Nutrition is very important to keep blood sugar levels balanced. If blood sugar levels are too high, it can lead to diseases such as cardiovascular disease and type 2 diabetes (T2DM). Therefore, adjusting what one eats, also called a diet or nutritional intervention, can help prevent these diseases. However, not everyone responds the same to a diet. In about 30% of people, a diet does not work as hoped. This can be due to various reasons, such as a person's metabolism, genetic predisposition, the composition of the food one eats, or the bacteria in the intestines. Everyday things like sleep, stress, and movement also play a role. The investigators used a computer model to classify people with overweight and obesity into groups based on these factors. The investigators call such a group a 'Metabolic Phenotype', or in short 'Metabotype'. Based on the Metabotype, a personalised diet was developed (personalised nutrition intervention) that may better suit each person's unique situation. The investigators hypothesize that a precision nutrition intervention, tailored to Metabotypes identified through unsupervised clustering (using the aforementioned computer model) of predefined, accurate features related to cardiometabolic health-specifically, tissue-specific glucose and lipid metabolism and detailed body composition-will enhance blood glucose homeostasis, reduce cardiometabolic risk, and improve adherence to the intervention and mental well-being, compared to population-based dietary guidelines. The present project will contribute to targeted and efficient precision-based dietary strategies for individuals at increased risk of T2DM.