Epidemiology is the study of the distribution as well as various factors affecting health and disease states in a well defined population . It is also a branch of medicine which specifically deals with prevalence and incidence of diseases in large and specific populations.
In public health, epidemiology is crucial because it offers a shape and the basis upon which decisions and policies can be made based on evidence-based practice. This is possible through the identification of the risks for disease development, as well as the preventive measures to be used. Epidemiology is integral to public health because it focuses on preventing the disease and promoting healthy populations. In this regards, the public health professionals use epidemiology skills to perform studies on the occurrence of diseases and their distribution in a given area.
Observational research involves going out and making observations of the participants or research subjects and recording the notable features that are in line with the research question being answered.
Strengths:
It provides access to people and situations where experiments cannot be carried out.
There is a direct access to real life situation while experiments would require a lot of protocols.
It provides in-depth and strong understanding abilities.
It provides an easier way for explaining the meanings of the generated data and information.
Weaknesses:
It takes a lot of time dealing with a person at a time, while experiments need a representative sample.
It does not take into consideration the issue of ethical principles.
Possibility for conflicts between practitioners.
Mostly viewed as being too subjective than other methods.
4a. what is the prevalence of high blood pressure at the start of the period?
Prevalence = number of people with high blood pressure / number of people without high blood pressure
=20/100 *100
The prevalence of high blood pressure at the start period is 20 %
4b. what is the cumulative incidence of blood pressure ?
Cumulative incidence = new case / people at risk
= 10 / 100*100
= 10 %
4c. if you assume for your calculations that there were a total of 80 person years at risk in this
study, calculate the incidence rate of blood pressure in this study.?
Incidence rate = new case/ person years
= 10 / 80*100
12.5 %
Prevalence is the measurement of the existing disease cases such that it is expressed in form of a proportion. It is calculated by dividing the number of people who have a certain health case by the total population being studied and then multiplied by 100 %.
Incidence rate is the measure of the rate at which new disease cases have occurred within a certain period of time. Cumulative incidence is the proportion of a certain population which stands a risk of developing a certain disease outcome in a given period of time. As a result, the cumulative incidence provides a measurement of the risk that a certain population is exposed to.
However, the cumulative incidence it is just an estimate of the rate of diseases, focusing on just new cases in a given time. It would-be preferable to use the incidence rate method because the cumulative incidence needs to provide a time frame. For instance, to calculate the cumulative incidence of child hood obesity, we get the number of children with obesity and divided by the total number of children.
This refers to a top down arrangement of study designs based on evidence-based research, which enables a researcher to make choices of the best study design to use. In this case, a researcher searches for all the recent systematic reviews which have been conducted. If the required information is not available, then one moves downwards to the next level of evidence in a systematic way. This helps the researchers to get an answer to the question being investigated. This hierarchy ranks various types of studies based on their strength. This hierarchy appears like this one, from top to bottom: systematic reviews, critically appraised topics, critically appraised individual articles, randomized control trials, cohort studies, case controlled studies and background information. It is believed that the more upper the study design is, the better the precision of the methods to be used indicating that the effects of bias can be reduced and make the results to reliable.
Analytical studies aim at making a comparison between variables so that it can be possible to reach casual inferences regarding a given hypothesis involving associations. This then makes it possible to find out whether there is an association which exists among the variables, test the hypotheses, and determine the cause which exists between an exposure and the disease. Analytical studies are used to make comparison between two and more data groups.
Examples: randomized-controlled, case – control and cohort studies.
A prospective longitudinal study would be used for this research. This is because it will require following up the study participants for a period of time to determine whether drinking tea is protective for the development of cancer.
9b.
Strength:
Weakness:
10.
Background: Improvements in health are an important expected outcome of many housing infrastructure programs. The authors aimed to determine if improvement in the notoriously poor housing infrastructure in Australian Indigenous communities results in reduction in common childhood illness and to identify important mediating factors in this relationship.
Methods: The authors conducted a prospective cohort study of 418 children aged 7 years or younger in 10 Australian Indigenous communities, which benefited most substantially from government-funded housing programs over 2004-2005. Data on functional and hygienic state of houses, reports of common childhood illness and on socio-economic conditions were collected through inspection of household infrastructure and interviews with children’s carers and householders.
Results: After adjustment for a range of potential confounding variables, the analysis showed no consistent reduction in carers’ reporting of common childhood illnesses in association with improvements in household infrastructure, either for specific illnesses or for these illnesses in general. While there was strong association between improvement in household infrastructure and improvement of hygienic condition of the house, there were only marginal improvements in crowding.
Conclusions: High levels of household crowding and poor social, economic and environmental conditions in many Australian Indigenous communities appear to place major constraints on the potential for building programs to impact on the occurrence of common childhood illness. These findings reinforce the need for building programs to be supported by a range of social, behavioural and community-wide environmental interventions in order for the potential health gains of improved housing to be more fully realised.
10a)
This study is termed as prospective study because it made a follow-up on children over time, who were living in unimproved housing facilities. After the floor was repaired, the same study was done again as a follow-up. In this case, the research sought to determine whether there is any association between poor housing, congestion facilities in among Indigenous Australians and development of childhood illnesses.
10b)
The major outcome variable in this study is the rate of illnesses among children who live in poor household infrastructure.
10c)
Indigenous Australian communities
Children
Poor housing infrastructures
10d)
Although this research topic addressed vital health problems in public health, a number of limitations can be noted:
The researchers did not indicate the sample size; say the number of households included in the study. They have indicated the number of children sampled yet the program was aimed at improving housing facilities.
No data analysis is highlighted.
The inclusion and exclusion criteria are not addressed.
10e)
The conclusion is not supported by the evidence. The conclusion would rather read as”It is evident that poor housing infrastructures among the Australian Indigenous communities contribute to a large extent the increase in childhood illnesses. The adoption of housing infrastructure is likely to improve the health of children.
The following table represents the results of a cross sectional study conducted to investigate the relationship between having a vegetarian diet and having diabetes.
Please answer the following questions.
11a. Calculate the risk ratio for the association between diet and illness. Please show all of the calculations for this
Risk ratio= cumulative incidence in exposed / cumulative incidence in unexposed
Exposed = 35+5= 40/100 =0.4
Unexposed =26+ 74 = 100/100 = 1
RR= 0.4/10 = 0.4
= 0.4
11b.
Since the risk ratio is less than 1, it means that the vegetarians have a 0.4 times risk of developing diabetes as compared to those who are not vegetarians.
11c.
Odds ratio = (5 / 26) divided by (35/74)
= 0.19 / 0.47
= 0.40
11d.
The odds ratio results indicate that there is a lower odds 0.40) for diabetes developing in people who are vegetarians as opposed to non vegetarians. This means the non vegetarians have higher chances of developing diabetes than the vegetarians.
11e.
In this case, there is no difference between the risk ratio and odds ratio. Although both methods are valid, majority of the medical literature prefer using risk ratio because it is easier to understand in terms of association between exposure and disease. The risk ratio can be determined directly from a cohort study.
11f.
The ratios as they are might not be meaningful to a person who is outside public health profession. Therefore a researcher needs to use the simplest language in explaining the ratios.
A risk ratio of 0.2 for the association between eating berries and the gastrointestinal disease indicates that I am at 0.2 times likely to develop gastrointestinal disease when I eat berries in a restaurant as compared to those who do not eat. This clearly indicates that the risk of developing a gastrointestinal disease is likely, but at low levels when one eats berries.
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