Reader Alexander Thorn in the UK put together some impressive work using data from the British Heart Foundation and emailed it to me the other day. Let’s take a look. You can click on all the graphs for the much larger "lightbox" image, and/or click on the links below each graph to download the files.
You can download the linked file here. Explains Alex:
Taking the same European countries and plotting the incidence of the various diseases against each country ranked in ascending order of the amount of saturated fat consumed as a percentage of total calories — from 3.9% for Bosnia to 15.5% for France — I got some very definite trend lines — all sloping downward toward the countries with the greatest saturated fat intakes (France being the highest, of course).
Unlike Keys, I used all the countries with the relevant data available (no cheating!). While there is the odd outlier on both sides of the divide — some countries with high disease rates and high sat fat and some with low disease rates and low sat fat — the vast majority, I think, echo the overall trend of more disease for less sat fat that is eaten as a percentage of total caloric intake.
But Alex wasn’t satisfied there. He noted that in using DALY figures, population size of the countries would make a difference. He explains.
Just thought I’d better clarify some points re the graph. The figures for CHD, stroke and other CVD are actually DALY figures – that is Disability Adjusted Lost Years – and it is per 100,000 of the countries’ populations (I hadn’t registered this distinction at first).
The DALY figures were already ‘age-adjusted’ and include not only the years lost due to mortality from the particular disease but also disability. It is calculated – as follows – from relatively accessible incidence data (ICD codes). Years of Lost LIfe (YLLs) is based on the inputs life expectancy at age of death and age at death, while Years Lost to Disability (YLDs) is based on the inputs duration of disease/injury, disability weight of disease/injury and percentage of long-term cases.
The only possible criticism I can foresee is that the population size of each country is obviously going to have a bearing on the DALY statistics. So I have just re-entered all of the data into another spreadsheet and made adjustments for the population size of each country. This has obviously made the graph less ‘exciting’ to look at but the trend lines for all diseases still slope downward toward the countries with the highest saturated fat intake.
And, it should also be noted: they don’t slope upward, so, where in that does one imagine a testable hypothesis where increased saturated fat intake causes anything bad?
Then he had the idea of plotting on a logarithmic scale. The simplest way to explain that is that it scales to percentage change rather than absolute values. So, for example, in a graph with a vertical axis from 1-100, 10 would be halfway, since the change from 1-10 in terms of percentage is the same as the change in 10-100.
But he still wasn’t finished.
Taking the same DALYs statistics from the last graphs (but this time combining the figures for CHD, stroke and other CVD) I have plotted the countries in ascending order of the total DALYs per 100,000 head of population (left to right along the x-axis) against the macro-nutrient ratio (C:P:F) for those same countries (along the y-axis) and plotted the linear regression (or trend) lines for each macro-nutrient. The relationships are pretty clear in the bars themselves but the trend lines confirm it: The less (total) fat you eat the greater the DALYs score (line slopes down toward the higher scores at the right-hand end of the x-axis) but even more telling, the more total carbohydrate you consume the greater the DALYs score (the line slopes upward toward the right-hand end of the x-axis). Protein appears to be neutral, with a perfectly level trend line.
So, more saturated fat, better, more carbohydrate, worse, and protein is not associated.
Download the file here.
Now let’s take a look at something related: total cholesterol. It so happened that Ricardo Carvalho rang in around this same time, calling attention to some data crunching of his own.
As I’ve speculated before, a total cholesterol of 200-220 seems to be the sweet spot for total C. Ricardo is calling it 200-240 and that looks like a good call, to me. Bear in mind, this does not equal causality, only association. Any individual can die of anything with any cholesterol number, or live to 101.
What this does accomplish, however, is tantamount to utter falsification of the hypothesis that either "high" saturated fat intake or "high" total cholesterol is independently causal for heart disease, stroke, or indeed, death from any cause.