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. 2026 Feb 20;105(8):e44812. doi: 10.1097/MD.0000000000044812

Exploring the impact of childhood obesity on sarcopenia-related traits: A 2-way Mendelian randomization analysis

Mengyan Zhao a, Tao Guo b,*, Chaoyang Liu a
PMCID: PMC12928889  PMID: 41731851

Abstract

Childhood obesity has become a major global public health concern. In recent years, sarcopenia, a syndrome characterized by progressive loss of muscle mass, strength, and function, has shown a tendency to develop at an earlier age and may be associated with metabolic abnormalities in childhood. However, it is difficult to clarify the direction of causality between childhood obesity and sarcopenia, and is subject to confounding factors and reverse causality interference. Mendelian randomization (MR), which uses genetic variation as an instrumental variable, can effectively control confounding and infer causality. Bidirectional MR can further explore the bidirectional causal association between exposure and outcome. This study aimed to clarify the causal direction of childhood obesity and sarcopenia-related traits by using bidirectional MR methods. To examine the relationship between childhood obesity and sarcopenia-related traits, the bidirectional 2-sample MR method was used, and the main analysis method was inverse-variance weighted analysis. The study used genome-wide association study data on childhood obesity, appendicular lean mass, hand grip strength, and walking pace (WP) that were taken from public databases. Childhood obesity and WP may have been causally related, according to the forward MR analysis (odds ratio [OR] = 0.982, 95% confidence interval: 0.966–0.998, P < .05). Reverse MR analysis indicated a link between WP and the risk of childhood obesity (OR = 0.215, 95% confidence interval: 0.047–0.976, P < .05), with accelerated WP reducing the likelihood of childhood obesity. The findings of the other MR analyses, however, did not reveal any noteworthy variations. Childhood obesity was a significant causal factor for reduced walking speed (OR = 0.982, P < .05), whereas increased walking speed significantly prevented the development of childhood obesity (OR = 0.215, P < .05). Although walking speed, one of the core indicators of sarcopenia, had a bidirectional causal association with obesity, the combined diagnosis of sarcopenia was not causally related to childhood obesity. Therefore, walking speed can be used as an independent and practical indicator for screening childhood obesity, assessing muscle function, and monitoring the effects of interventions.

Keywords: causal inference, childhood obesity, genome-wide association studies, Mendelian randomization, sarcopenia

1. Introduction

The global prevalence of obesity is skyrocketing, affecting not only adults, but also children and adolescents.[1] Evidence suggests that childhood overweight and obesity often persist into adulthood.[2,3] Recent estimates based on 2416 data sources indicate that 21% of school-age children worldwide are classified as overweight or obese.[4] Obesity is not merely a matter of excess weight; it is also associated with chronic low-grade inflammation, insulin resistance, and lipid metabolism disorders caused by abnormal expansion of adipose tissue.[5] These metabolic abnormalities not only directly increase the risk of metabolic diseases such as type 2 diabetes and hypertension[6,7] but may also affect long-term health by altering organ function.[6] However, traditional research has primarily focused on the association between childhood obesity and metabolic syndrome in adulthood, with insufficient attention given to its potential link with muscle degenerative diseases.

Sarcopenia was initially defined as a syndrome characterized by age-related progressive muscle mass loss, decreased muscle strength, and functional decline, and was widely regarded as a “disease of the elderly.”[8] However, recent epidemiological studies have revealed that the onset age has significantly shifted earlier: an analysis of the Korean National Health and Nutrition Examination Survey found that the prevalence of sarcopenia precursor states among young adults aged 20 to 39 was 19.2%,[9] and was significantly associated with childhood obesity.[10] Childhood obesity may accelerate muscle loss through multiple pathways: on one hand, the close association between obesity and mitochondrial dysfunction in fat cells leads to excessive reactive oxygen species production and inflammation in adipose tissue, which spreads systemically and causes metabolic disorders.[11] Mitochondrial dysfunction further exacerbates muscle strength decline[12]; on the other hand, insulin resistance-induced impaired muscle glucose uptake and lipotoxicity damage muscle fiber contractile function.[13] These findings challenge the traditional belief that sarcopenia occurs exclusively in the elderly, suggesting that childhood may be a critical window for intervening in sarcopenia.

Currently, the evidence regarding the relationship between childhood obesity and sarcopenia primarily stems from observational studies. A study of 431 healthy male and female children aged 6 to 10 years during the COVID-19 pandemic lockdown found that 25.2% were obese and 9.5% had sarcopenia[14]; however, observational studies cannot rule out 2 key biases: first, family lifestyle, such as high-calorie diets and sedentary habits, may simultaneously drive both obesity and sarcopenia[15]; second, abnormal fat accumulation within muscle tissue, leading to reduced muscle mass.[16] The presence of these confounders and reverse causality prevents observational studies from clearly establishing causal direction, thereby limiting the development of clinical intervention strategies.

Using genetic variation as a risk factor, Mendelian randomization (MR) is a reliable epidemiological study method for establishing the causal relationship between 2 illnesses. It identifies mutant genes that may cause sickness by using genome-wide association studies (GWAS) as a technique to predict the incidence of another disease.[17] Genetic variation is randomly distributed and less affected by confounding factors, according to Mendelian inheritance laws. This study used a bidirectional 2-sample MR method to examine whether childhood obesity and sarcopenia indicators are causally related. The study’s findings were intended to provide a theoretical foundation for the prediction and evaluation of childhood obesity in clinical practice.

2. Materials and methods

2.1. Study design

Single-nucleotide polymorphisms (SNPs) are used as genetic instrumental variables (IVs) in MR, a specialized study that evaluates the impact of risk factors on different outcomes.[18] SNPs linked to certain risk factors can be employed as IVs in GWAS to identify the causal impact of these variables on various outcomes. Three fundamental presumptions are involved in the IV selection process: The IV must have a strong correlation with the exposure; the IV cannot be linked to any known confounders that might change the exposure–outcome relationship; and the IV must have no connection to the outcome, perhaps only influencing it through its impact on exposure.[19,20]

This study used GWAS consortium pooled data to find characteristics linked to sarcopenia,[8] notably walking pace (WP), hand grip strength (HGS), and appendicular lean mass (ALM), which served as markers of performance, strength, and muscle mass, respectively. We conducted a bidirectional, 2-sample, 2-step MR analysis to investigate the causal relationship and direction between childhood obesity and sarcopenia-related traits. This study was structured in 2 stages. First, we examined whether childhood obesity was causally linked to sarcopenia-related traits. In the second stage, we evaluated whether the characteristics of sarcopenia were related to childhood obesity. Figure 1 shows a schematic of the MR study.

Figure 1.

Figure 1.

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Schematic diagram of a Mendelian randomization study on childhood obesity and sarcopenia.

2.2. Data sources

We collected the GWAS summary data for childhood obesity from an extensive investigation with 13,848 people from Europe (5530 cases and 8318 controls). Additionally, we acquired GWAS summary statistics from UKBiobank for ALM (n = 4,50,243), HGS (right, n = 4,61,089; left, n = 4,61,026), and WP (n = 4,59,915). An overview of the data utilized in the study is given in Table 1. As a secondary analysis of publicly accessible data, our study complies with the original GWAS procedure by obtaining informed consent from each participant. The original authors of the GWAS got all ethical permissions for the study.

Table 1.

Summary of genetic dataset information for the Mendelian randomization (MR) analysis.

Phenotype GWAS ID SNP Sample size Case Control Population PMID
Childhood obesity ieu-a-1096 24,42,739 13,848 5530 8318 European 22484627
Usual walk pace ukb-b-4711 98,51,867 4,59,915 European
Appendicular lean mass ebi-a-GCST90000025 1,80,71,518 4,50,243 European 33097823
Left-hand grip strength ukb-b-7478 98,51,867 4,61,026 European
Right-hand grip strength ukb-b-10215 98,51,867 4,61,089 European
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GWAS = genome-wide association study, MR = Mendelian randomization, PMID = PubMed identifier, SNP = single-nucleotide polymorphism.

2.3. Genetic instrument selection

The following guidelines were used in the selection of the genetic tools: determining if SNPs were in linkage disequilibrium by establishing a cutoff value of R2 < 0.001 (distance of aggregation = 10,000 kb) and a criterion of P < 5 × 10−8 for SNPs to reach genome-wide significance.[21] To prevent breaking the third aforementioned assumption, exclude SNPs having significant associations (P < 5 × 10−8) from the generated database.[22] Utilizing the formula below, determine the F statistic to assess each SNP’s efficacy: F = R2(N − K − 1)/K(1 − R2), where N is the sample size, K is the number of SNPs, and R2 is the exposure variation due to genetic variance. Based on the widely accepted rule that the F statistic should be higher than 10 in order to avoid mild instrumental bias in MR analysis, SNPs were chosen.[23] Potential outliers were eliminated by applying the Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) approach.[21] Coordinating exposure and outcome datasets to eliminate palindromic SNPs.[24,25] Following extensive screening, further analysis was conducted using the remaining SNPs (Fig. S1, Supplemental Digital Content, https://links.lww.com/MD/Q180).

2.4. Statistical analysis

We performed all MR and sensitivity analyses in this study using the 2-sample MR and MR-PRESSO packages in the R software (version 4.2.3; R Foundation for Statistical Computing), and we used bidirectional 2-sample MR analysis to examine the association between sarcopenia-related traits and childhood obesity. For continuous outcomes, we utilized the β coefficient of standard errors (SEs) as the OR of SEs, whereas for binary outcomes, we calculated the MR as the odds ratio (OR) with 95% confidence intervals [CIs].

To reevaluate the data, we used the MR-PRESSO test (10,000 repeated settings) to find and remove outliers.[26] For our analysis, we mostly used the random inverse-variance weighted (IVW) approach. To guarantee consistent outcomes, we used the weighted median and MR-Egger[22,27] and carried out a variety of sensitivity studies to evaluate the validity of our findings, such as the Cochran’s Q test, the MR-Egger intercept test, and the leave-one-out analysis.[22,27] Heterogeneity was assessed using Cochran’s Q test, and pleiotropy was assessed using the MR-Egger intercept test and leave-one-out analysis.[22,27] The SE and 95% CIs per standard deviation were computed using the delta technique.[28] Figure 2 illustrates the analysis’s course.

Figure 2.

Figure 2.

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MR analysis flowchart. Childhood obesity, sarcopenia. GWAS = genome-wide association study, MR = Mendelian randomization, MR-PRESSO = Mendelian Randomization Pleiotropy RESidual Sum and Outlier, SNP = single-nucleotide polymorphism.

3. Results

We found SNPs that were substantially linked to exposure using IVs for screening, and we acquired their OR, SE, and P-values. For these SNPs, we also found matching values in the database. This MR study’s findings were mostly based on IVW analysis.

3.1. Causal effects of childhood obesity on sarcopenia-related traits

We eliminated the outliers and corrected for possible confounding variables in the MR-PRESSO study. We found a possible causal link between childhood obesity and WP in the IVW analysis (OR = 0.982, 95% CI: 0.966–0.998, P < .05) in line with the weighted median approaches. The robustness and reliability of these results were evaluated using the MR-Egger intercept test, Cochran’s Q test, and leave-one-out analysis. Horizontal pleiotropy was not present, according to the MR-Egger intercept test (P > .05). Heterogeneity was detected, according to the Cochran’s Q test P-value < .05, which was deemed acceptable given that our primary outcome was the random-effect IVW.[22] Leave-one-out analysis confirmed that deletion of a single SNP did not significantly affect the results. Furthermore, no significant positive causal relationship was identified between childhood obesity and either left or right HGS or ALM (see Fig. S2, Supplemental Digital Content, https://links.lww.com/MD/Q180 for detailed MR analysis results).

3.2. Causal effects of sarcopenia-related traits on childhood obesity

We eliminated outliers and adjusted for possible confounding variables using the MR-PRESSO methodology. The rise in WP and increased risk of childhood obesity began were found to be causally related, according to IVW analysis (OR = 0.215, 95% CI: 0.047–0.976, P < .05). The presence of heterogeneity was indicated by the Cochran’s Q test P-value of <.05. Heterogeneity can be tolerated because the main consequence is random-effects IVW.[22] The MR-Egger intercept test revealed no horizontal pleiotropy, with all values being P > .05. The leave-one-out analysis indicates that eliminating 1 SNP has no effect on the directionality of the results; in other words, eliminating any SNP has no discernible effect on the outcomes. ALM, left and right HGS, and childhood obesity did not significantly correlate in a reverse causal manner (see Fig. S3, Supplemental Digital Content, https://links.lww.com/MD/Q180 for the full MR analysis results).

4. Discussion

This study aimed to explore the potential causal relationship between childhood obesity and sarcopenia-related traits by employing a MR analytical framework to overcome the confounding and reverse causality issues inherent in traditional observational studies. Our core findings reveal a unique bidirectional relationship between childhood obesity and a specific indicator of muscle function and walking speed but do not support a significant causal association between “sarcopenia” as a comprehensive diagnosis and childhood obesity.

Our positive MR analysis indicated that childhood obesity, as an exposure factor, had a significant negative impact on the outcome of “walking speed” (OR = 0.982, 95% CI: 0.966–0.998, P < .05). This result suggests that an increase in genetically predicted childhood obesity is a potential causal factor leading to reduced walking speed. An OR value <1 and an upper limit of the 95% confidence interval of <1 point indicated a negative relationship. This aligns with extensive epidemiological evidence suggesting that obesity may influence muscle function through various physiological mechanisms, such as inducing chronic low-grade inflammation,[29] disrupting muscle protein synthesis,[30] increasing skeletal and joint loads leading to mobility impairments and pain,[31] and adversely affecting muscle energy metabolism through insulin resistance.[32] These combined effects are likely to ultimately manifest as specific functional impairments such as slowed walking speed.

In the results of the inverse MR analysis, when “walking speed” was used as the exposure, we found that faster walking speed significantly reduced the risk of childhood obesity (OR = 0.215, 95% CI: 0.047–0.976, P < .05). This OR value was far <1, and the 95% confidence interval was <1, providing strong evidence supporting the causal inference that faster walking speed is a protective factor against childhood obesity. This finding suggests that improving walking ability is crucial for preventing or reducing childhood obesity. Therefore, walking can serve as an effective form of exercise for children with obesity.[33] In a retrospective study, effective walking speed was found to significantly improve muscle function and physical performance, with positive effects on muscle mass and bone density.[34] However, sarcopenia is defined by the simultaneous presence of low muscle mass, low muscle strength, and low walking speed.[35] While our study identified a clear bidirectional causal association between walking speed and childhood obesity, it is only 1 of the 3 necessary components of sarcopenia. Both forward and reverse MR analyses did not directly test the “muscle mass” and “muscle strength” indicators that constitute the core definition of sarcopenia, and based on a single positive result, we cannot conclude that there is a significant causal relationship between sarcopenia and childhood obesity. This suggests that the impact of obesity on muscle health or the impact of muscle health on obesity may be more directly reflected in specific functional aspects rather than strictly defined sarcopenia. This also suggests that, when assessing the impact of obesity on children’s muscle systems or identifying intervention points for obesity, focusing on functional indicators may have greater clinical significance.

In summary, the most important finding of this study is the establishment of walking speed as a causal factor and potential predictor of childhood obesity: childhood obesity is an independent causal factor leading to reduced walking speed; faster walking speed significantly reduces the risk of childhood obesity in a causal relationship. Although this conclusion does not support a direct causal relationship between sarcopenia and childhood obesity, the clear bidirectional causal relationship between walking speed, a core component of sarcopenia, and obesity has important clinical implications. Walking speed can serve as a functional indicator for childhood obesity screening, risk assessment, and the evaluation of intervention outcomes.

This study had several limitations. First, although MR can effectively control for confounding and reverse causality, it requires 3 core assumptions (associativity, independence, and exclusivity) to be met. Although we used high-quality pooled data and sensitivity analysis methods to test for these assumptions, we cannot completely rule out potential multivariability or genetic confounding. Because of sample size limitations and the exploratory character of bidirectional testing, we did not use formal multiplicity adjustments (such as Bonferroni or Benjamini-Hochberg) in primary analyses; therefore, results that satisfy the nominal significance criterion (P < .05) should be interpreted cautiously. Replication in separate cohorts is necessary for robust findings, and strict correction techniques should be given top priority in future research. Second, the data were derived from a public database primarily composed of individuals of European ancestry; therefore, caution is needed when generalizing the results to other populations. Third, walking speed is a component of sarcopenia; however, causal exploration of other core components (muscle strength and muscle mass) is an important direction for future research. Finally, the definitions and measurement methods for BMI and walking speed in childhood may vary depending on the age and developmental stage. Future studies should explore age- and sex-stratified effects, as metabolic development and muscle maturation trajectories differ significantly across childhood and adolescence. The study should include data from a broader racial population, utilize longitudinal designs to directly explore the dynamic causal relationship between changes in childhood BMI and the evolution of walking speed, and investigate the precise effects of specific interventions in preventing childhood obesity and improving muscle function.

5. Conclusion

MR analysis confirmed that childhood obesity is a significant causal factor for reduced walking speed (OR = 0.982, P < .05), and faster walking speed can significantly prevent the occurrence of childhood obesity (OR = 0.215, P < .05). Although walking speed, as one of the core indicators of sarcopenia, has a bidirectional causal relationship with obesity, sarcopenia diagnosed through a comprehensive assessment has no significant causal relationship with childhood obesity. Therefore, walking speed can serve as an independent and practical indicator for screening for childhood obesity, assessing muscle function, and monitoring the effectiveness of interventions.

Author contributions

Conceptualization: Mengyan Zhao, Tao Guo, Chaoyang Liu.

Data curation: Mengyan Zhao, Chaoyang Liu.

Formal analysis: Mengyan Zhao, Chaoyang Liu.

Visualization: Mengyan Zhao.

Writing – original draft: Mengyan Zhao.

Writing – review & editing: Mengyan Zhao, Tao Guo.

Supplementary Material

medi-105-e44812-s001.pdf (1.2MB, pdf)
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Abbreviations:

ALM
appendicular lean mass
CI
confidence interval
GWAS
genome-wide association studies
HGS
hand grip strength
IV
instrumental variable
IVW
inverse-variance weighted
MR
Mendelian randomization
MR-PRESSO
Mendelian randomization Pleiotropy RESidual Sum and Outlier
OR
odds ratio
SE
standard error
SNP
single-nucleotide polymorphisms
WP
walking pace

National Natural Scientific Foundation of China, Grant/Award Number: 82260431. Basic plan project of Guizhou Provincial Science and Technology Department, Grant/Award Number: ZK [2022] Normal 247. Guizhou Province Science and Technology Support Plan, Guizhou Science and Technology Cooperation Support [2023] General 196. Guizhou Provincial People’s Hospital, Grant/Award Number: GZSYBS [2021] 05.

The authors have no conflicts of interest to disclose.

The datasets generated during and/or analyzed during the current study are publicly available.

Supplemental Digital Content is available for this article.

How to cite this article: Zhao M, Guo T, Liu C. Exploring the impact of childhood obesity on sarcopenia-related traits: A 2-way Mendelian randomization analysis. Medicine 2026;XX:XX(e44812).

Contributor Information

Mengyan Zhao, Email: zmy0193@163.com.

Chaoyang Liu, Email: 976903029@qq.com.

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