A connection between factors causing diseases and diseases frequencies. It’s application in finding disease causes
Authors: Olan Alan 
Published: May 2023

In this work an author is building a theoretical model of a non-infectious disease, which shows that there is a connection betweendiseases frequencies and their causes. This connection allows to determine how many factors are causing a specific non-infectious disease if we know the disease rate in a population. The model shows that for a majority of non-infectious diseases there are at least two simultaneously acting factors which cause a disease and in many cases there are more factors simultaneously involved. This helps researchers to improve an understanding of specific disease causation and physiological mechanisms behind it and will lead to a research for additional, still missing causes to complete these mechanisms. This work determines a number of simultaneously acting factors causing diseases such as a breast cancer, coronary heart disease(CHD), multiple sclerosis, etc. and explains so called French Paradox for CHD. The work also deduces a formula and amethodofdeterminingthat a specificrisk factor is the one which really causes a diseaseor it is not. Applying a method developed in this work the author shows how three different simultaneously acting causes of atrial fibrillation are determined using an existing research data. This method should allow medical researchers to determine if a found risk factor for a disease is really acause of the diseaseor not and covers a significant gap in current understanding of risk factors nature and its connection to the physiological parameters of the human body..

Using statistical and experimental data a mathematical model of non-infectious disease is created which is applicable to any non-infectious disease (and to some degree to infectious diseases as well)

The model is considering thata cause of a disease isa changein a physiological parameterof the body approximately beyond 1-sigma interval of its measurements, slightly less.

The model predicts and the experimental data confirm its predictions that rate of non-infectious diseases is closely connected to the number of changes to physiological parameters of the human body which are causing the disease. Based on this connectionthe model allows to determine number of disease causes (as number of physiological parameters’ changed) for any non-infectious disease by only knowing the disease rate. For example, if the disease rate is 72 per 1000 people then the model determines that disease has 2 causes.Despite the differences in the ratesof a specific disease in different countries or populations the model determines thesamenumber of causes. The model introduces a formula to calculate a number of disease causes as below:

where a rate of disease can be for example as 45 per 10000 people and number of causes(as physiological parameters’ changes) is an integer number like 1, 2, 3, etc.

According to this non-infectious disease model in orderto cause a diseaseallof specific for each disease physiological parameters should be changed by actions of the external environment so their measurements will be beyond 1-sigma interval. Actually, slightly less than this interval.

The model showsthe more the rate of non-infectious disease the less number of simultaneous changes to the physiological parameters is required to cause it. The changes can be acquired over the lifetime of individual and have to be such so each physiological parameter’s measurement goesbeyond 1-sigma interval*.

The work also allows to use vast volume of existing medical research’sdata about diseases’ risk factors in order to determine real causes of non-infectious diseasesusing a simple criteria whichmathematicallyderived from the model.

The work mathematicallyderives the criteria which allows to determine which risk factor is a cause of diseaseand which is not. It mathematically proves that in orderto be a cause of the specific disease the found risk factors(calculated as[ risk_cases - normal_cases ] / normal_cases)should rich the value of 3.5 (or 350%)or19.7(1970%), etc. plus/minus a practical margin (recommendation is +/-50%)

The calculations based on themodel has shown that a majority of non-infectious diseases are caused by at least 2 simultaneously occurring changes to physiological parameters of human bodyor more. For example it shows thatCoronary Heart Disease (CHD) is caused by 4 physiological parameters changes taking place at the same time.

As the model derived in this work predicts that non-infectious diseases are caused at least by 2 changes (beyond 1-sigma) to physiological parameters of human body then it shows there is no reason and actually, often it is incorrect to search for a single cause of the non-infectious disease.The single cause of non-infectious disease does not exist for a majority of them, according to this mathematical model.

Based on the smoking risk factor value, the developed in this workcriteria determines that smoking is one of the causes of lung cancerand that is matching to already a well recognized medical fact, and supports the validity of the criteria used to make this prediction.

The model shows that Multiple Sclerosis in men is caused by changes to 5 physiological parameters (beyond 1 sigma interval *) while the same disease is caused by changes to 4 physiological parameters in women. Thisexplains why a rate of the Multiple Sclerosis is higher in women than in menas the more physiological parameters needs to be changed to cause the disease the less the rate of disease.

The work shows whybreast cancersandleukemiasarecaused by a change to 6 physiological parameters of the human body.

The model leads to a conclusion that the majority of non-infectious diseases cannot occur if only one physiological parameter of human body changes beyond 1-sigma interval.The multiple and simultaneously taking place changes to physiological parameters needs to be there for a non-infectious disease to occurbut the changes can be acquired over the time.

The work leads to a conclusion that by controlling few physiological parameters of the human body so they are located within the 1-sigma of its measurementsit is possible to prevent a non-infectious disease such cancers or strokes from occurring at allin the individual.

The work shows that the fact that few of physiological parameters changes needed to simultaneously occur in order to cause the non-infectious disease,allows to select some risks factors as real causes of the diseaseand that we have some room for an error in selecting these risk factors as disease causes because if few risk factors are correctly chosen they will compensate for an incorrectly chosen one. This way we can prevent many diseases from occurrence by keeping the right risk factors (physiological parameters) under control (meaning within 1-sigma interval).

The work mathematically derives aformula which connecting the numbers of disease causes(physiological parameters’ changes)determined in populationswith a risk factor and without,to a risk factor valuedetermined for the population impacted by this risk factor. TheRisk Factorvalue here is 0 and more and defined as(cases_with_risk - cases_without_risk) / cases_without_risk. HereRisk Causes / No Risk Causesare numbers of causes (physiological parameters changes) determined for a disease in a population with a risk factor and without it using a formula presented above and are integer numbers (0,1,etc.). The formula is:

The formula is a foundation of the criteria to determine if the risk factor is really a disease cause.It connects physiological parameters changes in the human body to the risk factor which creates themfor an individual. Using this formula researcherscan determine a number of physiological parameters changes the specific risk factor is causing in the human body.