García-Perea Aquilino, Fernández-Cruz Edwin, de la O-Pascual Victor, Gonzalez-Zorzano Eduardo, Moreno-Aliaga María J, Tur Josep A, Martinez J Alfredo
General Council of Pharmaceutical Associations, 28001 Madrid, Spain.
IMDEA-Food Institute (Madrid Institute for Advances Studies), 28049 Madrid, Spain.
Medicina (Kaunas). 2024 Apr 8;60(4):610. doi: 10.3390/medicina60040610.
Modern classification and categorization of individuals' health requires personalized variables such as nutrition, physical activity, lifestyle, and medical data through advanced analysis and clustering methods involving machine learning tools. The objective of this project was to categorize Mediterranean dwellers' health factors and design metabotypes to provide personalized well-being in order to develop professional implementation tools in addition to characterizing nutritional and lifestyle features in such populations. A two-phase observational study was conducted by the Pharmacists Council to identify Spanish nutritional and lifestyle characteristics. Adults over 18 years of age completed questionnaires on general lifestyle habits, dietary patterns (FFQ, MEDAS-17 p), physical activity (IPAQ), quality of life (SF-12), and validated well-being indices (LS7, MEDLIFE, HHS, MHL). Subsequently, exploratory factor, clustering, and random forest analysis methods were conducted to objectively define the metabotypes considering population determinants. A total of 46.4% of the sample ( = 5496) had moderate-to-high adherence to the Mediterranean diet (>8 points), while 71% of the participants declared that they had moderate physical activity. Almost half of the volunteers had a good self-perception of health (49.9%). Regarding lifestyle index, population LS7 showed a fair cardiovascular health status (7.9 ± 1.7), as well as moderate quality of life by MEDLIFE (9.3 ± 2.6) and MHL scores (2.4 ± 0.8). In addition, five metabotype models were developed based on 26 variables: Westernized Millennial (28.6%), healthy (25.1%), active Mediterranean (16.5%), dysmetabolic/pre-morbid (11.5%), and metabolically vulnerable/pro-morbid (18.3%). The support of tools related to precision nutrition and lifestyle integrates well-being characteristics and contributes to reducing the impact of unhealthy lifestyle habits with practical implications for primary care. Combining lifestyle, metabolic, and quality of life traits will facilitate personalized precision interventions and the implementation of targeted public health policies.
现代对个人健康的分类和归类需要通过涉及机器学习工具的先进分析和聚类方法，利用营养、身体活动、生活方式和医学数据等个性化变量。该项目的目标是对地中海居民的健康因素进行分类，并设计代谢型以提供个性化的健康状态，以便除了描述此类人群的营养和生活方式特征外，还能开发专业的实施工具。药剂师委员会进行了一项两阶段观察性研究，以确定西班牙人的营养和生活方式特征。18岁以上的成年人完成了关于一般生活习惯、饮食模式（食物频率问卷、地中海饮食评估量表-17项）、身体活动（国际体力活动问卷）、生活质量（简短健康调查问卷-12项）以及经过验证的健康指数（生活满意度量表7项、地中海生活健康量表、健康与幸福量表、心理健康量表）的问卷调查。随后，进行了探索性因素分析、聚类分析和随机森林分析方法，以考虑人群决定因素客观地定义代谢型。样本中共有46.4%（n = 5496）的人对地中海饮食有中度至高依从性（>8分），而71%的参与者表示他们有适度的身体活动。几乎一半的志愿者对健康有良好的自我认知（49.9%）。关于生活方式指数，人群的生活满意度量表7项显示心血管健康状况一般（7.9±1.7），地中海生活健康量表的生活质量中等（9.3±2.6），心理健康量表得分中等（2.4±0.8）。此外，基于26个变量开发了五种代谢型模型：西化千禧一代型（28.6%）、健康型（25.1%）、活跃地中海型（16.5%）、代谢异常/病前型（11.5%）和代谢脆弱/病前型（18.3%）。与精准营养和生活方式相关的工具的支持整合了健康特征，并有助于减少不健康生活习惯的影响，对初级保健具有实际意义。结合生活方式、代谢和生活质量特征将有助于个性化精准干预和有针对性的公共卫生政策的实施。
