Flashcards in FoPC III Deck (254)
what is epidemiology? state the 2 factors
looks at natural and type of illness in society using numerical science of epidemiology
looks at time and place and person affected
For example the rate of
occurrence of heart disease is very different between 18th Century English
women and 20th Century Finnish men.
what are the 3 main aims of epidemiology? Describe each
Description of the amount and distribution of disease in a population,
Explanation to elucidate the natural history and Aetiology of disease,
Disease control based on determining preventative measures, public health practice and therapeutic strategies
How might we compare Study Populations to determine epidemiologic clues?
1. Aetiological Clues
2. The Scope for prevention
3. Identifying high risk or priority groups in society.
We compare how often an event appears in one group compared to another.
E.g. we determined that there is a link between smoking and lung cancer but this does not mean that all smoking always causes lung cancer
The number of new cases of a disease in a given population at a specified period of time; indicates causation and Aetiology of disease
The total number of people with a specific illness in a population at a specified period of time; useful is assessing the workload for health services.
Define Relative Risk
The measure of the strength of an association between a suspected risk factor and the specified disease; it is calculated as incidence of exposed group over incidence of unexposed group
What are sources of epidemiological data?
1. Mortality data
2. Hospital activity statistics
3. Reproductive health data
4. Cancer statistics
5. Accident statistics
6. General practice morbidity
7. Health and household surveys
8. Social security statistics
9. Drug misuse databases
10. Expenditure data from the NHS
Name the different types of studies
1. Descriptive Studies
2. Analytical Studies
• Cross sectional
• Case Control Studies
• Cohort Studies
Define a descriptive study.
A study which attempts to describe the amount and distribution of a disease in a given population; it gives clues to possible risk factors and aetiologies of disease. They follow a time, place, person framework
When are descriptive studies useful?
-Identifying emerging public health problems through monitoring and surveillance of disease patterns
-Signaling the presence and effects worthy of further investigation
-Assessing the effectiveness of measures of prevention and control (such as screening programs)
-Assessing needs for health services and service planning
-Generating hypotheses about disease aetiology
What are the pros and cons of descriptive studies?
Pros: Cheap, quick, give valuable initial overview of a problem
Cons: no evidence of disease cause, do not test hypotheses.
What is a cross sectional study?
A study in which observations are made at a single point in time. Conclusions are drawn about the relationship between disease and variables of interest in a defined population
What are the pros and cons of a cross sectional study
Pros: provides quick results
Cons: usually impossible to infer causation
What is a case control study
An analytical study in which two groups of people are compared – those who have the disease of interest (cases) and those who do not have the disease (controls). The two groups are compared based on exposure to specific Aetiological risk factors to help give clue of disease cause. The results are published as ‘relative risks’
What is a cohort study?
Baseline data on exposure are collected from a group of people who do not have the disease under study. The group is then followed through time until a sufficient number have developed the disease to allow analysis. The original group is separated into subgroups based on exposure and incidence. They allow of calculation of cumulative incidence, allowing for differences in follow up time.
What are trials?
Experiments used to test ideas about Aetiology or to evaluate interventions. The randomized control trial is the definitive method of assessing any new treatment in medicine
What is a randomized control trial?
Two groups at risk of developing a disease are assembled; there is a study (intervention) group and a control group. The relative risk between the two groups is calculated to determine whether the intervention altered the incidence or course of the disease in any way
What factors must you consider when interpreting trial results?
1. Standardization – removing or adjusting for variables when comparing populations
2. Standardized mortality ratio – a standardized death rate converted into a ration for easy comparison (over a ratio of 100. E.g. A SMR of 120 indicates there were 20% more deaths than expected in a study populations)
3. Quality of data – ensuring the data is trustworthy
4. Case definition – to determine whether the individual has the condition of interest or not; necessary in determining true incidence
5. Coding and Classification – ensuring all proper coding and classification has been accurately converted to ensure results are accurate
6. Ascertainment – ensuring all data is accurate and that equal effort has been put into acquiring all aspects of information
What is bias?
Any trend in the collection, analysis, interpretation, publication or review of data that can lead to conclusions that are systematically different from the truth. There are 4 types of bias: selection bias, information bias, follow up bias, systematic error
What is selection bias?
When the study sample is not truly representative of the whole population, leading to inaccurate conclusions. E.g. deliberately allocating people to a specific group in a randomized control trial
What is Information Bias?
Systematic errors in measuring exposure or disease. E.g. a researcher knowing who is case vs. who is control prior to beginning an experiment may inadvertently lead to skewed results.
What is follow up bias?
When one group is followed up more carefully than the other leading to more accurate results in the one group. E.g. failing to accurately follow up members of a cohort group study
What is Systematic error?
A form of measurement bias where there is a tendency for measurements to always fall on one side of the true value due to inadequacies of the measuring instrument (through mechanical or human error)
What is a confounding factor?
A factor independently associated with both the disease and with the exposure under investigation, so it distorts the relationship between the exposure and the disease; age, sex and social class are common confounding factors.
How can one deal with confounding factors when designing a study?
-Randomization in trials
-Restriction of eligibility criteria to only certain study subjects
-Matching subjects for likely confounding factors
-Stratification of results according to confounding factors
-Adjusting results to take account of suspected confounding factors
What are the criteria for Causality?
1. Strength of association (as measured by relative risk or odds ratio)
2. Consistency (Repeated observation of an association in different population under different circumstances)
3. Specificity (a single exposure leading to a single disease)
4. Temporality (the exposure comes before the disease)
5. Biological Gradient (Dose-response relationship; as exposure increases so does the risk of disease)
6. Biological Plausibility (the association agrees with what is known about the disease)
7. Coherence (the association does not conflict with what is known about the biology of disease)
8. Analogy (exposure-disease relationship)
9. Experiment (a suitably controlled experiment to prove the association is casual – uncommon in human populations)
NOTE: temporality is the only absolutely necessary criterion
What percentage of the population is expected to be over the age of 80 in 2050?
22%; the majority (80%) will live in low or middle income countries
Describe the population, fertility rate and life expectancy of people in Developed Countries.
The population has a steady INCREASE, Fertility rate is decreasing and total life expectancy is increasing
It is suggested that old people will be exceeding the young by 2050. Why might life expectancies be increasing?
-Health education programs including AIDS and malaria prevention
-Improvements in public health related to housing, clean water and nutrition
-Increased involvement in aid agencies and charities