Case Study: Epidemiology - Residential Greenness & Prostate Cancer

This case study delves into the epidemiology of prostate cancer, specifically examining the correlation between residential greenness and the risk of developing the disease. The analysis is based on a case-control study conducted in Montreal, Canada, where researchers investigated whether living in greener areas was associated with a lower incidence of prostate cancer. The study addresses potential confounding factors such as age, socio-demographic variables, lifestyle choices (alcohol consumption, dietary habits, smoking), and family history of prostate cancer. Strategies to mitigate these confounding factors, including restricting controls and adjusting for individual and area-level variables, are also evaluated. The assessment of outcomes for both cases and controls is scrutinized for reliability and validity, ensuring that selection bias is minimized. Furthermore, the study's internal validity is assessed by examining the follow-up procedures, inclusion criteria, and the meaningfulness of exposure periods, considering the latency period between exposure and disease manifestation. This assignment solution provides detailed answers to questions regarding confounding factors, strategies to address them, outcome assessment, exposure period, and internal validity.

Running head: EPIDEMIOLOGY
Epidemiology
Name of the Student
Name of the University
Author note

1EPIDEMIOLOGY
Answer to question 6
Yes confounding factors were identified. Residential greenness was correlated with the
prostrated cancer. It was considered to be independent of socio-demographic and lifestyle
factors. The confounders identified are- age, history of prostate cancer, family income,
educational attainment, alcohol consumption and dietary habits, history of diabetes, marital
status, smoking, and marital status. It is also supported with the study by Raina (2015) according
to which in case control studies a situation is created by the confounding variable where it is
difficult to separate the effect of two processes. It is also stated that it is not possible to separate
the effect of two casual factors. It is also indicated in presented study where the effect of alcohol
on prostate cancer cannot be separated.
Answer to question 7
Yes the strategies to deal with confounding factors were stated. In the second set of
analyses the author Demoury et al. (2017), restricted controls to men who were screened with
prostate cancer within the 2 years preceding the index date. It will help eliminate the
confounding due to screening history. Study was adjusted for large range of confounders as it
may have the probability to be associated with the prostate cancer as well as exposure. The
author also adjusted the multiple individual- and area-level variables. This is in alignment with
the study by De Alencar Ximenes et al. (2009) which considered the influence of social variables
independently on the risk of tuberculosis at both the individual level as well as the area levels. It
means the author’s strategies are justified.

2EPIDEMIOLOGY
Answer to question 8
Yes both the cases and controls were assessed for outcome. It is indicated by the results
where there was no disparity between the cases and controls in respect to the NDVI values and
the socio-demographic indicators. The assessment is reliable in this regard as it eliminates
selection bias. The relationship between the disease and greenness was assessed equally for both
groups as same data was collected. It ensures validity as the results were significant at 95%
confidence intervals and yielded the acceptable odd ratio. The score does not include 1.0. It
means the assessment was overall standard, reliable and valid as highlighted in Niven et al.
(2012).
Answer to question 9
Yes the exposure period is long enough to be meaningful. Demoury et al. (2017) ensured
a potential latency period. The association was measured as relationship between living in
greener areas and incidence of the prostate cancer. The duration considered here was presence
of diseases both in time of diagnosis or recruitment and also its presence a decade earlier. It
means the disease or outcome has long induction period. It means there was long term or latency
between the eventual casual manifestations of disease and the exposure. It makes the case control
study meaningful as per Hystad et al. (2012). It is justified as it makes the exposure data hard to
achieve and moreover disease like prostate cancer may occur a long time after exposure.
Internal validity
There are no concerns related to internal validity of the study as there are right follow up
of cases and controls and also both meet the same inclusion criteria. Also the results are
generalisable. The outcomes are assed for both cases and controls and matched appropriately.

3EPIDEMIOLOGY
The outcomes are meaningful as the groups were comparable other than absence of disease in
controls and exposure was for long term. The exposures are measured in reliable way, strategies
well dealt with the confounders necessary to ensure internal validity (Raina 2015).

4EPIDEMIOLOGY
References
De Alencar Ximenes, R.A., de Fátima Pessoa Militão de Albuquerque, M., Souza, W.V.,
Montarroyos, U.R., Diniz, G.T., Luna, C.F. and Rodrigues, L.C., 2009. Is it better to be rich in a
poor area or poor in a rich area? A multilevel analysis of a case–control study of social
determinants of tuberculosis. International journal of epidemiology, 38(5), pp.1285-1296.
Demoury, C., Thierry, B., Richard, H., Sigler, B., Kestens, Y. and Parent, M.E., 2017.
Residential greenness and risk of prostate cancer: A case-control study in Montreal,
Canada. Environment international, 98, pp.129-136.
Hystad, P., Demers, P.A., Johnson, K.C., Brook, J., van Donkelaar, A., Lamsal, L., Martin, R.
and Brauer, M., 2012. Spatiotemporal air pollution exposure assessment for a Canadian
population-based lung cancer case-control study. Environmental Health, 11(1), p.22.
Niven, D.J., Berthiaume, L.R., Fick, G.H. and Laupland, K.B., 2012. Matched case-control
studies: a review of reported statistical methodology. Clinical epidemiology, 4, p.99.
Raina, S.K., 2015. Confounding in case control studies. Indian J Med Res. 142(1): 93.