MindMap Gallery Mind map of commonly used epidemiological research methods
This is a mind map about commonly used epidemiological research methods, including observation methods, experimental methods, mathematical methods, etc. Hope this helps!
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This is a mind map about bacteria, and its main contents include: overview, morphology, types, structure, reproduction, distribution, application, and expansion. The summary is comprehensive and meticulous, suitable as review materials.
This is a mind map about plant asexual reproduction, and its main contents include: concept, spore reproduction, vegetative reproduction, tissue culture, and buds. The summary is comprehensive and meticulous, suitable as review materials.
This is a mind map about the reproductive development of animals, and its main contents include: insects, frogs, birds, sexual reproduction, and asexual reproduction. The summary is comprehensive and meticulous, suitable as review materials.
Commonly used epidemiological research methods
Observation
The difference between descriptive epidemiology and analytical epidemiology: whether to establish controls
describe epidemiology
Concept: It is an observational study that groups the data obtained from special surveys or routine records according to different regions, different times and different population characteristics to show the distribution characteristics of diseases or health conditions in the population.
Three distributions: time distribution, regional distribution, and crowd distribution
Category: Cross-sectional studies (main research methods); Ecological studies; Disease surveillance
generate hypotheses
Analyze epidemiology
test hypothesis
case control study
Concept: Select people with and without a specific disease as the case group and control group respectively, investigate the proportion of the two groups of people exposed to certain or certain suspected risk factors in the past, and determine whether the exposure factors are related to the disease under study. An observational research method of the degree of correlation. If the proportion of the case group with a history of exposure or the degree of exposure is significantly higher than that of the control group, and the difference is statistically significant, then this exposure can be considered to be associated with the disease. Research direction: effect → cause
Features: 1. It is an observation method without intervention. 2. Establish a control group 3. The direction of observation is derived from the effect. 4. It is difficult to prove the causal relationship. We can only judge whether and how much the exposure is related to the disease, but cannot make a final conclusion on the causal relationship.
use: 1. Explore suspected risk factors for disease 2. Establish and test etiological hypotheses 3. Provide clues for further research
type
Unmatched group case-control study
exploratory
A certain number of research subjects are selected from the case and control populations specified in the design. Generally, the number of controls should be equal to or more than the number of cases. There are no other restrictions or regulations.
matched case-control study
Testability
Matching: That is, the control is required to be consistent with the case in certain factors or characteristics That is to say, cases and controls are required to be balanced and comparable in certain factors or characteristics.
type: 1. Frequency matching: group matching or frequency matching, the proportion of factors required to be matched must be consistent between the two groups 2. Individual matching: Matching on an individual basis
Selection of research subjects
Case selection
The basic principle: 1. Representativeness: The selected cases should be sufficient to represent the overall number of cases, and the controls should be sufficient to represent the overall population or source population where the cases occurred. 2. Comparability: There is no significant difference between the case group and the control group in terms of main characteristics such as age, gender (and socioeconomic status) 3. Criteria for confirming controls: Controls should be people who do not suffer from the disease under study and have been confirmed by the same diagnostic techniques as the cases.
Source of cases: Hospital case data, community population data
type New case: recent occurrence, accurate recall, first choice Current cases: recall is easily affected, but there are many Death cases: large error, rarely used
Choice of controls
form: 1. Non-matching control (unmatched) 2. Matching control (1) Frequency matching (2) Individual matching
type: Healthy people; non-research disease patients
source: Cases of other diseases diagnosed in the same or multiple medical institutions (hospital); crowd
statistical inference
Analysis of data from grouped case-control studies: OR=ad/bc
Ratio: The ratio of the probability of something happening to the probability of not happening Exposure ratio of case group = (a/(a c))/(c/(a c)) = a/c Exposure ratio of the control group=(b/(b d))/(d/(b d))=b/d Odds ratio (OR)=exposure ratio of case group/exposure ratio of control group=(a/c)/(b/d)=ad/bc
The meaning of OR value: How many times the disease risk of the exposed group is that of the unexposed group. ●OR>1: The presence of exposure factors increases the risk of disease, which is a positive association; ●OR<1: The presence of exposure factors reduces the risk of disease, which is a negative association; ●OR=1: No correlation.
Analysis of matched case-control study data: OR=c/b
Advantages and Disadvantages
advantage: 1. Suitable for common diseases and research on rare diseases 2. Save time, manpower, and material resources, easy to organize, and require fewer samples. 3. Multiple causes of a disease can be studied simultaneously. 4. Especially suitable for research on the causes of diseases with complex causes and long incubation periods and rare diseases. 5. Can initially evaluate the efficacy and side effects of treatment measures
shortcoming: 1. Not applicable to factors with very low exposure proportion in the study population. 2. It is difficult to determine the causal relationship between exposure factors and disease 3. Selecting research objects is prone to selection bias 4. Obtaining new information from the past is prone to recall bias. 5. The influence of confounding factors is difficult to control. 6. Incidence, mortality, etc. cannot be calculated, and relative risks cannot be directly analyzed.
array research
Concept: A research method that divides people into exposed groups and non-exposed groups according to whether they are exposed to the research factors. After a period of follow-up observation, the difference in morbidity or mortality between the two groups is compared to determine the relationship between the exposure factors and the disease. . Research direction: cause→effect
Classification: Fixed queue: In prospective observation, if the research subjects enter the queue at the same time (at a fixed time or within a short period), no new members join during the observation period, and almost no members withdraw until the observation is terminated, the queue remains unchanged during the observation period. Relatively fixed, this kind of queue is called a fixed queue. Dynamic queue: If the original queue members in the observation can continue to exit, new observation objects can join at any time, and the queue members are constantly changing, it is called a dynamic queue.
Features: 1. Belongs to the observation method 2. Establish a control group 3. From "cause" to "effect", the temporal sequence is from front to back. 4. Can confirm the causal link between exposure and outcome.
use: 1. Test the hypothesis of etiology 2. Describe the natural history of disease 3. Evaluate spontaneous preventive effects
type
Prospective cohort study: Study subjects are grouped according to their exposure status at the beginning of the study (current). At this time, the outcome of the study has not yet appeared, and it requires prospective observation for a period of time to obtain it. This design model is called an immediate or prospective cohort study.
Historical cohort study: Grouping of subjects based on historical data available to the researcher at the beginning of the study regarding the exposure of study subjects at a certain point in the past.
Bidirectional cohort study: also called a mixed cohort study, that is, after a historical cohort study, prospective observation is continued for a period of time. It is a design model that combines a prospective cohort study with a historical cohort study, so it has both The advantages of the above two categories make up for each other's shortcomings to a certain extent.
Selection of research subjects
Exposure group selection
Specially exposed groups; general population; organized groups
Selection of control group
1. Internal control: within a group of research subjects 2. External control: When occupational groups or specially exposed groups are used as the exposed group, a control group needs to be found outside the group. 3. Total population comparison: readily available morbidity or mortality statistics for the entire region 4. Multiple controls: Two or more control forms reduce the bias caused by using only one control and enhance the reliability of the results.
Statistical Inference: Calculation of Rates
1. Cumulative incidence rate: The research object is a fixed cohort, the population is relatively stable during the observation period, and the observation can be maintained for a long period of time. Cumulative incidence rate = number of cases (or deaths) during the observation period/number of people in the cohort at the beginning of the observation period 2. Incidence density: usually suitable for dynamic cohorts. The follow-up time of cohort studies is relatively long, and it is difficult to require research subjects to remain still. The length of observation time varied among study subjects. At this time, it is obviously inappropriate to use the total number of people at the beginning of the observation as the denominator to calculate the incidence rate. Incidence density = number of cases (or deaths) during the observation period/total number of person-hours during the observation period (Number of observation hours = Number of observations x Observation time)
Relative risk
Relative risk (RR): It is the ratio of morbidity or mortality in the exposed group to the morbidity or mortality in the unexposed group. RR=Ie/Io=(a/(a b))/(c/(c d))
The meaning of RR: 1. When RR=1, it means that the incidence probability of the exposed group is equal to that of the non-exposed group, and exposure has nothing to do with the disease; 2. When RR>1, it means that the incidence probability of the exposed group is greater than that of the non-exposed group, and exposure increases the risk of disease and may be a risk factor for the disease; 3. When RR<1, it means that the incidence probability of the exposed group is less than that of the non-exposed group. Exposure reduces the risk of disease and may be a protective factor for the disease.
Advantages and Disadvantages
advantage: 1. More suitable for common diseases 2. Deducing effects from causes with less bias 3. The incidence rates of the exposed group and the non-exposed group can be calculated, and the relative risk and specific risk between the two groups can be measured. 4. Multiple outcomes can be observed in one investigation. 5. Facilitate calculation of dose-response relationships
shortcoming: 1. Not applicable to rare diseases. 2. Observation is time-consuming, labor-intensive, and expensive. 3. The preparation work is relatively arduous, the scientific design requirements are high, and the implementation is difficult. 4. The workload of calculating exposed person-years is relatively heavy. 5. Only one factor or a group of factors can be studied at a time, so it is not suitable for diseases with multiple causes.
Differences and connections
Common points: All are analytical studies A control group is required
the difference:
Experimental Method
Test hypothesis
experimental epidemiology
Overview
Concept: Experimental epidemiological research is also called experimental epidemiology or epidemiological experiments. This method randomly divides research subjects from the same population into experimental groups and control groups. The experimental group is given experimental factors (the experimental group must have intervention measures), and the control group is not given the factors, but is given control measures or placebo, and then prospectively Follow up the outcomes of each group and compare the differences to determine the effect of experimental factors.
Basic Features: impose interventions prospective study There is parallel control random group
Quasi-experimental or quasi-experimental: When an experimental study lacks one or more of the three characteristics of prospective observation, parallel control, and random grouping, it is called a quasi-experiment or quasi-experiment.
Classification
Clinical Trials
Field Test
community trial
individual test
Differences and connections with cohort studies
Clinical Trials
randomized controlled clinical trial RCT
definition
Purpose: safety Curative effect
installment
Design Principles
establish comparative meaning
mathematical method
theoretical epidemiology