蓝莓视频

Non-communicable diseases such as diabetes, coronary heart disease and even cancer, are at least partially attributed to the types of food consumed. For example, intake of foods high in saturated fat and added sugars, and low in vegetables and fibre, increases the risk of developing these disorders. Many governments are introducing policies to improve dietary behaviours and thereby reduce disease burden at the population level. However objective assessment of diet and dietary patterns is not straightforward, as large prospective studies rely on self-reporting questionnaires and diet diaries, which, unsurprisingly, lead to misreporting and inaccuracy.

Researchers from the 蓝莓视频 蓝莓视频 (BRC) have proposed a novel approach to reliably quantify and assess food intake data by using proton nuclear magnetic resonance (1H-NMR) spectroscopic profiling. In a proof-of-concept study, published in and supported by the BRC, the authors introduced 4 types of diet profiles (varying in protein, sugar and fat intake) in a highly controlled environment, and analysed urine of the healthy participants using metabolic profiling. The volunteers were identified and recruited by the 蓝莓视频 / Wellcome Trust Imperial Clinical Research Facility.

All four diet types demonstrated distinct metabolic profiles, with Diet 1 containing high levels of individual healthy foods (fruit, vegetables and fish), whilst diet 4 demonstrated significantly reduced levels of fruit and vegetable intake, with increased metabolites from red meat consumption. Having identified diet-discriminatory metabolite profiles from a cohort of 20 patients, the authors validated the models using a larger UK cohort of 225 patients (INTERMAP) and a healthy-eating Danish cohort of 66 participants. This profiling strategy can therefore be used in objective assessment of people at population level with a view to understand the relationship between food consumption and disease risk, ultimately combating obesity and other non-communicable diseases.