A week or so ago, I posted a bit of epidemiology concerning saturated fat intake associated with heart-disease deaths by country. As you saw, it was all over the map. I did speculate, however, that if you were going to try to fit a curve, it would slope downward, meaning: more saturated fat, less heart disease deaths.
Well, owing to my vast network of resources [grin], physicist Robert McLeod offered to fit a curve if I could get him the tabular data, which, thanks to Ricardo, I did. So, here's the graph (see here for the one with the country labels).
Here's what Robert had to say.
All statistics done in MATLAB. I found that if I define
SF = % saturated fat intake
CHD = # heart deaths per year per 100,000 men
CHD = (-4.734 +/- 2.003)*SF + (144.5 +/- 21.4)
+/- errors are standard deviations (i.e. one sigma) with an R^2 =
0.13 (terrible) between the fit data and experimental data.
The plot I provided shows the baseline along
with a top and bottom curve which are the 95 % confidence interval
lines (~1.96 sigmas).
Although the statistics appear fairly poor, we can make one statement
of interest. A positive slope is equivalent to a positive
correlation between CHD and saturated fat (i.e. saturated fat bad!)
and a negative slope is a negative correlation (i.e. saturated fat
good!). Evaluating that statement using confidence intervals we have
a 0.9 % chance of a positive slope and a 99.1 % chance that the slope
In other words, increased saturated fat intake is 99 % likely to be
correlated with decreased incidence of death from heart disease.