Assessment of Causation in Epidemiologic Research

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23/09/19 Data Analysis Reference this

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Assessment of Causation in Epidemiologic Research

The causation model in epidemiology leads to many avenues of understanding where an avid research faces three key issues: how to differentiate causal from non-causal associations, whether inferences generated from causation stem from observed associations, and what is the degree of causation or association serving as enabler, or sufficient condition to disease outcomes (Hofler, 2005; Phillips & Goodman, 2004).

In this paper, the writer/researcher will look at the role of the Bradford Hill’s causal criteria, then explore the relationship between a dietary adoption of soy protein consumption to delineate the veracity of risk factors associated with breast cancer, and cardiovascular disease, in terms of exposure, observed association, and causation (Phillips & Goodman, 2004; Sacks et al., 2006; Wu et al., 2008).

The interesting frameworks presented in the literature suggest that for a disease to occur, a causative approach is important to be considered under the assumption that the Bradford Hill’s nine criteria can be seen as posts to challenge or justify causation, the writer/researcher asserts. There seems to be a guided approach of epistemology anchoring epidemiology that serves as a valid tool to address which rank order in the Bradford Hill’s criteria needs to be prioritized. It is plausible to understand causal assessments, and interpreting observed associations. However, this is a difficult task because observed associations do not easily join hand with causal associations. It is worthwhile to note that Parascandola & Weed’s (2001) parameters of causation: necessary and sufficient, or sufficient but not necessary correlate with the Bradford Hill’s strength of association, and factors influencing specificity (Hofler, 2005, pp.3-4).

Consistent with the causation debate, in which randomized control trials, and various epidemiologic studies tackle the strengths, unpredictability of the associations, and the depths of causal inference (Trock, et al., 2006; Weed, 2000), it appears prudent to ascertain , and ask if the Bradford Hill’s criteria are the best contemporary interpretive versions, one can adhere to in epidemiological research? The rationale for the criteria implementation has not been, and is not a recipe for consensus within all the corners of epidemiological research. The interpretive platform used by researchers using Hill’s criteria calls for an evolution of the paradigm created at its onset, until now, the writer/researcher argues.

The Bradford Hill’s Causal Criteria

The Bradford Hill’s causal criteria totaled 9 stops guiding a research endeavor that aims to explore causation components in terms of its environmental continuum, and associative observations: strengths of association, consistency, specificity, temporality, biological gradient, plausibility, coherence, experiment, and analogy (Hofler, 2005,pp.1-9). To grasp the essence of causality, it is important to look at the role of causal explanations under the lens of inquiries that address observations, not only in terms of strengths, but in terms of also counterfactual effects (p.2).A counterfactual effect is defined as a definite set of time for disease occurrence, based on exposure levels, and the causal effect. A causal effect is related to a necessary condition for an event or disease to occur, which is not sufficient. The fact that a counterfactual effect leads to a counterfactual condition, which is independent of an outcome, suggests that there is a degree of subjectivity one has to deal with when estimating a population with incidence and prevalence rates of a disease.

In attempting to summarize the 9 stops, the writer/researcher posits that considerations for associations and exposure to diseases require observation with specific outcomes in a population, at a specific time, where exposure depends on levels and outcomes. The limits the outcome calls for a plausible or credible observations based of science, medicine, knowledge, evidence. Whether the evidence yields to causal effects that are reduced by similar truths, the salient question that will continue to persist is when do we assess observations as a component to a counterfactual standpoint?

Soy Consumption and Breast Cancer

A panoply of studies embracing the role of soy protein/isoflavone composites, or soybeans as catalysts in reducing the risk of breast cancer in pre and post- menopausal women suggests that isoflavones through dietary intake play a role of competitors of selective estrogen, thus exerting an anti-carcinogenic influence on the breast (Messina & Loprinski, 2001; Sacks et al., 2006; Trock et al., 2006; Wu et al., 2008). The salient arguments in terms of the weak effects of estrogen on breast and endometrial cancer in Asian women who have soy-based foods in their diet (genesitin), various meta-analysis epidemiologic studies showing reduction of risk estimates due to soy exposure/intake, and breast cancer progression, showed that:

1)                 The line of demarcation for soy and breast cancer marker appears to be drawn from quantity of soy intake affecting hormonal mechanism. Nonetheless, the studies are not all conclusive.

2)                 The inhibitory effects of soy/isoflavones, and associations vary from cancers survivors, and Asian women who have been diagnosed with breast cancer.

3)                 Premenopausal breast cancer risk data are inconsistent, and some studies failed to show association.

4)                 The availability of soy in Asian women diet compared with Western women shows inconclusive associations in terms of type of soy ingested.

Wu et al.(2008) best captured the dichotomous situation by asking what is the relationship between soy and breast cancer, and what is the intake level that creates a “ dose- response relationship”(p.8)?.These questions, stemming from the epidemiologic studies are aligned with the causative framework in which the Bradford Hill’s strength of association, factors influencing specificity (Hofler, 2005, pp.3-4), and the necessary and sufficient, or sufficient but not necessary conditions highlighted by Parascandola and weed (2001), are pertinent concerns that force a researcher to look beyond the quagmire of etiologic, and causative associations linked with dietary intake habits.

References

  • Hoefler, M. (2005). The Bradford Hill consideration on causality: a counterfactual perspective. Emerging Themes in Epidemiology, 2(11), 1-9. doi: 10.1186/1742-7622-2-11.
  • Messina, M.J., & Loprinzi, C.L. (2001, July). Soy for breast cancer survivors: A critical review of the literature. Paper presented at American Institute for Cancer Research 11th Annual Research Conference on Diet, Nutrition and Cancer, Washington, D.C.
  • Parascandola, M., Weed D.L. (2001). Causation in epidemiology. Journal of Epidemiology and Community Health, 55(12), 905-911.
  • Phillips, C.V., & Goodman, K.J. (2004). The missed lessons of Sir. Austin Bradford Hill. Epidemiologic Perspectives & Innovations, 1(3),1-5.doi:10.1186/1742-5573-1-3.
  • Sacks, F.M., Lichtenstein, A., Van Horn, L., et al. (2006). Soy protein, isoflavones, and cardiovascular health. CirculationAHA, 106(171052), 1034-1044.
  • Trock, B.J., Hiakivi-Clarke, L., & Clarke, R. (2006). Meta-analysis of soy and breast cancer risk. Journal of the National Cancer Institute, 98(7), 459-471.
  • Weed, D.L. (2000). Interpreting epidemiological evidence: how meta-analysis and causal inference methods are related. International Journal of Epidemiology, 29, 387-390.
  • Wu, A.H., Yu, M.C., Tseng, C.C., & Pike, M.C. (2008). Epidemiology of soy exposures and breast cancer risk. British Journal of Cancer, 98, 9-14.

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