Gender Differences in Dietary Patterns and Physical Activity: An Insight With Principal Component Analysis (PCA)
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 2,509
- 试验地点
- 1
- 主要终点
- Principal Component Analysis (PCA)
研究概览
简要总结
This study investigates gender differences in dietary patterns and physical activity using Principal Component Analysis (PCA). It aims to identify distinct eating and activity behaviors between men and women in order to develop gender-specific interventions that promote better metabolic health. The study was conducted at a metabolic health center in Rome, Italy, with 2,509 participants. Data were collected through questionnaires and body composition assessments, and PCA was applied to classify participants into groups based on their behaviors.
详细描述
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.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 18 Years 至 —(Adult, Older Adult)
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •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.
排除标准
- •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).
结局指标
主要结局
Principal Component Analysis (PCA)
时间窗: Cross-sectional assessment at baseline
The primary outcome is the identification of distinct dietary patterns and physical activity behaviors based on gender differences.
次要结局
- Physical activity levels based on gender differences(Cross-sectional assessment at baseline)
研究者
Mauro Lombardo
Mauro Lombardo, MD, Associate Professor in Dietetics and Clinical Nutrition
San Raffaele Telematic University
