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ISDS 2016 Conference Abstracts

Linking Binge Drinking, Depression to SES? An age
old question with fresh eyes
Reka Sundaram-Stukel*2, 1, Benjamin Wiseman2 and Anne L. Ziege2
1Department of Agriculture and Applied Economics, University of Wisconsin-Madison, Madison, WI, USA; 2Wisconsin State
Department of Public Health, Madison, WI, USA

Objective
Our primary goal is to move towards establishing a causal link

between binge drinking, mental health, employment and income.

Introduction
One of the key questions in health economics is what is the

direction of causality: does poverty cause poor health outcomes; does
low education cause poor health outcomes; does poor health result
in lack of productivity; does poor health cause poor educational and
income outcomes; and how is this all related to mental health if at all.
We are used to breaking down data into fragments as researchers:
an investigator who is predominantly focused on health outcomes
will approach the problem with disease as the dependent variable and
income as the conditioning variable. However, if we are interested in
income inequality we will reverse the direction and income will be
the dependent variable with health status as the conditioning variable.

The representation above allows us to visualize data as a function
of multiple fragments. For example if we want to understand how
depression is related to income, one can look at the figure to observe
that with lower income there is a higher likelihood of being depressed.
With this simple illustration we can see that establishing causal links
can be very tricky, if not incredibly challenging.

Methods
Two methods are: applied descriptive analysis and estimation.

We approach this without causality in mind, but with an intention
to explore how behavior responds to income, education, labor and
health. Our descriptive approach looks at trends in binge drinking and
mental health as it affects key economic outcomes such as education,
employment, and income. For each outcome we then run a simple
probit model controlling for a variety of characteristics. The key
co-variates in these models are income, employment and health.

It is very useful to look at these simple probits because often it
is hard to separate the effects of income on health, employment on
income, health on employment, education on employment, health and
income, and finally income, employment, health and education on
mental health and substance abuse.

Results
Our estimated results are rather interesting. Examining the

marginal probits, e.g. figures 1.3, and 1.5, we show that there isn’t
a significant income effect, nor do we find significant education or
employment effects associated with binge drinking. In fact we find
that in Wisconsin binge drinking is a health burden for those who
are eligible to drink irrespective of education and that the effect is
significant; we also find that higher levels of education increase the
probability of being unemployed but not significantly. The second
set of probit estimates, e.g. figure 1.7, show that poor health is indeed
associated with outcomes lower employment as compared to other
groups, and higher probability of depression. The last set of probits,
e.g. figure 1.1, show that retired, self employed and employed are
less likely to be depressed but not significantly so, and those who are
unable to work have a higher estimated probablilty to be depressed.

Income doesn’t appear to have a significant estimated effect on
depression.

Conclusions
Our analysis provide insights into the question of socio-economic

status (SES), binge drinking, and depression in three important ways.
First, we explore the relationship between SES and binge drinking
and we find that binge drinking is SES invariant. Second we find
that depression is not associated with income it does have a strong
relationship with employment status. We are in the process of
unpacking the effects of SES, binge drinking and depression to move
beyond associational inferences to causal inferences.

Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * 9(1):e81, 2017

ISDS 2016 Conference Abstracts

Keywords
Binge Drinking; Depression; Employment; Income; Education

Acknowledgments
We acknowledge the staff at the office of health informatics for many
useful comments.

References
Cawley John, and Ruhm Christopher J. (2012). “The Economics of Risky

Health Behaviors.” Handbook of Health Economics, Vol. 2, pages
95-199.

*Reka Sundaram-Stukel
E-mail: Reka.SundaramStukel@dhs.wisconsin.gov

Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * 9(1):e81, 2017

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