Sex-specific Differences in the Association Between Leg Fat and Diabetes Risk

Sex-specific Differences in the Association Between Leg Fat and Diabetes Risk: The Mediating Role of Visceral Adipose Tissue

This study investigates the association between LFP, VAT and T2DM using DXA in 542 adults. We apply penalized regression, generalized additive models (GAM), and causal mediation analysis to explore whether higher LFP reduces diabetes risk and whether this effect is mediated by VAT. Sex-specific analyses further clarify the biological differences in adipose distribution. The findings aim to improve understanding of fat distribution and metabolic health.

Study Overview

• Status: Completed
• Conditions: Diabetes Mellitus; Body Fat Distribution; Visceral Adipose Tissue
• Intervention / Treatment: Other: Not Applicable - Retrospective study

Detailed Description

T2DM is a major public health concern, and growing evidence suggests that not all body fat confers equal metabolic risk. Beyond total adiposity, the regional distribution of fat strongly influences insulin resistance and diabetes development. VAT is metabolically detrimental, promoting inflammation and lipotoxicity, whereas lower-body subcutaneous fat, particularly in the legs and gluteofemoral region, may exert protective metabolic effects by serving as a "safe storage" depot for excess lipids. However, the causal mechanisms underlying these associations remain incompletely understood, and whether the protective role of LFP differs by sex remains unclear.

This study aims to elucidate the metabolic and causal pathways linking LFP, VAT, and diabetes risk in adults. Using DXA for precise body composition assessment, the study evaluates the associations between LFP, VAT, and T2DM prevalence, with a focus on sex-specific effects. A total of 542 adult participants will be analyzed, including both men and women with and without T2DM. Clinical, biochemical, and anthropometric data will be collected concurrently.

The analytic framework integrates multiple complementary approaches:

1. Penalized regression models (LASSO, ridge, elastic net) will identify the most predictive adiposity components for T2DM while minimizing collinearity.
2. GAMs will examine potential nonlinear relationships between LFP, VAT, and diabetes risk, separately for male and female.
3. Causal mediation analysis will quantify the extent to which VAT mediates the relationship between LFP and diabetes, providing mechanistic insight into adipose redistribution pathways.
4. Inverse-probability-of-treatment weighting (IPTW) will strengthen causal inference by balancing covariates across LFP strata.
5. Two-sample Mendelian randomization (MR) will further test the causal effect of genetically predicted LFP on T2DM risk using summary-level genome-wide association data.

We hypothesize that higher LFP will be associated with lower diabetes risk and that this protective effect will be partially mediated by reduced VAT accumulation, particularly in females.

This study integrates imaging-based body composition, causal modeling, and genetic validation to bridge observational and causal evidence. The findings are expected to improve the understanding of sex-specific fat distribution in metabolic health and support the development of personalized prevention strategies targeting regional adiposity rather than total body fat.

• Study Type: Observational
• Enrollment (Actual): 542

Contacts and Locations

Study Locations

• China
  • Jinan, China
    • The First Affiliated Hospital of Shandong First Medical University

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

Adults who underwent DXA examination and had complete clinical and biochemical data.

Description

Inclusion Criteria:

Adults (≥18 years old)

Available DXA measurement of fat distribution

Complete fasting glucose or diabetes diagnosis record

Exclusion Criteria:

• Missing key variables (fat distribution, diabetes status)

Severe systemic disease interfering with data integrity

Implausible or inconsistent records

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
diabetes group; Participants diagnosed with type 2 diabetes based on clinical guidelines, including elevated fasting plasma glucose (FPG) and/or HbA1c levels. This group will help assess how regional fat distribution (particularly leg-fat percentage) correlates with T2D risk.	Other: Not Applicable - Retrospective study; Not Applicable - Retrospective study
non-diabetes group; Participants without T2DM, with normal glucose metabolism and no history of insulin resistance. This group is used as a reference for comparing the metabolic effects of adipose distribution with the T2DM group.	Other: Not Applicable - Retrospective study; Not Applicable - Retrospective study

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Prevalence of diabetes in relation to lower extremity fat	T2DM will be defined according to standard diagnostic criteria (fasting plasma glucose ≥ 7.0 mmol/L and/or HbA1c ≥ 6.5%, or a physician diagnosis). The primary outcome is the association between LFP and diabetes status, estimated using multivariable logistic regression and causal mediation analysis.	Baseline

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Mediating Effect of VAT	Quantification of the indirect effect of VAT in the association between LFP and T2DM risk, estimated via causal mediation analysis.	baseline
Sex-specific Differences in the LFP-T2D Association	Evaluation of whether the association between LFP and diabetes risk differs between males and females using sex-stratified models and interaction testing.	Baseline

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
Nonlinear Relationship Between LFP/VAT and T2D Risk (GAM Analysis)	Characterization of potential nonlinear (threshold or saturation) relationships between LFP, VAT, and diabetes risk using generalized additive models (GAMs).	baseline
Causal Association Between Genetically Predicted LFP and T2D (Mendelian Randomization)	Two-sample Mendelian randomization (MR) using genome-wide association study (GWAS) summary statistics to test the causal effect of genetically predicted LFP on T2D risk.	baseline

Collaborators and Investigators

• Sponsor: Qianfoshan Hospital
• Investigators: Principal Investigator: Xuan Song, Shandong First medical university

Study record dates

Study Major Dates

• Study Start (Actual): December 31, 2024
• Primary Completion (Actual): February 12, 2025
• Study Completion (Actual): August 10, 2025

Study Registration Dates

• First Submitted: September 9, 2025
• First Submitted That Met QC Criteria: November 28, 2025
• First Posted (Estimated): December 3, 2025

Study Record Updates

• Last Update Posted (Estimated): December 3, 2025
• Last Update Submitted That Met QC Criteria: November 28, 2025
• Last Verified: September 1, 2025

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Endocrine System Diseases; Metabolic Diseases; Glucose Metabolism Disorders; Nutritional and Metabolic Diseases; Diabetes Mellitus
• Other Study ID Numbers: S877

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No