The study is to quantify the cardiovascular diseases, the assessment of the risk in the Australian population and the treatment associated with it like the lipid lowering therapy (2) The Heart Foundation of Australia analyses the prevalence of cardiovascular diseases. The Australian Bureau of Statistics and the Australian Health Survey in 2014 showed that it is the biggest reason of mortality with a risk greater than 26% (15) According to the Heart Foundation, the cardiovascular diseases contribute to 43,603 deaths, killing a person in every 12 minutes and every one in four suffer from CVD in rural and regional areas when compared to metropolitan cities where one in five suffer from the disease (16)
The cross-sectional study design was adopted to study the 9564 people aged 18 years and participated in 2011-2012 at the Australian National Health Measures (ANHM) design survey (13) This design was adopted to study the extent of the CVD and the associated risk exposures in Australia. It is suitable for studying the prevalence of the behavior of a disease in a population (12) It is quick, easy to understand, cheap to maintain and based on questionnaire (4) The study design was beneficial in quantifying the CVD, the associated risks in different age groups and the assessment of it (10) The underlying treatment was also studied like the use of lipid lowering therapy (9) In general population, the study was aimed at making the people aware about the CVD, the associated risk and different strategies to reduce it by performing awareness programs, planning and implementation of the strategies. In the concerned population, the individual risk can be studied, the factors contributing to that risk and the management plan of the reduction of the risk. The disadvantage of the study is that it failed to identify the studies done previously for absolute CVD detection for population, the representative information, the integration of primary and the secondary CVD and the treatment of high blood pressure and lipid lowering therapy. The important disadvantage was the NHMS tool with limitations that lacked data of Familial Hypercholesterolemia (FH) and proteinuria in feeding NVDPA algorithm. The above limitation led to inclusion of participants that are older in age and already suffering from one or more weakness. The authors managed this disadvantage by the under-inclusion of absolute risk of CVD that had been underestimated in people above 74 years.
The general population of interest is the study of CVD, the risk associated with it; implementation of CVD assessment on a large scale based on the absolute risk is most cost effective. The study sample was 9564 participants from the Australian Bureau of Statistics (ABS) Australian Health Survey (2) of group of 18 years and the data provided by the National Health Measures (NHM) survey between the years March 2011 till September 2012 (14) The 30,329 eligible participants in NHM survey and 46.5% of it aged 45-74 years. This sample population is considered because they were aimed at quantifying the absolute cardiovascular disease risk in the adult Australian population aged 45-74 years and treatment of blood pressure with lipid lowering medications as the risk factors are most in this aged population with CVD. This age group is important as they have an absolute risk of a future CVD. The findings concerned the population in a generalized way that is undergoing the treatment for CVD and the related risk. The risk could be assessed before the commencement of the treatment and moreover the category changed when the ongoing treatment shifted with the consumption of the blood pressure and the lipid lowering medications (3) The findings could not be generalized to the groups of people who are at low risk for CVD as compared to the group of people who are at high risk and undergoing treatment with lipid lowering therapy and reduction of blood pressure.
The concern for the study is appropriate. The cardiovascular diseases are reaching an alarming stage due to the sedentary lifestyle and due to obesity (5) The individual risk management, the factors contributing to the risk and the assessment of the concerned risk were also important that potentially benefitted to balance the harms and the benefits and cost-effectiveness of the associated treatment (1)
American Diabetes Association. 8. Cardiovascular disease and risk management. Diabetes care. 2015 Jan 1;38(Supplement 1):S49-57.
According to the above mentioned paper, cardiovascular disease is the major concern in people and the risk management in individuals. The blood pressure control with routine check-ups and self monitoring is important as it is an associated risk factor with CVD. The lipid management is also important as quoted by this article and it correlates with our concerned paper regarding the age group of 40 years and above. The lipid profile screening is crucial at the time of the first diagnosis and the initial evaluation for CVD.
Jansen J, Bonner C, McKinn S, Irwig L, Glasziou P, Doust J, Teixeira-Pinto A, Hayen A, Turner R, McCaffery K. General practitioners’ use of absolute risk versus individual risk factors in cardiovascular disease prevention: an experimental study. BMJ open. 2014 May 1;4(5):e004812.
The above paper stated the findings that justify the concerned paper. They found out that the management of risk in individuals is important for the absolute risk evaluation in CVD. The results could be concluded in a way in which the lipid lowering or blood pressure medication is provided for patients at low risk of CVD. It also stated that the management of individual risk is a more consistent approach for proper risk evaluation.
Internal validity is a term used to evaluate the authenticity of the research. It refers to the well execution of the experiment and avoiding the independent variables like the cause that is acting simultaneously (17) The internal validity helps you to choose only one explanation over the other with high confidence limits as it avoids multiple possibilities (19) It approximates the truth about the cause-effect relationships. When we extend our findings to a generalized population at large is the external validity. It validates the result obtained from a small group whether in laboratory or to a small sample group and extended to entire population (6) The poor external validity does not justify the results along with the sampling and the selection criteria.
The bias is defined as a tendency that occurs to systemic error during the introduction of sampling or selecting out just one outcome over the other ones. The scientists portray the outcome by performing research that influences the results called experimental bias. Bias is a qualitative research that makes the result more dependent (7) The error in research can be explained in a way that it is the difference between the average values obtained in a study and the true average value of the targeted population. The error explains the extent to which the study is lagging the mark by eliminating the flaws made in research study (8) The basic difference between the error and the bias in research is that error constitutes the flaws in a study result but the bias is only systematic in nature. When the data is collected in a way that is different from true value of the concerned population it is bias. The bias is a result of mistakes whereas the sampling error is selection of appropriate sample size and method (11)
The potential sources of bias that arises in a cross-sectional study are selection bias and the informational bias. In selection bias, it is necessary to select a sample called the study population but this selection is done at random and not representative resulting in the serious selection bias. The investigator and the study subjects are considered in the selection bias. The information on the risks and the outcomes along with the other factors was considered. The possible related biases are obtained in performing the research. It is an information bias. The exposure and the outcome are the main considerations in information bias.
A confounding variable is a pure prevalent of survey. It is also a potential source of bias. The dependent and the independent variable are considered in the experimental design. It is a secondary and a changing condition that hypothesize the experimenter’s inference of cause and the effect relationship. To maintain the integrity of the findings, the researchers control the confounding variables. The researcher needs to consider the potential conditions and the invalidation of the results. It is important to control the confounding variables so that the experimental findings are not unreliable (18)
The notion of bias is related to the confounding variable. The positive and the negative confounding are relatable to the notion of bias. Concisely, confounding is a condition in which the effect between the exposure and the outcome is distorted in presence of another variable. When the observed association is away from the null called the biased condition in positive confounding and when the observed association is towards the null is the biased condition in negative confounding. The positive and the negative conditions intend to occur in confounding variables (20)
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