Study Design, Physical Activity And CHD, Reserpine, BMI And BP Frequency: A Discussion

Question one

What study design does this study employ?

• The study uses a cohort study design.  A cohort study depicts a clinical research study in which individuals who currently have a particular condition or illness or get a given treatment are followed over time.  Normally, different study designs give information of varied quality (Mark, 2013).  This evidently implies that the choice of the study design by any given researcher influences the quality of the information generated in the particular study.  As such, it is indispensable for any researcher to be prudent when identifying the most appropriate study design to adequately address all the necessary study elements.  

Find the methodological aspects mentioned in the paper that convinced you that is the type of study design, please use dot points

• The data collection aspect.  In the research paper, the data involving the national random sample of 2,645 men and 2,551 women aged between 35 and 74 were gathered in the years 1988 and 1989 respectively, after which they were perpetually monitored concerning incident cases of CHD until December 31, 2000.  As such, the duration for data collection was continuous although it was done on the original sample size.
• The data analysis aspect.  As vividly evident in the research paper, the data collected in the study was analyzed after the completion of the follow-up on the initial random sample subjects.  This implies that the records from the responses to the interview and questionnaires questions and the follow-up observations on the study subjects were conclusively analyzed at the end of the study period on December 31, 2000.

What justification do the authors give for conducting this study, please use dot points

• To adequately address the gap of the absence of holistic inclusivity of study subjects from varied socioeconomic status in the sample in the previous researches.  They argue that in the previous research studies, there has been an overt lack of a wholesome inclusivity when selecting the study sample.  For instance, the authors argue that a majority of the previous researches on the association between physical inactivity and CHD have failed to include individuals with low socioeconomic status (SES).  As such, they are seeking to bridge this particular gap by including individuals from the low socioeconomic status as well as those from other socioeconomic statuses.
• The need to include both genders, that is, both men and women in the study to counter the lack of such inclusivity by the previous researchers.  According to them, such an inclusivity of the two genders would produce more reflective and reliable conclusions in the study.  For example, they point out the relative neglect of women in the studies of CHD epidemiology.  Evidently, including both men and women in their study is a chief reason for motivating them to conduct this particular study.

What was the proportion of those who (i) do not do any physical activity (ii) engaged in twice a week vigorous physical activity“? (You are not required to report 95% confidence intervals)

• The proportion of the individuals who do not perform any physical activity at all according to the results table is 9.0%, which represents a sample size of 463 out of the total sample size of 5191.
• Based on the results table in the research, the proportion of those who took part in twice a week vigorous physical activity was 10.9%, which reflects a sample size of 563 out of the overall sample size of 5191.

What is the crude incidence rate of CHD in inactive men and inactive women?

• In this case, the crude incidence rate describes the number of new coronary heart diseases in both the inactive men and women during a given period, expressed as the number such cases per 10,000 population at risk.  As such, the crude incident rate of CHD in physically inactive men is 111.
• For the case of women, the crude incident rate is 38.

What is the crude relative risk of being non-active versus being “highly active“(`vigorous physical activity at least twice a week) in men and` women

• For men, it is 111:61
• For women, it is 38:14

How would you interpret the relative risk in the above section f?

• The relative risk in both the genders exhibits a similar trend.  That is, the crude risk is high for men and women who do not perform any active physical activity at all while, on the other hand, those who engage in vigorous physical activity twice or more than twice a week have a lower crude risk.  This means that the highly physically active a person is the higher the possibilities of not suffering from CHD conditions.  Similarly, the opposite is vividly true.  Based on this observation, it is therefore advisable for individuals to engage in physically active and if possible vigorous physical activities two or more times in a week.  This will lower the chances of them having such life-threatening CHD conditions.  This should be encouraged across the board, that is, in both men and women of all ages.    

Looking at the sex and age-adjusted RR in Table 3 (the RR is measured by the Hazard Ratio which is similar) (i) how would you describe the association between physical activity and CHD

• Men and women who were completely physically inactive have increased chances of suffering from CHD.  This is expressed in the HR=1 as shown in the table.  This implies that such people face a highly possible likelihood of contracting CHD conditions and this is attributed to the absence of physical activities in their lives.  This illustration should quite serve as a warning to those people who are reluctant or lazy about performing some active physical activities in their lives.  They should see it as an opportunity to avert such possible chances of getting CHD.  Evidently, they can achieve this by starting with simple regular physical exercises at their home or work places if possible.
• Women and men who engaged in occasional physical activities have relatively reduced risks of having CHD compared to those who did not perform any physical activity at all.  There HR=0.72.  This is slightly lower than the HR=1 of those who did not engage in any physical activity totally.  As such, at this level, the individuals in this category are at better placed regarding susceptibility to CHD compared to their counterparts in the above-mentioned group.
• The men and women who performed physical activities once to twice a week had quite lower possibility of getting CHD relative to their counterparts who did occasional physical activities.  This is exhibited in their HR=0.64.  Evidently, there is an overt reduction from the HR of 0.72 faced by those who do occasional physical exercises to an HR of 0.64 in those who engaged in physical activities once or twice in every week.
• `There was a significantly lower risk of developing` CHD for men and women who performed vigorous physical activities at least twice each week.  This is indicated by their HD=0.46 in the illustration table in the research study.  As such, this cadre of people have a reduced risk of 0.54 relative to the risk faced by those who did not perform any physical activity at all of contracting CHD.  As a result, this statistic should serve as a key motivator to those men and women who would wish or desire to have higher chances of averting CHD conditions in their lives regardless of their age.  However, this should be a great motivator to the young people who are normally energetic and vibrant.  This will enable them to live a healthy life devoid of CHD conditions throughout their lives.

The authors removed from the analysis any person who self-rated their health as “bad” or “anywhere between good and bad why?  (one sentence

• The authors wanted only those respondents who had good self-rated health which provided the possibility of such individuals having good health.

What possible bias could have changed the estimate for the association between physical activity and CHD` – mention at least one, and explain why

• The high non-response rate of 21.8% in the study.  This nonresponse rate was quite high in such a study.  As such, this could lead to possible bias in the association results.  This may imply that people with CHD conditions were either particularly reluctant or anxious in taking part in that particular study.  This nonresponse rate could imply that those who responded to the comprehensive interview questions were possibly those who are open about their health status.  On the other hand, the individuals who did not give their responses may be those who felt that concealing their health status is the best thing to do.  As such, there exist the possibility of bias in the conclusively analyzed results of the study on the relationship between physical activity and CHD.
• The reliance on patients treated at the hospitals.  Patients attended to at the hospitals for CHD conditions are not representative of the entire patients with this condition.  This is because the patients with mild CHD conditions or extremely severe ones (so severe that there exist immense chances of them dying before arriving at the hospital) will normally tend to be excluded from the research or study.  It is not certainly possible to establish whether an individual is mildly suffering from CHD particularly when interviewing them.  As a result, such a crucial group of people perhaps end up being not considered in the research.  Essentially, both those with mild CHD conditions and those suffering from extreme CHD conditions can remarkably account for the reliability, accuracy, and validity of the study results.  This is because including such people will holistically give a representative sample that reflects the entire target population or rather the population under study.

Do you think this research adequately addressed `confounders`? `Justify your answers

Yes, it has quite satisfactorily addressed the necessary confounders.  It has evidently employed age as a confounder in a complete manner.  The age distribution in the study is different in the exposure categories being compared.  It has shown its association with exposure and outcome.  Additionally, BMI has been addressed.  It impacts both physical activity and CHD conditions.

1. What is the study design, justify?

• It is a cross-sectional study or a survey.  This is because the entire population in the study is defined at a single point in time.  Additionally, the exposure and outcomes are established simultaneously.  This means that they are determined at the same time.  In this case, the exposure is the Reserpine drug which is administered to the women while the outcomes are the breast cancer prevalence cases.  As such, the association between the use of this drug and the prevalence of breast cancer in the target or study population of 2 million women is determined at the same time, that is, simultaneously.

1. “Build the 2X2 table consist of data above. 

	High SES		Low SES
	Breast Cancer	No breast cancer	Totals		Breast Cancer	No breast cancer	Totals
Use Reserpine.	40,000	499,900	539,900		10,000	499,900	509,900
Non-users of Reserpine	460,000	100	460,100		490,000	100	490,100
Totals	500,000	500,000	1,000,000		500,000	500,000	1,000,000

`If `Reserpine `is causally related to breast`, `how `many cases of `breast-cancer` could be avoided in the `high SES` and `Low SES`, had `Reserpine` been banned` from being in the market?` (`in other words, what is the PAF?`)“ [3 points]“

  Population attributable risk fraction (PAF) describes the proportion of all the cases comprised in the entire study population (both the unexposed and the exposed) which can be attributed to the exposure.  PAR is normally computed by subtracting the incidence within the unexposed from the incidence in the sum population which includes both the exposed and the unexposed.  It is employed in measuring the likely effect of control measures within a given population and hence indispensable in public health decisions.  Its formula is shown below:

PAF= Population Attributable Risk (PAR) ÷ Overall population rate

That is, PAF=PAR/r

For the high SES, the PAF calculation is shown below:

Incidence rate =3       Non-incidence rate=1                              

Incidence of the unexposed is 3/4×460,000= 345,000

Incidence in the total population is 3/4×1,000,000= 750,000

Hence, PAR= 750,000-345,000= 405,000

Percentage of PAR= 405,000/705,000×100= 57%, cases to be possibly avoided are 57/100×1000000= 570,000 cases

For the low SES, the PAF calculation is illustrated below:

Incidence of the unexposed is 3/4×490,000= 367,500

Incidence in the total population is 3/4×1,000,000= 750,000

Hence, PAR= 750,000-367,500= 382500

Percentage of PAR= 382,500/750,000×100= 51%, cases to be possibly averted are 51/100×1000000= 510,000 cases

1. `Compute the crude measure of association between the drug and blood pressure [2 points]`

• The crude ratio is given as follows:

Question two

Crude ratio; (70/100) ÷ (40/100) = 0.7/0.4 = 1.75

1. “Calculate the stratum-specific association between the drug and blood pressure [2 points]”

• The stratum-specific ratios are illustrated below:

Among those whose BMI>=25, the risk ratio is calculated as follows;

RR= (30/50) ÷ (20/50) = (0.6/0.4) = 1.5 

Among those individuals whose BMI <25, the risk ratio is determined as shown in the below illustration:

RR= (40/50) ÷ (20/50) = 0.8/0.4 = 2.0

Interpret your findings

From the above calculations, the crude analysis proposed an association between drug use and lowered BP frequency.  This implies that there exists an overt relationship between the consumption of the new drug and the recorded blood pressure levels among individuals with different BMI.  Nevertheless, if this is stratified based on BMI, one can see a robust association with drug use in subjects with a BMI<25 compared to subjects with a BMI>=25.  Possibly the drug was more effective in individuals whose BMI is less than 25 than in their counterparts. 

Could this difference induce a bias?“ `Explain your answer`. “What would be a practical way to avoid such differences in case-control studies?

Yes, the difference can bring about quite a noticeable bias.  

The most likely type of bias is selection bias.  According to (Mark, 2013), selection bias is more likely to happen in case-control studies.  Usually, this type of study takes place when participation in the study is differential based on the disease status.  For instance, the people who participated as controls were half less when compared to those who participated as cases in reporting similar disorder particularly breathing. As a result, this may lead to bias or error in estimating the relationship between the type 2 diabetes conditions and sleeping disorders.      

   This is evidenced in the non-comparability exhibited between the cases and the controls.  First, the sole aim of case-control studies is to select study controls that are reflective of the population that from which the cases were produced.   As such, the percentage discrepancy between the men in the cases and those in control is bound to induce a bias.  This is because the less number of controls relative to the number of cases is likely to provide a poor estimate of the exposure rate in the study population.

   A possible efficacious way to avert such discrepancies in a case-control study is by ensuring that the number of controls matches the number of cases (Richard, 2005).  This can be achieved by ensuring that when you select one control, you also select one case.

Which of the following terms is associated with selection bias?

  The response rate is one of the terms closely related to selection bias.

  This is because, for instance, the selected study subjects in research about the prevalence of alcohol use among college students may show different response rates to the questionnaire or interview questions.

Which of the following term is associated with measurement bias?

    Validity is related to measurement bias.

     The measurement error or bias normally impacts the validity of the measured exposure or disease for instance.

What biases would you suspect in a survey of the prevalence of drug use among `young “people using a representative sample of students attending high school justify“ (“not enough to name the biases

  The most likely biases are;

• Students attending high school are not representative of the young population outside the institution.  This means that the sample of high school students selected does not reflect the entire population of young people who are not high school students.
• There may be a high nonresponse rate among the students in the selected sample.  

References

Mark, W. (2013). Epidemiology: Studt Design and Data Analysis. CRC Press.

Richard, R. (2005). `Studying a Study and Testing a Test: How to Read the Medical Evidence`. Lippincott Williams & Wilkins.