Dipartimento di Neuroscienze, Sezione di Biofisica, Università Cattolica del Sacro Cuore, 00168 Rome, Italy.
Fondazione Policlinico Universitario Agostino Gemelli, IRCCS, 00168 Rome, Italy.
Nutrients. 2024 Jun 26;16(13):2021. doi: 10.3390/nu16132021.
The rising obesity epidemic requires effective and sustainable weight loss intervention strategies that take into account both of individual preferences and environmental impact. This study aims to develop and evaluate the effectiveness of an innovative digital biohacking approach for dietary modifications in promoting sustainable weight loss and reducing carbon footprint impact. A pilot study was conducted involving four participants who monitored their weight, diet, and activities over the course of a year. Data on food consumption, carbon footprint impact, calorie intake, macronutrient composition, weight, and energy expenditure were collected. A digital replica of the metabolism based on nutritional information, the Personalized Metabolic Avatar (PMA), was used to simulate weight changes, plan, and execute the digital biohacking approach to dietary interventions. The dietary modifications suggested by the digital biohacking approach resulted in an average daily calorie reduction of 236.78 kcal (14.24%) and a 15.12% reduction in carbon footprint impact (-736.48 gCOeq) per participant. Digital biohacking simulations using PMA showed significant differences in weight change compared to actual recorded data, indicating effective weight reduction with the digital biohacking diet. Additionally, linear regression analysis on real data revealed a significant correlation between adherence to the suggested diet and weight loss. In conclusion, the digital biohacking recommendations provide a personalized and sustainable approach to weight loss, simultaneously reducing calorie intake and minimizing the carbon footprint impact. This approach shows promise in combating obesity while considering both individual preferences and environmental sustainability.
肥胖症的流行趋势不断上升,需要有效的、可持续的减肥干预策略,既要考虑到个体偏好,又要兼顾环境影响。本研究旨在开发和评估一种创新的数字生物黑客技术,用于饮食调整,以促进可持续的体重减轻和减少碳足迹影响。进行了一项试点研究,涉及四名参与者,他们在一年的时间内监测体重、饮食和活动。收集了关于食物消耗、碳足迹影响、卡路里摄入量、宏量营养素组成、体重和能量消耗的数据。基于营养信息的代谢数字复制品——个性化代谢头像(PMA)用于模拟体重变化、计划和执行饮食干预的数字生物黑客方法。数字生物黑客方法建议的饮食调整导致每个参与者平均每天减少 236.78 卡路里(14.24%)的热量摄入和减少 15.12%的碳足迹影响(减少 736.48gCOeq)。使用 PMA 的数字生物黑客模拟显示体重变化与实际记录数据存在显著差异,表明数字生物黑客饮食可有效减轻体重。此外,对实际数据的线性回归分析显示,建议饮食的遵守程度与体重减轻之间存在显著相关性。总之,数字生物黑客的建议为体重减轻提供了个性化和可持续的方法,同时减少卡路里摄入并最小化碳足迹影响。这种方法在考虑个体偏好和环境可持续性的同时,有希望用于对抗肥胖症。