Gender Differences in Dietary Patterns and Physical Activity: A PCA Approach

The study was designed as a cross-sectional analysis of gender differences in dietary patterns and physical activity, utilizing Principal Component Analysis (PCA) to identify distinct behavioral groups. A total of 2,509 participants were recruited from a metabolic health center in Rome, Italy, between May 2023 and June 2024. The study collected detailed data on eating habits, physical activity, and body composition through questionnaires and bioimpedance analysis. Five distinct behavioral groups were identified through PCA, with significant differences in dietary patterns and physical activity levels between men and women. Men were found to consume more meat and participate in strength training, while women favored vegetable-rich diets and had more structured eating routines. These differences also translated into body composition, with men having more lean mass and women more fat mass.

The study highlights the importance of gender-specific interventions in nutrition and physical activity to improve metabolic health outcomes. The results suggest that men could benefit from increased vegetable consumption, while women could benefit from engaging in more physical activity, particularly strength training. Future research should explore these patterns longitudinally to better understand how these behaviors evolve over time and to develop more tailored interventions.

Inclusion criteria

• Adults aged 18 years or older.
• Participants attending the metabolic health center in Rome, Italy.
• Participants who provided informed consent.
• Participants with complete data on dietary patterns, physical activity, and body composition.

Exclusion criteria

• Individuals under 18 years of age.
• Participants with diagnosed psychiatric disorders.
• Pregnant women.
• Participants with incomplete or inconsistent data.
• Individuals with alcohol dependence.
• Participants with significant medical conditions that could affect dietary or physical activity assessments (e.g., severe chronic illnesses).