JAMES COOK UNIVERSITY
XXXXXXXXXXCOLLEGE OF PUBLIC HEALTH AND VETERINARY SCIENCE
XXXXXXXXXXSUBJECT: EPIDEMIOLOGY
XXXXXXXXXXNAME OF THE STUDENT: DHVANI PATEL
XXXXXXXXXXSTUDENT NO: JC483609
Question 1:
What is the research question?
In Reading 1, Bradshaw et al., (2009), the research question is; To determine the incidence of coronary heart disease (CHD) events in an u
an Aboriginal population.
In Reading 2, Stacey et al., (2011), the research question is; To determine whether snoring, sleep position, and other sleep practices in pregnant women are associated with risk of late stillbirth.
Question 2:
A. What is the exposure, and how is it measured?
Exposure refers to the explanatory variable. It is also known as the independent variable. In reading 1, the exposure is coronary heart disease (CHD). The exposure is measured using risk-factor assessment among the u
an Aboriginal people.
In Reading 2, the exposure is Risk of late stillbirth. The exposure is measured using a case-control study and benched against variables such as snoring, sleep position, and relevant sleep practices.
B. What is the outcome, and how is it measured?
Reading 1: The outcome was that the Aboriginal Australians living within the city had high incidences of the CHD events, as opposed to the Aboriginal people who were living in the remote or local areas of Northern Australia. The outcome was measured using the First CHD event (hospital admission or death). Variables considered in the measurement included; overweight/obesity, diabetes, hypertension, smoking, and waist circumference.
Reading 2: The outcome was that practices related to maternal sleep were risk factors for stillbirth. It was the first study to
ing out such outcomes, hence need to evaluate it further. The outcome was measured using maternal snoring, daytime sleepiness which was measured using the Epworth sleepiness scale, sleeping position, times for going to sleep and waking up, sleeping sides like left, Right, back, etc.
C. Measurement for bias.
Reading 1: The research used a cohort study, hence the possibility of non-differential measurement bias. The bias would occur if the stated exposures for both the controls and the cases were inco
ect. In this study, all other outcome variables under consideration (overweight/obesity, diabetes, hypertension, smoking) were co
ect and relevant to the outcome variables, with an exception of the waist circumference. The waist of the circumference was found not to with coronary heart disease, but the other variables were. The researchers eliminated such variable in making their conclusions, hence removing the bias of non-differential measurement. Presence of measurement bias would automatically lead to wrong research conclusion. Differential measurement bias could arise, considering the fact that information obtained differed between the groups. Aboriginal Australians in the city had differing information relating to CHD as opposed to those in rural Northern Australia. The authors addressed the e
or by considering the information that was similar to both parties and that differed. Measurement would result in false results, such as concluding that geographical location (u
an or rural) does not affect CHD.
Reading 2: the study was case-control, hence the likelihood of non-differential measurement bias. Under such a study, the bias occurs in the event the exposure status is not the same for the individuals with the disease and those without. In this Reading, the exposure variables were found to the same for the singleton late stillbirth and who had no congenital abnormality, and the control group composed of the single ongoing pregnancies and gestation. The researchers addressed or eliminated the bias by considering exposure variables that cut across all the groups under consideration. The fact that the information used was similar to all the groups, means that the study had not differential measurement bias. Presence of measurement bias would have resulted in wrong study conclusions.
Question 3:
A) Describe the study population (sample). How were participants recruited? [4 marks]
Reading 1: the study considered a total of 1,904 individuals, comprising of 906 Aboriginal people who had no CHD, and 998 who had undergone risk-factor assessment. The recruitment took place in the Perth metropolitan area. The population was mainly composed of the locals (Nyoongar people) and were recruited through health, education, family and community contact as well as public service & community institutions.
Reading 2: the population was composed of 155 women who had singleton late stillbirth and who had no congenital Abnormality. Control experiment comprised of a total of 310 women, who had single ongoing pregnancies and gestation. The recruitment was based on the individuals who booked to deliver in Auckland.
B) bias related to choice sample
Bias related to sample includes selecting the wrong representation of the population and selecting a small sample that cannot serve as sufficient population representation. To avoid or minimize bias relating to the choice sample, researchers in Reading 1 considered using large sample. Again, the sample selection was limited on the Aboriginal people, to avoid mixing races which would interfere with the representation. In reading 2, a large sample of 155 women and 310 control group was used. Besides, the women considered were those who delivered in Auckland. Time duration (July 2006 and June 2009) and birth conditions were specified, to ensure effective selection of the sample. Bias occu
ing in the choice of the sample may lead to wrong results, hence adversely affecting the research objectives.
Question 4:
A) What are the main findings of the study?
Reading 1: The Aboriginal Australians living within the city had high incidences of the CHD events when compared to the Aboriginal people who were living in the remote or local areas of Northern Australia.
Reading 2: practices related to maternal sleep such as; sleeping position, times for going to sleep and waking up, sleeping sides like left, Right, back, etc. were risk factors for stillbirth.
) Tables
Reading 1: table 3
The main findings were that Aboriginal individuals within u
an areas were at a higher risk of contracting the heart disease as opposed to those in rural areas, a conclusion that is supported statistically by the data presented in table 3. The relative risk for those in u
an areas getting the CHD is high, and confidence interval (CI) is also high (above 95%) in support of the same. These measures are crucial in determining how two different variables under consideration differ, and the degree of the difference. The chance variation will affect the results if it does not occur uniformly across the two variables under consideration.
Reading 2: Table 5
The research findings were that various sleeping practices had an effect on stillbirth. The sleeping practices under consideration include; sleeping position, times for going to sleep and waking up, sleeping sides like left, Right, back, and so forth. Looking at the table, the 95% confidence interval (CI) is quite high in support of the effects of the variables, while the p-value differences are small, suggesting a strong relationship between the factors been considered and the independent variable. The results are likely to change in the event a chance variation occurs. We do not expect to get similar results, as it will depend on which side is favored more by the changes. Practically, a change in statistical value leads to change in the final results, which might end up strengthening the results findings or weakening them.
Question 5:
A confounding variable serves as an additional independent variable, given that it has the potential of raising hidden effect in the research. In Reading one, the confounding variable would be the environment under consideration; u
an and rural. The confounding was dealt with in the study by selecting representatives from both areas. The results are likely to be affected by the confounding, considering that individuals in u
an areas have got higher chances of contracting the CHD as opposed to those in rural areas. No other confounding variables that the author has not identified.
Question 6:
In Reading 1, ethical issues to consider to include seeking the consent of the women being experimented, and keeping personal information of the subjects confidential. When dealing with human subjects, it is considered unethical to study them without explaining to them about the research, benefits, and possible side effects. People have intrinsic value which must be protected. Relating to confidentiality, the information should only be used for the stipulated research purpose and no sharing with third parties. The issues require consideration of consent and secrecy to be incorporated in the design of the study, by creating trust and positive relationship between the researchers and the subjects, as it was done in this case.
Question 7:
The findings presented in Reading 1 are generalizable. This is based on the fact that findings have got practical applications in the real world, and can also be found in other similar studies. A sample is considered significant if it exceeds 30. In other cases, it is subject to the research subjects under study. The significant population was considered in this study, totaling to 1904. Based on the nature of the study and research findings, it is evident that the results have got cross applicability, indicating that they can be applied in other populations, within the same settings.
Question 8:
The study results have indicated that Aboriginal individuals within u
an areas have got higher incidences to coronary heart disease (CHD) when compared to those in the rural areas, which seems to be true. Individuals in u
an areas are highly subjected to heart complications factors than those in rural areas. However, that does not mean that those in rural areas won't suffer CHD. Geographical areas cannot serve as a differentiating factor to contracting CHD, as confirmed by other studies in the same field. The relationship between the area considered in relation to heart disease can be termed as a causal relationship. High-risk factors in u
an areas lead to health diseases, and the reverse is also true. The evidence can further be supported by results of similar studies in the same area, and it's cross applicability across various populations.