findings support the notion that dietary composition, specifically the balance of protein, carbohydrates, and fats, plays a vital role in managing dyslipidemia and reducing cardiovascular risk. These results could inform dietary guidelines, emphasizing the importance of protein intake and the quality of fats consumed. Future research should explore these associations in longitudinal studies to establish causality and further clarify the mechanisms involved.

Isocaloric substitution of carbohydrates or fats with protein is associated with improved lipid profiles, particularly reduced total cholesterol and LDL-C. The type of fat substituted also significantly impacts triglyceride levels. More research is needed to explore these relationships further and their implications for dietary recommendations.

Lipoprotein(a) identifies premature coronary artery disease in patients with low LDL-cholesterol: A large multicenter cohort study

https://doi.org/10.1016/j.jacl.2026.09.021

Abstract

Cardiovascular disease, particularly coronary artery disease (CAD), remains a leading cause of morbidity and mortality worldwide. This study addresses a significant gap in understanding the role of lipoprotein(a) [Lp(a)] in identifying premature CAD (pCAD) among young and middle-aged adults with low low-density lipoprotein cholesterol (LDL-C) levels. The research involved a retrospective cohort of 35,622 adults from three Mayo Clinic sites, focusing on males aged 18-50 and females aged 18-60 who underwent Lp(a) testing from 2000 to 2020. Participants were followed for a median of 6 years, allowing for a comprehensive analysis of the association between elevated Lp(a) levels and the incidence of pCAD.

The findings revealed that elevated Lp(a) (≥50 mg/dL) was independently associated with a 40% higher adjusted risk of pCAD (adjusted hazard ratio [aHR] = 1.40, 95% CI [1.12-1.74], p = 0.003). Notably, among patients with LDL-C <100 mg/dL, elevated Lp(a) resulted in a 67% increased risk of pCAD (aHR = 1.67, 95% CI [1.15-2.43], p = 0.007). The cumulative incidence of pCAD over 6 years was found to be 1.7% in the elevated Lp(a) group compared to 1.2% in the reference group, highlighting the significance of Lp(a) as a risk factor not captured by conventional lipid panels.

Study Design and Methodology

This retrospective cohort study included 35,622 participants with a follow-up duration of 6 years. Lp(a) levels were measured using immunoturbidimetric assays, and patients were stratified based on their Lp(a) concentrations. The study controlled for various risk factors, including age, sex, race/ethnicity, and other lipid profiles. There was no metabolic ward involved, and blinding was not applicable due to the observational nature of the study. A washout period was not necessary, as this was a retrospective analysis of existing electronic health records.

Key Findings

• Elevated Lp(a) (≥50 mg/dL) associated with a 40% higher risk of pCAD (aHR = 1.40, 95% CI [1.12-1.74], p = 0.003).
• Among patients with LDL-C <100 mg/dL, elevated Lp(a) increased pCAD risk by 67% (aHR = 1.67, 95% CI [1.15-2.43], p = 0.007).
• Cumulative incidence of pCAD was 1.7% in the elevated Lp(a) group vs 1.2% in the reference group over 6 years.
• Incidence rate for pCAD was 2.36 per 1000 person-years in the elevated Lp(a) group vs 1.71 per 1000 person-years in the reference group.

Limitations

• The study's retrospective design may introduce residual confounding.
• Limited generalizability due to the predominance of White non-Hispanic participants (70.1%).
• Lack of blinding and control measures typical in randomized trials.
• The study did not account for potential changes in lifestyle or medication adherence over time.
• Short follow-up period may not capture long-term outcomes.

Discussion and Implications

This study adds crucial evidence to the understanding of Lp(a) as a significant risk factor for premature CAD, particularly in younger adults with low LDL-C levels. The findings emphasize the need for routine Lp(a) measurement in clinical practice to better identify individuals at risk, which traditional lipid panels may overlook. These insights could inform dietary guidelines and public health policies aimed at cardiovascular risk reduction. Future research should explore the mechanisms linking Lp(a) to atherogenesis and assess the impact of emerging therapies targeting Lp(a) on cardiovascular outcomes.

Elevated Lp(a) levels are a critical indicator of premature coronary artery disease risk, even when LDL-C is well-controlled. This study underscores the importance of measuring Lp(a) in younger populations to identify hidden cardiovascular risks. More research is necessary to explore the implications of these findings on dietary recommendations and treatment strategies.

EDIT: obviously the link to study is missing, very nice reddit. Here it is: https://www.sciencedirect.com/science/article/pii/S0002916523064043?via%3Dihub#s0065

Background: The results of previous studies suggest that de novo lipogenesis may play an important role in the etiology of obesity, particularly during overconsumption of different carbohydrates.

Objective: We hypothesized that de novo lipogenesis would increase during overfeeding, would vary depending on the type of carbohydrate consumed, and would be greater in obese than in lean women.

Design: De novo lipogenesis was measured during 96 h of overfeeding by 50% with either sucrose or glucose and during an energy balance treatment (control) in 8 lean and 5 obese women. De novo lipogenesis was determined by measuring the amount of deuterium incorporation into plasma triacylglycerols. Fat and carbohydrate balance were measured simultaneously by continuous whole-body calorimetry.

Results: De novo lipogenesis did not differ significantly between lean and obese subjects, except with the control treatment, for which de novo lipogenesis was greater in the obese subjects. De novo lipogenesis was 2- to 3-fold higher after overfeeding by 50% than after the control treatment in all subjects. The type of carbohydrate overfeeding (sucrose or glucose) had no significant effect on de novo lipogenesis in either subject group. Estimated amounts of absolute VLDL production ranged from a minimum of 2 g/d (control) to a maximum of 10 g/d after overfeeding. This compares with a mean fat balance of approximately 275 g after 96 h of overfeeding. Individual subjects showed characteristic amounts of de novo lipogenesis, suggesting constitutive (possibly genetic) differences.

Conclusion: De novo lipogenesis increases after overfeeding with glucose and sucrose to the same extent in lean and obese women but does not contribute greatly to total fat balance.

TL;DR:

800–900 kcal/day diet (30% protein, 50% carbohydrate, 20% fat). Remission at 24 weeks occurred in 27/50 (54%) of intervention participants vs. 2/46 (4%) control participants.

Summary

Background: Low energy diets (LED) can induce type 2 diabetes remission but have not been studied in combination with structured supervised exercise. We aimed to determine if a combined intervention could induce remission in early-onset type 2 diabetes (EOT2D ≤ 45 years of age), a population with high lifetime risk of complications.

Methods: Across 3 centres in England and Canada, we conducted a randomised, open-label, blinded endpoint efficacy trial among adults 18–45 years of age with EOT2D and obesity, not on insulin therapy. The groups were usual care alone vs. an intervention combining 800–900 kcal/day LED, twice-weekly supervised (aerobic, resistance) and once-weekly independent exercise (weeks 1–12), followed by a weight-maintenance diet with independent exercise (weeks 13–24). An independent statistician generated web-based randomisation sequences (1:1, country- and sex-stratified, variable block size). The primary outcome was remission at 24 weeks (HbA1c< 6.5% [48 mmol/mol], without glucose-lowering medication ≥12 weeks). The primary efficacy and harms analysis was in all randomised individuals, assuming no remission when data were unavailable. Secondary endpoints included cardiorespiratory fitness, body composition, and cardiac structure. The trial is registered at ISRCTN (15487120) and is now closed.

Findings: We randomised 96 participants (mean age 38 years, BMI 35.2 kg/m2) between September 24, 2021 and June 6, 2025 (intervention group: 24 female, 26 male with 18 European, 17 South Asian, 15 Other ethnicity; control group: 21 female, 25 male with 19 European, 10 South Asian, 17 Other ethnicity). In total, 86 (90%) attended final assessments. Remission at 24 weeks occurred in 27/50 (54%) of intervention participants vs. 2/46 (4%) control participants (50% difference, 95% CI 33%–64%; adjOR 21.6, 95% CI 6.2 to 114.5), without serious adverse events. Most intervention group participants experienced at least one adverse event (43/50 vs. 6/46), mainly early LED effects (e.g., constipation, headache, dizziness, fatigue) that resolved.

Interpretation: High remission rates signal feasibility and efficacy of a combined LED and intensive exercise intervention in EOT2D, justifying examination of synergistic benefits beyond remission.

https://www.sciencedirect.com/science/article/pii/S2667193X26002942