Case-control Study On The Intake Of Dietary Fat And The Development Of Skin Cancer

• The type of study portrayed by the above article is 

• This is a cohort study which entails following the certain group of persons of interest for a certain period of time to assess exposure outcomes on a longitudinal study.   

• Data used to obtain the first study participants entailed  

• The study utilized data from the Swedish Annual Level of Living Survey,  which details a national representative of the non-institutionalized population. This sample obtained included 7090 women and men between ages 35-74 surveyed between 1988 and 1989. 

• The authors excluded a total of 1984 participants from the study because   

• They rated their general health as poor hence this was for a reason to remove underlying conditions which might affect the assessment of coronary heart disease. As these factors could have a confounding effect on the focus of the study.   

• The crude overall incidence  for CHD  was   

• The crude incidence rate was 59 cases per 10,000 persons over the various levels of physical activity. 

• Comparison of relative risks and physical activity levels   

• The physical activity engagement of twice a week had RR of 0.72 at CI between 0.52-1.01 compared to low-income earners having RR of 1.20 at CI interval of 0.95-1.52 compared to those of other incomes at RR at 1.   

• The relative risks discussed above can be best explained through   

• Physical activity engagement of twice a week led to a reduced incidence rate of coronary disease exposure.
• The low-income earners were linked to increased risks of exposure towards getting coronary heart disease while other income category earners had no effect on the emergence of the disease. 

• Relative risks in this study are better described as    

• The relative risks in this task can be described as risk ratio, as it outlines the probability of developing coronary heart disease on exposure to physical activity compared to those not engaging in intense physical activity and at the same time level of income as a risk factor of developing coronary heart disease. 

• The major confounding factors which were not considered in this study which could have a significant factor on the study results include; 

• The major confounders which were not considered in this study include disease and social factors such as hypertension, smoking, obesity, and hypercholesterolemia.
• These factors have the opportunity to progress the development of coronary heart disease as they are major underlying factors and risks factors for CHD development. However the researchers omitted the participations who had poorly rated health state, the above factors could be within the recruited participants.
• These risk factors thus signify profound confounding factors which were not litigated in the study. Thus physical activity could not be extensively be assessed with regard to the development of physical; activity among the participants.   

• Why do you think the author could not adjust for these confounders?  Hint: think about the way this study was designed  

• The authors of this study could not confound the factors mentioned above due to the study framework in that it excluded the participants who rated their self-health as poor. This could mean that people who were obese, overweight, smoking and even having other factors such as diabetes were excluded from participating in the study.
• Further, as the study was prospective in nature, the participants could have developed these conditions as the study was progressing. As mentioned and outline during the study, these assessments were not undertaken hence could mean that the respondents could have been having underlying health issues which coupes up to be coronary heart disease being a final factor and cause of death.     

Comparison groups in the study

A case-control study on the intake of dietary fat and the development of skin cancer Comparison groups in the study involved

Cancer cases =500

Case-control subjects= 500 

Dietary intake cases

Low consumption intake = 150

High consumption intake = 80

Control

Low consumption intake = 130

High consumption intake cases 100  

1. Data summary table for disease state and fat intake 

	Having disease	Without the disease	Total
High fat intake	80	100	180
Moderate fat intake	270	270	540
Low fat intake	150	130	280
Total	500	500	1000

Comparison of relative risks of high intake of fat compared to low intake of fat and the Relative risks of medium to high fat intake in relation to the development of melanoma cancer  

= a/(a+b)/ c/(c+d) 

= a-80, b-100, c-150,d-130 

= (80/180)/(150/280) 

= 0.444/0.535 

= 0.833

This results obtained indicate that there are lowered risks of developing skin cancer upon intake of a high-fat diet, thus concluding that that skin cancer can be reduced through the intake of high-fat diet. 

RR of medium to high fat intake

= a/(a+b)/ c/(c+d) 

= a-270, b-270, c-80,d-100 

= (270/540)/(80/180) 

= 0.5/0.44

= 1.1336

 This result indicates the intake of medium o high fat consumption of food leading to increased incidence of the risk of melanoma, thus the rate of melanoma is increased with high intake of fat in the body.    

1. The attributable risk related to exposure of low fat intake on skin cancer development is  

	Cases	Controls	Totals
Exposed	150	130	280
Unexposed	350	370	720
Total	500	500	1000

AR = I_E-I_U 

= P(D/E)-P(D/U)

= a/(a+b)-c/(c+d)

= 150/280-350/720

= 0.53-0.48

AR% = 0.05×100 

= 5%

The result obtained indicates that there is a 5% attributable risk difference in the development of exposed and unexposed group of individuals in the study. 

1. Population attributable risk of low fat intake on melanoma can be calculated by  

PAR = (IT-IU)/IT

= Pe(RR-1)/Pe(RR-1)+1)

= 5(1.1336-1)/ 5(1.1336-1)+1

= 0.668/1.668

= 0.40

• The disease rate attribution in this study is found to be 0.4 which reflect a causal relationship, indicating that there is low exposure and development of the disease among low fat diet consumers 

1. The conclusions of PAR above the display that ;   

• The population attributable risks show that low intake of dietary fat is linked to the low occurrence of disease, which means that they have low disease rate. Thus 4% of the population experience incidence of melanoma cancer.   

In a small cohort study investigating the effect of a rare exposure ( E), the following results were found:   

Table 1                                                 Disease

	Yes	No
Yes	120	360
No	120	360

Exposure

• Association of exposure and the disease [2 points]
• Association between the exposure and the disease can be best calculated using relative risks assessment.

RR = a(a+b)/c(c+d)

= (120/480)/(120/380)

= 0.25/0.315

= 0.80

The results above show no association between the exposure and the occurrence of the disease.

• A stratified analysis by Age-groups  shows the following:

	Younger adults	Older adults
Disease	Disease
Exposure	Yes	No	Exposure	Yes	No
Yes	60	180	Yes	80	160
No	40	160	No	60	180

The relative risks of the exposure and disease development between younger adults and older adults shows that ;

RR = a(a+b)/c(c+d)

Younger adults

Relative Risk = (60/240)/(40/200)

= 0.25/0.2

= 1.25

Older adults

Relative Risk = (80/240)/(60/240)

= 0.33/0.25

= 1.32

c- The interpretation of the above results shows that; 

• There is a weak strength of association between exposure and disease among the two groups under study. This can imply that the causation of the disease might not be the exposure under study thus other factors could have a play in the development of the disease.

1. a) An example of a typical bias in a cohort study is ;

This bias occurs when the researchers beliefs and included tend to influent the way information is being processed. In qualitative research, measurement bias can occur when the tools being utilized have not been assessed in terms of their validity and reliability. Through avenues such as shared decision-making model, (Sica, 2006).

A case example in retrospective studies is when filling forms on eating habits, where the data tools rely on recall, which the participants may not recall past foods consumed.

1. b) A classical example of bias in a case-control study is 

This aspect relates to a process of participant’s recruitment and inclusion criteria in the study. Effective research approaches begin with recruiting study participants who meet the aims of the study, (Francis et al., 2010). A typical example is when participants are invited to an online survey, which excludes the users of the internet.

An effective way of enabling the confounding factor is to undertake a 

Stratification

• This is a process where the overall population varies in the population, which could lead to an advantage when sampling the subpopulation. Thus distributing the homogeneity of the population into subgroups and offering equal treatment of process is an effective way of handling the cofounder displayed in the case study.  

Effect of loss to participants in the above case study shows that 

• In this there is no effect on the study findings as studies have shown that the impact caused by participant loss can be minimal, thus can’t affect much in the case study provided. Further, the participant loss is natural and data analysis can be adjusted to suit the remainder of the participants to validate the results, (Krieger, 2012).

References 

Francis, J. J., Johnston, M., Robertson, C., Glidewell, L., Entwistle, V., Eccles, M. P., & Grimshaw, J. M. (2010). What is an adequate sample size? Operationalising data saturation for theory-based interview studies. Psychology and Health, 25(10), 1229-1245.

Krieger, N. (2012). Who and what is a “population”? Historical debates, current controversies, and implications for understanding “population health” and rectifying health inequities. The Milbank Quarterly, 90(4), 634-681.

Sica, G. T. (2006). Bias in research studies. Radiology, 238(3), 780-789.