Effects of carbohydrate-restricted diets and macronutrient replacements on cardiovascular health and body composition in adults: a meta-analysis of randomized trials

Shuo Feng; Renming Liu; Christopher Thompson; Brian Colwell; Sunghyun Chung; Adam Barry; Huishan Wang

doi:10.1016/j.ajcnut.2025.09.012

. 2025 Sep 8;122(5):1461–1478. doi: 10.1016/j.ajcnut.2025.09.012

Effects of carbohydrate-restricted diets and macronutrient replacements on cardiovascular health and body composition in adults: a meta-analysis of randomized trials

Shuo Feng ^1,^⁎, Renming Liu ², Christopher Thompson ³, Brian Colwell ¹, Sunghyun Chung ¹, Adam Barry ¹, Huishan Wang ¹

PMCID: PMC12799388 PMID: 40935153

Abstract

Background

Carbohydrate-restricted diets (CRDs) are widely promoted for improving cardiovascular and body composition outcomes, yet evidence remains mixed across dietary patterns, populations, and study designs.

Objectives

This meta-analysis evaluated the effects of CRDs on cardiovascular and anthropometric outcomes and examined whether these effects varied by diet type, macronutrient replacement, participant characteristics, and study features.

Methods

Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines, 174 randomized trials (n = 11,481) from 27 countries were included. Eligible studies compared CRDs (≤45% of energy from carbohydrates) to higher-carbohydrate diets in adults and reported cardiovascular or anthropometric outcomes. Random-effects models estimated standardized mean differences (SMDs) and 95% confidence intervals (CIs). Subgroup analyses explored differences by CRD type (ketogenic, low-carb, and moderate-carb), replacement macronutrient (fat, protein, or combination), sex, weight status, diabetes status, intervention delivery, caloric intakes, and study design. Metaregressions assessed the effects of intervention duration.

Results

CRDs significantly reduced triglycerides [SMD: –15.11 mg/dL; 95% CI: –18.76, –11.46], systolic (SMD: –2.05 mmHg; 95% CI: –3.13, –0.96) and diastolic blood pressure (SMD: –1.26 mmHg; 95% CI: –1.94, –0.57), various lipid profile ratios, and inflammatory markers (C-reactive protein, tumor necrosis factor-alpha), whereas increasing high-density lipoprotein (SMD: 2.92 mg/dL, 95% CI: 2.10, 3.74). Low-density lipoprotein (LDL) and total cholesterol increased modestly (SMD: 4.81, 95% CI: 2.58, 7.05; and SMD: 4.32 mg/dL, 95% CI: 1.66, 6.97, respectively). All measured body composition markers showed significant reductions. Moderate-carbohydrate diets offered balanced benefits, whereas ketogenic diets produced greater weight loss but greater increases in LDL and total cholesterol. Combined fat and protein replacements yielded the most comprehensive improvements. Benefits were most pronounced in females and individuals with overweight or obesity. Longer interventions amplified effects on lipid ratios and inflammatory markers.

Conclusions

CRDs improved cardiovascular health and body composition, especially in diets with combined macronutrient replacement. Potential adverse effects, including LDL elevation and lean mass loss, warrant clinical monitoring.

Trial registration number: for body composition, PROSPERO: CRD420251043066 (https://www.crd.york.ac.uk/PROSPERO/view/CRD420251043066); for cardiovascular health: CRD420251011748 (https://www.crd.york.ac.uk/PROSPERO/view/CRD420251011748).

Keywords: carbohydrate-restricted diets, cardiovascular health, body composition, lipid profiles, inflammatory markers, meta-analysis, macronutrient replacement

Introduction

Cardiovascular diseases (CVDs), as the leading cause of death worldwide, account for 32% of all deaths [1]. The major contributor, overweight/obesity [2], defined as excessive and abnormal fat accumulation, is affecting ∼ 2.5 billion adults aged 18 y and older (BMI >25 kg/m²), including over 890 million living with obesity (BMI >30 kg/m²) [3]. The global economic burden is projected to rise to $3 trillion annually by 2030 and over $18 trillion by 2060 [4]. Promoting cardiovascular health and a healthy body composition remains a global public health priority.

Carbohydrate-restricted diets (CRDs), originally developed as a therapeutic intervention for epilepsy [5], have demonstrated potential clinical benefits across a broad spectrum of health conditions, including neurodegenerative diseases [6] and cancer [7]. Moreover, their roles in cardiovascular health and weight management have been recognized. Meta-analyses have shown that higher-carbohydrate intake is associated with increased risk of CVDs [8,9], including coronary artery disease [10,11] and stroke [10,12]. Comparatively, CRDs have demonstrated favorable effects on cardiovascular biomarkers, such as reduced triglycerides (TG) and blood pressure, along with increased HDL levels [13,14]. Parallel evidence supports the benefits of CRDs on anthropometric outcomes, including reductions in body weight (BW), BMI, body fat percentage (BFP) [[15], [16], [17], [18]], as well as fat mass (FM), fat-free mass (FFM), waist circumference (WC), and visceral adipose tissue (VAT) [18].

Despite these findings, the effects of CRDs on cardiovascular health and body composition remain inconsistent. Some studies report that CRD increased LDL and total cholesterol (TC) [13,14], markers traditionally considered adverse for cardiovascular disease risk. Others have found no significant improvements in blood pressure, lipid profiles [19], or body composition metrics such as FM [15], WC [16], BW, BFP, or lean mass (LM) [20,21]. Further complicating the evidence base is a proposed U-shaped relationship between carbohydrate intake and mortality, suggesting that both very low and very high carbohydrate consumption may elevate health risks [22]. Additionally, the precise role of diet duration remains unclear [18].

To address these knowledge gaps and clarify the mixed findings, this meta-analysis aims to systematically evaluate the effects of CRDs on a broad range of cardiovascular and anthropometric outcomes. Subgroup analyses and metaregressions examined differences by CRD type [ketogenic diet (KD): ≤10% of kcal, low-carb diet (LCD): 10%–26% of kcal, and moderate-carb diet (MCD): 26%–45% of kcal] [23] and replacement type (fat/protein/both), intervention length, participant characteristics (sex, diabetic status, and weight status), study design (consultation-only and food-provided; randomized crossover and parallel), and energy intakes [isocaloric (±5%) [24] and nonisocaloric].

Methods

Search strategy

This systematic review and meta-analysis followed the PRISMA 2020 guidelines [25] and was registered with PROSPERO (registration number and link are blinded for peer-review purposes). To ensure a comprehensive assessment, minor deviations from the registered protocol were implemented during data extraction. These included an expanded evaluation of cardiovascular outcomes, such as soluble intercellular adhesion molecule-1 (sICAM-1) and soluble vascular cell adhesion molecule-1 (sVCAM-1), and additional subgroup analyses (e.g., energy intake). A comprehensive search was conducted across 5 electronic databases—PubMed, Medline, Embase, Education Resources Information Center and Web of Science—to identify relevant randomized trials, including randomized crossover trials and randomized parallel-group trials. No restrictions were placed on language or publication date during the initial screening phase. Search terms were developed based on previous literature in the field [18,[26], [27], [28]], with the full strategy provided in the Supplementary Material. The final database search was conducted on March 14, 2025, covering studies from database inception to that date. All references were imported into Covidence systematic review software, which was used for managing title/abstract screening, full–text review, and duplicate removal. The screening process lasted ∼2 mo until mid-May.

Eligibility criteria

Following the population, intervention, comparator, outcomes, and study design framework, studies were selected based on the following eligibility criteria: 1) population: studies conducted on adults aged 18 y and older; 2) intervention: randomized trials assessing the effects of macronutrient intake (e.g., variation in carbohydrate, fat, or protein intake) on anthropometric measures and body composition; 3) comparator: studies employing either a crossover design with adequate washout periods or parallel-group designs with appropriate control or alternative diet comparison groups; 4) outcomes: studies reporting ≥1 of the following measures, for blood pressure (mmHg): systolic (SBP) and diastolic (DBP), for lipid and apolipoprotein profiles: TG (mg/dL), TC (mg/dL), LDL (mg/dL), HDL (mg/dL), non-HDL (mg/dL), VLDL (mg/dL), LDL–HDL ratio, TC-HDL ratio, TG-HDL ratio, apolipoprotein A-I (ApoA1, g/L), apolipoprotein B-100 (ApoB, g/L), ApoB/ApoA1 ratio, for endothelial function: flow-mediated dilation (%), E-selectin (ng/mL), sICAM-1 (ng/mL), sVCAM-1 (ng/mL), for inflammatory biomarkers: C-reactive protein (CRP, mg/L), TNF-alpha (pg/mL), and IL-6 (pg/mL), and predicted 10-y CVD risk (%). Body composition outcomes include BW (kg), BMI (kg/m²), FM (kg), BFP (%), LM (kg), FFM (kg), WC (cm), hip circumference (HC, cm), waist-to-hip ratio (WHR), and VAT (kg); 5) study design: original peer-reviewed studies with randomized trials, either a single-arm crossover design or multiple-arm parallel designs.

In addition, studies must report sufficient data to calculate delta mean and pooled SDs for pre- and postintervention comparisons (detailed in the Supplementary Material). Only studies published in English were included. Two reviewers (SF and RL) independently screened the titles, abstracts, and full texts of the identified studies. Disagreements were resolved through discussion and consensus.

Data extraction

From each eligible study, the following data were extracted: study title, first author’s last name, and key intervention characteristics (e.g., country, study design, intervention type, duration, calorie intakes, and macronutrient distribution). Participant characteristics included sex distribution, mean age, baseline BMI, diabetes status, and weight classification. Additional details collected included the number of participants per group and the type of reported outcomes. For each outcome, the extracted data encompassed delta means (post and pre mean differences), pooled SDs, SE, 95% confidence interval (CI), median and IQR, as well as pre- and postintervention means, SDs, SEs, and 95% CIs. Data extraction was conducted by one reviewer (SF) and independently cross-checked by 2 additional reviewers (SC and HW). Any discrepancies were resolved through discussion and mutual consensus. There is no acknowledged missing data during the data extraction. The extracted data were converted to delta means and their associated SDs for analysis (detailed in the Supplementary Material).

Risk of bias assessment

The Cochrane Risk of Bias 2 (RoB 2) tool [29] was used for evaluating the risk of bias in 5 domains: 1) selection bias arising from the randomization process; 2) performance bias due to deviations from intended interventions; 3) attrition bias; 4) detection/outcome bias in measurement; and 5) reporting bias. Each domain was rated as having low risk, some concerns, or high risk of bias. Two reviewers (SF and RL) evaluated the included studies independently. Discrepancies were discussed and resolved with consensus. A traffic-light plot was used to visualize the risk of bias judgments across domains for each study.

Statistical analysis

We performed and reported a given meta-analysis only when the number of independent data points reached ≥4 (k ≥ 4) [30]. Given the anticipated heterogeneity among studies, a random-effects model was employed to estimate standardized mean differences (SMDs) with corresponding 95% CIs. The restricted maximum likelihood (REML) was used for conducting the analyses. REML provides less biased estimates of between-study variance (τ²) compared with DerSimonian-Laird or other methods, and it is a preferred estimation method for random-effects meta-analysis and metaregression [[31], [32], [33]]. For data harmonization and consistency, due to variability in reported units across studies, all biomarker outcomes were converted to a common unit (e.g., mg/dL for lipid profiles) using standardized conversion factors. Detailed formulas are provided in the Supplementary Material. Heterogeneity was assessed by Cochran’s Q test and the I² statistic. Forest plots and funnel plots were used to represent the meta-analysis results and associated publication bias.

After conducting the main meta-analysis for each outcome, subgroup analyses were conducted with grouping by macronutrient proportions (KD: ≤10% of total calorie or 20–50 g/d, LCD: 10%–26% of total calories or 50–130 g/d, and MCD: 26%–45% of total calorie or 130–230 g/d) [23], carbohydrate replacements (fat compared with protein compared with a combination of both) (see Supplementary Material for macronutrient calculation), dietary intervention length, sex (females compared with males), diabetic status [nondiabetic compared with type 2 diabetes (T2DM)], weight status (nonoverweight compared with overweight/obese). Finally, given concerns about consultation-only interventions in prior meta-analyses [34], this study also investigates differences between consultation-only and food-provided interventions, as well as between randomized crossover and parallel study designs, and between isocaloric (small energy margin with ∼±5%) [24] and nonisocaloric interventions (including personalized calorie intake calculated by the Harris-Benedict equation, ad libitum, etc.).

For each subgroup (e.g., males and females), we performed separate random-effects meta-analyses. Between-group heterogeneity was assessed using Cochran’s Q-between statistic (Qb) to determine whether the subgroup moderators could explain the observed variability in effect sizes. Lastly, the effects of diet length (in weeks) were assessed via metaregression analyses. Stata SE version 17.0 was used for analyses (Stata Corp LLC).

Multiple testing correction

To control the family-wise error rate for multiple comparisons, a hybrid version of the Bonferroni correction was used. The corrected significance threshold (α∗) was calculated as α∗=α/m, where α∗ is the corrected alpha (i.e., type I error rate), α is original significance level (here, set as 0.05), and m is the total number of independent tests, computed as the sum of the number of omnibus tests (equal to the number of moderators, 8) and the number of multiple comparisons within each moderator (a total of 12). The corrected significance threshold was 0.0025 (i.e., 0.05/20). A test result was considered statistically significant if its P value ≤0.0025, ensuring a conservative approach to type I error. This decision balances specificity (reducing false positives) whereas acknowledging the exploratory nature of subgroup analyses.

Sensitivity analysis

The robustness and reliability of the meta-analytic findings were tested by sensitivity analyses, which are repeated analyses excluding data from studies rated as having a high risk of bias, based on the RoB 2 tool, and outliers. After comparing the results of sensitivity analyses with the original meta-analyses, notable deviations in effect size or statistical significance are reported and interpreted in the context of potential bias and heterogeneity.

Results

Included study characteristics

A total of 13,638 publications were identified through the initial database search. After removing 1753 duplicates, 11,885 records remained for title and abstract screening. Of these, 11,434 were excluded based on relevant criteria. The remaining 451 full–text articles were assessed for eligibility, resulting in 174 studies being included in the final meta-analysis [[35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], [82], [83], [84], [85], [86], [87], [88], [89], [90], [91], [92], [93], [94], [95], [96], [97], [98], [99], [100], [101], [102], [103], [104], [105], [106], [107], [108], [109], [110], [111], [112], [113], [114], [115], [116], [117], [118], [119], [120], [121], [122], [123], [124], [125], [126], [127], [128], [129], [130], [131], [132], [133], [134], [135], [136], [137], [138], [139], [140], [141], [142], [143], [144], [145], [146], [147], [148], [149], [150], [151], [152], [153], [154], [155], [156], [157], [158], [159], [160], [161], [162], [163], [164], [165], [166], [167], [168], [169], [170], [171], [172], [173], [174], [175], [176], [177], [178], [179], [180], [181], [182], [183], [184], [185], [186], [187], [188], [189], [190], [191], [192], [193], [194], [195], [196], [197], [198], [199], [200], [201], [202], [203], [204], [205], [206], [207], [208]]. The PRISMA flow diagram (Figure 1) illustrates the detailed study selection process. The included studies were published between 1992 and 2025, representing a sample of 11,481 participants from 27 countries. Comprehensive study characteristics, including participant demographics, study design, intervention types, and reported outcomes, are summarized in Supplemental Table 1.

PRISMA diagram. ERIC stands for Education Resources Information Center.

Risk of bias

On the basis of the Cochrane RoB 2 tool, 59% (k = 102) had some concerns, 33% (k = 57) had low risk, and 8% (k = 15) had high risk of bias. A visualization of the risk of bias assessment is presented in a traffic-light plot (Supplemental Figure 1).

Meta-analysis results: overall effect sizes (SMDs)

The summary SMDs and corresponding 95% CIs for all outcomes are presented in Table 1. Detailed forest plots illustrating individual and pooled effects are provided in Supplemental Figure 2, whereas funnel plots assessing potential publication bias are included in Supplemental Figure 3. For cardiovascular health, compared with higher-carbohydrate diets, CRDs significantly reduced blood pressure: SBP (–2.05 mmHg) and DBP (–1.26 mmHg); lipid profiles: TG (–15.11 mg/dL), LDL–HDL ratio (–0.18), TG-HDL ratio (–0.32), VLDL (–3.34 mg/dL), and ApoB-ApoA1 ratio (–0.03); and other endothelial and inflammatory markers: E-selectin (–2.23 ng/mL), CRP (–0.37 mg/L), and TNF-α (–0.27 pg/mL). Conversely, increases were observed in TC (+4.32 mg/dL), LDL (+4.81 mg/dL), HDL (+2.92 mg/dL), and ApoA1 (+0.04 g/L). The overall CVD risk was decreased by 1.05% (95% CI: –1.89, –0.21).

TABLE 1.

The pooled effect sizes (SMD) of outcomes.

	N of obs.	SMD (95% CI)	P	I² (%)
Cardiovascular health
Blood pressure
SBP (mmHg)	88	–2.05 (–3.13, –0.96)	<0.001	99.91
DBP (mmHg)	89	–1.26 (–1.94, –0.57)	<0.001	99.64
Lipid profile
TG (mg/dL)	143	–15.11 (–18.76, –11.48)	<0.001	99.24
TC (mg/dL)	128	4.32 (1.66, 6.97)	<0.001	99.70
LDL (mg/dL)	141	4.81 (2.58, 7.05)	<0.001	99.66
HDL (mg/dL)	142	2.92 (2.10, 3.74)	<0.001	99.79
Non-HDL (mg/dL)	12	1.91 (–4.66, 8.48)	0.57	99.91
LDL–HDL ratio	8	–0.18 (–0.31, –0.05)	<0.05	92.69
TC-HDL ratio	32	–0.13 (–0.26, 0.01)	0.06	99.47
TG-HDL ratio	16	–0.32 (–0.44, –0.20)	<0.001	90.83
VLDL (mg/dL)	10	–3.34 (–6.03, –0.66)	<0.05	96.39
ApoA1 (g/L)	16	0.04 (0.00, 0.07)	<0.05	94.90
ApoB (g/L)	20	0.02 (–0.01, 0.06)	0.18	99.72
ApoB-ApoA1 ratio	6	–0.03 (–0.04, –0.02)	<0.001	71.76
Endothelial functions
FMD (%)	7	0.11 (–0.41, 0.63)	0.68	92.68
E-selectin (ng/mL)	8	–2.23 (–4.09, –0.36)	<0.05	96.11
sICAM-1 (ng/mL)	7	–12.60 (–28.93, 3.72)	0.13	96.52
sVCAM-1 (ng/mL)	6	–1.42 (–20.84, 18.00)	0.89	95.97
Inflammatory markers
CRP (mg/L)	54	–0.37 (–0.69, –0.05)	<0.05	99.12
TNF-α (pg/mL)	10	–0.27 (–0.42, –0.11)	<0.001	83.56
IL-6 (pg/mL)	10	–0.21 (–0.67, 0.24)	0.36	91.60
CVD risk (%)	4	–1.05 (–1.89, –0.21)	<0.05	99.75
Body composition
BW (kg)	135	–1.75 (–2.20, –1.31)	<0.001	99.56
BMI	93	–0.72 (–0.93, –0.51)	<0.001	99.01
FM (kg)	66	–0.84 (–1.19, –0.49)	<0.001	95.59
BFP	48	–0.78 (–1.09, –0.47)	<0.001	98.36
LM (kg)	31	–0.30 (–0.59, –0.01)	<0.05	98.33
FFM (kg)	27	–0.41 (–0.57, –0.25)	<0.001	70.72
WC (cm)	84	–1.86 (–2.48, –1.24)	<0.001	99.66
HC (cm)	18	–1.65 (–2.50, –0.79)	<0.001	95.97
WHR	23	–0.01 (–0.02, –0.00)	<0.05	93.71
VAT (kg)	6	–0.28 (–0.50, –0.05)	<0.05	98.48

Open in a new tab

Restricted maximum likelihood (REML) was used for conducting the analyses.

N of Obs. refers to the number of observations included for the associated outcomes.

Abbreviations: ApoA1, Apolipoprotein A-I; ApoB, Apolipoprotein B, BFP, body fat percentage; BW, body weight (kg); CRP, C-reactive protein; CVD risk%, cardiovascular disease risk (percentage); DBP, diastolic blood pressure; FFM, fat-free mass (kg); FM, fat mass (kg); FMD%, flow-mediated dilation (percentage); HC, hip circumference (cm); LM, lean mass (kg); SBP, systolic blood pressure; sICAM-1, soluble intercellular adhesion molecule-1; SMD (95% CI), standardized mean difference and the corresponding 95% confidence interval; sVCAM-1, soluble vascular cell adhesion molecule-1; TC, total cholesterol; TG, triglycerides; VAT, visceral adipose tissue; WC, waist circumference (cm); WHR, waist–hip ratio.

For body composition, compared with individuals with higher-carbohydrate intakes, those with CRDs had lowered levels of all measured anthropometric metrics (Table 1 for detailed information on reduced anthropometric metrics and their associated statistical indices). Lastly, excluding high-risk studies and outliers confirmed the robustness of results, except for VLDL and LM, which became nonsignificant (Supplemental Table 2).

Subgroup analyses: macronutrient composition

Subgroup analyses were conducted to evaluate the differential effects of various CRD types and macronutrient replacements. Results are summarized in Table 2.

TABLE 2.

Subgroup analysis of diet characteristics (types and replacements).

	KD		LCD		MCD
	SMD (95% CI)	P	SMD (95% CI)	P	SMD (95% CI)	P
Blood pressure
SBP (16 vs. 23 vs. 36)¹	–1.10 (–3.63, 1.43)	0.39	–2.73 (–4.46, –1.00)	<0.001²	–2.18 (–4.14, –0.22)	<0.05
DBP (16 vs. 25 vs. 36)¹	1.14 (–0.74, 3.02)	0.23	–1.23 (–2.36, –0.10)	<0.05	–2.39 (–3.41, –1.36)	<0.001²
Lipid profile
TG (30 vs. 29 vs. 63)¹	–15.73 (–24.59, –6.88)	<0.001²	–15.48 (–22.28, –8.67)	<0.001²	–15.54 (–21.41, –9.67)	<0.001²
TC (27 vs. 27 vs. 55)¹	13.80 (6.67, 20.93)	<0.001²	7.46 (0.70, 14.23)	<0.05	–0.20 (–2.98, 2.58)	0.89
LDL (29 vs. 33 vs. 59)¹	13.34 (7.68, 19.01)	<0.001²	7.30 (1.75, 12.84)	<0.05	0.29 (–2.28, 2.86)	0.82
HDL (30 vs. 33 vs. 59)¹	7.30 (3.53, 11.07)	<0.001²	2.92 (1.04, 4.81)	<0.001²	1.86 (1.00, 2.72)	<0.001²
Non-HDL (2 vs. 3 vs. 4)¹	19.93³ (–0.90, 40.76)	0.06	2.98³ (–6.23, 12.19)	0.53	–5.82 (–14.72, 3.08)	0.20
LDL–HDL (0 vs. 2 vs. 5)¹	—		–0.40³ (–0.42, –0.38)	<0.001	–0.14 (–0.26, –0.02)	<0.05
TC-HDL (8 vs. 7 vs. 12)¹	0.03 (–0.20, 0.26)	0.79	–0.07 (–0.30, 0.15)	0.53	–0.32 (–0.62, –0.01)	<0.05
TG-HDL (7 vs. 3 vs. 3)¹	–0.30 (–0.45, –0.16)	<0.001	–0.14³ (–0.25, –0.02)	<0.05	–0.55³ (–0.95, –0.15)	<0.05
VLDL (3 vs. 0 vs. 5)¹	–1.50³ (–5.99, 2.98)	0.51	—		–7.58 (–9.60, –5.57)	<0.001²
ApoA-1 (1 vs. 2 vs. 8)¹	0.20³ (0.15, 0.25)	<0.001	0.02³ (–0.01, 0.05)	0.29	0.01 (–0.03, 0.05)	0.48
ApoB (5 vs. 3 vs. 9)¹	0.11 (0.02, 0.20)	<0.05	0.03³ (–0.07, 0.13)	0.52	–0.02 (–0.04, 0.00)	0.10
ApoB-ApoA1 (0 vs. 1 vs. 3)¹	—		–0.05³ (–0.05, –0.05)	<0.001	–0.02³ (–0.04, –0.01)	<0.001
Endothelial functions
FMD, % (1 vs. 5 vs. 1)¹	–1.00³ (–3.91, 1.91)	0.50	–0.04 (–0.54, 0.46)	0.87	0.90³ (0.30, 1.50)	<0.001
E-selectin (2 vs. 1 vs. 4)¹	–0.56³ (–2.67, 1.55)	0.60	–7.70³ (–13.93, –1.47)	<0.05	–2.62 (–5.02, –0.22)	<0.05
sICAM-1 (2 vs. 1 vs. 4)¹	–12.50³ (–16.14, –8.86)	<0.001	–22.70³ (–70.11, 24.71)	0.35	–8.68 (–34.86, 17.50)	0.52
sVCAM-1 (1 vs. 1 vs. 4)¹	–31.20³ (–48.91, –13.49)	<0.001	–25³ (–210.4, 160.4)	0.79	5.26 (–4.28,14.80)	0.28
Inflammatory markers
CRP (12 vs. 14 vs. 20)¹	–0.47 (–1.19, 0.26)	0.21	–0.13 (–0.63, 0.30)	0.60	–0.63 (–1.46, 0.21)	0.14
TNF-α (1 vs. 4 vs. 5)¹	–0.10³ (–0.27, 0.07)	0.25	–0.11 (–0.19, –0.04)	<0.001²	–0.41 (–0.64, –0.17)	<0.001²
IL-6 (2 vs. 4 vs. 3)¹	–0.41³ (–1.00, 0.19)	0.18	0.19 (–0.35, 0.73)	0.50	–0.58³ (–1.69, 0.53)	0.31
Body composition
BW (28 vs. 31 vs. 56)¹	–3.36 (–4.80, –1.92)	<0.001²	–1.97 (–2.75, –1.15)	<0.001²	–0.77 (–1.26, –0.29)	<0.001²
BMI (23 vs. 22 vs. 37)¹	–1.24 (–1.82, –0.65)	<0.001²	–0.87 (–1.37, –0.37)	<0.001²	–0.36 (–0.52, –0.20)	<0.001²
FM (15 vs. 13 vs. 29)¹	–0.93 (–1.72, –0.14)	<0.05	–0.92 (–1.73, –0.12)	<0.05	–0.71 (–1.25, –0.16)	<0.05
BFP (9 vs. 13 vs. 23)¹	–1.15 (–2.31, 0.00)	0.05	–0.47 (–1.07, 0.13)	0.13	–0.90 (–1.28, –0.51)	<0.001²
LM (8 vs. 6 vs. 15)¹	–0.72 (–1.39, –0.06)	<0.001²	–0.56 (–1.56, 0.43)	0.27	–0.08 (–0.35, 0.20)	0.59
FFM (6 vs. 8 vs. 9)¹	–0.71 (–1.22, –0.21)	<0.05	–0.29 (–0.50, –0.09)	<0.001²	–0.37 (–0.79, 0.04)	0.08
WC (14 vs. 23 vs. 38)¹	–4.88 (–7.35, –2.41)	<0.001²	–2.08 (–2.87, –1.28)	<0.001²	–0.89 (–1.53, –0.26)	<0.05
HC (3 vs. 5 vs. 8)¹	–0.91³ (–2.37, 0.55)	0.22	–2.96 (–4.86, –1.07)	<0.001²	–0.95 (–2.02, 0.13)	0.08
WHR (4 vs. 5 vs. 12)¹	–0.02 (–0.03, –0.02)	<0.001²	–0.00 (–0.02, 0.01)	0.61	–0.01 (–0.02, 0.00)	0.14

	Fat	Protein	Both
	SMD	P	SMD	P	SMD	P

Blood pressure
SBP (21 vs. 9 vs. 58)⁴	–1.01 (–3.08, 1.07)	0.34	–1.29 (–3.28, 0.70)	0.20	–2.52 (–3.95, –1.09)	<0.001²
DBP (19 vs. 11 vs. 59)⁴	–0.19 (–1.59, 1.22)	0.80	–0.49 (–1.39, 0.40)	0.28	–1.70 (–2.60, –0.80)	<0.001²
Lipid profile
TG (46 vs. 18 vs. 79)⁴	–12.24 (–19.24, –5.24)	<0.001²	–12.92 (–23.72, –2.11)	<0.05	–17.11 (–21.7, –12.54)	<0.001²
TC (41 vs. 17 vs. 70)⁴	5.68 (1.12, 10.24)	<0.05	–4.29 (–7.28, –1.30)	<0.001²	5.78 (1.92, 9.64)	<0.001²
LDL (43 vs. 17 vs. 81)⁴	6.39 (2.95, 9.84)	<0.001²	–6.55 (–13.07, –0.02)	0.05	6.49 (3.59, 9.39)	<0.001²
HDL (46 vs. 17 vs. 79)⁴	3.56 (2.11, 5.02)	<0.001²	0.47 (–1.27, 2.21)	0.60	3.14 (1.99, 4.29)	<0.001²
Non-HDL (3 vs. 2 vs. 7)⁴	1.56³ (–4.43, 7.55)	0.61	–5.20³ (–7.36, –3.04)	<0.001	4.16 (–7.22. 15.54)	0.47
LDL–HDL (4 vs. 0 vs. 4)⁴	0.00 (–0.06, 0.06)	0.97	—		–0.29 (–0.40, –0.18)	<0.001²
TC-HDL (12 vs. 1 vs. 19)⁴	–0.10 (–0.19, –0.01)	<0.05	0.10³ (0.00, 0.20)	0.05	–0.13 (–0.34, 0.08)	0.22
TG-HDL (2 vs. 0 vs. 14)⁴	–0.33³ (–0.43, –0.24)	<0.001	—		–0.32 (–0.47, –0.17)	<0.001²
VLDL (6 vs. 1 vs. 3)⁴	–3.66 (–7.54, 0.22)	0.06	–7.40³ (–9.57, –5.23)	<0.001	–1.50³ (–5.99, 2.98)	0.51
ApoA1 (7 vs. 0 vs. 7)⁴	0.05 (0.01, 0.08)	<0.05	—		0.03 (–0.03, 0.09)	0.32
ApoB (8 vs. 0 vs. 12)⁴	0.02 (–0.02, 0.07)	0.25	—		0.02 (–0.03, 0.07)	0.42
ApoB-ApoA1(2 vs. 0 vs. 4)⁴	–0.02³ (–0.03, –0.01)	<0.05	—		–0.04 (–0.06, –0.02)	<0.001²
Endothelial functions
FMD, % (1 vs. 0 vs. 6)⁴	–0.56³ (–0.77, –0.35)	<0.001	—		0.31 (–0.14, 0.76)	0.18
e-Selectin (3 vs. 1 vs. 4)⁴	0.00³ (–0.41, 0.41)	0.99	–4.90³ (–5.40, –4.40)	<0.001	–2.70 (–5.04, –0.36)	<0.05
sICAM-1 (2 vs. 1 vs. 4)⁴	–6.92³ (–28.51, 14.67)	0.53	15.60³ (–1.86, 33.06)	0.08	–23.24 (–40.46, –6.03)	<0.01
sVCAM-1 (1 vs. 0 vs. 5)⁴	73.64³ (–8.68, 155.96)	0.08	—		–4.95 (–23.69, 13.78)	0.60
Inflammatory markers
CRP (13 vs. 7 vs. 34)⁴	0.13 (–0.33, 0.58)	0.59	–2.17 (–5.32, 0.96)	0.18	–0.38 (–0.72, –0.04)	<0.05
TNF-α (2 vs. 1 vs. 7)⁴	–0.11³ (–0.18, –0.04)	<0.001	–0.90³ (–3.07, 1.27)	0.42	–0.34 (–0.54, –0.15)	<0.001²
IL-6 (4 vs. 1 vs. 5)⁴	–0.10 (–0.33, 0.13)	0.41	–0.90³ (–3.55, 1.75)	0.51	–0.06 (–0.88, 0.76)	0.89
CVD risk, % (0 vs. 0 vs. 4)⁴	—		—		–1.05 (–1.89, –0.21)	<0.05
Body composition
BW (45 vs. 12 vs. 78)⁴	–1.14 (–2.10, –0.19)	<0.05	–1.64 (–3.48, 0.20)	0.08	–2.01 (–2.46, –1.56)	<0.001²
BMI (29 vs. 7 vs. 57)⁴	–0.71 (–1.18, –0.23)	<0.001²	–1.11 (–2.04, –0.18)	<0.05	–0.65 (–0.85, –0.45)	<0.001²
FM (25 vs. 10 vs. 31)⁴	–0.78 (–1.29, –0.26)	<0.001²	–1.29 (–2.41, –0.17)	<0.05	–0.73 (–1.23, –0.23)	<0.001²
BFP (17 vs. 3 vs. 28)⁴	–0.39 (–0.77, –0.01)	<0.05	–1.74³ (–3.43, –0.05)	<0.05	–0.90 (–1.32, –0.68)	<0.001²
LM (14 vs. 6 vs. 11)⁴	–0.49 (–1.12, 0.15)	0.13	–0.30 (–0.58, –0.01)	0.10	–0.15 (–0.52, 0.22)	0.43
FFM (10 vs. 1 vs. 16)⁴	–0.37 (–0.59, –0.15)	<0.001²	1.10³ (–0.50, 2.70)	0.18	–0.48 (–0.74, –0.23)	<0.001²
WC (27 vs. 6 vs. 51)⁴	–1.87 (–3.30, –0.45)	<0.05	–2.52 (–5.46, 0.43)	0.09	–1.73 (–2.34, –1.12)	<0.001²
HC (5 vs. 0 vs. 13)⁴	–0.62 (–1.66, 0.42)	0.24	—		–2.00 (–3.02, –0.98)	<0.001²
WHR (7 vs. 0 vs. 16)⁴	–0.01 (–0.02, –0.01)	<0.001²	—		–0.01 (–0.02, 0.00)	0.30
VAT (2 vs. 0 vs. 4)⁴	–0.22³ (–0.56, 0.11)	0.19	—		–0.30 (–0.62, 0.02)	0.06

Open in a new tab

Restricted maximum likelihood (REML) was used for conducting the analyses.

Abbreviations: 95% CI, 95% confidence interval; ApoA1, Apolipoprotein A-I; ApoB, Apolipoprotein B; BFP, body fat percentage; CRP, C-reactive protein; CVD risk%, cardiovascular disease risk (percentage). BW, body weight (kg); DBP, diastolic blood pressure; FFM, fat-free mass (kg); FM, fat mass (kg); FMD%, flow-mediated dilation (percentage); HC, hip circumference (cm); KD, ketogenic diet: ≤10% of total calories or 20–50 g/d; LCD, low-carb diet: 10%–26% of total calories or 50–130 g/d; LM, lean mass (kg); MCD, moderate-carb diet: 26%–45% of total calories or 130–230 g/d; SBP, systolic blood pressure; sICAM-1, soluble intercellular adhesion molecule-1; SMD, standardized mean difference; sVCAM-1, soluble vascular cell adhesion molecule-1; TC, total cholesterol; TG, triglycerides; VAT, visceral adipose tissue; WC, waist circumference (cm); WHR, waist–hip ratio.

(k vs. k vs. k) stands for the number of observations included for each associated group: KD vs. LCD vs. MCD.

Represents statistical significance after adjusted for multiple testing correction (P < 0.00125) among analyses included >4 studies (k ≥ 4).

Represents the number analyzed by fewer than 4 observations for the particular group.

⁴

(k vs. k vs. k) stands for the number of observations included for each associated group: fat vs. protein vs. combination.

Effects of CRD types on cardiovascular and anthropometric outcomes

Among analyses with >4 studies and adjustment for multiple testing (corrected alpha: P < 0.0025), all 3 CRDs demonstrated significant cardiovascular benefits, including reduced TG and increased HDL cholesterol. Additionally, both LCD and MCD were associated with improvements in blood pressure and reductions in TNF-α. In contrast, KD increased LDL and TC but reduced the TG:HDL ratio by –0.27 (95% CI: –0.45, –0.16). Regarding body composition, all 3 CRDs led to reductions in BW and BMI, with varying effects on BFP, FFM, HC, WC, and WHR (Table 2 for details).

Effects of carbohydrate replacement strategies

When comparing carbohydrate replacements (fat, protein, and combination), analyses with >4 studies (corrected alpha: P < 0.0025) indicated that combined replacement (fat and protein) exerted the broadest cardiovascular benefits. This approach significantly influenced blood pressure, lipid profiles, and TNF-α levels. In addition, nearly all anthropometric measures—except LM, WHR, and VAT were improved (Table 2 for details).

Sensitivity analysis results

Sensitivity analyses revealed minor changes in statistical significance, including attenuated reductions in systolic and diastolic blood pressure for MCD. The majority of outcomes remained robust, supporting the stability and reliability of the primary findings (Supplemental Table 3).

Metaregression on intervention length

As presented in Table 3, longer durations were associated with greater reductions in LDL–HDL ratio (β = –0.03, P < 0.001), ApoB-ApoA1 (β = –0.001, P < 0.001), and IL-6 (β = –0.03, P < 0.001). The sensitivity analysis confirmed the robustness of the original findings (Supplemental Table 4).

TABLE 3.

Metaregression of intervention length (in weeks).

	b-coefficient	SE	P
Blood pressure
SBP	0.02	0.02	0.30
DBP	–0.01	0.01	0.28
Lipid profile
TG	–0.04	0.08	0.67
TC	–0.09	0.06	0.11
LDL	–0.08	0.05	0.08
HDL	–0.01	0.02	0.61
Non-HDL	0.08	0.21	0.69
LDL–HDL	–0.02	0.003	<0.001¹
TC-HDL	0.003	0.004	0.34
TG-HDL	–0.002	0.003	0.55
VLDL	–0.34	0.39	0.39
ApoA-1	–0.001	0.001	0.45
ApoB	–0.001	0.001	0.47
ApoB-ApoA1	–0.001	0.0003	<0.001¹
Endothelial functions
FMD, %	–0.004	0.008	0.68
E-selectin	–0.02	0.05	0.65
sICAM-1	–0.03	0.45	0.94
sVCAM-1	–0.55	0.63	0.38
Inflammatory markers
CRP	0.01	0.01	0.25
TNF-α	–0.01	0.003	0.06
IL-6	–0.03	0.004	<0.001¹
CVD risk, %	0.02	0.02	0.31
Body composition
BW	–0.002	0.01	0.87
BMI	0.002	0.004	0.61
FM	0.01	0.008	0.13
BFP	–0.002	0.006	0.72
LM	–0.01	0.007	0.13
FFM	0.002	0.003	0.37
WC	0.02	0.01	0.15
HC	–0.02	0.02	0.40
WHR	0.0001	0.0002	0.65
VAT	0.003	0.003	0.43

Open in a new tab

Restricted maximum likelihood (REML) was used for conducting the analyses.

Abbreviations: ApoA1, Apolipoprotein A-I; ApoB, Apolipoprotein B; BFP, body fat percentage; BW, body weight (kg); CRP, C-reactive protein; CVD risk%, cardiovascular disease risk (percentage); DBP, diastolic blood pressure; FFM, fat-free mass (kg); FM, fat mass (kg); FMD%, flow-mediated dilation (percentage); HC, hip circumference (cm); LM, lean mass (kg); SBP, systolic blood pressure; sICAM-1, soluble intercellular adhesion molecule-1; sVCAM-1, soluble vascular cell adhesion molecule-1; TC, total cholesterol; TG, triglycerides; VAT, visceral adipose tissue; WC, waist circumference (cm); WHR, waist–hip ratio.

Represents statistical significance after adjusted for multiple testing correction (P < 0.00125) among analyses included >4 studies (k ≥ 4).

Subgroup analyses of participants’ characteristics

Subgroup analyses based on participant characteristics were conducted to explore differential effects (Table 4).

TABLE 4.

Subgroup analysis of population characteristics (sex, weight, and diabetic status).

	Male		Female		Diff.
	SMD (95% CI)	P	SMD (95% CI)	P	Qb(1)	P
Blood pressure
SBP (3 vs. 17)¹	–5.34² (–12.28, 1.60)	0.13	–2.10 (–5.66, 1.45)	0.25	0.66	0.42
DBP (4 vs. 20)¹	–0.28 (–5.07, 4.50)	0.91	–1.41 (–2.77, –0.04)	<0.05	0.20	0.66
Lipid profile
TG (11 vs. 29)¹	–29.20 (–48.55, –11.88)	<0.001³	–14.47 (–23.34, –5.81)	<0.001³	2.20	0.14
TC (12 vs. 27)¹	9.30 (–2.98, 21.58)	0.14	2.56 (–2.81, 7.93)	0.35	0.97	0.32
LDL (12 vs. 27)¹	6.76 (–7.50, 21.02)	0.35	3.99 (–0.05, 8.02)	0.05	0.13	0.71
HDL (11 vs. 27)¹	1.77 (–0.97, 4.50)	0.21	3.04 (1.27, 4.81)	<0.001³	0.59	0.44
TC-HDL (6 vs. 8)¹	0.02 (–0.17, 0.21)	0.82	–0.17 (–0.30, –0.04)	<0.05	2.73	0.10
Inflammatory markers
CRP (2 vs. 10)¹	–2.23² (–5.09, 0.63)	0.13	–1.76 (–3.80, 0.28)	0.09	0.07	0.79
Body composition
BW (7 vs. 26)¹	–1.08 (–3.16, 1.01)	0.31	–1.91 (–3.30, –0.51)	<0.05	0.42	0.52
BMI (9 vs. 22)¹	–0.53 (–0.96, –0.10)	<0.05	–0.90 (–1.40, –0.40)	<0.001³	1.23	0.27
FM (6 vs. 14)¹	–1.44 (–3.12, 0.23)	0.09	–1.40 (–2.11, –0.70)	<0.001³	0.00	0.96
BFP (6 vs. 11)¹	–1.09 (–2.45, 0.27)	0.12	–1.17 (–1.86, –0.48)	<.001³	0.01	0.92
LM (3 vs. 11)¹	0.11² (–0.32, 0.53)	0.62	–0.17 (–0.50, 0.16)	0.31	1.03	0.31
FFM (4 vs. 6)¹	–0.47 (–1.17, 0.23)	0.19	–0.60 (–0.77, –0.43)	<0.001³	0.11	0.74
WC (6 vs. 16)¹	–1.77 (–5.04, 1.49)	0.29	–3.13 (–5.11, –1.16)	<0.001³	0.49	0.49
HC (0 vs. 6)¹	—		–1.31 (–3.07, 0.45)	0.14	—
WHR (0 vs. 10)¹	—		–0.01 (–0.02, –0.01)	<0.001³	—

	Nonoverweight		Overweight/obese		Diff.
	SMD (95% CI)	P	SMD (95% CI)	P	Qb(1)	P

Blood pressure
SBP (2 vs. 71)⁴	–2.86² (–8.94, 3.21)	0.36	–1.74 (–3.01, –0.56)	<0.001³	0.13	0.72
DBP (2 vs. 70)⁴	4.06² (–3.58, 11.71)	0.30	–1.15 (–1.89, –0.42)	<0.001³	10.77	0.18
Lipid profile
TG (5 vs. 114)⁴	–8.01 (–28.16, 12.13)	0.44	–13.70 (–17.72, –9.67)	<0.001³	0.29	0.59
TC (5 vs. 100)⁴	10.66 (–6.47, 27.80)	0.22	4.21 (1.21, 7.29)	<0.05	0.53	0.47
LDL (5 vs. 111)⁴	9.44 (–3.10, 21.98)	0.14	5.06 (2.56, 7.71)	<0.001³	0.45	0.50
HDL (5 vs. 112)⁴	3.70 (–0.20, 7.60)	0.06	2.72 (1.81, 3.54)	<0.001³	0.23	0.63
Non-HDL (2 vs. 7)⁴	18.17² (–6.07, 42.41)	0.14	2.57 (–2.61, 7.74)	0.33	1.52	0.22
LDL–HDL (1 vs.5)⁴	0.01² (–0.05, 0.07)	0.76	–0.27 (–0.39, –0.16)	<0.001³	17.33	<0.001
TC-HDL (1 vs. 24)⁴	–0.05² (–0.06, –0.04)	<0.001	–0.11 (–0.27, 0.08)	0.19	0.56	0.46
TG-HDL (0 vs. 14)⁴	—		–0.34 (–0.46, –0.21)	<0.001³	—
ApoA1 (1 vs. 9)⁴	0.20² (0.15, 0.25)	<0.001	0.02 (0.00, 0.05)	<0.05	38.12	<0.001
ApoB (2 vs. 13)⁴	0.11² (–0.05, 0.28)	0.18	0.01 (–0.02, 0.04)	0.54	1.40	0.24
ApoB-ApoA1 (0 vs. 5)⁴	—		–0.03 (–0.04, –0.01)	<0.001³	—
Endothelial functions
FMD, % (0 vs. 5)⁴	—		0.26 (–0.22, 0.75)	0.29	—
E-selectin (0 vs. 7)⁴	—		–1.89 (–3.74, –0.04)	0.05	—
sICAM-1 (0 vs. 6)⁴	—		–11.76 (–29.56, 6.04)	0.20	—
sVCAM-1 (0 vs. 5)⁴	—		–1.11 (–20.89, 18.67)	0.91	—
Inflammatory markers
CRP (1 vs. 45)⁴	–0.80² (–1.37, –0.23)	<0.05	–0.31 (–0.54, –0.02)	<0.05	2.32	0.13
TNF-α (1 vs. 7)⁴	–0.11² (–0.19, –0.03)	<0.05	–0.29 (–0.49, –0.10)	<0.001³	2.98	0.08
IL-6 (1 vs. 7)⁴	–0.34² (–1.54, 0.86)	0.58	–0.31 (–0.93, 0.30)	0.32	0.00	0.97
Body composition
BW (3 vs. 104)⁴	0.19 (–0.44, 0.82)	0.56	–1.90 (–2.45, –1.40)	<0.001³	24.81	<0.001³
BMI (4 vs. 74)⁴	–0.30 (–0.84, 0.23)	0.27	–0.78 (–0.98, –0.52)	<0.001³	31.45	<0.001³
FM (2 vs. 56)⁴	0.19² (0.00, 0.97)	0.64	–0.75 (–1.11, –0.38)	<0.001³	4.51	<0.05
BFP (1 vs. 40)⁴	–0.30² (–0.82, 0.22)	0.25	–0.70 (–1.03, –0.37)	<0.001³	1.65	0.20
LM (0 vs. 24)⁴	—		–0.24 (–0.53, 0.05)	0.11	—
FFM (1 vs. 24)⁴	0²	1.00	–0.43 (–0.60, –0.25)	<0.001³	1.60	0.21
WC (2 vs. 68)⁴	–0.77² (–3.90, 2.37)	0.63	–1.96 (–2.74, –1.31)	<0.001³	0.53	0.47
HC (0 vs. 13)⁴	—		–1.70 (–2.78, –0.62)	<0.001³	—
WHR (0 vs. 20)⁴	—		–0.01 (–0.02, 0.00)	<0.05	—
VAT (0 vs. 4)⁴	—		–0.19 (–0.31, –0.07)	<0.001³	—

	Nondiabetic		T2D		Diff.
	SMD (95% CI)	P	SMD (95% CI)	P	Qb(1)	P

Blood pressure
SBP (41 vs. 23)⁵	–2.02 (–3.03, –1.02)	<0.001³	–1.56 (–3.79, 0.68)	0.17	0.08	0.77
DBP (44 vs. 20)⁵	–1.05 (–2.02, –0.10)	<0.05	–1.41 (–3.00, 0.19)	0.08	0.14	0.71
Lipid profile
TG (73 vs. 35)⁵	–14.17 (–19.29, –9.07)	<0.001³	–14.15 (–22.17, –6.14)	<0.001³	0.00	1.00
TC (67 vs. 27)⁵	4.41 (0.62, 8.33)	<0.05	0.09 (–3.19, 3.38)	0.96	2.84	0.09
LDL (72 vs. 32)⁵	5.44 (2.34, 8.77)	<0.001³	1.27 (–1.77, 4.32)	0.41	3.45	0.06
HDL (72 vs. 33)⁵	2.79 (1.77, 3.66)	<0.001³	4.03 (1.28, 6.79)	<0.001³	0.70	0.40
Non-HDL (7 vs. 4)⁵	6.83 (–2.04, 15.69)	0.13	–5.87 (–14.17, 2.43)	0.17	4.20	<0.05
LDL–HDL (5 vs. 1)⁵	–0.15 (–0.41, 0.11)	0.26	–0.09² (–0.28, 0.10)	0.36	0.13	0.72
TC-HDL (20 vs. 5)⁵	–0.14 (–0.33, 0.09)	0.17	–0.20 (–0.40, 0.00)	0.05	0.18	0.67
TG-HDL (8 vs. 1)⁵	–0.30 (–0.53, –0.08)	<0.05	–0.60² (–0.65, –0.55)	<0.001	6.18	<0.05
VLDL (4 vs. 4)⁵	–4.56 (–8.58, –0.55)	<0.05	–5.44 (–10.61, –0.26)	<0.05	0.07	0.79
ApoA1 (8 vs. 6)⁵	0.06 (0.02, 0.11)	<0.05	0.00 (–0.04, 0.05)	0.95	3.44	0.06
ApoB (13 vs. 7)⁵	0.04 (0.00, 0.09)	0.06	–0.01 (–0.06, 0.04)	0.70	2.51	0.11
Endothelial functions
E-selectin (6 vs. 1)⁵	–1.85 (–3.70, 0.01)	0.05	–11.00² (–39.26, 17.26)	0.45	0.40	0.53
sICAM-1 (5 vs. 1)⁵	–9.87 (–28.97, 9.22)	0.31	–35.00² (–90.02, 20.02)	0.21	0.71	0.40
sVCAM-1 (4 vs. 1)⁵	0.93 (–30.01, 31.88)	0.95	–0.30² (–0.75, 0.15)	0.19	0.01	0.94
Inflammatory markers
CRP (32 vs. 12)⁵	–0.73 (–1.19, –0.20)	<0.001³	0.10 (–0.44, 0.64)	0.72	5.07	<0.05
TNF-α (9 vs. 0)⁵	–0.27 (–0.43, –0.11)	<0.001³	—		—
IL-6 (8 vs. 0)⁵	–0.24 (–0.74, 0.26)	0.36	—		—
Body composition
BW (63 vs. 34)⁵	–1.41 (–1.93, –0.88)	<0.001³	–2.03 (–3.01, –1.05)	<0.001³	1.20	0.27
BMI (41 vs. 25)⁵	–0.61 (–0.80, –0.43)	<0.001³	–0.99 (–1.49, –0.48)	<0.001³	1.66	0.17
FM (38 vs. 9)⁵	–0.93 (–1.48, –0.40)	<0.001³	–0.57 (–1.18, 0.05)	0.07	0.75	0.38
BFP (28 vs. 8)⁵	–0.79 (–1.23, –0.35)	<0.001³	–0.65 (–1.27, –0.03)	<0.05	0.13	0.72
LM (21 vs. 2)⁵	–0.33 (–0.67, 0.00)	0.05	–1.32² (–3.82, 1.18)	0.30	0.59	0.44
FFM (10 vs. 5)⁵	–0.52 (–0.78, –0.27)	<0.001³	–0.18 (–0.28, –0.08)	<0.001³	6.14	<0.05
WC (40 vs. 22)⁵	–1.54 (–2.23, –0.86)	<0.001³	–2.34 (–3.59, –1.10)	<0.001³	1.21	0.27
HC (10 vs. 5)⁵	–1.50 (–2.56, –0.43)	<0.05	–2.60 (–4.35, –0.86)	<0.001³	1.12	0.29
WHR (16 vs. 1)⁵	–0.01 (–0.01, 0.00)	0.16	–0.01² (–0.04, 0.02)	0.48	0.07	0.80
VAT (4 vs. 1)⁵	–0.37 (–0.67, –0.06)	<0.05	–0.14² (–0.18, –0.10)	<0.001	2.12	0.15

Open in a new tab

Restricted maximum likelihood (REML) was used for conducting the analyses.

Abbreviations: 95% CI, 95% confidence interval; ApoA1, Apolipoprotein A-I; ApoB, Apolipoprotein B; BFP, body fat percentage; BW, body weight (kg); CRP, C-reactive protein; CVD risk%, cardiovascular disease risk (percentage); DBP, diastolic blood pressure; Diff., group difference; FFM, fat-free mass (kg); FM, fat mass (kg); FMD%, flow-mediated dilation (percentage); HC, hip circumference (cm); LM, lean mass (kg); Q(b), Cochran’s Q-between statistics; SBP, systolic blood pressure; sICAM-1, soluble intercellular adhesion molecule-1; SMD, standardized mean difference; sVCAM-1, soluble vascular cell adhesion molecule-1; T2D, type 2 diabetes; TC, total cholesterol; TG, triglycerides; VAT, visceral adipose tissue; WC, waist circumference (cm); WHR, waist–hip ratio.

(k vs. k) stands for the number of observations included for each associated group: male vs. female.

Represents the number analyzed by fewer than 4 observations for the particular group.

Represents statistical significance after adjusted for multiple testing correction (P < 0.00125) among analyses included >4 studies (k ≥ 4).

⁴

(k vs. k) stands for the number of observations included for each associated group: nonoverweight vs. overweight/obesity.

⁵

(k vs. k) stands for the number of observations included for each associated group: nondiabetic vs. T2D.

The effects of sex

After adjustment for multiple testing (corrected alpha: P < 0.0025), both sexes exhibited significant reductions in TG. However, females demonstrated more pronounced improvements in cardiovascular and anthropometric outcomes, including increased HDL, as well as reductions in BMI, DBP, BFP, WC, and WHR. Despite these trends, formal group comparisons revealed no statistically significant differences between sexes (Table 4).

The effects of weight status

Among individuals with overweight/obesity, significant improvements were observed in blood pressure, various lipid profile markers, and all anthropometric measures, except for LM and WHR. In contrast, nonoverweight individuals showed minimal changes. Group comparisons confirmed significantly greater reductions in BW and BMI in the overweight/obesity group (Table 4).

The effects of diabetic status

Both nondiabetic and T2DM groups exhibited significant decreases in TG, BW, BMI, FFM, and WC, alongside increased HDL. Although each group displayed unique significant outcomes, none reached statistical significance in direct group comparisons (Table 4).

Sensitivity analysis results

Sensitivity analyses revealed additional significant reductions in SBP, CRP, and BW among females, as well as decreases in FM and BFP in individuals with T2DM. Overall, most outcomes remained consistent with the primary analyses, supporting the robustness of the findings (Supplemental Table 5).

Effects of study characteristics

Analyses with >4 studies (corrected alpha: P < 0.0025) revealed differential effects across study designs and intervention characteristics (Table 5). For study designs, although no statistically significant differences emerged between groups, randomized parallel trials demonstrated significant improvements in blood pressure, multiple lipid parameters, and anthropometric measures. In contrast, randomized crossover trials showed effects limited to TG, BMI, BFP, and WC. As for intervention delivery methods, consultation-only interventions produced more pronounced improvements in blood pressure and anthropometric outcomes compared with food-provided interventions. Lastly, when considering energy balance, nonisocaloric and isocaloric interventions showed similar effects on lipid profiles and body composition. However, differential blood pressure effects were observed: isocaloric studies demonstrated significant reductions in systolic blood pressure (SBP), whereas nonisocaloric studies showed decreases in DBP (Table 5). Overall, the sensitivity analyses showed minor variations in statistical significance, but the overall pattern of results remained consistent with the primary analyses (Supplemental Table 6).

TABLE 5.

Subgroup analysis of study characteristics.

	Crossover		Parallel		Diff.
	SMD (95% CI)	P	SMD (95% CI)	P	Qb(1)	P
Blood pressure
SBP (16 vs. 73)¹	–1.43 (–3.24, 0.37)	0.12	–2.04 (–3.35, –0.85)	<0.001²	0.30	0.58
DBP (16 vs. 74)¹	–1.17 (–2.04, –0.31)	<0.05	–1.24 (–2.05, –0.45)	<0.001²	0.01	0.91
Lipid profile
TG (35 vs. 109)¹	–18.76 (–26.68, –10.84)	<0.001²	–14.01 (–18.76, –11.46)	<0.001²	1.10	0.29
TC (34 vs. 95)¹	4.19 (–2.09, 10.47)	0.19	4.28 (1.42, 7.21)	<0.001²	0.00	0.98
LDL (35 vs. 107)¹	5.32 (1.23, 9.42)	<0.05	4.62 (2.04, 7.33)	<0.001²	0.08	0.78
HDL (32 vs. 111)¹	2.73 (0.75, 4.71)	<0.05	3.00 (2.07, 3.86)	<0.001²	0.06	0.81
Non-HDL (5 vs. 7)¹	–2.48 (–11.97, 7.00)	0.61	5.18 (–3.68, 14.05)	0.25	1.34	0.25
LDL–HDL (4 vs. 4)¹	–0.09 (–0.26, 0.08)	0.29	–0.21 (–0.38, –0.05)	<0.05	1.01	0.31
TC-HDL (14 vs. 19)¹	–0.15 (–0.29, –0.01)	<0.05	–0.12 (–0.31, 0.11)	0.22	0.04	0.85
TG-HDL (4 vs. 12)¹	–0.19 (–0.43, 0.05)	0.11	–0.35 (–0.49, –0.22)	<0.001²	1.32	0.25
VLDL (7 vs. 3)¹	–1.91 (–5.14, 1.32)	0.25	–5.05³ (–8.16, –1.95)	<0.001	1.90	0.17
ApoA1 (7 vs. 7)¹	0.04 (0.00, 0.07)	<0.05	0.04 (–0.02, 0.10)	0.20	0.00	0.96
ApoB (6 vs. 14)¹	0.01 (–0.05, 0.06)	0.80	0.03 (–0.01, 0.07)	0.19	0.35	0.56
Endothelial functions
FMD, % (1 vs. 6)¹	1.00³ (–0.64, 2.64)	0.23	0.04 (–0.51, 0.59)	0.89	1.19	0.28
E-selectin (4 vs. 4)¹	–0.05 (–0.45, 0.36)	0.82	–3.31 (–5.69, –0.94)	<0.05	7.05	<0.05
sICAM-1(3 vs. 4)¹	–3.30³ (–11.54, 4.94)	0.43	–14.57 (–38.70, 9.57)	0.24	0.75	0.39
Inflammatory markers
CRP (8 vs. 47)¹	–.45 (–1.01, 0.10)	0.11	–0.42 (–0.76, 0.00)	<0.05	0.01	0.91
TNF-α (2 vs. 8)¹	–0.11³ (–0.19, –0.03)	<0.05	–0.30 (–0.48, –0.12)	<0.001²	3.79	0.05
IL-6 (4 vs. 6)¹	–0.04 (–0.12, 0.04)	0.34	–0.24 (–0.94, 0.47)	0.51	0.30	0.59
Body composition
BW (29 vs. 106)¹	–0.78 (–1.76, 0.20)	0.12	–1.94 (–2.43, –1.45)	<0.001²	4.35	<0.05
BMI (17 vs. 76)¹	–0.48 (–0.80, –0.16)	<0.001²	–0.74 (–0.97, –0.51)	<0.001²	1.61	0.20
FM (10 vs. 56)¹	–1.00 (–1.70, –0.29)	<0.05	–0.83 (–1.22, –0.44)	<0.001²	0.17	0.68
BFP (11 vs. 37)¹	–0.90 (–1.48, –0.32)	<0.001²	–0.76 (–1.10, –0.39)	<0.001²	0.20	0.66
LM (6 vs. 25)¹	–0.45 (–1.91, 1.01)	0.55	–0.29 (–0.57, –0.02)	<0.05	0.04	0.84
FFM (3 vs. 24)¹	–1.12³ (–3.50, 1.26)	0.36	–0.42 (–0.58, –0.26)	<0.001²	0.33	0.56
WC (15 vs. 66)¹	–2.20 (–3.39, –1.00)	<0.001	–1.80 (–2.52, –1.08)	<0.001²	0.32	0.57
HC (3 vs. 15)¹	–.40³ (–1.83, 1.03)	0.58	–1.91 (–2.85, –0.97)	<0.001²	2.99	0.08
WHR (1 vs. 22)¹	–0.01³ (–0.04, 0.02)	0.48	–0.01 (–0.02, 0.00)	<0.05	0.01	0.91
VAT (0 vs. 6)¹	—		–0.28 (–0.50, –0.05)	<0.05		—

	Consultation		Food		Diff.
	SMD (95% CI)	P	SMD (95% CI)	P	Qb(1)	P

Blood pressure
SBP (68 vs. 20)⁴	–2.29 (–3.59, –0.98)	<0.001²	–1.30 (–3.11, 0.51)	0.16	0.67	0.41
DBP (73 vs. 17)⁴	–1.32 (–2.11, –0.55)	<0.001²	–0.98 (–2.44, 0.48)	0.19	0.16	0.69
Lipid profile
TG (103 vs. 41)⁴	–13.69 (–17.97, –9.41)	<0.001²	–18.65 (–25.56, –11.74)	<0.001²	1.44	0.23
TC (93 vs. 36)⁴	6.52 (3.20, 9.99)	<0.001²	–1.19 (–4.45, 2.08)	0.48	10.42	<0.001²
LDL (102 vs. 40)⁴	7.06 (4.61, 9.70)	<0.001²	–1.07 (–5.05, 2.90)	0.60	11.46	<0.001²
HDL (104 vs. 39)⁴	3.38 (2.27, 4.41)	<0.001²	2.00 (0.81, 3.18)	<0.001²	2.89	0.09
Non-HDL (5 vs. 7)⁴	7.42 (–4.16, 18.99)	0.21	–1.91 (–9.20, 5.38)	0.61	1.78	0.18
LDL–HDL (3 vs. 5)⁴	–0.33³ (–0.47, –0.19)	<0.001	–0.09 (–0.22, 0.04)	0.19	5.99	<0.05
TC-HDL (22 vs. 11)⁴	–0.09 (–0.26, 0.11)	0.30	–0.18 (–0.27, –0.08)	<0.001²	0.71	0.40
TG-HDL (14 vs. 2)⁴	–0.33 (–0.45, –0.21)	<0.001	–0.25³ (–0.74, 0.24)	0.31	0.09	0.76
VLDL (5 vs. 5)⁴	–2.22 (–5.50, 1.06)	0.19	–5.30 (–10.17, –0.42)	<0.05	1.06	0.30
ApoA1 (6 vs. 8)⁴	0.06 (0.00, 0.13)	0.06	0.02 (–0.01, 0.06)	0.20	1.21	0.27
ApoB (11 vs. 9)⁴	0.06 (0.01, 0.12)	<0.05	–0.01 (–0.03, 0.01)	0.39	5.81	<0.05
ApoB-ApoA1 (1 vs. 5)⁴	–0.05³ (–0.05, –0.05)	<0.001	–0.02 (–0.03, –0.01)	<0.001²	25.47	<0.001
Endothelial functions
FMD, % (6 vs. 1)⁴	0.15 (–0.39, 0.68)	0.59	–1.50³ (–4.92, 1.92)	0.39	0.87	0.35
E-selectin (6 vs. 2)⁴	–2.01 (–4.11, 0.09)	0.06	–2.49³ (–7.30, 2.31)	0.31	0.03	0.86
sICAM-1(7 vs. 0)⁴	–12.60 (–28.93, 3.72)	0.13	—		—
sVCAM-1(5 vs. 1)⁴	–0.02 (–29.59, 29.56)	1.00	–0.30³ (–0.75, 0.15)	0.19	0.00	0.99
Inflammatory markers
CRP (46 vs. 9)⁴	–0.33 (–0.57, –0.03)	<0.001²	–1.41 (–3.83, 1.01)	0.25	0.75	0.39
TNF-α (6 vs. 4)⁴	–0.40 (–0.60, –0.20)	<0.001²	–0.11 (–0.17, –0.04)	<0.001²	7.38	<0.05
IL-6 (5 vs. 5)⁴	–0.23 (–1.01, 0.55)	0.57	–0.07 (–0.24, 0.10)	0.42	0.15	0.70
CVD risk, % (4 vs. 0)⁴	–1.05 (–1.89, –0.21)	<0.05	—		—
Body composition
BW (99 vs. 36)⁴	–1.99 (–2.56, –1.42)	<0.001²	–1.14 (–1.73, –0.56)	<0.001²	4.10	<0.05
BMI (72 vs. 21)⁴	–0.82 (–1.08, –0.56)	<0.001²	–0.42 (–0.66, –0.18)	<0.001²	5.02	<0.05
FM (49 vs. 17)⁴	–0.78 (–1.19, –0.38)	<0.001²	–0.98 (–1.69, –0.26)	<0.05	0.22	0.64
BFP (34 vs. 14)⁴	–0.80 (–1.17, –0.43)	<0.001²	–0.73 (––1.30, –0.18)	<0.05	0.04	0.84
LM (23 vs. 8)⁴	–0.20 (–.54, 0.14)	0.25	–0.58 (–1.14, –0.01)	<0.05	1.27	0.26
FFM (20 vs. 7)⁴	–0.44 (–0.61, –0.27)	<0.001²	–0.26 (–0.76, 0.24)	0.31	0.44	0.51
WC (67 vs. 17)⁴	–1.93 (–2.65, –1.20)	<0.001²	–1.59 (–2.73, –0.45)	<0.05	0.23	0.63
HC (13 vs. 5)⁴	–1.97 (–2.83, –1.10)	<0.001²	–1.04 (–3.04, 0.96)	0.31	0.69	0.40
WHR (20 vs. 3)⁴	–0.01 (–0.02, 0.00)	0.09	–0.02³ (–0.04, 0.01)	0.15	0.72	0.40
VAT (5 vs. 1)⁴	–0.25 (–0.52, 0.01)	0.06	–0.40³ (–0.55, –0.25)	<0.001	0.87	0.35

	Nonisocaloric		Isocaloric		Diff.
	SMD (95% CI)	P	SMD (95% CI)	P	Qb(1)	P

Blood pressure
SBP (38 vs. 37)⁵	–1.66 (–3.51, 0.18)	0.08	–1.96 (–3.28, –0.65)	<0.001²	0.07	0.79
DBP (41 vs. 74)⁵	–1.20 (–1.97, –0.43)	<0.001²	–0.84 (–2.02, 0.34)	0.16	0.26	0.61
Lipid profile
TG (60 vs. 60)⁵	–18.79 (–24.95, –12.64)	<0.001²	–12.60 (–17.45, –7.75)	<0.001²	2.40	0.12
TC (54 vs. 54)⁵	4.97 (0.57, 9.38)	<0.05	3.34 (–0.30, 6.97)	0.07	0.32	0.57
LDL (62 vs. 58)⁵	4.79 (0.99, 8.59)	<0.05	4.54 (1.52, 7.55)	<0.001²	0.01	0.92
HDL (63 vs. 60)⁵	2.97 (1.37, 4.57)	<0.001²	2.56 (1.70, 3.42)	<0.001²	0.20	0.66
Non-HDL (3 vs. 5)⁵	–0.58³ (–5.80, 4.63)	0.83	0.32 (–5.74, 6.39)	0.92	0.05	0.82
TC-HDL (13 vs. 13)⁵	–0.07 (–0.22, 0.08)	0.34	–0.17 (–0.45, 0.12)	0.25	0.35	0.56
TG-HDL (6 vs. 6)⁵	–0.28 (–0.45, –0.11)	<0.001²	–0.48 (–0.75, –0.20)	<0.001²	1.39	0.24
VLDL (4 vs. 5)⁵	–3.96 (–8.47, 0.55)	0.08	–0.50 (–1.21, 0.22)	0.17	2.21	0.14
ApoA1 (8 vs. 6)⁵	0.02 (0.00, 0.04)	0.11	0.06 (–0.01, 0.13)	0.09	1.19	0.28
ApoB (8 vs. 11)⁵	–0.00 (–0.05, 0.04)	0.83	0.05 (0.00, 0.11)	<0.05	2.87	0.09
Inflammatory markers
CRP (26 vs. 23)⁵	–0.52 (–1.05, 0.00)	0.05	–0.14 (–0.50, 0.22)	0.44	1.38	0.24
TNF-α (3 vs. 4)⁵	–0.23³ (–0.45, 0.00)	0.05	–0.17 (–0.32, –0.02)	<0.05	0.16	0.69
Body composition
BW (50 vs. 50)⁵	–1.86 (–2.72, –1.01)	<0.001²	–1.27 (–1.83, –0.70)	<0.001²	1.30	0.25
BMI (36 vs. 38)⁵	–.92 (–1.28, –0.55)	<0.001²	–0.55 (–0.84, –0.25)	<0.001²	2.31	0.13
FM (22 vs. 27)⁵	–1.00 (–1.60, –0.41)	<0.001²	–0.52 (–1.06, 0.05)	0.07	1.35	0.25
BFP (17 vs. 18)⁵	–0.62 (–1.13, –0.11)	<0.05	–0.83 (–1.37, –0.28)	<0.001²	0.30	0.58
LM (6 vs. 25)⁵	–0.71 (–1.17, –0.24)	<0.001²	–0.11 (–0.74, 0.52)	0.73	2.22	0.14
FFM (9 vs. 11)⁵	–0.21 (–0.44, 0.02)	0.07	–0.54 (–0.82, –0.26)	<0.001²	3.08	0.08
WC (30 vs. 66)⁵	–2.82 (–3.98, –1.67)	<0.001²	–0.90 (–1.67, –0.14)	<0.05	7.35	<0.05
HC (5 vs. 8)⁵	–1.59 (–2.14, –1.04)	<0.001²	–1.77 (–3.39, –0.14)	<0.05	0.04	0.84
WHR (8 vs. 10)⁵	–0.01 (–0.02, 0.00)	<0.05	0.00 (–0.02, 0.01)	0.52	0.83	0.36

Open in a new tab

Restricted maximum likelihood (REML) was used for conducting the analyses.

Abbreviations: 95% CI, 95% confidence interval; ApoA1, Apolipoprotein A-I; ApoB, Apolipoprotein B; BFP, body fat percentage; BW, body weight (kg); Consultation, studies with consultation-only interventions; Crossover, crossover designs; CRP, C-reactive protein; CVD risk%, cardiovascular disease risk (percentage); DBP, diastolic blood pressure; Diff., group difference; FFM, fat-free mass (kg); Food, interventions with food provided; FM, fat mass (kg); FMD%, flow-mediated dilation (percentage); HC, hip circumference (cm); LM, lean mass (kg); Q(b), Cochran’s Q-between statistics; Parallel, parallel designs; SBP, systolic blood pressure; sICAM-1, soluble intercellular adhesion molecule-1; SMD, standardized mean difference; sVCAM-1, soluble vascular cell adhesion molecule-1; TC, total cholesterol; TG, triglycerides; VAT, visceral adipose tissue; WC, waist circumference (cm); WHR, waist–hip ratio.

(k vs. k) stands for the number of observations included for each associated group: crossover trials vs. parallel trials.

Represents statistical significance after adjusted for multiple testing correction (P < 0.00125) among analyses included >4 studies (k≥4).

Represents the number analyzed by fewer than 4 observations for the particular group.

⁴

(k vs. k) stands for the number of observations included for each associated group: consultation-only interventions vs. food-provided intervention.

⁵

(k vs. k) stands for the number of observations included for each associated group: nonisocaloric diets vs. isocaloric diets.

Discussion

This meta-analysis of 174 randomized trials (n = 11,481; 27 countries) examined the effects of CRDs on cardiovascular and anthropometric outcomes. Consistent with previous meta-analyses [13,14], CRDs were associated with reduced TG, blood pressure, and increased HDL, LDL, and TC. The lipid energy model (LEM) offers a potential mechanistic explanation for these changes. Among lean individuals, with depletion of glucose and glycogen stores during CRDs, the body shifts toward utilizing fat (lipid) metabolism, leading to VLDL conversion to LDL and enhanced ApoA1 production, which supports HDL formation [209].

Given these mixed lipid effects, a critical question is whether CRDs are ultimately beneficial for cardiovascular health. This meta-analysis further evaluated stronger predictors of cardiovascular disease risk—lipid ratios (LDL–HDL, TG-HDL, and ApoB-ApoA1) [[210], [211], [212]]. Our findings demonstrated favorable effects on all these lipid ratios. Additionally, CRDs reduced inflammation and endothelial dysfunction markers (CRP, IL-6, and E-selectin). Overall, like previous studies [[8], [9], [10], [11], [12]], CRDs were associated with a significant reduction in overall CVD risk.

Regarding body composition, consistent with previous meta-analyses, CRDs led to significant reductions in BW [[15], [16], [17], [18],213], BMI [15,16,18], BFP [15,16,18], FFM, WC, FM, and VAT [18]. A significant reduction was also found in HC. The carbohydrate-insulin model provides a framework for these results: high insulin levels from carbohydrate intake promote lipogenesis and inhibit fat oxidation, favoring storage. CRDs lower insulin, which facilitates fat oxidation and weight loss. The observed loss of FFM and LM may be explained by the gluconeogenic demand for glucose by certain tissues, leading to protein catabolism.

A closer look at diets with various macronutrient proportions

The effects varied by carbohydrate restriction level. Blood pressure improved with LCD and MCD but not KD. Increases in LDL and TC were more pronounced with greater carbohydrate restriction (i.e., KD), likely due to higher dietary fat intake, consistent with the LEM [209]. However, the improvement in the TG:HDL ratio suggests this rise may not be atherogenic. Due to limited observations (k < 4), valid significant effects were minimal, indicating a need for research.

Certain anthropometric improvements followed a dose–response pattern, with greater weight and BMI loss seen in stricter diets. However, these also resulted in greater losses of LM and FFM. This trade-off suggests that MCDs may offer a more balanced option. KDs and LCDs may be preferred for aggressive weight loss, provided LM and lipids are monitored.

As for macronutrient replacement strategies, previous meta-analyses have reported that higher protein intake [9,214] and higher fat intake [9] are associated with reduced CVD risk. This study further indicates that replacing carbohydrates with fat improved the lipid profile (increased HDL, reduced TG). Substitution with protein lowered TC while preserving HDL. Most notably, a combination replacement (using both fat and protein) yielded the most comprehensive cardiometabolic benefits, including reductions in blood pressure, inflammation, and endothelial dysfunction. For body composition, fat replacement and combination replacement showed broad benefits across multiple anthropometric markers. The narrower benefits from protein replacement may be due to a smaller number of available studies. Overall, combination replacement appears optimal for improving both cardiovascular and anthropometric outcomes.

Differences in participants’ characteristics

CRDs exert sex-specific effects, with females exhibiting stronger cardiovascular improvements than males. Among participants with T2DM, CRDs led to greater enhancements in TG and HDL, without the elevations in LDL or TC. CRDs also conferred more pronounced anthropometric benefits (e.g., weight loss, WC reduction) in the T2DM subgroup.

For weight differences, a prior meta-analysis reports an inverse association between baseline BMI and LDL changes under LCDs: individuals with a healthy BMI (<25 kg/m²) experienced LDL increases, whereas those with overweight (BMI: 25–35 kg/m²) or obesity (BMI >35 kg/m²) showed neutral or reduced levels [215]. Contrary to the previous report, LDL increased even among individuals with overweight/obesity in this study. The "lipid overflow hypothesis" may explain: in obesity, saturated fat from a high-fat CRD could exacerbate the dysregulation of hepatic lipoprotein metabolism in individuals with dysfunctional adipose tissue [216]. Under CRDs, increased dietary fat intake may exacerbate this pathway, driving LDL rises. Further research is needed to clarify the interplay between macronutrient composition, adipose dysfunction, and lipid dynamics across various populations.

Differences in study designs

Sensitivity analyses found broadly consistent results across study designs. Parallel trials yielded more significant results than crossover designs. Consultation-only interventions produced stronger effects than those providing food, potentially because higher attrition in consultation studies left a more adherent and motivated completer population. Similar results between isocaloric and nonisocaloric trials might suggest that the macronutrient composition independently influences outcomes beyond caloric intake.

Potential negative effects of CRDs

Potential drawbacks include the observed reductions in LM and increases in LDL and TC. Other reported concerns include the risk of osteoporosis [217], nutritional deficiencies and gut microbiota dysbiosis [218], hair loss, muscle cramps [213], gastrointestinal complications [218], and hyperuricemia [219]. The evidence for renal impairment remains inclusive. Despite reported negative effects [220], research also suggested that nutritional ketosis, a metabolic state induced by KD, may confer renal benefits among people with T2DM [221]. Additionally, the utility of CRDs may be limited for high-intensity anaerobic athletes due to the reliance on glucose. Clinical supervision is advised for implementing very low-carbohydrate diets.

Limitations

Substantial heterogeneity was present due to diverse populations and interventions. Significant funnel plot asymmetry for outcomes including SBP, blood lipids (non-HDL, LDL:HDL, ApoB:ApoA1), CVD (%), sICAM-1, WC, HC, WHR, and VAT indicates potential publication bias, which may inflate effect estimates and necessitates cautious interpretation of these results. The conservative adjusted alpha for multiple testing correction might increase type II error risk, potentially leading to the false dismissal of true effects for certain outcomes. Use of SMDs may have inflated variance [222]. High attrition in some trials may also have introduced bias. To mitigate these issues, sensitivity analyses were conducted and confirmed the robustness of the findings. Another important limitation of this meta-analysis is the inadvertent omission of at least one eligible study [223], due to the search strategy (e.g., “RCT” not fully captured by our predefined search terms). While our results remain consistent with the findings of the omitted trial, we acknowledge that incomplete study inclusion has the potential to introduce bias. Future reviews should consider broader search strategies to minimize this risk. Other limitations include insufficient studies (k < 4) for certain subgroup analyses, an inability to assess food quality, and a geographic skew toward North America and Europe, with underrepresentation from Asia, Africa, and South America.

In conclusion, this meta-analysis supports the cardiovascular (including blood pressure, lipid profile, and inflammation markers) and anthropometric benefits of CRDs. MCDs provided a balanced benefit–risk profile, whereas stricter diets (LCD, KD) were more effective for weight loss. Replacing carbohydrates with a combination of fat and protein yielded the most comprehensive benefits. Benefits were most pronounced among females and individuals with overweight/obesity. Despite potential drawbacks, CRDs represent a viable dietary strategy for cardiovascular health when implemented with appropriate professional guidance, particularly for more restrictive regimens.

Author contributions

The authors’ responsibilities were as follows – SF, BC, AB: designed research; SF, RL, SC, HW: conducted research; SF, CT: analyzed data; RL: conducted visualization; SF, CT, BC: wrote the paper; SF, RL, CT, BC, AB: reviewed and revised the paper; SF: has primary responsibility for the final content; and all authors: read and approved the final manuscript.

Data availability

Data described in the manuscript, code book, and analytic code will be made publicly and freely available without restriction at https://figshare.com/s/7dd68520ec63bf964d77

Funding

The authors reported no funding received for this study.

Conflict of interest

The authors report no conflicts of interest.

Footnotes

^{Appendix A}

Supplementary data to this article can be found online at https://doi.org/10.1016/j.ajcnut.2025.09.012.

Appendix A. Supplementary data

The following are the Supplementary data to this article:

Multimedia component 1

mmc1.xlsx^{(85.3KB, xlsx)}

Multimedia component 2

mmc2.docx^{(87.9KB, docx)}

Multimedia component 3

mmc3.pdf^{(2.6MB, pdf)}

References

1.WHO, Cardiovascular diseases (CVDs), 2021 Updated July 31, 2025. Accessed August 20, 2025. Available from: https://www.who.int/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds).
2.Emerging Risk Factors Collaboration, Wormser D., Kaptoge S., Di Angelantonio E., Wood A.M., Pennells L., et al. Separate and combined associations of body-mass index and abdominal adiposity with cardiovascular disease: collaborative analysis of 58 prospective studies. Lancet. 2011;377(9771):1085–1095. doi: 10.1016/S0140-6736(11)60105-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
3.World Health Organization . 2025. Obesity and overweight. [Google Scholar]
4.Okunogbe A., Nugent R., Spencer G., Powis J., Ralston J., Wilding J. Economic impacts of overweight and obesity: current and future estimates for 161 countries. BMJ Glob. Health. 2022;7(9) [Google Scholar]
5.Kossoff E.H., Zupec-Kania B.A., Auvin S., Ballaban-Gil K.R., Christina Bergqvist A.G., Blackford R., et al. Optimal clinical management of children receiving dietary therapies for epilepsy: updated recommendations of the International Ketogenic Diet Study Group. Epilepsia Open. 2018;3(2):175–192. doi: 10.1002/epi4.12225. [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Zhu H., Bi D., Zhang Y., Kong C., Du J., Wu X., et al. Ketogenic diet for human diseases: the underlying mechanisms and potential for clinical implementations. Signal Transduct. Target. Ther. 2022;7(1):11. doi: 10.1038/s41392-021-00831-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Seyfried T.N., Sanderson T.M., El-Abbadi M.M., McGowan R., Mukherjee P. Role of glucose and ketone bodies in the metabolic control of experimental brain cancer. Br. J. Cancer. 2003;89(7):1375–1382. doi: 10.1038/sj.bjc.6601269. [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Jo U., Park K. Carbohydrate intake and risk of cardiovascular disease: a systematic review and meta-analysis of prospective studies. Nutrients. 2023;15(7):1740. doi: 10.3390/nu15071740. [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Ma Y., Zheng Z., Zhuang L., Wang H., Li A., Chen L., et al. Dietary macronutrient intake and cardiovascular disease risk and mortality: a systematic review and dose-response meta-analysis of prospective cohort studies. Nutrients. 2024;16(1):152. doi: 10.3390/nu16010152. [DOI] [PMC free article] [PubMed] [Google Scholar]
10.Qin P., Huang C., Jiang B., Wang X., Yang Y., Ma J., et al. Dietary carbohydrate quantity and quality and risk of cardiovascular disease, all-cause, cardiovascular and cancer mortality: a systematic review and meta-analysis. Clin. Nutr. 2023;42(2):148–165. doi: 10.1016/j.clnu.2022.12.010. [DOI] [PubMed] [Google Scholar]
11.Dwivedi A.K., Dubey P., Reddy S.Y., Clegg D.J. Associations of glycemic index and glycemic load with cardiovascular disease: updated evidence from meta-analysis and cohort studies. Curr. Cardiol. Rep. 2022;24(3):141–161. doi: 10.1007/s11886-022-01635-2. [DOI] [PubMed] [Google Scholar]
12.Mohammadifard N., Mansourian M., Firouzi S., Taheri M., Haghighatdoost F. Longitudinal association of dietary carbohydrate and the risk cardiovascular disease: a dose-response meta-analysis. Crit. Rev. Food Sci. Nutr. 2022;62(23):6277–6292. doi: 10.1080/10408398.2021.1900057. [DOI] [PubMed] [Google Scholar]
13.Dong T., Guo M., Zhang P., Sun G., Chen B. The effects of low-carbohydrate diets on cardiovascular risk factors: a meta-analysis. PLOS ONE. 2020;15(1) [Google Scholar]
14.Mansoor N., Vinknes K.J., Veierød M.B., Retterstøl K. Effects of low-carbohydrate diets v. low-fat diets on body weight and cardiovascular risk factors: a meta-analysis of randomised controlled trials. Br. J. Nutr. 2016;115(3):466–479. doi: 10.1017/S0007114515004699. [DOI] [PubMed] [Google Scholar]
15.Leung L.Y., Tam H.L., Ho J.K. Effects of ketogenic and low-carbohydrate diets on the body composition of adults with overweight or obesity: a systematic review and meta-analysis of randomised controlled trials. Clin. Nutr. 2025;46:10–18. doi: 10.1016/j.clnu.2025.01.017. [DOI] [PubMed] [Google Scholar]
16.Darand M., Hassanizadeh S., Talebi S., Darabi Z., Bagherniya M., Yaghoubi F., et al. Comparison of the effect of a low-carbohydrate diet with a low-fat diet on anthropometric indices and body fat percentage: a systematic review and meta-analysis of randomized controlled trials. J. Nutr. Food Secur. 2023;8(3):493–520. [Google Scholar]
17.Ashtary-Larky D., Bagheri R., Asbaghi O., Tinsley G.M., Kooti W., Abbasnezhad A., et al. Effects of resistance training combined with a ketogenic diet on body composition: a systematic review and meta-analysis. Crit. Rev. Food Sci. Nutr. 2022;62(21):5717–5732. doi: 10.1080/10408398.2021.1890689. [DOI] [PubMed] [Google Scholar]
18.Amini M.R., Aminianfar A., Naghshi S., Larijani B., Esmaillzadeh A. The effect of ketogenic diet on body composition and anthropometric measures: a systematic review and meta-analysis of randomized controlled trials. Crit. Rev. Food Sci. Nutr. 2022;62(13):3644–3657. doi: 10.1080/10408398.2020.1867957. [DOI] [PubMed] [Google Scholar]
19.Naude C.E., Schoonees A., Senekal M., Young T., Garner P., Volmink J. Low carbohydrate versus isoenergetic balanced diets for reducing weight and cardiovascular risk: a systematic review and meta-analysis. PLOS ONE. 2014;9(7) [Google Scholar]
20.Smith E.S., Smith H.A., Betts J.A., Gonzalez J.T., Atkinson G. A systematic review and meta-analysis comparing heterogeneity in body mass responses between low-carbohydrate and low-fat diets. Obesity (Silver Spring). 2020;28(10):1833–1842. doi: 10.1002/oby.22968. [DOI] [PubMed] [Google Scholar]
21.Wang Y., Zhou K., Wang V., Bao D., Zhou J. The effects of concurrent training combined with low-carbohydrate high-fat ketogenic diet on body composition and aerobic performance: a systematic review and meta-analysis. Int. J. Environ. Res. Public Health. 2022;19(18) [Google Scholar]
22.Seidelmann S.B., Claggett B., Cheng S., Henglin M., Shah A., Steffen L.M., et al. Dietary carbohydrate intake and mortality: a prospective cohort study and meta-analysis. Lancet Public Health. 2018;3(9):e419–e428. doi: 10.1016/S2468-2667(18)30135-X. [DOI] [PMC free article] [PubMed] [Google Scholar]
23.Feinman R.D., Pogozelski W.K., Astrup A., Bernstein R.K., Fine E.J., Westman E.C., et al. Dietary carbohydrate restriction as the first approach in diabetes management: critical review and evidence base. Nutrition. 2015;31(1):1–13. doi: 10.1016/j.nut.2014.06.011. [DOI] [PubMed] [Google Scholar]
24.Ebbeling C.B., Swain J.F., Feldman H.A., Wong W.W., Hachey D.L., Garcia-Lago E., et al. Effects of dietary composition on energy expenditure during weight-loss maintenance. JAMA. 2012;307(24):2627–2634. doi: 10.1001/jama.2012.6607. [DOI] [PMC free article] [PubMed] [Google Scholar]
25.Page M.J., Moher D., Bossuyt P.M., Boutron I., Hoffmann T.C., Mulrow C.D., et al. PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. BMJ. 2021;372 [Google Scholar]
26.Feng S., Liu R., Thompson C., Colwell B. The associations between secondhand smoke exposure and various cardiovascular diseases: a meta-analysis. Nicotine Tob. Res. 2025 doi: 10.1093/ntr/ntaf111. [DOI] [Google Scholar]
27.Parry-Strong A., Wright-McNaughton M., Weatherall M., Hall R.M., Coppell K.J., Barthow C., et al. Very low carbohydrate (ketogenic) diets in type 2 diabetes: a systematic review and meta-analysis of randomized controlled trials. Diabetes Obes. Metab. 2022;24(12):2431–2442. doi: 10.1111/dom.14837. [DOI] [PMC free article] [PubMed] [Google Scholar]
28.Willems A.E.M., Sura-de Jong M., van Beek A.P., Nederhof E., van Dijk G. Effects of macronutrient intake in obesity: a meta-analysis of low-carbohydrate and low-fat diets on markers of the metabolic syndrome. Nutr. Rev. 2021;79(4):429–444. doi: 10.1093/nutrit/nuaa044. [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Sterne J.A.C., Savović J., Page M.J., Elbers R.G., Blencowe N.S., Boutron I., et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ. 2019;366 [Google Scholar]
30.Hoppen T.H., Cuno R.M., Nelson J., Lemmel F., Schlechter P., Morina N. Meta-analysis of randomized controlled trials examining social comparison as a behaviour change technique across the behavioural sciences. Nat. Hum. Behav. 2025;9(8):1595–1612. doi: 10.1038/s41562-025-02209-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Veroniki A.A., Jackson D., Viechtbauer W., Bender R., Bowden J., Knapp G., et al. Methods to estimate the between-study variance and its uncertainty in meta-analysis. Res. Synth. Methods. 2016;7(1):55–79. doi: 10.1002/jrsm.1164. [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Langan D., Higgins J.P.T., Simmonds M. Comparative performance of heterogeneity variance estimators in meta-analysis: a review of simulation studies. Res. Synth. Methods. 2017;8(2):181–198. doi: 10.1002/jrsm.1198. [DOI] [PubMed] [Google Scholar]
33.Viechtbauer W. Bias and efficiency of meta-analytic variance estimators in the random-effects model. J. Educ. Behav. Stat. 2005;30(3):261–293. [Google Scholar]
34.Ludwig D.S., Ebbeling C.B. The carbohydrate-insulin model of obesity: beyond "calories in, calories out,". JAMA Intern. Med. 2018;178(8):1098–1103. doi: 10.1001/jamainternmed.2018.2933. [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Abete I., Parra D., De Morentin B.M., Alfredo Martinez J. Effects of two energy-restricted diets differing in the carbohydrate/protein ratio on weight loss and oxidative changes of obese men. Int. J. Food Sci. Nutr. 2009;60(Suppl 3):1–13. [Google Scholar]
36.Ahmad A., Isherwood C., Umpleby M., Griffin B. Effects of high and low sugar diets on cardiovascular disease risk factors. J. Nutr. Sci. Vitaminol. (Tokyo). 2020;66(Suppl):S18–S24. doi: 10.3177/jnsv.66.S18. [DOI] [PubMed] [Google Scholar]
37.Alnoubi A.A., Alqurashi R.M. The role of high-fat ketogenic and low-fat diets in weight reduction and cardiovascular risk mitigation among overweight and obese women: a single-blind controlled study. Curr. Res. Nutr. Food Sci. 2024;12(3):1366–1375. [Google Scholar]
38.Archer W.R., Lamarche B., Dériaz O., Landry N., Corneau L., Després J.P., et al. Variations in body composition and plasma lipids in response to a high-carbohydrate diet. Obes. Res. 2003;11(8):978–986. doi: 10.1038/oby.2003.135. [DOI] [PubMed] [Google Scholar]
39.Baba N.H., Sawaya S., Torbay N., Habbal Z., Azar S., Hashim S.A. High protein vs high carbohydrate hypoenergetic diet for the treatment of obese hyperinsulinemic subjects. Int. J. Obes. Relat. Metab. Disord. 1999;23(11):1202–1206. doi: 10.1038/sj.ijo.0801064. [DOI] [PubMed] [Google Scholar]
40.Ballard K.D., Quann E.E., Kupchak B.R., Volk B.M., Kawiecki D.M., Fernandez M.L., et al. Dietary carbohydrate restriction improves insulin sensitivity, blood pressure, microvascular function, and cellular adhesion markers in individuals taking statins. Nutr. Res. 2013;33(11):905–912. doi: 10.1016/j.nutres.2013.07.022. [DOI] [PubMed] [Google Scholar]
41.Bazzano L.A., Hu T., Reynolds K., Yao L., Bunol C., Liu Y., et al. Effects of low-carbohydrate and low-fat diets: a randomized trial. Ann. Intern. Med. 2014;161(5):309–318. doi: 10.7326/M14-0180. [DOI] [PMC free article] [PubMed] [Google Scholar]
42.Boers I., Muskiet F.A., Berkelaar E., Schut E., Penders R., Hoenderdos K., et al. Favourable effects of consuming a Palaeolithic-type diet on characteristics of the metabolic syndrome: a randomized controlled pilot-study. Lipids Health Dis. 2014;13:160. doi: 10.1186/1476-511X-13-160. [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Bradley U., Spence M., Courtney C.H., McKinley M.C., Ennis C.N., McCance D.R., et al. Low-fat versus low-carbohydrate weight reduction diets: effects on weight loss, insulin resistance, and cardiovascular risk: a randomized control trial. Diabetes. 2009;58(12):2741–2748. doi: 10.2337/db09-0098. [DOI] [PMC free article] [PubMed] [Google Scholar]
44.Brehm B.J., Spang S.E., Lattin B.L., Seeley R.J., Daniels S.R., D'Alessio D.A. The role of energy expenditure in the differential weight loss in obese women on low-fat and low-carbohydrate diets. J. Clin. Endocrinol. Metab. 2005;90(3):1475–1482. doi: 10.1210/jc.2004-1540. [DOI] [PubMed] [Google Scholar]
45.Brinkworth G.D., Noakes M., Keogh J.B., Luscombe N.D., Wittert G.A., Clifton P.M. Long-term effects of a high-protein, low-carbohydrate diet on weight control and cardiovascular risk markers in obese hyperinsulinemic subjects. Int. J. Obes. Relat. Metab. Disord. 2004;28(5):661–670. doi: 10.1038/sj.ijo.0802617. [DOI] [PubMed] [Google Scholar]
46.Brinkworth G.D., Noakes M., Parker B., Foster P., Clifton P.M. Long-term effects of advice to consume a high-protein, low-fat diet, rather than a conventional weight-loss diet, in obese adults with type 2 diabetes: one-year follow-up of a randomised trial. Diabetologia. 2004;47(10):1677–1686. doi: 10.1007/s00125-004-1511-7. [DOI] [PubMed] [Google Scholar]
47.Brinkworth G.D., Noakes M., Buckley J.D., Keogh J.B., Clifton P.M. Long-term effects of a very-low-carbohydrate weight loss diet compared with an isocaloric low-fat diet after 12 mo. Am. J. Clin. Nutr. 2009;90(1):23–32. doi: 10.3945/ajcn.2008.27326. [DOI] [PubMed] [Google Scholar]
48.Buga A., Welton G.L., Scott K.E., Atwell A.D., Haley S.J., Esbenshade N.J., et al. The effects of carbohydrate versus fat restriction on lipid profiles in highly trained, recreational distance runners: a randomized, cross-over trial. Nutrients. 2022;14(6):1135. doi: 10.3390/nu14061135. [DOI] [PMC free article] [PubMed] [Google Scholar]
49.Buscemi S., Verga S., Tranchina M.R., Cottone S., Cerasola G. Effects of hypocaloric veryus fat restriction on lipid profiles in highly trained, real function in obese women. Eur. J. Clin. Invest. 2009;39(5):339–347. doi: 10.1111/j.1365-2362.2009.02091.x. [DOI] [PubMed] [Google Scholar]
50.Bush N.C., Resuehr H.E.S., Goree L.L., Locher J.L., Bray M.S., Soleymani T., et al. A high-fat compared with a high-carbohydrate breakfast enhances 24-hour fat oxidation in older adults. J. Nutr. 2018;148(2):220–226. doi: 10.1093/jn/nxx040. [DOI] [PMC free article] [PubMed] [Google Scholar]
51.Cai L., Yin J., Ma X., Mo Y., Li C., Lu W., et al. Low-carbohydrate diets lead to greater weight loss and better glucose homeostasis than exercise: a randomized clinical trial. Front. Med. 2021;15(3):460–471. doi: 10.1007/s11684-021-0861-6. [DOI] [PubMed] [Google Scholar]
52.Chen C.Y., Huang W.S., Chen H.C., Chang C.H., Lee L.T., Chen H.S., et al. Effect of a 90 g/day low-carbohydrate diet on glycaemic control, small, dense low-density lipoprotein and carotid intima-media thickness in type 2 diabetic patients: an 18-month randomised controlled trial. PLOS ONE. 2020;15(10) [Google Scholar]
53.Chen C.Y., Huang W.S., Ho M.H., Chang C.H., Lee L.T., Chen H.S., et al. The potential prolonged effect at one-year follow-up after 18-month randomized controlled trial of a 90 g/day low-carbohydrate diet in patients with type 2 diabetes. Nutr. Diabetes. 2022;12(1):17. doi: 10.1038/s41387-022-00193-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
54.Chiu S., Williams P.T., Dawson T., Bergman R.N., Stefanovski D., Watkins S.M., et al. Diets high in protein or saturated fat do not affect insulin sensitivity or plasma concentrations of lipids and lipoproteins in overweight and obese adults. J. Nutr. 2014;144(11):1753–1759. doi: 10.3945/jn.114.197624. [DOI] [PMC free article] [PubMed] [Google Scholar]
55.Cipryan L., Litschmannova M., Maffetone P.B., Plews D.J., Dostal T., Hofmann P., et al. Very low-carbohydrate high-fat diet improves risk markers for cardiometabolic health more than exercise in men and women with overfat constitution: secondary analysis of a randomized controlled clinical trial. Front. Nutr. 2022;9 [Google Scholar]
56.Claessens M., Van Baak M.A., Monsheimer S., Saris W.H.M. The effect of a low-fat, high-protein or high-carbohydrate ad libitum diet on weight loss maintenance and metabolic risk factors. Int. J. Obes. (Lomd). 2009;33(3):296–304. [Google Scholar]
57.Cunha G.M., Guzman G., Correa De Mello L.L., Trein B., Spina L., Bussade I., et al. Efficacy of a 2-month very low-calorie ketogenic diet (VLCKD) compared to a standard low-calorie diet in reducing visceral and liver fat accumulation in patients with obesity. Front. Endocrinol. (Lausanne). 2020;11:607. doi: 10.3389/fendo.2020.00607. [DOI] [PMC free article] [PubMed] [Google Scholar]
58.D’Abbondanza M., Ministrini S., Pucci G., Nulli Migliola E., Martorelli E.E., Gandolfo V., et al. Very low-carbohydrate ketogenic diet for the treatment of severe obesity and associated non-alcoholic fatty liver disease: the role of sex differences. Nutrients. 2020;12(9):2748. doi: 10.3390/nu12092748. [DOI] [PMC free article] [PubMed] [Google Scholar]
59.Dalle Grave R., Calugi S., Gavasso I., El Ghoch M., Marchesini G. A randomized trial of energy-restricted high-protein versus high-carbohydrate, low-fat diet in morbid obesity. Obesity (Silver Spring) 2013;21(9):1774–1781. doi: 10.1002/oby.20320. [DOI] [PubMed] [Google Scholar]
60.Davis N.J., Crandall J.P., Gajavelli S., Berman J.W., Tomuta N., Wylie-Rosett J., et al. Differential effects of low-carbohydrate and low-fat diets on inflammation and endothelial function in diabetes. J. Diabetes Complications. 2011;25(6):371–376. doi: 10.1016/j.jdiacomp.2011.08.001. [DOI] [PubMed] [Google Scholar]
61.Davis N.J., Tomuta N., Schechter C., Isasi C.R., Segal-Isaacson C.J., Stein D., et al. Comparative study of the effects of a 1-year dietary intervention of a low-carbohydrate diet versus a low-fat diet on weight and glycemic control in type 2 diabetes. Diabetes Care. 2009;32(7):1147–1152. doi: 10.2337/dc08-2108. [DOI] [PMC free article] [PubMed] [Google Scholar]
62.de Luis D.A., Izaola O., Aller R., de la Fuente B., Bachiller R., Romero E. Effects of a high-protein/low carbohydrate versus a standard hypocaloric diet on adipocytokine levels and insulin resistance in obese patients along 9 months. J. Diabetes Complications. 2015;29(7):950–954. doi: 10.1016/j.jdiacomp.2015.06.002. [DOI] [PubMed] [Google Scholar]
63.de Luis D.A., Aller R., Izaola O., Gonzalez Sagrado M., Bellioo D., Conde R. Effects of a low-fat versus a low-carbohydrate diet on adipocytokines in obese adults. Horm. Res. 2007;67(6):296–300. doi: 10.1159/000099329. [DOI] [PubMed] [Google Scholar]
64.Dorans K.S., Bazzano L.A., Qi L., He H., Chen J., Appel L.J., et al. Effects of a low-carbohydrate dietary intervention on hemoglobin A1c: a randomized clinical trial, JAMA Netw. Open. 2022;5(10) [Google Scholar]
65.Ebbeling C.B., Knapp A., Johnson A., Wong J.M.W., Greco K.F., Ma C., et al. Effects of a low-carbohydrate diet on insulin-resistant dyslipoproteinemia-a randomized controlled feeding trial. Am. J. Clin. Nutr. 2022;115(1):154–162. doi: 10.1093/ajcn/nqab287. [DOI] [PMC free article] [PubMed] [Google Scholar]
66.Egert S., Kratz M., Kannenberg F., Fobker M., Wahrburg U. Effects of high-fat and low-fat diets rich in monounsaturated fatty acids on serum lipids, LDL size and indices of lipid peroxidation in healthy non-obese men and women when consumed under controlled conditions. Eur. J. Nutr. 2011;50(1):71–79. doi: 10.1007/s00394-010-0116-9. [DOI] [PubMed] [Google Scholar]
67.Dellis D., Tsilingiris D., Eleftheriadou I., Tentolouris A., Sfikakis P.P., Jr., Dellis G., et al. Carbohydrate restriction in the morning increases weight loss effect of a hypocaloric Mediterranean type diet: a randomized, parallel group dietary intervention in overweight and obese subjects. Nutrition. 2020;71 [Google Scholar]
68.de Luis D.A., Aller R., Izaola O., Romero E. Effects of a high-protein/low-carbohydrate versus a standard hypocaloric diet on adipocytokine levels and cardiovascular risk factors during 9 months, role of rs6923761 gene variant of glucagon-like peptide 1 receptor. J. Endocrinol. Invest. 2015;38(11):1183–1189. doi: 10.1007/s40618-015-0304-9. [DOI] [PubMed] [Google Scholar]
69.Elhayany A., Lustman A., Abel R., Attal-Singer J., Vinker S. A low carbohydrate Mediterranean diet improves cardiovascular risk factors and diabetes control among overweight patients with type 2 diabetes mellitus: a 1-year prospective randomized intervention study. Diabetes Obes. Metab. 2010;12(3):204–209. doi: 10.1111/j.1463-1326.2009.01151.x. [DOI] [PubMed] [Google Scholar]
70.Foraker R.E., Pennell M., Sprangers P., Vitolins M.Z., DeGraffinreid C., Paskett E.D. Effect of a low-fat or low-carbohydrate weight-loss diet on markers of cardiovascular risk among premenopausal women: a randomized trial. J. Womens Health (Larchmt). 2014;23(8):675–680. doi: 10.1089/jwh.2013.4638. [DOI] [PMC free article] [PubMed] [Google Scholar]
71.Foster G.D., Wyatt H.R., Hill J.O., Makris A.P., Rosenbaum D.L., Brill C., et al. Weight and metabolic outcomes after 2 years on a low-carbohydrate versus low-fat diet: a randomized trial. Ann. Intern. Med. 2010;153(3):147–157. doi: 10.1059/0003-4819-153-3-201008030-00005. [DOI] [PMC free article] [PubMed] [Google Scholar]
72.Frisch S., Zittermann A., Berthold H.K., Gotting C., Kuhn J., Kleesiek K., et al. A randomized controlled trial on the efficacy of carbohydrate-reduced or fat-reduced diets in patients attending a telemedically guided weight loss program. Cardiovasc. Diabetol. 2009;8:36. doi: 10.1186/1475-2840-8-36. [DOI] [PMC free article] [PubMed] [Google Scholar]
73.Gardner C.D., Kiazand A., Alhassan S., Kim S., Stafford R.S., Balise R.R., et al. Comparison of the Atkins, Zone, Ornish, and LEARN diets for change in weight and related risk factors among overweight premenopausal women: the A TO Z Weight Loss Study: a randomized trial. JAMA. 2007;297(9):969–977. doi: 10.1001/jama.297.9.969. [DOI] [PubMed] [Google Scholar]
74.Gardner C.D., Offringa L.C., Hartle J.C., Kapphahn K., Cherin R. Weight loss on low-fat vs. low-carbohydrate diets by insulin resistance status among overweight adults and adults with obesity: a randomized pilot trial. Obesity (Silver Spring) 2016;24(1):79–86. doi: 10.1002/oby.21331. [DOI] [PMC free article] [PubMed] [Google Scholar]
75.Gardner C.D., Trepanowski J.F., Del Gobbo L.C., Hauser M.E., Rigdon J., Ioannidis J.P.A., et al. Effect of low-fat vs low-carbohydrate diet on 12-month weight loss in overweight adults and the association with genotype pattern or insulin secretion: the DIETFITS randomized clinical trial. JAMA. 2018;319(7):667–679. doi: 10.1001/jama.2018.0245. [DOI] [PMC free article] [PubMed] [Google Scholar]
76.Garg A., Grundy S.M., Unger R.H. Comparison of effects of high and low carbohydrate diets on plasma lipoproteins and insulin sensitivity in patients with mild NIDDM. Diabetes. 1992;41(10):1278–1285. [PubMed] [Google Scholar]
77.Genoni A., Lyons-Wall P., Lo J., Devine A. Cardiovascular, metabolic effects and dietary composition of ad-libitum paleolithic vs. Australian guide to healthy eating diets: a 4-week randomised trial. Nutrients. 2016;8(5):314. doi: 10.3390/nu8050314. [DOI] [PMC free article] [PubMed] [Google Scholar]
78.Gerhard G.T., Ahmann A., Meeuws K., McMurry M.P., Duell P.B., Connor W.E. Effects of a low-fat diet compared with those of a high-monounsaturated fat diet on body weight, plasma lipids and lipoproteins, and glycemic control in type 2 diabetes. Am. J. Clin. Nutr. 2004;80(3):668–673. doi: 10.1093/ajcn/80.3.668. [DOI] [PubMed] [Google Scholar]
79.Goday A., Bellido D., Sajoux I., Crujeiras A.B., Burguera B., García-Luna P.P., et al. Short-term safety, tolerability and efficacy of a very low-calorie-ketogenic diet interventional weight loss program versus hypocaloric diet in patients with type 2 diabetes mellitus. Nutr. Diabetes. 2016;6(9) [Google Scholar]
80.Golay A., Allaz A.F., Morel Y., de Tonnac N., Tankova S., Reaven G. Similar weight loss with low- or high-carbohydrate diets. Am. J. Clin. Nutr. 1996;63(2):174–178. doi: 10.1093/ajcn/63.2.174. [DOI] [PubMed] [Google Scholar]
81.Goss A.M., Gower B., Soleymani T., Stewart M., Pendergrass M., Lockhart M., et al. Effects of weight loss during a very low carbohydrate diet on specific adipose tissue depots and insulin sensitivity in older adults with obesity: a randomized clinical trial. Nutr. Metab. (Lond). 2020;17:64. doi: 10.1186/s12986-020-00481-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
82.Gram-Kampmann E.M., Hansen C.D., Hugger M.B., Jensen J.M., Brønd J.C., Hermann A.P., et al. Effects of a 6-month, low-carbohydrate diet on glycaemic control, body composition, and cardiovascular risk factors in patients with type 2 diabetes: an open-label randomized controlled trial. Diabetes Obes. Metab. 2022;24(4):693–703. doi: 10.1111/dom.14633. [DOI] [PubMed] [Google Scholar]
83.Gram-Kampmann E.M., Olesen T.B., Hansen C.D., Hugger M.B., Jensen J.M., Handberg A., et al. A six-month low-carbohydrate diet high in fat does not adversely affect endothelial function or markers of low-grade inflammation in patients with type 2 diabetes: an open-label randomized controlled trial. Cardiovasc. Diabetol. 2023;22(1):212. doi: 10.1186/s12933-023-01956-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
84.Guay V., Lamarche B., Charest A., Tremblay A.J., Couture P. Effect of short-term low- and high-fat diets on low-density lipoprotein particle size in normolipidemic subjects. Metabolism. 2012;61(1):76–83. doi: 10.1016/j.metabol.2011.06.002. [DOI] [PubMed] [Google Scholar]
85.Guevara-Cruz M., Hernández-Gómez K.G., Condado-Huerta C., González-Salazar L.E., Peña-Flores A.K., Pichardo-Ontiveros E., et al. Intermittent fasting, calorie restriction, and a ketogenic diet improve mitochondrial function by reducing lipopolysaccharide signaling in monocytes during obesity: a randomized clinical trial. Clin. Nutr. 2024;43(8):1914–1928. doi: 10.1016/j.clnu.2024.06.036. [DOI] [PubMed] [Google Scholar]
86.Guldbrand H., Dizdar B., Bunjaku B., Lindström T., Bachrach-Lindström M., Fredrikson M., et al. In type 2 diabetes, randomisation to advice to follow a low-carbohydrate diet transiently improves glycaemic control compared with advice to follow a low-fat diet producing a similar weight loss. Diabetologia. 2012;55(8):2118–2127. doi: 10.1007/s00125-012-2567-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
87.Guo H., Wang L., Huang X., Shen F., Lu Y., Zhang P. Effects of low-carbohydrate vs low-fat diets on weight loss and metabolic risk factors in obese/overweight individuals with impaired glucose regulation: a randomized controlled trial, Asia Pac. J. Clin. Nutr. 2022;31(3):512–519. [Google Scholar]
88.Haji-Ghazi Tehrani L., Mousavi S.N., Chiti H., Afshar D. Effect of Atkins versus a low-fat diet on gut microbiota, and cardiometabolic markers in obese women following an energy-restricted diet: randomized, crossover trial. Nutr. Metab. Cardiovasc. Dis. 2022;32(7):1734–1741. doi: 10.1016/j.numecd.2022.04.007. [DOI] [PubMed] [Google Scholar]
89.Hansen C.D., Gram-Kampmann E.M., Hansen J.K., Hugger M.B., Madsen B.S., Jensen J.M., et al. Effect of calorie-unrestricted low-carbohydrate, high-fat diet versus high-carbohydrate, low-fat diet on type 2 diabetes and nonalcoholic fatty liver disease: a randomized controlled trial. Ann. Intern. Med. 2023;176(1):10–21. doi: 10.7326/M22-1787. [DOI] [PubMed] [Google Scholar]
90.Harvey C., Schofield G.M., Zinn C., Thornley S.J., Crofts C., Merien F.L.R. Low-carbohydrate diets differing in carbohydrate restriction improve cardiometabolic and anthropometric markers in healthy adults: a randomised clinical trial. PeerJ. 2019;7 [Google Scholar]
91.Haufe S., Engeli S., Kast P., Böhnke J., Utz W., Haas V., et al. Randomized comparison of reduced fat and reduced carbohydrate hypocaloric diets on intrahepatic fat in overweight and obese human subjects. Hepatology. 2011;53(5):1504–1514. doi: 10.1002/hep.24242. [DOI] [PubMed] [Google Scholar]
92.Haufe S., Utz W., Engeli S., Kast P., Böhnke J., Pofahl M., et al. Left ventricular mass and function with reduced-fat or reduced-carbohydrate hypocaloric diets in overweight and obese subjects. Hypertension. 2012;59(1):70–75. doi: 10.1161/HYPERTENSIONAHA.111.178616. [DOI] [PubMed] [Google Scholar]
93.He M., Wang J., Liang Q., Li M., Guo H., Wang Y., et al. Time-restricted eating with or without low-carbohydrate diet reduces visceral fat and improves metabolic syndrome: a randomized trial, Cell Rep. Med. 2022;3(10) [Google Scholar]
94.Holmer M., Lindqvist C., Petersson S., Moshtaghi-Svensson J., Tillander V., Brismar T.B., et al. Treatment of NAFLD with intermittent calorie restriction or low-carb high-fat diet—a randomised controlled trial. JHEP Rep. 2021;3(3) [Google Scholar]
95.Hu T., Yao L., Reynolds K., Whelton P.K., Niu T., Li S., et al. The effects of a low-carbohydrate diet vs. a low-fat diet on novel cardiovascular risk factors: a randomized controlled trial. Nutrients. 2015;7(9):7978–7994. doi: 10.3390/nu7095377. [DOI] [PMC free article] [PubMed] [Google Scholar]
96.Hyde P.N., Sapper T.N., LaFountain R.A., Kackley M.L., Buga A., Fell B., et al. Effects of palm stearin versus butter in the context of low-carbohydrate/high-fat and high-carbohydrate/low-fat diets on circulating lipids in a controlled feeding study in healthy humans. Nutrients. 2021;13(6):1944. doi: 10.3390/nu13061944. [DOI] [PMC free article] [PubMed] [Google Scholar]
97.Jenkins D.J.A., Wong J.M.W., Kendall C.W.C., Esfahani A., Ng V.W.Y., Leong T.C.K., et al. Effect of a 6-month vegan low-carbohydrate ('Eco-Atkins') diet on cardiovascular risk factors and body weight in hyperlipidaemic adults: a randomised controlled trial. BMJ Open. 2014;4(2) [Google Scholar]
98.Jeppesen J., Schaaf P., Jones C., Zhou M.Y., Chen Y.D., Reaven G.M. Effects of low-fat, high-carbohydrate diets on risk factors for ischemic heart disease in postmenopausal women. Am. J. Clin. Nutr. 1997;65(4):1027–1033. doi: 10.1093/ajcn/65.4.1027. [DOI] [PubMed] [Google Scholar]
99.Jönsson T., Granfeldt Y., Ahrén B., Branell U.C., Pålsson G., Hansson A., et al. Beneficial effects of a Paleolithic diet on cardiovascular risk factors in type 2 diabetes: a randomized cross-over pilot study. Cardiovasc. Diabetol. 2009;8:35. doi: 10.1186/1475-2840-8-35. [DOI] [PMC free article] [PubMed] [Google Scholar]
100.Keogh J.B., Brinkworth G.D., Clifton P.M. Effects of weight loss on a low-carbohydrate diet on flow-mediated dilatation, adhesion molecules and adiponectin. Br. J. Nutr. 2007;98(4):852–859. doi: 10.1017/S0007114507747815. [DOI] [PubMed] [Google Scholar]
101.Kikuchi T., Kushiyama A., Yanai M., Kashiwado C., Seto T., Kasuga M. Comparison of weight reduction, change in parameters and safety of a very low carbohydrate diet in comparison to a low carbohydrate diet in obese Japanese subjects with metabolic disorders. Nutrients. 2023;15(6):1342. doi: 10.3390/nu15061342. [DOI] [PMC free article] [PubMed] [Google Scholar]
102.Kitabchi A.E., McDaniel K.A., Wan J.Y., Tylavsky F.A., Jacovino C.A., Sands C.W., et al. Effects of high-protein versus high-carbohydrate diets on markers of β-cell function, oxidative stress, lipid peroxidation, proinflammatory cytokines, and adipokines in obese, premenopausal women without diabetes: a randomized controlled trial. Diabetes Care. 2013;36(7):1919–1925. doi: 10.2337/dc12-1912. [DOI] [PMC free article] [PubMed] [Google Scholar]
103.Kleiner R.E., Hutchins A.M., Johnston C.S., Swan P.D. Effects of an 8-week high-protein or high-carbohydrate diet in adults with hyperinsulinemia. MedGenMed. 2006;8(4):39. [Google Scholar]
104.Kleissl-Muir S., Owen A., Rasmussen B., Zinn C., Driscoll A. Effects of a low carbohydrate diet on heart failure symptoms and quality of life in patients with diabetic cardiomyopathy: a randomised controlled trial pilot study. Nutr. Metab. Cardiovasc. Dis. 2023;33(12):2455–2463. doi: 10.1016/j.numecd.2023.08.015. [DOI] [PubMed] [Google Scholar]
105.Krauss R.M., Blanche P.J., Rawlings R.S., Fernstrom H.S., Williams P.T. Separate effects of reduced carbohydrate intake and weight loss on atherogenic dyslipidemia. Am. J. Clin. Nutr. 2006;83(5):1025–1031. doi: 10.1093/ajcn/83.5.1025. quiz 205. [DOI] [PubMed] [Google Scholar]
106.Krebs J.D., Elley C.R., Parry-Strong A., Lunt H., Drury P.L., Bell D.A., et al. The Diabetes Excess Weight Loss (DEWL) Trial: a randomised controlled trial of high-protein versus high-carbohydrate diets over 2 years in type 2 diabetes. Diabetologia. 2012;55(4):905–914. doi: 10.1007/s00125-012-2461-0. [DOI] [PubMed] [Google Scholar]
107.Krebs J.D., Strong A.P., Cresswell P., Reynolds A.N., Hanna A., Haeusler S. A randomised trial of the feasibility of a low carbohydrate diet vs standard carbohydrate counting in adults with type 1 diabetes taking body weight into account. Asia Pac. J. Clin. Nutr. 2016;25(1):78–84. doi: 10.6133/apjcn.2016.25.1.11. [DOI] [PubMed] [Google Scholar]
108.Lambadiari V., Katsimbri P., Kountouri A., Korakas E., Papathanasi A., Maratou E., et al. The effect of a ketogenic diet versus Mediterranean diet on clinical and biochemical markers of inflammation in patients with obesity and psoriatic arthritis: a randomized crossover trial. Int. J. Mol. Sci. 2024;25(5):2475. doi: 10.3390/ijms25052475. [DOI] [PMC free article] [PubMed] [Google Scholar]
109.Le T., Flatt S.W., Natarajan L., Pakiz B., Quintana E.L., Heath D.D., et al. Effects of diet composition and insulin resistance status on plasma lipid levels in a weight loss intervention in women. J. Am. Heart Assoc. 2016;5(1) [Google Scholar]
110.Lean M.E.J., Han T.S., Prvan T., Richmond P.R., Avenell A. Weight loss with high and low carbohydrate 1200 kcal diets in free living women. Eur. J. Clin. Nutr. 1997;51(4):243–248. doi: 10.1038/sj.ejcn.1600391. [DOI] [PubMed] [Google Scholar]
111.Li S., Lin G., Chen J., Chen Z., Xu F., Zhu F., et al. The effect of periodic ketogenic diet on newly diagnosed overweight or obese patients with type 2 diabetes. BMC Endocr. Disord. 2022;22(1):34. doi: 10.1186/s12902-022-00947-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
112.Lim S.S., Noakes M., Keogh J.B., Clifton P.M. Long-term effects of a low carbohydrate, low fat or high unsaturated fat diet compared to a no-intervention control. Nutr. Metab. Cardiovasc. Dis. 2010;20(8):599–607. doi: 10.1016/j.numecd.2009.05.003. [DOI] [PubMed] [Google Scholar]
113.Liu X., Zhang G., Ye X., Li H., Chen X., Tang L., et al. Effects of a low-carbohydrate diet on weight loss and cardiometabolic profile in Chinese women: a randomised controlled feeding trial. Br. J. Nutr. 2013;110(8):1444–1453. doi: 10.1017/S0007114513000640. [DOI] [PubMed] [Google Scholar]
114.Liu K., Wang B., Zhou R., Lang H.D., Ran L., Wang J., et al. Effect of combined use of a low-carbohydrate, high-protein diet with omega-3 polyunsaturated fatty acid supplementation on glycemic control in newly diagnosed type 2 diabetes: a randomized, double-blind, parallel-controlled trial. Am. J. Clin. Nutr. 2018;108(2):256–265. doi: 10.1093/ajcn/nqy120. [DOI] [PubMed] [Google Scholar]
115.London A., Richter M.M., Sjøberg K.A., Wewer Albrechtsen N.J., Považan M., Drici L., et al. The impact of short-term eucaloric low- and high-carbohydrate diets on liver triacylglycerol content in males with overweight and obesity: a randomized crossover study. Am. J. Clin. Nutr. 2024;120(2):283–293. doi: 10.1016/j.ajcnut.2024.06.006. [DOI] [PubMed] [Google Scholar]
116.Luong T.V., Pedersen M.G.B., Abild C.B., Lauritsen K.M., Kjærulff M.L.G., Møller N., et al. A 3-week ketogenic diet increases skeletal muscle insulin sensitivity in individuals with obesity: a randomized controlled crossover trial. Diabetes. 2024;73(10):1631–1640. doi: 10.2337/db24-0162. [DOI] [PMC free article] [PubMed] [Google Scholar]
117.Martins C., Bryan D.R., Sweatt S.K., Garvey W.T., Fontaine K.R., Dutton G.R., et al. The impact of a low increases skeletal muscle insulin sensitivity in individuals with obesity: a randomized controlled crossovert. Obesity (Silver Spring) 2025;33(2):257–266. doi: 10.1002/oby.24201. [DOI] [PMC free article] [PubMed] [Google Scholar]
118.McAuley K.A., Hopkins C.M., Smith K.J., McLay R.T., Williams S.M., Taylor R.W., et al. Comparison of high-fat and high-protein diets with a high-carbohydrate diet in insulin-resistant obese women. Diabetologia. 2005;48(1):8–16. doi: 10.1007/s00125-004-1603-4. [DOI] [PubMed] [Google Scholar]
119.McCullough D., Harrison T., Boddy L.M., Enright K.J., Amirabdollahian F., Schmidt M.A., et al. The effect of dietary carbohydrate and fat manipulation on the metabolome and markers of glucose and insulin metabolism: a randomised parallel trial. Nutrients. 2022;14(18):3691. doi: 10.3390/nu14183691. [DOI] [PMC free article] [PubMed] [Google Scholar]
120.McMillan-Price J., Petocz P., Atkinson F., O'Neill K., Samman S., Steinbeck K., et al. Comparison of 4 diets of varying glycemic load on weight loss and cardiovascular risk reduction in overweight and obese young adults: a randomized controlled trial. Arch. Intern. Med. 2006;166(14):1466–1475. doi: 10.1001/archinte.166.14.1466. [DOI] [PubMed] [Google Scholar]
121.Meckling K.A., O'Sullivan C., Saari D. Comparison of a low-fat diet to a low-carbohydrate diet on weight loss, body composition, and risk factors for diabetes and cardiovascular disease in free-living, overweight men and women. J. Clin. Endocrinol. Metab. 2004;89(6):2717–2723. doi: 10.1210/jc.2003-031606. [DOI] [PubMed] [Google Scholar]
122.Meckling K.A., Sherfey R. A randomized trial of a hypocaloric high-protein diet, with and without exercise, on weight loss, fitness, and markers of the Metabolic Syndrome in overweight and obese women. Appl. Physiol. Nutr. Metab. 2007;32(4):743–752. doi: 10.1139/H07-059. [DOI] [PubMed] [Google Scholar]
123.Meksawan K., Pendergast D.R., Leddy J.J., Mason M., Horvath P.J., Awad A.B. Effect of low and high fat diets on nutrient intakes and selected cardiovascular risk factors in sedentary men and women. J. Am. Coll. Nutr. 2004;23(2):131–140. doi: 10.1080/07315724.2004.10719353. [DOI] [PubMed] [Google Scholar]
124.Mellberg C., Sandberg S., Ryberg M., Eriksson M., Brage S., Larsson C., et al. Long-term effects of a Palaeolithic-type diet in obese postmenopausal women: a 2-year randomized trial. Eur. J. Clin. Nutr. 2014;68(3):350–357. doi: 10.1038/ejcn.2013.290. [DOI] [PMC free article] [PubMed] [Google Scholar]
125.Merovci A., Finley B., Hansis-Diarte A., Neppala S., Abdul-Ghani M.A., Cersosimo E., et al. Effect of weight-maintaining ketogenic diet on glycemic control and insulin sensitivity in obese T2D subjects. BMJ Open Diabetes Res. Care. 2024;12(5) [Google Scholar]
126.Michalczyk M.M., Klonek G., Maszczyk A., Zajac A. The effects of a low calorie ketogenic diet on glycaemic control variables in hyperinsulinemic overweight/obese females. Nutrients. 2020;12(6):1854. doi: 10.3390/nu12061854. [DOI] [PMC free article] [PubMed] [Google Scholar]
127.Michalczyk M.M., Maszczyk A., Stastny P. The effects of low-energy moderate-carbohydrate (MCD) and mixed (MixD) diets on serum lipid profiles and body composition in middle-aged men: a randomized controlled parallel-group clinical trial. Int. J. Environ. Res. Public Health. 2020;17(4):1332. doi: 10.3390/ijerph17041332. [DOI] [PMC free article] [PubMed] [Google Scholar]
128.Michalopoulou M., Jebb S.A., MacKillop L.H., Dyson P., Hirst J.E., Zhu S., et al. REduced-Carbohydrate intervention for managing Obesity and Reduction of gestational Diabetes (RECORD): a randomized controlled feasibility trial. Diabetes Obes. Metab. 2024;26(4):1407–1420. doi: 10.1111/dom.15442. [DOI] [PMC free article] [PubMed] [Google Scholar]
129.Moreno B., Bellido D., Sajoux I., Goday A., Saavedra D., Crujeiras A.B., et al. Comparison of a very low-calorie-ketogenic diet with a standard low-calorie diet in the treatment of obesity. Endocrine. 2014;47(3):793–805. doi: 10.1007/s12020-014-0192-3. [DOI] [PubMed] [Google Scholar]
130.Morgan S.A., O'Dea K., Sinclair A.J. A low-fat diet supplemented with monounsaturated fat results in less HDL-C lowering than a very-low-fat diet. J. Am. Diet. Assoc. 1997;97(2):151–156. doi: 10.1016/S0002-8223(97)00770-0. [DOI] [PubMed] [Google Scholar]
131.Morris E., Aveyard P., Dyson P., Noreik M., Bailey C., Fox R., et al. A food-based, low-energy, low-carbohydrate diet for people with type 2 diabetes in primary care: a randomized controlled feasibility trial. Diabetes Obes. Metab. 2020;22(4):512–520. doi: 10.1111/dom.13915. [DOI] [PMC free article] [PubMed] [Google Scholar]
132.Mousavi S.M., Ejtahed H.S., Marvasti F.E., Taghavi M., Siadat S.D., Hasani-Ranjbar S., et al. The effect of a moderately restricted carbohydrate diet on cardiometabolic risk factors in overweight and obese women with metabolic syndrome: a randomized controlled trial. Clin. Ther. 2023;45(3):e103–e114. doi: 10.1016/j.clinthera.2023.02.002. [DOI] [PubMed] [Google Scholar]
133.Noakes M., Keogh J.B., Foster P.R., Clifton P.M. Effect of an energy-restricted, high-protein, low-fat diet relative to a conventional high-carbohydrate, low-fat diet on weight loss, body composition, nutritional status, and markers of cardiovascular health in obese women. Am. J. Clin. Nutr. 2005;81(6):1298–1306. doi: 10.1093/ajcn/81.6.1298. [DOI] [PubMed] [Google Scholar]
134.Numao S., Kawano H., Endo N., Yamada Y., Konishi M., Takahashi M., et al. Effects of a single bout of aerobic exercise on short-term low-carbohydrate/high-fat intake-induced postprandial glucose metabolism during an oral glucose tolerance test. Metabolism. 2013;62(10):1406–1415. doi: 10.1016/j.metabol.2013.05.005. [DOI] [PubMed] [Google Scholar]
135.Appel L.J., Sacks F.M., Carey V.J., Obarzanek E., Swain J.F., Miller E.R., et al. Effects of protein, monounsaturated fat, and carbohydrate intake on blood pressure and serum lipids: results of the OmniHeart randomized trial. JAMA. 2005;294(19):2455–2464. doi: 10.1001/jama.294.19.2455. [DOI] [PubMed] [Google Scholar]
136.Otten J., Mellberg C., Ryberg M., Sandberg S., Kullberg J., Lindahl B., et al. Strong and persistent effect on liver fat with a Paleolithic diet during a two-year intervention. Int. J. Obes. (Lond). 2016;40(5):747–753. doi: 10.1038/ijo.2016.4. [DOI] [PubMed] [Google Scholar]
137.Parr E.B., Coffey V.G., Cato L.E., Phillips S.M., Burke L.M., Hawley J.A. A randomized trial of high-dairy-protein, variable-carbohydrate diets and exercise on body composition in adults with obesity. Obesity (Silver Spring) 2016;24(5):1035–1045. doi: 10.1002/oby.21451. [DOI] [PubMed] [Google Scholar]
138.Perissiou M., Borkoles E., Kobayashi K., Polman R. The effect of an 8 week prescribed exercise and low-carbohydrate diet on cardiorespiratory fitness, body composition and cardiometabolic risk factors in obese individuals: a randomised controlled trial. Nutrients. 2020;12(2):482. doi: 10.3390/nu12020482. [DOI] [PMC free article] [PubMed] [Google Scholar]
139.Peterson C.M., Jovanovic-Peterson L. Randomized crossover study of 40% vs. 55% carbohydrate weight loss strategies in women with previous gestational diabetes mellitus and non-diabetic women of 130-200% ideal body weight. J. Am. Coll. Nutr. 1995;14(4):369–375. doi: 10.1080/07315724.1995.10718523. [DOI] [PubMed] [Google Scholar]
140.Pinsawas B., Surawit A., Mongkolsucharitkul P., Pongkunakorn T., Suta S., Manosan T., et al. Asian low-carbohydrate diet with increased whole egg consumption improves metabolic outcomes in metabolic syndrome: a 52-week intervention study. J. Nutr. 2024;154(11):3331–3345. doi: 10.1016/j.tjnut.2024.08.027. [DOI] [PubMed] [Google Scholar]
141.Rajaie S., Azadbakht L., Saneei P., Khazaei M., Esmaillzadeh A. Comparative effects of carbohydrate versus fat restriction on serum levels of adipocytokines, markers of inflammation, and endothelial function among women with the metabolic syndrome: a randomized cross-over clinical trial. Ann. Nutr. Metab. 2013;63(1-2):159–167. doi: 10.1159/000354868. [DOI] [PubMed] [Google Scholar]
142.Ranjan A., Schmidt S., Damm-Frydenberg C., Holst J.J., Madsbad S., Nørgaard K. Short-term effects of a low carbohydrate diet on glycaemic variables and cardiovascular risk markers in patients with type 1 diabetes: a randomized open-label crossover trial. Diabetes Obes. Metab. 2017;19(10):1479–1484. doi: 10.1111/dom.12953. [DOI] [PubMed] [Google Scholar]
143.Raygan F., Bahmani F., Kouchaki E., Aghadavod E., Sharifi S., Akbari E., et al. Comparative effects of carbohydrate versus fat restriction on metabolic profiles, biomarkers of inflammation and oxidative stress in overweight patients with Type 2 diabetic and coronary heart disease: a randomized clinical trial. ARYA Atheroscler. 2016;12(6):266–273. [PMC free article] [PubMed] [Google Scholar]
144.Retterstol K., Svendsen M., Narverud I., Holven K.B. Effect of low carbohydrate high fat diet on LDL cholesterol and gene expression in normal-weight, young adults: a randomized controlled study. Atherosclerosis. 2018;279:52–61. doi: 10.1016/j.atherosclerosis.2018.10.013. [DOI] [PubMed] [Google Scholar]
145.Rodríguez-Villar C., Pérez-Heras A., Mercadé I., Casals E., Ros E. Comparison of a high-carbohydrate and a high-monounsaturated fat, olive oil-rich diet on the susceptibility of LDL to oxidative modification in subjects with type 2 diabetes mellitus. Diabet. Med. 2004;21(2):142–149. doi: 10.1046/j.1464-5491.2003.01086.x. [DOI] [PubMed] [Google Scholar]
146.Röhling M., Kempf K., Banzer W., Berg A., Braumann K.M., Tan S., et al. Prediabetes conversion to normoglycemia is superior adding a low-carbohydrate and energy deficit formula diet to lifestyle intervention—a 12-month subanalysis of the ACOORH trial. Nutrients. 2020;12(7):2022. doi: 10.3390/nu12072022. [DOI] [PMC free article] [PubMed] [Google Scholar]
147.Ruth M.R., Port A.M., Shah M., Bourland A.C., Istfan N.W., Nelson K.P., et al. Consuming a hypocaloric high fat low carbohydrate diet for 12 weeks lowers C-reactive protein, and raises serum adiponectin and high density lipoprotein-cholesterol in obese subjects. Metabolism. 2013;62(12):1779–1787. doi: 10.1016/j.metabol.2013.07.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
148.Sacks F.M., Carey V.J., Anderson C.A., Miller E.R., 3rd, Copeland T., Charleston J., et al. Effects of high vs low glycemic index of dietary carbohydrate on cardiovascular disease risk factors and insulin sensitivity: the OmniCarb randomized clinical trial. JAMA. 2014;312(23):2531–2541. doi: 10.1001/jama.2014.16658. [DOI] [PMC free article] [PubMed] [Google Scholar]
149.Samaha F.F., Iqbal N., Seshadri P., Chicano K.L., Daily D.A., McGrory J., et al. A low-carbohydrate as compared with a low-fat diet in severe obesity. N. Engl. J. Med. 2003;348(21):2074–2081. doi: 10.1056/NEJMoa022637. [DOI] [PubMed] [Google Scholar]
150.Sargrad K.R., Homko C., Mozzoli M., Boden G. Effect of high protein vs high carbohydrate intake on insulin sensitivity, body weight, hemoglobin A1c, and blood pressure in patients with type 2 diabetes mellitus. J. Am. Diet. Assoc. 2005;105(4):573–580. doi: 10.1016/j.jada.2005.01.009. [DOI] [PubMed] [Google Scholar]
151.Saslow L.R., Daubenmier J.J., Moskowitz J.T., Kim S., Murphy E.J., Phinney S.D., et al. Twelve-month outcomes of a randomized trial of a moderate-carbohydrate versus very low-carbohydrate diet in overweight adults with type 2 diabetes mellitus or prediabetes. Nutr. Diabetes. 2017;7(12):304. doi: 10.1038/s41387-017-0006-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
152.Saslow L.R., Jones L.M., Sen A., Wolfson J.A., Diez H.L., O’Brien A., et al. Comparing very low-carbohydrate vs DASH diets for overweight or obese adults with hypertension and prediabetes or type 2 diabetes: a randomized trial. Ann. Fam. Med. 2023;21(3):256–263. doi: 10.1370/afm.2968. [DOI] [PMC free article] [PubMed] [Google Scholar]
153.Saslow L.R., Kim S., Daubenmier J.J., Moskowitz J.T., Phinney S.D., Goldman V., et al. A randomized pilot trial of a moderate carbohydrate diet compared to a very low carbohydrate diet in overweight or obese individuals with type 2 diabetes mellitus or prediabetes. PLOS ONE. 2014;9(4) [Google Scholar]
154.Segal-Isaacson C.J., Johnson S., Tomuta V., Cowell B., Stein D.T. A randomized trial comparing low-fat and low-carbohydrate diets matched for energy and protein. Obes. Res. 2004;12(Suppl 2):130S–140S. doi: 10.1038/oby.2004.278. [DOI] [PubMed] [Google Scholar]
155.Seshadri P., Iqbal N., Stern L., Williams M., Chicano K.L., Daily D.A., et al. A randomized study comparing the effects of a low-carbohydrate diet and a conventional diet on lipoprotein subfractions and C-reactive protein levels in patients with severe obesity. Am. J. Med. 2004;117(6):398–405. doi: 10.1016/j.amjmed.2004.04.009. [DOI] [PubMed] [Google Scholar]
156.Sharman M.J., Gómez A.L., Kraemer W.J., Volek J.S. Very low-carbohydrate and low-fat diets affect fasting lipids and postprandial lipemia differently in overweight men. J. Nutr. 2004;134(4):880–885. doi: 10.1093/jn/134.4.880. [DOI] [PubMed] [Google Scholar]
157.Skytte M.J., Samkani A., Petersen A.D., Thomsen M.N., Astrup A., Chabanova E., et al. A carbohydrate-reduced high-protein diet improves HbA 1c and liver fat content in weight stable participants with type 2 diabetes: a randomised controlled trial. Diabetologia. 2019;62(11):2066–2078. doi: 10.1007/s00125-019-4956-4. [DOI] [PubMed] [Google Scholar]
158.Stern L., Iqbal N., Seshadri P., Chicano K.L., Daily D.A., McGrory J., et al. The effects of low-carbohydrate versus conventional weight loss diets in severely obese adults: one-year follow-up of a randomized trial. Ann. Intern. Med. 2004;140(10):778–785. doi: 10.7326/0003-4819-140-10-200405180-00007. [DOI] [PubMed] [Google Scholar]
159.Stoernell C.K., Tangney C.C., Rockway S.W. Short-term changes in lipoprotein subclasses and C-reactive protein levels of hypertriglyceridemic adults on low-carbohydrate and low-fat diets. Nutr. Res. 2008;28(7):443–449. doi: 10.1016/j.nutres.2008.03.013. [DOI] [PubMed] [Google Scholar]
160.Sun S., Kong Z., Shi Q., Hu M., Zhang H., Zhang D., et al. Non-energy-restricted low-carbohydrate diet combined with exercise intervention improved cardiometabolic health in overweight Chinese females. Nutrients. 2019;11(12):3051. doi: 10.3390/nu11123051. [DOI] [PMC free article] [PubMed] [Google Scholar]
161.Sun J., Ruan Y., Xu N., Wu P., Lin N., Yuan K., et al. The effect of dietary carbohydrate and calorie restriction on weight and metabolic health in overweight/obese individuals: a multi-center randomized controlled trial. BMC Med. 2023;21(1):192. doi: 10.1186/s12916-023-02869-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
162.Tay J., Brinkworth G.D., Noakes M., Keogh J., Clifton P.M. Metabolic effects of weight loss on a very-low-carbohydrate diet compared with an isocaloric high-carbohydrate diet in abdominally obese subjects. J. Am. Coll. Cardiol. 2008;51(1):59–67. doi: 10.1016/j.jacc.2007.08.050. [DOI] [PubMed] [Google Scholar]
163.Tay J., Luscombe-Marsh N., Thompson C., Noakes M., Buckley J., Wittert G., et al. Long-term effects of a low carbohydrate, low saturated fat diet versus a conventional high carbohydrate, low fat diet in type 2 diabetes: a randomised trial. Diabetes Res. Clin. Pract. 2014;106:S34. [Google Scholar]
164.Tay J., Luscombe-Marsh N.D., Thompson C.H., Noakes M., Buckley J.D., Wittert G.A., et al. A very low-carbohydrate, low–saturated fat diet for type 2 diabetes management: a randomized trial. Diabetes Care. 2014;37(11):2909–2918. doi: 10.2337/dc14-0845. [DOI] [PubMed] [Google Scholar]
165.Tay J., Luscombe-Marsh N.D., Thompson C.H., Noakes M., Buckley J.D., Wittert G.A., et al. Comparison of low- and high-carbohydrate diets for type 2 diabetes management: a randomized trial. Am. J. Clin. Nutr. 2015;102(4):780–790. doi: 10.3945/ajcn.115.112581. [DOI] [PubMed] [Google Scholar]
166.Tay J., Thompson C.H., Luscombe-Marsh N.D., Wycherley T.P., Noakes M., Buckley J.D., et al. Effects of an energy-restricted low-carbohydrate, high unsaturated fat/low saturated fat diet versus a high-carbohydrate, low-fat diet in type 2 diabetes: a 2-year randomized clinical trial. Diabetes Obes. Metab. 2018;20(4):858–871. doi: 10.1111/dom.13164. [DOI] [PubMed] [Google Scholar]
167.Teng K.T., Chang L.F., Vethakkan S.R., Nesaretnam K., Sanders T.A.B. Effects of exchanging carbohydrate or monounsaturated fat with saturated fat on inflammatory and thrombogenic responses in subjects with abdominal obesity: a randomized controlled trial. Clin. Nutr. 2017;36(5):1250–1258. doi: 10.1016/j.clnu.2016.08.026. [DOI] [PubMed] [Google Scholar]
168.Thomsen M.N., Skytte M.J., Samkani A., Carl M.H., Weber P., Astrup A., et al. Dietary carbohydrate restriction augments weight loss-induced improvements in glycaemic control and liver fat in individuals with type 2 diabetes: a randomised controlled trial. Diabetologia. 2022;65(3):506–517. doi: 10.1007/s00125-021-05628-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
169.Thomsen M.N., Skytte M.J., Samkani A., Weber P., Fenger M., Frystyk J., et al. Replacing dietary carbohydrate with protein and fat improves lipoprotein subclass profile and liver fat in type 2 diabetes independent of body weight: evidence from 2 randomized controlled trials. Am. J. Clin. Nutr. 2025;121(2):224–231. doi: 10.1016/j.ajcnut.2024.11.030. [DOI] [PubMed] [Google Scholar]
170.Thomson C.A., Stopeck A.T., Bea J.W., Cussler E., Nardi E., Frey G., et al. Changes in body weight and metabolic indexes in overweight breast cancer survivors enrolled in a randomized trial of low-fat vs. reduced carbohydrate diets. Nutr. Cancer. 2010;62(8):1142–1152. doi: 10.1080/01635581.2010.513803. [DOI] [PubMed] [Google Scholar]
171.Thorning T.K., Raziani F., Bendsen N.T., Astrup A., Tholstrup T., Raben A. Diets with high-fat cheese, high-fat meat, or carbohydrate on cardiovascular risk markers in overweight postmenopausal women: a randomized crossover trial. Am. J. Clin. Nutr. 2015;102(3):573–581. doi: 10.3945/ajcn.115.109116. [DOI] [PubMed] [Google Scholar]
172.Turton J.L., Brinkworth G.D., Parker H.M., Lim D., Lee K., Rush A., et al. Effects of a low-carbohydrate diet in adults with type 1 diabetes management: a single arm non-randomised clinical trial. PLOS ONE. 2023;18(7) [Google Scholar]
173.Tzenios N., Lewis E.D., Crowley D.C., Chahine M., Evans M. Examining the efficacy of a very-low-carbohydrate ketogenic diet on cardiovascular health in adults with mildly elevated low-density lipoprotein cholesterol in an open-label pilot study. Metab. Syndr. Relat. Disord. 2022;20(2):94–103. doi: 10.1089/met.2021.0042. [DOI] [PMC free article] [PubMed] [Google Scholar]
174.Valsdottir T.D., Øvrebø B., Falck T.M., Litleskare S., Johansen E.I., Henriksen C., et al. Low-carbohydrate high-fat diet and exercise: effect of a 10-week intervention on body composition and CVD risk factors in overweight and obese women-a randomized controlled trial. Nutrients. 2020;13(1):110. doi: 10.3390/nu13010110. [DOI] [PMC free article] [PubMed] [Google Scholar]
175.Valsdottir T.D., Øvrebø B., Kornfeldt T.M., Litleskare S., Johansen E.I., Henriksen C., et al. Effect of aerobic exercise and low-carbohydrate high-fat diet on glucose tolerance and android/gynoid fat in overweight/obese women: a randomized controlled trial. Front. Physiol. 2023;14 [Google Scholar]
176.Veum V.L., Laupsa-Borge J., Eng Ø., Rostrup E., Larsen T.H., Nordrehaug J.E., et al. Visceral adiposity and metabolic syndrome after very high–fat and low-fat isocaloric diets: a randomized controlled trial. Am. J. Clin. Nutr. 2017;105(1):85–99. doi: 10.3945/ajcn.115.123463. [DOI] [PubMed] [Google Scholar]
177.Volek J.S., Sharman M.J., Gómez A.L., DiPasquale C., Roti M., Pumerantz A., et al. Comparison of a very low-carbohydrate and low-fat diet on fasting lipids, LDL subclasses, insulin resistance, and postprandial lipemic responses in overweight women. J. Am. Coll. Nutr. 2004;23(2):177–184. doi: 10.1080/07315724.2004.10719359. [DOI] [PubMed] [Google Scholar]
178.Wachsmuth N.B., Aberer F., Haupt S., Schierbauer J.R., Zimmer R.T., Eckstein M.L., et al. The impact of a high-carbohydrate/low fat vs. low-carbohydrate diet on performance and body composition in physically active adults: a cross-over controlled trial. Nutrients. 2022;14(3):423. doi: 10.3390/nu14030423. [DOI] [PMC free article] [PubMed] [Google Scholar]
179.Wan Y., Wang F., Yuan J., Li J., Jiang D., Zhang J., et al. Effects of macronutrient distribution on weight and related cardiometabolic profile in healthy non-obese Chinese: a 6-month, randomized controlled-feeding trial. EBioMedicine. 2017;22:200–207. doi: 10.1016/j.ebiom.2017.06.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
180.Weber P., Thomsen M.N., Skytte M.J., Samkani A., Carl M.H., Astrup A., et al. Effects of carbohydrate restriction on body weight and glycemic control in individuals with type 2 diabetes: a randomized controlled trial of efficacy in real-life settings. Nutrients. 2022;14(24):5244. doi: 10.3390/nu14245244. [DOI] [PMC free article] [PubMed] [Google Scholar]
181.Wekesa A.L., Doyle L.M., Fitzmaurice D., O'Donovan O., Phelan J.P., Ross M.D., et al. Influence of a low-carbohydrate diet on endothelial microvesicles in overweight women. Appl. Physiol. Nutr. Metab. 2016;41(5):522–527. doi: 10.1139/apnm-2015-0507. [DOI] [PubMed] [Google Scholar]
182.Wolever T.M., Gibbs A.L., Mehling C., Chiasson J.L., Connelly P.W., Josse R.G., et al. The Canadian Trial of Carbohydrates in Diabetes (CCD), a 1-y controlled trial of low-glycemic-index dietary carbohydrate in type 2 diabetes: no effect on glycated hemoglobin but reduction in C-reactive protein. Am. J. Clin. Nutr. 2008;87(1):114–125. doi: 10.1093/ajcn/87.1.114. [DOI] [PubMed] [Google Scholar]
183.Wycherley T.P., Brinkworth G.D., Keogh J.B., Noakes M., Buckley J.D., Clifton P.M. Long-term effects of weight loss with a very low carbohydrate and low fat diet on vascular function in overweight and obese patients. J. Intern. Med. 2010;267(5):452–461. doi: 10.1111/j.1365-2796.2009.02174.x. [DOI] [PubMed] [Google Scholar]
184.Wycherley T.P., Thompson C.H., Buckley J.D., Luscombe-Marsh N.D., Noakes M., Wittert G.A., et al. Long-term effects of weight loss with a very-low carbohydrate, low saturated fat diet on flow mediated dilatation in patients with type 2 diabetes: a randomised controlled trial. Atherosclerosis. 2016;252:28–31. doi: 10.1016/j.atherosclerosis.2016.07.908. [DOI] [PubMed] [Google Scholar]
185.Yamada Y., Uchida J., Izumi H., Tsukamoto Y., Inoue G., Watanabe Y., et al. A non-calorie-restricted low-carbohydrate diet is effective as an alternative therapy for patients with type 2 diabetes. Intern. Med. 2014;53(1):13–19. doi: 10.2169/internalmedicine.53.0861. [DOI] [PubMed] [Google Scholar]
186.Yancy W.S., Jr., Westman E.C., McDuffie J.R., Grambow S.C., Jeffreys A.S., Bolton J., et al. A randomized trial of a low-carbohydrate diet vs orlistat plus a low-fat diet for weight loss. Arch. Intern. Med. 2010;170(2):136–145. doi: 10.1001/archinternmed.2009.492. [DOI] [PubMed] [Google Scholar]
187.Zainordin N.A., Eddy Warman N.A., Mohamad A.F., Abu Yazid F.A., Ismail N.H., Chen X.W., et al. Safety and efficacy of very low carbohydrate diet in patients with diabetic kidney disease—a randomized controlled trial. PLOS ONE. 2021;16(10) [Google Scholar]
188.Zinn C., McPhee J., Harris N., Williden M., Prendergast K., Schofield G. A 12-week low-carbohydrate, high-fat diet improves metabolic health outcomes over a control diet in a randomised controlled trial with overweight defence force personnel. Appl. Physiol. Nutr. Metab. 2017;42(11):1158–1164. doi: 10.1139/apnm-2017-0260. [DOI] [PubMed] [Google Scholar]
189.Dening J., Mohebbi M., Abbott G., George E.S., Ball K., Islam S.M.S. A web-based low carbohydrate diet intervention significantly improves glycaemic control in adults with type 2 diabetes: results of the T2diet Study randomised controlled trial. Nutr. Diabetes. 2023;13(1):12. doi: 10.1038/s41387-023-00240-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
190.Iqbal N., Seshadri P., Stern L., Loh J., Kundu S., Jafar T., et al. Serum resistin is not associated with obesity or insulin resistance in humans. Eur. Rev. Med. Pharmacol. Sci. 2005;9(3):161–165. [PubMed] [Google Scholar]
191.Martens E.A., Gonnissen H.K., Gatta-Cherifi B., Janssens P.L., Westerterp-Plantenga M.S. Maintenance of energy expenditure on high-protein vs. high-carbohydrate diets at a constant body weight may prevent a positive energy balance. Clin. Nutr. 2015;34(5):968–975. doi: 10.1016/j.clnu.2014.10.007. [DOI] [PubMed] [Google Scholar]
192.Wal J.S., McBurney M.I., Moellering N., Marth J., Dhurandhar N.V. Moderate-carbohydrate low-fat versus low-carbohydrate high-fat meal replacements for weight loss. Int. J. Food Sci. Nutr. 2007;58(4):321–329. doi: 10.1080/09637480701240752. [DOI] [PubMed] [Google Scholar]
193.White A.M., Johnston C.S., Swan P.D., Tjonn S.L., Sears B. Blood ketones are directly related to fatigue and perceived effort during exercise in overweight adults adhering to low-carbohydrate diets for weight loss: a pilot study. J. Am. Diet. Assoc. 2007;107(10):1792–1796. doi: 10.1016/j.jada.2007.07.009. [DOI] [PubMed] [Google Scholar]
194.Wolever T.M., Mehling C. Long-term effect of varying the source or amount of dietary carbohydrate on postprandial plasma glucose, insulin, triacylglycerol, and free fatty acid concentrations in subjects with impaired glucose tolerance. Am. J. Clin. Nutr. 2003;77(3):612–621. doi: 10.1093/ajcn/77.3.612. [DOI] [PubMed] [Google Scholar]
195.Brinkworth G.D., Noakes M., Clifton P.M., Buckley J.D. Effects of a low carbohydrate weight loss diet on exercise capacity and tolerance in obese subjects. Obesity (Silver Spring). 2009;17(10):1916–1923. doi: 10.1038/oby.2009.134. [DOI] [PubMed] [Google Scholar]
196.Brinkworth G.D., Buckley J.D., Noakes M., Clifton P.M. Renal function following long-term weight loss in individuals with abdominal obesity on a very-low-carbohydrate diet vs high-carbohydrate diet. J. Am. Diet. Assoc. 2010;110(4):633–638. doi: 10.1016/j.jada.2009.12.016. [DOI] [PubMed] [Google Scholar]
197.Cohen C.W., Fontaine K.R., Arend R.C., Alvarez R.D., Leath C.A., III, Huh W.K., et al. A ketogenic diet reduces central obesity and serum insulin in women with ovarian or endometrial cancer. J. Nutr. 2018;148(8):1253–1260. doi: 10.1093/jn/nxy119. [DOI] [PMC free article] [PubMed] [Google Scholar]
198.Crabtree C.D., Kackley M.L., Buga A., Fell B., LaFountain R.A., Hyde P.N., et al. Comparison of ketogenic diets with and without ketone salts versus a low-fat diet: liver fat responses in overweight adults. Nutrients. 2021;13(3):966. doi: 10.3390/nu13030966. [DOI] [PMC free article] [PubMed] [Google Scholar]
199.Iacovides S., Maloney S.K., Bhana S., Angamia Z., Meiring R.M. Could the ketogenic diet induce a shift in thyroid function and support a metabolic advantage in healthy participants? A pilot randomized-controlled-crossover trial. PLOS ONE. 2022;17(6) [Google Scholar]
200.Karl J.P., Roberts S.B., Schaefer E.J., Gleason J.A., Fuss P., Rasmussen H., et al. Effects of carbohydrate quantity and glycemic index on resting metabolic rate and body composition during weight loss. Obesity (Silver Spring) 2015;23(11):2190–2198. doi: 10.1002/oby.21268. [DOI] [PMC free article] [PubMed] [Google Scholar]
201.Lundanes J., Storliløkken G.E., Solem M.S., Dankel S.N., Tangvik R.J., Ødegård R., et al. Gastrointestinal hormones and subjective ratings of appetite after low-carbohydrate vs low-fat low-energy diets in females with lipedema—a randomized controlled trial. Clin. Nutr. ESPEN. 2025;65:16–24. doi: 10.1016/j.clnesp.2024.11.018. [DOI] [PubMed] [Google Scholar]
202.Oliveira B.F., Chang C.R., Oetsch K., Falkenhain K., Crampton K., Stork M., et al. Impact of a low-carbohydrate compared with low-fat breakfast on blood glucose control in type 2 diabetes: a randomized trial. Am. J. Clin. Nutr. 2023;118(1):209–217. doi: 10.1016/j.ajcnut.2023.04.032. [DOI] [PubMed] [Google Scholar]
203.Rasmussen L.G., Larsen T.M., Mortensen P.K., Due A., Astrup A. Effect on 24-h energy expenditure of a moderate-fat diet high in monounsaturated fatty acids compared with that of a low-fat, carbohydrate-rich diet: a 6-mo controlled dietary intervention trial. Am. J. Clin. Nutr. 2007;85(4):1014–1022. doi: 10.1093/ajcn/85.4.1014. [DOI] [PubMed] [Google Scholar]
204.Swenson B.R., Saalwachter Schulman A., Edwards M.J., Gross M.P., Hedrick T.L., Weltman A.L., et al. The effect of a low-carbohydrate, high-protein diet on post laparoscopic gastric bypass weight loss: a prospective randomized trial. J. Surg. Res. 2007;142(2):308–313. doi: 10.1016/j.jss.2007.02.052. [DOI] [PubMed] [Google Scholar]
205.Walker K.Z., O'Dea K., Johnson L., Sinclair A.J., Piers L.S., Nicholson G.C., et al. Body fat distribution and non-insulin-dependent diabetes: comparison of a fiber-rich, high-carbohydrate, low-fat (23%) diet and a 35% fat diet high in monounsaturated fat. Am. J. Clin. Nutr. 1996;63(2):254–260. doi: 10.1093/ajcn/63.2.254. [DOI] [PubMed] [Google Scholar]
206.Wycherley T.P., Buckley J.D., Noakes M., Clifton P.M., Brinkworth G.D. Long-term effects of a very low-carbohydrate weight loss diet on exercise capacity and tolerance in overweight and obese adults. J. Am. Coll. Nutr. 2014;33(4):267–273. doi: 10.1080/07315724.2014.911668. [DOI] [PubMed] [Google Scholar]
207.Yancy W.S., Jr., Olsen M.K., Guyton J.R., Bakst R.P., Westman E.C. A low-carbohydrate, ketogenic diet versus a low-fat diet to treat obesity and hyperlipidemia: a randomized, controlled trial. Ann. Intern. Med. 2004;140(10):769–777. doi: 10.7326/0003-4819-140-10-200405180-00006. [DOI] [PubMed] [Google Scholar]
208.McManus K., Antinoro L., Sacks F. A randomized controlled trial of a moderate-fat, low-energy diet compared with a low fat, low-energy diet for weight loss in overweight adults. Int. J. Obes. Relat. Metab. Disord. 2001;25(10):1503–1511. doi: 10.1038/sj.ijo.0801796. [DOI] [PubMed] [Google Scholar]
209.Norwitz N.G., Soto-Mota A., Kaplan B., Ludwig D.S., Budoff M., Kontush A., et al. The lipid energy model: reimagining lipoprotein function in the context of carbohydrate-restricted diets. Metabolites. 2022;12(5):460. doi: 10.3390/metabo12050460. [DOI] [PMC free article] [PubMed] [Google Scholar]
210.McLaughlin T., Reaven G., Abbasi F., Lamendola C., Saad M., Waters D., et al. Is there a simple way to identify insulin-resistant individuals at increased risk of cardiovascular disease? Am. J. Cardiol. 2005;96(3):399–404. doi: 10.1016/j.amjcard.2005.03.085. [DOI] [PubMed] [Google Scholar]
211.Castelli W.P., Garrison R.J., Wilson P.W.F., Abbott R.D., Kalousdian S., Kannel W.B. Incidence of coronary heart disease and lipoprotein cholesterol levels: the Framingham Study. JAMA. 1983;250:1865–1871. [Google Scholar]
212.Millán J., Pintó X., Muñoz A., Zúñiga M., Rubiés-Prat J., Pallardo L.F., et al. Lipoprotein ratios: physiological significance and clinical usefulness in cardiovascular prevention. Vasc. Health Risk Manag. 2009;5:757–765. [PMC free article] [PubMed] [Google Scholar]
213.Soltani S., Jayedi A., Abdollahi S., Vasmehjani A.A., Meshkini F., Shab-Bidar S. Effect of carbohydrate restriction on body weight in overweight and obese adults: a systematic review and dose-response meta-analysis of 110 randomized controlled trials. Front. Nutr. 2023;10 [Google Scholar]
214.Naghshi S., Sadeghi O., Willett W.C., Esmaillzadeh A. Dietary intake of total, animal, and plant proteins and risk of all cause, cardiovascular, and cancer mortality: systematic review and dose-response meta-analysis of prospective cohort studies. BMJ. 2020;370 [Google Scholar]
215.Soto-Mota A., Flores-Jurado Y., Norwitz N.G., Feldman D., Pereira M.A., Danaei G., et al. Increased low-density lipoprotein cholesterol on a low-carbohydrate diet in adults with normal but not high body weight: a meta-analysis. Am. J. Clin. Nutr. 2024;119(3):740–747. doi: 10.1016/j.ajcnut.2024.01.009. [DOI] [PubMed] [Google Scholar]
216.Tan C.Y., Vidal-Puig A. Adipose tissue expandability: the metabolic problems of obesity may arise from the inability to become more obese. Biochem. Soc. Trans. 2008;36(5):935–940. doi: 10.1042/BST0360935. [DOI] [PubMed] [Google Scholar]
217.Scott P.M. Which diet is better--low-fat or low-carb? JAAPA. 2006;19(1):49. doi: 10.1097/01720610-200601000-00010. [DOI] [PubMed] [Google Scholar]
218.David L.A., Maurice C.F., Carmody R.N., Gootenberg D.B., Button J.E., Wolfe B.E., et al. Diet rapidly and reproducibly alters the human gut microbiome. Nature. 2014;505(7484):559–563. doi: 10.1038/nature12820. [DOI] [PMC free article] [PubMed] [Google Scholar]
219.St Jeor S.T., Howard B.V., Prewitt T.E., Bovee V., Bazzarre T., Eckel R.H., et al. Dietary protein and weight reduction: a statement for healthcare professionals from the Nutrition Committee of the Council on Nutrition, Physical Activity, and Metabolism of the American Heart Association. Circulation. 2001;104(15):1869–1874. doi: 10.1161/hc4001.096152. [DOI] [PubMed] [Google Scholar]
220.Van Elswyk M.E., Weatherford C.A., McNeill S.H. A systematic review of renal health in healthy individuals associated with protein intake above the US recommended daily allowance in randomized controlled trials and observational studies. Adv. Nutr. 2018;9(4):404–418. doi: 10.1093/advances/nmy026. [DOI] [PMC free article] [PubMed] [Google Scholar]
221.Athinarayanan S.J., Roberts C.G.P., Phinney S.D., Weimbs T., Friedman A.N., Volek J.S. Effects of a continuous remote care intervention including nutritional ketosis on kidney function and inflammation in adults with type 2 diabetes: a post-hoc latent class trajectory analysis. Front. Nutr. 2025;12 [Google Scholar]
222.J.J. Deeks, J.P.T. Higgins, D.G. Altman, Analysing data and undertaking meta-analyses. In: J.P.T. Higgins, J. Thomas, J. Chandler, et al. (Eds.), Cochrane Handbook for Systematic Reviews of Interventions Version 6.5 (updated February 2023).
223.A. Hengist, R.G. Davies, J.P. Walhin, J. Buniam, L.H. Merrell, L. Rogers, et al. Ketogenic diet but not free-sugar restriction alters glucose tolerance, lipid metabolism, peripheral tissue phenotype, and gut microbiome: RCT. Cell Rep Med. 2024 Aug 20;5(8):101667. 10.1016/j.xcrm.2024.101667. [DOI]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

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mmc1.xlsx^{(85.3KB, xlsx)}

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Data Availability Statement

Data described in the manuscript, code book, and analytic code will be made publicly and freely available without restriction at https://figshare.com/s/7dd68520ec63bf964d77

[bib1] 1.WHO, Cardiovascular diseases (CVDs), 2021 Updated July 31, 2025. Accessed August 20, 2025. Available from: https://www.who.int/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds).

[bib2] 2.Emerging Risk Factors Collaboration, Wormser D., Kaptoge S., Di Angelantonio E., Wood A.M., Pennells L., et al. Separate and combined associations of body-mass index and abdominal adiposity with cardiovascular disease: collaborative analysis of 58 prospective studies. Lancet. 2011;377(9771):1085–1095. doi: 10.1016/S0140-6736(11)60105-0. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib3] 3.World Health Organization . 2025. Obesity and overweight. [Google Scholar]

[bib4] 4.Okunogbe A., Nugent R., Spencer G., Powis J., Ralston J., Wilding J. Economic impacts of overweight and obesity: current and future estimates for 161 countries. BMJ Glob. Health. 2022;7(9) [Google Scholar]

[bib5] 5.Kossoff E.H., Zupec-Kania B.A., Auvin S., Ballaban-Gil K.R., Christina Bergqvist A.G., Blackford R., et al. Optimal clinical management of children receiving dietary therapies for epilepsy: updated recommendations of the International Ketogenic Diet Study Group. Epilepsia Open. 2018;3(2):175–192. doi: 10.1002/epi4.12225. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib6] 6.Zhu H., Bi D., Zhang Y., Kong C., Du J., Wu X., et al. Ketogenic diet for human diseases: the underlying mechanisms and potential for clinical implementations. Signal Transduct. Target. Ther. 2022;7(1):11. doi: 10.1038/s41392-021-00831-w. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib7] 7.Seyfried T.N., Sanderson T.M., El-Abbadi M.M., McGowan R., Mukherjee P. Role of glucose and ketone bodies in the metabolic control of experimental brain cancer. Br. J. Cancer. 2003;89(7):1375–1382. doi: 10.1038/sj.bjc.6601269. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib8] 8.Jo U., Park K. Carbohydrate intake and risk of cardiovascular disease: a systematic review and meta-analysis of prospective studies. Nutrients. 2023;15(7):1740. doi: 10.3390/nu15071740. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib9] 9.Ma Y., Zheng Z., Zhuang L., Wang H., Li A., Chen L., et al. Dietary macronutrient intake and cardiovascular disease risk and mortality: a systematic review and dose-response meta-analysis of prospective cohort studies. Nutrients. 2024;16(1):152. doi: 10.3390/nu16010152. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib10] 10.Qin P., Huang C., Jiang B., Wang X., Yang Y., Ma J., et al. Dietary carbohydrate quantity and quality and risk of cardiovascular disease, all-cause, cardiovascular and cancer mortality: a systematic review and meta-analysis. Clin. Nutr. 2023;42(2):148–165. doi: 10.1016/j.clnu.2022.12.010. [DOI] [PubMed] [Google Scholar]

[bib11] 11.Dwivedi A.K., Dubey P., Reddy S.Y., Clegg D.J. Associations of glycemic index and glycemic load with cardiovascular disease: updated evidence from meta-analysis and cohort studies. Curr. Cardiol. Rep. 2022;24(3):141–161. doi: 10.1007/s11886-022-01635-2. [DOI] [PubMed] [Google Scholar]

[bib12] 12.Mohammadifard N., Mansourian M., Firouzi S., Taheri M., Haghighatdoost F. Longitudinal association of dietary carbohydrate and the risk cardiovascular disease: a dose-response meta-analysis. Crit. Rev. Food Sci. Nutr. 2022;62(23):6277–6292. doi: 10.1080/10408398.2021.1900057. [DOI] [PubMed] [Google Scholar]

[bib13] 13.Dong T., Guo M., Zhang P., Sun G., Chen B. The effects of low-carbohydrate diets on cardiovascular risk factors: a meta-analysis. PLOS ONE. 2020;15(1) [Google Scholar]

[bib14] 14.Mansoor N., Vinknes K.J., Veierød M.B., Retterstøl K. Effects of low-carbohydrate diets v. low-fat diets on body weight and cardiovascular risk factors: a meta-analysis of randomised controlled trials. Br. J. Nutr. 2016;115(3):466–479. doi: 10.1017/S0007114515004699. [DOI] [PubMed] [Google Scholar]

[bib15] 15.Leung L.Y., Tam H.L., Ho J.K. Effects of ketogenic and low-carbohydrate diets on the body composition of adults with overweight or obesity: a systematic review and meta-analysis of randomised controlled trials. Clin. Nutr. 2025;46:10–18. doi: 10.1016/j.clnu.2025.01.017. [DOI] [PubMed] [Google Scholar]

[bib16] 16.Darand M., Hassanizadeh S., Talebi S., Darabi Z., Bagherniya M., Yaghoubi F., et al. Comparison of the effect of a low-carbohydrate diet with a low-fat diet on anthropometric indices and body fat percentage: a systematic review and meta-analysis of randomized controlled trials. J. Nutr. Food Secur. 2023;8(3):493–520. [Google Scholar]

[bib17] 17.Ashtary-Larky D., Bagheri R., Asbaghi O., Tinsley G.M., Kooti W., Abbasnezhad A., et al. Effects of resistance training combined with a ketogenic diet on body composition: a systematic review and meta-analysis. Crit. Rev. Food Sci. Nutr. 2022;62(21):5717–5732. doi: 10.1080/10408398.2021.1890689. [DOI] [PubMed] [Google Scholar]

[bib18] 18.Amini M.R., Aminianfar A., Naghshi S., Larijani B., Esmaillzadeh A. The effect of ketogenic diet on body composition and anthropometric measures: a systematic review and meta-analysis of randomized controlled trials. Crit. Rev. Food Sci. Nutr. 2022;62(13):3644–3657. doi: 10.1080/10408398.2020.1867957. [DOI] [PubMed] [Google Scholar]

[bib19] 19.Naude C.E., Schoonees A., Senekal M., Young T., Garner P., Volmink J. Low carbohydrate versus isoenergetic balanced diets for reducing weight and cardiovascular risk: a systematic review and meta-analysis. PLOS ONE. 2014;9(7) [Google Scholar]

[bib20] 20.Smith E.S., Smith H.A., Betts J.A., Gonzalez J.T., Atkinson G. A systematic review and meta-analysis comparing heterogeneity in body mass responses between low-carbohydrate and low-fat diets. Obesity (Silver Spring). 2020;28(10):1833–1842. doi: 10.1002/oby.22968. [DOI] [PubMed] [Google Scholar]

[bib21] 21.Wang Y., Zhou K., Wang V., Bao D., Zhou J. The effects of concurrent training combined with low-carbohydrate high-fat ketogenic diet on body composition and aerobic performance: a systematic review and meta-analysis. Int. J. Environ. Res. Public Health. 2022;19(18) [Google Scholar]

[bib22] 22.Seidelmann S.B., Claggett B., Cheng S., Henglin M., Shah A., Steffen L.M., et al. Dietary carbohydrate intake and mortality: a prospective cohort study and meta-analysis. Lancet Public Health. 2018;3(9):e419–e428. doi: 10.1016/S2468-2667(18)30135-X. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib23] 23.Feinman R.D., Pogozelski W.K., Astrup A., Bernstein R.K., Fine E.J., Westman E.C., et al. Dietary carbohydrate restriction as the first approach in diabetes management: critical review and evidence base. Nutrition. 2015;31(1):1–13. doi: 10.1016/j.nut.2014.06.011. [DOI] [PubMed] [Google Scholar]

[bib24] 24.Ebbeling C.B., Swain J.F., Feldman H.A., Wong W.W., Hachey D.L., Garcia-Lago E., et al. Effects of dietary composition on energy expenditure during weight-loss maintenance. JAMA. 2012;307(24):2627–2634. doi: 10.1001/jama.2012.6607. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib25] 25.Page M.J., Moher D., Bossuyt P.M., Boutron I., Hoffmann T.C., Mulrow C.D., et al. PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. BMJ. 2021;372 [Google Scholar]

[bib26] 26.Feng S., Liu R., Thompson C., Colwell B. The associations between secondhand smoke exposure and various cardiovascular diseases: a meta-analysis. Nicotine Tob. Res. 2025 doi: 10.1093/ntr/ntaf111. [DOI] [Google Scholar]

[bib27] 27.Parry-Strong A., Wright-McNaughton M., Weatherall M., Hall R.M., Coppell K.J., Barthow C., et al. Very low carbohydrate (ketogenic) diets in type 2 diabetes: a systematic review and meta-analysis of randomized controlled trials. Diabetes Obes. Metab. 2022;24(12):2431–2442. doi: 10.1111/dom.14837. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib28] 28.Willems A.E.M., Sura-de Jong M., van Beek A.P., Nederhof E., van Dijk G. Effects of macronutrient intake in obesity: a meta-analysis of low-carbohydrate and low-fat diets on markers of the metabolic syndrome. Nutr. Rev. 2021;79(4):429–444. doi: 10.1093/nutrit/nuaa044. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib29] 29.Sterne J.A.C., Savović J., Page M.J., Elbers R.G., Blencowe N.S., Boutron I., et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ. 2019;366 [Google Scholar]

[bib30] 30.Hoppen T.H., Cuno R.M., Nelson J., Lemmel F., Schlechter P., Morina N. Meta-analysis of randomized controlled trials examining social comparison as a behaviour change technique across the behavioural sciences. Nat. Hum. Behav. 2025;9(8):1595–1612. doi: 10.1038/s41562-025-02209-2. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib31] 31.Veroniki A.A., Jackson D., Viechtbauer W., Bender R., Bowden J., Knapp G., et al. Methods to estimate the between-study variance and its uncertainty in meta-analysis. Res. Synth. Methods. 2016;7(1):55–79. doi: 10.1002/jrsm.1164. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib32] 32.Langan D., Higgins J.P.T., Simmonds M. Comparative performance of heterogeneity variance estimators in meta-analysis: a review of simulation studies. Res. Synth. Methods. 2017;8(2):181–198. doi: 10.1002/jrsm.1198. [DOI] [PubMed] [Google Scholar]

[bib33] 33.Viechtbauer W. Bias and efficiency of meta-analytic variance estimators in the random-effects model. J. Educ. Behav. Stat. 2005;30(3):261–293. [Google Scholar]

[bib34] 34.Ludwig D.S., Ebbeling C.B. The carbohydrate-insulin model of obesity: beyond "calories in, calories out,". JAMA Intern. Med. 2018;178(8):1098–1103. doi: 10.1001/jamainternmed.2018.2933. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib35] 35.Abete I., Parra D., De Morentin B.M., Alfredo Martinez J. Effects of two energy-restricted diets differing in the carbohydrate/protein ratio on weight loss and oxidative changes of obese men. Int. J. Food Sci. Nutr. 2009;60(Suppl 3):1–13. [Google Scholar]

[bib36] 36.Ahmad A., Isherwood C., Umpleby M., Griffin B. Effects of high and low sugar diets on cardiovascular disease risk factors. J. Nutr. Sci. Vitaminol. (Tokyo). 2020;66(Suppl):S18–S24. doi: 10.3177/jnsv.66.S18. [DOI] [PubMed] [Google Scholar]

[bib37] 37.Alnoubi A.A., Alqurashi R.M. The role of high-fat ketogenic and low-fat diets in weight reduction and cardiovascular risk mitigation among overweight and obese women: a single-blind controlled study. Curr. Res. Nutr. Food Sci. 2024;12(3):1366–1375. [Google Scholar]

[bib38] 38.Archer W.R., Lamarche B., Dériaz O., Landry N., Corneau L., Després J.P., et al. Variations in body composition and plasma lipids in response to a high-carbohydrate diet. Obes. Res. 2003;11(8):978–986. doi: 10.1038/oby.2003.135. [DOI] [PubMed] [Google Scholar]

[bib39] 39.Baba N.H., Sawaya S., Torbay N., Habbal Z., Azar S., Hashim S.A. High protein vs high carbohydrate hypoenergetic diet for the treatment of obese hyperinsulinemic subjects. Int. J. Obes. Relat. Metab. Disord. 1999;23(11):1202–1206. doi: 10.1038/sj.ijo.0801064. [DOI] [PubMed] [Google Scholar]

[bib40] 40.Ballard K.D., Quann E.E., Kupchak B.R., Volk B.M., Kawiecki D.M., Fernandez M.L., et al. Dietary carbohydrate restriction improves insulin sensitivity, blood pressure, microvascular function, and cellular adhesion markers in individuals taking statins. Nutr. Res. 2013;33(11):905–912. doi: 10.1016/j.nutres.2013.07.022. [DOI] [PubMed] [Google Scholar]

[bib41] 41.Bazzano L.A., Hu T., Reynolds K., Yao L., Bunol C., Liu Y., et al. Effects of low-carbohydrate and low-fat diets: a randomized trial. Ann. Intern. Med. 2014;161(5):309–318. doi: 10.7326/M14-0180. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib42] 42.Boers I., Muskiet F.A., Berkelaar E., Schut E., Penders R., Hoenderdos K., et al. Favourable effects of consuming a Palaeolithic-type diet on characteristics of the metabolic syndrome: a randomized controlled pilot-study. Lipids Health Dis. 2014;13:160. doi: 10.1186/1476-511X-13-160. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib43] 43.Bradley U., Spence M., Courtney C.H., McKinley M.C., Ennis C.N., McCance D.R., et al. Low-fat versus low-carbohydrate weight reduction diets: effects on weight loss, insulin resistance, and cardiovascular risk: a randomized control trial. Diabetes. 2009;58(12):2741–2748. doi: 10.2337/db09-0098. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib44] 44.Brehm B.J., Spang S.E., Lattin B.L., Seeley R.J., Daniels S.R., D'Alessio D.A. The role of energy expenditure in the differential weight loss in obese women on low-fat and low-carbohydrate diets. J. Clin. Endocrinol. Metab. 2005;90(3):1475–1482. doi: 10.1210/jc.2004-1540. [DOI] [PubMed] [Google Scholar]

[bib45] 45.Brinkworth G.D., Noakes M., Keogh J.B., Luscombe N.D., Wittert G.A., Clifton P.M. Long-term effects of a high-protein, low-carbohydrate diet on weight control and cardiovascular risk markers in obese hyperinsulinemic subjects. Int. J. Obes. Relat. Metab. Disord. 2004;28(5):661–670. doi: 10.1038/sj.ijo.0802617. [DOI] [PubMed] [Google Scholar]

[bib46] 46.Brinkworth G.D., Noakes M., Parker B., Foster P., Clifton P.M. Long-term effects of advice to consume a high-protein, low-fat diet, rather than a conventional weight-loss diet, in obese adults with type 2 diabetes: one-year follow-up of a randomised trial. Diabetologia. 2004;47(10):1677–1686. doi: 10.1007/s00125-004-1511-7. [DOI] [PubMed] [Google Scholar]

[bib47] 47.Brinkworth G.D., Noakes M., Buckley J.D., Keogh J.B., Clifton P.M. Long-term effects of a very-low-carbohydrate weight loss diet compared with an isocaloric low-fat diet after 12 mo. Am. J. Clin. Nutr. 2009;90(1):23–32. doi: 10.3945/ajcn.2008.27326. [DOI] [PubMed] [Google Scholar]

[bib48] 48.Buga A., Welton G.L., Scott K.E., Atwell A.D., Haley S.J., Esbenshade N.J., et al. The effects of carbohydrate versus fat restriction on lipid profiles in highly trained, recreational distance runners: a randomized, cross-over trial. Nutrients. 2022;14(6):1135. doi: 10.3390/nu14061135. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib49] 49.Buscemi S., Verga S., Tranchina M.R., Cottone S., Cerasola G. Effects of hypocaloric veryus fat restriction on lipid profiles in highly trained, real function in obese women. Eur. J. Clin. Invest. 2009;39(5):339–347. doi: 10.1111/j.1365-2362.2009.02091.x. [DOI] [PubMed] [Google Scholar]

[bib50] 50.Bush N.C., Resuehr H.E.S., Goree L.L., Locher J.L., Bray M.S., Soleymani T., et al. A high-fat compared with a high-carbohydrate breakfast enhances 24-hour fat oxidation in older adults. J. Nutr. 2018;148(2):220–226. doi: 10.1093/jn/nxx040. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib51] 51.Cai L., Yin J., Ma X., Mo Y., Li C., Lu W., et al. Low-carbohydrate diets lead to greater weight loss and better glucose homeostasis than exercise: a randomized clinical trial. Front. Med. 2021;15(3):460–471. doi: 10.1007/s11684-021-0861-6. [DOI] [PubMed] [Google Scholar]

[bib52] 52.Chen C.Y., Huang W.S., Chen H.C., Chang C.H., Lee L.T., Chen H.S., et al. Effect of a 90 g/day low-carbohydrate diet on glycaemic control, small, dense low-density lipoprotein and carotid intima-media thickness in type 2 diabetic patients: an 18-month randomised controlled trial. PLOS ONE. 2020;15(10) [Google Scholar]

[bib53] 53.Chen C.Y., Huang W.S., Ho M.H., Chang C.H., Lee L.T., Chen H.S., et al. The potential prolonged effect at one-year follow-up after 18-month randomized controlled trial of a 90 g/day low-carbohydrate diet in patients with type 2 diabetes. Nutr. Diabetes. 2022;12(1):17. doi: 10.1038/s41387-022-00193-4. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib54] 54.Chiu S., Williams P.T., Dawson T., Bergman R.N., Stefanovski D., Watkins S.M., et al. Diets high in protein or saturated fat do not affect insulin sensitivity or plasma concentrations of lipids and lipoproteins in overweight and obese adults. J. Nutr. 2014;144(11):1753–1759. doi: 10.3945/jn.114.197624. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib55] 55.Cipryan L., Litschmannova M., Maffetone P.B., Plews D.J., Dostal T., Hofmann P., et al. Very low-carbohydrate high-fat diet improves risk markers for cardiometabolic health more than exercise in men and women with overfat constitution: secondary analysis of a randomized controlled clinical trial. Front. Nutr. 2022;9 [Google Scholar]

[bib56] 56.Claessens M., Van Baak M.A., Monsheimer S., Saris W.H.M. The effect of a low-fat, high-protein or high-carbohydrate ad libitum diet on weight loss maintenance and metabolic risk factors. Int. J. Obes. (Lomd). 2009;33(3):296–304. [Google Scholar]

[bib57] 57.Cunha G.M., Guzman G., Correa De Mello L.L., Trein B., Spina L., Bussade I., et al. Efficacy of a 2-month very low-calorie ketogenic diet (VLCKD) compared to a standard low-calorie diet in reducing visceral and liver fat accumulation in patients with obesity. Front. Endocrinol. (Lausanne). 2020;11:607. doi: 10.3389/fendo.2020.00607. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib58] 58.D’Abbondanza M., Ministrini S., Pucci G., Nulli Migliola E., Martorelli E.E., Gandolfo V., et al. Very low-carbohydrate ketogenic diet for the treatment of severe obesity and associated non-alcoholic fatty liver disease: the role of sex differences. Nutrients. 2020;12(9):2748. doi: 10.3390/nu12092748. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib59] 59.Dalle Grave R., Calugi S., Gavasso I., El Ghoch M., Marchesini G. A randomized trial of energy-restricted high-protein versus high-carbohydrate, low-fat diet in morbid obesity. Obesity (Silver Spring) 2013;21(9):1774–1781. doi: 10.1002/oby.20320. [DOI] [PubMed] [Google Scholar]

[bib60] 60.Davis N.J., Crandall J.P., Gajavelli S., Berman J.W., Tomuta N., Wylie-Rosett J., et al. Differential effects of low-carbohydrate and low-fat diets on inflammation and endothelial function in diabetes. J. Diabetes Complications. 2011;25(6):371–376. doi: 10.1016/j.jdiacomp.2011.08.001. [DOI] [PubMed] [Google Scholar]

[bib61] 61.Davis N.J., Tomuta N., Schechter C., Isasi C.R., Segal-Isaacson C.J., Stein D., et al. Comparative study of the effects of a 1-year dietary intervention of a low-carbohydrate diet versus a low-fat diet on weight and glycemic control in type 2 diabetes. Diabetes Care. 2009;32(7):1147–1152. doi: 10.2337/dc08-2108. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib62] 62.de Luis D.A., Izaola O., Aller R., de la Fuente B., Bachiller R., Romero E. Effects of a high-protein/low carbohydrate versus a standard hypocaloric diet on adipocytokine levels and insulin resistance in obese patients along 9 months. J. Diabetes Complications. 2015;29(7):950–954. doi: 10.1016/j.jdiacomp.2015.06.002. [DOI] [PubMed] [Google Scholar]

[bib63] 63.de Luis D.A., Aller R., Izaola O., Gonzalez Sagrado M., Bellioo D., Conde R. Effects of a low-fat versus a low-carbohydrate diet on adipocytokines in obese adults. Horm. Res. 2007;67(6):296–300. doi: 10.1159/000099329. [DOI] [PubMed] [Google Scholar]

[bib64] 64.Dorans K.S., Bazzano L.A., Qi L., He H., Chen J., Appel L.J., et al. Effects of a low-carbohydrate dietary intervention on hemoglobin A1c: a randomized clinical trial, JAMA Netw. Open. 2022;5(10) [Google Scholar]

[bib65] 65.Ebbeling C.B., Knapp A., Johnson A., Wong J.M.W., Greco K.F., Ma C., et al. Effects of a low-carbohydrate diet on insulin-resistant dyslipoproteinemia-a randomized controlled feeding trial. Am. J. Clin. Nutr. 2022;115(1):154–162. doi: 10.1093/ajcn/nqab287. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib66] 66.Egert S., Kratz M., Kannenberg F., Fobker M., Wahrburg U. Effects of high-fat and low-fat diets rich in monounsaturated fatty acids on serum lipids, LDL size and indices of lipid peroxidation in healthy non-obese men and women when consumed under controlled conditions. Eur. J. Nutr. 2011;50(1):71–79. doi: 10.1007/s00394-010-0116-9. [DOI] [PubMed] [Google Scholar]

[bib67] 67.Dellis D., Tsilingiris D., Eleftheriadou I., Tentolouris A., Sfikakis P.P., Jr., Dellis G., et al. Carbohydrate restriction in the morning increases weight loss effect of a hypocaloric Mediterranean type diet: a randomized, parallel group dietary intervention in overweight and obese subjects. Nutrition. 2020;71 [Google Scholar]

[bib68] 68.de Luis D.A., Aller R., Izaola O., Romero E. Effects of a high-protein/low-carbohydrate versus a standard hypocaloric diet on adipocytokine levels and cardiovascular risk factors during 9 months, role of rs6923761 gene variant of glucagon-like peptide 1 receptor. J. Endocrinol. Invest. 2015;38(11):1183–1189. doi: 10.1007/s40618-015-0304-9. [DOI] [PubMed] [Google Scholar]

[bib69] 69.Elhayany A., Lustman A., Abel R., Attal-Singer J., Vinker S. A low carbohydrate Mediterranean diet improves cardiovascular risk factors and diabetes control among overweight patients with type 2 diabetes mellitus: a 1-year prospective randomized intervention study. Diabetes Obes. Metab. 2010;12(3):204–209. doi: 10.1111/j.1463-1326.2009.01151.x. [DOI] [PubMed] [Google Scholar]

[bib70] 70.Foraker R.E., Pennell M., Sprangers P., Vitolins M.Z., DeGraffinreid C., Paskett E.D. Effect of a low-fat or low-carbohydrate weight-loss diet on markers of cardiovascular risk among premenopausal women: a randomized trial. J. Womens Health (Larchmt). 2014;23(8):675–680. doi: 10.1089/jwh.2013.4638. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib71] 71.Foster G.D., Wyatt H.R., Hill J.O., Makris A.P., Rosenbaum D.L., Brill C., et al. Weight and metabolic outcomes after 2 years on a low-carbohydrate versus low-fat diet: a randomized trial. Ann. Intern. Med. 2010;153(3):147–157. doi: 10.1059/0003-4819-153-3-201008030-00005. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib72] 72.Frisch S., Zittermann A., Berthold H.K., Gotting C., Kuhn J., Kleesiek K., et al. A randomized controlled trial on the efficacy of carbohydrate-reduced or fat-reduced diets in patients attending a telemedically guided weight loss program. Cardiovasc. Diabetol. 2009;8:36. doi: 10.1186/1475-2840-8-36. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib73] 73.Gardner C.D., Kiazand A., Alhassan S., Kim S., Stafford R.S., Balise R.R., et al. Comparison of the Atkins, Zone, Ornish, and LEARN diets for change in weight and related risk factors among overweight premenopausal women: the A TO Z Weight Loss Study: a randomized trial. JAMA. 2007;297(9):969–977. doi: 10.1001/jama.297.9.969. [DOI] [PubMed] [Google Scholar]

[bib74] 74.Gardner C.D., Offringa L.C., Hartle J.C., Kapphahn K., Cherin R. Weight loss on low-fat vs. low-carbohydrate diets by insulin resistance status among overweight adults and adults with obesity: a randomized pilot trial. Obesity (Silver Spring) 2016;24(1):79–86. doi: 10.1002/oby.21331. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib75] 75.Gardner C.D., Trepanowski J.F., Del Gobbo L.C., Hauser M.E., Rigdon J., Ioannidis J.P.A., et al. Effect of low-fat vs low-carbohydrate diet on 12-month weight loss in overweight adults and the association with genotype pattern or insulin secretion: the DIETFITS randomized clinical trial. JAMA. 2018;319(7):667–679. doi: 10.1001/jama.2018.0245. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib76] 76.Garg A., Grundy S.M., Unger R.H. Comparison of effects of high and low carbohydrate diets on plasma lipoproteins and insulin sensitivity in patients with mild NIDDM. Diabetes. 1992;41(10):1278–1285. [PubMed] [Google Scholar]

[bib77] 77.Genoni A., Lyons-Wall P., Lo J., Devine A. Cardiovascular, metabolic effects and dietary composition of ad-libitum paleolithic vs. Australian guide to healthy eating diets: a 4-week randomised trial. Nutrients. 2016;8(5):314. doi: 10.3390/nu8050314. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib78] 78.Gerhard G.T., Ahmann A., Meeuws K., McMurry M.P., Duell P.B., Connor W.E. Effects of a low-fat diet compared with those of a high-monounsaturated fat diet on body weight, plasma lipids and lipoproteins, and glycemic control in type 2 diabetes. Am. J. Clin. Nutr. 2004;80(3):668–673. doi: 10.1093/ajcn/80.3.668. [DOI] [PubMed] [Google Scholar]

[bib79] 79.Goday A., Bellido D., Sajoux I., Crujeiras A.B., Burguera B., García-Luna P.P., et al. Short-term safety, tolerability and efficacy of a very low-calorie-ketogenic diet interventional weight loss program versus hypocaloric diet in patients with type 2 diabetes mellitus. Nutr. Diabetes. 2016;6(9) [Google Scholar]

[bib80] 80.Golay A., Allaz A.F., Morel Y., de Tonnac N., Tankova S., Reaven G. Similar weight loss with low- or high-carbohydrate diets. Am. J. Clin. Nutr. 1996;63(2):174–178. doi: 10.1093/ajcn/63.2.174. [DOI] [PubMed] [Google Scholar]

[bib81] 81.Goss A.M., Gower B., Soleymani T., Stewart M., Pendergrass M., Lockhart M., et al. Effects of weight loss during a very low carbohydrate diet on specific adipose tissue depots and insulin sensitivity in older adults with obesity: a randomized clinical trial. Nutr. Metab. (Lond). 2020;17:64. doi: 10.1186/s12986-020-00481-9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib82] 82.Gram-Kampmann E.M., Hansen C.D., Hugger M.B., Jensen J.M., Brønd J.C., Hermann A.P., et al. Effects of a 6-month, low-carbohydrate diet on glycaemic control, body composition, and cardiovascular risk factors in patients with type 2 diabetes: an open-label randomized controlled trial. Diabetes Obes. Metab. 2022;24(4):693–703. doi: 10.1111/dom.14633. [DOI] [PubMed] [Google Scholar]

[bib83] 83.Gram-Kampmann E.M., Olesen T.B., Hansen C.D., Hugger M.B., Jensen J.M., Handberg A., et al. A six-month low-carbohydrate diet high in fat does not adversely affect endothelial function or markers of low-grade inflammation in patients with type 2 diabetes: an open-label randomized controlled trial. Cardiovasc. Diabetol. 2023;22(1):212. doi: 10.1186/s12933-023-01956-8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib84] 84.Guay V., Lamarche B., Charest A., Tremblay A.J., Couture P. Effect of short-term low- and high-fat diets on low-density lipoprotein particle size in normolipidemic subjects. Metabolism. 2012;61(1):76–83. doi: 10.1016/j.metabol.2011.06.002. [DOI] [PubMed] [Google Scholar]

[bib85] 85.Guevara-Cruz M., Hernández-Gómez K.G., Condado-Huerta C., González-Salazar L.E., Peña-Flores A.K., Pichardo-Ontiveros E., et al. Intermittent fasting, calorie restriction, and a ketogenic diet improve mitochondrial function by reducing lipopolysaccharide signaling in monocytes during obesity: a randomized clinical trial. Clin. Nutr. 2024;43(8):1914–1928. doi: 10.1016/j.clnu.2024.06.036. [DOI] [PubMed] [Google Scholar]

[bib86] 86.Guldbrand H., Dizdar B., Bunjaku B., Lindström T., Bachrach-Lindström M., Fredrikson M., et al. In type 2 diabetes, randomisation to advice to follow a low-carbohydrate diet transiently improves glycaemic control compared with advice to follow a low-fat diet producing a similar weight loss. Diabetologia. 2012;55(8):2118–2127. doi: 10.1007/s00125-012-2567-4. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib87] 87.Guo H., Wang L., Huang X., Shen F., Lu Y., Zhang P. Effects of low-carbohydrate vs low-fat diets on weight loss and metabolic risk factors in obese/overweight individuals with impaired glucose regulation: a randomized controlled trial, Asia Pac. J. Clin. Nutr. 2022;31(3):512–519. [Google Scholar]

[bib88] 88.Haji-Ghazi Tehrani L., Mousavi S.N., Chiti H., Afshar D. Effect of Atkins versus a low-fat diet on gut microbiota, and cardiometabolic markers in obese women following an energy-restricted diet: randomized, crossover trial. Nutr. Metab. Cardiovasc. Dis. 2022;32(7):1734–1741. doi: 10.1016/j.numecd.2022.04.007. [DOI] [PubMed] [Google Scholar]

[bib89] 89.Hansen C.D., Gram-Kampmann E.M., Hansen J.K., Hugger M.B., Madsen B.S., Jensen J.M., et al. Effect of calorie-unrestricted low-carbohydrate, high-fat diet versus high-carbohydrate, low-fat diet on type 2 diabetes and nonalcoholic fatty liver disease: a randomized controlled trial. Ann. Intern. Med. 2023;176(1):10–21. doi: 10.7326/M22-1787. [DOI] [PubMed] [Google Scholar]

[bib90] 90.Harvey C., Schofield G.M., Zinn C., Thornley S.J., Crofts C., Merien F.L.R. Low-carbohydrate diets differing in carbohydrate restriction improve cardiometabolic and anthropometric markers in healthy adults: a randomised clinical trial. PeerJ. 2019;7 [Google Scholar]

[bib91] 91.Haufe S., Engeli S., Kast P., Böhnke J., Utz W., Haas V., et al. Randomized comparison of reduced fat and reduced carbohydrate hypocaloric diets on intrahepatic fat in overweight and obese human subjects. Hepatology. 2011;53(5):1504–1514. doi: 10.1002/hep.24242. [DOI] [PubMed] [Google Scholar]

[bib92] 92.Haufe S., Utz W., Engeli S., Kast P., Böhnke J., Pofahl M., et al. Left ventricular mass and function with reduced-fat or reduced-carbohydrate hypocaloric diets in overweight and obese subjects. Hypertension. 2012;59(1):70–75. doi: 10.1161/HYPERTENSIONAHA.111.178616. [DOI] [PubMed] [Google Scholar]

[bib93] 93.He M., Wang J., Liang Q., Li M., Guo H., Wang Y., et al. Time-restricted eating with or without low-carbohydrate diet reduces visceral fat and improves metabolic syndrome: a randomized trial, Cell Rep. Med. 2022;3(10) [Google Scholar]

[bib94] 94.Holmer M., Lindqvist C., Petersson S., Moshtaghi-Svensson J., Tillander V., Brismar T.B., et al. Treatment of NAFLD with intermittent calorie restriction or low-carb high-fat diet—a randomised controlled trial. JHEP Rep. 2021;3(3) [Google Scholar]

[bib95] 95.Hu T., Yao L., Reynolds K., Whelton P.K., Niu T., Li S., et al. The effects of a low-carbohydrate diet vs. a low-fat diet on novel cardiovascular risk factors: a randomized controlled trial. Nutrients. 2015;7(9):7978–7994. doi: 10.3390/nu7095377. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib96] 96.Hyde P.N., Sapper T.N., LaFountain R.A., Kackley M.L., Buga A., Fell B., et al. Effects of palm stearin versus butter in the context of low-carbohydrate/high-fat and high-carbohydrate/low-fat diets on circulating lipids in a controlled feeding study in healthy humans. Nutrients. 2021;13(6):1944. doi: 10.3390/nu13061944. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib97] 97.Jenkins D.J.A., Wong J.M.W., Kendall C.W.C., Esfahani A., Ng V.W.Y., Leong T.C.K., et al. Effect of a 6-month vegan low-carbohydrate ('Eco-Atkins') diet on cardiovascular risk factors and body weight in hyperlipidaemic adults: a randomised controlled trial. BMJ Open. 2014;4(2) [Google Scholar]

[bib98] 98.Jeppesen J., Schaaf P., Jones C., Zhou M.Y., Chen Y.D., Reaven G.M. Effects of low-fat, high-carbohydrate diets on risk factors for ischemic heart disease in postmenopausal women. Am. J. Clin. Nutr. 1997;65(4):1027–1033. doi: 10.1093/ajcn/65.4.1027. [DOI] [PubMed] [Google Scholar]

[bib99] 99.Jönsson T., Granfeldt Y., Ahrén B., Branell U.C., Pålsson G., Hansson A., et al. Beneficial effects of a Paleolithic diet on cardiovascular risk factors in type 2 diabetes: a randomized cross-over pilot study. Cardiovasc. Diabetol. 2009;8:35. doi: 10.1186/1475-2840-8-35. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib100] 100.Keogh J.B., Brinkworth G.D., Clifton P.M. Effects of weight loss on a low-carbohydrate diet on flow-mediated dilatation, adhesion molecules and adiponectin. Br. J. Nutr. 2007;98(4):852–859. doi: 10.1017/S0007114507747815. [DOI] [PubMed] [Google Scholar]

[bib101] 101.Kikuchi T., Kushiyama A., Yanai M., Kashiwado C., Seto T., Kasuga M. Comparison of weight reduction, change in parameters and safety of a very low carbohydrate diet in comparison to a low carbohydrate diet in obese Japanese subjects with metabolic disorders. Nutrients. 2023;15(6):1342. doi: 10.3390/nu15061342. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib102] 102.Kitabchi A.E., McDaniel K.A., Wan J.Y., Tylavsky F.A., Jacovino C.A., Sands C.W., et al. Effects of high-protein versus high-carbohydrate diets on markers of β-cell function, oxidative stress, lipid peroxidation, proinflammatory cytokines, and adipokines in obese, premenopausal women without diabetes: a randomized controlled trial. Diabetes Care. 2013;36(7):1919–1925. doi: 10.2337/dc12-1912. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib103] 103.Kleiner R.E., Hutchins A.M., Johnston C.S., Swan P.D. Effects of an 8-week high-protein or high-carbohydrate diet in adults with hyperinsulinemia. MedGenMed. 2006;8(4):39. [Google Scholar]

[bib104] 104.Kleissl-Muir S., Owen A., Rasmussen B., Zinn C., Driscoll A. Effects of a low carbohydrate diet on heart failure symptoms and quality of life in patients with diabetic cardiomyopathy: a randomised controlled trial pilot study. Nutr. Metab. Cardiovasc. Dis. 2023;33(12):2455–2463. doi: 10.1016/j.numecd.2023.08.015. [DOI] [PubMed] [Google Scholar]

[bib105] 105.Krauss R.M., Blanche P.J., Rawlings R.S., Fernstrom H.S., Williams P.T. Separate effects of reduced carbohydrate intake and weight loss on atherogenic dyslipidemia. Am. J. Clin. Nutr. 2006;83(5):1025–1031. doi: 10.1093/ajcn/83.5.1025. quiz 205. [DOI] [PubMed] [Google Scholar]

[bib106] 106.Krebs J.D., Elley C.R., Parry-Strong A., Lunt H., Drury P.L., Bell D.A., et al. The Diabetes Excess Weight Loss (DEWL) Trial: a randomised controlled trial of high-protein versus high-carbohydrate diets over 2 years in type 2 diabetes. Diabetologia. 2012;55(4):905–914. doi: 10.1007/s00125-012-2461-0. [DOI] [PubMed] [Google Scholar]

[bib107] 107.Krebs J.D., Strong A.P., Cresswell P., Reynolds A.N., Hanna A., Haeusler S. A randomised trial of the feasibility of a low carbohydrate diet vs standard carbohydrate counting in adults with type 1 diabetes taking body weight into account. Asia Pac. J. Clin. Nutr. 2016;25(1):78–84. doi: 10.6133/apjcn.2016.25.1.11. [DOI] [PubMed] [Google Scholar]

[bib108] 108.Lambadiari V., Katsimbri P., Kountouri A., Korakas E., Papathanasi A., Maratou E., et al. The effect of a ketogenic diet versus Mediterranean diet on clinical and biochemical markers of inflammation in patients with obesity and psoriatic arthritis: a randomized crossover trial. Int. J. Mol. Sci. 2024;25(5):2475. doi: 10.3390/ijms25052475. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib109] 109.Le T., Flatt S.W., Natarajan L., Pakiz B., Quintana E.L., Heath D.D., et al. Effects of diet composition and insulin resistance status on plasma lipid levels in a weight loss intervention in women. J. Am. Heart Assoc. 2016;5(1) [Google Scholar]

[bib110] 110.Lean M.E.J., Han T.S., Prvan T., Richmond P.R., Avenell A. Weight loss with high and low carbohydrate 1200 kcal diets in free living women. Eur. J. Clin. Nutr. 1997;51(4):243–248. doi: 10.1038/sj.ejcn.1600391. [DOI] [PubMed] [Google Scholar]

[bib111] 111.Li S., Lin G., Chen J., Chen Z., Xu F., Zhu F., et al. The effect of periodic ketogenic diet on newly diagnosed overweight or obese patients with type 2 diabetes. BMC Endocr. Disord. 2022;22(1):34. doi: 10.1186/s12902-022-00947-2. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib112] 112.Lim S.S., Noakes M., Keogh J.B., Clifton P.M. Long-term effects of a low carbohydrate, low fat or high unsaturated fat diet compared to a no-intervention control. Nutr. Metab. Cardiovasc. Dis. 2010;20(8):599–607. doi: 10.1016/j.numecd.2009.05.003. [DOI] [PubMed] [Google Scholar]

[bib113] 113.Liu X., Zhang G., Ye X., Li H., Chen X., Tang L., et al. Effects of a low-carbohydrate diet on weight loss and cardiometabolic profile in Chinese women: a randomised controlled feeding trial. Br. J. Nutr. 2013;110(8):1444–1453. doi: 10.1017/S0007114513000640. [DOI] [PubMed] [Google Scholar]

[bib114] 114.Liu K., Wang B., Zhou R., Lang H.D., Ran L., Wang J., et al. Effect of combined use of a low-carbohydrate, high-protein diet with omega-3 polyunsaturated fatty acid supplementation on glycemic control in newly diagnosed type 2 diabetes: a randomized, double-blind, parallel-controlled trial. Am. J. Clin. Nutr. 2018;108(2):256–265. doi: 10.1093/ajcn/nqy120. [DOI] [PubMed] [Google Scholar]

[bib115] 115.London A., Richter M.M., Sjøberg K.A., Wewer Albrechtsen N.J., Považan M., Drici L., et al. The impact of short-term eucaloric low- and high-carbohydrate diets on liver triacylglycerol content in males with overweight and obesity: a randomized crossover study. Am. J. Clin. Nutr. 2024;120(2):283–293. doi: 10.1016/j.ajcnut.2024.06.006. [DOI] [PubMed] [Google Scholar]

[bib116] 116.Luong T.V., Pedersen M.G.B., Abild C.B., Lauritsen K.M., Kjærulff M.L.G., Møller N., et al. A 3-week ketogenic diet increases skeletal muscle insulin sensitivity in individuals with obesity: a randomized controlled crossover trial. Diabetes. 2024;73(10):1631–1640. doi: 10.2337/db24-0162. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib117] 117.Martins C., Bryan D.R., Sweatt S.K., Garvey W.T., Fontaine K.R., Dutton G.R., et al. The impact of a low increases skeletal muscle insulin sensitivity in individuals with obesity: a randomized controlled crossovert. Obesity (Silver Spring) 2025;33(2):257–266. doi: 10.1002/oby.24201. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib118] 118.McAuley K.A., Hopkins C.M., Smith K.J., McLay R.T., Williams S.M., Taylor R.W., et al. Comparison of high-fat and high-protein diets with a high-carbohydrate diet in insulin-resistant obese women. Diabetologia. 2005;48(1):8–16. doi: 10.1007/s00125-004-1603-4. [DOI] [PubMed] [Google Scholar]

[bib119] 119.McCullough D., Harrison T., Boddy L.M., Enright K.J., Amirabdollahian F., Schmidt M.A., et al. The effect of dietary carbohydrate and fat manipulation on the metabolome and markers of glucose and insulin metabolism: a randomised parallel trial. Nutrients. 2022;14(18):3691. doi: 10.3390/nu14183691. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib120] 120.McMillan-Price J., Petocz P., Atkinson F., O'Neill K., Samman S., Steinbeck K., et al. Comparison of 4 diets of varying glycemic load on weight loss and cardiovascular risk reduction in overweight and obese young adults: a randomized controlled trial. Arch. Intern. Med. 2006;166(14):1466–1475. doi: 10.1001/archinte.166.14.1466. [DOI] [PubMed] [Google Scholar]

[bib121] 121.Meckling K.A., O'Sullivan C., Saari D. Comparison of a low-fat diet to a low-carbohydrate diet on weight loss, body composition, and risk factors for diabetes and cardiovascular disease in free-living, overweight men and women. J. Clin. Endocrinol. Metab. 2004;89(6):2717–2723. doi: 10.1210/jc.2003-031606. [DOI] [PubMed] [Google Scholar]

[bib122] 122.Meckling K.A., Sherfey R. A randomized trial of a hypocaloric high-protein diet, with and without exercise, on weight loss, fitness, and markers of the Metabolic Syndrome in overweight and obese women. Appl. Physiol. Nutr. Metab. 2007;32(4):743–752. doi: 10.1139/H07-059. [DOI] [PubMed] [Google Scholar]

[bib123] 123.Meksawan K., Pendergast D.R., Leddy J.J., Mason M., Horvath P.J., Awad A.B. Effect of low and high fat diets on nutrient intakes and selected cardiovascular risk factors in sedentary men and women. J. Am. Coll. Nutr. 2004;23(2):131–140. doi: 10.1080/07315724.2004.10719353. [DOI] [PubMed] [Google Scholar]

[bib124] 124.Mellberg C., Sandberg S., Ryberg M., Eriksson M., Brage S., Larsson C., et al. Long-term effects of a Palaeolithic-type diet in obese postmenopausal women: a 2-year randomized trial. Eur. J. Clin. Nutr. 2014;68(3):350–357. doi: 10.1038/ejcn.2013.290. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib125] 125.Merovci A., Finley B., Hansis-Diarte A., Neppala S., Abdul-Ghani M.A., Cersosimo E., et al. Effect of weight-maintaining ketogenic diet on glycemic control and insulin sensitivity in obese T2D subjects. BMJ Open Diabetes Res. Care. 2024;12(5) [Google Scholar]

[bib126] 126.Michalczyk M.M., Klonek G., Maszczyk A., Zajac A. The effects of a low calorie ketogenic diet on glycaemic control variables in hyperinsulinemic overweight/obese females. Nutrients. 2020;12(6):1854. doi: 10.3390/nu12061854. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib127] 127.Michalczyk M.M., Maszczyk A., Stastny P. The effects of low-energy moderate-carbohydrate (MCD) and mixed (MixD) diets on serum lipid profiles and body composition in middle-aged men: a randomized controlled parallel-group clinical trial. Int. J. Environ. Res. Public Health. 2020;17(4):1332. doi: 10.3390/ijerph17041332. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib128] 128.Michalopoulou M., Jebb S.A., MacKillop L.H., Dyson P., Hirst J.E., Zhu S., et al. REduced-Carbohydrate intervention for managing Obesity and Reduction of gestational Diabetes (RECORD): a randomized controlled feasibility trial. Diabetes Obes. Metab. 2024;26(4):1407–1420. doi: 10.1111/dom.15442. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib129] 129.Moreno B., Bellido D., Sajoux I., Goday A., Saavedra D., Crujeiras A.B., et al. Comparison of a very low-calorie-ketogenic diet with a standard low-calorie diet in the treatment of obesity. Endocrine. 2014;47(3):793–805. doi: 10.1007/s12020-014-0192-3. [DOI] [PubMed] [Google Scholar]

[bib130] 130.Morgan S.A., O'Dea K., Sinclair A.J. A low-fat diet supplemented with monounsaturated fat results in less HDL-C lowering than a very-low-fat diet. J. Am. Diet. Assoc. 1997;97(2):151–156. doi: 10.1016/S0002-8223(97)00770-0. [DOI] [PubMed] [Google Scholar]

[bib131] 131.Morris E., Aveyard P., Dyson P., Noreik M., Bailey C., Fox R., et al. A food-based, low-energy, low-carbohydrate diet for people with type 2 diabetes in primary care: a randomized controlled feasibility trial. Diabetes Obes. Metab. 2020;22(4):512–520. doi: 10.1111/dom.13915. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib132] 132.Mousavi S.M., Ejtahed H.S., Marvasti F.E., Taghavi M., Siadat S.D., Hasani-Ranjbar S., et al. The effect of a moderately restricted carbohydrate diet on cardiometabolic risk factors in overweight and obese women with metabolic syndrome: a randomized controlled trial. Clin. Ther. 2023;45(3):e103–e114. doi: 10.1016/j.clinthera.2023.02.002. [DOI] [PubMed] [Google Scholar]

[bib133] 133.Noakes M., Keogh J.B., Foster P.R., Clifton P.M. Effect of an energy-restricted, high-protein, low-fat diet relative to a conventional high-carbohydrate, low-fat diet on weight loss, body composition, nutritional status, and markers of cardiovascular health in obese women. Am. J. Clin. Nutr. 2005;81(6):1298–1306. doi: 10.1093/ajcn/81.6.1298. [DOI] [PubMed] [Google Scholar]

[bib134] 134.Numao S., Kawano H., Endo N., Yamada Y., Konishi M., Takahashi M., et al. Effects of a single bout of aerobic exercise on short-term low-carbohydrate/high-fat intake-induced postprandial glucose metabolism during an oral glucose tolerance test. Metabolism. 2013;62(10):1406–1415. doi: 10.1016/j.metabol.2013.05.005. [DOI] [PubMed] [Google Scholar]

[bib135] 135.Appel L.J., Sacks F.M., Carey V.J., Obarzanek E., Swain J.F., Miller E.R., et al. Effects of protein, monounsaturated fat, and carbohydrate intake on blood pressure and serum lipids: results of the OmniHeart randomized trial. JAMA. 2005;294(19):2455–2464. doi: 10.1001/jama.294.19.2455. [DOI] [PubMed] [Google Scholar]

[bib136] 136.Otten J., Mellberg C., Ryberg M., Sandberg S., Kullberg J., Lindahl B., et al. Strong and persistent effect on liver fat with a Paleolithic diet during a two-year intervention. Int. J. Obes. (Lond). 2016;40(5):747–753. doi: 10.1038/ijo.2016.4. [DOI] [PubMed] [Google Scholar]

[bib137] 137.Parr E.B., Coffey V.G., Cato L.E., Phillips S.M., Burke L.M., Hawley J.A. A randomized trial of high-dairy-protein, variable-carbohydrate diets and exercise on body composition in adults with obesity. Obesity (Silver Spring) 2016;24(5):1035–1045. doi: 10.1002/oby.21451. [DOI] [PubMed] [Google Scholar]

[bib138] 138.Perissiou M., Borkoles E., Kobayashi K., Polman R. The effect of an 8 week prescribed exercise and low-carbohydrate diet on cardiorespiratory fitness, body composition and cardiometabolic risk factors in obese individuals: a randomised controlled trial. Nutrients. 2020;12(2):482. doi: 10.3390/nu12020482. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib139] 139.Peterson C.M., Jovanovic-Peterson L. Randomized crossover study of 40% vs. 55% carbohydrate weight loss strategies in women with previous gestational diabetes mellitus and non-diabetic women of 130-200% ideal body weight. J. Am. Coll. Nutr. 1995;14(4):369–375. doi: 10.1080/07315724.1995.10718523. [DOI] [PubMed] [Google Scholar]

[bib140] 140.Pinsawas B., Surawit A., Mongkolsucharitkul P., Pongkunakorn T., Suta S., Manosan T., et al. Asian low-carbohydrate diet with increased whole egg consumption improves metabolic outcomes in metabolic syndrome: a 52-week intervention study. J. Nutr. 2024;154(11):3331–3345. doi: 10.1016/j.tjnut.2024.08.027. [DOI] [PubMed] [Google Scholar]

[bib141] 141.Rajaie S., Azadbakht L., Saneei P., Khazaei M., Esmaillzadeh A. Comparative effects of carbohydrate versus fat restriction on serum levels of adipocytokines, markers of inflammation, and endothelial function among women with the metabolic syndrome: a randomized cross-over clinical trial. Ann. Nutr. Metab. 2013;63(1-2):159–167. doi: 10.1159/000354868. [DOI] [PubMed] [Google Scholar]

[bib142] 142.Ranjan A., Schmidt S., Damm-Frydenberg C., Holst J.J., Madsbad S., Nørgaard K. Short-term effects of a low carbohydrate diet on glycaemic variables and cardiovascular risk markers in patients with type 1 diabetes: a randomized open-label crossover trial. Diabetes Obes. Metab. 2017;19(10):1479–1484. doi: 10.1111/dom.12953. [DOI] [PubMed] [Google Scholar]

[bib143] 143.Raygan F., Bahmani F., Kouchaki E., Aghadavod E., Sharifi S., Akbari E., et al. Comparative effects of carbohydrate versus fat restriction on metabolic profiles, biomarkers of inflammation and oxidative stress in overweight patients with Type 2 diabetic and coronary heart disease: a randomized clinical trial. ARYA Atheroscler. 2016;12(6):266–273. [PMC free article] [PubMed] [Google Scholar]

[bib144] 144.Retterstol K., Svendsen M., Narverud I., Holven K.B. Effect of low carbohydrate high fat diet on LDL cholesterol and gene expression in normal-weight, young adults: a randomized controlled study. Atherosclerosis. 2018;279:52–61. doi: 10.1016/j.atherosclerosis.2018.10.013. [DOI] [PubMed] [Google Scholar]

[bib145] 145.Rodríguez-Villar C., Pérez-Heras A., Mercadé I., Casals E., Ros E. Comparison of a high-carbohydrate and a high-monounsaturated fat, olive oil-rich diet on the susceptibility of LDL to oxidative modification in subjects with type 2 diabetes mellitus. Diabet. Med. 2004;21(2):142–149. doi: 10.1046/j.1464-5491.2003.01086.x. [DOI] [PubMed] [Google Scholar]

[bib146] 146.Röhling M., Kempf K., Banzer W., Berg A., Braumann K.M., Tan S., et al. Prediabetes conversion to normoglycemia is superior adding a low-carbohydrate and energy deficit formula diet to lifestyle intervention—a 12-month subanalysis of the ACOORH trial. Nutrients. 2020;12(7):2022. doi: 10.3390/nu12072022. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib147] 147.Ruth M.R., Port A.M., Shah M., Bourland A.C., Istfan N.W., Nelson K.P., et al. Consuming a hypocaloric high fat low carbohydrate diet for 12 weeks lowers C-reactive protein, and raises serum adiponectin and high density lipoprotein-cholesterol in obese subjects. Metabolism. 2013;62(12):1779–1787. doi: 10.1016/j.metabol.2013.07.006. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib148] 148.Sacks F.M., Carey V.J., Anderson C.A., Miller E.R., 3rd, Copeland T., Charleston J., et al. Effects of high vs low glycemic index of dietary carbohydrate on cardiovascular disease risk factors and insulin sensitivity: the OmniCarb randomized clinical trial. JAMA. 2014;312(23):2531–2541. doi: 10.1001/jama.2014.16658. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib149] 149.Samaha F.F., Iqbal N., Seshadri P., Chicano K.L., Daily D.A., McGrory J., et al. A low-carbohydrate as compared with a low-fat diet in severe obesity. N. Engl. J. Med. 2003;348(21):2074–2081. doi: 10.1056/NEJMoa022637. [DOI] [PubMed] [Google Scholar]

[bib150] 150.Sargrad K.R., Homko C., Mozzoli M., Boden G. Effect of high protein vs high carbohydrate intake on insulin sensitivity, body weight, hemoglobin A1c, and blood pressure in patients with type 2 diabetes mellitus. J. Am. Diet. Assoc. 2005;105(4):573–580. doi: 10.1016/j.jada.2005.01.009. [DOI] [PubMed] [Google Scholar]

[bib151] 151.Saslow L.R., Daubenmier J.J., Moskowitz J.T., Kim S., Murphy E.J., Phinney S.D., et al. Twelve-month outcomes of a randomized trial of a moderate-carbohydrate versus very low-carbohydrate diet in overweight adults with type 2 diabetes mellitus or prediabetes. Nutr. Diabetes. 2017;7(12):304. doi: 10.1038/s41387-017-0006-9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib152] 152.Saslow L.R., Jones L.M., Sen A., Wolfson J.A., Diez H.L., O’Brien A., et al. Comparing very low-carbohydrate vs DASH diets for overweight or obese adults with hypertension and prediabetes or type 2 diabetes: a randomized trial. Ann. Fam. Med. 2023;21(3):256–263. doi: 10.1370/afm.2968. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib153] 153.Saslow L.R., Kim S., Daubenmier J.J., Moskowitz J.T., Phinney S.D., Goldman V., et al. A randomized pilot trial of a moderate carbohydrate diet compared to a very low carbohydrate diet in overweight or obese individuals with type 2 diabetes mellitus or prediabetes. PLOS ONE. 2014;9(4) [Google Scholar]

[bib154] 154.Segal-Isaacson C.J., Johnson S., Tomuta V., Cowell B., Stein D.T. A randomized trial comparing low-fat and low-carbohydrate diets matched for energy and protein. Obes. Res. 2004;12(Suppl 2):130S–140S. doi: 10.1038/oby.2004.278. [DOI] [PubMed] [Google Scholar]

[bib155] 155.Seshadri P., Iqbal N., Stern L., Williams M., Chicano K.L., Daily D.A., et al. A randomized study comparing the effects of a low-carbohydrate diet and a conventional diet on lipoprotein subfractions and C-reactive protein levels in patients with severe obesity. Am. J. Med. 2004;117(6):398–405. doi: 10.1016/j.amjmed.2004.04.009. [DOI] [PubMed] [Google Scholar]

[bib156] 156.Sharman M.J., Gómez A.L., Kraemer W.J., Volek J.S. Very low-carbohydrate and low-fat diets affect fasting lipids and postprandial lipemia differently in overweight men. J. Nutr. 2004;134(4):880–885. doi: 10.1093/jn/134.4.880. [DOI] [PubMed] [Google Scholar]

[bib157] 157.Skytte M.J., Samkani A., Petersen A.D., Thomsen M.N., Astrup A., Chabanova E., et al. A carbohydrate-reduced high-protein diet improves HbA 1c and liver fat content in weight stable participants with type 2 diabetes: a randomised controlled trial. Diabetologia. 2019;62(11):2066–2078. doi: 10.1007/s00125-019-4956-4. [DOI] [PubMed] [Google Scholar]

[bib158] 158.Stern L., Iqbal N., Seshadri P., Chicano K.L., Daily D.A., McGrory J., et al. The effects of low-carbohydrate versus conventional weight loss diets in severely obese adults: one-year follow-up of a randomized trial. Ann. Intern. Med. 2004;140(10):778–785. doi: 10.7326/0003-4819-140-10-200405180-00007. [DOI] [PubMed] [Google Scholar]

[bib159] 159.Stoernell C.K., Tangney C.C., Rockway S.W. Short-term changes in lipoprotein subclasses and C-reactive protein levels of hypertriglyceridemic adults on low-carbohydrate and low-fat diets. Nutr. Res. 2008;28(7):443–449. doi: 10.1016/j.nutres.2008.03.013. [DOI] [PubMed] [Google Scholar]

[bib160] 160.Sun S., Kong Z., Shi Q., Hu M., Zhang H., Zhang D., et al. Non-energy-restricted low-carbohydrate diet combined with exercise intervention improved cardiometabolic health in overweight Chinese females. Nutrients. 2019;11(12):3051. doi: 10.3390/nu11123051. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib161] 161.Sun J., Ruan Y., Xu N., Wu P., Lin N., Yuan K., et al. The effect of dietary carbohydrate and calorie restriction on weight and metabolic health in overweight/obese individuals: a multi-center randomized controlled trial. BMC Med. 2023;21(1):192. doi: 10.1186/s12916-023-02869-9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib162] 162.Tay J., Brinkworth G.D., Noakes M., Keogh J., Clifton P.M. Metabolic effects of weight loss on a very-low-carbohydrate diet compared with an isocaloric high-carbohydrate diet in abdominally obese subjects. J. Am. Coll. Cardiol. 2008;51(1):59–67. doi: 10.1016/j.jacc.2007.08.050. [DOI] [PubMed] [Google Scholar]

[bib163] 163.Tay J., Luscombe-Marsh N., Thompson C., Noakes M., Buckley J., Wittert G., et al. Long-term effects of a low carbohydrate, low saturated fat diet versus a conventional high carbohydrate, low fat diet in type 2 diabetes: a randomised trial. Diabetes Res. Clin. Pract. 2014;106:S34. [Google Scholar]

[bib164] 164.Tay J., Luscombe-Marsh N.D., Thompson C.H., Noakes M., Buckley J.D., Wittert G.A., et al. A very low-carbohydrate, low–saturated fat diet for type 2 diabetes management: a randomized trial. Diabetes Care. 2014;37(11):2909–2918. doi: 10.2337/dc14-0845. [DOI] [PubMed] [Google Scholar]

[bib165] 165.Tay J., Luscombe-Marsh N.D., Thompson C.H., Noakes M., Buckley J.D., Wittert G.A., et al. Comparison of low- and high-carbohydrate diets for type 2 diabetes management: a randomized trial. Am. J. Clin. Nutr. 2015;102(4):780–790. doi: 10.3945/ajcn.115.112581. [DOI] [PubMed] [Google Scholar]

[bib166] 166.Tay J., Thompson C.H., Luscombe-Marsh N.D., Wycherley T.P., Noakes M., Buckley J.D., et al. Effects of an energy-restricted low-carbohydrate, high unsaturated fat/low saturated fat diet versus a high-carbohydrate, low-fat diet in type 2 diabetes: a 2-year randomized clinical trial. Diabetes Obes. Metab. 2018;20(4):858–871. doi: 10.1111/dom.13164. [DOI] [PubMed] [Google Scholar]

[bib167] 167.Teng K.T., Chang L.F., Vethakkan S.R., Nesaretnam K., Sanders T.A.B. Effects of exchanging carbohydrate or monounsaturated fat with saturated fat on inflammatory and thrombogenic responses in subjects with abdominal obesity: a randomized controlled trial. Clin. Nutr. 2017;36(5):1250–1258. doi: 10.1016/j.clnu.2016.08.026. [DOI] [PubMed] [Google Scholar]

[bib168] 168.Thomsen M.N., Skytte M.J., Samkani A., Carl M.H., Weber P., Astrup A., et al. Dietary carbohydrate restriction augments weight loss-induced improvements in glycaemic control and liver fat in individuals with type 2 diabetes: a randomised controlled trial. Diabetologia. 2022;65(3):506–517. doi: 10.1007/s00125-021-05628-8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib169] 169.Thomsen M.N., Skytte M.J., Samkani A., Weber P., Fenger M., Frystyk J., et al. Replacing dietary carbohydrate with protein and fat improves lipoprotein subclass profile and liver fat in type 2 diabetes independent of body weight: evidence from 2 randomized controlled trials. Am. J. Clin. Nutr. 2025;121(2):224–231. doi: 10.1016/j.ajcnut.2024.11.030. [DOI] [PubMed] [Google Scholar]

[bib170] 170.Thomson C.A., Stopeck A.T., Bea J.W., Cussler E., Nardi E., Frey G., et al. Changes in body weight and metabolic indexes in overweight breast cancer survivors enrolled in a randomized trial of low-fat vs. reduced carbohydrate diets. Nutr. Cancer. 2010;62(8):1142–1152. doi: 10.1080/01635581.2010.513803. [DOI] [PubMed] [Google Scholar]

[bib171] 171.Thorning T.K., Raziani F., Bendsen N.T., Astrup A., Tholstrup T., Raben A. Diets with high-fat cheese, high-fat meat, or carbohydrate on cardiovascular risk markers in overweight postmenopausal women: a randomized crossover trial. Am. J. Clin. Nutr. 2015;102(3):573–581. doi: 10.3945/ajcn.115.109116. [DOI] [PubMed] [Google Scholar]

[bib172] 172.Turton J.L., Brinkworth G.D., Parker H.M., Lim D., Lee K., Rush A., et al. Effects of a low-carbohydrate diet in adults with type 1 diabetes management: a single arm non-randomised clinical trial. PLOS ONE. 2023;18(7) [Google Scholar]

[bib173] 173.Tzenios N., Lewis E.D., Crowley D.C., Chahine M., Evans M. Examining the efficacy of a very-low-carbohydrate ketogenic diet on cardiovascular health in adults with mildly elevated low-density lipoprotein cholesterol in an open-label pilot study. Metab. Syndr. Relat. Disord. 2022;20(2):94–103. doi: 10.1089/met.2021.0042. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib174] 174.Valsdottir T.D., Øvrebø B., Falck T.M., Litleskare S., Johansen E.I., Henriksen C., et al. Low-carbohydrate high-fat diet and exercise: effect of a 10-week intervention on body composition and CVD risk factors in overweight and obese women-a randomized controlled trial. Nutrients. 2020;13(1):110. doi: 10.3390/nu13010110. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib175] 175.Valsdottir T.D., Øvrebø B., Kornfeldt T.M., Litleskare S., Johansen E.I., Henriksen C., et al. Effect of aerobic exercise and low-carbohydrate high-fat diet on glucose tolerance and android/gynoid fat in overweight/obese women: a randomized controlled trial. Front. Physiol. 2023;14 [Google Scholar]

[bib176] 176.Veum V.L., Laupsa-Borge J., Eng Ø., Rostrup E., Larsen T.H., Nordrehaug J.E., et al. Visceral adiposity and metabolic syndrome after very high–fat and low-fat isocaloric diets: a randomized controlled trial. Am. J. Clin. Nutr. 2017;105(1):85–99. doi: 10.3945/ajcn.115.123463. [DOI] [PubMed] [Google Scholar]

[bib177] 177.Volek J.S., Sharman M.J., Gómez A.L., DiPasquale C., Roti M., Pumerantz A., et al. Comparison of a very low-carbohydrate and low-fat diet on fasting lipids, LDL subclasses, insulin resistance, and postprandial lipemic responses in overweight women. J. Am. Coll. Nutr. 2004;23(2):177–184. doi: 10.1080/07315724.2004.10719359. [DOI] [PubMed] [Google Scholar]

[bib178] 178.Wachsmuth N.B., Aberer F., Haupt S., Schierbauer J.R., Zimmer R.T., Eckstein M.L., et al. The impact of a high-carbohydrate/low fat vs. low-carbohydrate diet on performance and body composition in physically active adults: a cross-over controlled trial. Nutrients. 2022;14(3):423. doi: 10.3390/nu14030423. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib179] 179.Wan Y., Wang F., Yuan J., Li J., Jiang D., Zhang J., et al. Effects of macronutrient distribution on weight and related cardiometabolic profile in healthy non-obese Chinese: a 6-month, randomized controlled-feeding trial. EBioMedicine. 2017;22:200–207. doi: 10.1016/j.ebiom.2017.06.017. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib180] 180.Weber P., Thomsen M.N., Skytte M.J., Samkani A., Carl M.H., Astrup A., et al. Effects of carbohydrate restriction on body weight and glycemic control in individuals with type 2 diabetes: a randomized controlled trial of efficacy in real-life settings. Nutrients. 2022;14(24):5244. doi: 10.3390/nu14245244. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib181] 181.Wekesa A.L., Doyle L.M., Fitzmaurice D., O'Donovan O., Phelan J.P., Ross M.D., et al. Influence of a low-carbohydrate diet on endothelial microvesicles in overweight women. Appl. Physiol. Nutr. Metab. 2016;41(5):522–527. doi: 10.1139/apnm-2015-0507. [DOI] [PubMed] [Google Scholar]

[bib182] 182.Wolever T.M., Gibbs A.L., Mehling C., Chiasson J.L., Connelly P.W., Josse R.G., et al. The Canadian Trial of Carbohydrates in Diabetes (CCD), a 1-y controlled trial of low-glycemic-index dietary carbohydrate in type 2 diabetes: no effect on glycated hemoglobin but reduction in C-reactive protein. Am. J. Clin. Nutr. 2008;87(1):114–125. doi: 10.1093/ajcn/87.1.114. [DOI] [PubMed] [Google Scholar]

[bib183] 183.Wycherley T.P., Brinkworth G.D., Keogh J.B., Noakes M., Buckley J.D., Clifton P.M. Long-term effects of weight loss with a very low carbohydrate and low fat diet on vascular function in overweight and obese patients. J. Intern. Med. 2010;267(5):452–461. doi: 10.1111/j.1365-2796.2009.02174.x. [DOI] [PubMed] [Google Scholar]

[bib184] 184.Wycherley T.P., Thompson C.H., Buckley J.D., Luscombe-Marsh N.D., Noakes M., Wittert G.A., et al. Long-term effects of weight loss with a very-low carbohydrate, low saturated fat diet on flow mediated dilatation in patients with type 2 diabetes: a randomised controlled trial. Atherosclerosis. 2016;252:28–31. doi: 10.1016/j.atherosclerosis.2016.07.908. [DOI] [PubMed] [Google Scholar]

[bib185] 185.Yamada Y., Uchida J., Izumi H., Tsukamoto Y., Inoue G., Watanabe Y., et al. A non-calorie-restricted low-carbohydrate diet is effective as an alternative therapy for patients with type 2 diabetes. Intern. Med. 2014;53(1):13–19. doi: 10.2169/internalmedicine.53.0861. [DOI] [PubMed] [Google Scholar]

[bib186] 186.Yancy W.S., Jr., Westman E.C., McDuffie J.R., Grambow S.C., Jeffreys A.S., Bolton J., et al. A randomized trial of a low-carbohydrate diet vs orlistat plus a low-fat diet for weight loss. Arch. Intern. Med. 2010;170(2):136–145. doi: 10.1001/archinternmed.2009.492. [DOI] [PubMed] [Google Scholar]

[bib187] 187.Zainordin N.A., Eddy Warman N.A., Mohamad A.F., Abu Yazid F.A., Ismail N.H., Chen X.W., et al. Safety and efficacy of very low carbohydrate diet in patients with diabetic kidney disease—a randomized controlled trial. PLOS ONE. 2021;16(10) [Google Scholar]

[bib188] 188.Zinn C., McPhee J., Harris N., Williden M., Prendergast K., Schofield G. A 12-week low-carbohydrate, high-fat diet improves metabolic health outcomes over a control diet in a randomised controlled trial with overweight defence force personnel. Appl. Physiol. Nutr. Metab. 2017;42(11):1158–1164. doi: 10.1139/apnm-2017-0260. [DOI] [PubMed] [Google Scholar]

[bib189] 189.Dening J., Mohebbi M., Abbott G., George E.S., Ball K., Islam S.M.S. A web-based low carbohydrate diet intervention significantly improves glycaemic control in adults with type 2 diabetes: results of the T2diet Study randomised controlled trial. Nutr. Diabetes. 2023;13(1):12. doi: 10.1038/s41387-023-00240-8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib190] 190.Iqbal N., Seshadri P., Stern L., Loh J., Kundu S., Jafar T., et al. Serum resistin is not associated with obesity or insulin resistance in humans. Eur. Rev. Med. Pharmacol. Sci. 2005;9(3):161–165. [PubMed] [Google Scholar]

[bib191] 191.Martens E.A., Gonnissen H.K., Gatta-Cherifi B., Janssens P.L., Westerterp-Plantenga M.S. Maintenance of energy expenditure on high-protein vs. high-carbohydrate diets at a constant body weight may prevent a positive energy balance. Clin. Nutr. 2015;34(5):968–975. doi: 10.1016/j.clnu.2014.10.007. [DOI] [PubMed] [Google Scholar]

[bib192] 192.Wal J.S., McBurney M.I., Moellering N., Marth J., Dhurandhar N.V. Moderate-carbohydrate low-fat versus low-carbohydrate high-fat meal replacements for weight loss. Int. J. Food Sci. Nutr. 2007;58(4):321–329. doi: 10.1080/09637480701240752. [DOI] [PubMed] [Google Scholar]

[bib193] 193.White A.M., Johnston C.S., Swan P.D., Tjonn S.L., Sears B. Blood ketones are directly related to fatigue and perceived effort during exercise in overweight adults adhering to low-carbohydrate diets for weight loss: a pilot study. J. Am. Diet. Assoc. 2007;107(10):1792–1796. doi: 10.1016/j.jada.2007.07.009. [DOI] [PubMed] [Google Scholar]

[bib194] 194.Wolever T.M., Mehling C. Long-term effect of varying the source or amount of dietary carbohydrate on postprandial plasma glucose, insulin, triacylglycerol, and free fatty acid concentrations in subjects with impaired glucose tolerance. Am. J. Clin. Nutr. 2003;77(3):612–621. doi: 10.1093/ajcn/77.3.612. [DOI] [PubMed] [Google Scholar]

[bib195] 195.Brinkworth G.D., Noakes M., Clifton P.M., Buckley J.D. Effects of a low carbohydrate weight loss diet on exercise capacity and tolerance in obese subjects. Obesity (Silver Spring). 2009;17(10):1916–1923. doi: 10.1038/oby.2009.134. [DOI] [PubMed] [Google Scholar]

[bib196] 196.Brinkworth G.D., Buckley J.D., Noakes M., Clifton P.M. Renal function following long-term weight loss in individuals with abdominal obesity on a very-low-carbohydrate diet vs high-carbohydrate diet. J. Am. Diet. Assoc. 2010;110(4):633–638. doi: 10.1016/j.jada.2009.12.016. [DOI] [PubMed] [Google Scholar]

[bib197] 197.Cohen C.W., Fontaine K.R., Arend R.C., Alvarez R.D., Leath C.A., III, Huh W.K., et al. A ketogenic diet reduces central obesity and serum insulin in women with ovarian or endometrial cancer. J. Nutr. 2018;148(8):1253–1260. doi: 10.1093/jn/nxy119. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib198] 198.Crabtree C.D., Kackley M.L., Buga A., Fell B., LaFountain R.A., Hyde P.N., et al. Comparison of ketogenic diets with and without ketone salts versus a low-fat diet: liver fat responses in overweight adults. Nutrients. 2021;13(3):966. doi: 10.3390/nu13030966. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib199] 199.Iacovides S., Maloney S.K., Bhana S., Angamia Z., Meiring R.M. Could the ketogenic diet induce a shift in thyroid function and support a metabolic advantage in healthy participants? A pilot randomized-controlled-crossover trial. PLOS ONE. 2022;17(6) [Google Scholar]

[bib200] 200.Karl J.P., Roberts S.B., Schaefer E.J., Gleason J.A., Fuss P., Rasmussen H., et al. Effects of carbohydrate quantity and glycemic index on resting metabolic rate and body composition during weight loss. Obesity (Silver Spring) 2015;23(11):2190–2198. doi: 10.1002/oby.21268. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib201] 201.Lundanes J., Storliløkken G.E., Solem M.S., Dankel S.N., Tangvik R.J., Ødegård R., et al. Gastrointestinal hormones and subjective ratings of appetite after low-carbohydrate vs low-fat low-energy diets in females with lipedema—a randomized controlled trial. Clin. Nutr. ESPEN. 2025;65:16–24. doi: 10.1016/j.clnesp.2024.11.018. [DOI] [PubMed] [Google Scholar]

[bib202] 202.Oliveira B.F., Chang C.R., Oetsch K., Falkenhain K., Crampton K., Stork M., et al. Impact of a low-carbohydrate compared with low-fat breakfast on blood glucose control in type 2 diabetes: a randomized trial. Am. J. Clin. Nutr. 2023;118(1):209–217. doi: 10.1016/j.ajcnut.2023.04.032. [DOI] [PubMed] [Google Scholar]

[bib203] 203.Rasmussen L.G., Larsen T.M., Mortensen P.K., Due A., Astrup A. Effect on 24-h energy expenditure of a moderate-fat diet high in monounsaturated fatty acids compared with that of a low-fat, carbohydrate-rich diet: a 6-mo controlled dietary intervention trial. Am. J. Clin. Nutr. 2007;85(4):1014–1022. doi: 10.1093/ajcn/85.4.1014. [DOI] [PubMed] [Google Scholar]

[bib204] 204.Swenson B.R., Saalwachter Schulman A., Edwards M.J., Gross M.P., Hedrick T.L., Weltman A.L., et al. The effect of a low-carbohydrate, high-protein diet on post laparoscopic gastric bypass weight loss: a prospective randomized trial. J. Surg. Res. 2007;142(2):308–313. doi: 10.1016/j.jss.2007.02.052. [DOI] [PubMed] [Google Scholar]

[bib205] 205.Walker K.Z., O'Dea K., Johnson L., Sinclair A.J., Piers L.S., Nicholson G.C., et al. Body fat distribution and non-insulin-dependent diabetes: comparison of a fiber-rich, high-carbohydrate, low-fat (23%) diet and a 35% fat diet high in monounsaturated fat. Am. J. Clin. Nutr. 1996;63(2):254–260. doi: 10.1093/ajcn/63.2.254. [DOI] [PubMed] [Google Scholar]

[bib206] 206.Wycherley T.P., Buckley J.D., Noakes M., Clifton P.M., Brinkworth G.D. Long-term effects of a very low-carbohydrate weight loss diet on exercise capacity and tolerance in overweight and obese adults. J. Am. Coll. Nutr. 2014;33(4):267–273. doi: 10.1080/07315724.2014.911668. [DOI] [PubMed] [Google Scholar]

[bib207] 207.Yancy W.S., Jr., Olsen M.K., Guyton J.R., Bakst R.P., Westman E.C. A low-carbohydrate, ketogenic diet versus a low-fat diet to treat obesity and hyperlipidemia: a randomized, controlled trial. Ann. Intern. Med. 2004;140(10):769–777. doi: 10.7326/0003-4819-140-10-200405180-00006. [DOI] [PubMed] [Google Scholar]

[bib208] 208.McManus K., Antinoro L., Sacks F. A randomized controlled trial of a moderate-fat, low-energy diet compared with a low fat, low-energy diet for weight loss in overweight adults. Int. J. Obes. Relat. Metab. Disord. 2001;25(10):1503–1511. doi: 10.1038/sj.ijo.0801796. [DOI] [PubMed] [Google Scholar]

[bib209] 209.Norwitz N.G., Soto-Mota A., Kaplan B., Ludwig D.S., Budoff M., Kontush A., et al. The lipid energy model: reimagining lipoprotein function in the context of carbohydrate-restricted diets. Metabolites. 2022;12(5):460. doi: 10.3390/metabo12050460. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib210] 210.McLaughlin T., Reaven G., Abbasi F., Lamendola C., Saad M., Waters D., et al. Is there a simple way to identify insulin-resistant individuals at increased risk of cardiovascular disease? Am. J. Cardiol. 2005;96(3):399–404. doi: 10.1016/j.amjcard.2005.03.085. [DOI] [PubMed] [Google Scholar]

[bib211] 211.Castelli W.P., Garrison R.J., Wilson P.W.F., Abbott R.D., Kalousdian S., Kannel W.B. Incidence of coronary heart disease and lipoprotein cholesterol levels: the Framingham Study. JAMA. 1983;250:1865–1871. [Google Scholar]

[bib212] 212.Millán J., Pintó X., Muñoz A., Zúñiga M., Rubiés-Prat J., Pallardo L.F., et al. Lipoprotein ratios: physiological significance and clinical usefulness in cardiovascular prevention. Vasc. Health Risk Manag. 2009;5:757–765. [PMC free article] [PubMed] [Google Scholar]

[bib213] 213.Soltani S., Jayedi A., Abdollahi S., Vasmehjani A.A., Meshkini F., Shab-Bidar S. Effect of carbohydrate restriction on body weight in overweight and obese adults: a systematic review and dose-response meta-analysis of 110 randomized controlled trials. Front. Nutr. 2023;10 [Google Scholar]

[bib214] 214.Naghshi S., Sadeghi O., Willett W.C., Esmaillzadeh A. Dietary intake of total, animal, and plant proteins and risk of all cause, cardiovascular, and cancer mortality: systematic review and dose-response meta-analysis of prospective cohort studies. BMJ. 2020;370 [Google Scholar]

[bib215] 215.Soto-Mota A., Flores-Jurado Y., Norwitz N.G., Feldman D., Pereira M.A., Danaei G., et al. Increased low-density lipoprotein cholesterol on a low-carbohydrate diet in adults with normal but not high body weight: a meta-analysis. Am. J. Clin. Nutr. 2024;119(3):740–747. doi: 10.1016/j.ajcnut.2024.01.009. [DOI] [PubMed] [Google Scholar]

[bib216] 216.Tan C.Y., Vidal-Puig A. Adipose tissue expandability: the metabolic problems of obesity may arise from the inability to become more obese. Biochem. Soc. Trans. 2008;36(5):935–940. doi: 10.1042/BST0360935. [DOI] [PubMed] [Google Scholar]

[bib217] 217.Scott P.M. Which diet is better--low-fat or low-carb? JAAPA. 2006;19(1):49. doi: 10.1097/01720610-200601000-00010. [DOI] [PubMed] [Google Scholar]

[bib218] 218.David L.A., Maurice C.F., Carmody R.N., Gootenberg D.B., Button J.E., Wolfe B.E., et al. Diet rapidly and reproducibly alters the human gut microbiome. Nature. 2014;505(7484):559–563. doi: 10.1038/nature12820. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib219] 219.St Jeor S.T., Howard B.V., Prewitt T.E., Bovee V., Bazzarre T., Eckel R.H., et al. Dietary protein and weight reduction: a statement for healthcare professionals from the Nutrition Committee of the Council on Nutrition, Physical Activity, and Metabolism of the American Heart Association. Circulation. 2001;104(15):1869–1874. doi: 10.1161/hc4001.096152. [DOI] [PubMed] [Google Scholar]

[bib220] 220.Van Elswyk M.E., Weatherford C.A., McNeill S.H. A systematic review of renal health in healthy individuals associated with protein intake above the US recommended daily allowance in randomized controlled trials and observational studies. Adv. Nutr. 2018;9(4):404–418. doi: 10.1093/advances/nmy026. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib221] 221.Athinarayanan S.J., Roberts C.G.P., Phinney S.D., Weimbs T., Friedman A.N., Volek J.S. Effects of a continuous remote care intervention including nutritional ketosis on kidney function and inflammation in adults with type 2 diabetes: a post-hoc latent class trajectory analysis. Front. Nutr. 2025;12 [Google Scholar]

[bib222] 222.J.J. Deeks, J.P.T. Higgins, D.G. Altman, Analysing data and undertaking meta-analyses. In: J.P.T. Higgins, J. Thomas, J. Chandler, et al. (Eds.), Cochrane Handbook for Systematic Reviews of Interventions Version 6.5 (updated February 2023).

[bib223] 223.A. Hengist, R.G. Davies, J.P. Walhin, J. Buniam, L.H. Merrell, L. Rogers, et al. Ketogenic diet but not free-sugar restriction alters glucose tolerance, lipid metabolism, peripheral tissue phenotype, and gut microbiome: RCT. Cell Rep Med. 2024 Aug 20;5(8):101667. 10.1016/j.xcrm.2024.101667. [DOI]

PERMALINK

Effects of carbohydrate-restricted diets and macronutrient replacements on cardiovascular health and body composition in adults: a meta-analysis of randomized trials

Shuo Feng

Renming Liu

Christopher Thompson

Brian Colwell

Sunghyun Chung

Adam Barry

Huishan Wang

Abstract

Background

Objectives

Methods

Results

Conclusions

Introduction

Methods

Search strategy

Eligibility criteria

Data extraction

Risk of bias assessment

Statistical analysis

Multiple testing correction

Sensitivity analysis

Results

Included study characteristics

FIGURE 1.

Risk of bias

Meta-analysis results: overall effect sizes (SMDs)

TABLE 1.

Subgroup analyses: macronutrient composition

TABLE 2.

Effects of CRD types on cardiovascular and anthropometric outcomes

Effects of carbohydrate replacement strategies

Sensitivity analysis results

Metaregression on intervention length

TABLE 3.

Subgroup analyses of participants’ characteristics

TABLE 4.

The effects of sex

The effects of weight status

The effects of diabetic status

Sensitivity analysis results

Effects of study characteristics

TABLE 5.

Discussion

A closer look at diets with various macronutrient proportions

Differences in participants’ characteristics

Differences in study designs

Potential negative effects of CRDs

Limitations

Author contributions

Data availability

Funding

Conflict of interest

Footnotes

Appendix A. Supplementary data

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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