Epidemiological Frameworks: Web of Causation (Nursing)

00:01 This presentation is all about an epidemiological framework called The Web of Causation.

00:07 This framework is used to understand the causes of disease.

00:12 We use this in order to understand all of the multiple factors that can cause disease to occur.

00:17 This framework can be used for communicable diseases, chronic diseases, as well as health outcomes.

00:23 Now, a web of causation looks different depending on the specific disease or health outcome that you're mapping out.

00:31 Some webs are as simple as just linking together a couple points, but others contain complex links between several different factors that all contribute to the same disease process.

00:43 Developing a web of causation requires that you ask questions about the root causes of a disease process.

00:50 So we ask ourselves why, why, why, over and over again, until we get to that root cause of disease.

00:58 A communicable disease that has a clearly identified agent can be diagrammed based on factors such as the availability of treatments, or the availability of preventative medications or vaccines, public awareness about the disease.

01:14 Any of these factors could greatly influence the progression of the disease within a community.

01:19 So let's take a look at an example.

01:21 We're going to use the communicable disease of tuberculosis.

01:26 So anytime we start to build a web of causation, we start at the ending point and move backwards.

01:32 So here, we're going to start with an individual who has tuberculosis, and ask herself why that happened.

01:39 So here's our individual who has TB.

01:42 Why do they have TB? Well, it's because they've been infected.

01:47 Well, why was this person infected with tuberculosis? It's because of exposure to the mycobacterium.

01:54 Now that's the agent, the agent that caused infection in the susceptible host.

02:00 So here we are, again, we have to ask ourselves why that exposure happened in the first place.

02:06 Here are a few reasons.

02:08 It could be related to overcrowding, or malnutrition, or they could be susceptible based on genetics, or susceptible because they did not get the TB vaccine.

02:19 And then you could take this even a step further and ask why these conditions exist.

02:24 Why is the population living in overcrowded conditions? Based on your knowledge about the population, you might even add poverty to this as an additional layer.

02:34 By starting with the outcome here that's tuberculosis, and asking ourselves why, over and over again, we've created a web of causation for a communicable disease.

02:46 Now, let's develop a web of causation for chronic disease.

02:50 Again, we start with the outcome, and we move backwards by asking ourselves why, why did this disease form in the first place? We're going to use heart disease as our example here.

03:03 So this is the very beginning of a web for an individual who has heart disease.

03:09 What I've done here is presented factors related to heart disease for this individual.

03:14 As you can see, we have smoking, alcohol consumption, arterial stiffness, stress.

03:21 Now the next step here is to connect all of the dots.

03:26 We know that there's a direct link between smoking, high cholesterol, high blood pressure, and diabetes.

03:34 We also see that high cholesterol is linked to alcohol consumption and high blood pressure.

03:40 High blood pressure is linked to arterial stiffness.

03:44 Arterial stiffness is linked to diabetes, which is also linked back to smoking and poor diet and high cholesterol.

03:52 As you can see, we continue to connect the dots.

03:55 And as we do so what we have is a comprehensive web of causation for chronic condition for one individual.

04:03 These are all the things that contribute to heart disease for a person.

04:09 Now, let's create a web of causation for a health outcome.

04:13 Again, we start with the outcome.

04:15 Here, we're going to use infant mortality as our health outcome.

04:19 And we ask ourselves, why, why, why.

04:23 So let's start by asking ourselves, why could an infant die in their first year of life? Here we see some answers.

04:32 We see the why's.

04:34 Low birth weight, birth injuries, SIDS, accidents.

04:39 So of course, we're going to ask ourselves, why again.

04:43 Here are some of the why's.

04:44 Maternal age, marital status, access to prenatal care.

04:49 So now we need to ask ourselves, why is it that only some people get access to prenatal care? Well, here are some contributors.

04:58 Race and ethnicity, socioeconomic and educational status.

05:03 Now let's ask why one more time.

05:05 We'll take it a step further and ask, why is race a factor that contributes to everything else that we see on this web so far? So let's take a look at our web one more time, all together.

05:17 As a reminder, we started with the outcome.

05:19 We started with infant mortality.

05:22 We asked ourselves why.

05:24 Once we came up with those answers, we asked why again, then why again, and why again.

05:29 And finally, we got to the very top where we see structural racism, and discriminatory policies.

05:35 Those are root causes of infant mortality.

05:39 So clearly, the use of this model allows us to understand all of the factors that influence disease.

05:45 In addition, this model gives us the information that we need in order to break the web and stop the disease onset.

05:53 A public health nurse could focus on any specific factor that's included in the web, and work to eliminate that factor as a way to decrease the risk of disease.

06:03 And I'm not suggesting that all factors have to be eliminated in order to stop disease.

06:08 However, the more factors addressed through an intervention, the higher chance of preventing disease.

06:16 So let's take a look at an example.

06:18 Let's go back to our web of causation for heart disease, we'll focus on smoking.

06:23 We could put together strategies for decreasing smoking with individuals or in the community.

06:29 Here, we see that there's a direct link between smoking, diabetes, cholesterol and high blood pressure.

06:36 So by eliminating smoking as a risk factor, we begin to decrease the impact of all other factors that are related to smoking.

06:44 And doing so we begin to break up the web of causation and decrease the chances of the onset of heart disease.