Comment by uniqueuid
2 days ago
It's really good to ask these questions.
I'm not a medial researcher, but my impression is that many fields find it difficult to produce the robust high-level risk comparisons that you ask about. I.e. if you're looking at blood fats, even there you'll find many complicated contextual factors (age, sex, ethnicity, type of lipids i.e. LDL or lp(a) or ...?). The same might be the case for sugar. So it's not really easy/cheap to combine detailed state-of-the-art measurements of different causes into one randomized controlled trial.
As for the effects of sugar, I think there's some evidence that's not too hard to find, e.g. some meta analyses showing something around 10% increase in dose-dependent risk (RR ~ 1.10) [1,2]. A lot of the literature seems to be focused on beverages, e.g. this comparative cross-national study [3].
[1] https://jamanetwork.com/journals/jamainternalmedicine/fullar...
[2] https://www.sciencedirect.com/science/article/abs/pii/S08999...
But is it the actual sugar, or the habits surrounding consumption of the beverage?
That's pretty easy.
If you have a randomized controlled trial, the sugar dose is varied and other confounding variables are controlled by randomization. So you measure the causal impact of sugar only. There are studies showing that.
With observational studies, if you have a dose-dependent effect, then that's good evidence (although not completely conclusive) of a causal relationship. This is what many studies do.
If you have a meta analysis covering many primary studies, and if those vary a lot of context (i.e. countries, year, composition of the population), and you still get a consistent effect, then that's another piece of support for a causal relationship.
The few studies that I've looked at seem to show a pretty robust picture of sugar being a cause, but there might be selection bias - i.e. we'd need an umbrella / meta meta study (which ideally accounts for publication bias) to get the best estimate possible.
Observational studies, and meta analyses relying on them, don't resolve the fundamental problem of causal inference. The best you can do without an experiment is a really clean natural experiment, but those are rare. It's hard to credibly establish a causal relationship without a robust experiment.
What are "the habits surrounding consumption of the beverage?" It's been my observation that soda drinkers drink soda all day, no matter what they are doing.