commentary free acces publishedin the journal of epidemiology

1. THE CHANGING FACE OF EPIDEMIOLOGY
Editors’ note: This series addresses topics of interest to epidemiologists across a
range of specialties. Commentaries start as invited talks at symposia organized by the
E
­ ditors. This paper was presented at the Third North American Congress of Epidemiology
held in Montreal in June 2011.
Social Epidemiology
Questionable Answers and Answerable Questions
Sam Harpera and Erin C. Strumpf a,b
S ocial epidemiology encompasses the study of relationships between health and a broad
range of social factors such as race, social class, gender, social policies, and so on. One
could broadly partition the work of social epidemiology into surveillance (ie, descriptive
relationships between social factors and health, tracking of health inequalities over time)
and etiology (ie, causal effects of social exposures on health).1 Many social epidemiolo-
gists believe these twin pursuits should ultimately serve to structure interventions aimed
at reducing health-damaging social exposures or increasing exposure to social factors that
enhance health.
SOCIAL EPIDEMIOLOGY RISING
Two decades ago one could have argued that social epidemiology was a fringe sub-
discipline; now it is as prominent as any other specialization within epidemiology. Many
schools of public health now offer concentrations in social epidemiology, most countries
have public health goals aimed specifically at reducing social inequalities in health, and no
fewer than three general and two methodological textbooks on social epidemiology are now
in circulation. More importantly, social epidemiology now occupies an important place in
the realm of public health policy. The World Health Organization’s landmark Commission
on the Social Determinants of Health Report,2 published in 2008, attempted to bring world-
wide attention to social determinants of health and to affect policy decisions in ways that
would reduce social inequalities in health. The Commission’s report would not have been
possible without the pathbreaking work on health inequalities that developed in the United
Kingdom after the Black Report3 in 1980, which subsequently led to two full-scale reports
on health inequalities in the United Kingdom.4,5
Each of these reports has used evidence assembled by social epidemiologists to
advocate for policies aimed at reducing health inequalities, and yet, after the most recent
report5—which found little evidence that health inequalities in England have decreased—
there seems to be considerable consternation about the potential for policies to reduce
social inequalities in health. Johan Mackenbach, who has produced as much evidence on
health inequalities across the European region as anyone, seemed especially pessimistic:
“The main conclusion therefore is that reducing health inequalities is currently beyond
our means. That is the sad but inevitable conclusion from the story of the English strat-
egy to reduce health inequalities.”6 Echoing these same concerns, Bambra and colleagues
From the aDepartment of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada; and bDepartment of Economics,
McGill University, Montreal, Quebec, Canada.
Supported by a Chercheur Boursier Junior 1 from the Fonds de la Recherche du Québec–Santé (to S.H.) and from the Fonds de la Recherche du Québec–Santé
and the Ministère de la Santé et des Services sociaux du Québec (to E.S.).
Editors’ note: Related articles appear on pages 785, 787, and 790.
Correspondence: Sam Harper, Department of Epidemiology, Biostatistics & Occupational Health, McGill University, 1020 Pine Avenue West, Purvis Hall, Room
34, Montreal, Quebec, Canada H3A 1A2. E-mail: sam.harper@mcgill.ca.
Copyright © 2012 by Lippincott Williams & Wilkins
ISSN:1044-3983/12/2306-0795
DOI:10.1097/EDE.0b013e31826d078d
Epidemiology • Volume 23, Number 6, November 2012 www.epidem.com | 795

2. Harper and Strumpf Epidemiology • Volume 23, Number 6, November 2012
were dismayed by the similarity of the conclusions of each of health is not strong enough to overwhelm the effect of social
the English reports more than 30-odd years and questioned causation.16,17 These studies typically ask the descriptive ques-
the purpose of accumulating evidence from social epidemi- tion of whether those in higher status occupations have better
ology, given the fact that the policy conclusions never seem health (controlling for a range of covariates), rather than the
to change.7 These self-critical remarks among committed question of whether intervening to change occupational status
researchers are concordant with evidence from policymak- would lead to improved health outcomes. Case and Paxson,18
ers who charge social epidemiologists (and the broader social however, use the Whitehall data to reframe the question and
determinants of health movement) with providing “policy-free ask whether changes in occupational grade affect changes in
evidence” and the “right answers to the wrong questions.”8 health and, in a parallel fashion, whether changes in health
affect changes in occupational grade. Using a fixed-effects
CRITIQUES OF THE SOCIAL APPROACH design that controls for unmeasured time-invariant individual
The gap between the questions policymakers want characteristics, they find no evidence that civil service grade
answered and the kinds of questions social epidemiologists affects health, but some evidence that health affects future
have been answering is evident in a series of commentar- employment. They also find that future civil service grade
ies on the most recent report9 by Michael Marmot on health predicts current health, suggesting health-related selection or
inequalities in the United Kingdom. While social epide- unmeasured confounding. Although this identification strat-
miologists largely praised the report (some even chided the egy trades off a lot of precision for a reduction in bias,19 it is
UK committee for not being radical enough in their policy probably closer to the kind of question that we would ask if
recommendations),10 others questioned whether the report we could design a randomized trial to evaluate the effects of
had provided sufficient evidence to back its strong policy occupational grade on health.
recommendations.11,12 Critics accused social epidemiologists A second example comes from a randomized trial
of being “casual about causality” and argued that there was, called the Moving to Opportunity study. The backdrop here
in fact, little evidence to suggest causal effects of income or is an abundance of observational research showing that
education on health (although there is better evidence for the neighborhood characteristics such as poverty concentration
association between early-life conditions and health in later are associated with a wide range of health and social
life). The discrepant readings of this evidence may be a conse- outcomes.20 In the randomized study, nearly 5000 families
quence of social epidemiologists generally answering descrip- living in high-poverty urban neighborhoods in five U.S. cities
tive questions (whether socially disadvantaged individuals were randomly assigned one of two treatments, one of which
have poorer health), but interpreting their findings causally required relocating to a more prosperous neighborhood.
(whether socially disadvantaged individuals would have bet- The intervention was successful in reducing exposure to
ter health if they were to become advantaged, or vice versa). concentrated poverty, but intention-to-treat (ITT) estimates
Such interpretation implies both an intervention and a causal on social and health outcomes (in the presence of substantial
effect of that intervention. Social epidemiologists often pres- non-compliance) were largely null.21 Sociologists Clampet-
ent their results in counterfactual terms that imply causation: Lundquist and Massey used the same data but analyzed it
if clerical workers had the same mortality as administrators,13 as an observational study, arguing that the ITT estimate can
if blacks had the same mortality as whites,14 if everyone had “measure the effects of the policy initiative, but is not well
the same mortality rates as those with a university educa- suited to capturing neighborhood effects.”22 This quote seems
tion,15 the reduction in disease burden would be substantial. to reflect some of the tension mentioned above between the
Furthermore, such counterfactuals often do not correspond to kind of evidence wanted by policymakers (causal effect
any known or feasible interventions. We suggest that the epi- of the policy) and the kind of evidence being delivered by
demiologic question should be reframed and that changing the social epidemiology. The investigators found evidence that
question can make an important difference both to the answer increased exposure to low poverty areas is beneficial—
one gets about the impact of social conditions on health and although by breaking the randomization they reintroduced
to one’s ability to provide useful information to policymakers. precisely the same kinds of selection effects that led to the
Some examples follow. concerns cited above about being “casual about causality.”23
This does not mean that randomized experiments are the only
REFRAMING THE QUESTION solution. Sampson and colleagues,24 for example, were able to
The UK Whitehall studies have provided numerous “recover” the randomization study estimates on verbal IQ by
analyses demonstrating positive associations between civil explicitly mimicking the design of a trial in observational data
service occupational grade and health, but concerns are often from Chicago neighborhoods.
raised about the potential for social gradients to arise because A third example of reframing concerns the effect of
of unmeasured confounding or health-related selection. education on mortality. Countless social epidemiologic stud-
Whitehall investigators have largely attributed their results to ies have followed persons with high versus low education
social causation, arguing that any social selection based on and found substantially increased mortality among the less
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3. Epidemiology • Volume 23, Number 6, November 2012 Social Epidemiology
educated—an association that is in most cases robust to con- is to inform policy then our questions should be motivated by
trols for additional socioeconomic, behavioral, and biologic identifying causal relationships that can be of the most use to
factors.25 These observational studies ask whether more edu- policymakers. It goes without saying that in this short essay
cated individuals have lower mortality, but generally do not we have painted social epidemiology with perhaps too broad
ask what policymakers want to know: what would the health a brush—many social epidemiologists undoubtedly produce
effects be of intervening to increase a person’s amount of high-quality evidence on the impact of social exposures on
education, or their achievement of a certain educational qual- health. Yet, our concern here is that much of social epidemiol-
ification? Most observational study designs cannot answer ogy is providing questionable answers to important questions,
this question, because it is very difficult to control for the rather than focusing on answerable questions. Batty35 recently
multitude of factors that jointly determine both education and lamented the lack of interest among the research community
health.26 However, more recent studies have used changes in in generating experimental or quasi-experimental evidence on
schooling policies that are more plausibly independent of social determinants of health. To focus on answerable ques-
unobserved individual characteristics and their health out- tions, social epidemiologists may need to sharpen their focus
comes (eg, minimum age required for leaving school) to on specific questions that are more narrow in scope, but for
minimize unmeasured confounding. These studies bring us which experimental or quasi-experimental data exist.
closer to answering the question of whether intervening to The major strength of experimental and quasi-experi-
increase educational achievement is likely to have effects on mental designs lies in their robustness to unobserved con-
mortality, and the results are decidedly more mixed.25 Several founding. Such designs also have conceptual strengths that
studies provide evidence that exogenous changes in school- come from asking specific causal questions. Trials have their
ing resulting from policies reduce mortality,27–29 but several own limitations and will never answer some social epidemi-
other studies do not, even for different analyses of the same ologic hypotheses, but attempting to mimic the randomized
country.29–32 The contrast between the consistency of studies trial one would hypothetically conduct to answer an important
answering descriptive questions and the mixed evidence for question would seem to be a good place to start.36,37 Finally,
(more approximately) causal questions suggests that this dis- we would also argue that greater transparency in methods
tinction matters. and reporting would increase the value of replication stud-
A final example comes from our own work, but again ies38 that can directly address the question of how sensitive
reflects the importance of focusing on a well-specified causal research findings in social epidemiology may be to measure-
question. A recent article found that U.S. states with medi- ment error, model selection, unmeasured confounding, and
cal marijuana laws had higher adolescent marijuana use.33 other potential biases.39,40 Greater attention to both research
The authors focused on two comparisons: (1) the difference design and rigorous analysis can help social epidemiologists
in marijuana use between states passing laws and states with answer important questions rather than continuing to generate
no laws and no history of such laws and (2) the difference in questionable answers.
marijuana use between states that had already passed laws and
states that had never passed a law. Neither of these contrasts ABOUT THE AUTHORS
represent the causal question facing policymakers in a state Sam Harper and Erin Strumpf are Assistant Professors in
currently without a medical marijuana law; namely, what is the Department of Epidemiology, Biostatistics & Occupational
likely to happen to marijuana use among adolescents if we Health at McGill University, where Erin Strumpf also holds
legalize medical marijuana? Yet the data do permit asking an appointment in the Department of Economics.
precisely this question. Using difference-in-differences esti- Sam Harper works on measuring social inequalities in
mation, we compared the change in marijuana use among health and how they change over time. Erin Strumpf's research
adolescents after a medical marijuana law is passed to cor- in health economics focuses on measuring the causal impacts
responding changes over the same period in states that do not of health and health care policies on spending and health
pass a law and found little evidence of any effect.34 Although outcomes overall, and in inequalities across groups.
this strategy obviously does not approach randomization to
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