# Help in understanding epidemiological studies abbreviations in abstracts

I need help in understanding some typical abbreviations in the abstract of an epidemiological study, in particular this: http://www.ncbi.nlm.nih.gov/pubmed/24522443)

"
[...]
RESULTS:
In 2007-2010, 83.0% ± 0.7% (±SE) of adults consumed seafood in the preceding month. In adults consuming seafood, the blood mercury concentration increased as the frequency of seafood consumption increased (P < 0.001). In 2007-2010, 4.6% ± 0.39% of adults had blood mercury concentrations =5.8 µg/L. Results of the logistic regression on blood mercury concentrations =5.8 µg/L showed no association with shrimp (P = 0.21) or crab (P = 0.48) consumption and a highly significant positive association with consumption of high-mercury fish (adjusted OR per unit monthly consumption: 4.58; 95% CI: 2.44, 8.62; P < 0.001), tuna (adjusted OR: 1.14; 95% CI: 1.10, 1.17; P < 0.001), salmon (adjusted OR: 1.14; 95% CI: 1.09, 1.20; P < 0.001), and other seafood (adjusted OR: 1.12; 95% CI: 1.08, 1.15; P < 0.001).
[...]"

Some abbreviation that I don't understand:
- (±SE)
- (adjusted OR: 1.14; 95% CI: 1.10, 1.17; P < 0.001)

###### Who is Participating?

Commented:
In short (and very non-technical) summary.
The OR is a measure of how much the one thing affects the other.
The P is a measure of how likely it is that the correlation we saw was from random chance.
P < .0001 means it is very unlikely that it was a coincidence. Something probably is related.

(Note OR and P are not related at all).

The SE is how confident we are in the number.
So 83%+=.7SE means we're pretty sure the real number was between 82.3% and 83.7%
If you want to know how something affects everyone in the world and you only survey 100 people, then your SE will be very high because you can't be sure those 100 people represent the world well.
If you want to know how something affects people in a company and you survey half of them, SE will be a lot lower. If you surveyed all of them (and trusted their answers), SE would be 0.

95% CI: 1.10, 1.17 very roughly means that 95% of the data is expected to fall between 1.1 and 1.17
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Commented:
SE = Standard Error.

CI = Confidence Interval.

P = Probability.

Please look up in an introductory statistics book.
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Commented:
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Author Commented:
so does P <0.001  mean "almost impossible"?
I still don't understand.
I am an IT technician used to read analytical data but I don't understand it.

Any link to an "introductory statistics book" that can help me (in less than 2 pages of reading)?
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Author Commented:
oh I didn't read your last message Tommy, much more clear now! thanks!
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Commented:
No. Sorry. In science, there are no "30-second sound bytes". Its nature and practice is different than our modern culture of "give-me-everything-quick".

Again, sorry.
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Commented:
Note that many statistics experts will cringe as they read those explanations, but as aadih points out, to really understand them would take some time.

To confirm, here (and in general), the lower P is, the more likely there is a correlation.

A very important note: Just because two things are correlated DOES NOT MEAN one caused the other. There could be a third thing not apparent in the study that caused both.
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Commented:
[Thanks, TommySzalapski.]

Enjoy:

Scotch with water. Vodka with water. Gin with water....  Feel drunk?

One gets drunk with water, the common factor. ;-)
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