When we discuss various topics in health, we typically interchange the words correlation and causation. We look for common patterns and tend to conclude causation. This approach simplifies the process for discovery, but inadvertently reaches unfounded and inaccurate conclusions in many cases. When seeking “today’s truth,” we must pursue realities that reach beyond the boundaries of “correlation.”
Just because something “appears” to correlate doesn’t prove causation. Until recently, the health care field claimed a correlation existed between cholesterol in food and cholesterol levels in the blood. Without validating this correlation to be causal, the industry placed dietary guidelines recommending no more than 300mg of cholesterol be consumed on a daily basis in the 1960’s. For more than 50 years this “apparent” correlation was considered causal for high cholesterol. Today, this correlation has been completely invalidated.
Until recently the health care field claimed a correlation existed between moderate to high levels of fat consumption and cardiovascular disease. Poorly designed scientific studies concluded these dietary patterns were CAUSAL for strokes and heart attacks. Today, Ketogenic diets, Paleo diets, Atkin diets, etc… all profess to be solutions to risk factors associated with cardiovascular disease even though each is higher in fat consumption. Once again we see examples where correlation has not conclusively been the factor determining direct causation.
The germ theory is probably one of the best examples showing the misrepresentation between correlation and causation. It was determined in the 19th century that a correlation existed between “germ exposure” (bacteria, virus, fungi, etc…) and disease development. We saw outbreaks and epidemics that resulted in disease and death. It seemed clear that “germs” were the CAUSATIVE factor since a CORRELATION was seen among those exposed to the germ. Once again our conclusions were wrong. They were based on fear, not reality. Today we recognize that germs alone are not causal for disease. There is certainly a correlation between germs and the potential for health maladies, but the CAUSATIVE factor associated with disease is a compromised immune system incapable of optimal performance. If germs were the “causative factor” everyone exposed to the germ would succumb to disease. How often has an entire family living together been exposed to the same germ, yet experienced different health outcomes? How many times have groups of people eaten foods contaminated with bacteria, yet only some experience the symptoms of “food poisoning.” The “germ” plays a factor, but is not directly causal for the outcome.
These three examples (out of countless numbers) aim to show how “experts” setting health care policy use CORRELATION to prove CAUSATION. Causation only exists if it occurs EACH AND EVERY TIME. Correlation, on the other hand, has a significantly lower standard that establishes a commonality to a condition. We can conclude, therefore, even a high degree of CORRELATION will NOT necessarily be the CAUSATIVE factor in an outcome. (Ex. A high correlation may be exist among poor diets and elevated blood sugar, but we can’t conclude that Diabetes is CAUSED by poor dieting.) This is an important point, because it demonstrates the complexity in understanding CAUSATION. CORRELATION may play a role, but we can’t scientifically conclude it is always CAUSATIVE.
Our new science is changing traditional thinking and expanding our outdated views of health. Today, we are moving in a direction that understands the uniqueness of each individual regardless of common anatomy and physiology. We are turning away from the concept of correlation and seeking INDIVIDUAL CAUSATION by expanding our diagnostic skills and searching for COMPREHENSIVE ANSWERS as it applies to each and every person. This new approach will seek deficiencies rather than symptoms; its treatment plans will be designed to re-balance physical, mental and emotional weaknesses rather than relying on answers solely found in life long prescriptions. It will convert our current DISEASE CARE MODEL into a true HEALTH CARE MODEL. Understanding the differences between CORRELATION and CAUSATION as it applies to health and disease is an important first step as we transition our health care system and its approach to providing quality care.