Mediterranean Diet and Cardiometabolic Biomarkers in Children and Adolescents: A Systematic Review and Meta-Analysis

José Francisco López-Gil; Antonio García-Hermoso; Miguel Ángel Martínez-González; Fernando Rodríguez-Artalejo

doi:10.1001/jamanetworkopen.2024.21976

. 2024 Jul 12;7(7):e2421976. doi: 10.1001/jamanetworkopen.2024.21976

Mediterranean Diet and Cardiometabolic Biomarkers in Children and Adolescents

A Systematic Review and Meta-Analysis

José Francisco López-Gil ^1,^✉, Antonio García-Hermoso ², Miguel Ángel Martínez-González ^3,^4,^5,⁶, Fernando Rodríguez-Artalejo ^7,^8,⁹

PMCID: PMC11245727 PMID: 38995643

Key Points

Question

What is the association of Mediterranean diet–based interventions with cardiometabolic biomarkers in children and adolescents?

Findings

In this systematic review and meta-analysis of 9 studies in 577 participants, interventions promoting adherence to the Mediterranean diet was modestly associated with reduced systolic blood pressure and triglyceride, total cholesterol, and low-density lipoprotein cholesterol levels and increased high-density lipoprotein cholesterol levels in youths.

Meaning

These findings highlight the relevance of Mediterranean diet–based interventions as a useful tool to optimize cardiometabolic health in children and adolescents.

This systematic review and meta-analysis assesses the association of Mediterranean diet interventions with levels of cardiometabolic biomarkers in children and adolescents.

Abstract

Importance

No prior systematic review and meta-analysis has specifically verified the association of Mediterranean diet (MedDiet)–based interventions with biomarkers of cardiometabolic health in children and adolescents.

Objective

To review and analyze the randomized clinical trials (RCTs) that assessed the effects of MedDiet-based interventions on biomarkers of cardiometabolic health among children and adolescents.

Data Sources

Four electronic databases were searched (PubMed, Cochrane Library, Web of Science, and Scopus) from database inception to April 25, 2024.

Study Selection

Only RCTs investigating the effect of interventions promoting the MedDiet on cardiometabolic biomarkers (ie, systolic blood pressure [SBP], diastolic blood pressure [DBP], triglycerides [TGs], total cholesterol [TC], high-density lipoprotein cholesterol [HDL-C], low-density lipoprotein cholesterol [LDL-C], glucose, insulin, and homeostatic model assessment for insulin resistance [HOMA-IR]) among children and adolescents (aged ≤18 years) were included.

Data Extraction and Synthesis

A systematic review and meta-analysis was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Data were extracted from the studies by 2 independent reviewers. Results across studies were summarized using random-effects meta-analysis.

Main Outcome and Measures

The effect size of each trial was computed by unstandardized mean differences (MDs) of changes in biomarker levels (ie, SBP, DBP, TGs, TC, HDL-C, LDL-C, glucose, insulin, HOMA-IR) between the intervention and the control groups. The quality of the evidence was assessed using the Grading of Recommendations, Assessment, Development, and Evaluations approach.

Results

Nine RCTs were included (mean study duration, 17 weeks; range, 8-40 weeks). These studies involved 577 participants (mean age, 11 years [range, 3-18 years]; 344 girls [59.6%]). Compared with the control group, the MedDiet-based interventions showed a significant association with reductions in SBP (mean difference, −4.75 mm Hg; 95% CI, −8.97 to −0.52 mm Hg), TGs (mean difference, −16.42 mg/dL; 95% CI, −27.57 to −5.27 mg/dL), TC (mean difference, −9.06 mg/dL; 95% CI, −15.65 to −2.48 mg/dL), and LDL-C (mean difference, −10.48 mg/dL; 95% CI, −17.77 to −3.19 mg/dL) and increases in HDL-C (mean difference, 2.24 mg/dL; 95% CI, 0.34-4.14 mg/dL). No significant associations were observed with the other biomarkers studied (ie, DBP, glucose, insulin, and HOMA-IR).

Conclusions and Relevance

These findings suggest that MedDiet-based interventions may be useful tools to optimize cardiometabolic health among children and adolescents.

Introduction

Cardiovascular disease (CVD) prevention should start early in life, as there is substantial evidence linking atheromatosis and cardiovascular risk factors during childhood and adulthood to subsequent CVD later over the life course.¹ In 2020, metabolic syndrome was observed in approximately 3% of children and 5% of adolescents, with slight differences in prevalence among various countries and regions, which underscores the urgent need for multisectoral interventions to improve cardiometabolic health in this population.² In this sense, lifestyle factors,³ particularly diet,⁴ seem to exert a significant role on cardiometabolic health. Unhealthy dietary patterns have been linked to cardiometabolic disturbances in children and adolescents (aged ≤18 years).⁵ Conversely, consuming a diet rich in unprocessed or minimally processed foods could have positive outcomes for future cardiometabolic health in children, including lower body weight and body fat, smaller waist circumference, lower blood pressure, and lower serum insulin levels.⁶

The Mediterranean diet (MedDiet) has gained recognition for its health benefits among various healthy dietary patterns.^7,8 This eating pattern is characterized by the use of olive oil as the primary dietary fat and abundant consumption of seasonal fruits, vegetables, legumes, whole grains, and nuts, with low intake of red and processed meats, ultraprocessed food (UPF), sweets, confections, and pastries.⁹ It also involves a moderate intake of white or lean meats and fish. There is evidence that the MedDiet reduces the risk of noncommunicable diseases, such as cancer, metabolic syndrome, hypertension, and CVD.⁹ Additionally, adherence to the MedDiet has been associated with lower mortality rates, with several dietary components within the MedDiet playing an important role.¹⁰ Specifically, interventions based on the MedDiet have shown an association with a reduction in body mass index (BMI) and the proportion of obesity in children and adolescents.¹¹

However, much less is known about the cardiometabolic effects of the MedDiet in children and adolescents than in adults, as most studies in the former group are cross-sectional.¹² Indeed, to our knowledge, no systematic review of the literature has been conducted to assess the association of MedDiet-based interventions on biomarkers of cardiometabolic health specifically in this population. Therefore, our objective was to review and analyze the randomized clinical trials (RCTs) that have assessed MedDiet interventions among children and adolescents.

Methods

This systematic review and meta-analysis followed the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement¹³ and adhered to the recommendations provided by the Cochrane Handbook for Systematic Reviews of Interventions.¹⁴ The meta-analysis was registered with PROSPERO (CRD42022372269).

Eligibility Criteria

Studies were eligible if they met the following inclusion criteria: (1) participants aged 18 years or younger, (2) assessment of biomarkers as outcomes based on standardized tests, (3) RCT design, and (4) MedDiet-based interventions. The studied cardiometabolic biomarkers were systolic blood pressure (SBP), diastolic blood pressure (DBP), triglycerides (TGs), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), glucose, insulin, homeostatic model assessment for insulin resistance (HOMA-IR), and glycated hemoglobin (HbA_1c). Review articles, editorials, and case reports were excluded. The selection of studies was performed by 2 independent reviewers (J.F.L.-G. and A.G.-H.) who assessed titles and abstracts. There were no disagreements between the reviewers at this stage.

Information Sources, Search Strategy, and Data Extraction

The search was conducted in the PubMed, Scopus, the Cochrane Library, and Web of Science databases, covering studies published from database inception through April 25, 2024. The search strategy was developed based on the participants, intervention, comparison, outcome, and study design framework and used specific sets of terms, which were as follows: (1) preschoolers, children, youths, or teenagers, or adolescents; (2) Mediterranean diet; (3) anthropometric measurements, BMI, obesity, overweight, excess weight, adiposity, abdominal obesity, body fat, fat mass, or high trunk fat mass; and (4) intervention, clinical trial, randomized clinical trial, randomised clinical trial, randomized controlled trial, randomised controlled trial, or RCT. In addition to the database searches, the reference lists of the included studies in this review were screened to identify any additional relevant studies. The complete search strategy in each database is provided in eTable 1 in Supplement 1. Information on country of the study, participant characteristics (number, sex, age, and baseline BMI), type and duration of intervention, and cardiometabolic biomarkers were extracted from the studies by 2 independent reviewers (J.F.L.-G. and A.G.-H.), with a 100% of agreement.

Risk-of-Bias Assessment

The risk of bias in each study was evaluated using the Cochrane risk of bias tool for RCTs, version 2.0.¹⁵ This tool assesses 5 key domains: the randomization process, deviations from intended interventions, missing outcome data, outcome measurement, and selection of the reported outcome. Risk of bias in each study was categorized as follows: (1) low risk if all domains had a low risk of bias, (2) some concerns if 1 domain raised some concerns but there was no high risk of bias for any individual domain. or (3) high risk if there was a high risk of bias in at least 1 domain or if multiple domains were deemed to have some concerns.¹⁵

Quality of Evidence

We appraised the quality of the evidence using the Grading of Recommendations, Assessment, Development, and Evaluations approach,¹⁶ which considers 4 levels of quality (high, moderate, low, and very low). The overall quality of evidence was initially regarded as high but was downgraded by 1 level for each of the following 5 issues: (1) limitations (ie, risk of bias); (2) indirectness of patients, intervention, and comparator; (3) inconsistency; (4) imprecision; and (5) other considerations.

Small Study Effects and Publication Biases

To assess small study effects and publication biases, the Doi plot and the Luis Furuya-Kanamori (LFK) index were used.¹⁷ The presence of asymmetry was evaluated using the LFK index, with values of 1 indicating no asymmetry, between 1 and 2 indicating minor asymmetry, and 2 indicating major asymmetry.¹⁷

Statistical Analysis

The effect size of each intervention was calculated using absolute mean differences of changes in biomarkers between the intervention and control group in each RCT. Several independent random-effects meta-analyses (1 for each outcome) were performed to summarize the effect of interventions promoting the MedDiet on each cardiometabolic biomarker. The random-effects inverse variance model with Paule-Mandel adjustment was used to calculate the overall effect size estimate and its corresponding 95% CI.¹⁸ Furthermore, prediction intervals were estimated, indicating the range within which the effect size of a newly conducted study is expected to fall if it were randomly selected from the same population of studies that have already been included in a meta-analysis.

To ensure the robustness of the findings, sensitivity analyses were conducted by excluding 1 study at a time from the overall estimates. In addition, subgroup and meta-regression analyses were not conducted because we did not have more than 10 studies in the meta-analysis for any of the outcomes.¹⁹

All analyses were performed using R, version 4.3.0 (R Core Team) and RStudio, version 2023.03.1 (Posit) software, and the packages meta (commands metagen, forest, and metainf)²⁰ and metasens (command lfkindex)²⁰ were used to conduct this study. A 2-sided P < .05 was considered significant.

Results

Study Selection

The PRISMA flow diagram illustrating the study selection process is shown in Figure 1. eTable 2 in Supplement 1 provides information on the studies that were excluded from the analysis, along with the reasons for their exclusion.

Study Characteristics

This review comprises 9 RCTs^{21,22,23,24,25,26,27,28,29} in 577 participants (344 girls [59.6%] and 233 boys [40.4%]) (Table). The mean participant age was 11 years (range, 3-18 years). The mean study duration was 17 weeks (range, 8-40 weeks). The intervention groups across RCTs consisted of 322 participants. Six studies focused on children and adolescents with excess weight^{21,22,23,24,25,26} (of which 2 targeted children and adolescents with nonalcoholic fatty liver disease^23,26), 1 study enrolled children with prediabetes,²⁷ and 2 studies involved apparently healthy children.^28,29 Eight studies included participants of both sexes,^{21,23,24,25,26,27,28,29} while 1 included only girls.²² The MedDiet-based interventions had a minimum duration of 8 weeks. Additional characteristics of the included studies are provided in eTable 3 in Supplement 1.

Table. Summary of the Included Studies’ Characteristics.

Source	Country	Age range, y	No. of participants		Baseline weight status	Duration, wk	Intervention type		Biomarkers examined
Source	Country	Age range, y	IG	CG	Baseline weight status	Duration, wk	IG	CG	Biomarkers examined
Akbulut et al,²⁶ 2022	Turkey	9-17	23	22	Excess^a	12	Prescribed MedDiet and physical exercise	Low-fat diet and physical exercise	TG, TC, HDL-C, LDL-C, glucose, insulin, and HOMA-IR
Andueza et al,²⁹ 2023	Spain	6-12	44	11	Unrestricted^b	8	Prescribed MedDiet	Usual care	SBP, DBP, TG, TC, HDL-C, LDL-C, glucose, insulin, and HOMA-IR
Asoudeh et al,²² 2023	Iran	13-18	35	35	Excess^a	12	Prescribed MedDiet	Usual care	SBP, DBP, TG, TC, HDL-C, LDL-C, glucose, insulin, and HOMA-IR
Blancas-Sánchez et al,²⁷ 2022	Spain	9-15	14	15	Unrestricted^b	20	Nutrition education	Usual care	Insulin and HbA_1c
Fernández-Ruiz et al,²⁴ 2021	Spain	6-12	51	50	Excess^a	40	Prescribed MedDiet and physical activity promotion	Usual care	TG, TC, HDL-C, LDL-C, and glucose
Muros et al,²⁸ 2015	Spain	10-11	21^c	41	Unrestricted^b	24	Nutrition education	No actions received	SBP, DBP, TG, TC, HDL-C, LDL-C, and glucose
Ojeda-Rodríguez et al,²⁵ 2018	Spain	7-16	81	26	Excess^a	8	Prescribed MedDiet and physical activity promotion	Standard diet and physical activity promotion	SBP, DBP, TC, glucose, insulin, and HOMA-IR
Velázquez-López et al,²¹ 2014	Mexico	3-18	24	25	Excess^a	16	Prescribed MedDiet	Standard diet and physical activity promotion	SBP, DBP, TG, TC, HDL-C, LDL-C, and glucose
Yurtdaş et al,²³ 2022	Turkey	11-18	22	22	Excess^a	12	Prescribed MedDiet and physical activity promotion	Low-fat diet	TG, TC, HDL-C, LDL-C, glucose, insulin, HOMA-IR, and HbA_1c

Open in a new tab

Abbreviations: CG, control group; DBP, diastolic blood pressure; HbA_1c, glycosylated hemoglobin; HDL-C, high-density lipoprotein cholesterol; HOMA-IR, homeostatic model assessment for insulin resistance; IG, intervention group; MedDiet, Mediterranean diet; LDL-C, low-density lipoprotein cholesterol; SBP, systolic blood pressure; TC, total cholesterol; TG, triglyceride.

^{^a}

Participants with excess weight (overweight or obesity).

^{^b}

Participants with any weight status (thinness, normal weight, overweight, or obesity).

^{^c}

Intervention group received only a MedDiet-based intervention.

Adherence to the MedDiet was assessed in only 4 studies (44.4%) and was based on the Mediterranean Diet Quality Index for Children and Adolescents (eTable 4 in Supplement 1). In 7 RCTs,^{21,22,23,24,25,26,29} the intervention group received a MedDiet prescription, while in the other 2 RCTs,^27,28 it received nutritional education based on the MedDiet. The control group consisted of usual care in 5 RCTs,^{22,24,27,28,29} a standard diet in 2,^21,25 and a low-fat diet in 2.^23,26 Detailed information on the intervention and control groups is shown in eTable 5 in Supplement 1.

Summary of Cardiometabolic Biomarkers

Blood Pressure

Compared with the control group, the MedDiet-based interventions showed a significant association with reductions in SBP (mean difference, −4.75 mm Hg; 95% CI, −8.97 to −0.52 mm Hg; 5 RCTs^{21,22,25,28,29}) (Figure 2). In addition, no association was found for decreased DBP (mean difference, −1.91 mm Hg; 95% CI, −3.98 to 0.17 mm Hg; 5 RCTs^{21,22,25,28,29}).

Figure 2. — MD indicates mean difference; PM, Paule-Mandel.

Lipids

Compared with the control group, the MedDiet-based interventions showed significant associations with reductions in TGs (mean difference, −16.42 mg/dL; 95% CI, −27.57 to −5.27 mg/dL [to convert mg/dL to mmol/L, multiply by 0.0113]; 6 RCTs^{21,22,23,24,26,28}), TC (mean difference, −9.06 mg/dL; 95% CI, −15.65 to −2.48 mg/dL [to convert TC, LDL-C, and HDL-C from mg/dL to mmol/L, multiply by 0.0259]; 8 RCTs^{21,22,23,24,25,26,29}), and LDL-C (mean difference, −10.48 mg/dL; 95% CI, −17.77 to −3.19 mg/dL; 7 RCTs^{21,22,23,24,26,28,29}). In addition, the MedDiet was associated with increases in HDL-C (mean difference, 2.24 mg/dL; 95% CI, 0.34-4.14 mg/dL; 7 RCTs^{21,22,23,24,26,28,29}) compared with the control group (Figure 3).

Figure 3. — MD indicates mean difference; PM, Paule-Mandel, except for HDL-C.

^aNegative values favor control and positive values favor intervention.

Glucose and Insulin Resistance

Compared with the control group, the MedDiet-based interventions were not associated with decreases in glucose (mean difference, −2.61 mg/dL; 95% CI, −5.87 to 0.66 mg/dL [to convert mg/dL to mmol/L, multiply by 0.0555]; 8 RCTs^{21,22,23,24,25,26,29}), insulin (mean difference, −1.26 μIU/mL; 95% CI, −2.98 to 0.46 μIU/mL [to convert μIU/mL to pmol/L, multiply by 6.945]; 6 RCTs^{22,23,25,26,27,29}), and HOMA-IR (−0.14; 95% CI, −0.74 to 0.46; 5 RCTs^{22,23,25,26,29}) (Figure 4). Finally, a meta-analysis could not be conducted for HbA_1c as there were only 2 studies published on this particular outcome.^23,27

Figure 4. — To convert insulin to pmol/L, multiply by 6.945. HOMA-IR indicates homeostatic model assessment for insulin resistance; MD, mean difference; PM, Paule-Mandel.

Sensitivity Analysis

Overall, when each study was individually removed from the analyses, no relevant changes were observed in the main results (regarding the direction of the estimates). However, for SBP, the results were not significant when Asoudeh et al,²² Muros et al,²⁸ or Ojeda-Rodríguez et al²⁵ were removed. Similarly, for HDL-C, the results did not retain their statistical significance when Asoudeh et al, Fernández-Ruiz et al,²⁴ or Muros et al were eliminated. Conversely, for DBP, the results were significant when Andueza et al²⁹ (mean difference, −6.70 mm Hg; 95% CI, −1.17 to 0.05 mm Hg; P = .045) or Asoudeh et al (mean difference, −3.12 mm Hg; 95% CI, −7.22 to 0.97 mm Hg; P = .01) were removed. In addition, for glucose, the estimates were significant when Ojeda-Rodríguez et al (mean difference, −3.75 mg/dL; 95% CI, −6.82 to −0.68 mg/dL; P = .02) or Yurtdaş et al²³ (mean difference, −3.57 mg/dL; 95% CI, −6.67 to −0.46 mg/dL; P = .02) were removed. eTables 6 to 8 in Supplement 1 provide further results of the sensitivity analyses.

Risk of Bias in Studies

The risk of bias was assessed using the Cochrane risk of bias tool for RCTs¹⁵ on the 9 included RCTs. Among these RCTs, 5 were classified as having a low risk of bias,^{23,24,25,26,27} while 4 were identified as having some concerns of bias^22,25,28,29 (eFigure 1 in Supplement 1).

Small Study Effects and Publication Bias

A major asymmetry suggestive of small study effects was observed for SBP (LFK index, 2.09) (eFigure 2 in Supplement 1), TGs (LFK index, −3.54) (eFigure 3 in Supplement 1), TC (LFK index, −2.03) (eFigure 4 in Supplement 1), glucose (LFK index, 2.98) (eFigure 5 in Supplement 1), and insulin (LFK index, 2.33) (eFigure 6 in Supplement 1). Minor asymmetries were found for LDL-C (LFK index, 1.54) (eFigure 7 in Supplement 1) and HOMA-IR (LFK index, 1.33) (eFigure 8 in Supplement 1). Finally, no asymmetries of small studies were observed for DBP (eFigure 9 in Supplement 1) and HDL-C (eFigure 10 in Supplement 1).

Quality of Evidence

Overall, the quality of evidence for the pooled estimates was classified as moderate for most of the examined biomarkers (ie, DBP, TGs, TC, HDL-C, LDL-C, and insulin). However, the pooled estimates for SBP and serum glucose were graded as low quality. Furthermore, the HOMA-IR pooled estimate was of very low quality (eTable 9 in Supplement 1).

Discussion

The findings from this systematic review and meta-analysis indicate that MedDiet-based interventions (9 RCTs with a minimum duration of 8 weeks) were associated with reductions in SBP, TGs, TC, and LDL-C and increases in HDL-C. However, caution should be exercised when interpreting the results due to the limited number of RCTs. Several factors could account for the variation in results among studies. First, the use of different types of interventions, such as prescribed diet, nutrition education, or a combination of diet and physical activity or exercise, may have contributed to the inconsistency among the results obtained. Additionally, the variation in geographic locations (Mediterranean and non-Mediterranean countries) or whether interventions were targeted solely at young individuals or involved parents and families may have also influence our findings. Finally, the control groups varied across the studies, which also may have influenced the results.

Our findings show that MedDiet-based interventions were somewhat effective in reducing SBP, TGs, TC, and LDL-C and in increasing HDL-C. Even though the reductions may seem modest, decreases in SBP during childhood and adolescence may be important,³⁰ since elevated blood pressure in childhood or adolescence has been consistently associated with several intermediate CVD markers in adulthood.³¹ Decreases in SBP may lead to substantial reductions in the risk of CVD and mortality in adulthood.³¹ Furthermore, elevated levels of TGs, TC, and LDL-C are associated with a higher risk of atherosclerosis and CVDs, while higher levels of HDL-C are considered protective.³² The observed improvements suggest a favorable shift in lipid profiles in children and adolescents, which may lower the risk of developing atherosclerosis and CVDs in adulthood.³³ Concerning children and adolescents, some observational studies have also investigated the association between the MedDiet and cardiometabolic health^{34,35,36,37,38,39,40} with inconsistent results. Some studies reported that the MedDiet may be linked to better cardiometabolic profiles (eg, lower odds of having metabolic syndrome,^35,36,37 insulin resistance,³⁶ hypertension,^35,36 hypertriglyceridemia,^35,36,37 high LDL-C,³⁵ high HOMA-IR,³⁸ central obesity,^35,36 metabolically unhealthy obesity^34,38,39), while others found no association (eg, metabolic syndrome⁴⁰). However, these studies were cross-sectional investigations, which preclude causal inference.

There are several possible mechanisms of the influence of the MedDiet on lipid biomarkers in children and adolescents. First, the MedDiet has a low intake of saturated fats and transfats,⁴¹ which raise LDL-C levels.⁷ Second, the MedDiet includes a high intake of healthy fats, such as monounsaturated and polyunsaturated fats (ie, olive oil, nuts, seeds, fatty fish),⁴² which lower LDL-C. Similarly, these specific fats, together with some vitamins, trace elements, and polyphenols found in the traditional MedDiet,⁴² appear to promote a healthy intestinal microbiota and the integrity of the intestinal barrier, which are altered in some health conditions (eg, metabolic syndrome).⁴³ Our findings are practically relevant since elevated LDL-C and TG levels are frequently observed cardiovascular risk factors among the pediatric population with overweight or obesity.⁴⁴

Another possible contributor to our findings is the low UPF consumption characteristic of the traditional MedDiet. People with low adherence to the MedDiet have a significantly higher UPF intake than those with moderate and high adherence,⁴⁵ which has also been reported in children.⁴⁶ Ultraprocessed foods have been associated with an increased risk of excess weight, as they are energy dense and associated with higher calorie intake.⁴⁷ Furthermore, a positive dose-response outcome was observed for an absolute increment of 10% of UPF on TC and TGs during a mean follow-up period of 3 years.⁴⁸

On the other hand, although our findings are compatible with reductions in the rest of the biomarkers studied (ie, DBP, glucose, insulin, HOMA-IR) in the groups that received MedDiet-based interventions, results were not statistically significant. There are some possible reasons for these nonsignificant findings, such as the small sample size of studies, which may limit the statistical power; the variability between studies in participants (eg, participants with excess weight, with nonalcoholic fatty liver disease, with prediabetes) and interventions (eg, prescribed diet, nutrition education, inclusion of physical activity); and the inclusion of studies with weak designs or methodological limitations. Thus, we need more high-quality RCTs to establish whether the MedDiet (or some of its components) are associated with improvements in these biomarkers among the younger population.

Limitations

The interpretation of our results should be done with caution for several reasons. First, the review included some RCTs with risk-of-bias concerns, which limits confidence in the results. Second, not all interventions focused solely on the MedDiet content; some also incorporated physical activity or exercise, which may influence the overall outcomes observed. Third, not all RCTs provided data on participants’ prior knowledge of or adherence to the MedDiet.⁴⁹ Fourth, publication bias may have overestimated the associations, as indicated by the major asymmetry observed in the Doi plot and LFK index for certain biomarkers. Fifth, it was not possible to conduct subgroup analyses or meta-regressions due to the scarcity of studies. As a result, we could not determine whether the outcomes were consistent across different subgroups, such as sex or race and ethnicity, or whether certain variables (eg, duration of the intervention, mean age, BMI at baseline) may have substantially influenced the estimates obtained. Finally, there was a low number of non-Mediterranean countries represented by the included RCTs, which is problematic due to variations in specific foods and primary cooking methods between Mediterranean and non-Mediterranean countries, potentially limiting the generalizability of the results.⁵⁰

Conclusions

The findings of this systematic review and meta-analysis of RCTs suggest that MedDiet-based interventions are associated with reductions in SBP, TGs, TC, and LDL-C and an increase in HDL-C among children and adolescents. These results underscore the importance of promoting healthy eating habits in youths, as these habits may lead to substantially improved cardiometabolic health, even during the early stages of life. Specifically, MedDiet-based interventions in different contexts (eg, schools, hospitals) may be a valuable tool for optimizing cardiometabolic health in the younger population.

Supplement 1.

eTable 1. Search Strategy

eTable 2. Excluded Studies and Reasons for Exclusion

eTable 3. Additional Characteristics of the Included Studies

eTable 4. Adherence to the Mediterranean Diet at Baseline in the Randomized Controlled Trials Examined

eTable 5. Detailed Information About the Intervention and Control Groups in the Randomized Controlled Trials

eTable 6. Sensitivity Analyses for Blood Pressure Biomarkers Excluding One by One the Different Randomized Controlled Trials

eTable 7. Sensitivity Analyses for Lipid Biomarkers Excluding One by One the Different Randomized Controlled Trials

eTable 8. Sensitivity Analyses for Insulin Resistance–Related Biomarkers Excluding One by One the Different Randomized Controlled Trials

eTable 9. Grading of Recommendations, Assessment, Development, and Evaluations (GRADE)

eFigure 1. Risk of Bias (RoB 2.0)

eFigure 2. Luis Furuya-Kanamori (LFK) Index and Doi Plot for Systolic Blood Pressure (SBP)

eFigure 3. Luis Furuya-Kanamori (LFK) Index and Doi Plot for Triglycerides (TG)

eFigure 4. Luis Furuya-Kanamori (LFK) Index and Doi Plot for Total Cholesterol (TC)

eFigure 5. Luis Furuya-Kanamori (LFK) Index and Doi Plot for Glucose

eFigure 6. Luis Furuya-Kanamori (LFK) Index and Doi Plot for Insulin

eFigure 7. Luis Furuya-Kanamori (LFK) Index and Doi Plot for Low-Density Lipoprotein Cholesterol (LDL-C)

eFigure 8. Luis Furuya-Kanamori (LFK) Index and Doi Plot for Homeostatic Model Assessment for Insulin Resistance (HOMA-IR)

eFigure 9. Luis Furuya-Kanamori (LFK) Index and Doi Plot for Diastolic Blood Pressure (DBP)

eFigure 10. Luis Furuya-Kanamori (LFK) Index and Doi Plot for High-Density Lipoprotein Cholesterol (HDL-C)

jamanetwopen-e2421976-s001.pdf^{(615.5KB, pdf)}

Supplement 2.

Data Sharing Statement

jamanetwopen-e2421976-s002.pdf^{(9.2KB, pdf)}

References

1.Virani SS, Alonso A, Benjamin EJ, et al. ; American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee . Heart disease and stroke statistics—2020 update: a report from the American Heart Association. Circulation. 2020;141(9):e139-e596. doi: 10.1161/CIR.0000000000000757 [DOI] [PubMed] [Google Scholar]
2.Noubiap JJ, Nansseu JR, Lontchi-Yimagou E, et al. Global, regional, and country estimates of metabolic syndrome burden in children and adolescents in 2020: a systematic review and modelling analysis. Lancet Child Adolesc Health. 2022;6(3):158-170. doi: 10.1016/S2352-4642(21)00374-6 [DOI] [PubMed] [Google Scholar]
3.García-Hermoso A, López-Gil JF, Ezzatvar Y, Ramírez-Vélez R, Izquierdo M. Twenty-four-hour movement guidelines during middle adolescence and their association with glucose outcomes and type 2 diabetes mellitus in adulthood. J Sport Health Sci. 2023;12(2):167-174. doi: 10.1016/j.jshs.2022.08.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Siscovick DS. Scientific discovery, contextual factors, and cardiometabolic health research: back to the future. Circ Res. 2017;120(10):1555-1557. doi: 10.1161/CIRCRESAHA.116.310254 [DOI] [PubMed] [Google Scholar]
5.Rocha NP, Milagres LC, Longo GZ, Ribeiro AQ, Novaes JFD. Association between dietary pattern and cardiometabolic risk in children and adolescents: a systematic review. J Pediatr (Rio J). 2017;93(3):214-222. doi: 10.1016/j.jped.2017.01.002 [DOI] [PubMed] [Google Scholar]
6.Vilela S, Magalhães V, Severo M, Oliveira A, Torres D, Lopes C. Effect of the food processing degree on cardiometabolic health outcomes: a prospective approach in childhood. Clin Nutr. 2022;41(10):2235-2243. doi: 10.1016/j.clnu.2022.07.034 [DOI] [PubMed] [Google Scholar]
7.Guasch-Ferré M, Willett WC. The Mediterranean diet and health: a comprehensive overview. J Intern Med. 2021;290(3):549-566. doi: 10.1111/joim.13333 [DOI] [PubMed] [Google Scholar]
8.Doundoulakis I, Farmakis IT, Theodoridis X, et al. Effects of dietary interventions on cardiovascular outcomes: a network meta-analysis. Nutr Rev. 2024;82(6):715-725. doi: 10.1093/nutrit/nuad080 [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Martínez-González MA, Trichopoulou A. Observational epidemiology, lifestyle, and health: the paradigm of the Mediterranean diet. Am J Health Promot. 2020;34(8):948-950. doi: 10.1177/0890117120960580c [DOI] [PubMed] [Google Scholar]
10.Galbete C, Schwingshackl L, Schwedhelm C, Boeing H, Schulze MB. Evaluating Mediterranean diet and risk of chronic disease in cohort studies: an umbrella review of meta-analyses. Eur J Epidemiol. 2018;33(10):909-931. doi: 10.1007/s10654-018-0427-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
11.López-Gil JF, García-Hermoso A, Sotos-Prieto M, Cavero-Redondo I, Martínez-Vizcaíno V, Kales SN. Mediterranean diet-based interventions to improve anthropometric and obesity indicators in children and adolescents: a systematic review with meta-analysis of randomized controlled trials. Adv Nutr. 2023;14(4):858-869. doi: 10.1016/j.advnut.2023.04.011 [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Lassale C, Fitó M, Morales-Suárez-Varela M, Moya A, Gómez SF, Schröder H. Mediterranean diet and adiposity in children and adolescents: a systematic review. Obes Rev. 2022;23(S1):e13381. doi: 10.1111/obr.13381 [DOI] [PubMed] [Google Scholar]
13.Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71. doi: 10.1136/bmj.n71 [DOI] [PMC free article] [PubMed] [Google Scholar]
14.Higgins JPT, Thomas J, Chandler J, et al. , eds. Cochrane Handbook for Systematic Reviews of Interventions. 2nd ed. Wiley-Blackwell; 2020. [Google Scholar]
15.Sterne JAC, Savović J, Page MJ, et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ. 2019;366:l4898. doi: 10.1136/bmj.l4898 [DOI] [PubMed] [Google Scholar]
16.Schünemann H, Brożek J, Guyatt G, Oxman A, eds. GRADE handbook. GRADEPro. Updated October 2013. Accessed February 1, 2024. https://gdt.gradepro.org/app/handbook/handbook.html
17.Furuya-Kanamori L, Barendregt JJ, Doi SAR. A new improved graphical and quantitative method for detecting bias in meta-analysis. Int J Evid Based Healthc. 2018;16(4):195-203. doi: 10.1097/XEB.0000000000000141 [DOI] [PubMed] [Google Scholar]
18.Paule RC, Mandel J. Consensus values and weighting factors. J Res Natl Bur Stand (1977). 1982;87(5):377-385. doi: 10.6028/jres.087.022 [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Deeks JJ, Higgins JPT, Altman DG; Cochrane Statistical Methods Group . Analysing data and undertaking meta-analyses. In: Higgins J, Thomas J, Chandler J, et al. , eds. Cochrane Handbook for Systematic Reviews of Interventions. Version 6.4. Cochrane Training; 2023:chap 10. Accessed February 1, 2024. http://www.training.cochrane.org/handbook [Google Scholar]
20.Schwarzer G, Carpenter JR, Rücker G. Meta-Analysis With R. Springer International Publishing; 2015. doi: 10.1007/978-3-319-21416-0 [DOI] [Google Scholar]
21.Velázquez-López L, Santiago-Díaz G, Nava-Hernández J, Muñoz-Torres AV, Medina-Bravo P, Torres-Tamayo M. Mediterranean-style diet reduces metabolic syndrome components in obese children and adolescents with obesity. BMC Pediatr. 2014;14(1):175. doi: 10.1186/1471-2431-14-175 [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Asoudeh F, Fallah M, Aminianfar A, et al. The effect of Mediterranean diet on inflammatory biomarkers and components of metabolic syndrome in adolescent girls. J Endocrinol Invest. 2023;46(10):1995-2004. doi: 10.1007/s40618-023-02027-1 [DOI] [PubMed] [Google Scholar]
23.Yurtdaş G, Akbulut G, Baran M, Yılmaz C. The effects of Mediterranean diet on hepatic steatosis, oxidative stress, and inflammation in adolescents with non-alcoholic fatty liver disease: a randomized controlled trial. Pediatr Obes. 2022;17(4):e12872. doi: 10.1111/ijpo.12872 [DOI] [PubMed] [Google Scholar]
24.Fernández-Ruiz VE, Solé-Agustí M, Armero-Barranco D, Cauli O. Weight loss and improvement of metabolic alterations in overweight and obese children through the I²AO² Family Program: a randomized controlled clinical trial. Biol Res Nurs. 2021;23(3):488-503. doi: 10.1177/1099800420987303 [DOI] [PubMed] [Google Scholar]
25.Ojeda-Rodríguez A, Zazpe I, Morell-Azanza L, Chueca MJ, Azcona-Sanjulian MC, Marti A. Improved diet quality and nutrient adequacy in children and adolescents with abdominal obesity after a lifestyle intervention. Nutrients. 2018;10(10):1500. doi: 10.3390/nu10101500 [DOI] [PMC free article] [PubMed] [Google Scholar]
26.Akbulut UE, Isik IA, Atalay A, et al. The effect of a Mediterranean diet vs. a low-fat diet on non-alcoholic fatty liver disease in children: a randomized trial. Int J Food Sci Nutr. 2022;73(3):357-366. doi: 10.1080/09637486.2021.1979478 [DOI] [PubMed] [Google Scholar]
27.Blancas-Sánchez IM, Del Rosal Jurado M, Aparicio-Martínez P, et al. A Mediterranean-diet-based nutritional intervention for children with prediabetes in a rural town: a pilot randomized controlled trial. Nutrients. 2022;14(17):3614. doi: 10.3390/nu14173614 [DOI] [PMC free article] [PubMed] [Google Scholar]
28.Muros JJ, Zabala M, Oliveras-López MJ, et al. Effect of physical activity, nutritional education, and consumption of extra virgin olive oil on lipid, physiological, and anthropometric profiles in a pediatric population. J Phys Act Health. 2015;12(9):1245-1252. doi: 10.1123/jpah.2014-0236 [DOI] [PubMed] [Google Scholar]
29.Andueza N, Martin-Calvo N, Navas-Carretero S, Cuervo M. The ALINFA intervention improves diet quality and nutritional status in children 6 to 12 years old. Nutrients. 2023;15(10):2375. doi: 10.3390/nu15102375 [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Daniels SR, Pratt CA, Hayman LL. Reduction of risk for cardiovascular disease in children and adolescents. Circulation. 2011;124(15):1673-1686. doi: 10.1161/CIRCULATIONAHA.110.016170 [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Bundy JD, Li C, Stuchlik P, et al. Systolic blood pressure reduction and risk of cardiovascular disease and mortality: a systematic review and network meta-analysis. JAMA Cardiol. 2017;2(7):775-781. doi: 10.1001/jamacardio.2017.1421 [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Mach F, Baigent C, Catapano AL, et al. ; ESC Scientific Document Group . 2019 ESC/EAS guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk. Eur Heart J. 2020;41(1):111-188. doi: 10.1093/eurheartj/ehz455 [DOI] [PubMed] [Google Scholar]
33.Koskinen J, Juonala M, Dwyer T, et al. Impact of lipid measurements in youth in addition to conventional clinic-based risk factors on predicting preclinical atherosclerosis in adulthood: International Childhood Cardiovascular Cohort Consortium. Circulation. 2018;137(12):1246-1255. doi: 10.1161/CIRCULATIONAHA.117.029726 [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Arenaza L, Huybrechts I, Ortega FB, et al. Adherence to the Mediterranean diet in metabolically healthy and unhealthy overweight and obese European adolescents: the HELENA study. Eur J Nutr. 2019;58(7):2615-2623. doi: 10.1007/s00394-018-1809-8 [DOI] [PubMed] [Google Scholar]
35.Mar Bibiloni M, Martínez E, Llull R, et al. Metabolic syndrome in adolescents in the Balearic Islands, a Mediterranean region. Nutr Metab Cardiovasc Dis. 2011;21(6):446-454. doi: 10.1016/j.numecd.2009.11.008 [DOI] [PubMed] [Google Scholar]
36.George ES, Gavrili S, Itsiopoulos C, Manios Y, Moschonis G. Poor adherence to the Mediterranean diet is associated with increased likelihood of metabolic syndrome components in children: the Healthy Growth Study. Public Health Nutr. 2021;24(10):2823-2833. doi: 10.1017/S1368980021001701 [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Martino F, Puddu PE, Lamacchia F, et al. Mediterranean diet and physical activity impact on metabolic syndrome among children and adolescents from Southern Italy: contribution from the Calabrian Sierras Community Study (CSCS). Int J Cardiol. 2016;225:284-288. doi: 10.1016/j.ijcard.2016.10.008 [DOI] [PubMed] [Google Scholar]
38.Mirzaei S, Saneei P, Asadi A, Feizi A, Askari G, Akhlaghi M. Association between major dietary patterns and metabolic health status in overweight and obese adolescents. Nutrition. 2022;103-104:111793. doi: 10.1016/j.nut.2022.111793 [DOI] [PubMed] [Google Scholar]
39.Mohammadi S, Lotfi K, Mirzaei S, Asadi A, Akhlaghi M, Saneei P. Adherence to Mediterranean diet and its association with metabolic health status in overweight and obese adolescents. Int J Clin Pract. 2022;2022:9925267. doi: 10.1155/2022/9925267 [DOI] [PMC free article] [PubMed] [Google Scholar]
40.Kim RJ, Lopez R, Snair M, Tang A. Mediterranean diet adherence and metabolic syndrome in US adolescents. Int J Food Sci Nutr. 2021;72(4):537-547. doi: 10.1080/09637486.2020.1840533 [DOI] [PubMed] [Google Scholar]
41.Bach-Faig A, Berry EM, Lairon D, et al. ; Mediterranean Diet Foundation Expert Group . Mediterranean diet pyramid today. science and cultural updates. Public Health Nutr. 2011;14(12A):2274-2284. doi: 10.1017/S1368980011002515 [DOI] [PubMed] [Google Scholar]
42.Willett WC. The Mediterranean diet: science and practice. Public Health Nutr. 2006;9(1A):105-110. doi: 10.1079/PHN2005931 [DOI] [PubMed] [Google Scholar]
43.García-Montero C, Fraile-Martínez O, Gómez-Lahoz AM, et al. Nutritional components in Western diet versus Mediterranean diet at the gut microbiota–immune system interplay. implications for health and disease. Nutrients. 2021;13(2):699. doi: 10.3390/nu13020699 [DOI] [PMC free article] [PubMed] [Google Scholar]
44.Jacobs DR Jr, Woo JG, Sinaiko AR, et al. Childhood cardiovascular risk factors and adult cardiovascular events. N Engl J Med. 2022;386(20):1877-1888. doi: 10.1056/NEJMoa2109191 [DOI] [PMC free article] [PubMed] [Google Scholar]
45.Dinu M, Tristan Asensi M, Pagliai G, et al. Consumption of ultra-processed foods is inversely associated with adherence to the Mediterranean diet: a cross-sectional study. Nutrients. 2022;14(10):2073. doi: 10.3390/nu14102073 [DOI] [PMC free article] [PubMed] [Google Scholar]
46.da Rocha BRS, Rico-Campà A, Romanos-Nanclares A, et al. Adherence to Mediterranean diet is inversely associated with the consumption of ultra-processed foods among Spanish children: the SENDO project. Public Health Nutr. 2021;24(11):3294-3303. doi: 10.1017/S1368980020001524 [DOI] [PMC free article] [PubMed] [Google Scholar]
47.Monteiro CA, Cannon G, Moubarac JC, Levy RB, Louzada MLC, Jaime PC. The UN Decade of Nutrition, the NOVA food classification and the trouble with ultra-processing. Public Health Nutr. 2018;21(1):5-17. doi: 10.1017/S1368980017000234 [DOI] [PMC free article] [PubMed] [Google Scholar]
48.Leffa PS, Hoffman DJ, Rauber F, Sangalli CN, Valmórbida JL, Vitolo MR. Longitudinal associations between ultra-processed foods and blood lipids in childhood. Br J Nutr. 2020;124(3):341-348. doi: 10.1017/S0007114520001233 [DOI] [PubMed] [Google Scholar]
49.López-Gil JF, Victoria-Montesinos D, García-Hermoso A. Effects of lifestyle-based interventions to improve Mediterranean diet adherence among the young population: a meta-analysis of randomized controlled trials. Nutr Rev. 2023;nuad107. doi: 10.1093/nutrit/nuad107 [DOI] [PubMed] [Google Scholar]
50.Salas-Salvadó J, Papandreou C. Chapter 1—the Mediterranean diet: history, concepts and elements. In: Preedy VR, Watson RR, eds. The Mediterranean Diet: An Evidence-Based Approach. 2nd ed. Academic Press; 2020:3-11. doi: 10.1016/B978-0-12-818649-7.00001-1 [DOI] [Google Scholar]

Associated Data

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

Supplementary Materials