NutriNet-Brasil, a web-based prospective study on dietary patterns and risk of chronic diseases: cohort profile

NutriNet-Brasil,一项基于网络的关于饮食模式与慢性病风险的前瞻性研究:队列概况

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Abstract

PURPOSE: Non-communicable diseases (NCDs), such as diabetes, cardiovascular diseases and cancer, are major global public health concerns. Diet quality-particularly the consumption of ultra-processed foods-has been associated with increased risk of NCDs. Traditional cohort studies are often expensive and logistically complex. The NutriNet-Brasil cohort leverages a web-based approach, offering a cost-effective and practical solution for comprehensive data collection and long-term follow-up. PARTICIPANTS: Recruitments began in January 2020 through mass media, social media campaigns and collaborations with health organisations. Eligible participants are adults (aged ≥18 years) living in Brazil with internet access. Participants complete self-administered online questionnaires covering dietary intake, health status and other health determinants. Dietary assessment is based on the Nova classification system, which categorises foods by their level of processing. FINDINGS TO DATE: Over 88 000 participants have completed the initial questionnaire. The cohort is predominantly women (79.9%) and highly educated (67.9% had completed higher education). The web-based design enabled the development and application of innovative dietary assessment tools, including the Nova24h and the Nova24hScreener, specifically designed to evaluate food processing levels. These tools have shown good performance in capturing dietary patterns and are central to the cohort's aim. The online platform facilitates efficient recruitment, data collection and participant retention. FUTURE PLANS: NutriNet-Brasil is pioneering the development of web-based cohort methodologies and instruments tailored to food processing research. Future work includes leveraging collaborations with national and international research centres to conduct multidisciplinary analyses and inform public health policies.

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