[wgd]

The obvious objection to almost every study of this sort is that associated with doesn't imply causality, and it could be that some third factor like "propensity to consume highly-processed food products" is responsible for the observed correlation. But from the abstract:

> Associations between sweeteners and cancer incidence were assessed by Cox proportional hazards models, adjusted for age, sex, education, physical activity, smoking, body mass index, height, weight gain during follow-up, diabetes, family history of cancer, number of 24-hour dietary records, and baseline intakes of energy, alcohol, sodium, saturated fatty acids, fibre, sugar, fruit and vegetables, whole-grain foods, and dairy products

So I have a more interesting question here: how effective are these sorts of statistical methods? Is it plausible to start out with a highly-biased population [1], adjust for twenty or so distinct factors, and get results that are actually meaningful?

[1] As I understand it, the study population consists of 102k French adults, self-selected via finding the relevant website and their willingness to go fill out a bunch of surveys. As TFA notes "[...] 78.5% of the participants included in the analysis were women, which could be considered a selection bias. Additional biases noted by the researchers were that participants were more likely to have higher educational levels, and to demonstrate health-conscious behaviors."

[slymon99]

> some third factor like "propensity to consume highly-processed food products" is responsible

Even with the significant controls in the study, I still completely believe this is the case. People who avoid artificial sweeteners likely make many other health-promoting decisions (healthy user bias) that are far too granular to control against using simple factors like weight and smoking status. The HR is only 1.15. Are you really confident enough in the controls to see this as a real association?

[greatpatton]

"how effective are these sorts of statistical methods?"

Exactly they are so many variables to take into account that each population subset is becoming very small. I would love to have the insight of a stats nerd on the study.

Btw if you look at the raw data, they are for instance less cases per subject in the high consumer than in the low or none consumer (table 2), but they get a higher hazard ration, meaning that other correction were taken into account. It is very difficult to interpret such results.

[throwawaycities]

There is research showing artificial sweeteners can spike insulin, so even if not the cause but coincidentally associated with highly processed foods which are more closely linked to the cause of cancer itself, by triggering insulin spikes artificial sweeteners would feed/enlarge cancer cells.