Show HN: Visualization of Longevity and Mortality

https://www.infino.me/mortality/usmap

by subcosmos • 11 years ago

38 24 11 years ago

subcosmos12• 11 years ago

As lifespan in the modern age continues to increase, it is interesting to dig into the leading causes of death for perspectives on where to put our research efforts.

Made using the dc.js library. It's interactive! You can click on any of the plots to refilter the data.

deckar012• 11 years ago

dc.js seems to support mobile devices[0], why doesn't this visualization?

[0] https://dc-js.github.io/dc.js/

subcosmos12• 11 years ago

I have indeed been chasing an obscure bug. It's not within dc.js itself, but the underlying D3 library.

Sorry mobile users! The best Ive been able to do is show a screenshot for many mobile browsers. Even so, the draw performance is terrible since there is so much data being loaded. While smaller dc visualizations can work on a mobile device, its just too dang slow to show 10's of thousands of records. A laptop however has no problem.

adrianN• 11 years ago

I think it's worthwhile not to put all our efforts into curing a particular cause of death. First because this doesn't necessarily increase quality of live for the elderly, which I think is hugely important. Secondly, because after a certain age all kinds of things break down and the current leading cause of death (eg cancer, heart-disease, alzheimer) is likely just an effect of general accumulation of damage in the body.

subcosmos12• 11 years ago

Agreed completely. My deepest passion is aging biology. What I learned however in studying type II diabetes and obesity, is that the molecular mechanisms are hugely aligned. Its all the same core metabolic genes that the aging biologists focus on in worms and flies. Those are the genes that seem to be related to insulin signaling and diabetes.

My core vision of this project is to better understand this overlap.

xaa3• 11 years ago

Very cool. I think if you added a few more ways of slicing and dicing this data, you would have a decent chance at getting it accepted to a bioinformatics journal. For example, Oxford Journals Bioinformatics has an "Application Note" type of submission for useful programs that aren't quite original research. I work with one of the editors and he was impressed with the interface and thought it would have a good shot at acceptance.

In particular I think there need to be options added to normalize the y-axis of the graph beyond raw counts to percentage of deaths by age group to control for the fact that the number of deaths per bin is not the same.

It would also be nice to add a little more categorization to the causes of death, in a tree-like structure. For example, all vascular disease, with cerebrovascular disease, CVD, etc, as subtypes.

Also it would be nice to be able to ask questions like, "which states have the most (or least) fraction of deaths by, e.g., CVD"? Do some states have smaller or larger gender gaps in particular diseases?

subcosmos12• 11 years ago

I DO have a much larger viz in the works! It lets you cut down by race, year (1999-2013), and a few other metrics. I wanted to put this out first to see how it performs on various devices. Stay tuned!

I come from an academic background. Made this in my PhD: amass-db.org

But my core passion this days is the project that this viz is hosted at (www.infino.me). I think I can make a much bigger impact with more consumer-facing nonprofit apps than in publishing academic articles.

xaa3• 11 years ago

Cool, I am looking forward to an improved version.

I would be interested in your rationale behind how the public would/could use this kind of data. I think the infino.me/health seems to be an example, pointing out major risk factors behind cancer and CVD. But don't you think this is already common knowledge?

Or is the primary goal to get people to voluntarily share their health and genotype data to get a big dataset for analysis, and maybe eventually provide a sort of personalized risk assessment? I wonder how the FDA views that sort of thing.

kbenson• 11 years ago

The age of death graph cuts off the values of the y axis on the left, so all I can see is a bunch of "00,000" values. I can only really make relative assessments to the age groups. :/

subcosmos12• 11 years ago

Im tempted just to turn the axis off and make a box showing total counts. Getting things to line up is always a pain. Yuck!

Thanks for reporting the bug.

varelse5• 11 years ago

Not to sound snarky, but uploading my fitbit data IMO just solved the mystery of obesity (at least for me).

I burn ~3200 calories a day and I walk >10 miles a day. This is the 100th percentile of your data and that floors me.

So I have to say that step 1 is getting people to get off their asses and move. It'd be nice if they cut down on red meat and sugar intake while they were at it, but small steps, no?

subcosmos12• 11 years ago

Well, so this project of mine is in beta, which makes you the 22nd Fitbit user. Not the best sample size :) Im on the higher end too. Not sure how we stand up against the 20 million other fitbit users out there.

varelse5• 11 years ago

Cool, one thing though, you're not getting my genome. That's like giving you my fingerprints and we've just barely met. My fitbit data has probably already outed me to you given what I said previously. I'm OK with that because there's nothing but good news there. My genome? Well, it's a mixed bag like anyone else's hence the 20K+ steps per day as an ongoing service patch.

I do wish there were a way to anonymously calculate the very comparative statistics you're generating, but alas I don't see one. Am I missing something?

Show HN: Visualization of Longevity and Mortality

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