Two terms don't always mean what we believe they do: "research " and "evidence-based." Take the research just published in the Journal of Epidemiology Community Health entitled: "Evidence-based Public Health Policy and Practice: Could targeted food taxes improve health?"
That's the question posted by Junkfoodscience author Sandy Szwarc who attributes the authors' "yes" answer to creation of a mathematical computer model which, necessarily, includes countless "arbitrary decisions and assumptions" and, unnecessarily, introduces a false sense of certainty about relationships where none may, in fact, exist. The phrase springs to mind: figures don't lie, but liars can figure. In the case of this study, she observes:
For their model, the authors in this study attempted to predict the number of lives saved by assuming that lowering salt and saturated fats in the diet (assuming low-fat diets work by lowering blood cholesterol levels) would reduce deaths from cardiovascular disease and strokes. For example, they estimated that every 3 gram/day reduction in salt intake would lower incidence of heart disease by 9-10% and strokes by 12-14%. Their estimated health benefits for low-fat diets were based on the assumption that every 1 mg/dl reduction in low-density lipoprotein ("bad cholesterol") would reduce heart disease by 1%.
Without the need to go any further, it'a already clear these assumptions contradict and exceed the actual clinical evidence on the ability of "heart healthy" low-salt diets and low-fat diets to prevent deaths from cardiovascular disease and strokes. In fact, as we've examined , even the latest Cochrane review of 39 clinical trials conducted in multiple countries over the course of three decades on the ability of "heart healthy" dietary interventions (reducing saturated fats and salt) and lifestyle interventions found: "Contrary to expectations, these lifestyle changes had little or no impact on the risk of heart attack or death..."
You'll want to read the whole blog, but, in summary, she notes the various assumptions about several variables including food consumption, then returns to the salt example:
Most disturbingly absent from their computer model was consideration of any potential harmful effects of compelling "heart healthy" diets. (emphasis in original)
Salt reduction, for example, doesn't appear entirely benign, according to growing medical research. The European Society of Cardiology Guidelines for the Management of Arterial Hypertension, for instance, reported recent research showing low-salt diets can have negative effects: activating the rennin (sic)-angiotensin system and the sympathetic nervous system, increasing insulin resistance and hypodehydration (especially with the elderly). This, they concluded, could lead to increased risks for cardiovascular disease. Similarly, people who might benefit from salt in their diets wouldn't be helped, but weren't included in their computer model, either. Salt also improves the flavor of many nutritious foods, helping to prevent nutritional deficiencies especially among vulnerable populations, such as children and elderly.
We've blogged before ( 1 2 3 4 5 6 7 8 ) on the disturbing gap between true "evidence-based" health policy-making as defined by the Cochrane Collaboration and the damaging abuse of the term by authors or editors trying to fabricate news from the end product of computer models whose results reflect the programmer's biases more than the data of the study itself. We've seen this abuse in the Intersalt Study, the DASH-Sodium Study and in an alarming number of national dietary guidelines which seize the mantle of being "evidence-based" while ignoring the discipline inherent in proper application of that term.
