A connection between factors causing diseases and diseases frequencies. Its application in finding disease causes.

In this work an author is building a theoretical model of a non-infectious disease, which shows that there is a connection between diseases 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 a method of determining that a specific risk factor is the one which really causes a disease or 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 a cause of the disease or not and covers a significant gap in current understanding of risk factors nature and its connection to the physiological parameters of the human body.. SummaryO_LIUsing 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) C_LIO_LIThe model is considering that a cause of a disease is a change in a physiological parameter of the body approximately beyond 1-sigma interval of its measurements, slightly less. C_LIO_LIThe 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 connection the 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 rates of a specific disease in different countries or populations the model determines the same number of causes. The model introduces a formula to calculate a number of disease causes as below: C_LI O_FD O_INLINEFIG[Formula 1]C_INLINEFIGM_FD(1)C_FD 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. O_LIAccording to this non-infectious disease model in order to cause a disease all of 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. C_LIO_LIThe model shows the 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 parameters measurement goes beyond 1-sigma interval*. C_LIO_LIThe work also allows to use vast volume of existing medical researchs data about diseases risk factors in order to determine real causes of non-infectious diseases using a simple criteria which mathematically derived from the model. C_LIO_LIThe work mathematically derives the criteria which allows to determine which risk factor is a cause of disease and which is not. It mathematically proves that in order to 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%) or 19.7 (1970%), etc. plus/minus a practical margin (recommendation is +/-50%) C_LIO_LIThe calculations based on the model has shown that a majority of non-infectious diseases are caused by at least 2 simultaneously occurring changes to physiological parameters of human body or more. For example it shows that Coronary Heart Disease (CHD) is caused by 4 physiological parameters changes taking place at the same time. C_LIO_LIAs 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. C_LIO_LIBased on the smoking risk factor value, the developed in this work criteria determines that smoking is one of the causes of lung cancer and that is matching to already a well recognized medical fact, and supports the validity of the criteria used to make this prediction. C_LIO_LIThe 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. This explains why a rate of the Multiple Sclerosis is higher in women than in men as the more physiological parameters needs to be changed to cause the disease the less the rate of disease. C_LIO_LIThe work shows why breast cancers and leukemias are caused by a change to 6 physiological parameters of the human body. C_LIO_LIThe 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 occur but the changes can be acquired over the time. C_LIO_LIThe 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 measurements it is possible to prevent a non-infectious disease such cancers or strokes from occurring at all in the individual. C_LIO_LIThe 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 disease and 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). C_LIO_LIThe work mathematically derives a formula which connecting the numbers of disease causes (physiological parameters changes) determined in populations with a risk factor and without, to a risk factor value determined for the population impacted by this risk factor. The Risk Factor value here is 0 and more and defined as (cases_with_risk - cases_without_risk) / cases_without_risk. Here Risk Causes / No Risk Causes are 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: C_LI O_FD O_INLINEFIG[Formula 2]C_INLINEFIGM_FD(2)C_FD 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 them for an individual. Using this formula researchers can determine a number of physiological parameters changes the specific risk factor is causing in the human body.