A multivariate analysis of fatness and relative fat patterning

Area of Science:

• Anthropometry
• Human Biology
• Obesity Research

Background:

• Body composition analysis is crucial for understanding health and disease.
• Previous studies have explored body fat distribution but lacked comprehensive multivariate analysis.
• Understanding fat patterning and its determinants is essential for public health initiatives.

Purpose of the Study:

• To identify components of obesity and relative fat patterning using principal components analysis.
• To investigate the influence of age, sex, and socioeconomic status on fatness and fat patterning.
• To explore the familial resemblance of fatness and fat patterning.

Main Methods:

• Skinfold measurements were taken from four samples in rural Colombia (boys, girls, men, women).
• Principal components analysis was used to identify components of fatness and relative fat patterning.
• Canonical correlation analysis examined relationships between socioeconomic status and body composition.

Main Results:

• Three consistent components emerged across samples: fatness (70-80% variance), trunk-extremity pattern (10-15%), and upper-lower body pattern (10-15%).
• Fatness and trunk-extremity patterns varied with age in children but not adults.
• Higher fatness correlated with greater patterning, and familial resemblance was observed for both fatness and patterning, suggesting genetic influence.

Conclusions:

• Principal components analysis is a valuable tool for quantitative anthropometric studies.
• Body fatness and patterning have distinct components with varying influences from age and genetics.
• Socioeconomic status is more closely linked to overall fatness than to fat distribution patterns.