We often see statements or articles about disease causes and risk factors. What’s the difference between a cause of illness and a disease risk factor? When we study cures the difference is clear and dramatic.
A cause causes an illness. A cause is that which, when addressed, leads to a cure. A cause of illness only exists when an actual illness exists.
Risk factors are everywhere and do not require illnesses to exist. A risk factor is something that increases the statistical risk of disease. When a risk factor is addressed, the statistical risk of a disease is reduced, but it does not cure any illness, nor even prevent a cause from causing an illness.
Illness or Disease?
Maybe you noticed, maybe not, that causes are linked to illnesses and risk factors are linked to diseases. What’s the difference? Why is there a difference?
“A patient goes to the doctor with an illness, and goes home with a disease.”
An illness is a specific case. It is what a patient has when they are ill. Some illnesses cannot be diagnosed as diseases, because they don’t match any known diagnosis. Many illnesses are never diagnosed as a disease — because we don’t bother going to a doctor.
A disease is a general class of illnesses with a name and a diagnostic protocol, a prognosis and a treatment recommendation. When we say that someone “has a disease“, they have a specific case of illness that has been diagnosed as a disease.
An illness cause causes an illness. Addressing the cause cures the illness. Addressing the cause of an illness stops the illness from existing, from progressing. It does not necessarily cure the consequences of the illness — those may require significant work and healing. A risk factor is a potential risk of a disease.
Three: Types of Causes, Illness, Cures
There are three basic types of illnesses, requiring three different types of cures.
Process cause: the presence or absence of a process can cause illness. A process caused illness is cured by addressing the process cause, and if necessary addressing the negative consequences. The illness stops when the cause is addressed, the process cure. Secondary cures may be necessary to address consequences of the illness process. A process cause can be in the body, the mind, the spirit, the community, or the environment of the patient.
Example: scurvy, caused by a faulty dietary process and cured by an appropriate dietary change. Healing damage caused by scurvy — the second cure — takes time and is aided by supplemental Vitamin C.
Attribute cause: the presence or absence of an attribute that is causing an illness. Attribute illnesses are cured by transformation — by transforming the present or absent attribute to a new state or status. The attribute illness ends when the attribute cause has been addressed. It might also be necessary to address negative consequences of the illness, typically by healing. The attribute can be in the body, the mind, the spirit, or the community of the patient.
Example: Depression caused by loss of a job might be cured if a better job is found. The new job might cause some discomfort or pain, which might require some additional adjustments. Healing takes time.
Injury cause: a force that causes an injury. The force might come from a process, or a thing, an attribute. The cause of an injury is no longer present. Injuries are cured by healing. Healing is a type of transformation, but not every transformation is a type of healing. An injury can be in the body, the mind, the spirit, the community, of the patient.
Example: Tripping and falling might cause a sprained ankle or even a broken leg. Healing takes time and proceeds naturally regardless of cause. Note: Injuries can also be caused by illness — but that’s at the next layer, not discussed in this post.
All cures can be viewed as improvements in healthiness. Process cures, transformational cures, and healing cures work faster and function better when the patient is healthier, slower and not so well when the patient is less healthy.
Successful cures and successfully addressing risk factors can both improve healthiness. Unsuccessful cures can decrease healthiness. Failing to address risk factors can lead to a drop in healthiness. As healthiness drops, we become more vulnerable to illness — a lesser cause might result in illness. As healthiness rises, we are less vulnerable to illness, able to tolerate stronger causes without illness.
Addressing risk factors of a disease statistically prevents that disease, an entire class of illnesses, from occurring. Addressing risk factors does not cure any disease and does not absolutely prevent any disease from occurring. It provides a statistical prevention, such that we believe some illnesses were prevented, based on statistics, not proof. Preventative actions are always statistical, never perfect.
We summarize the difference between causes and risk factors in this diagram.
Risk Factors to Causes
Before the illness exists, a cause is often a risk factor. Risk factors are commonplace and rarely cause illness. For example, overeating doesn’t cause obesity until it has occurred consistently over a very long time period. Few cancers are caused by overeating, but overeating is a risk factor for cancer. Tripping might cause an injury — a sprain or even a broken leg, but we can trip many times without injury. We might lose or quit many jobs without causing any depression.
Risk factors should not be confused with causes. A risk factor might eventually cause an illness, but when it does — it is no longer a risk factor, it’s the cause. A cause might be seen as a risk of producing other diseases, other cases of illness, but a cause is 100 percent the cause of an illness, or 100 percent not the cause of the illness. A cause is real, not a statistic. What if an illness has TWO causes? In the healthicine model, any illness that truly has two causes, requires two cures. Any illness that requires two cures — is not a single illness, it is two illnesses.
A cause causes an illness. A cure proves the cause. Once the cause is addressed, the illness is cured. Each cure proof is a single case, with many unique factors. Every cure is an anecdote, not a statistic. Every anecdote has some potential for fiction, potential to be wrong.
It’s possible to gather a number of cure claims together for statistical analysis. As cure claims become statistical, some variables disappear, making the information less valuable in some ways, and more valuable in other ways. Specifically, it becomes more valuable to prevent illness, less reliable for curing.
Risk factors increase chances of illness. Statistical analysis proves risk factors. Each risk factor proof is a statistic and when risk factor analysis is applied to a single case, it might simply be wrong. Walking is a risk factor for tripping, a risk factor for sprained ankles and broken bones, but walking is healthy in most cases.
When we look more closely at causes, we can see other differences between risk factors and causes.
“This world and yonder world are incessantly giving birth: Every cause is a mother, its effect the child. When the effect is born, it too becomes a cause and gives birth to wondrous effects. These causes are generation on generation, but it needs a very well lighted eye to see the links in their chain.” — RUMI
Rumi, the famous Persian poet, was not speaking just about illness, but his quote applies to illness perfectly. Every cause of illness has a cause and consequences. Every cause of a cause has a cause. And every set of consequences causes other consequences.
It is very useful to view causes of illness as links in a chain. A causal chain pulls us towards illness, as in this diagram.
The important thing about causes is cure. Breaking any link in the causal chain breaks the chain and cures the illness. Perhaps this can be difficult to understand without an example.
Suppose someone has scurvy. Scurvy is caused by a deficiency of Vitamin C. That’s the final cause, cause 5 in the image above. But giving them Vitamin C supplements will not address the process cause. They have a deficiency of Vitamin C because their diet is deficient in Vitamin C. That’s cause #4. In this case, the scurvy might be cured by changing their diet. For a prisoner, a worker on board a ship, or a senior living in a care home — this might be the perfect cure. The cure proves the cause. But maybe their diet is deficient because they are too poor to buy healthy food, cause #3. Simply changing their diet is not possible, because they can’t afford healthy food. In this case, maybe getting the person a job, so they can afford healthy food, will cure the scurvy. If so, the lack of a job is cause #2, and a job cures that cause. But maybe, the person doesn’t have a job because they are alcoholic, cause #1. In that case, they will be cured when their alcoholism is cured, so they can get a job, so they can afford healthy food. Of course, when we look far down the chain of causes — we might not find the best cure. The best cure for an alcoholic might be to put them into a situation where their food is provided for them, curing the scurvy and potentially curing the alcoholism as well.
Whenever we cure, the cure proves a cause. Causal chains provide opportunities to find cures. Each link in the causal chain might present many cure opportunities.
Risks Factors are Additive
Risk factors are not chains, because they don’t actually cause specific illnesses, they only move us closer to illness. Risk factors add up. When we are exposed to many risk factors, our likelihood of disease increases.
Each additional risk factor increases the risk of disease slightly. Addressing a risk factor reduces the chances of disease slightly, but will not cure any disease — because no illness, no case of disease is present.
We don’t get an illness when the risk factors increase to some threshold, we get an illness when a cause, a causal chain creates an illness. We use risk factors to design preventatives and causes to cure.
Analysis and Reporting of Causes and Risk Factors
There are many complications in how causes of illness and risk factors of illness are reported, which make understanding difficult.
Causes of illness and disease are rarely studied and seldom reported, for several reasons. Cured is not defined for most illnesses, and generally not defined for any illness not cured by a medicine. As a result, a depression “cured” by getting a new job, is not counted as a cure, and in today’s model of mental illness might not be counted as depression. It may appear that an illness is cured by medicine, when it is actually cured by healthiness — the medicine just happened at the same time. Many infections are cured by health and should be viewed as caused by a lack of healthiness. Gingivitis is a clear example. But when infections caused by gingivitis are cured with antibiotics, we place the “cause” on the infecting pathogen. It’s easier to understand and calculate risk factors than to examine causes.
Causes of injuries are always speculative, never 100 percent. It’s speculative because we can always create chains of causes for any injury and ask “what if I had…”, “what if I hadn’t…” for each link in our chain of speculation. Attempting to assign percentages to causes of injuries is confusing, but because the cause cannot be used to cure — it cannot be proven. It can only be used for prevention — like a risk factor.
Risk factors are usually very small, but potentially very dangerous, so instead of reporting as a percentage risk, they are reported as an “increased risk”. For example, every child has a risk of drowning, but having a private swimming pool INCREASES the risk of drowning many times, several hundred percent. Statistical calculations of risk are complex and error prone. Many risks are also healthy and therefore are not studied as risk factors. Walking increases risk of sprained ankles, but walking is generally perceived as healthy — so the risks of walking are seldom analyzed.
This post is written using the concepts of illness, disease, causes, and cures as explored in the book: A Calculus of Curing.
Disclosure: I am not a doctor. There are no books about the concepts of cures and curing by doctors.
Originally published at healthicine.org on September 21, 2018.