Body fat distribution and aging: Unveiling association and potential intervention strategies.

All body fat distribution indicators were positively correlated with phenotypic age (PhenoAge), with trunk fat mass showing the strongest association.

• Indicators examined included trunk fat mass, limb fat mass, total fat mass, and body fat percentage
• Data from NHANES 2015-2018 was analyzed using weighted linear regression models
• Trunk fat mass exhibited the strongest association among all body fat distribution indicators
• A restrictive cubic spline curve was used to explore potential non-linear relationships between body fat indicators and PhenoAge

Subgroup analyses revealed significant correlations between body fat distribution and PhenoAge across genders, age groups, and BMI categories.

• Subgroup analyses were conducted to examine consistency of associations
• Significant correlations were found across different genders
• Significant correlations were maintained across different age groups and BMI categories
• The findings suggest the relationship between body fat distribution and biological aging is robust across demographic subgroups

C-reactive protein (CRP), the systemic immune-inflammation index (SII), and the triglyceride-glucose index were identified as partial mediators between body fat distribution and PhenoAge.

• Mediation analysis was conducted to identify pathways linking body fat distribution to biological aging
• Three mediators were identified: C-reactive protein, the systemic immune-inflammation index, and the triglyceride-glucose index
• These mediators were described as 'partial' mediators, indicating other pathways also contribute
• The findings suggest inflammatory and metabolic pathways play roles in the body fat-aging relationship

Mendelian randomization analysis supported a causal relationship between body fat distribution and PhenoAge.

• MR analysis was performed using genome-wide association study (GWAS) data
• The MR approach was used to address potential confounding and reverse causality in the observational analysis
• Results from MR analysis were consistent with the observational findings, supporting a causal interpretation
• The causal direction was from body fat distribution to biological aging (PhenoAge)

Two-step Mendelian randomization analysis suggested a potential role of gut microbiota in linking body fat distribution and aging.

• Two-step MR analysis was employed to test gut microbiota as a mediator between body fat distribution and PhenoAge
• Results suggested gut microbiota may act as a pathway connecting body fat distribution and biological aging
• Diet targeting gut microbiota diversity was identified as potentially mitigating the effects of body fat on aging
• Optimizing dietary patterns to enhance gut microbiota diversity was described as 'a promising approach to delaying biological aging'

BMI has limitations in reflecting body fat distribution and its health implications, motivating the use of more precise body fat indicators.

• The study was motivated by the recognized limitations of BMI as a measure of body composition
• More precise indicators used included trunk fat mass, limb fat mass, total fat mass, and body fat percentage
• NHANES 2015-2018 data provided the population-level dataset for these more detailed body composition measurements
• PhenoAge was used as the measure of biological aging