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Mr. Akil Hossain, a 45-year-old man, had been battling diabetes and kidney stone for two years. After consulting a clinical dietitian and following specific dietary and lifestyle changes, he recovered within a year. Motivated by his improvement, he suggested the same regimen to others with similar conditions. Unfortunately, their health worsened, highlighting a crucial point: what works for one individual may not work for another. This case underscores the necessity of personalised care in treating chronic illnesses, as a universal approach is often ineffective.
This is where precision nutrition comes into play. Precision nutrition is a cutting-edge approach in nutritional science that customises dietary recommendations based on an individual's unique traits, including genetics, microbiome composition, metabolic profile, health status, physical activity, dietary habits, food environment, and socioeconomic and psychosocial factors. By leveraging advanced technologies like Artificial Intelligence (AI) and Big Data Analytics, precision nutrition aims to enhance health through tailored dietary guidelines.
Also known as personalised nutrition, precision nutrition recognises that each person has unique genetic traits, gut microbiota, lifestyle, and dietary habits. Therefore, their nutritional needs are also unique. AI and Big Data Analytics are crucial in this approach, processing large amounts of data to generate individualised nutritional recommendations. By examining genetics, gut microbiota, physical activity, and other relevant information, these technologies provide comprehensive nutritional guidelines specific to each person.
Several factors are considered in formulating these individualised recommendations, including:
Personal Data and Genetics: Understanding the impact of genes on the body.
Nutrigenomics: Exploring how nutrients influence genetic expression.
Clinical and Biochemical Parameters: Assessing health markers.
Gut Microbiota: Analysing the microbial population in the gut.
Physical Activity Levels: Evaluating daily activity patterns.
Meal Timing and Nutrient Content: Considering the timing and
composition of meals.
Dietary Intake Data: Reviewing dietary habits.
Metabolic Patterns: Understanding biochemical reactions like glycolysis and the TCA cycle.
Medical and Family History: Considering personal and familial health histories.
Interactome: Examining interactions between drugs and nutrients.
Proteome, Transcriptome, and Anatomy: Studying proteins, RNA, and body structure.
State of Mind and Cognition: Assessing mental health.
Anthropometric Data: Measuring body dimensions (weight, height, midupper arm circumference).
Bibliome: Utilising relevant literature.
The process begins with collecting this information, which is then integrated and analysed by AI and big data analytics to produce precise, individualised nutritional recommendations. This approach holds significant potential for improving health and nutritional status on a personalised level.
Precision nutrition challenges traditional nutritional recommendations by emphasising personalised care. The future of nutrition science will likely rely heavily on AI and Big Data Analytics. As AI-powered tools like ChatGPT, Gemini AI, and Bing AI gain popularity, the role of AI in nutrition is set to expand. In the near future, personal AI chatbots could offer precise nutritional advice based on an individual’s history and habits, transforming smartphones into personal dietitians.
The demand for AI-driven nutrition education is expected to rise. Graduates with a combination of technological skills (AI, Big Data, and Machine Learning literacy) and degrees in Applied Nutrition, Nutrition Science, or related fields will be highly sought after.
Despite its potential, challenges such as a shortage of skilled personnel, high costs, and privacy concerns remain. Overcoming these obstacles is essential to successfully implementing precision nutrition on a larger scale.
In summary, the future of nutritional science is shifting towards personalised approaches. Precision nutrition, supported by artificial intelligence, is emerging as a revolutionary method for tailoring dietary advice to individual needs. This field is just beginning to unfold, offering exciting and limitless possibilities.
The writer is a Lecturer, Department of Food Engineering and Nutrition Science, State University of Bangladesh. He can be reached at: [email protected].
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