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An excellent new study demonstrated how analizing a food product based combining 2 key criteria can be used to more accurately identify less healthy foods for policy recommendation:
(i) its ๐ป๐๐๐ฟ๐ถ๐๐ถ๐ผ๐ป๐ฎ๐น ๐๐ฎ๐น๐๐ฒ (๐๐๐ถ๐ป๐ด ๐๐ต๐ฒ ๐๐ต๐ถ๐น๐ฒ๐ฎ๐ป ๐๐๐๐๐ฒ๐บ) to penalize those high in Fat, Salt, Sugar)
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(ii) whether degree of ๐๐น๐๐ฟ๐ฎ-๐ฝ๐ฟ๐ผ๐ฐ๐ฒ๐๐๐ถ๐ป๐ด ย (๐ก๐ข๐ฉ๐) / ๐ฎ๐ฑ๐ฑ๐ถ๐๐ถ๐๐ฒ๐
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It's exactly the philosophy and standards we used to create the algorithm of our GoCoCo food scoring app 5 years ago!
Thank you Juan for helping us create the algorithm. We are delighted ย to see that, instead of opposing 2 approaches (Nutritional value vs. degree of Processing), which are in fact 2 sides of the same coin, this double-lense approach now starts to gain momentum. ๐
๐ Full paper here.
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๐ฒ So while we wait for regulation updates, we consumers can use the GoCoCo food scanning app to help make informed choices and select suggested healthier alternatives. The scoring method not only considers both ultra-processing (UPF) & "high in fat/sugar/salt" (HFSS) approaches, but also a scale, because neither UPF nor HFFS standards are binary criteria.
๐ Our scoring criteria includes:
(๐ถ) ๐ช๐๐ข,
(๐ถ๐ถ) ๐ก๐ข๐ฉ๐ (๐จ๐ฃ๐)
(๐ถ๐ถ๐ถ) ๐๐ต๐ถ๐น๐ฒ๐ฎ๐ป (๐๐๐๐ฆ) ๐น๐ฎ๐ฏ๐ฒ๐น๐ถ๐ป๐ด.
Learn more here.
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Feel free to comment, agree, disagree, provide further details on this topic here.
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