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Descriptive epidemiology

This document discusses descriptive epidemiology and the concept of association vs causation. It defines descriptive epidemiology as describing the pattern of disease occurrence in a population. The key steps in a descriptive study are defining the population and disease, describing disease characteristics, measuring disease occurrence, comparing to other populations, and formulating hypotheses. Association means two variables occur together more than by chance, while causation means a change in one variable causes a change in the other. Causation can be direct, indirect, or spurious. Multifactorial diseases have multiple causal factors that interact. Determining causation from associations requires considering multiple types of evidence.

Health & Medicine◦
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Visión de la Salud Pública•
DESCRIPTIVE EPIDEMIOLOGY ASSOCIATION AND CAUSATION Department of Public Health Dentistry People’s College of Dental Sciences and Research Centre.
DEFINITION The study of the distribution and determinants of disease frequency in man.
EPIDEMIOLOGICAL METHODS Epidemiology as a science is organized into three distinct divisions; 1. Descriptive Epidemiology 2. Analytical Epidemiology 3. Experimental Epidemiology
1. DESCRIPTIVE EPIDEMIOLOGY It is the study which describes the pattern of occurrence of a disease or a condition relative to other characteristics of a population. The various steps involved in a descriptive study are- 1. Defining the population which has to be studied. 2. Defining the disease under study. 3. Describing the disease in terms of time, place and person. 4. Measurement of the disease. 5. Comparing with known indices. 6. Formulating an etiological hypothesis.
VARIOUS STEPS IN DESCRIPITVE EPIDEMIOLOGY: 1.Defining the population : the defined population can be the whole population in a geographic area or more often representative sample taken from it. - Not only the total number, but also its composition in terms of age, sex, occupation, cultural characters etc. - the community chosen should be stable, without migration into or out of the area.
2. Defining the disease under study The disease is defined in such away that helps in identifying and measuring the disease in the defined way with a degree of accuracy. “Operational Definition” : by which the disease or condition can be identified and measured in the defined population with a degree of accuracy. If definition is not valid, it can be powerful source of error in presentation and comparability of measurements. Case definition should be must be adhered to throughout the study.
3. Describing the disease : The occurrence and distribution of disease is described by time, place, and person and identifying those characteristics associated with presence or absence of disease in individuals. Characteristics examined : Time Place Person Year Climate zone Age Birth order Season Country, region Sex Family Month Urban, rural Marital status Height Week Local community Occupation Weight Day Towns Social status Blood pressure Hour of onset Cities education habits duration institutions
4. Measurement of Disease : • “Disease load” • The measurement of disease is done in terms of mortality and morbidity indicators. • The morbidity can be expressed in terms of two units- “incidence” and “prevalence”. • Descriptive Epidemiology either uses a cross- sectional or longitudinal study.
4. A. CROSS-SECTIONAL STUDIES : -are also called as “prevalence studies” as they measures the prevalence of disease. - examination at a point in time, so that results can be projected to the whole population. -More useful for chronic than short lived diseases. B. LONGITUDINAL STUDIES : Observations are repeated in the same population over a long period of time. They are extremely useful : 1. For studying the natural history of the disease and its outcome. 2. For identifying the risk factors associated with the disease and 3. For calculating the incidence rate of the disease.
5. COMPARING WITH KNOWN INDICES: -The essence of epidemiology is make comparisons and ask questions. -to arrive at clues to disease etiology. - also helps in defining the groups who are at increased risk for certain diseases.
6. FORMULATION OF HYPOTHESIS : -A hypothesis is a supposition, arrived from observation and reflection. -Using the techniques of descriptive epidemiology, it is possible to formulate hypothesis relating to disease etiology. -It can be accepted or rejected using the techniques of analytical epidemiology.
An epidemiological hypothesis should specify :  the population – characteristics of persons to whom hypothesis applies.  specific cause being considered.  expected outcome – the disease.  the dose - response relationship – the amount needed to lead to stated incidence of the effect.  the time – response relationship – the time period that will elapse between exposure to the cause and observation of the effect. Eg : cigarette smoking causes cancer – is incomplete hypothesis. Correct : The smoking of 30-40 cigarettes per day causes lung cancer in 10% of smokers after 20 years of exposure.
USES OF DESCRIPTIVE EPIDEMIOLOGY 1.Useful in providing data with regard to the types of disease problems and their magnitude in community. (mortality and morbidity rates and ratios) 2.Provides information on the etiology of the disease and helps in formulating an etiological hypothesis. 3.Provides background data required for the planning, organizing, and evaluating preventive and curative services. 4.Leads the path for further research with regard to a particular disease problem.
When the disease is multifactorial, numerous factors become implicated in the ‘web of causation’ and notion of ‘cause’ becomes confused. The more associations, the more investigations to disentangle the web of causation.
Association and relationship are interchangeable. Association : defined as the concurrence of 2 variables more often than would be expected by chance. Correlation : Indicates the degree of association between 2 characteristics. Range of correlation coefficient : -1.0 to +1.0. 1.0 : means that 2 variables exhibit a perfect linear relationship.
TYPES OF ASSOCIATION 1.Spurious Association 2. Indirect Association 3. Direct (casual) Association • one-to-one • Multifactorial
SPURIOUS ASSOCIATION Sometimes an observed association between a disease and a suspected factor may not be real. INDIRECT ASSOCIATION Associations which at first appeared to be casual have been found on further study to be due to indirect association. i.e. association is because of presence of another factor (aka ‘confounding factor’) Eg: This amplifies the fact that statistical association does not necessarily mean causation.
One-to-one casual relationship Two variables are stated to be casually related (AB) if a change in A is followed by a change in B. This model suggests that when factor A is present, disease B must result. Conversely, when disease is present, the factor must also be present. Eg: Measles. (Kosh postulates)
Multifactorial Causation Causal relationship is different in considering a non communicable disease or condition where aetiology is multifactorial. Each factor can produce the disease independently. Eg: Lung cancer (smoking, air pollution, exposure to aesbestos) – discover a common biochemical event at cellular level. So in this case molecular or cellular factor will then be considered as a causal factor. In second model the causal factors act cumulatively to produce disease. (synergistic effect. )
The causal significance of an association is a matter of judgement which goes beyond any statement of statistical probability. No one by itself is self-sufficient for or sine qua- non for drawing causal inferences from statistical associations, but each adds to the quantum of evidence, and put all together contribute to a probability of the association being casual. CONCLUSION