This LA Times article, like every article that you ever see discussing any of these results, describes a causation: "sitting cuts about 22 minutes from their life span". None of these "studies" were "experiments" that are capable of demonstrating causation: they are either cohort studies or surveys, and are only able to demonstrate correlation.

In this case, "The authors constructed a life table model that incorporates a previously reported mortality risk associated with TV time. Data were from the Australian Bureau of Statistics and the Australian Diabetes, Obesity and Lifestyle Study, a national population-based observational survey that started in 1999–2000. The authors modelled impacts of changes in population average TV viewing time on life expectancy at birth."

We thereby have to ask, what is the more likely explanation: that sitting causes your life span to decrease, or that the same things that cause your life span to decrease make sitting, or watching television, something you do more often? We aren't doing experiments where we assign people into groups, one which will sit for most of their life and one which will stand/walk, so we can't assume the causation.

Maybe you don't have any friends, and maybe that is why you sit inside all day watching the television. Some people believe being a social outcast directly leads to health issues, but one could also point out that friends often are the people who goad you into seeing the doctor for that thing you never cared enough about, or are quite literally the people who pick you up when you fall, maybe calling 911.

Alternatively, it could be that your life really sucks, and you need the outlet of watching television to make your life feel more reasonable. Things that cause peoples' lives to suck might be abusive relationships, chronic illness, or stressful jobs (and other studies, I believe even real experiments, and I even further believe demonstrated mechanisms, show that stress leads to health problems).

Some might argue "it is easy to control for people who are dying and remove them from your study", but it is very difficult to control for subtle effects, and we are talking about a subtle effect here. This is especially true once you look into compliance effects: people who don't sit around all day watching television are probably also the kinds of people who visit the dentist regularly, or simply eat better food.

The result of this mistake is that it could even be dangerous to be making claims that sitting reduces your lifespan: maybe by telling the people who are sitting around watching television that its unhealthy for them (again, based on no direct evidence) causes them to now feel bad about watching television, increasing their stress, or even causes them to push themselves even further to exercise, when they were sitting down because their knee was already giving out.

A lot of people, at this point, get angry at shoddy science reporting. That's a real problem: articles like this blow studies that are correlations into causations. The result is that people hear every couple years opposing information on some debates they care about (such as whether something like wine or aspirin is "good for your heart"), and eventually decide "it isn't like scientists know anything" and "give it a year, we'll learn something new", something they then apply to other branches of science (like evolution).

But, frankly: the scientists who are publishing these papers really need to use less ambiguous wording--especially if they are not going to be really proactive reaching out to press to be involved in the writing of the articles, making certain the right kinds of hedges get quoted by the reporters (which may scuttle the article, as maybe it is no longer interesting to them: in comparison to bad information spreading, less reporting should be a positive thing)--as I think they are complicit in the confusion.

This paper uses wording that technically doesn't imply a correlation if you know what all of the words mean and you are careful with your reading, but to any normal person they are quite clearly saying "X causes Y": "The amount of TV viewed in Australia in 2008 reduced life expectancy at birth by 1.8 years (95% uncertainty interval (UI): 8.4 days to 3.7 years) for men and 1.5 years (95% UI: 6.8 days to 3.1 years) for women...".

When I read that, I know that that just means "if I'm building a probability distribution over the life expectancy of a person (who would be similar to the people studied, potentially including 'having not heard about this study') and I know how much TV they watch I can use that information to adjust my expectation based on this metric, as established by this well-founded study". However, "X reduced life expectancy" to normal people means "if I do X it will reduce my life expectancy, and if I avoid X, I can avoid that effect".

:(