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Comment by cosmicvarion | Hacker News Reader

I haven't dug into their controls, but it seems to me that higher altitude may be associated with remoteness.

Are Denver and SLC considered remote? My own city is about at sea level, but by car the next closest cities are 3 hours to the north, 6 hours to the east, and 9 hours to the south. I’d say we are more remote, despite being at a much lower elevation.

Denver and SLC are reasonably big cities. If you need, for example, a big-city childrens' hospital, they have them.

Then you start to drive out of town, and there is N O T H I N G. I mean, from SLC, there's Ogden and Provo, maybe Park City. From Denver, there's Colorado Springs and Fort Collins. Once you get past those, it's a long way to the next anywhere.

So are they isolated? Depends on how you define isolation. Does that particular kind of isolation affect depression and/or suicide? No clue.

Maybe isolation would be another variable that correlates to extreme altitude regions

I live in that "long way to anywhere" zone (a day's drive from both Salt Lake and Denver). Lots of suicide here (annual 41 deaths by suicide per 100,000 people).

Then it would be interesting to compare those cities to my own. If you leave the metro area, there is basically nothing in any direction for many hundreds of miles. But our elevation is at sea level instead of elevated.

I think he is equating remote and rural. Essentially, not as much human contact, more separation from the world, and lack of socialization.

Also altitude’s correlation with climate.

I'd say Utah and Colorado probably have better climate due to their elevation. If they were at sea-level they would probably be insanely hot.

They controlled for population density

That's not the same thing. A town in the middle of nowhere Appalachia is much more remote than sparse suburbs twenty miles from a city. Hell, you might find higher density in some remote towns than eg Farmville Iowa.

Plus, depending how you measure it, "population density" can be a nearly useless metric. County-level population density is spread widely over 3 orders of magnitude. The smallest county has 64 people and the largest has ten million.

My wife's job took us to a small rural city. By population size and density, we weren't that small. The metro area was 60k+ people. However, we were a 3 hours drive from any major city.

To me this panned out in two ways:

* There really wasn't a lot to do outside a 10 mile radius. Anything worth doing was 1 to 2+ hours drive (often more). That meant nearly everything we did was in the small city we lived in.

* Travel was frustrating. We essentially had to pay a 3 hour driving tax on every trip we took.

In other words, despite living in a "suburban" density city (with some urban density areas), it was really how our city was positioned relative to other cities that determined it's feeling. It wasn't large enough to explore internally.

Controlling for population density doesn't control for the impact of population density on the issue at hand, as these are two different factors which are related and which are named very similarly.

Consider this simplified example.

11 areas. 10 of these are isolated and have 10 people living in each area. The last area has 100,000 people living in it. Of those 10 areas, 9 have 0 incidents, and 1 has 1 incident. In the 100,000 area, there are 100 incidents.

Not controlling for the population: The populated area has 100 incidents, the isolated areas have an average of 0.1 incidents. A 1,000 times difference. Populated area is much more dangerous.

Well that's obviously the wrong way to look at the data, so lets account for population:

Isolated areas have a rate of 1 per 100 population, populated areas have a rate of 1 per 1,000 population. A 10 times difference, in the opposite direction. So now we have established a link between being isolated and have more incidents, but we don't know why.

We still haven't controlled for the impact of population density on incident rates. We need much more data to solve this, as with the given information the result would be "Isolated areas have 10 times the risk of incidents" and then controlling for that factor we would see no more trends in our data. If we added thousands of more areas with different levels of population, calculate the per capita rate of incidents in each population, and then create an analysis of how populate density relates to incident rates, we could then control for both factors. The catch is that this last step is more difficult without enough data and often researchers aren't able to isolate single individual items to control for because they correlate too strongly with other issues.

Terrain also means more jumping opportunities, so you’d need to break down by cause.

They said there's a clear pattern both for suicides in general and suicides by firearm.

Did they do a study in Colombia or Mexico?

From the headline: in 2584 U.S. Counties

Nope.

From the article:

Increased altitude has recently been shown to have a protective association with certain medical illnesses, with apparent decreases in mortality among patients with end-stage renal disease receiving dialysis (Winkelmayer et al., 2009), coronary artery disease (Baibas et al., 2005; Faeh et al., 2009), and stroke (Faeh et al., 2009). By contrast, increased altitude may enhance psychiatric disorders, such as panic attacks (Roth et al., 2002).

AND

Controlling for... population density of each county

The mountain West is the most highly urbanized part of the US.

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