BIOSTATISTICS AND ITS VALUE FOR ESTIMATION OF POPULATION HEALTH AND ACTIVITY OF HEALTH CARE INSTITUTIONS.

ORGANIZATION OF STATISTICAL RESEARCH IN THE SYSTEM OF HEALTH CARE.

RELATIVE VALUES.

 

Biostatistics (a portmanteau word made from biology and statistics; sometimes referred to as biometry or biometrics) is the application of statistics to a wide range of topics in biology. The science of biostatistics encompasses the design of biological experiments, especially in medicine and agriculture; the collection, summarization, and analysis of data from those experiments; and the interpretation of, and inference from, the results.

Biostatistics and the history of biological thought

Biostatistical reasoning and modeling were of critical importance to the foundation theories of modern biology. In the early 1900s, after the rediscovery of Mendel’s work, the conceptual gaps in understanding between genetics and evolutionary Darwinism led to vigorous debate between biometricians such as Walter Weldon and Karl Pearson and Mendelians such as Charles Davenport, William Bateson and Wilhelm Johannsen. By the 1930s statisticians and models built on statistical reasoning had helped to resolve these differences and to produce the neo-Darwinian modern evolutionary synthesis.

The leading figures in the establishment of this synthesis all relied on statistics and developed its use in biology.

·                     Sir Ronald A. Fisher developed several basic statistical methods in support of his work The Genetical Theory of Natural Selection

·                     Sewall G. Wright used statistics in the development of modern population genetics

·                     J. B. S Haldane’s book, The Causes of Evolution, reestablished natural selection as the premier mechanism of evolution by explaining it in terms of the mathematical consequences of Mendelian genetics.

These individuals and the work of other biostatisticians, mathematical biologists, and statistically inclined geneticists helped bring together evolutionary biology and genetics into a consistent, coherent whole that could begin to be quantitatively modeled.

In parallel to this overall development, the pioneering work of D’Arcy Thompson in On Growth and Form also helped to add quantitative discipline to biological study.

Despite the fundamental importance and frequent necessity of statistical reasoning, there may nonetheless have been a tendency among biologists to distrust or deprecate results which are not qualitatively apparent. One anecdote describes Thomas Hunt Morgan banning the Frieden calculator from his department at Caltech, saying “Well, I am like a guy who is prospecting for gold along the banks of the Sacramento River in 1849. With a little intelligence, I can reach down and pick up big nuggets of gold. And as long as I can do that, I’m not going to let any people in my department waste scarce resources in placer mining.”^[1] Educators are now adjusting their curricula to focus on more quantitative concepts and tools.^[2]

Walter Frank Raphael Weldon FRS (15 March 1860, Highgate, London – 13 April 1906), Oxford, generally called Raphael Weldon, was an English evolutionary zoologist and biometrician.

Weldon was the second child of the journalist and industrial chemist, Walter Weldon (FRS 1882), and his wife Anne Cotton. Weldon père moved around the country so frequently that Raphael could not attend school until he was thirteen years old. Walter and Anne had three children; their first child was a girl, with Raphael borext followed by his younger brother Dante.

Raphael did receive some tutoring from a local clergyman before he was thirteen years old then, in 1873, he entered Mr Watson’s boarding school at Caversham near Reading. After three years there, plus several months of private study, he entered University College London. Weldon spent the academic year 1876/1877 at UCL, being taught by the zoologist E. Ray Lankester and the Danish mathematician Olaus Henrici. There he studied a wide range of subjects which he took in preparation for studying medicine. Henrici impressed Weldon more than any other lecturer; he later wrote that Henrici was the first naturally gifted teacher he had studied under^{[citatioeeded]}.

Later in 1877 he transferred to King’s College London and then to St John’s College, Cambridge in 1878. There Weldon studied with the developmental morphologist Francis Balfour who influenced him greatly: Weldon gave up his plans for a career in medicine. In 1881 he gained a first-class honours degree in the Natural Science Tripos despite the loss of his brother Dante, who died suddenly. In the autumn he left for the Naples Zoological Station to begin the first of his studies on marine biological organisms.

Weldon married Florence Tebb, daughter of William Tebb of Rede Hall, Burstow in Surrey, on 13 March 1883. She played a large role in his scientific work, assisting him on many of his projects. He died in 1906 of acute pneumonia, and is buried at Holywell Church, Oxford.

Upon returning to Cambridge in 1882, he was appointed university lecturer in Invertebrate Morphology. Weldon’s work was centred around the development of a fuller understanding of marine biological phenomena and selective death rates of these organisms.

After graduating he began research, going to Naples where he worked at the Zoological Station. He was appointed a demonstrator in zoology at Cambridge University in 1882, and became a Fellow of St John’s College and a university lecturer in invertebrate morphology in 1884. His teaching was described in these glowing terms:-

“Seldom is it given to a man to teach as Weldon taught. He lectured almost as one inspired. His extreme earnestness was only equalled by his lucidity. He awoke enthusiasm even in the dullest, and had the divine gift of compelling interest.“^{[citation needed]}

After he was married to Florence, Weldon took all his holidays with his wife in places where they could study marine biology. In particular they visited the Bahamas in 1886, which was scientifically very profitable. The Marine Biological Association set up a laboratory in Plymouth, and Weldon and his wife began spending all their vacations there undertaking research. By 1888 they were spending as much time there as his duties at Cambridge would allow, and he only went to the university to give his lectures. He undertook research June to January, teaching at Cambridge for two terms each year.

In 1889 Weldon succeeded Lankester in the Jodrell Chair of Zoology at University College London, and was elected to the Royal Society in 1890. Royal Society records show his election supporters included the great zoologists of the day: Huxley, Lankester, Poulton, Newton, Flower, Romanes and others.

His interests were changing from morphology to problems in variation and organic correlation. He began using the statistical techniques that Francis Galton had developed for he had come to the view that “the problem of animal evolution is essentially a statistical problem.” Weldon began working with his University College colleague, the mathematician Karl Pearson. Their partnership was very important to both men and survived Weldon’s move to the Linacre Chair of Zoology at Oxford University in 1899. In the years of their collaboration Pearson laid the foundations of modern statistics. Magnello emphasises this side of Weldon’s career. In 1900 he took the DSc degree and as Linacre Professor he also held a Fellowship at Merton College, Oxford.

By 1893 a Royal Society Committee included Weldon, Galton and Karl Pearson ‘For the Purpose of conducting Statistical Enquiry into the Variability of Organisms’. In an 1894 paper Some remarks on variation in plants and animals arising from the work of the Royal Society Committee, Weldon wrote:-

“… the questions raised by the Darwinian hypothesis are purely statistical, and the statistical method is the only one at present obvious by which that hypothesis can be experimentally checked.”

In 1900 the work of Gregor Mendel was rediscovered and this precipitated a conflict between Weldon and Pearson on the one side and William Bateson on the other. Bateson, who had been taught by Weldon, took a very strong line against the biometricians. This bitter dispute ranged across substantive issues of the nature of evolution and methodological issues such as the value of the statistical method. Will Provine gives a detailed account of the controversy. The debate lost much of its intensity with the death of Weldon in 1906, though the general debate between the biometricians and the Mendelians continued until the creation of the modern evolutionary synthesis in the 1930s.

Karl Pearson FRS (March 27, 1857 – April 27, 1936^[1]) established the discipline of mathematical statistics.^[2]

In 1911 he founded the world’s first university statistics department at University College London. He was a controversial proponent of eugenics, and a protégé and biographer of Sir Francis Galton.

A sesquicentenary conference was held in London on 23 March 2007, to celebrate the 150th anniversary of his birth.^[2]

Carl Pearson, later known as Karl Pearson (1857-1936) was born to William Pearson and Fanny Smith, who had three children, Arthur, Carl and Amy. William Pearson also sired an illegitimate son, Frederick Mockett.

Pearson’s mother, née Fanny Smith, came from a family of master mariners who sailed their own ships from Hull; his father read law at Edinburgh and was a successful barrister and Queen’s Counsel (QC). William Pearson’s father’s family came from the North Riding of Yorkshire. The family grave is at Crambe, near York. Its motto, “ERIMUS” means “We shall be”, and is also the motto of the Middlesbrough coat-of-arms.

“Carl Pearson” inadvertently became “Karl Pearson” when he enrolled at the University of Heidelberg in 1879, which changed the spelling. He used both variants of his name until 1884 when he finally adopted Karl – supposedly also after Karl Marx^{[citatioeeded]}, though some argue otherwise.^[3] Eventually he became universally known as “KP”.

He was also an accomplished historian and Germanist. He spent much of the 1880s in Berlin, Heidelberg, Vienna^{[citatioeeded]}, Saig bei Lenzkirch,^[4] and Brixlegg. He wrote on Passion plays, religion, Goethe, Werther, as well as sex-related themes e.g. The Men and Women’s Club.

In 1890 he married Maria Sharpe who was related to the Kenrick, Reid, Rogers and Sharpe families, late 18th century and 19th century non-conformists largely associated with north London; they included:

·                     Samuel Rogers, poet (1763-1855)

·                     Sutton Sharpe (1797-1843), barrister

·                     Samuel Sharpe, Egyptologist and philanthropist (1799-1881)

·                     John Kenrick, a non-Conformist minister (1788-1877)

Karl and Maria Pearson had two daughters, Sigrid Loetitia Pearson and Helga Sharpe Pearson, and one son, Egon Sharpe Pearson. Egon Pearson became an eminent statistician himself, establishing the Neyman-Pearson lemma. He succeeded his father as head of the Applied Statistics Department at University College.

Karl Pearson was educated privately at University College School, after which he went to King’s College, Cambridge in 1876 to study mathematics. He then spent part of 1879 and 1880 studying medieval and 16th century German literature at the universities of Berlin and Heidelberg – in fact, he became sufficiently knowledgeable in this field that he was offered a Germanics post at Kings College, Cambridge.

He graduated from Cambridge University in 1879 as Third Wrangler in the Mathematical Tripos. He then travelled to Germany to study physics at the University of Heidelberg under G H Quincke and metaphysics under Kuno Fischer. He next visited the University of Berlin, where he attended the lectures of the famous physiologist Emil du Bois-Reymond on Darwinism (Emil was a brother of Paul du Bois-Reymond, the mathematician). Other subjects which he studied in Berlin included Roman Law, taught by Bruns and Mommsen, medieval and 16th century German Literature, and Socialism. He was strongly influenced by the courses he attended at this time and he became sufficiently expert on German literature that he was offered a post in the German Department of Cambridge University. On returning to England in 1880, Pearson first went to Cambridge:- Back in Cambridge, I worked in the engineering shops, but drew up the schedule in Mittel– and Althochdeutsch for the Medieval Languages Tripos.

In his first book, The New Werther, Pearson gives a clear indication of why he studied so many diverse subjects:- I rush from science to philosophy, and from philosophy to our old friends the poets; and then, over-wearied by too much idealism, I fancy I become practical in returning to science. Have you ever attempted to conceive all there is in the world worth knowing – that not one subject in the universe is unworthy of study? The giants of literature, the mysteries of many-dimensional space, the attempts of Boltzmann and Crookes to penetrate Nature’s very laboratory, the Kantian theory of the universe, and the latest discoveries in embryology, with their wonderful tales of the development of life – what an immensity beyond our grasp! … Mankind seems on the verge of a new and glorious discovery. What Newton did to simplify the planetary motions must now be done to unite in one whole the various isolated theories of mathematical physics.

Pearson then returned to London to study law so that he might, like his father, be called to the Bar. Quoting Pearson’s own account: Coming to London, I read in chambers in Lincoln’s Inn, drew up bills of sale, and was called to the Bar, but varied legal studies by lecturing on heat at Barnes, on Martin Luther at Hampstead, and on Lasalle and Marx on Sundays at revolutionary clubs around Soho.

His next career move was to Inner Temple, where he read law until 1881 (although he never practised). After this, he returned to mathematics, deputizing for the mathematics professor at King’s College London in 1881 and for the professor at University College London in 1883. In 1884, he was appointed to the Goldsmid Chair of Applied Mathematics and Mechanics at University College London. 1891 saw him also appointed to the professorship of Geometry at Gresham College; here he met Walter Frank Raphael Weldon, a zoologist who had some interesting problems requiring quantitative solutions. The collaboration, in biometry and evolutionary theory, was a fruitful one and lasted until Weldon died in 1906. Weldon introduced Pearson to Charles Darwin‘s cousin Francis Galton, who was interested in aspects of evolution such as heredity and eugenics. Pearson became Galton’s protégé — his “statistical heir” as some have put it — at times to the verge of hero worship.

After Galton’s death in 1911, Pearson embarked on producing his definitive biography—a three-volume tome of narrative, letters, genealogies, commentaries, and photographs—published in 1914, 1924, and 1930, with much of Pearson’s own financing paying for their print runs. The biography, done “to satisfy myself and without regard to traditional standards, to the needs of publishers or to the tastes of the reading public”, triumphed Galton’s life, work, and personal heredity. He predicted that Galton, rather than Charles Darwin, would be remembered as the most prodigious grandson of Erasmus Darwin.

When Galton died, he left the residue of his estate to the University of London for a Chair in Eugenics. Pearson was the first holder of this chair—the Galton Chair of Eugenics, later the Galton Chair of Genetics^[5]—in accordance with Galton’s wishes. He formed the Department of Applied Statistics (with financial support from the Drapers’ Company), into which he incorporated the Biometric and Galton laboratories. He remained with the department until his retirement in 1933, and continued to work until his death in 1936.

When the 23 year-old Albert Einstein started a study group, the Olympia Academy, with his two younger friends, Maurice Solovine and Conrad Habicht, he suggested that the first book to be read was Pearson’s The Grammar of Science. This book covered several themes that were later to become part of the theories of Einstein and other scientists. Pearson asserted that the laws of nature are relative to the perceptive ability of the observer. Irreversibility of natural processes, he claimed, is a purely relative conception. An observer who travels at the exact velocity of light would see an eternal now, or an absence of motion. He speculated that an observer who traveled faster than light would see time reversal, similar to a cinema film being run backwards. Pearson also discussed antimatter, the fourth dimension, and wrinkles in time.

Pearson’s relativity was based on idealism, in the sense of ideas or pictures in a mind. “There are many signs,” he wrote, “that a sound idealism is surely replacing, as a basis for natural philosophy, the crude materialism of the older physicists.” (Preface to 2nd Ed., The Grammar of Science) Further, he stated, “…science is in reality a classification and analysis of the contents of the mind….” “In truth, the field of science is much more consciousness than an external world.”

Pearson’s work was all-embracing in the wide application and development of mathematical statistics, and encompassed the fields of biology, epidemiology, anthropometry, medicine and social history. In 1901, with Weldon and Galton, he founded the journal Biometrika whose object was the development of statistical theory. He edited this journal until his death. He also founded the journal Annals of Eugenics (now Annals of Human Genetics) in 1925. He published the Drapers’ Company Research Memoirs largely to provide a record of the output of the Department of Applied Statistics not published elsewhere.

Pearson’s thinking underpins many of the ‘classical’ statistical methods which are in common use today. Some of his main contributions are:

1.                Linear regression and correlation – Pearson was instrumental in the development of this theory. One of his classic data sets (originally collected by Galton) involves the regression of sons’ height upon that of their fathers’. Pearson built a 3-dimensional model of this data set (which remains in the care of the Statistical Science Department) to illustrate the ideas. The Pearson product-moment correlation coefficient is named after him, and it was the first important effect size to be introduced into statistics.

2.                Classification of distributions – Pearson’s work on classifying probability distributions forms the basis for a lot of modern statistical theory; in particular, the exponential family of distributions underlies the theory of generalized linear models.

3.                Pearson’s chi-square test – A particular kind of chi-square test, a statistical test of significance.

4.                Coefficient of correlation and two coefficients of skewness.

 

Social medicine and organization of health protection have no a final definition yet. That is explained of their relative youth. Less than one hundred years has passed from the time of subject describe and methods of research. That is a short period of time as compared with thousand years of   medicine development on the whole. That is conditioned by great spaciousness of their interest, which includes health character of social people’s layers, of nations and humanity in general (such called, civic health). It also includes search for actions, which influence on this health, attempt to improve it by taking different measures, and first of all by organization of medical aid.

There were proposed the next definitions:

“Civic medicine” studies laws of distribution of diseases among people’s layers and searches for causes of this distribution /commission of the Pirogov association/.

“Civic medicine” studies experience, principles and forms of organization of medical aid, its connection and interaction with civic life and with local authorities. /A.Shyngarov/

“Social medicine” studies state action mainly in field of disease prophylactic /commission/.

“Social medicine and civic medicine” study laws of health protection of people         /V.Kanel/.

“Social hygiene” studies social measures for hygienic perfections.  /E.Yakovenko/.

As we see, in spite of some divergence, all of this definitions had the only joint feature, which is characterized by necessity to study the influence of social conditions (measures, activities) on the health, to study protection of humanity health and its separate layers.

New science acquired a wide development in many European countries, specifically in German. Hygiene and bacteriology, connected with the names of M.Petenkofer, R.Koch and others, achieved great success here at the end of the XIX century.

“Saving consolidation and increasing of people’s health” (A.Fisher) was determined as the subject of studying   of the hygiene.

In its turn “civic medicine” was divided into two parts – physical and social.

“Physical hygiene” is the part of civic medicine that studies the  influence of natural conditions of the surroundings upon sanitary condition of the people. 

“Social hygiene” studied social (cultural) influence upon people’s health.

At the some time such concepts as “social pathology”,  “social prophylaxis (hygiene)”, and “social therapy” appeared and were confirmed. The social pathology was implied as the science that studied the influence of social environment on beginning and coursing of disease. The social prophylaxis  (hygiene) was implied as the science that occupied with disease prevention by using social measures. The social therapy (medicine) was implied as a science that tried to eliminate diseases with the help of social measures. The later concept (social medicine) was treated as a notion that unificated all of three above-named concepts.

Studying of reasons of disease’s spreading had begun long before realizing of social conditionality of the health. Since for a long time infectious diseases with typical for them mass epidemic spreading were the main problem so the science, which studied that, was named “epidemiology”.

Later on the diseases that were not caused by infectious agents but other reasons became of wide spread. But the conformity with a low of their spreading coincided mostly with infectious diseases, because in the first and in the second cases those reasons lay mostly in the social space. Epidemiology spread its methods concerning these diseases, which were interpreted as the most important mass noninfectious diseases.

In fact the parallel existence of different concepts and definitions of one science is going on since then.

On arising of the World Health Organization (WHO, 1948) search in this direction continued. New definitions on such concepts as “civic health protection”, “research into practice of health protection”, “social medicine”,  “communal health protection” and “communal medicine” were given. The WHO conferencing gave the following definition to civic health protection” – this is the science and the art of prevention from diseases, prolongation of life and strengthening of mental and physical health and capacity for work by organization of social efforts, which are directed to make healthier the environment, to fight against infectious diseases, to learn people skills of individual hygiene, to organizate medical and nursling service for early diagnostics and preventive treatment of diseases.

The history of social medicine.

Many years ago people tried to make their health stronger by helping of the social measures. That measures can be divided into 2 groups:

-measures, against the diseases;

-measures, to make the health stronger.

There are a lot of historical things, which played a big role in the health protection. One of them is Bible. In that book you can read that it is necessary to take a rest at the end of every week (10 commandments). And this commandment of Christian people is a tradition in different nations.

You can see a height level of health-improvement measures during Roman and Greek epoch. Their hygienic measures were directed to tempering of the organism and to making it clean. They had a lot of perfect reservoirs, pump-houses, bath-houses.

Big contribution into the development of social medicine were put by the father of medicine-Hipocrates. He told that the doctor must pay attention to the living conditions of the patient. He must know if the patient prefer  to take a lot of food and drink or to work and physical training.

Learning the history of social medicine you can see the importance of social doctors, which have worked in the state-job. They appear, at first, in Egypt, then in Greek and Roman republics. Their services were free of charge for poor people. That doctors were paid by state.

First hospitals appeared at the 4^th century. They were built near the monastery and sisters of Christ took care of the patients. That hospitals had their own specialization: 1.to treat people who had leprosy; 2.to treat all the rest patients.

First medical school appeared in Salerno in 10^th century. At the same time you can see the height level of the development of hygiene. In 1440 the king of Sicilia Rodger promulgated the act, according to which all the doctors were to pass the exam before starting their practice.

The main problem of social medicine were infectious diseases. Lots of measures were held to protect people because of leprosy. Doctors used an isolation against all the rest infectious diseases.

Famous scientist B.Ramaccini wrote a significant book “Thinking about the work diseases. In that book he described different kinds of diseases caused to different kinds of work. B.Ramaccini-the father of professional hygiene.

Big significance in the development of the social medicine played the finding of statistical analyses. In 1662 D.Grount wrote a work, where he described death-rate and birth-rate in London. His friend ,doctor V.Petti called his own work “political arithmetic”. Soon, the death-rate tables were used as a base of life-insurance.

In 17^th-18^th centuries lots of acts, which regulated the doctor’s and pharmacist’s work were promulgated.

The development of social medicine was connected with an organization of people’s health protection. Working with this problem I.Frank wrote a work “The System of Perfect Medical Police” . the author worked with this question during all his life. He thought that the doctors were to learn the nature, the living conditions of their patients, different diseases and their causes, different social classes according to every geographical region.

England was the motherland of the first industrial revolution. In 1802 “The act about moral and health was promulgated. According to this act the central statistical office was made for registration death-rate, birth-rate and the level of diseases.

C.Neiman in his work “The health protection and property’(1847)says: ”Medicine is a social science”. In 1876 in Germany the act about the injections against smallpox was promoted. In the way of the development of social medicine and organization of health protection of the people big role were paid by creation of “Berlin’s association of health protection” in 1883.

So, before the beginning of the 20^th century 3 ways of health protection were formed:

-with help of state measures(the promulgation of different medical and social work);

-with help of social measures;

-with help of medical insurance.

In 1946 “International collection of sanitary acts” was promulgated. In 1948 was founded that the “Health-is a state of social, physical and mental goodness and not only the absentee of different diseases and physical defects.

In 1976 “International act about economical, social and cultural rights of people”.

The aim of the 30^th session of Universal Assembly was to amount the fixed level of health until 2000.

First scientist institutes, which learned the questions of social medicine appeared at the beginning of 20^th century.

In the West-states height level of the development of social medicine. The heightest quantity of science researches was in the USA. There were many national institutes of health ,medical schools , universities with special departments for learning social medicine. Different scientist associations (American medical association of social health protection) made a lot of researches. Big job according to organization and financing of science researches in health protection was made by National center science researches an the development of health protection. At the same time the center of National statistic of health protection was founded.

The centers of communal medicine and organization of health protection, epidemiology, social health protection worked in England.

In France, there is “National institute of health protection and medical researches”.

The main role in learning different problems of health protection in Germany plays the bureau of social health protection. It consists of 4 specialized institutes, institutes of social medicine and epidemiology. The last one consists of 3 departments: social medicine, epidemiology and diagnostic.

In Italy there are the Height institute of health protection and Central statistical institute which works with problems of social health protection.

In Netherlands the questions of social medicine are in competention of  institute of prophylactic medicine, in Belgium-institute of hygiene and epidemiology  , in Hungary- institute of social medicine and organization of health protection. 

The World Health Organization conference (1965) gave the follow definition to “civic health protection” – this is a science and art of prevention from diseases, prolongation of life and strengthening of mental and physical health and capacity for work by organization of social efforts, which are directed to make the environment healthier, to fight against infectious diseases, to study people skills of individual hygiene, to organize medical and nursery service for early diagnostics and preventive treatment for diseases. And the efforts also are directed to develop civic institutes for ensuring every man the life conditions, which are necessary for saving the health; they are directed to organize all these prevalence’s that every citizen could use his right to have a long life.

This vast definition was made surer by the WHO committee of experts (1973), which noted that the definition of  “civic health protection” includes problems that threaten human’s health and includes health condition on the whole, hygiene of the environment, health protection services and organization of medical-sanitary aid.

The international association of epidemiologists in collaboration with the WHO published the textbook on the teaching of the methods of epidemiology, in which the follow definition was given: studying the factor that cause frequency and spreading of diseases among people. By the way, it was marked that epidemiologic research have to direct the development of health services by establishment of disease spreading dimensions and the problems connected with it. This research must also reveal etiological factors, this will give an opportunity to fight purposefully against diseases; the research must work out the methods which definite the efficiency of measures conducting with the purpose of overcoming diseases and improvement social health.

Thus, we may suppose largely that the definition of “epidemiology” is analogous to the definition of “social hygiene”. The another conceptions of “organization of health protection” corresponded largely to the definition of “practice of health protection research”, which was adopted by the WHO. This definition was interpreted as use of scientific methods in research of planning and organization health services and their administrative management. Its wide purpose is to study and analyze the systems of giving medical aid and other health service for search of optimum organization, revelation of the ways and means to perfect the health service planning …

At the same time, the new interpretation to the definition of “social medicine” was given, which is occupied with conception of needs in services (disease realization, need in medical aid); it is occupied with satisfaction of this problem, with social participation in the programs of the fight against diseases, perception and accessibility of services.

Recently, the terms of “communal health protection”, “communal medicine” became of wide inculcation. The WHO gave them the following definitions.

“Communal health protection” includes the problems of influence upon human’s health, determination of its composition, the environment hygiene, health protection services and administrative management of medical-sanitary aid services. But in some countries “communal health protection” is used as a synonym of “environment hygiene”; in other countries it personifies medical-sanitary aid out of hospital or medical-sanitary work among people.

The widest interpretation of “communal medicine” was settled in Great Britain. It forced out the conception of civic health protection, preventive medicine and social medicine, and acquired the following content there: “communal medicine” studies health and diseases of different people layers. The functions of specialist in communal medicine consist in studying and valuing people’s necessities in urgent measures, which are directed to strengthen the health, to prevent diseases and to ensure medical aid. This profession also includes the co-ordination of medical specialist’s opinions with the purpose of giving the organs, which are responsible for work of health services, recommendations in reference to politics that correspond to medical needs.

Numerous attempts were made to modernize this definition.

“Social hygiene” is a science on social conformity with a low of health and health protection (L.Lekaryev, 1969).

“Social hygiene” studies interaction of social factors and human’s health including changing of need in medical aid with the purpose of making the rational economic system of civic health protection measures (K.Gargov, 1969).

“Social hygiene and organization of health protection” study the sanitative and negative influence of social factors upon people’s health and their separate layers, and work out scientific substantiated recommendations for realization of measures concerning liquidation and prevention of unhealthy influence of social  factors upon people’s health and their separate layers, and work out scientific substantiated recommendations for realization of measures concerning liquidation and prevention of unhealthy influence of social factors on human’s health to promote the protection and increasing the level of civic health (Y. Lisicyn, 1987).

The second Allukrainian congress of social hygienists and organizers of health protection (1990) came to a decision to change somewhat the terminology, having approached it to international definition, such as “Social medicine and organization of health protection”. But it didn’t give the definition to a new conception.

Following aforesaid we give our definition: “Social medicine and organization of health protection” is a science that studies social conformity with a low of human’s health and substantiate the ways of its improvement by rational organization of health protection.

In the theory and especially in the practice of social medicine and organization of health protection the two conceptions are met as synonyms frequency, thought they are very different. They are “health protection” and “medical aid”. We give them the following definitions.

Health protection is a system of state, civic and individual measures and means that promote to become people healthy, to warn diseases and prevent of premature death, to ensure the active life and capacity for work.

Health protection is a conception that includes all complex of measures and means, which concern of human’s health, or it take into consideration all complex of the factors, which influences upon human’s health.

Medical aid is a system of special medical measured and means that promote to become people healthy, to warn diseases and prevent of premature death, to ensure the active life and capacity for work.

Medical aid is much narrow conception as compared with health protection, though the purpose of medical aid is the same as of health protection.

The incessant increasing of social health level gets a prevailing ideal of its life activity, subordinates all of other social interests. According to these social movements the demands for development level of social medicine and for organization of health protection as science increase. The main tasks of social medicine are:

-studying of the state of human’s health and processes of its reproduction;

-ensuring of thorough characteristic of movements(dynamics), which take place in indices of human’s health of the country in the whole and which take place in regional levels, social-economic, ecologic-geographic zones, settlements and separate collectives;

-scientific exposing of conditions and factors, which reduce to positive and negative  divergence in the state of health of different social, age-sexual and other population groups;

-elaboration of the directions  of population’s sanitation and determination of  principles of health protection system, its theoretical and organizing bases;

-analysis of health service organ’s activity and establishments, creating their rational structures and scientific substantiation of the most expedient forms of work organization, reformation and restructurization;

-creating of different-term prognoses and plans of the development of health protection system with the purpose of carry-out goal-directed measures concerning maintaining the due level of human’s health.

Fulfilling tasks, which include the sphere of scientific and practical interests of social medicine and organization of health protection, is connected as with department as with interdepartmental correlations, which need permanent scientific elaboration and creating the most prolific theoretical principles.

The World Assembly of Health Protection (WAHP) in its resolutioumber 23.61 considers that the optimum development of health protection in any country needs making use of generalized experience of health protection development in all the countries of the world. Among them the most effective and checked by the experience of different countries principles of building and development of national health protection system are the following principles:

·                   Proclamation of the responsibility of state and society for health protection of the population, which is to be incarnate on the basis of carrying out the complex of economic and social measures/ which promote directly or collaterally to reach the highest health level of population by creating general national system of health protection services on the basis of the only national plan and local plans, and also by goal-directed and effective making use of all strength and resources, which society may apport on every stage of its development for requirements of health protection;

·                   Organization of rational training national specialists of all levels of health protection as the basis for successful work of any health protection system and realization of all medical specialists their high social responsibility to society;

·                   Health protection development, in first turn on the basis of wide carrying out the measures, which are directed to the development of social and individual prophylactic, foreseeing fundamental connecting medical and prophylactic work in all medical and sanitary establishments and services, foreseeing also protection of women and children health, which are the future of every country and whole humanity, and establishment the effective control of sanitary state of environment as the source of health and life of modern and future generations;

·                   To ensure all population of the country the highest possible level of qualified, generally accessible prophylactic and medical aid, which is given without financial or other restrictions by creating suitable network of medical, prophylactic and rehabilitation establishments;

·                   Wide use achievement of world medical science and practice of health protection in every country with the purpose of ensuring conditions for getting maximum effectiveness of all taken measures in health protection sphere;

·                   Sanitary education of citizens and drawing into participation in conducting the all programmers of health protection of wide sphere of population are the argument of personal and collective responsibility of all members of society for health protection of people.

The above-mentioned principles were determined and used by most of all countries of the world for development of the people’s health examination and activity of establishments and organs of health protection.

Majority of the demands of human’s right Declaration concerning of ensuring human’s health, fond their incarnation in the constitution, adopted by Supreme Rada in 1996.

Article 46. Citizens have the right to social protection, which includes the right to ensuring it in case of full, partial or temporary losing of capacity for work, losing of breadwinner, unemployment, in old age and in other cases, which are foreseen by law.

This right is guaranteed by generally compulsory state social insurance at the expense of insurance payments of citizens, enterprises, institutions and organizations, and also of budgetary, and other sources of social ensuring. This right is also guaranteed by creating of the network of state, communal private establishment for care of the disabled.

Pensions, other kinds of social payments and aid, that are the main source of existence, should ensure such level of life, which have be not lower than living minimum, that is determined by low.

Article 48. Everyone has right to sufficient standard of living for himself and his family. This right includes sufficient fooding, clother, and home.

Article 49. Everyone has right to health protection, medical aid and medical ensuring.

Health protection is ensured by state finance of corresponding social-economic, medical-sanitary and sanitative-prophilactic programmers.

The state creates conditions for effective and accessible medical service for all citizens. In the state and communal establishments of health protection, medical aid is given fee of change. Existing network of such establishments should not be reduced. The state promotes to develop medical establishments of all forms of property.

The state takes care of development of physical culture and sport, ensure sanitary-epidemiologic well being.

Article 50. Everyone has right to safe life and healthy environment and compensation damage, which is done by violation of this right.

Everyone is guaranteed with free access to the information of the environment situation, food quality.

And also for the right to expand this information. No one must not keep this in secret.

Pg 52. All children are equell in their right and it doesn’t matter whether they were born in marriage or out of it.

 Any child violence and their exploitation  are prosecuted by government.

The government must take care about children’s education and their holding, who have been repudiated by their real parent’s.

The government supports child charity/ according to the world care of the public health, experience, there is more detailed description has been found in “Legislation of the Public Health service of Ukraine”. You will find the effect on the health of separate conditions and factors. They fit to facts, which are confirmed by the international documents of the Public Health service.

Basically Ukrainian Government is managed by present regularity of Health formation of the population and it’s protection.

The basic principles of the Public Health service:

·                                  The determination of the Public Health service with the priority direction of the sasaity activities and government as the one of the basic factors of the surviving  and Ukrainiaation development.

·                                  The observance of the right and liberties of  human and citizen according to the Public Health service and securing with the state guarantees.

·                                  The human direction, securing with priority, common to all mankind  treasures in classical, national, grope or individual interests, medical-social protection of the most vulnerable part of the population.

·                                  Of the citizens, democratism and opened to general use of the medical aid and  other services in the Public Health service.

·                                  Accordance to the task and social-economical level and cultural development of the sasaity, scientific explanation, material and technical and financial securing.

·                                  Orientation to the modern health standards  and medical aid.

·                                  The unit of the old traditions and achievements  in Public Health service.

·                                  Preventive character, and composite. Social ecological and medical approach to the Public Health service.

·                                  The unit state guarantees with demonopolization and connecting of the enterprises and competition.

·                                  Decentralization of the state department, development of the autocracy of the institutions and Public health service staff independence, based on low and contract.

So the positions of our government coincide,  with progressive sights world thought about health sasaity.

Social medicine – is a science that studies social laws of peoples health and characterizes the ways of its improvement according to rational organization of public health services.

Social medicine lays between biological and social sciences which are involved in studying the essence of health and diseases of a person.

Basic features that differ social medicine from fundamental and clinical disciplines that occupy a prevailing part of teaching at the high and secondary medical schools are the following:

1. The subject of its interest are health and diseases of groups of people – collectives, populations, society as a whole, not the separate person, in other words not health or disease of an individual, but the public’s one.

2. Considering the occurrence, pathogenesis and clinics of separate diseases all of them are equivalent between themselves. In fact it is impossible to imagine the physician who has well learnt etiology, pathogenesis and clinic of hyper, tonic disease but who is poorly acquainted with the same questions dealing with stomach ulcer.

From the positions of social medicine diseases are not equivalent, because at a certain historical stage they influence public health differently. So, 50-60 years ago most people were dying from epidemic diseases and tuberculosis, now – from so-called chronic degenerate diseases (of heart and vessels, malignant formations, chronic diseases of lungs, etc.).

3. Fundamental and clinical sciences consider the health and diseases to be a biological phenomenon, social medicine – the social one.

An individual is a complex biopsychosociological system. It can be viewed under three corners of sight: as a biological organism, as a personality (the carrier of consciousness) and as a carrier of social quality.

Therefore, there is a clear definition of health by World Health Organization (WHO): «Health is a condition of complete social, mental and biological well-being and not just the absence of diseases or physical defects».

There is a natural question concerning the influence of separate factors on health. This question is still poorly studied.

It is proved, that 25 % of person’s health depends on biological factors, 15 % – on environmental conditions and 60 % on social factors. Among social factors 10 % occupies the system of medical services, the one that appeared quite a long time ago and gradually developed into a powerful social factor of health protection.

Social medicine as the science and a subject of teaching uses different methods. 

Among them it is necessary to name the following ones:

1. Historical, establishes historical regularities of development of public health and its protection;

2. Sociological, that allows studying social structure of a society and its influence on health;

3. Experimental, allows studying advantages (lacks) of organizational forms of medical service;

4. Expertise, which help quality and efficiency of medical service is studied;

5.Economical, that enable to determine economic efficiency of systems of medical service.

The basic concepts of medical statistics are:

A statistical aggregate is the commoumber of units of supervision, taken in the set borders of space and time.

A general statistical aggregate is an aggregate, which includes all units of supervision. For example, all morbidity on the earth.

A selective statistical aggregate is an aggregate, which includes the certain part of units of supervision, but this part is able to represent all general aggregate.

Unit of supervision is every special case of the phenomenon, that is studied, that it is every primary element of aggregate, which belongs to the account (for example, every case of disease, birth, deaths, hospitalizations and others like that). Such registration elements of aggregate divide into attributive (expressed verbally) and quantitative (expressed by a number).

Group properties of statistical totality:

1.                 Distribution of characteristic      (criterion – relative sizes);

2.                 Average level of index (criterions – Mo-mean, Me-median, arithmetical mean);

3.                 Variety of characteristic (criterions – lim– limit, am – amplitude, σ – average deviation);

4.                 Representation (criterions – m_M – mistake of average sizes, m_% – mistake of relative sizes);

5.                 Mutual connection between characteristics (criterion – r_xy  – coefficient of connection.

The important interest of medical statistics is quantitative and qualitative analyses of activity of a treatment-and-prophylactic network, an estimation of this activity through the mechanism of influence on a state of health with the obligatory account of complex influence of different factors.

 

 

 

The stages of statistic investigation.

1^st stage – composition of the program and plan of investigation

2^nd stage – collection of material

3^ed  stage – working up of material

4^th stage – analysis of material, conclusions, proposals

5^th stage – putting into practice

The program of statistical research shows the basic directions of research and information, which it is necessary to collect. The programs are official (medical statistical forms of document) and special (which are folded by a researcher).

The program of statistic investigation consists of the program of material collection, the elaboration program and the program of analysis.

The collection program is the program of statistic observation, the form with the list of signs, that have to be registered (registration’ signs) with an indication on whom it will be filled in, that is with a determination of the unit of observation. There are the official programs of material collection to study the health and activity of medical establishments, and special ones, composed by the investigater. 

The material elaboration program is the composition of models of tables. There are three types of tables: simple (that give the material bringing together only by one sign); group (that give the material bringing together only by two sign); combinational (connection of three or more signs).

The plan of statistic investigation foresees the organizational elements of work. It consists of: 1) the determination of the object of investigation; 2) the place of investigation; 3) the time of investigation; 4) the volume of investigation; 5) the method of material elaboration (manual, with the help of ECM); 6) the terms of the carrying out of the work; 7) executors; 8) composition of the instructions of the methods of work; 9) carrying out of the seminar for the executors.

         The ways of formation of the object of investigation: by the scope of observation are continuous or selective; by the time of observation – flowing or one-moment; by the way of obtaining the information – direct observation, copying, filling in a form.

Registration and accounting medical documents can serve as programs of medic-statistical research.

Medic-statistical research can be complete or selective.

Complete or continuous research covers all observation units.

Selective research covers a representative part of the supervision units, which enables to evaluate phenomenon in whole.

Research is of great importance. The territory strongly influences the results of research.

The next question is the time and the term of the research. Research can last constantly, that is to be current, to be carried out periodically, during certain time or to be one-stage.

Constant researches are: studying of natural movement of the population, periodic — studying of prevalence of chronic diseases, one-stage — population census, fixing of a condition of medical service.

So, after collection of the statistical data their working up is being processed. This process includes the quantitative and qualitative check, coding and grouping of these data. The quantitative check means check of correctness of statistical record of documents, the qualitative is the logic comparison of the data, for example, age and diagnosis, age and employment, growth and weight of a body, etc. Later there is coding. To each quantitative or qualitative characteristic of the phenomenon certain code is given.

Grouping may be a distribution of the data according to the quantitative or qualitative characteristics with the purpose of their analysis. The quantitative characteristics are: age, growth, weight, etc. The qualitative characteristics are background, social status, occupation, disease, etc.

Grouping is simple (according to one characteristic), complex (according to many characteristics, which are combined among themselves) and repeated (grouping before the divided earlier groups with the purpose of deeper studying the phenomenon).

The ways of formation of the statistic integrity you see on the slide.

The stages of development of statistical material are following:

o        control /logical and technical/;

o        enciphering /code/ of registered signs by numbers, letters of alphabet;

o        lay-out of cards on groups for the subaccount or groupment;

o        report of material;

o        deduction of statistical criteria /indexes/, their graphic image.

 

RANDOMIZED CONTROLLED TRIALS − AS Element of evidential medicine

Animal experiments

Throughout history animals have played an important role in men’s quest for knowledge about himself and his environment. Animal studies have contributed to our knowledge of anatomy, physiology, pathology, microbiology, immunology, genetics, chemotherapy and so many others. At the beginning of this century, Webster in United States and Topley, Wilson and Greenwood in England had carried out classical animal experiments. Their studies centred round inducing epidemics in animals and in studies of herd immunity under laboratory conditions.

More important application of animal experiments have been in (a) experimental reproduction of human disease in animals to confirm aetiological hypotheses and to study the pathogenetic phenomena or mechanisms (b) testing the efficacy of preventive and therapeutic measures such as vaccines and drugs, and (c) completing the natural history of disease. For example, naturally occurring leprosy has been found in armadillos. Data obtained from studying these animals indicate that lepra bacilli might exist outside of humans.

Animal experiments have their own advantages and limitations. The advantages are that the experimental animals can be bred in laboratories and manipulated easily according to the wishes of the investigator. A more important point is that they multiply rapidly and enable the investigators to carry out certain experiments (e.g., genetic experiments) which in human population would take several years and involve many generations. The limitations of animal experiments are that not all human diseases can be reproduced in animals. Secondly, all the conclusions derived from animal experiments may not be strictly applicable to human beings. An excellent example to illustrate this point is the WHO trial of typhoid vaccine in Yugoslavia in the mid-1950s. Laboratory tests in animals showed the alcohol-killed and preserved vaccine to be more effective than the traditional heat-killed phenol-preserved vaccine. But randomized controlled trials in human beings demonstrated that, contrary to laboratory evidence, the alcohol-preserved vaccine was found to be less than half as effective in preventing typhoid fever as the traditional phenol-preserved vaccine introduced by Almorth Wright. This highlights the difficulties encountered in extrapolating findings from animal experiments in man.

Human experiments

Human experiments will always be needed to investigate disease aetiology and to evaluate the preventive and therapeutic measures. These studies are even more essential in the investigation of diseases that cannot be reproduced in animals.

Historically, in 1747, James Lind performed a human experiment (clinical trial) in which he added different substances to diet of 12 soldiers who were suffering from scurvy. He divided his patients into 6 pairs and supplemented the diets of each pair with cider, elixir vitriol, vinegar, sea water; a mixture of nutmeg, garlic, mustard and tamarind in barley water; and two oranges and one lemon daily. All the subjects were studied for 6 days. At the end of 6 days the LIMEYS recovered from scurvy and were found fit for duty. Then came Edward Jenner’s experiment with cowpox in 1796. Other classical experiments are Finlay and Reed’s experiments (1881-1900) to elucidate the mosquito-borne nature of yellow fever and Goldberger’s classical experiments in 1915 inducing pellagra by diets deficient iicotinic acid, thereby proving pellagra to be a nutritional deficiency disease, not an infectious disease as was then supposed. Since then, human beings have participated in studies of malaria, syphilis, hepatitis, measles, polio and others. These experiments have played decisive roles in investigating disease aetiology and in testing preventive and therapeutic measures.

Although the experimental method is unquestionably the most incisive approach to scientific problem, ethical and logistic considerations often prevent its application to the study of disease in humans. Therefore, before launching human experiments, the benefits of the experiment have to be weighed against risks involved. The volunteers should be made fully aware of all possible consequences of the experiment. Thus when an illness is fatal (e.g., excessive haemorrhage) and the benefit of treatment (e.g., blood transfusion) is self-evident, it would be ethically unacceptable to prove or disprove the therapeutic value of blood transfusion. However, such instances represent only a small part of the total research effort. On the other hand, in the present era of scientific medicine, many unscientific or scientifically unsound procedures are still being carried out. For instance, in the study of prescription drugs, a panel of experts in USA found that only 23 per cent of some 16,000 drugs could be classified unequivocally as “effective” (36). It is now conceded that it is equally unethical if a drug or procedure is brought into general use without establishing its effectiveness by controlled trials. The thalidomide disaster and the occurrence of carcinoma of the vagina in the offspring of pregnant women treated with diethylstilbestrol highlight the unfortunate consequence of therapy on the basis of uncontrolled observations. The WHO in 1980 has laid down a strict code of practice in connection with human trials.

Experimental studies are of two types:

a. Randomized controlled trials (i.e., those involving a process of random allocation); and

b. Non-randomized or “non-experimental” trials (i.e., those departing from strict randomization for practical purposes, but in such a manner that non-randomization does not seriously affect the theoretical basis of conclusions).

RANDOMIZED CONTROLLED TRIALS

Too often physicians are guided in their daily work by clinical impressions of their own or their teachers. These impressions, particularly, when they are incorporated in textbooks and repeatedly quoted by reputed teachers and their students acquire authority, just as if they were proved facts. Similarly many public health measures are introduced on the basis of assumed benefits without subjecting them to rigorous testing. The history of medicine amply illustrates this. For instance, it took centuries before therapeutic blood letting and drastic purging were abandoned by the medical profession.

It is mainly in the last 35 to 40 years, determined efforts have been made to use scientific techniques to evaluate methods of treatment and prevention. An important advance in this field has been the development of an assessment method, known as Randomized Controlled Trial (RCT). It is really an epidemiologic experiment. Since its introduction, the RCT has questioned the validity of such widely used treatments as oral hypoglycemic agents, varicose vein stripping, tonsillectomy, hospitalization of all patients with myocardial infarction, multiphasic screening, and toxicity and applicability of many preventive and therapeutic procedures.

The design of a randomized controlled trial is given in Figure 1. For new programmes or new therapies, the RCT is the No.l method of evaluation. The basic steps in conducting a RCT include the following:

1.      Drawing up a protocol

2.      Selecting reference and experimental populations

3.      Randomization

4.      Manipulation or intervention

5.      Follow-up

6.      Assessment of outcome

1. The Protocol:    

One of the essential features of a randomized controlled trial is that the study is conducted under a strict protocol. The protocol specifies the aims and objectives of the study, questions to be answered, criteria for the selection of study and control groups, size of the sample, the procedures for allocation of subjects into study and control groups, treatments to be applied – when and where and how to what kind of patients, standardization of working procedures and schedules as well as responsibilities of the parties involved in the trial, up to the stage of evaluation of outcome of the study. A protocol is essential especially when a number of centres are participating in the trial. Once a protocol has been evolved, it should be strictly adhered to throughout the study. The protocol aims at preventing bias and to reduce the sources of error in the study.

Preliminary test runs: Sometimes, before a protocol is completed, preliminary (pilot) studies have to be made to find out the feasibility or operational efficiency of certain procedures, or unknown effects, or on the acceptability of certain policies. Sometimes it is useful to have a short test run of the protocol to see whether it contains any flaws. It is important that the final version of the protocol should be agreed upon by all concerned before the trial begins.

2. Selecting Reference and Experimental Populations:

(a) Reference or target population: It is the population to which the findings of the trial, if found successful, are expected to be applicable (e.g., a drug, vaccine or other procedure). A reference population may be as broad as mankind or it may be geographically limited or limited to persons in specific age, sex, occupational or social groups. Thus the reference population may comprise the population of a whole city, or a population of school children, industrial workers, obstetric population and so on according to the nature of the study.

FIG. 1. Design of a randomized controlled trial

(b) Experimental or study population: The study population is derived from the reference population. It is the actual population that participates in the experimental study. Ideally, it should be randomly chosen from the reference population, so that it has the same characteristics as the reference population. If the study population differs from the reference population, it may not be possible to generalise the findings of the study to the reference population.

When an experimental population has been defined, its members are invited to participate in the study. It is important to choose a stable population whose cooperation is assured to avoid losses to follow-up. The participants or volunteers must fulfill the following three criteria:

a. they must give “informed consent”, that is they must agree to participate in (he trial after having been fully informed about the purpose, procedures and possible dangers of the trial;

b. they should be representative of the population to which they belong (i.e., reference population); and

c. they should be qualified or eligible for the trial. That is, let us suppose we are testing the effectiveness of a new drug for the treatment of anaemia. If the volunteers are not anaemic, we will then say, they are not eligible or qualified for the trial. Similarly, let us suppose; we are going to test the effectiveness of a new vaccine against whooping cough. If the volunteers are already immune to the disease in question, we will then say, they are not qualified for the trial. In other words, the participants must I fully susceptible to the disease under study.

It must be recognized that persons who agree to participate in a study are likely to differ from those who do not, in many ways that may affect the outcome under investigation.

3. Randomization:

Rancomization is a statistical procedure by which the participants are allocated into groups usually called “study” and “control” groups, to receive or not to receive an experimental preventive or therapeutic procedure, manoeuvre or intervention. Randomization is an attempt to eliminate “bias” and allow for comparability. Theoretically it is possible to assure comparability by matching. But when one matches, one can only march those factors which are known to be important. There may be other factors which are important but whose effect is not recognized or cannot be determined. By a process of randomization, hopefully, these factors will be distributed equally between the two groups.

Randomization is the “heart” of a control trial. It will give the greatest confidence that the groups are comparable so that like can be compared with like. It ensures that the investigator has no control over allocation of participants to either study or control group, thus eliminating what is known as “selection bias”. In other words, by random allocation, every individual gets an equal chance of being allocated into either group or any of the trial groups.

It is crucial that both the groups should be alike with regard to certain variables or characteristics that might affect the outcome of the experiment (e.g., age, sex), the entire study population can be stratified into subgroups according to the variable, and individuals within each subgroup can then be randomly allocated into study and control groups. It is always desirable to check that the groups formed initially are basically similar in composition. Randomization is done only after the participant has entered the study that is after having been qualified for the trial and has given his informed consent to participate in the study. Randomization is best done by using a table of random numbers.

The essential difference between a randomized controlled trial and an analytical study is that in the latter, there is no randomization because a differentiation into diseased and non-diseased (exposed or non-exposed) groups has already taken place. The only option left to ensure comparability in analytical studies is by matching.

4. Manipulation:

Having formed the study and control groups, the next step is to intervene or manipulate the study (experimental) group by the deliberate application or withdrawal or reduction of the suspected causal factor (e.g., this may be a drug, vaccine, dietary component, a habit, etc) as laid down !n the protocol.

This manipulation creates an independent variable (e.g., drug, vaccine, a new procedure) whose effect is then determined by measurement of the final outcome, which constitutes the dependent variable (e.g., incidence of disease, survival time, recovery period).

5. Follow -up:

This implies examination of the experimental and control group subjects at defined intervals of time, in a standard manner, with equal intensity, under the same given circumstances, in the same time frame till final assessment of outcome. The duration of the trial is usually based on the expectation that a significant difference (e.g., mortality) wilt be demonstrable at a given point in time after the start of the trial. Thus the follow-up may be short or may require many years depending upon the study undertaken.

It may be mentioned that some losses to follow-up are inevitable due to factors, such as death, migration and loss of interest. This is known as attrition. If the attrition is substantial, it may be difficult to generalise the results of the study to the reference population. Every effort, therefore, should be made to minimise the losses to follow-up.

6. Assessment:

The final step is assessment of the outcome of the trial in terms of (a) positive results: that is, benefits of the experimental measure such as reduced incidence or severity of the disease, cost to the health service or other appropriate outcome in the study .and control groups, (b) negative results: that is, severity and frequency of side-effects and complications, if any, including death. Adverse effects may be missed if they are not sought.

The incidence of positive/negative results is rigorously compared in both the groups, and the differences, if any, are toted for statistical significance. Techniques are available for the analysis of data as they are collected (sequential analysis), but it is more useful to analyse the results at the end of the trial.

Bias may arise from errors of assessment of the outcome due to human element. These may be from three sources: First, there may be bias on the part of the participants, who may subjectively feel better or report improvement if they knew they were receiving a new form of treatment. This is known as “subject variation^”. Secondly there may be observer bias that is the investigator measuring the outcome of a .therapeutic trial may be influenced if he knows beforehand the particular procedure or therapy to which the patient has been subjected. This is known as “observer bias.” Thirdly, there may be bias in evaluation – that is, the investigator may subconsciously give a favorable report of the outcome of the trial. Randomization cannot guard against these sorts of bias, nor the size of the sample. In order to reduce these problems, a technique known as “blinding” is adopted, which will ensure that the outcome is assessed objectively.

BLINDING: Blinding can be done In three ways – (a) Single blind trial: The trial is so planned that the participant is not aware whether he belongs to the study group or control group (b) Double blind trial: The trial is so planned that neither the doctor nor the participant is aware of the group allocation and the treatment received (c) Triple blind trial: This goes one step further. The participant, the investigator and the person analysing the data are all “blind”. Ideally, of course, triple blinding should be used; but the double blinding is the most frequently used method when a blind trial is conducted. When an outcome such as death is being measured, blinding is not so essential.

SOME STUDY DESIGNS

It is useful to consider here some of the study designs of controlled trials:

1. Concurrent parallel study design

Fig. 2. Schematic diagram of the design of concurrent parallel and cross-over controlled therapeutic trials

In this situation (Fig. 2-a), comparisons are made between two randomly assigned groups, one group exposed to specific treatment, and the other group not exposed. Patients remain in the study group or the control group for the duration of the investigation.

 

2. Cross-over type of study design

This is illustrated in Fig. 2–b. With this type of study design, each patient serves as his own control. As before, the patients are randomly assigned to a study group and control group. The study group receives the treatment under consideration. The control group receives some alternate form of active treatment or placebo. The two groups are observed over time. Then the patients in each group are taken off their medication or placebo to allow for the elimination of the medication from the .body and for the possibility of any “carry over” effects, as shown in Fig. 2–b by the diagonal tines. After this period of medication (the length of this interval is determined by the pharmacologic properties of the drug being, tested), the two groups are switched. Those who received the treatment under study are changed to the control group therapy or placebo, and vice versa. Cross-over studies offer a number of advantages. With such a design, ail patients can be assured that sometime during the course of investigation, they will receive the new therapy. Such studies generally economize on the total number of patients required at the expense of the time necessary to complete the study. This method of study is not suitable if the drug of interest cures the disease, if the drug is effective only during a certain stage of the disease or if the disease changes radically during the period of time required for the study.

TYPES OF RANDOMIZED CONTROLLED TRIALS

1. Clinical trials

For the most part, “clinical trials” have been concerned with evaluating therapeutic agents, mainly drugs. The last three decades have been clearly the utility of clinical trials. Some of the recent examples include – evaluation of beta-blockers in reducing cardiovascular mortality in patient surviving the acute phase of myocardial infarction; trials of folate treatment/supplementation before conception to prevent recurrence of neural tube defects; trials of aspirin on cardiovascular mortality and beta carotene on cancer incidence; efficacy of tonsillectomy for recurrent throat infection; randomized controlled trial of coronary bypass surgery for the prevention of myocardial infarction, etc. The list is endless.

Unfortunately, not all clinical trials are susceptible to being blinded. For example, there is no way to perform a clinical trial of tonsillectomy and adenoidectomy without its being obvious who received surgery and who did not, a reason why the value of these procedures continues to be uncertain. Many ethical, administrative and technical problems are involved in the .conduct of clinical trials. Nevertheless, they are a powerful tool and should be carried out before any new therapy, procedure or service is introduced.

2. Preventive trials

In general usage, prevention is synonymous with primary prevention, and the term “preventive trials” implies trials of primary preventive measures. These trials are purported to prevent or eliminate disease on an experimental basis. The most frequently occurring type of preventive trials are the trials of vaccines and chemo-prophylactic drugs. The basic principles of experimental design are also applicable to these trials. It may be necessary to apply the trial to groups of subjects instead of to individual subjects. For example, in 1946, the Medical Research Council of UK conducted an extensive trial to test whooping cough vaccine from three manufacturers in ten separate field trials. Those children between 6-18 months who were entered into the trial were randomly allocated in study and control groups. The vaccine was given in three, monthly injections, and the children were followed up at monthly intervals to detect the occurrence of whooping cough. The study group comprised of 3801 children who were vaccinated, and 149 developed whooping cough. The control group consisted of 3757 unvaccinated children, and 687 of them developed the infection. This gave an attack rate of 1,45 per 1000 child months in the vaccinated group and 6,72 per 1000 child months in the control group. The difference was significant.

Analysis of a preventive trial must result in a clear statement about (a) the benefit the community will derive from the measure (b) the risks involved, and (c) the costs to the health service in terms of money, men and material resources. Since preventive trials involve larger number of subject and sometimes a longer time span to obtain results, there may be greater number of practical problems in their organization and execution.

3. Risk factor trials

A type of preventive trial is the trial of risk factors in which the investigator intervenes to interrupt the usual sequence in the development of disease for those individuals who have “risk factor” for developing the disease; often this involves risk factor modification. The concept of “risk factor” gave a new dimension to epidemiological research.

For example, the major risk factors of coronary heart disease are elevated blood cholesterol, smoking, hypertension and sedentary habits. Accordingly, the four main possibilities of intervention in coronary heart disease are: reduction of blood cholesterol, the cessation of smoking, control of hypertension and promotion of regular physical activity. Risk factor trials can be “single-factor” or “multi-factor” trials. Both the approaches are complementary, and both are needed.

The WHO promoted a trial on primary prevention of coronary heart disease using clofibrate to lower serum cholesterol, which was accepted as a significant risk factor for CHD. This study is the largest preventive trial yet conducted comprising more than 15,000 men of whom one-third received clofibrate and two-third received olive oil as a control treatment. The study was conducted in 3 centres in Europe (Edinburgh, Prague, and Budapest). The design was double-blind and randomization was successfully achieved. The meant observation was 9.6 years. The trial showed a significant reduction in non-fatal cardiac infarction, but unfortunately, there were 25 per cent more deaths in the clofibrate-treated group than in the control group possibly due to long-term toxic effect of the drug. The trial illustrates the kind of contribution that an epidemiological approach can make to protect the public health against possible adverse effects of long-term medication, with potent drugs.

The other widely reported risk-factor intervention trials in coronary heart disease are: (a) The Stanford Three Community Study (b) The North Karelia Project in Finland (c) The Oslo Study and (d) The Multiple Risk Factor Intervention (MRFIT) in USA.

4. Cessation experiments

Another type of preventive trial is the cessation experiment. In this type of study, an attempt is made to evaluate the termination of a habit (or removal of suspected agent) which is considered to be causally related to a disease. If such action is followed by a significant reduction in the disease, the hypothesis of cause is greatly strengthened. The familiar example is cigarette smoking and lung cancer. If in a randomized controlled trial, one group of cigarette smokers, continue to smoke and the other group has given up, the demonstration of a decrease in the incidence of lung cancer in the study group greatly strengthens the hypothesis of a causal relationship. A large randomized controlled trial has been mounted to study the role of smoking cessation in the primary prevention of coronary heart disease.

5. Trial of aetiological agents

One of the aims of experimental epidemiology is to confirm or refute an aetiological hypothesis. The best known example of trial of an aetiological agent relates to retrolental fibroplasia (RLF). Retrolental fibroplasia, as a cause of blindness, was non-existent prior to 1938. It was originally observed and reported by T.L.Terry, a Boston ophthalmologist in 1942, and later in many other countries outside the USA.

RLF was recognized as a leading cause of blindness by descriptive studies, which showed (hat beginning in about 1940-1941, .the incidence of the disease increased at an alarming rate (Fig. 3) and that this previously unknown disease was occurring only in premature babies. Analytical studies demonstrated its close association with administration of oxygen to premature babies. A large randomized controlled trial was mounted involving 18 hospitals in United States by Kinsey and Hemphill (79,80) in which premature babies with birth weight of 1500 g or less were allocated into experimental and control groups. In the experimental group, all the babies received 50 per cent oxygen therapy for 28 days, while in the control group (“curtailed oxygen group”) oxygen was used only for clinical emergency. It was later found that all of the babies in the “curtailed oxygen group” who developed RLF had received some oxygen. There were no cases among those who received none, confirming the aetiological hypothesis.

The dramatic rise and fall in frequency of RLF can be seen in Fig. 3. It will be noted that RLF reached its peak during the years 1952-53. The sharp drop in the graph after 1953 highlights the results of the decreased use of oxygen. RLF illustrates one of the problems often introduced by technological or scientific advances.

Since most diseases are fatal, disabling or unpleasant, human, experiments to confirm an aetiological hypothesis are rarely possible.

YEAR OF BIRTH

Fig. 3. Incidence of Retrolenlal Fibroplasia in New York, 1938-1956

6. Evaluation of health services

Randomized controlled trials have been extended to assess the effectiveness and efficiency of health services. Often, choices have to be made between alternative policies of health care delivery. The necessity of choice arises from the fact that resources are limited, and priorities must be set for the implementation of a large number of activities which could contribute to the welfare of the society. An excellent example of such an evaluation is the controlled trials in the chemotherapy of tuberculosis in India, which demonstrated that “domiciliary treatment” of pulmonary tuberculosis was as effective as the more costlier “hospital or sanatorium” treatment. The results of the study have gained international acceptance and ushered in a new era – the era of domiciliary treatment, in the treatment of tuberculosis.

More recently, multiphasic screening which has achieved great popularity in some countries, was evaluated by a randomized controlled trial in South-East London. The study led to the withholding of vast outlay, of resources required to mount a national programme of multiphasic screening in UK. Another example is that related to studies which have shown that many of the health care delivery tasks traditionally performed by physicians can be performed by nurses and other paramedical workers, thus saving physician time. These studies are also labelled as “health services research” studies.

NON-RANDOMIZED TRIALS

Although the experimental method is almost always to be preferred, it is not always possible for ethical, administrative and other reasons to resort to a randomized controlled trial in human beings. For example, smoking and lung cancer and induction of cancer by viruses have not lent themselves to direct experimentation in human beings. Secondly, some preventive measures can be applied only to groups or on a community-wide basis (e.g., community trials of water fluoridation). Thirdly, when disease frequency is low and the natural history long (e.g., cancer cervix) randomized controlled trials require follow-up of thousands of people for a decade or more. The cost and logistics are often prohibitive. These trials are rare. In such situations, we must depend upon other study designs – these are referred to as non-randomized (or non-experimental) trials.

Where the approach is sophisticated in randomized controlled trials, it is rather crude in non-randomized trials. As there is no randomization ion-experimental trials, the degree of comparability will be low and the chances of a spurious result higher than where randomization had taken place. In other words, the validity of causal inference remains largely a matter of extra-statistical judgement. Nevertheless, vital decisions affecting public health and preventive medicine have been made by non-experimental studies. A few examples of non-randomized trials are discussed below:

1. Uncontrolled trials

There is room for uncontrolled trials (i.e., trials with no comparison group). For example, there were no randomized controlled studies of the benefits of the Pap test (cervical cancer) when it was introduced in 1920s. Today, there is indirect epidemiological evidence from well over a dozen uncontrolled studies of cervical cancer screening that the Pap test is effective in reducing mortality from this disease. Initially uncontrolled trials may be useful in evaluating whether a specific therapy-appears lo have any value in a particular disease, to determine an appropriate dose, to investigate adverse reactions, etc. However, even in these uncontrolled trials, one is using implied “historical controls”, i.e., the experience of earlier untreated patients affected by the same disease.

Since most therapeutic trials deal with drugs which do not produce such remarkably beneficial results, it is becoming increasingly common to employ the procedures of a double-blind controlled clinical trial in which the effects of a new drug are compared to some concurrent experience (either placebo or a currently utilized therapy).

2. Natural experiments

Where experimental studies are not possible in human populations, the epidemiologist seeks to identify “natural circumstances” that mimic an experiment. For example, in respect of cigarette smoking, people have separated themselves “naturally” into two groups, smokers and non-smokers. Epidemiologists have taken advantage of this separation and tested hypothesis regarding lung cancer and cigarette smoking. Other populations involved iatural experiments comprise the following groups: (a) migrants (b) religious or social groups (c) atomic bombing of Japan (d) famines (c) earthquakes, etc. A major earthquake in Athens in 1931 provided a “natural experiment” to epidemiologists who studied the effects of acute stress on cardiovascular mortality. They showed an excess of deaths from cardiac and external causes on the days after the major earthquake, but no excess deaths from other causes.

John Snow’s discovery that cholera is a water-borne disease was the outcome of a natural experiment. Snow in his “grand experiment” identified two randomly mixed populations, alike in other important respects, except the source of water supply in their households. The results of the experiment are given in Table 1.

TABLE 1.

Deaths from cholera per 10.000 houses and sources of water supply of these houses, London, 1853

 

It will be seen from Table 1 that deaths were fewer in houses supplied by Lambeth company compared to houses supplied by Southwark and Vauxhall company. The inference was obvious – the Lambeth company water came from an intake on the River Thames well above London, whereas the Southwark and Vauxhall company water was derived from the sewage polluted water basin. The great difference in the occurrence of cholera among these two populations gave clear demonstration that cholera is a water-borne disease. This was demonstrated long before the advent of the bacteriological era; it also led to the institution of public health measures to control cholera.

3. Before and After Comparison Studies

These are community trials which fall into two distinct groups:

A. Before and after comparison studies without control, and

B. Before and after comparison studies with control

A. Before and After Comparison Studies Without Control

These studies centre round comparing the incidence of disease before and after introduction of a preventive measure. The events which took place prior to the use of the new treatment or preventive procedure are used as a standard for comparison. In other words, the experiment serves as its own control; this eliminates virtually all group differences. The classic examples of “before and after comparison studies” were the prevention of scurvy among sailors by James Lind in 1750 by providing fresh fruit: studies on the transmission of cholera by John Snow in 1854; and more recently, prevention of polio by Salk and Sabin vaccines.

In order to establish evidence in before and after comparison studies, the following are needed: (a) data regarding the incidence of disease, before and after introduction of a preventive measure must be available, (b) there should be introduction or manipulation of only one factor or change relevant to the situation, other factors remaining the same, as for example, addition of fluorine to drinking water to prevent dental caries (c) diagnostic criteria of the disease should remain the same (d) adoption of preventive measures should be over a wide area (e) reduction in the incidence must be large following the introduction of the preventive measure, because there is no control and (f) several trials may be needed before the evaluation is considered conclusive.

Table 2 gives an example of a “before and after comparison study” in Victoria (Australia) following introduction of seat-belt legislation for prevention of deaths and injuries caused by motor vehicle accidents.

TABLE 2

Effect of adoption of compulsory seat-belt legislation in Victoria. Australia, 1971

 

Table 2 shows a definite fall in the numbers of death and injuries in occupants of cars, following the introduction compulsory seat-belts in one state of Australia.

6. Before and After Comparison Studies with Control

In the absence of a control group, comparison between observations before and after the use of a new treatment or procedure may be misleading. In such situations, the epidemiologist tries to utilize a “natural” control group i.e., the one provided by nature or natural circumstances. If the preventive programme is to be applied to an entire community, he would select another community as similar as possible, particularly with respect to frequency and characteristics of the disease to be prevented. One of them is arbitrarily chosen to provide the study group and the other a control group. In the example cited (e.g., seat-belt legislation in Victoria, Australia), a natural “control” was sought by comparing the results in Victoria with other states in Australia where similar legislation was not introduced. The findings are given in Table 3.

TABLE 3

Effect of adoption of compulsory seat-belt legislation in Victoria, 1971 compared with other states where similar legislation was not introduced

 

In the example cited above, the existence of a control with which the results in Victoria could be compared strengthens the conclusion that there was definite fall in the number of deaths and injuries in occupants of cats after the introduction compulsory seat-belt legislation.

In the evaluation of preventive measures, three questions are generally considered: (a) How much will it benefit the community? This will depend upon the effectiveness of the preventive measure and the acceptance of the measure] by the community. The combined outcome of effectiveness and acceptability is measured by the difference in the incidence rate among the experimental and control groups. (b) What are the risks to the recipients? These include the immediate and long term risks. (c) Cost in money and man power? This is done to find out whether the preventive measure is economical and practical in terms of money spent. It is now conceded that no health measure should be introduced on a large scale without proper evaluation.

Recent problems that have engaged the attention of epidemiologists are studies of medical care and health services; planning and evaluation of health measures, services and research.

Association and causation

Descriptive studies help in the identification of the disease problem in the community; and by relating disease to host agent and environmental factors it endeavours to suggest an aetiological hypothesis. Analytical and experimental studies test the hypotheses derived from descriptive studies and confirm or refute the observed association between suspected causes and disease. When the disease is multifactorial (e.g., coronary heart disease) numerous factors or variables become implicated in the web of causation, and the notion of “cause” becomes confused. The more associations, the more investigations to disentangle the web of causation. The epidemiologist whose primary interest is to establish a “cause and effect” relationship has to sift the husk from the grain. He proceeds from demonstration of statistical association to demonstration that the association is causal.

The terms “association” and “relationship” are often used interchangeably. Association may be defined as the concurrence of two variables more often than would be expect by chance. In other words, events are said to be associated when they occur more frequently together than one would expect by chance. Association does not necessarily imply a causal relationship.

It will be useful to consider here the concept of correlation. Correlation indicates the degree of association between two characteristics. The correlation coefficients range from -1.0 to +1,0. A correlation coefficient of 1.0 means, that the two variables exhibit a perfect linear relationship. However, correlation cannot be used to invoke causation, because the sequence of exposure preceding disease (temporal association) cannot be assumed to have occurred. Secondly, correlation does not measure risk. It may be said that causation implies correlation, but correlation does not imply causation.

Association can be broadly grouped under three headings:

a.     Spurious association

b.     Indirect association

c.      Direct (causal) association

(I) one-to-one causal association

(II) multifactorial causation

a. Spurious association

Sometimes an observed association between a disease and suspected factor may not be real. For example, a study in UK of 5174 births at home and 11,156 births in hospitals showed perinatal mortality rates of 5,4 per 1000 in the home births, and 27,8 per 1000 in the hospital births. Apparently, the perinatal mortality was higher in hospital births than in the home births. It might be concluded that homes are a safer place for delivery of births than hospitals. Such a conclusion is spurious or artifactual, because in general, hospitals attract women at high risk for delivery because of their special equipment and expertise, whereas this is not the case with home deliveries. The high perinatal mortality rate in hospitals might be due to this fact alone, and not because the quality of care was inferior. There might be other factors also such as. differences in age, parity, prenatal care, home circumstances, general health and disease state between the study and, control groups. This type of bias where “like” is not compared with “like” (selection bias) is very important in epidemiological studies. It may lead to a spurious association or an association wheone actually existed.

b. Indirect association

Many associations which at first appeared to be causal have been found on further study to be due to indirect association. The indirect association is a statistical association between a characteristic (or variable) of interest and a disease due to the presence of another factor, known or unknown, that is common to both the characteristic and the disease. This third factor (i.e., the common factor) is also known as the “confounding” variable. Since it is related both to the disease and to the variable, it might explain the statistical association between disease and a characteristic wholly or in part. Such confounding variables (e.g., age, sex, social class) are potentially and probably present in all data and represent a formidable obstacle to overcome in trying to assess the causal nature of the relationship. Two examples of an indirect association are given below.

FIG. 4. Model of an indirect association

(a) Altitude and endemic goitre:

Endemic goitre is generally found in high altitudes^ showing thereby an association between altitude and endemic goitre (Fig. 4). According to current knowledge, we know that endemic goitre is not due to altitude but due to environmental deficiency of iodine. Fig.4 illustrates how a common factor (i.e., iodine deficiency) can result in an apparent association between two variables, wheo association exists. This amplifies the earlier statement that statistical association does not necessarily mean causation.

(b) Sucrose and CHD:

Yudkin and Roddy found a higher intake of sugar by patients with myocardial infarction. Their study was based on an enquiry by questionnaire method into dietary habits of .cases and controls. They put forward an attractive hypothesis that people who consume lot of sugar are far more likely to have a heart attack than those who take little.

Further studies were undertaken to lest whether sugar intake was associated with other variables such as cigarette smoking, which might be causally related to CHD. Bennet and others found that heavy cigarette smoking was positively associated with an increase in the number of cups of hot drinks consumed daily and the amount of sugar consumed. They concluded that it was cigarette smoking and not sugar consumption which was implicated in the aetiology of CHD. In their study, they did not find any evidence of increasing trend of CHD with increasing consumption of sugar. Finally, proof came from experimental studies that high sucrose feeding did not induce arteriosclerotic disease in animals.

Sometimes knowledge of indirect associations can be applied towards reducing disease risk. Before the discovery of the cholera vibrio, elimination of certain water supplies achieved a marked decrease iew cases of the disease. Such indirect associations must be pursued, for it is likely that they may provide aetiological clues.

c. Direct (causal) association

(I) One-to-one causal relationship:

Two variables are stated to be causally related (AB) if a change in A is followed by a change in B: If it does not, then their relationship cannot be causal. This is known as “one-to-one” causal relationship. This model suggests that when the factor A is present, the disease B must result. Conversely, when the disease is present, the factor must also be present. Measles may be one disease in which such a relation exists.

Epidemiologists are interested in identifying the “cause”. The most satisfactory procedure to demonstrate this would be by direct experiment. But this procedure is scarcely available to the epidemiologist. And, in some cases, the “cause” is not amenable to manipulation.

The above concept of one-to-one causal relationship was the essence of Koch’s postulates. The proponents of the germ theory of disease insisted that the cause must be:

a. necessary, and

b. sufficient for the occurrence of disease

before it can qualify as cause of disease. In other words, whenever the disease occurs, the factor or cause must be present.

Although Koch’s postulates are theoretically sound, the “necessary and sufficient” concept does not fit welt for many diseases. Taking for example tuberculosis tubercle bacilli cannot be found in all cases of the disease but this does not rule out the statement that tubercle bacilli are the cause of tuberculosis. That the cause must be “sufficient” is also not always supported by evidence. In tuberculosis, it is well-known that besides tubercle bacilli, there are additional factors such as host susceptibility which are required to produce the disease.

The concept of one-to-one causal relationship is further complicated by the fact that sometimes, a single cause or factor may lead to more than one outcome, as shown in Fig.5. In short, one-to-one causal relationship, although ideal in disease aetiology, does not explain every situation.

FIG. 5. Model in which one factor is shown to lead to more than one disease

(II) Multifactorial causation:

The causal thinking is different when we consider a non-communicable disease or condition (e.g., CHD) where the aetiology is multifactorial. Two models are presented in Figures 6 and 7 to explain the complex situation. In one model (Fig. 6), there are alternative causal factors (Factors 1,2 and 3) each acting Independently. This situation is exemplified in lung cancer where more than one aetiological factor (e.g., smoking, air pollution, exposure to asbestos) can produce the disease independently. It is possible as our knowledge of cancer increases we may discover a common biochemical event at the cellular level that can be produced by each of the factors. The cellular or molecular factor will then b« considered necessary as a-causal factor.

 

FIG. 6. A model of multifactorial causation showing synergism.

 

In the second model (Fig. 7) the causal factors act cumulatively to produce disease. This is probably the correct model for many diseases. It is possible that each of the several factors act independently, but when an individual is exposed to 2 or more factors, there may be a synergistic effect.

FIG. 7 A model of multifactorial causation showing synergism

From the above discussion, it is reasonable to conclude that “one-to-one” relationship in causation Is an oversimplification. In biological phenomena, the requirement that “cause” is both “necessary” and “sufficient” condition is not easily reached because of the existence of multiple factors in disease aetiology. This has created a serious problem to the epidemiologist, who is in search of causes of disease.

Additional criteria for judging causality

In the absence of controlled experimental evidence to incriminate the “cause”, certain additional criteria have been evolved (or deciding when an .association may be considered a causal association. An elegant elucidation of these criteria appears in “Smoking and Health” the (1964) Report of the Advisory Committee to the Surgeon General of Health Service in US. Bradford Hill and others have pointed out that the likelihood of a causal relationship is increased by the presence of the following criteria.

1. Temporal association

2. Strength of association

3. Specificity of the association

4. Consistency of the association

5. Biological plausibility

6. Coherence of the association

The Surgeon-General’s Report (1964) states, that the causal significance of an association is a matter of judgement, which goes beyond any statement of statistical probability. To judge or evaluate the causal significance of an association, all the above criteria must be utilized, no one of which by itself is self-sufficient or a sine qua- non for drawing, causal inferences from statistical associations, but each adds to the quantum of evidence, and all put together contribute to a probability of the association being causal.

Investigation of an epidemic

The occurrence of an epidemic always signals some significant shift in the existing balance between the agent, host and environment. It calls for a prompt and thorough investigation of the cases to uncover the factor (s) responsible and to guide in advocating control measures to prevent further spread. Emergencies caused by epidemics remain one of the most important challenges to national health administrations. Epidemiology has an important role to play in the investigation of epidemics. The objectives of an epidemic investigation are:

a.      to define the magnitude of the epidemic outbreak or involvement in terms of time, place and person.

b.      to determine the particular conditions and factors responsible for the occurrence of the epidemic.

c.       to identify the cause, source(s) of infection, and modes of transmission to determine measures necessary to control the epidemic; and

d.      to make recommendations to prevent recurrence.

An epidemic investigation calls for inference as well as description. Frequently, epidemic investigations are called for after the peak of the epidemic has occurred; in such cases, the investigation is mainly retrospective. No step by step approach applicable in all situations can be described like a “cook-book”. However, in investigating an epidemic, it is desired to have an orderly procedure or practical guidelines as outlined below which are applicable for almost any epidemic study. Some of the steps can be done concurrently.

1.      Verification of diagnosis

Verification of diagnosis is the first step in an epidemic investigation, as it may happen sometimes that the report may be spurious, and arise from misinterpretation of signs and symptoms by the lay public. It is therefore necessary to have the verification of diagnosis on the spot, as quickly as possible. It is not necessary to examine all the cases to arrive at a diagnosis. A clinical examination of a sample of cases may well suffice. Laboratory investigations wherever applicable, are most useful to confirm the diagnosis but the epidemiological investigations should not be delayed until the laboratory results are available.

2.      Confirmation of the existence of an epidemic

The next step is to confirm if epidemic exists. This is done by comparing the disease frequencies during the same period of previous years. An epidemic is said to exist when the number of cases (observed frequency) is in excess of the expected frequency for that population, based on past experience. An arbitrary limit of two standard errors from the endemic occurrence is used to define the epidemic threshold for common diseases such as influenza. Often the existence of an epidemic is obvious needing no such comparison, as in the case of common-source epidemics of cholera, food poisoning and hepatitis A. These epidemics are easily recognized. In contrast the existence of modern epidemics (e.g., cancer, cardiovascular diseases) is not easily recognized unless comparison is made with previous experience.

3.      Defining the population at risk

(a)Obtaining a map of the area: Before beginning the investigation, it is necessary to have a detailed and current map of the area. If this is not available it may be necessary to prepare such a map. It should contain information concerning natural landmarks, roads and the location of all dwelling units along each road or in isolated areas. The area may be divided into segments, using natural landmarks as boundaries. This may again be divided into smaller sections. Within each section the dwelling units (houses) may be designated by numbers.

(b)Counting the population: The denominator may be related to the entire population or subgroups of a population. It may also be related to total events. For example, if the denominator is the entire population a complete census of the population by age and sex should be carried out in the defined area by house-to-house visits. For this purpose lay health workers in sufficient numbers may be employed. Using this technique it is possible to establish the size of the population. The population census will help in computing the much-needed attack rates in various groups and subgroups of the population later on. Without an appropriate denominator of “population at risk” attack rates cannot be calculated.

4.      Rapid search for all cases and their characteristics

(a)Medical survey: Concurrently, a medical survey should be carried out in the defined area to identify all cases including those who have not sought medical care, and those possibly exposed to risk. Ideally, the complete survey (screening each member of the population for the presence of the disease in question) will pick up all affected individuals with symptoms or signs of the disorder. Lay health workers may be trained to administer the “epidemiological case sheet” or questionnaire to collect relevant data.

(b)Epidemiological case sheet: The epidemiologist should be armed with an “epidemiological case sheet” for collecting data from cases and from persons apparently exposed but unaffected. The epidemiological case sheet or “case interview form” should be carefully designed (based on the findings of a rapid preliminary inquiry) to collect relevant information. This includes: name, age, sex, occupation, social class, travel, history of previous exposure, time of onset of disease, signs and symptoms of illness, personal contacts at home, work, school and other places; special events such as parties attended, foods eaten and exposure to common vehicles such as water, food and milk; visits out of the community, history of receiving injections or blood products, attendance at large gathering, etc. The information collected should be relevant to the disease under study. For example, if the disease is food-borne, detailed food histories are necessary. A case review form will ensure completeness and consistency of data collection.

If the outbreak is large, it may not be possible to interview all the cases (e.g., influenza). In such cases, a random sample should be examined and data collected.

(c)     Searching for more cases: The patient may be asked if he knew of other cases in the home, family, neighbourhood, school, work place having an onset within the incubation of the Index case. Cases admitted to the local hospitals should also be taken into consideration. This may reveal not only additional cases but also person-to-person spread. The search for new cases (secondary cases) should be carried out everyday, till the area is declared free of epidemic. This period is usually taken as twice the incubation period of the disease since the occurrence of last case.

5.      Data analysis

The data collected should be analysed on ongoing basis, using the classical epidemiological parameters – time, place and person. If the disease agent is known, the characteristics of time, place and person may be rearranged into Agent-Host-Environment model.

a.      Time: Prepare a chronological distribution of dates of onset and construct an “epidemic curve”. Look for time clustering of cases. An epidemic curve may suggest: (a) a time relationship with exposure to a suspected source; (b)whether it is a common-source or propagated epidemic, and (c) whether it is a seasonal or cyclic pattern suggestive of a particular infection.

b.      Place: Prepare a “spot map” (geographic distribution) of cases, and if possible, their relation to possible sources of infection, e.g., water supply, air pollution, foods eaten, occupation, etc. Clustering of cases may indicate a common source of Infection. Analysis of geographic distribution may provide evidence of the source of disease and its mode of spread. This was demonstrated by John Snow in the cholera outbreak in the

Golden Square

district, London.

c.       Person: Analyse the data by age, sex, occupation and other possible risk factors. Determine the attack rates/case fatality rates, for those exposed and those not exposed and according to hose factors. For example, in most food-borne outbreaks, food-specific attack rates must be calculated for each food eaten to determine the source of infection.

The purpose of data analysis is to identify common event or experience, and to delineate the group involved in the common experience.

6.      Formulation of hypotheses

On the basis of time, place and person distribution or the Agent-Host-Environment model, formulate hypotheses to explain the epidemic in terms of (a) possible source (b) causative agent (c) Possible modes of spread, and (d) the environmental factors which enabled it to occur. These hypotheses should be placed in order of relative likelihood. Formulation of a tentative hypothesis should guide further investigation.

7.      Testing of hypotheses

All reasonable hypotheses need to be considered and weighed by comparing the attack rates in various groups for those exposed and those not exposed to each suspected factor. This will enable the epidemiologist to ascertain which hypothesis is consistent with all the known facts. When divergent theories are presented, it is not easy to distinguish immediately between those which are sound and those which are merely plausible. Therefore it is instructive to turn back to arguments which have been tested by the subsequent course of events.

8.      Evaluation of ecological factors

An investigation of the circumstances involved should be carried out to undertake appropriate measures to prevent further transmission of the disease. Ecological factors which have made the epidemic possible should be investigated such as sanitary status of eating establishments, water and milk .supply; breakdown in the water supply system; movements of the human population, atmospheric changes such as temperature, humidity and air pollution, population dynamics of insects and animal reservoirs. The outbreak can be studied in a case control fashion. One of the primary concerns of the epidemiologist is to relate the disease to environmental factors to know the source(s) of infection, reservoirs and modes of transmission.

9.      Further investigation of population at risk

A study of the population at risk or a sample of it may be needed to obtain additional information. This may involve medical examination, screening tests, examination of suspected food, faeces or blood samples, biochemical studies, assessment of immunity status, etc. The approach may be retrospective or prospective, For example, serological study may reveal clinically inapparent cases and throw light on the pathogenesis of the condition. Healthy individuals (those who are not ill) from the same universe may be studied in a case control fashion. This will permit classification of ail members as to:

a. exposure to specific potential vehicles

b. whether ill or not

10. Writing the report

The report should be complete and convincing. Information to be included in the final report on an epidemic is given in Table 4.

TABLE 4

Information to be included in the final report on an epidemic

Section

Contents

 

1.      Background

Geographical location

Climatic conditions

Demographic status (population pyramid)

Socioeconomic situation

Organization of health services

Surveillance and early warning systems

Normal disease prevalence

2.      Historical data

Previous occurrence of epidemics

of the same disease,

locally or elsewhere   .

Occurrence of related diseases, if any

                   –        in the same area

                   –        in other areas

Discovery of the first cases of the present outbreak

3.      Methodology of investigations

Case definition

Questionnaire used in epidemiological

investigation

Survey teams

Household survey

Retrospective survey

Prospective surveillance

Collection of laboratory specimens

Laboratory techniques

4.      Analysis of data

Clinical data:

–    frequency of signs and symptoms

–    course of disease

–    differential diagnosis

–    death or sequelae rates

                   Epidemiological data:

–    mode of occurrence

–    in time

–   by place

–   by population groups

                   Modes of transmission:

–    source(s) of infection

–    route(s) of excretion and portal(s) of entry

–    factors influencing transmission

Laboratory data:

–    isolation of agent(s)

–    serological confirmation

–    significance of results

                   Interpretation of data :

–    comprehensive picture of the outbreak

–    hypotheses as to cause(s)

–     formulation and testing of hypotheses by statistical analysis

5.      Control measures

Definition of strategies and methodology of implementation

                            – constraints

–    results

                   Evaluation:

–    significance of results

–    cost/effectiveness

                   Preventive measures

It may be necessary to implement temporary control measures at the commencement of an epidemic on the basis of known facts of the disease. These measures may be modified or replaced in the light of new knowledge acquired by the epidemic investigation. As Frost observed, an epidemiological investigation is more than the collection of tablished facts. It includes their orderly arrangement into chains of inference, which extend more or less beyond the bounds of direct observation.

The field of Social Medicine seeks to: (1) understand how social and economic conditions impact health, disease and the practice of medicine and (2) foster conditions in which this understanding can lead to a healthier society. This type of study began formally in the early 1800’s. The Industrial Revolution and the subsequent increase in poverty and disease among workers raised concerns about the effect of social processes on the health of the poor.

 

What is social medicine?

This is a question we hear all the time from students. This site has been created by faculty at the Department of Social and Family Medicine at AECOM to answer that question. The Social Medicine Portal will showcase the many aspects of social medicine and the incredible breadth of the movements inspired by it.

It is possible to argue that all medicine by its very nature is social. The way we define diseases and health, the methods we use for diagnosis and treatment, how we finance health care, all these cannot help but reflect the social environment in which medicine operates.

Social medicine, however, looks at these interactions in a systematic way and seeks to understand how health, disease and social conditions are interrelated. This type of study began in earnest in the early 1800’s. It was the time of the Industrial Revolution and it was impossible to ignore the extent to which the factory system impoverished the workers, thus creating poverty and disease.

The most famous representative of early social medicine is Rudolf Virchow, the distinguished German pathologist who developed the theory of cellular pathology. Virchow was also a social reformer who remarked that “politics is nothing more than medicine on a grand scale.” In the 20th century George Rosen would distill the Virchow’s principles into the following:

1.                 Social and economic conditions profoundly impact health, disease and the practice of medicine.

2.                 The health of the population is a matter of social concern.

3.                 Society should promote health through both individual and social means.

As might be gathered from these ideas, social medicine was not simply an academic pursuit. Its practitioners were political reformers, radicals, activists. Virchow believed that the “physician was the natural advocate for the poor.” And this defense of social justice would stamp future generations of physicians and health care workers.

Social medicine has grown and developed in many different ways in the past two centuries. At times it has seemed as if the “biomedical paradigm” would make social issues in medicine irrelevant. Yet we cannot escape the reality that we are social animals and our diseases occurs in “social animals” and not in test-tubes. The current debate over HIV treatment access illustrates both the astounding success and spectacular failure of modern biomedicine. Why is it that most AIDS patients will simply not get the medications that can save their lives? What would Virchow have said?

For a brief introduction to social medicine, Drs. Tim Holtz and Alyssa Finlay have prepared a talk entitled Social Medicine: History and Contemporary Relevance, which you can download from this page (PowerPoint™ document).

 

The person as biopsychosociosystem

 

Statistical methods

The bases definitions

Among many definitions of statistics in general and medical statistics in particular the best expression of the essence of the science makes the following:

The medical statistics is a science which studies health of the population depending on social, economic, cultural, sanitary-hygienic, medical and biologic factors and has a goal of establishment of tendencies of these dependences in conditions of activity of system medical care.

The medical statistics studies:

1.0 Health of the population:

        1.1 Demographic processes;

1.2 Morbidity;

1.3 Invalidity;

1.4 Somatometry and determining of biochemical constants;

1.5 Mental health and psychometry.

2.0 Conditions of an environment and people’s life styles:

2.1 Air;

2.2 Water;

2.3 Radiation;

2.4 Nutrition;

2.5 Material welfare;

2.6 Work and training;

2.7 Rest;

2.8 Behavior.

3.0 Medical base:

3.1 Medical establishments;

3.2 Health manpower;

3.3 The budget of public health services.

4.0 Activity of system of public health services:

4.1 Ambulatory and polyclinics;

4.2 Hospitals;

4.3 Drugstores;

4.4 Social – medical activity.

The stages of statistical research:

1.0  Composition of the program and plan of research.

Choosing of the aim and tasks of research, choosing of the unit and object of investigation.

2.0  Collection of the material.

      Making a program of date collection and analysis of date, current   control.

      Working up of material.

Documents control.

Encoding and tabulation.

Distribution to groups.

3.0  Analysis of material.

Machine processing.

              Conclusions and proposals.

4.0  Putting into practice.

 

The ways of formation of statistical integrity:

1.0 By volume

2.0 By time

3.0 By type

 

The plan and program of medico-statistical research includes:

1.0 Data collection:

1.1 A concentration and preservation of the data;

1.2 Data transmission.

2.0 Data processing:

2.1 Normalization (standardization) of the data;

        2.2 Coding and grouping of the data;

        2.3 Registration;

2.4 Calculation of average values, dispersions, errors;

2.5 Comparison, definition of a difference;

2.6 Correlation, regress, complex estimations.

3.0 The analysis of the data:

3.1 Survey, interpretation analysis;

3.2 The mathematical analysis: disperse, discriminately,

               multifactor, initial, logistic, system, etc.

                                                                                     

So, the subject of studying of medical statistics is a level of health of the population in its structure and dynamics.

The important interest of medical statistics is quantitative and qualitative analyses of activity of a treatment-and-prophylactic network, an estimation of this activity through the mechanism of influence on a state of health with the obligatory account of complex influence of different factors.

Registration and accounting medical documents can serve as programs of medic-statistical research.

Medic-statistical research can be complete or selective.

Complete or continuous research covers all observation units.

Selective research covers a representative part of the supervision units, which enables to evaluate phenomenon in whole.

Research is of great importance. The territory strongly influences the results of research.

The next question is time and term of the research. Research can last constantly, that is to be current, to be carried out periodically, during certain time or to be one-stage.

Constant researches are: studying of natural movement of the population, periodic — studying of prevalence of chronic diseases, one-stage — population census, fixing of a condition of medical service.

So, after collection the statistical data is being processed. This process includes quantitative and qualitative check, coding and grouping of these data. Quantitative check means check of correctness of statistical record of documents, qualitative — logic comparison of the data, for example, age and the diagnosis, age and employment, growth and weight of a body, etc. Later there is coding. To each quantitative or qualitative characteristic of the phenomenon certain code is given.

Grouping may be a distribution of the data according to quantitative or qualitative characteristics with the purpose of their analysis. Quantitative characteristics are age, growth, weight, etc. Qualitative characteristics are background, social status, occupation, disease, etc.

Grouping is simple (according to one characteristic), complex (according to many characteristics, which are combined among themselves) and repeated (grouping before the divided earlier groups with the purpose of deeper studying the phenomenon).

Grouping — is the central moment of research and it should be carried out on the basis of deep study of the essence of a problem.

Variable — is a quantitative or qualitative values of the concrete characteristic of the phenomenon, for example, newborn can have length of a body 47, 48, 49, 50, etc. see. This newborn can be of a different sex: boy or girl. A variable can be submitted as absolute, relative number and qualitative characteristics.

An absolute value — the number which characterizes the phenomenon in its absolute (arithmetic) value.

A relative value — a number which characterizes the relation of one value to another and can mean a part, frequency or a ratio of one number to another.

Each value of variable (х) is answered with its frequency (n) from which it repeats. A row of variable with their frequencies makes a so-called variation line.

Table  2.1 A variation line

 

Variable which form a variation line, can consist of simple a variable (weight — 2900g) or discrete (2900-3100 g).

  The Range

The range is the difference between the highest and lowest values in a series.

1. The range is used to measure data spread.

2. The range provides no information concerning the scatter within the series.

Statistical totality will consist of elements, which have identical characteristics and represent an object of the statistical analysis. For example, in research of demographic problems of the country by statistical set there will be all of its population; in research of the stationary aid — hospitalized patients.

General statistical totality includes all elements of research.

Selective statistical totality contains a part of general totality, which represents all of its elements. It should to be selected from general statistical set to give the same chance to get in sample to each statistical unit.

Statistical unit (unit supervision) submitted by an element of which there is a statistical set (for example, a person, a family, a newborn, a pregnant woman, a patient with ischemic heart disease, etc.

    Statistical attribute is a general property for all units, which is studied during statistical research, for example, studying of weight, growth, disease iewborn etc.

Statistical index is the statistical value which makes it possible to characterize the phenomenon.

Processing the statistical data and the formation of statistical tables allows understanding the researched phenomena better.

Statistical tables are breadboard models, which will consist of columns and lines on which crossing statistics data are placed.

There are simple, group and combined tables.

Table  2.2 Number of medical establishments in the area (the simple table)

 

Table  2.3 Territorial distribution of medical establishments in the area (the group table)

 

 

Table   2.4 Territorial division of medical establishments according to the form of property

 

 

After processing the material and formation of statistic tables process of calculation of statistics or values   starts.

Absolute numbers have certain value, in particular, if the question is about insignificant or, on the contrary, socially significant phenomena. So, one case of AIDS on a medical station indicates the extremely negative epidemiological situation; at the same time 4 cases of AIDS has to put all medical service of the region on ears.

The average value characterizes the phenomenon in one way. It is much more frequently applied in the statistical analysis — an average term of stay of the patient in bed, average spaciousness of hospitals, etc.

The dispersion from average value shows variability (fluctuation) of an individual cases in relation to average value.

The average error displays the relation of the statistics received at selective research, to a parameter of continuous or complete research.

Parameters of correlation and regress are used for definition of functional, causal relationships between two or more characteristics.

Extensive parameters characterize the structure of statistical totality.

Intensive parameters display frequency of the phenomenon in the environment, indicate its level.

 

Relative values 

As a result of statistical research during processing of the statistical data of disease, mortality rate, lethality, etc. absolute numbers are received, which specify the number of the phenomena. Though absolute numbers have a certain cognitive values, but their use is limited. For determination of a level of the phenomenon, for comparison of a parameter in dynamics or with a parameter of other territory it is necessary to calculate  relative values (parameters, factors) which represent result of a ratio of statistical numbers between itself. The basic arithmetic action at subtraction of relative values is division.

In medical statistics themselves the following kinds of relative parameters are used:

— Extensive;

— Intensive;

— Relative intensity;

— Visualization;

—   Correlation.

For the determination of a structure of disease (mortality rate, lethality, etc.) the extensive parameter is used.

The extensive parameter or a parameter of distribution characterizes a parts of the phenomena (structure), that is it shows, what part from the general number of all diseases (died) is made with this or that disease which enters into total.

Using this parameter, it is possible to determine the structure of patients according to age, social status, etc. It is accepted to express this parameter in percentage, but it can be calculated and in parts per thousand case when the part of the given disease is small and at the calculation in percentage it is expressed as decimal fraction, instead of an integer.

The general formula of its subtraction is the following:       

part × 100

commoumber

Technique of the calculation of an extensive parameter will be shown on an example.

To determine an age structure of those who has addressed in a polyclinic if the following data is known:

Number of addressed — 1500 it is accepted by 100 %, number of patients of each age — accordingly for X, from here per cent of what have addressed in a polyclinic in the age of 15-19 years from the general number, will make:

 

1500 – 100

150 – X,                                  

Table 2.5 Age groups of people, which have visit to polyclinic

Conclusion: most of the people that have addressed in a polyclinic were in the age of 20-29 and 40-49 years.

The extensive parameter at the analysis needs to be used carefully and we must remember that it is used only for the characteristic of structure of the phenomena in the given place and at present time. Comparison of a structure makes it possible to tell only about change of a serial number of the given diseases in structure of diseases.

If it is necessary to determine distribution of the phenomenon intensive parameters are used.

The intensive parameter characterizes frequency or distribution.

It shows how frequently the given phenomenon occurs in the given environment.

For example, how frequently there is this or that disease among the population or how frequently people are dying from this or that disease.

To calculate the intensive parameter, it is necessary to know the population or the contingent.

General formula of the calculation is the following:

phenomenon × 100 (1000; 10 000; 100 000)

environment

 

Intensive parameters are calculated on 1000 persons. These are parameters of birth, morbidity, mortality, etc.; on separate disease they are being calculated on 10.000 and disease, which occurs seldom — on 100000 persons.

Parameters of relative intensity represent a numerical ratio of two or several structures of the same elements of a set, which is studied.

They allow determining a degree of conformity (advantage or reduction) of similar attributes and are used as auxiliary reception; in those cases where it isn’t possible to receive direct intensive parameters or if it is necessary to measure a degree of a disproportion in structure of two or several close processes.

For example, there are data only about structure of the general morbidity, physical disability and mortality rate.

Comparison of these structures and subtraction of parameters of relative intensity allows finding out the relative importance of these or those diseases in health parameters of the population.

So, for example, comparison of densities of physical disability and mortality rates from cardiovascular diseases with its densities in  morbidity  allows to determine, that cardiovascular diseases occupy almost in 7 times more part in physical disability and almost in 5 times — in  mortality , than in structure of morbidity .

The parameter of correlation characterizes the relation between diverse values.

For example, the parameter of average bed occupancy, nurses, etc.

The techniques of subtraction of the correlation  parameter  is the same as for intensive parameter, nevertheless the number of an intensive parameter stands in the numerator,  is included into denominator, where as in a parameter  of visualization  of numerator and denominator different.

The parameter of visualization characterizes the relation of any of comparable values to the initial level accepted for 100. This parameter is used for convenience of comparison, and also in case shows a direction of process (increase, reduction) not showing a level or the numbers of the phenomenon.

It can be used for the characteristic of dynamics of the phenomena, for comparison on separate territories, in different groups of the population, for the construction of graphic.

It is possible to calculate visualization parameters, using absolute numbers, intensive parameters, parameters of correlation, average values, but not extensive parameters, taking into account the above mentioned about this parameter.

It is enough to calculate parameters with the practical purpose to within one tenth.

To determine the tenth share, it is necessary to make calculation to the second sign after a point.

Depending on, whether there will be a second sign more than five or less, the first sign after a point is determined, in the first case it increases for a unit, in the second – it remains the same.

 

References:

1.    David Machin. Medical statistics: a textbook for the health sciences / David Machin, Michael J. Campbell, Stephen J Walters. – John Wiley & Sons, Ltd., 2007. – 346 p.

2.    Nathan Tintle. Introduction to statistical investigations / Nathan Tintle, Beth Chance, George Cobb, Allan Rossman, Soma Roy, Todd Swanson, Jill VanderStoep. – UCSD BIEB100, Winter 2013. – 540 p.

3.    Armitage P. Statistical Methods in Medical Research / P. Armitage, G. Berry, J. Matthews. – Blaskwell Science, 2002. – 826 p.

4.    Larry Winner. Introduction to Biostatistics / Larry Winner. – Department of Statistics University of Florida, July 8, 2004. – 204 p.

5.     Weiss N. A. (Neil A.) Elementary statistics / Neil A. Weiss; biographies by Carol A. Weiss. – 8th ed., 2012. – 774 p.