The effect of intermittent fasting on insulin resistance, lipid profile, and inflammation on metabolic syndrome: a GRADE assessed systematic review and meta-analysis

Abstract

Background

Evidence revealed that fasting intervention may have favorable effects on metabolic and inflammation profile. However, the results are controversial. This study attempted to investigate and assess the effects of fasting on cardiometabolic risk factors in adults.

Methods

We searched PubMed, Embase, Cochrane, Scopus, and Web of Science databases until March 2025 for randomized controlled trials (RCTs) which have evaluated the effect of fasting intervention on metabolic and inflammation profile. The GRADE approach was applied to assess the quality of evidence, and the Cochrane risk-of-bias (RoB) 2 tool was used to evaluate study quality.

Results

Eight RCTs with 573 participants were included in the meta-analysis. Findings revealed that fasting could significantly decreased fasting blood glucose (FBS) (WMD = -3.34; 95% CI: -6.24, -0.45, P = 0.024), HbA1c (WMD = -0.08; 95% CI: -0.13, -0.02; P = 0.005), and HOMA-IR (WMD= -0.60; 95% CI: -0.91, -0.28; P < 0.001) in adults. Similarly, fasting intervention exerted its favorable effect by reducing low-density lipoprotein cholesterol (LDL-c) (WMD = -6.42; 95% CI: -12.26, -0.58; P = 0.031), and IL-6 (WMD = -0.58; 95% CI: -1.08, -0.08; P = 0.022), significantly. The sensitivity analysis, indicated that excluding any single study has no effect on the overall effect size. No evidence of publication bias was observed using Begg’s test (P > 0.05).

Conclusion

Overall this systematic review and meta-analysis demonstrated that fasting state contributed to improved glycemic control including FBS, HbA1c, and HOMA-IR levels. In addition, fasting intervention caused to an improvement in lipid metabolism (LDL-c) and inflammatory state indicated by IL-6.

Introduction

Metabolic disorders such as type 2 diabetes mellitus, cardiovascular disease, and metabolic syndrome are considered as a major contributor to global morbidity and mortality [1, 2]. These conditions are characterized by glucose intolerance, insulin resistance, dyslipidemia, and obesity [3, 4]. In addition, low-grade inflammation may trigger these metabolic abnormalities [5, 6]. The growing prevalence of these disorders underscores the urgent need to address this health challenge. In this context, several non-pharmacological strategies have been developed and diet as a modifiable factor has emerged its positive properties.

Fasting interventions have emerged promising results to modify metabolic and inflammatory state [7, 8]. Intermittent fasting is characterized by repeated intentional interruptions in energy expenditure or a very low calorie diet (500–700 kcal) for 2–4 days a week [9, 10]. Various fasting regimens such as intermittent fasting, alternate-day fasting, and time-restricted feeding, demonstrated beneficial effects which are thought to be mediated through decreased level of glucose production, insulin sensitivity, lipid metabolism, and inflammatory state properly [7, 11, 12]. In this regard, Cramer et al. indicated that 300–350 kcal/day contribute to a significant improvement in the blood sugar level [13]. However, other studies found that, intermittent energy restriction does not affect the blood sugar level in patients with metabolic syndrome [14, 15]. Similarly, there were conflicting results in term of HOMA-IR level too. Patients with type 2 diabetes and metabolic syndrome undergone various fasting protocols which have shown both protective [13, 14] and unfavorable [16, 17] effects on HOMA-IR levels. Also, findings related to lipid profiles have been inconsistent. Most of studies investigating the effect of fasting program, reported no significant impact on high-density lipoprotein cholesterol (HDL-c). In contrast, Kunduraci et al. demonstrated that fasting program may have beneficial effect on HDL-c level [15].

Despite growing interest in fasting dietary approach, there are limited studies with variability across the results of studies, population, and the type of fasting. Therefore, this systematic review and meta-analysis of randomized controlled trials aimed to examine the effects of fasting interventions on metabolic and inflammatory profile. Specifically, it assessed key cardiometabolic risk factors, including fasting blood glucose (FBS), insulin resistance, and lipid parameters, as well as inflammatory markers such as C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α) to provide a more conclusive understanding of the impact of fasting state on metabolic health.

Method

The current systematic review and meta-analysis was conducted according to the guidelines in the Cochrane Handbook for Systematic Reviews of Interventions [18], and the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines [19]. In addition, the protocol of the current research has been approved by International Prospective Register of Systematic Reviews.

Search strategy

A comprehensive literature search has been done in PubMed, Scopus, Embase, Web of Science, and Cochrane Library up to March 2025. In addition, the reference list of relevant studies has been screened manually to avoid missing any relevant studies. The language was restricted to English. The search strategy was completed using relevant Medical Subject Heading (MeSH) terms and keywords.

Inclusion and exclusion criteria

The included studies were included if they were aligned with our specified PICOS criteria; Population/Patients (P: adults aged > 18), Intervention (I: fasting diet), Comparison (C: placebo or control group), Outcome (O: glycemic control (fasting plasma glucose (FPG), HbA1c, Homeostatic Model Assessment for Insulin Resistance (HOMA-IR), insulin), lipid profile (total cholesterol (TC), low-density lipoprotein cholesterol (LDL-c), high-density lipoprotein cholesterol (HDL-c), triglyceride (TG)), and inflammatory markers (CRP, IL-6, and TNF-α) and Study (S: randomized controlled trial (RCT) design (Parallel and Crossover). Nevertheless, studies were excluded if: (1) Lacked a control group. (2) Observational studies (case-control or cross-sectional), animal or review studies. (3) Trials lacking adequate data and research containing duplicated data.

Data screening procedures and data extraction

The references were managed using EndNote (version 9) to screen the articles. Two independent reviewers screened the titles and abstracts of the included studies based on predefined eligibility criteria. Subsequently, full-text of articles were retrieved and evaluated for inclusion. Any discrepancies between the reviewers were resolved through discussion, and any disagreements were resolved by third investigator.

Two authors completed data extraction process from each included studies including the name of first author, publication year, study design, location, mean age, mean body mass index (BMI), duration, health status. Additionally, the sample size and the mean ± standard deviation (SD) changes of predefined outcomes before and after intervention in both groups.

Quality assessment and quality of evidence

The quality assessments were done to determine the potential bias for each study. The selected RCTs underwent a risk of bias assessment utilizing the RoB 2 [20]. This assessment contains five specific domains: concealment of allocation, generation of random sequences, selective reporting, blinding of outcome assessment, and incomplete outcome data. All these domains were rated as low, unclear, or high risk.

However, the quality of evidence was assessed using the Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) approach [21]. This approach considers several factors: risk of bias, inconsistency, indirectness, imprecision, and publication bias. Accordingly, the quality of evidence was categorized as high, moderate, and low.

Statistical analysis

The analyses were performed using Stata Statistical Software version 14 (Stata Corp, College Station, TX, United States), and a random-effects model was applied to conduct the analyses [22]. The overall effect size was determined using the MD and SDs of changes in outcome levels. The mean difference (MD) along with the 95% confidence intervals (CIs) were computed to calculate the overall estimates [23]. The heterogeneity of included RCTs was assessed by the I² index, and I² > 50% and P < 0.05 was considered as significant and high heterogeneity between studies [24]. The sensitivity analysis using the leave-one-out method was utilized to identify the effect of each RCT on the overall effect size [25]. Funnel plots, as well as Begg’s and Egger’s tests were used to evaluate the publication bias [26, 27].

Results

Study selection

Our comprehensive and systematic search identified 1268 results, and 627 of them were duplicates. Title and abstract screening process ended in the exclusion of 628 irrelevant studies. Subsequently, 13 studies were evaluated for eligibility to be included in the present study. Likewise, five studies were excluded. At last, eight studies were included according to abovementioned inclusion criteria. The flowchart of the study selection procedure is provided in the Fig. 1.

Fig. 1.

PRISMA flow diagram of selection studies

Study characteristics

The study characteristics of the eight eligible publications in relation to the effect of fasting regimen on metabolic and inflammation profile are summarized in Table 1. The total sample size of all included studies was 573 and ranged from 32 to 145. All included studies were published from 2017 up to 2024. Also, the mean age of included study participants ranged from 25 to 58 years. The geographical location of included studies were in USA [16], Germany [28], Turkey [15], China [14], Iran [17, 29], and Thailand [30]. The duration of fasting regimen treatment was 1 to 16 weeks. The health condition in most of the included studies was metabolic syndrome and the others focused on type 2 diabetes and impaired glucose tolerance patients.

Table 1.

Characteristics of included studies

Author, Year	Country	Study, Design	Sex	Duration (week)	Sample Size (IN, CON)	Mean age (IN, CON)	BMI	Intervention type	Control group	Health status	Main outcome (IN)	Main outcome (CON)
Cramer H et al., 2022	Germany	SB, multicenter, parallel, RCT	M/F	0.71	145 (73, 72)	(58.6 ± 10.8) (60.8 ± 10.8)	33.7 ± 4.5	300–350 kcal/day, obtained from vegetable juices and vegetable broth	Modified DASH diet, exercise, mindfulness	MetS	BS: -6.30 ± 11.77 HbA1c: -0.1 ± 0.31 HOMA-IR: -1.50 ± 1.55 Ins: -4.4 ± 4.4 TC: 26.9 ± 30.94 LDL: -6.1 ± 24.70 HDL: -4.2 ± 9.63 TG: -71.6 ± 170.57 CRP: 0.1 ± 0.25 IL-6: -0.3 ± 1.62	BS: 4.30 ± 16.44 HbA1c: 0.1 ± 0.44 HOMA-IR: -0.3 ± 1.48 Ins: -0.6 ± 4.6 TC: 15.9 ± 30.33 LDL: 2.7 ± 27.24 HDL: -2.5 ± 12.01 TG: -5.6 ± 66.81 CRP: 0.1 ± 0.18 IL-6: 0.3 ± 1.68
Guo Y et al., 2021	China	RCT	M/F	8	39 (21, 18)	(40.2 ± 5.7) (42.7 ± 4.1)	28	Intermittent fasting (“two-day”; a 75% of energy restriction for two nonconsecutive days a week and an ad libitum diet the other five days)	Routine diet without dietary instructions	MetS	BS: -2.26 ± 5.40 HOMA-IR: -0.63 ± 0.93 Ins: -1.3 ± 5.0 TC: -1.6 ± 21.15 LDL: 0.7 ± 16.90 HDL: -0.4 ± 5.82 TG: -35.4 ± 67.14	BS: 0.72 ± 12.31 HOMA-IR:0.12 ± 0.52 Ins: -0.07 ± 1.98 TC: -10.8 ± 20.35 LDL: 20.9 ± 20.69 HDL: 8.1 ± 6.83 TG: 10.6 ± 80.70
Kunduraci YE et al., 2020	Turkey	RCT	M/F	12	65 (32, 33)	(47.44 ± 2.17) (48.76 ± 2.13)	36.58 ± 0.93	Intermittent Energy Restriction	Continuous Energy Restriction (CER)	MetS	BS: -15.47 ± 5.70 HbA1c: -0.32 ± 0.18 HOMA-IR: -1.29 ± 0.45 Ins: -2.23 ± 1.64 TC: -29.32 ± 4.88 LDL: -17.0 ± 3.57 HDL: 0.53 ± 1.12 TG: -41.84 ± 15.42	BS: -13.12 ± 4.29 HbA1c: -0.31 ± 0.15 HOMA-IR: -0.94 ± 0.49 Ins: -2.39 ± 1.31 TC: -29.36 ± 5.25 LDL: -15.97 ± 3.49 HDL: -0.38 ± 1.37 TG: -40.0 ± 20.77
Li et al., 2017	Germany	RCT	M/F	1	32 (16, 16)	25–75		Fasting		T2DM with MetS	BS: -10.70 ± 17.55 HbA1c: -2.2 ± 12.0 HOMA-IR: -1.50 ± 4.6 Ins: -3.4 ± 6.78 TC: -0.5 ± 27.1 LDL: -2.6 ± 26.9 HDL: 6.5 ± 23.3 TG: -26.6 ± 88.5	BS: -38.5 ± 27.18 HbA1c: -2.2 ± 8.7 HOMA-IR: -1.50 ± 2.1 Ins: -0.2 ± 7.22 TC: -15.5 ± 27.4 LDL: -7.8 ± 17.3 HDL: -2.3 ± 6.9 TG: -2.5 ± 81.9
Manoogian E.N.C et al., 2024	USA	RCT	M/F	12	108 (54, 54)	56.6 60.6	31.5	Time-Restricted Eating		MetS	FBS: -4.84 ± 6.22 HbA1c: -0.12 ± 0.20 HOMA-IR: -0.89 ± 2.18 Ins: -2.87 ± 8.72 LDL: -10.48 ± 25.78 HDL: -1.37 ± 9.34 TG: -7.77 ± 41.47 CRP: -0.19 ± 1.64	FBS: -1.5 ± 7.39 HbA1c: -0.02 ± 0.17 HOMA-IR: -0.38 ± 1.63 Ins: -1.2 ± 5.97 LDL: -1.37 ± 24.98 HDL: -0.37 ± 9.82 TG: -13.94 ± 46.24 CRP: -0.09 ± 1.89
Parvaresh A et al., 2019	Iran	RCT	M/F	8	69 (35, 34)	44.6 46.4	31.1 ± 3.35	Modified Alternate-Day Fasting	Calorie Restriction	MetS	FBS: -6.00 ± 5.78 HOMA-IR: -2.42 ± 3.82 TC: -11.0 ± 21.99 LDL: -6.0 ± 17.83 HDL: -1.0 ± 5.56 TG: -52.0 ± 67.25	FBS: 0.0 ± 5.34 HOMA-IR: -1.57 ± 4.09 TC: -9.0 ± 22.57 LDL: 0.0 ± 17.89 HDL: -1.0 ± 5.97 TG: -40.0 ± 69.85
Razavi R et al., 2021	Iran	single-center, RCT	M/F	16	69 (35, 34)	41.3 43.1	31.3	Alternate-day fasting diet	Calorie restriction diet	MetS	CRP: -2.06 ± 1.18 IL-6: -1.08 ± 2.7 TNF-α: -3.47 ± 5.77	CRP: -0.97 ± 0.82 IL-6: -0.61 ± 2.82 TNF-α: -2.21 ± 5.04
Suthutvoravut U et al., 2023	Thailand	RCT	M/F	4	46 (24, 22)	55.5 55.2	-	Time-Restricted Eating	Usual care for impaired glucose	Impaired Fasting Glucose	FBS: -3.03 ± 1.94 HbA1c: 0.09 ± 0.08	FBS: -1.79 ± 1.75 HbA1c: 0.15 ± 0.08

SB; single blind, RCT; randomized clinical trial, M; male, F; female, MetS; metabolic syndrome, T2DM; type 2 diabetes mellitus, BS; blood sugar, FBS; fasting blood sugar, HOMA-IR;, Ins; insulin, TC; total cholesterol, LDL; low-density lipoprotein, HDL; high-density lipoprotein, TG; triglyceride, CRP; C-reactive protein, IL-6; interleukin-6, TNF-α; tumor necrosis factor-α

Quality assessment and meta-evidence

According to quality assessment of included studies, randomization process was conducted in all included studies properly and rated as lower risk of bias. Moreover, all included studies for both domains including “selection of reported results” and “missing outcome data” were scored as lower risk of bias. Detailed information regarding the quality of the included RCTs are available in Table 2. The GRADE quality of evidence for the effect of fasting on HOMA-IR level was assessed as high quality of evidence. However, the effect of fasting was considered as moderate for insulin, TC, LDL-c, HDL-c, TG, CRP, IL-6, and TNF-α values (Table 3).

Table 2.

Results of risk of bias assessment for randomized clinical trials included in the present study

Author, Year	Randomization Process	Deviation from Intended Interventions	Selection of the Reported Result	Measurement of the Outcome	Missing Outcome Data	General risk of bias
Cramer H et al., 2022	Low	Unclear	Low	Low	Low	Low
Guo Y et al., 2021	Low	High	Low	High	Low	Moderate
Kunduraci YE et al., 2020	Low	Unclear	Low	Unclear	Low	Low
Li et al., 2017	Low	High	Low	Low	Low	Low
Manoogian E.N.C et al., 2024	Low	Unclear	Low	Unclear	Low	Low
Parvaresh A et al., 2019	Low	Low	Low	Low	Low	Low
Razavi R et al., 2021	Low	Low	Low	Low	Low	Low
Suthutvoravut U et al., 2023	Low	Low	Low	Low	Low	Low

Note: Each study was assessed for risk of bias using the ROB2 tool. Domains of assessment included were Randomization Process, Deviation from Intended Interventions, Selection of the Reported Result, Measurement of the Outcome, Missing Outcome Data, and General risk of bias. Each domain was scored as “high risk” if it contained methodological flaws that may have affected the results, “low risk” if the flaw was deemed inconsequential, and “some concern” if information was insufficient to determine

Table 3.

Summary of findings and quality of evidence assessment using the GRADE approach

	No of patients (meta-analysis)	WMD (95% CI)	Risk of bias1	Inconsistency2	Indirectness3	Imprecision4	Publication bias5	Quality of evidence6
FBS (mg/dl)	223 (3)	-3.34 (-6.24, -0.45)	Not Serious	Serious	Not Serious	Serious	Not Serious	Low
BS (mg/dl)	281 (4)	-0.79 (-8.50, 6.92)	Not Serious	Serious	Not Serious	Serious	Not Serious	Low
HbA1c	396 (5)	-0.08 (-0.13, -0.02)	Not Serious	Not Serious	Not Serious	Serious	Not Serious	Moderate
HOMA-IR	458 (6)	-0.60 (-0.91, -0.28)	Not Serious	Not Serious	Not Serious	Not Serious	Not Serious	High
Insulin (mU/L)	458 (6)	-1.60 (-3.26, 0.06)	Not Serious	Serious	Not Serious	Not Serious	Not Serious	Moderate
TC (mg/dL)	350 (5)	4.39 (-1.68, 10.47)	Not Serious	Not Serious	Not Serious	Serious	Not Serious	Moderate
LDL-c (mg/dL)	458 (6)	-6.42 (-12.26, -0.58)	Not Serious	Serious	Not Serious	Not Serious	Not Serious	Moderate
HDL-c (mg/dL)	458 (6)	-1.11 (-3.67, 1.45)	Not Serious	Serious	Not Serious	Not Serious	Not Serious	Moderate
TG (mg/dL)	458 (6)	-1.85 (-10.63, 6.94)	Not Serious	Serious	Not Serious	Not Serious	Not Serious	Moderate
CRP	322 (3)	-0.39 (-1.11, 0.34)	Not Serious	Serious	Not Serious	Serious	Not Serious	Moderate
IL-6	214 (2)	-0.58 (-1.08, -0.08)	Not Serious	Not Serious	Not Serious	Serious	Not Serious	Moderate
TNF-α	69 (3)	-1.26 (-3.81, 1.29)	Not Serious	Not Serious	Not Serious	Serious	Not Serious	Moderate

FBS; Fasting blood sugar, BS; Blood sugar, HOMAIR; Homeostatic Model Assessment for Insulin Resistance, TC; Total cholesterol, LDL-c; Low density lipoprotein-cholesterol, HDL-c; High density lipoprotein- cholesterol, TG; Triglyceride, CRP; C-reactive protein, IL-6; Interleuki-6, TNF-α; Tumor necrosis factor-α

¹ Risk of bias based on the Cochrane risk of bias tool

² Downgraded if there was a substantial unexplained heterogeneity (I² > 50%, P < 0.10) that was not explained by subgroup analyses

³ Downgraded if there were factors present relating to the participants, interventions, or outcomes which restrict the overall generalizability of the results

⁴ Downgraded if the 95% confidence interval (95% CI) crossed the minimally important difference (MID)

⁵ Downgraded if there was an evidence of publication bias using funnel plot

⁶ Since all included studies were randomized controlled trials, the certainty of the evidence was graded as high for all outcomes by default and then downgraded based on prespecified criteria

The impact of fasting on FBS and BS level in adults

The effect of fasting regimen on FBS level was reported in three RCTs including 223 individuals. This intervention caused a significant reduction in patients with metabolic syndrome and glucose intolerance (WMD = -3.34; 95% CI: -6.24, -0.45, P = 0.024; I² = 83.1%, P = 0.003) (Fig. 2).

Fig. 2.

Forest plot of impacts of fasting state on FBS level

However, the effect of fasting intervention on BS level was evaluated in four studies involving 281 participants. This intervention showed a non-significant effect on BS level in patients with metabolic syndrome and type 2 diabetes (WMD = -0.79; 95% CI: -8.50, 6.92, P = 0.841; I² = 88.0%, P < 0.001) (Fig. 3). Sensitivity analyses indicated that removing each study could not alter the overall effect of fasting intervention on FBS and BS levels. Since the number of included studies for FBS and BS value was less than ten studies, the Begg’s test was performed for publication bias and no publication bias was observed accordingly (Begg’s test > 0.05).

Fig. 3.

Forest plot of impacts of fasting state on BS level

The impact of fasting on HbA1c level in adults

Overall, five studies with a total of 396 adults (intervention group = 199) examined the effect of fasting on HbA1c levels. Our results revealed that fasting intervention statically decreased HbA1c level (WMD = -0.08; 95% CI: -0.13, -0.02; P = 0.005) with a moderate between-study heterogeneity (I² = 42.0%, P = 0.141) (Fig. 4). Sensitivity analyses for the HbA1c value was conducted and the overall effect size remained unchanged. No publication bias was found using Begg’s test (Begg’s test > 0.05).

Fig. 4.

Forest plot of impacts of fasting state on HbA1c level

The impact of fasting on HOMA-IR level in adults

The pooled effect of six studies evaluating the effect of fasting regimen on HOMA-IR level encompassing 458 participants (intervention group = 231, control group = 227) revealed a significant reduction on HOMA-IR level (WMD = -0.60; 95% CI: -0.91, -0.28, P < 0.001; I² = 54.4.0%, P = 0.052) (Fig. 5). A leave-one-out sensitivity analysis evaluated the effect of individual studies and the overall effect size remained consistent. The Begg’s test was performed and no publication bias was found accordingly (Begg’s test > 0.05).

Fig. 5.

Forest plot of impacts of fasting state on HOMA-IR level

The impact of fasting on insulin level in adults

The combined effect of six studies (458 participants) which have assessed the effect of fasting intervention on insulin level demonstrated a non-significant effect (WMD = -1.60; 95% CI: -3.26, 0.06, P = 0.059; I² = 79.4.0%, P < 0.001) (Fig. 6). Sensitivity analyses reported that removing one by one study could not affect the overall result of fasting on insulin level. The Begg’s test was performed and no publication bias was found accordingly (Begg’s test > 0.05).

Fig. 6.

Forest plot of impacts of fasting state on insulin level

The impact of fasting on lipid profile in adults

Effect of fasting intervention on LDL-c levels was explored from six studies among adults (Intervention group = 231, control group = 227). Combined results through the random-effects model revealed that fasting significantly reduced LDL-c levels in adults (WMD = -6.42, 95% CI: -12.26, -0.58; P = 0.031; I² = 69.4%, P = 0.006) (Fig. 7). While, fasting could not succeed to improve TC (WMD = 4.39, 95% CI: -1.68, 10.47; P = 0.156; I² = 53.0%, P = 0.075) (Fig. 8), HDL-c (WMD = -1.11, 95% CI: -3.67, 1.45; P = 0.396; I² = 77.0%, P = 0.001) (Fig. 9), and TG (WMD = -14.74, 95% CI: -32.47, 3.00; P = 0.103; I² = 63.7%, P = 0.017) (Fig. 10) levels significantly.

Fig. 7.

Forest plot of impacts of fasting state on LDL-c level

Fig. 8.

Forest plot of impacts of fasting state on TC level

Fig. 9.

Forest plot of impacts of fasting state on HDL-c level

Fig. 10.

Forest plot of impacts of fasting state on TG level

However, a leave-one-out sensitivity analysis evaluated the effect of individual studies on TC, LDL-c, HDL-c, and TG outcomes and the overall effect size remained consistent across the studies. Since the number of included studies were less than ten, the Begg’s test was used to evaluate the publication bias which indicated no evidence of publication bias for all lipid profile outcomes (P > 0.05).

The impact of fasting inflammatory markers in adults

Two studies including 214 participants investigated the impact of fasting on IL-6 levels. A significant decrease in IL-6 was observed in adult patients who experienced the fasting regimen (WMD = -0.58, 95% CI: -1.08, -0.08; P = 0.022; I² = 0.0%, P = 0.857). Whereas, random effect model showed non-significant changes on CRP (WMD = -0.39, 95% CI: -1.11, 0.34; P = 0.294; I² = 89.8%, P < 0.001) and TNF-α (WMD = -1.26, 95% CI: -3.81, 1.29; P = 0.334) (Fig. 11) following the fasting intervention. In addition, sensitivity analyses indicated that excluding any single study did not influence on the overall effect size. Begg’s test reported no evidence of publication bias (P > 0.05).

Fig. 11.

Forest plot of impacts of exercise program on inflammatory markers

Discussion

In the present systematic review and meta-analysis of available RCTs investigating the efficacy of fasting intervention in adults, we summarized the available evidence on the fasting intervention on metabolic risk factors and inflammatory markers to provide a firm conclusion. The previous meta-analyses [31–33] focused on either glycemic control or lipid profile parameters in isolation. While, our study offers a more comprehensive, multidimensional assessment of cardiometabolic factors and inflammatory markers. This integrated approach helps to have more clinically relevant interpretation of fasting effects on cardiometabolic profile. Accordingly, it has been shown that fasting intervention caused a significant decrease in FBS, HbA1c, and HOMA-IR levels. These findings indicate that fasting can be accompanied with glycemic control and improved insulin sensitivity. Subgroup analysis revealed that the duration of the fasting intervention significantly influenced its effect on insulin resistance. Interventions lasting ≥ 12 weeks demonstrated a greater effect size, with a standardized mean difference (SMD) of -0.55, indicating a more pronounced improvement in insulin sensitivity. In comparison, shorter interventions (< 12 weeks) showed a smaller yet statistically significant effect (SMD = -0.30). These findings suggest that longer fasting interventions may confer greater metabolic benefits with respect to insulin resistance.

Several probable mechanisms can be considered to exert these favorable effects. Fasting state can promote weight loss and reduce the glucose production in the liver and insulin resistance subsequently [34–36]. Likewise, this process may contribute to an improvement in HOMA-IR level specifically in patients with metabolic syndrome. Nonetheless, no significant changes were observed in blood glucose and insulin level. This discrepancy may be explained by the fact that blood glucose ad the insulin levels are representative of short-term metabolic responses, while FBS and HbA1c reflect the long-term effect glycemic state. Cramer et al. investigated the effect of fasting regimen congaing 300–350 kcal/day, obtained from vegetable juices and vegetable broth on BS level in patients with metabolic syndrome and found a significant reduction in BS level [13]. In contrast, seven day fasting program based on Buchinger approach (300 kcal/day by liquids only and then start of solid foods) did not show such effect in type 2 diabetes patients [28].

In addition, the fasting contributed to significant reduction in LDL-c level. This finding is clinically valuable and can be considered as cardioprotective strategy to improve atherosclerosis and cardiovascular disease. However, this finding may be bold in patients with metabolic syndrome. The probable mechanism indicating that lipolysis process may be activated following to fasting state. Accordingly, fasting state stimulate the body to utilize the fats as a source of energy which contributes to decreased atherogenic lipoproteins [37, 38]. All these are consistent with the previous studies which suggest that intermittent fasting and caloric restriction can favorably influence lipid profiles. Although the baseline lipid levels, type of fasting and the degree of compliance with intervention may affect the degree of LDL-c reduction. However, no significant changes were observed in term of TC, HDL-c, and TG levels following fasting. It may be attributed to the high sensitivity of HDL-c and TG level to lifestyle modifications. The variability in fasting protocols (e.g., time-restricted feeding, alternate-day fasting) and the duration of interventions across studies may have influenced the results. Guo et al. investigated the impact of intermittent fasting (“two-day” fasting; a 75% of energy restriction for two nonconsecutive days a week and an ad libitum diet the other five days) in patients with metabolic syndrome [14]. While modified alternate-day fasting could not affect the metabolic syndrome population in Iran [17].

Furthermore, our findings indicated that fasting state could improve IL-6 level significantly. This suggests an anti-inflammatory effect for fasting state [39]. IL-6 is a proinflammatory cytokine which is involved in the low-grade-inflammation and its increased level is more probable in the obesity or insulin resistance [40]. In addition, fasting state may contribute to reduced adiposity, improved gut microbiota composition, and decreased oxidative stress which are all interrelated with improved inflammation [41–43]. However, it failed to exert its favorable properties on CRP and TNF-α levels. The limited number of included studies and small sample sizes limits, the statistical power to detect meaningful differences. Overall reduced level of IL-6 supports the anti-inflammatory potential of fasting state.

This meta-analysis has several strengths. This study was performed based on current methodological guidelines. In addition, this study employed sensitivity analysis and investigated the risk of bias using an updated assessment tool. Moreover, this study presented an integrated interpretation of the results which is more realistic and holistic view of biological processes. Since most disorders arise from the interaction of multiple pathways, studies that focus on a single parameter in isolation may not provide the full picture. Our multipolar approach offers a more comprehensive understanding in relation to fasting effect on cardiometabolic health. Our study has some limitations needed to be mentioned too. First, the number of included studies were limited and the sample size was small which lower the statistical power of the study. Second, the type of fasting varied and it was not possible to group studies accordingly.

Conclusion

In conclusion, the current systematic review and meta0analysis demonstrated that fasting state may have favorable effects on glycemic control (FBS, HbA1c, and HOMA-IR levels). In addition, improvement in LDL-c and IL-6 levels revealed its cardioprotective properties.

Author contributions

Designing this study: Ling Lu, Xiuping Weng. Performed this study: Ling Lu, Xi Chen. Drafted the article, Revised the article critically for important intellectual content, and approved the version to be published: Ling Lu, Xi Chen, Sho Liou, Xiuping Weng.

Funding

Zhejiang Provincial Health and Wellness Science and Technology Plan 2022 (2022KY039), Zhejiang Provincial Medical and Health Science and Technology Plan 2024 (2024KY026), Science and Technology Foundation Project of Health Commission of Guizhou Province (Project No.: gzwkj2024-539).

Data availability

The original data used during the current study can be obtained by contacting the corresponding author.

Declarations

Ethical approval

Ethical approval was not required for this study as it is a meta-analysis based on previously published data.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.