Medical statistics and its value for the estimation of populations health and activity of organs and establishments of health

INTRODUCTION TO MEDICAL STATISTICS.

MEDICAL STATISTICS AND ITS VALUE FOR THE ESTIMATION OF POPULATIONS HEALTH AND OF ACTIVITY OF ORGANS AND ESTABLISHMENTS OF HEALTH CARE.

 

Statistical analysis features in the majority of papers published in health care journals. Most health care practitioners will need a basic understanding of statistical principles, but not necessarily full details of statistical techniques. Medical statistics can contribute to good research by improving the design of studies as well as suggesting the optimum analysis of the results. Medical statisticians should be consulted early in the planning of a study. They can contribute in a variety of ways at all stages and not just at the final analysis of the data once the data have been collected.

Most health care practitioners do not carry out medical research. However, if they pride themselves on being up to date then they will definitely be consumers of medical research. It is incumbent on them to be able to discern good studies from bad; to be able to verify whether the conclusions of a study are valid and to understand the limitations of such studies. Evidence-based medicine (EBM) or more comprehensively evidence-based health care (EHBC) requires that health care practitioners consider critically all evidence about whether a treatment works. As Machin and Campbell (2005) point out, this requires the systematic assembly of all available evidence followed by a critical appraisal of this evidence.

A particular example might be a paper describing the results of a clinical trial of a new drug. A physician might read this report to try to decide whether to use the drug on his or her own patients. Since physicians are responsible for the care of their patients, it is their own responsibility to ensure the validity of the report, and its possible generalisation to particular patients. Usually, in the reputable medical press, the reader is to some extent protected from grossly misleading papers by a review process involving both specialist clinical and statistical referees. However, often there is no such protection in the general press or in much of the promotional literature sponsored by self-interested parties. Even in the medical literature, misleading results can get through the refereeing net and no journal offers a guarantee as to the validity of its papers.

The use of statistical methods pervades the medical literature. In a survey of original articles published in three UK journals of general practice; British Medical Journal (General Practice Section), British Journal of General Practice and Family Practice; over a 1-year period, Rigby et al (2004) found that 66% used some form of statistical analysis. It appears, therefore, that the majority of papers published in these journals require some statistical knowledge for a complete understanding.

Statistics is not only a discipline in its own right but it is also a fundamental tool for investigation in all biological and medical science. As such, any serious investigator in these fields must have a grasp of the basic principles. With modern computer facilities there is little need for familiarity with the technical details of statistical calculations. However, a health care professional should understand when such calculations are valid, when they are not and how they should be interpreted.

Why use statistics?

To students schooled in the hard sciences of physics and chemistry it may be difficult to appreciate the variability of biological data. If one repeatedly puts blue litmus paper into acid solutions it turns red 100% of the time, not most (say 95%) of the time. In contrast, if one gives aspirin to a group of people with headaches, not all of them will experience relief. Penicillin was perhaps one of the few miracle cures where the results were so dramatic that little evaluation was required. Absolute certainty in medicine is rare.

Measurements on human subjects rarely give exactly the same results from one occasion to the next. For example, O Sullivan et al (1999), found that systolic blood pressure in normal healthy children has a wide range, with 95% of children having systolic blood pressures below 130 mmHg when they were resting, rising to 160 mmHg during the school day, and falling to below 130 mmHg at night.

This variability is also inherent in responses to biological hazards. Most people now accept that cigarette smoking causes lung cancer and heart disease, and yet nearly everyone can point to an apparently healthy 80-year-old who has smoked for 60 years without apparent ill effect.

Although it is now known from the report of Doll et al (2004) that about half of all persistent cigarette smokers are killed by their habit, it is usually forgotten that until the 1950s, the cause of the rise in lung cancer deaths was a mystery and commonly associated with diesel fumes. It was not until the carefully designed and statistically analysed casecontrol and cohort studies of Richard Doll and Austin Bradford Hill and others, that smoking was identified as the true cause. Enstrom and Kabat (2003) have now moved the debate on to whether or not passive smoking causes lung cancer. This is a more difficult question to answer since the association is weaker.

With such variability, it follows that in any comparison made in a medical context, differences are almost bound to occur. These differences may be due to real effects, random variation or both. It is the job of the analyst to decide how much variation should be ascribed to chance, so that any remaining variation can be assumed to be due to a real effect. This is the art of statistics.

 

The field of Medical Statistics 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.

: :  :  :  : timthumb

 

What is Medical Statistics?

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 Medical Statistics Portal will showcase the many aspects of Medical Statistics 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.

Medical Statistics, 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 Medical Statistics 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, Medical Statistics 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.

Medical Statistics 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 Medical Statistics, Drs. Tim Holtz and Alyssa Finlay have prepared a talk entitled Medical Statistics: History and Contemporary Relevance, which you can download from this page (PowerPoint document).

Social properties

Educational level and cultural level, including sanitary

Qualification, working conditions

Rest

Material maintenance

Behavior, lifestyle

Family conditions

Needs in shelter and meal

Consumption of energy and natural goods

Need in medical service

The person as the carrier of social - system quality

 

 

 

 

Mental properties

Interest, inclinations, aspirations, ideals, outlook, beliefs, orientation on socially useful activities

Knowledge, skills, habits

Sensation, memory, perception, thinking, emotions, will

Temperament

Individual as personality (the carrier of consciousness)

 

 

 

 

Biological properties

Heredity

Constitution

Age, sex

Anatomy, physiology, biochemistry and biophysics of organs and systems

The person as a biological organism

 

The person as biopsychosociosystem

 

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]

: :  :  :  : :  : Image:WFR Weldon.jpgWalter 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 born next 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[citation needed].

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]

: :  :  :  : :  : Image:Karl Pearson.jpgCarl 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[citation needed], 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[citation needed], 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 biographya three-volume tome of narrative, letters, genealogies, commentaries, and photographspublished 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 chairthe 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

 

Statistics is about common sense and good design

A well-designed study, poorly analysed, can be rescued by a reanalysis but a poorly designed study is beyond the redemption of even sophisticated statistical manipulation. Many experimenters consult the medical statistician only at the end of the study when the data have been collected. They believe that the job of the statistician is simply to analyse the data, and with powerful computers available, even complex studies with many variables can be easily processed. However, analysis is only part of a statisticians job, and calculation of the final p-value a minor one at that!

A far more important task for the medical statistician is to ensure that results are comparable and generalisable.

-:  : Example from the literature: Fluoridated water supplies
A classic example is the debate as to whether fluorine in the water supply is related to cancer mortality. Burke and Yiamouyannis (1975) considered 10 fluoridated and 10 non-fluoridated towns in the USA. In the fluoridated towns, the cancer mortality rate had increased by 20% between 1950 and 1970, whereas in the non-fluoridated towns the increase was only 10%. From this they concluded that fluoridisation caused cancer. However, Oldham and Newell (1977), in a careful analysis of the changes in agegenderethnic structure of the 20 cities between 1950 and 1970, showed that in fact the excess cancer rate in the fluoridated cities increased by only 1% over the 20 years, while in the unfluoridated cities the increase was 4%. They concluded from this that there was no evidence that fl uoridisation caused cancer. No statistical significance testing was deemed necessary by these authors, both medical statisticians, even though the paper appeared in a statistical journal!

In the above example age, gender and ethnicity are examples of confounding variables as illustrated in Figure 1.1. In this example, the types of individuals exposed to fluoridation depend on their age, gender and ethnic mix, and these same factors are also known to influence cancer mortality rates. It was established that over the 20 years of the study, fluoridated towns were more likely to be ones where young, white people moved away and these are the people with lower cancer mortality, and so they left behind a higher risk population.

Any observational study that compares populations distinguished by a particular variable (such as a comparison of smokers and non-smokers) and ascribes the differences found in other variables (such as lung cancer rates) to the first variable is open to the charge that the observed differences are in fact due to some other, confounding, variables. Thus, the difference in lung cancer rates between smokers and non-smokers has been ascribed to genetic factors; that is, some factor that makes people want to smoke also makes them more susceptible to lung cancer. The difficulty with observational studies is that there is an infinite source of confounding variables. An investigator can measure all the variables that seem reasonable to him but a critic can always think of another, unmeasured, variable that just might explain the result. It is only in prospective randomised studies that this logical difficulty is avoided. In randomised studies, where exposure variables (such as alternative treatments) are assigned purely by a chance mechanism, it can be assumed that unmeasured confounding variables are comparable, on average, in the two groups. Unfortunately, in many circumstances it is not possible to randomise the exposure variable as part of the experimental design, as in the case of smoking and lung cancer, and so alternative interpretations are always possible.

 

Types of data

Just as a farmer gathers and processes a crop, a statistician gathers and processes data. For this reason the logo for the UK Royal Statistical Society is a sheaf of wheat. Like any farmer who knows instinctively the difference between oats, barley and wheat, a statistician becomes an expert at discerning different types of data. Some sections of this book refer to different data types and so we start by considering these distinctions. Figure 1.2 shows a basic summary of data types, although some data do not fi t neatly into these categories.

 

-:  : Example from the literature: Risk factors for endometrial cancer
Table 1.1 gives a typical table reporting baseline characteristics of a set of patients entered into a casecontrol study which investigated risk factors for endometrial cancer (Xu et al, 2004). We will discuss the different types of data given in this paper.

Categorical or qualitative data

Nominal categorical data

Nominal or categorical data are data that one can name and put into categories. They are not measured but simply counted. They often consist of unordered eitheror type observations which have two categories and are often know as binary. For example: Dead or Alive; Male or Female; Cured or Not Cured; Pregnant or Not Pregnant. In Table 1.1 having a first-degree relative with cancer, or taking regular exercise are binary variables. However, categorical data often can have more that two categories, for example: blood group O, A, B, AB, country of origin, ethnic group or eye colour. In Table 1.1 marital status is of this type. The methods of presentation of nominal data are limited in scope. Thus, Table 1.1 merely gives the number and percentage of people by marital status.

Ordinal data

If there are more than two categories of classification it may be possible to order them in some way. For example, after treatment a patient may be either improved, the same or worse; a woman may never have conceived, conceived but spontaneously aborted, or given birth to a live infant. In Table 1.1 education is given in three categories: none or elementary school, middle school, college and above. Thus someone who has been to middle school has more education than someone from elementary school but less than someone from college. However, without further knowledge it would be wrong to ascribe a numerical quantity to position; one cannot say that someone who had middle school education is twice as educated as someone who had only elementary school education. This type of data is also known as ordered categorical data.

Ranks

In some studies it may be appropriate to assign ranks. For example, patients with rheumatoid arthritis may be asked to order their preference for four dressing aids. Here, although numerical values from 1 to 4 may be assigned to each aid, one cannot treat them as numerical values. They are in fact only codes for best, second best, third choice and worst.

 

Numerical or quantitative data

Count data

Table 1.1 gives details of the number of pregnancies each woman had had, and this is termed count data. Other examples are often counts per unit of time such as the number of deaths in a hospital per year, or the number of attacks of asthma a person has per month. In dentistry, a common measure is the number of decayed, filled or missing teeth (DFM).Measured or numerical continuous Such data are measurements that can, in theory at least, take any value within a given range. These data contain the most information, and are the ones most commonly used in statistics. Examples of continuous data in Table 1.1 are: age, years of menstruation and body mass index.

However, for simplicity, it is often the case in medicine that continuous data are dichotomised to make nominal data. Thus diastolic blood pressure, which is continuous, is converted into hypertension (>90 mmHg) and normotension (≤90 mmHg). This clearly leads to a loss of information. There are two main reasons for doing this. It is easier to describe a population by the proportion of people affected (for example, the proportion of people in the population with hypertension is 10%). Further, one often has to make a decision: if a person has hypertension, then they will get treatment, and this too is easier if the population is grouped.

One can also divide a continuous variable into more than two groups. In Table 1.1 per capita income is a continuous variable and it has been divided into four groups to summarise it, although a better choice may have been to split at the more convenient and memorable intervals of 4000, 6000 and 8000 yuan. The authors give no indication as to why they chose these cut-off points, and a reader has to be very wary to guard against the fact that the cuts may be chosen to make a particular point.

: :  : http://img.skitch.com/20101122-c1p8jwrwfe1acy3utbkc86tara.jpg

Interval and ratio scales

One can distinguish between interval and ratio scales. In an interval scale, such as body temperature or calendar dates, a difference between two measurements has meaning, but their ratio does not. Consider measuring temperature (in degrees centigrade) then we cannot say that a temperature of 20C is twice as hot as a temperature of 10C. In a ratio scale, however, such as body weight, a 10% increase implies the same weight increase whether expressed in kilograms or pounds. The crucial difference is that in a ratio scale, the value of zero has real meaning, whereas in an interval scale, the position of zero is arbitrary.

One difficulty with giving ranks to ordered categorical data is that one cannot assume that the scale is interval. Thus, as we have indicated when discussing ordinal data, one cannot assume that risk of cancer for an individual educated to middle school level, relative to one educated only to primary school level is the same as the risk for someone educated to college level, relative to someone educated to middle school level. Were Xu et al (2004) simply to score the three levels of education as 1, 2 and 3 in their subsequent analysis, then this would imply in some way the intervals have equal weight.

How a statistician can help

Statistical ideas relevant to good design and analysis are not easy and we would always advise an investigator to seek the advice of a statistician at an early stage of an investigation. Here are some ways the medical statistician might help.

: :  : http://annals.org/data/Journals/AIM/19935/8FF1.jpeg

Sample size and power considerations

One of the commonest questions asked of a consulting statistician is: How large should my study be? If the investigator has a reasonable amount of knowledge as to the likely outcome of a study, and potentially large resources of finance and time, then the statistician has tools available to enable a scientific answer to be made to the question. However, the usual scenario is that the investigator has either a grant of a limited size, or limited time, or a limited pool of patients. Nevertheless, given certain assumptions the medical statistician is still able to help. For a given number of patients the probability of obtaining effects of a certain size can be calculated. If the outcome variable is simply success or failure, the statistician will need to know the anticipated percentage of successes in each group so that the difference between them can be judged of potential clinical relevance. If the outcome variable is a quantitative measurement, he will need to know the size of the difference between the two groups, and the expected variability of the measurement. For example, in a survey to see if patients with diabetes have raised blood pressure the medical statistician might say, with 100 diabetics and 100 healthy subjects in this survey and a possible difference in blood pressure of 5 mmHg, with standard deviation of 10 mmHg, you have a 20% chance of obtaining a statistically significant result at the 5% level.

This statement means that one would anticipate that in only one study in five of the proposed size would a statistically significant result be obtained. The investigator would then have to decide whether it was sensible or ethical to conduct a trial with such a small probability of success. One option would be to increase the size of the survey until success (defined as a statistically significant result if a difference of 5 mmHg or more does truly exist) becomes more probable.

Questionnaires

Rigby et al (2004), in their survey of original articles in three UK general practice journals, found that the most common design was that of a cross-sectional or questionnaire survey, with approximately one third of the articles classified as such.

For all but the smallest data sets it is desirable to use a computer for statistical analysis. The responses to a questionnaire will need to be easily coded for computer analysis and a medical statistician may be able to help with this. It is important to ask for help at an early stage so that the questionnaire can be piloted and modified before use in a study.

: :  : http://www.thelancetstudent.com/wp-content/uploads/2010/06/numbers-300x290.jpgChoice of sample and of control subjects

The question of whether one has a representative sample is a typical problem faced by statisticians. For example, it used to be believed that migraine was associated with intelligence, perhaps on the grounds that people who used their brains were more likely to get headaches but a subsequent population study failed to reveal any social class gradient and, by implication, any association with intelligence. The fallacy arose because intelligent people were more likely to consult their physician about migraine than the less intelligent.

In many studies an investigator will wish to compare patients suffering from a certain disease with healthy (control) subjects. The choice of the appropriate control population is crucial to a correct interpretation of the results.

Design of study

It has been emphasised that design deserves as much consideration as analysis, and a statistician can provide advice on design. In a clinical trial, for example, what is known as a double-blind randomised design is nearly always preferable (see Chapter 13), but not always achievable. If the treatment is an intervention, such as a surgical procedure it might be impossible to prevent individuals knowing which treatment they are receiving but it should be possible to shield their assessors from knowing.

Laboratory experiments

Medical investigators often appreciate the effect that biological variation has in patients, but overlook or underestimate its presence in the laboratory. In doseresponse studies, for example, it is important to assign treatment at random, whether the experimental units are humans, animals or test tubes. A statistician can also advise on quality control of routine laboratory measurements and the measurement of within- and between-observer variation.

Displaying data

A well-chosen figure or graph can summarise the results of a study very concisely. A statistician can help by advising on the best methods of displaying data. For example, when plotting histograms, choice of the group interval can affect the shape of the plotted distribution; with too wide an interval important features of the data will be obscured; too narrow an interval and random variation in the data may distract attention from the shape of the underlying distribution.

Choice of summary statistics and statistical analysis

The summary statistics used and the analysis undertaken must reflect the basic design of the study and the nature of the data. In some situations, for example, a median is a better measure of location than a mean. In a matched study, it is important to produce an estimate of the difference between matched pairs, and an estimate of the reliability of that difference. For example, in a study to examine blood pressure measured in a seated patient compared with that measured when he is lying down, it is insufficient simply to report statistics for seated and lying positions separately. The important statistic is the change in blood pressure as the patient changes position and it is the mean and variability of this difference that we are interested in. A statistician can advise on the choice of summary statistics, the type of analysis and the presentation of the results.

Further reading

Swinscow and Campbell (2002) is an introductory text, which concentrates mainly on the analysis of studies, while Bland (2000) and Campbell (2006) are intermediate texts. Altman (1991) and Armitage et al (2002) give lengthier and more detailed accounts. Machin and Campbell (2005) focus on the design, rather than analysis, of medical studies in general.

: :  : http://www.learn-medical-statistics.com/Layout/courses-for-doctors-Learn-Medical-Statistics-for-clinicians.jpg

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 peoples 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 peoples 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 peoples 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 peoples 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 diseases 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 4th 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 10th 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 17th-18th centuries lots of acts, which regulated the doctors and pharmacists work were promulgated.

The development of social medicine was connected with an organization of peoples 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 Berlins association of health protection in 1883.

So, before the beginning of the 20th 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 30th 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 20th 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 prevalences 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 humans 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 humans 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 peoples 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 specialists 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 humans 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 peoples 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 peoples 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 humans 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 didnt 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 humans 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 humans health, or it take into consideration all complex of the factors, which influences upon humans 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 humans health and processes of its reproduction;

-ensuring of thorough characteristic of movements(dynamics), which take place in indices of humans 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 populations sanitation and determination of principles of health protection system, its theoretical and organizing bases;

-analysis of health service organs 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 humans 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 resolution number 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 peoples health examination and activity of establishments and organs of health protection.

Majority of the demands of humans right Declaration concerning of ensuring humans 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 doesnt 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 childrens education and their holding, who have been repudiated by their real parents.

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 its 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 Ukrainian nation 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 society.

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 publics 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 persons 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 common number 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 mM mistake of average sizes, m% - mistake of relative sizes);

5.                  Mutual connection between characteristics (criterion rxy - 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.

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 peoples 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.

 

: :  :  :  : http://www4.asq.org/blogs/statistics/Images/Stat_Thinking-Methods%20A.jpg

Exercises

1. Consider a survey of nurses opinions of their working conditions. What type of variables are: (i) length of service (ii) staff grade (iii) age (iv) salary (v) number of patients seen in a day (vi) possession of a degree.

2. What differences do you think are there in a discrete measurement such as shoe size, and a discrete measurement such as family size?

3. Many continuous variables are dichotomised to make them easier to understand e.g. obesity (body mass index >30 kg/m2) and anaemia (haemoglobin level <10 g/dl). What information is lost in this process? If you were told that a patient was anaemic, what further information would you want before treating the patient? How does a label, such as anaemia, help?

 

 

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.