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. 2025 Jul 11:12:1560080.
doi: 10.3389/fnut.2025.1560080. eCollection 2025.

Leptin, CRP, and adiponectin correlate with body fat percentage in adolescents: systematic review and meta-analysis

Ariane Ribeiro de Freitas Rocha  1 , Nubia de Souza de Morais  1 , Francilene Maria Azevedo  1 , Dayane de Castro Morais  1 , Patrícia Feliciano Pereira  1 , Maria do Carmo Gouveia Peluzio  1 , Sylvia do Carmo Castro Franceschini  1 , Silvia Eloiza Priore  1
Affiliations

Leptin, CRP, and adiponectin correlate with body fat percentage in adolescents: systematic review and meta-analysis

Ariane Ribeiro de Freitas Rocha et al. Front Nutr. .

Abstract

Introduction: Adipose tissue is important in the secretion of inflammatory substances, and may be directly or indirectly associated to the development of cardiovascular and metabolic diseases in adolescence.

Objective: To evaluate whether inflammatory markers are associated to body fat percentage in adolescents.

Methodology: Systematic review conducted following the items of the PRISMA, and registered in PROSPERO. The descriptors adolescent, body fat distribution and cytokines were combined together in the electronic databases: Scopus, PubMed, Embase, Cochrane, Scholar Google and ProQuest, independently by two researchers, in January 2022 and atualized in November 2024. Meta-analysis of the correlation of inflammatory markers with body fat percentage was conducted using the metabin function of the meta package of the RStudio software (4.0.4).

Results: Resulted in 7,592 records, of which 31 articles met the inclusion criteria and were selected for this study. Cross-sectional and prospective cohort observational studies were included. The meta-analysis included 4,682 adolescents, aged 10 to 19 years, of both sexes. The inflammatory markers leptin and C-reactive protein were positively correlated (r = 0.67; r = 0.32) and adiponectin was negatively correlated (r = -0.23) with body fat percentage in adolescents of both sexes.

Conclusion: In adolescents, the body fat percentage is related to the inflammatory markers leptin, C-reactive protein and adiponectin. It is important to evaluate the body fat composition of adolescents in clinical practice to identify those with a higher percentage of fat, that may reflect an inflammatory profile, as well as increased cardiometabolic risk that accompanies adolescents into adulthood.

Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD42020208305, identifier PROSPERO: CRD42020208305.

Keywords: adipose tissue; adolescence; body composition; cardiometabolic risk; inflammatory markers.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Flow chart depicting the article selection process. Identified articles total 7,592 from six databases: Cochrane (482), Embase (1,617), ProQuest (1,275), PubMed (1,735), Scholar Google (200), Scopus (2,283). After removing duplicates, 3,208 articles remain. Forty-five full articles are assessed for eligibility. Thirteen are excluded: five did not assess the outcome of interest, and eight included other age groups. Zero articles are included via reverse search. In total, 31 articles are included.
FIGURE 1
Flowchart of articles selected in the systematic review.
Three forest plots labeled A, B, and C depict meta-analysis results. Each plot includes study names, total participants, correlation coefficients, and confidence intervals. Plot A shows a random effects model correlation of 0.32 with significant heterogeneity. Plot B has a random effects model correlation of 0.67 with even greater heterogeneity. Plot C indicates a negative random effects model correlation of -0.23 with no heterogeneity. Each plot provides weights for common and random effects models.
FIGURE 2
Forestplot for correlation coefficients between body fat percentage and Leptin (A), CRP (B) and Adiponectin (C) in adolescents. This figure represents the individual effect of each study and the size indicates the sample weight; The black line represents the confidence interval (CI) of each study; The diamond systematizes the correlation between the inflammatory marker and the percentage of fat from all studies and the horizontal edges indicate the CI.
Bar chart showing responses to eight questions. Categories include No (blue), Unclear (orange), Not applicable (gray), and Yes (yellow). Most responses are Yes. Some questions show responses in other categories.
FIGURE 3
Risk of bias assessment, according to the Joanna Briggs Institute critical assessment checklist, for cross-sectional studies. 1. Criteria for inclusion in the sample cleary defined; 2. Study subjects and the setting described in detail; 3. Exposure measured in a valid and reliable way; 4. Objective and standard criteria for measurement; 5. Confounding factors identified; 6. Strategies to deal with confounding factors; 7. Outcomes measured in a valid and reliable way; 8. Appropriate statically analysis.
Bar chart with eleven rows labeled one to eleven, primarily yellow, representing “Yes.” Row four is partly blue for “No,” row five is blue and gray for “No” and “Not applicable,” row six is partly orange for “Unclear,” and row ten is partly gray. The x-axis is a percentage scale from zero to one hundred percent.
FIGURE 4
Risk of bias assessment, according to the Joanna Briggs Institute critical assessment checklist, for cohort studies. 1. Similar groups recruited from the same population; 2. Exposures in a similar way to designate as persons to exposed and unexposed groups; 3. Validly and reliably measured exposure; 4. Identification factors; 5 Strategies for dealing with confounders; 6. Groups were free/participating at baseline (or at time of exposure); 7. Intermediate results validly and reliably; 8. Follow-up time was observed and sufficient for results to occur; 9. Follow-up was complete and, if not, reasons for loss of follow-up were described and exploratory; 10. Strategies were used to address incomplete follow-up; 11. Appropriate statistics.
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