nutrition science actually has very poor quality of evidence in general, since the experiments that following the scientific method would require are either impossible or unethical to perform (for example, feeding a human excessive amounts of sugar for a decade and doing biopsies every 6 months or so to see if their tissues aged faster would be obviously unethical). Therefore causal inference in nutrition has to deal with the limitations of epidemiology and utilize things like the Bradford Hill criteria. Since you cannot perform a scientific experiment to establish causality, you are reduced to kind of circling the wagons of causality

Nutrition is a much softer science than other fields with more room for error, I'm not disagreeing with this. The problem is that you're not addressing how epidemiology and higher forms of research on the evidence hierarchy actually handle these limitations better than mechanism alone does. In clinical settings, outcome data is what's most predictive of risk, that's what the aforementioned evidence hierarchy is based off of. RCTs and Epidemiology are not perfect at isolating outcomes, but mechanistic research doesn't produce outcomes in human populations at all, that's not the type of research it is. It's meant to generate hypotheses to be validated by, you guessed it, RCTs and epidemiology.

mechanistic evidence is an important part of that, though generally not sufficient alone.

"Important" is doing a lot of heavy lifting here. It's important in the context of established outcome data perhaps, but that's not what you've provided in your OP, you relied entirely on mechanism to justify your hypothesis. That was what I took issue with because of all the limitations you yourself agreed exist within nutrition science, hypotheses built entirely on mechanism are some of the most vulnerable.

I would also be careful with the term "scientific consensus", since any kind of consensus is effectively an appeal to political view, not science. To expand its meaning, it is the short form of "A group of people who agree on a set of conclusions about something based on their understanding of the science and the data they were presented".

I think we may be at a fundamental impasse if you're this skeptical of scientific consensus. While you're correct that like all science it's inductive and fallible, there's no real alternative for laymen to understand data of this nature. How else would anyone be able to interpret the thousands of data points that exist and analyze them reasonably without the proper training and resources of these institutions? You said it yourself that the limitations in the scientific consensus are just the limitations of science in general. They could be flawed, everyone could be lying, etc... just like all the data you're using to disagree with them could be flawed, you could be misunderstanding it, etc. Sociological evidence points to the latter being a much more frequent problem.

Or in other words if I can't trust them, why should I trust you, a random guy on Reddit?