Epidemiology is often described as the cornerstone science in public health. Epidemiology in public health practice uses study design and analyses to identify causes in an outbreak situation, guides interventions to improve population health, and evaluates programs and policies. In this course, we'll define the role of the professional epidemiologist as it relates to public health services, functions, and competencies. With that foundation in mind, we'll introduce you to the problem solving methodology and demonstrate how it can be used in a wide variety of settings to identify problems, propose solutions, and evaluate interventions. This methodology depends on the use of reliable data, so we'll take a deep dive into the routine and public health data systems that lie at the heart of epidemiology and then conclude with how you can use that data to calculate measures of disease burden in populations.
Conceptual Framework
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Epidemiology in Public Health Practice
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Methodology
In this module, we will introduce the problem solving methodology. This methodology is a powerful tool that can useful when identifying a public health problem, building the case that there truly is a problem, suggesting interventions, and suggestions ways to evaluate the interventions and disseminate the findings of the evaluation.
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Keri AlthoffAssociate Professor
Epidemiology
The next step in the problem solving methodology,
is creating a conceptual framework.
A conceptual framework is a visualization of how we think the world is working.
And as Paul Hughes said,
a conceptual framework is a frame that works to put those concepts into practice.
As you can see in our figure,
once you have a problem definition that you think is close to your final version,
remembering that you can revise your problem definition at any point
in this methodology, you have meaningful measures of the magnitude of the problem.
So now you're ready to move on to drawing a picture of the problem.
That's really what the conceptual framework is,
a picture of the problem that includes key determinants of the problem.
So before you start drawing your picture, you turn to the literature and
existing information.
You review peer-reviewed literature, Grey Literature which includes expert opinions.
And consensus statements, you search the web, you look throughout your individual
agency to see if there's additional information that may be unpublished.
You use all of these resources to identify key determinants.
Although there are maybe not a lot of literature about key determinants of
infant mortality specifically in Baltimore City.
There's certainly a lot of literature about key determinants
of infant mortality in other settings that could be applicable to Baltimore City.
So you search for information and literature and
you start making lists of key indicators or determinants of infant mortality.
When you're looking at the literature and
other sources of information don't only observe the key determinants.
Be sure you are paying attention to the outcomes in these studies and
other pieces of information.
Do they use infant mortality rate?
What other indicators of infant mortality are being used?
Create a list of the outcome indicators next to your list of key determinants.
Next, focus in on your key determinants.
Sort that list of key determinants into proximal and distal determinants.
Proximal key determinants are the factors closest to your outcome.
We have two categories of proximal determinants.
Direct causes of the outcome and the individual level characteristics
of determinants that may or may not be causal.
The importance of identifying proximal determinants
is that these are the determinants we target for intervention.
These proximal determinants help answer our question about how to best intervene.
Intervening on proximal determinants typically results in a greater decrease
in the problem, as compared to when we target distal determinants.
Next we identify the distal determinants in our list.
And these are the determinants that are little bit further removed from
the outcome.
These are often times associated but not causally linked to the outcome.
We'll be using two categories for distal determinants.
The first are environmental determinants,
which are characteristics of the environment.
The other are non-modifiable distal determinants, and
these are typically individual level characteristics that are not
modifiable with public health intervention like changing someone's education level.
Alternatively, they could be truly non-modifiable, like race,
something you are born with.
The importance of the distal determinants and more specifically the non-modifiable
determinants is that these determinants help us to identify the group
of people we should target for intervention.
Now that we've sorted our key determinants,
we can begin to draw them into a picture.
The first box on the far right side is the outcome.
For our problem definition we can simply write infant mortality.
Notice we did not write infant mortality rate because we know that
there are numerous statistics we could use to measure infant mortality.
That being said, the infant mortality rate is standardized to the size of
the population because the denominator is the number of live births.
So there are benefits to using this specific indicator of
infant mortality rate.
So let's start drawing our picture.
First, we draw in the proximal indicators that are the direct causes of
infant mortality.
Here I've identified congenital malformations, low birth weight and
short gastration, respiratory distress, sudden infant death syndrome or
SIDS, and accidental suffocation or strangulation bed.
These determinates can directly result in infant mortality.
I found them in the literature and other web based resources.
We can draw end arrows to show their direct link with infant mortality and
we can also draw end arrows to show the relationships between these proximal
causal key determinants.
Now we can move on to proximal key determinants that are individual level
characteristics of mother and baby.
Let's pause right here to work it out.
You can write down the proximal individual level characteristics of mother and baby,
and draw lines from these determinants to other determinants currently shown.
If you're unfamiliar with this content area of infant mortality rate,
please do attempt this exercise with key determinants
you think may fit the proximal, individual level characteristic category.
It's okay to guess because drawing this framework is also an iterative process
like the drafting of the problem definition.
Click Continue when you're ready to move on.
Let's compare proximal individual level determinants of mother and baby.
I have listed low maternal intake of magnesium and folic acid.
Lack of prenatal care, smoking, alcohol and drug use, and malnutrition
of either the mother or the baby, as proximal individual level determinants.
You will notice only one is directly applicable to the baby, malnutrition.
The others are characteristics of the mother.
I have also drawn the lines between these determinants and
our proximal causal determinants.
Notice that none of the proximal mother-baby determinants
have arrows directly drawn from them to infant mortality.
If one of these proximal mother-baby determinants was directly causal with
infant mortality,
we would want to move it into the proximal causal determinants category.
Let's keep working on this exercise.
The next category of determinants is distal environmental determinants.
You give it a try.
Add distal environmental determinants on the appropriate arrows
into our conceptual framework.
Click Continue when you are ready to move on.
Let's compare again.
I have added air pollution, parental chemical exposures and
unsafe sleeping environments including sharing a bed with the infant.
As distal environmental determinants,again, these determinants
have been shown in the literature to be associated with infant mortality.
You can see I've drawn in arrows that link these distal environmental determinants,
to proximal causes of infant mortality.
If applicable,
the arrows could have also been drawn to the mother baby proximal characteristics.
Last category of determinants.
Distal, non-modifiable determinants.
Add your distal non-modifiable determinants in appropriate arrows.
Click Continue when you're ready to move on.
The distal non-modifiable determinants I identified
were African American race of the mother and or baby, adolescent age of the mother,
low educational attainment of the mother, and short inter-pregnancy interval.
You could argue that these could be listed under the proximal mother baby category.
I chose to put them under non-modifiable distal determinants
because I like to use this category as the keeper of the determinants I will use
to target sub-groups for intervention.
This is a stylistic decision.
The two main uses of the conceptual framework are to identify the who and
how of your intervention.
For organizational purposes the determinants like guide
who you'll intervene upon are best kept in the individual non-modifiable
characteristics but could also be in the proximal individual level characteristics,
if you find that makes more organizational sense to you.
The determinants that will guide how you intervene, that is,
what types of interventions would most likely result in a decrease in the infant
mortality rate, are going to be found in the proximal causes.
For example, in order to address the proximal cause determinant like accidental
supplication or strangulation in bed, one intervention maybe to provide
new mothers with this safe sleep space for their babies outside of their mothers bed.
Such as a bassinet with sleep sacks or other materials to keep
babies sufficiently warm without the risk of accidental strangulation.
Although we provide guidance for creating conceptual frameworks.
There is a lot of art in creating these frameworks.
With practice and experience, you will develop your own style for
the conceptual framework that best suits you, and
the public health problem that you are working on.
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