Ecological study
Cross-sectional study
Retrospective cohort study
Cross-sectional study
Prospective cohort study
Period prevalence
Maintaining high rates of follow up can be difficult
The disease should be severe, relatively common and perceived as a public health problem
Relatively quick and cheap to conduct
Can investigate a wide range of possible risk factors
Can be used to effectively identify and study cases of rare outcomes
Can employ expensive or time-consuming tests
Occurs clearly in excess of the expected numbers
They are quick, cheap and easy to do with existing data
They are useful for generating hypotheses for later testing
The gender of the study participants
The household annual income of the study participants
Odds ratio
True
The results should be treated with caution as it could be due to chance variability in the data. This is because it has an odds ratio of 0.86 with a 95% CI of 0.61-1.26. This means that the true odds ratio of the target population lies between 0.61-1.26. Therefore, the true population odds ratio has a possibility of being 1.0. Odd ratio is one if the measure of association between the cases and the control in case control study or exposure and the outcome in the cohort study. Odds ratio also measures the strength of association between the exposure and the outcome. It is calculated by taking the odds of the disease in the exposed group divided by the odds of the disease in the unexposed group.
Odds ratio, OR =
Interpretation: An odds ratio of 1 is interpreted as there being no increased or decreased likelihood of a factor (living in rural area) affecting an outcome (daily smoking). Living in rural is not associated with more daily smoking. An odds ratio of more than 1 means there is an increased likelihood of the outcome occurring due to the factor in question while an odds ratio of less than 1 means there is a decreased likelihood of the outcome occurring due to the factor in question. It should be noted that Odds ratio does not totally establish that the exposure is the contributing factor to the outcome. It could be that the association is due to a third factor that was not checked in the study. These factors that are related to both the exposure and outcome are known as confounding factors.
Airborne diseases like influenza flu. This is because the games will bring together a lot of people together within relatively enclosed spaces. This is a conducive environment for the transmission of airborne diseases. Some flu strains are also known to be very contagious. Some of the flu can also be fatal. This means they pose a big threat and are therefore a major public health concern.
Sexually transmitted infections. The common wealth games gives an opportunity for a large number of people to meet at a single place. This opportunity would increase the level of sexual activity and incidences of sexually transmitted infections. The games might also be an avenue of spread of new, more drug resistant strain of sexually transmitted infections.
The health surveillance system was not designed in the best way. They should have collected more data. A better way was to start the data collection before the arrival of the teams. This would have enabled collection of data on determinants of health that would have influenced the health of the teams and were in place before the teams arrived. These factors include the level of sanitation, water supply and food sanitation and safety, accommodation and any pre-existing diseases among others.
Data collection should also continue past the final day. This is because some diseases have a longer incubation period. This means that the clinical symptoms of the disease will manifest several hours or days after the exposure. Such disease includes most of the sexually transmitted infections. These diseases might be missed if data collection is stopped on the final day of the games.
Loss to follow up
The analysis compared people who were randomised to the aspirin group with those who were not randomised to take aspirin, regardless of whether or not they actually took the aspirin.
Controls who are also hospital patients may be more representative of hospitalised cases than controls selected from general population
Odds Ratio. This is the odds of the disease in the exposed divided by the odds of the disease in the unexposed.
OR= odds exposed/odds unexposed
= 1.419
= 1.4
The result means that heavy alcohol drinkers have 1.4 times more likelihood of developing pancreatic cancer compared to the non-heavy alcohol drinkers. An odds ratio of 1 signifies that the exposure in this case heavy drinking has no association with the outcome. An odds ratio of more than 1 signifies that the exposure increases the risk of having the outcome by a fold represented by the value of the odds ratio. An odds ratio of less than 1 signifies that the exposure reduces the risk of having the outcome in question. It means that the exposure is instead protective against the outcome in question. However, the odds ratio does not totally establish the association between the exposure and the outcome as there might be other confounding factors.
The exposed and non-exposed groups under study be as similar as possible with regard to possible confounding factors
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