Last week I attended the Canadian Society for Epidemiology and Biostatistics Student Conference, the first conference I traveled to present at. Sandro Galea gave a great keynote speech.
- population health vs. personalized health
- mismatch of funds spent and health of populations
- article in Fortune, “Can genes really predict your health?”
- our health has deteriorated, but our genes haven’t changed, so why all the fuss (and funding) about them?
- population estimates do NOT allow us to predict individual event inference (a point about personalized medicine)
- no lone ranger, no silver bullet. obesity is associated with a HUGE causal web, not one isolated factor
- book written with Katherine Keyes
slides I was interested in
- health determinants vs. health expenditures
- social causes of death vs. others (poverty causes same no. as injury)
- what percentage of your intelligence depends on genes?
- it depends on your environment
- need with grapple with health equity vs. efficiency trade-off
- people of high SES benefit most from changes
- embrace intellectual and moral challenges of our time: how to change the socio-economic context that influences health?
- goalie is medicine. for every one goalie, ten players that are not goalies are needed to move the ball up the field. OTHERWISE WE LOSE.
- goldfish in a bowl: can exercise, have safe sex, and eat not too much food, but if the water isn’t changed, it will still die.
I liked this talk because it confirmed everything I believe about the social nature of how society functions. our health is mostly determined by our social environment, and it’s those social factors that are at the crux of making sure populations are healthy. poverty stunts, sickens, and kills people. we must create societies that take care of the least privileged, the most vulnerable. otherwise, rich people will enjoy the advances of health while their neighbours rot in misery.
We had a session in which we spoke to a group of people who work in different epidemiology/public health positions.
National Collaboration Centre (NCC)
- different centres in different provinces
- funded by Public Health Agency of Canada
data management and data cleaning are 90% of the work that must be done in data analysis. get experience working with horrible data sets.
Public Health Ontario epidemiologists – mailing list, great resources
make yourself stand out in an interview, educate yourself well about the place/department. also, want to be flexible, be a generalist with enough knowledge about a lot of things, not in-depth for one topic (advice is diametrically opposed to that for someone who wants to continue in academia).
working in government
- BUREAUCRACY. the right thing to do takes 10 years, but it happens! sometimes even in just 2 years.
- important impact on populations
- FYI: WHO makes up data where none exists, read the fine print and footnotes of everything you use
- Global Health Observatory data is cool, check it out
- beware the reification of stats due to pretty charts and maps (ie they become true because they are visualized)
- data don’t exist in a social vacuum