I started with the "common knowledge" that US veterans are more likely the nonveterans to have drinking problems. I tested this hypothesis by analyzing responses to the 2005 Behavioral Risk Factor Surveillance System (BRFSS) survey. Initially, I was seduced into thinking that I would get definitive answers because the study interviewed >350,000 people (>900 Mb of data).
I ended up being dismayed because the various interpretations that could be applied to the results precluded a definitive answer.
But, I was also delighted to uncover a relationship between age and veteran drinking that had been overlooked. The full paper can be downloaded here.
The BRFSS survey distinguishes two types of problem drinking:
- Binge drinking = having five or more drinks on a particular occasion in the past 30 days.
- Heavy drinking = engaging in Binge drinking five or more times in the past 30 days.
Veterans were identified by the answer to this question:
- Have you ever served on active duty in the United States Armed Forces, either in the regular military or in a National Guard or military reserve unit?
Note that "active duty" does not imply that the person ever saw battle!
One more important thing about the BRFSS. They conducted telephone interviews with the >350,000 participants. But, only with people who have landlines. If you used a cell phone, you were not included. If you did not have a phone or even a home, you were not included.
A published result from an earlier study (ref 2 in paper) suggested that veterans were 1.06 times more likely than non-veterans to engage in binge drinking and 1.17 times more likely for heavy drinking. The binge drinking number was considered to be "not significant" because the 95% confidence interval included 1.0 (an "odds ratio" of 1.0 means that there is no difference between groups). The heavy drinking number was significant.
My analysis found similar results. Binge drinking was 1.11 times more prevalent in vets than non-vets. Heavy drinking was 1.32 times more prevalent. Both numbers were significant using the 95% confidence interval standard.
However, my analysis also considered the age of individuals. At right are the results for binge drinking.
The graph shows that young vets (20-40 yrs) are more likely than young non-vets to binge drink.
But, older vets (60-80 yrs) are less likely than older non-vets to binge drink.
I found similar results for heavy drinking (see paper).
Now, the fun part! What does it mean? Why do young vets binge drink but old vets do not (compared to non-vets)?
- Maybe alcohol-abusing vets are more likely to die prematurely (or become homeless - remember the survey technique) than non-vets.
- Maybe vets, as they get older, are more likely (than non-vets) to seek and receive help to deal with their
alcoholism.
- Maybe there is a cohort effect. Recent vets are more likely to survive
after suffering injuries that would have killed soldiers
from previous wars. These survivors have severe
handicaps (e.g. loss of limbs) that could lead to
depression and to alcohol abuse.
- Maybe young vets exaggerate their alcohol use to appear "macho" to someone in the room during the telephone interview. Young non-vets may do this too.
- Maybe old vets downplay their alcohol use to appear "in compliance" with someone in the room during the telephone interview. Old non-vets may be guilty as well.
- Maybe "front line" vets should be distinguished from other active duty vets.
This is the problem with many surveys. You get a ton of data to analyze, you find an effect, but you cannot really identify the underlying cause of the effect. Add to that the tendency of people to stretch the truth. But that doesn't stop people from publishing or publicizing their findings. And, maybe setting policies according to the findings.
I know I wouldn't be able to do this for a living! I'll stick to analyzing molecules.
- Maybe old vets downplay their alcohol use to appear "in compliance" with someone in the room during the telephone interview. Old non-vets may be guilty as well.
- Maybe "front line" vets should be distinguished from other active duty vets.
This is the problem with many surveys. You get a ton of data to analyze, you find an effect, but you cannot really identify the underlying cause of the effect. Add to that the tendency of people to stretch the truth. But that doesn't stop people from publishing or publicizing their findings. And, maybe setting policies according to the findings.
I know I wouldn't be able to do this for a living! I'll stick to analyzing molecules.




