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When Better Blood Sugar Comes at the Heart’s Expense

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dr Karunia Valeriani Japar

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Keywords: All-Cause Mortality, Apolipoprotein B, Atherogenic Dyslipidemia, Cardiovascular Disease, Continuous Glucose Monitoring, Insulin Resistance, Ketogenic Diet, LDL Cholesterol, Lean Mass Hyper-Responder, Lipid Profile, Low-Carbohydrate Diet, Metabolic Health, Plant-Based Diet, Precision Nutrition, Saturated Fat

Introduction

Low-carbohydrate and ketogenic diets have gained substantial global popularity as strategies for rapid weight loss, improved glycemic control, and broader “metabolic optimization,” particularly among individuals and communities focused on biohacking and the prevention or remission of type 2 diabetes. Short-term clinical trials consistently demonstrate favourable changes in body weight, fasting glucose, insulin, and, in some cases, triglyceride concentrations, findings that are often interpreted as evidence that these dietary patterns are inherently cardioprotective. Yet, emerging long-term cohort data and mechanistic studies depict a more nuanced reality, in which certain low-carbohydrate patterns, especially those characterized by high intakes of animal protein and saturated fat may increase cardiovascular and all-cause mortality despite these metabolic improvements. This apparent paradox raises a central question for clinicians and health-technology platforms: can a dietary pattern meaningfully improve insulin resistance and body composition while at the same time increasing the risk of atherosclerotic cardiovascular disease (ASCVD)?

Large prospective cohorts and pooled analyses indicate that both very low and very high carbohydrate intakes are associated with increased mortality, with the lowest risk typically observed at moderate carbohydrate intakes of approximately 50–55% of total energy. Within the low-carbohydrate spectrum, patterns emphasizing animal-derived sources of protein and fat are consistently linked to higher total and cardiovascular mortality, whereas plant-focused low-carbohydrate patterns appear to be associated with lower cardiovascular and all-cause mortality. Complementary evidence from randomized and controlled feeding trials shows that ketogenic low-carbohydrate, high-fat diets frequently raise low-density lipoprotein cholesterol (LDL-C) and apolipoprotein B (ApoB), indicating an increased burden of atherogenic lipoprotein particles in circulation. Taken together, these observations suggest that clinical and digital health decision-making should move beyond simplistic “carbs versus fat” framing and instead prioritize diet quality, individual lipid responses, and long-term cardiovascular risk when recommending low-carbohydrate strategies for metabolic health.

The Epidemiological Signal: Low Carb and Cardiovascular Outcomes

Multiple large cohort studies and meta-analyses have evaluated the association between low-carbohydrate intake and long-term health outcomes, providing a critical population-level signal that informs clinical risk–benefit assessment. A systematic review and meta-analysis of 17 observational studies, incorporating 272,216 participants and 15,981 deaths, demonstrated that individuals with the highest low-carbohydrate scores had a significantly increased risk of all-cause mortality, with a pooled relative risk of 1.31 (95% CI 1.07–1.59) compared with those with the lowest scores, while cardiovascular mortality and incident cardiovascular disease were not significantly different. These findings suggest that, although low-carbohydrate diets may offer short-term metabolic advantages, their widespread adoption at the population level could carry a measurable penalty in terms of overall survival. Supporting this concern, a large European cohort with a median follow-up of 15.9 years reported that participants in the lowest-carbohydrate quartile had substantially higher risks of overall (32%), cardiovascular (50%), cerebrovascular (51%), and cancer (36%) mortality compared with those consuming higher amounts of carbohydrate, even after multivariable adjustment [1,2].

Prospective data from the Atherosclerosis Risk in Communities (ARIC) cohort, combined with a meta-analysis of external cohorts, further refine this signal by demonstrating a U-shaped relationship between carbohydrate intake and mortality. In ARIC, which followed participants for a median of 25 years and documented 6,283 deaths, the lowest mortality risk was observed at carbohydrate intakes of approximately 50–55% of total energy, with increased mortality at both low (<40%) and high (>70%) carbohydrate intakes. Importantly, substitution analyses showed that replacing carbohydrate with animal-derived fat and protein was associated with higher mortality, whereas replacing carbohydrate with plant-derived fat and protein was associated with lower mortality, highlighting the central role of food source and diet quality rather than carbohydrate quantity alone. Asian cohort data mirror these patterns: a large Japanese study of more than 90,000 adults reported a U-shaped association between low-carbohydrate diet scores and both total and cardiovascular mortality, with particularly adverse outcomes when low-carbohydrate intake was accompanied by higher consumption of animal protein and fat and more favourable outcomes when plant proteins and fats predominated. While these observational findings cannot establish causality and are subject to residual confounding, their consistency across diverse populations supports the conclusion that very low-carbohydrate, animal-based dietary patterns may incur long-term cardiovascular and mortality risks, even when they produce desirable changes in weight and glycemic control in the short term [1,2,3,4,5,6].

Beyond “Glucose Numbers”: The Atherogenic Lipoprotein Response

Alterations in lipoprotein number and composition appear to be a central mechanism by which low-carbohydrate, high-fat diets may increase cardiovascular risk, even when glycemic indices improve. In a randomized, controlled crossover feeding trial of 17 healthy, young, normal-weight women, four weeks of a ketogenic low-carbohydrate, high-fat diet increased LDL-C in every participant, with a mean treatment effect of 1.82 mmol/L compared with a control diet. This intervention also raised ApoB, non-HDL cholesterol, and both small dense and large buoyant LDL subfractions, indicating an overall expansion of the atherogenic lipoprotein pool rather than a benign “particle size shift.” Notably, these changes occurred despite concurrent reductions in fasting glucose and insulin, underscoring that favourable glycemic responses do not preclude the development of a more atherogenic lipid profile [7,8].

Beyond controlled trials, observational series and case reports describe individuals developing marked hypercholesterolemia on ketogenic or very low-carbohydrate diets, with LDL-C concentrations sometimes exceeding 250–400 mg/dL and parallel increases in ApoB, despite leanness, low triglycerides, and high HDL-C. This phenotype has been termed the “lean mass hyper-responder” and appears to occur disproportionately in metabolically healthy, lean individuals who adopt strict carbohydrate restriction, suggesting an interaction between baseline metabolic status, energy trafficking, and genetic predisposition. While some advocates argue that high HDL-C, low triglycerides, and absence of insulin resistance mitigate atherosclerotic risk in this group, Mendelian randomization, prospective cohort data, and randomized statin trials collectively support a causal relationship between cumulative exposure to ApoB-containing lipoproteins and ASCVD, regardless of HDL-C or triglyceride levels. Accordingly, expert commentary has emphasized that dramatic elevations in LDL-C and ApoB in the context of carbohydrate restriction should be regarded as potentially harmful until proven otherwise, rather than dismissed as a benign adaptation [9,10,11,12,13].

Importantly, these adverse lipid responses are heterogeneous and modulated by diet composition and individual biology. Controlled and mechanistic studies show that diets high in saturated fatty acids (SFA), from butter, cream, fatty red meats, and some cheeses consistently raise LDL-C and ApoB more than diets rich in monounsaturated and polyunsaturated fats from sources such as olive oil, nuts, seeds, and fatty fish. Case-based analyses of lean mass hyper-responders further highlight that shifting from SFA-rich ketogenic patterns toward unsaturated fat–dominant versions can substantially reduce LDL-C and ApoB without necessarily abandoning carbohydrate restriction altogether. Reflecting this evidence, the National Lipid Association and other expert groups have stressed that patients who develop significant LDL-C and ApoB elevations on low-carbohydrate diets should not be reassured solely by improvements in triglycerides, HDL-C, body weight, or glycemic markers. Instead, recommended management includes reducing saturated fat intake, increasing unsaturated fats, liberalizing carbohydrate intake when appropriate, reassessing ApoB and LDL particle number, and initiating lipid-lowering pharmacotherapy for those with persistently elevated atherogenic lipoprotein levels in line with standard dyslipidemia guidelines [7,11,13,14].

For AI-driven prevention programs and metabolic health platforms, an exclusive focus on glucose metrics, weight, and patient-reported energy or cognitive performance risks overlooking this atherogenic lipoprotein response as a critical long-term determinant of ASCVD. Many low-carbohydrate interventions are currently titrated based on CGM data, HbA1c, and body composition, with far less frequent monitoring of ApoB, LDL-C, non-HDL-C, and, where available, lipoprotein particle number. Given the emerging evidence that a subset of individuals experience large, diet-induced increases in ApoB on ketogenic and very low-carbohydrate diets, integrating routine lipid surveillance and automated alerts for concerning ApoB trajectories into digital protocols is essential to align short-term metabolic optimization with long-term cardiovascular safety [8,9,12,13,14,15].

Protein Source Matters: Animal vs Plant-Based Low-Carb Patterns

Epidemiological evidence indicates that the cardiovascular impact of low-carbohydrate diets depends strongly on whether the “replacement calories” come from animal- or plant-derived protein and fat, rather than on carbohydrate restriction alone. In the ARIC cohort and accompanying meta-analysis, substituting carbohydrates with animal-based protein and fat (e.g., beef, lamb, pork, chicken) was associated with an 18% higher all-cause mortality, whereas substituting with plant-based protein and fat (e.g., nuts, vegetables, whole grains) was associated with an 18% lower mortality risk. When low-carbohydrate diet scores were decomposed into animal-based and plant-based patterns, animal-based low-carbohydrate diets showed increased all-cause mortality, while plant-based low-carbohydrate diets were linked to significantly reduced all-cause and cardiovascular mortality, even at lower carbohydrate intakes. These findings underscore that the quality of the dietary pattern, fiber density, phytonutrient content, unsaturated versus saturated fat profile, and overall food matrix substantially modifies the health impact of carbohydrate restriction [3,6,16,17,18].

Similar patterns are observed in Asian populations. In a Japanese cohort with nearly three decades of follow-up (NIPPON DATA80), lower-carbohydrate, higher-protein diets were associated with increased total and cardiovascular mortality, particularly when protein and fat were derived predominantly from animal sources. More recent pooled analyses of plant-based versus animal-based low-carbohydrate diet scores confirm a U-shaped association between total carbohydrate intake and mortality, with the lowest risk at moderate carbohydrate intake and divergent outcomes at lower intakes depending on protein and fat source: animal-based low-carbohydrate scores tended to show neutral or higher mortality, whereas plant-based low-carbohydrate scores showed a linear reduction in all-cause and cardiovascular mortality with decreasing carbohydrate content. Together, these data suggest that adopting a “low-carb” label does not inherently confer cardiometabolic benefit; instead, cardioprotection appears to emerge when carbohydrate restriction is implemented within a plant-forward, unsaturated fat–rich dietary pattern [3,17,19,20,21].

The Swedish Women’s Lifestyle and Health cohort adds further nuance by examining the combined effect of reduced carbohydrate and increased protein intake. In this prospective study of 43,396 women followed for an average of 15.7 years, each 2-unit increase in a 20-point low-carbohydrate/high-protein score was associated with a 5% increase in incident cardiovascular disease, after adjustment for total energy intake, saturated and unsaturated fat, and multiple non-dietary confounders. A clear exposure–response pattern was observed: compared with women with the lowest scores (≤6), those with scores ≥16 had a 60% higher incidence of cardiovascular events. Although this study did not directly differentiate animal versus plant protein sources, background dietary patterns in Sweden suggest that the predominant protein source was animal-based, aligning with other cohorts in which animal-based low-carbohydrate patterns are linked to higher cardiovascular risk [5,21,22].

Collectively, these findings argue against simplistic narratives that low-carbohydrate diets are universally “good” or “bad” for cardiovascular health. Instead, they support a more nuanced conceptualization: low-carbohydrate patterns anchored in minimally processed plant foods, nuts, seeds, legumes (where tolerated), and unsaturated fats may confer cardiometabolic advantages, particularly when carbohydrate restriction replaces refined starches and added sugars. In contrast, low-carbohydrate patterns centered on processed meats, saturated fat–rich animal products, and ultra-processed “keto” foods may increase ASCVD risk, even in the presence of favourable changes in weight, glucose, or triglycerides by amplifying atherogenic lipoprotein burden and reducing dietary fiber and phytonutrient intake. For clinicians and AI health-tech platforms, this evidence supports prioritizing plant-forward low-carbohydrate designs and explicitly distinguishing between animal- and plant-based implementations when counselling patients or building decision-support algorithms [3,5,6,17,20,22].

Cardiometabolic Trade-Offs: Metabolic Flexibility, Insulin Resistance, and Vascular Health

Low-carbohydrate and ketogenic diets can produce substantial short- to medium-term improvements in key features of the metabolic syndrome, which partly explains their prominence in metabolic clinics and wellness programs. Randomized trials and meta-analyses in individuals with overweight, obesity, pre-diabetes, or type 2 diabetes demonstrate that carbohydrate restriction often reduces fasting glucose and insulin, lowers HbA1c, and improves indices of insulin resistance such as HOMA-IR, particularly when accompanied by energy restriction and weight loss. Very-low-calorie ketogenic interventions have also been shown to reduce visceral adipose tissue and intrahepatic fat more rapidly than isocaloric or modestly hypocaloric higher-carbohydrate diets, likely via reductions in hepatic insulin resistance, enhanced hepatic triglyceride hydrolysis, and increased ketone production. These adaptations can enhance metabolic flexibility, the capacity to switch between carbohydrate and fatty acid oxidation and, in some cases, allow for de-escalation of glucose-lowering medications in type 2 diabetes management. From a biohacking standpoint, improvements in continuous glucose monitoring (CGM) metrics, such as lower glycemic variability, reduced postprandial glucose excursions, and more time in range are often taken as direct proxies for cardiometabolic risk reduction [23,24,25,26,27,28,29,30].

Figure 1. Overview of the short-term metabolic benefits of the low carbohydrate diet (LCD) [24]

However, cardiometabolic health and atherosclerotic cardiovascular disease (ASCVD) risk are determined by a broader constellation of factors than glycemia and body weight alone. Vascular biology, cumulative exposure to ApoB-containing lipoproteins, systemic inflammation, blood pressure, and thrombosis pathways all contribute materially to ASCVD risk. Even in the setting of improved insulin sensitivity and weight loss, a persistent elevation in LDL-C and ApoB increases the flux of atherogenic particles across the endothelium, promoting subendothelial cholesterol retention, plaque formation, and, eventually, clinical events. Observational cohorts and pooled analyses indicate that both very low and very high carbohydrate intakes are associated with increased all-cause mortality, with the lowest risk typically seen at moderate carbohydrate intakes of approximately 50–55% of total energy. These U-shaped associations suggest that extreme macronutrient distributions, whether heavily skewed toward fat and protein or toward carbohydrate may compromise long-term vascular and overall health, despite improvements in selected intermediate biomarkers [1,3,7,13,24].

Conceptually, strict low-carbohydrate diets can be understood as shifting the dominant “metabolic load” from glucose and insulin dynamics toward lipid handling and lipoprotein trafficking. By substantially lowering carbohydrate intake, these diets reduce postprandial glycemic excursions and insulin demand but often increase reliance on dietary and endogenous fats, alter bile acid composition, and may raise LDL-C and ApoB, particularly when saturated fat intake is high. In some feeding trials of insulin-resistant individuals, low-carbohydrate diets enriched in saturated fat improved indices of insulin-resistant dyslipoproteinemia and inflammatory markers without raising LDL-C, highlighting that not all low-carbohydrate implementations produce atherogenic lipid profiles. Yet other randomized and observational data show that ketogenic, high-saturated-fat patterns can substantially increase LDL-C and ApoB in a subset of individuals, underscoring the need for individualized lipid surveillance rather than assuming uniform benefit. For preventive cardiometabolic care, the central aim should therefore be to optimize the entire cardiometabolic profile, including ApoB, blood pressure, inflammatory markers, liver health, and cardiorespiratory fitness rather than solely normalizing glucose or achieving weight loss [7,12,24,31].

In practice, this means that low-carbohydrate and ketogenic strategies should be implemented within a framework that routinely monitors both glycemic control and markers of vascular risk. Clinicians and AI-driven health platforms can leverage CGM and body composition data to capture short-term metabolic gains, while simultaneously tracking ApoB, LDL-C, non-HDL cholesterol, blood pressure, liver enzymes, and, when available, imaging or functional measures of vascular health. When patients exhibit robust improvements in HbA1c and visceral adiposity but also develop sustained elevations in ApoB or blood pressure, protocols should include clear pathways for dietary modification (e.g., reducing saturated fat, increasing unsaturated fats and fiber, liberalizing carbohydrates modestly), medication adjustment, or even transitioning to less extreme macronutrient distributions. Ultimately, aligning low-carbohydrate dietary interventions with long-term ASCVD prevention requires integrating metabolic flexibility and insulin sensitivity gains with vigilant stewardship of vascular health, rather than equating better glucose metrics with comprehensive cardiometabolic safety [1,3,7,24,26,28].

Practical Implications for Clinicians and AI Health-Tech Platforms

For clinicians and AI-driven health platforms, the principal implication is that low-carbohydrate diets should not be prescribed, titrated, or evaluated on the basis of weight, fasting glucose, HbA1c, or CGM metrics alone. Comprehensive cardiometabolic monitoring, including ApoB, LDL-C, non-HDL cholesterol, blood pressure, and markers of liver and kidney function should accompany any aggressive macronutrient intervention, particularly in individuals with established ASCVD, subclinical atherosclerosis, familial hypercholesterolemia, or strong family history of premature cardiovascular events. Consensus statements and reviews from lipidology and cardiometabolic expert groups emphasize that low-carbohydrate and very-low-carbohydrate diets may be reasonable tools for weight loss and glycemic control in selected patients, but that clinicians must actively surveil atherogenic lipoproteins and global risk rather than assuming cardioprotection based on metabolic syndrome reversal alone [1,8,13,33,34].

When patients manifest substantial elevations in LDL-C and ApoB on low-carbohydrate or ketogenic diets, a structured response is warranted rather than reassurance based on favourable triglycerides, HDL-C, or glucose profiles. Recommended options include reducing saturated fat intake (e.g., limiting butter, cream, processed and fatty red meats), replacing them with unsaturated fats from plant sources (olive oil, nuts, seeds, avocado) and fatty fish, and reintroducing moderate amounts of high-fiber carbohydrates from minimally processed sources such as legumes, intact whole grains, and non-starchy vegetables. In individuals with persistently elevated ApoB or high estimated ASCVD risk despite nutritional adjustments, pharmacologic lipid-lowering therapy like statins, ezetimibe, or PCSK9-targeted agents should be considered in accordance with prevailing dyslipidemia guidelines and individualized risk stratification. Importantly, patient counselling should explicitly frame these adjustments not as “diet failure,” but as tailoring macronutrient distribution and food quality to the patient’s unique lipid and vascular response, consistent with a precision nutrition paradigm [7,13,33,34,35].

Emerging clinical and experimental data support the promotion of plant-forward low-carbohydrate patterns often termed “plant-based low carb” or “Eco-Atkins”/Mediterranean-style low carb which combine moderate carbohydrate restriction with high intake of vegetables, legumes (as tolerated), nuts, seeds, olive oil, and fish. In randomized trials, such patterns have achieved weight loss and improvements in glycemic markers comparable to higher-carbohydrate diets, while producing more favourable changes in LDL-C, ApoB-related ratios, and blood pressure than animal-based low-carbohydrate comparators. Large observational datasets further indicate that plant-based and healthful plant-forward dietary patterns are associated with lower risks of coronary heart disease, type 2 diabetes, and cardiovascular mortality, whereas unhealthful plant-based or animal-heavy low-carbohydrate patterns are linked to increased risk. These findings reinforce the message that “low-carb” is not a homogeneous intervention; the source, processing, and matrix of foods are as important as the macronutrient ratio itself [33,34,36,37,38,39,40].

For biohacking-oriented and digitally engaged populations, translating these principles into simple, actionable heuristics can align performance goals with long-term vascular health. Practical guidance includes tracking both CGM-derived metrics (time in range, glycemic variability) and periodic ApoB/LDL-C, anchoring meals around whole plant foods and unsaturated fats, minimizing ultra-processed “keto” snacks and SFA-rich animal products, and periodically reassessing global cardiometabolic risk rather than focusing solely on weight or glucose. On the AI design side, platforms that currently optimize interventions primarily for CGM stability, weight loss, or short-term symptom improvement should evolve toward multi-dimensional risk engines that treat elevated ApoB or rising blood pressure as critical alerts, prompting automated recommendations for dietary reformulation, intensification of lipid-lowering therapy, or cardiology referral. Ultimately, a precision nutrition approach that integrates clinical biomarkers, patient phenotype (e.g., insulin resistance status, genetic risk variants), and high-resolution digital health data offers the most robust framework to harness the short-term metabolic benefits of carbohydrate reduction while minimizing unintended long-term cardiovascular harm [8,33,34,35,41,42,43].

Conclusion

Low-carbohydrate and ketogenic diets can offer meaningful short-term metabolic benefits, including weight loss, improved glycemic control, and reductions in some features of the metabolic syndrome. However, converging epidemiological and mechanistic data indicate that specific low-carbohydrate patterns, particularly those characterized by high intakes of animal protein, saturated fat, and ultra-processed “keto” products are associated with increased long-term cardiovascular and all-cause mortality. In these contexts, adverse changes in LDL-C and ApoB, reflecting an elevated burden of atherogenic lipoproteins, may counterbalance or even outweigh the vascular benefits expected from improved glucose control and weight reduction.

In contrast, low-carbohydrate patterns that emphasize plant-based proteins, unsaturated fats, high-fiber foods, and minimal processing appear to confer more favourable cardiovascular profiles and are likely to represent a safer paradigm for carbohydrate restriction. This heterogeneity underscores that “low-carb” is not a single intervention, but a spectrum of dietary patterns whose health effects are determined by food quality, fat and protein sources, and individual biological responses. For clinicians and AI health-tech platforms dedicated to metabolic disease prevention and biohacking, the key challenge is therefore not to frame low-carbohydrate diets as universally harmful or universally protective, but to determine which versions of these diets, in which patients, under which biomarker constraints, actually reduce lifetime ASCVD risk.

Accordingly, low-carbohydrate protocols should be embedded within a comprehensive cardiometabolic risk framework that systematically monitors ApoB, LDL-C, blood pressure, markers of organ function, and, where possible, measures of vascular health alongside glycemic indices and body composition. By integrating lipid and vascular risk assessment into dietary personalization algorithms, healthcare systems and digital platforms can help ensure that the pursuit of metabolic optimization does not inadvertently increase the risk of heart disease it seeks to prevent.

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