From a Cambridge nutritional epi class to a letter in PHN

Created on February 18, 2026

2026   ·   TikTok   food-marketing   nutritional-epidemiology   Cambridge   ·   research-journey

This one came out of my MPhil dissertation work on ultra-processed foods, supervised by Mike Essman and Jean Adams at Cambridge. Reading widely around UPFs and the food environment for the dissertation, I kept running into TikTok food-marketing surveillance papers — careful methodology, but the implicit step from “content prevalence” to “adolescent exposure” bothered me.

On algorithm-driven platforms, what creators post is not what teenagers see. The platform decides. A handful of high-view posts can drive most of the actual exposure; a much larger number of low-view posts can drive almost none. Sampling content does not give you exposure unless you weight by views.

Conversations with Mike, Jean, and other colleagues across the MRC Epidemiology Unit and CEDAR sharpened the argument. I wrote it up as a letter. Public Health Nutrition published it.

The proposal is methodological: surveillance studies should report view-weighted prevalence, bounded sensitivity analysis for missing nutrient data, and audit multi-product appearances. None of these require platform-side data access; they make the inference defensible.

Letter in Public Health Nutrition, 2026: link.



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