A Campayo

C Barbui

Centers for Disease Control and Prevention

EH Turner

F Andersohn

G. D. Batty

HE Pigott

LC Brown

M Kivimäki

M Olfson

M. Kivimäki

MJ Knol

RR Rubin

English

PubMed

Crossref

Diabetologia

Antidepressant drug use and future diabetes risk

Springer - Publisher Connector

COMMENTARY
Antidepressant drug use and future diabetes risk
M. Kivimäki & G. D. Batty
Received: 5 September 2011 /Accepted: 4 October 2011 /Published online: 29 October 2011
# The Author(s) 2011. This article is published with open access at Springerlink.com
Keywords Adverse drug effects . Antidepressants .
Depression . Diabetes mellitus
Abbreviations
FDA Food and Drug Administration
RCT Randomised controlled trial
Debate around the side effects of antidepressants, one of the
most prescribed groups of drugs worldwide [1], continues.
First there was a concern that antidepressant medication
may, with rather tragic irony, increase suicide risk. Then,
meta-analyses suggested that there was no significant
benefit of antidepressants over placebo in treating patients
with minor depression [2]. The most recent controversy
relates to a series of studies, including one in the present
issue of Diabetologia, suggesting that long-term use of
antidepressants might predispose individuals to type 2
diabetes [3–5].
Given the large number of existing randomised con-
trolled trials (RCTs) on antidepressants and the fact that
antidepressants are prescription drugs approved by govern-
mental authorities in all Western countries, how is it
possible that all major side effects have not already been
ruled out and that efficacy still remains uncertain? One
reason relates to publication bias. In 2008, Turner and
colleagues analysed 74 RCTs approved by the US Food and
Drug Administration (FDA) and found that a total of 37 of
the 38 RCTs regarded by this agency as having positive
results were published whereas 36 RCTs viewed by the
FDA as having negative or questionable results were, with
three exceptions, either unpublished or published in a way
that conveyed a positive outcome [6]. A 2010 review of
four meta-analyses of efficacy RCTs submitted to the FDA
confirmed this profound publication bias and additionally
identified a new source of potential error [7]. The authors of
the review noticed that in the Sequenced Treatment
Alternatives to Relieve Depression (STAR*D) study, the
largest antidepressant effectiveness trial ever conducted,
there was an apparent progressively increasing dropout rate
across each study phase [7]. If this dropout was selective—
and for this study it’s unknown whether it was—it could
seriously bias the findings.
Given these concerns, combined with the fact that
diabetes is considerably under-diagnosed, it seems possible
that diabetogenic side effects could have gone unnoticed in
RCTs. This possibility is supported by observational data
based on medical records showing that long-term antide-
pressant medication use is associated with an up to twofold
increased risk for type 2 diabetes [3–5]. However, as with
all study designs, observational data, particularly those in
register-based studies, also have their methodological
shortcomings. One is that the observed association can
reflect common antecedent causes, such as weight gain,
socioeconomic circumstances and lifestyle factors; that is,
confounding factors that have not been measured, and have
therefore not been taken into account. By contrast,
investigator-led studies are typically better characterised.
An exemplar appears in this issue of Diabetologia, in
which Pan and colleagues present new analyses based on
three large well-known US datasets: the Nurses’ Health
M. Kivimäki (*) :G. D. Batty
Department of Epidemiology and Public Health,
University College London,
1-19 Torrington Place,
WC1E 6BT London, UK
e-mail: m.kivimaki@ucl.ac.uk
Diabetologia (2012) 55:10–12
DOI 10.1007/s00125-011-2360-9
Studies I and II and the Health Professionals Follow-up
Study, a total of 139,000 women and 30,000 men [8].
Besides large sample sizes, these observational studies
include measurements of lifetime history of depression,
current depressive symptoms, and demographic, lifestyle
and anthropometric data. During over 1.6 million person-
years of follow-up, Pan et al. documented a total of 6,641
new cases of type 2 diabetes and found that self-reported
antidepressant use was associated with an approximately
10–30% excess risk of developing diabetes. Importantly,
this association was robust to adjustment for age,
ethnicity, marital and living status, smoking habits,
alcohol intake, physical activity, family history of
diabetes, diet, body mass index and major comorbidities
(e.g. hypertension and dyslipidaemia) and their treat-
ments. In women, oral contraceptive use, menopausal
status and hormone use were also taken into account.
Furthermore, to allow for changes in antidepressant use
and levels of covariates, the authors treated all these
variables as time-dependent by entering in the equation
data from each 2–4 year update. The study was therefore
able to control for a much more comprehensive range of
potential confounding factors and causes common to
both antidepressant use/depression and diabetes than any
of the previous observational investigations.
This evidence should be placed into context. First,
some observational studies have not found a link
between antidepressant use and diabetes [9, 10], raising
the possibility that any positive association might be a
chance finding. This seems unlikely, however, as the
studies reporting a null finding have typically not assessed
antidepressant use with repeated measurements and there-
fore may have missed any effects of long-term antidepres-
sant use. Second, safety issues have been examined in
registered RCTs of antidepressants and no clear evidence
of increased diabetes risk has been documented. However,
as the follow-up periods in trials are relatively short
(typically 12 months rather than several years), these data
do not necessarily rule out the possibility of an elevated
risk of a condition like diabetes, which, like many chronic
diseases, may have a long induction period. Third, it is
also the case that depression per se, rather than antide-
pressant drugs themselves, could be elevating diabetes
rates. A thorough investigation of this issue would require
dissecting the effects of depression and antidepressant
medication on diabetes risk; such data are currently
lacking.
An important challenge to investigating the potential
link between antidepressant drug therapy and future
diabetes risk concerns the assessment of diabetes. By
using self-reports, Pan et al. [8], in keeping with many
other investigators [3–5], have measured only diagnosed
diabetes. Failure to capture undiagnosed diabetes is clearly
a potential source of error because it raises the possibility
of detection bias as an alternative explanation for the
observed associations. That is, a diagnosis of depression
requiring pharmacological treatment might increase the
likelihood of being diagnosed with other medical con-
ditions such as diabetes, artificially creating a link
between the two. There are ways of addressing this
concern. One is to examine whether antidepressant use is
associated with undiagnosed diabetes. If the relationship
between antidepressant use and diabetes is truly causal,
then antidepressant use should be associated with diabetes
irrespective of the method of detection. In a related point,
antidepressant use should also increase blood glucose
levels among those participants who remain non-diabetic
during study follow-up.
Currently, evidence regarding the existence of detec-
tion bias is mixed. In the Whitehall II study of British
civil servants, exposure to antidepressant medication was
monitored by repeated clinical interviews and undiag-
nosed diabetes was screened using an oral glucose
tolerance test in four examinations over an 18 year
follow-up period [11]. In this study, antidepressant use
was associated with self-reported diagnosed diabetes but
not with undiagnosed diabetes, higher fasting plasma
glucose levels or increasing glucose levels over time
[11]. These findings are consistent with the indication bias
explanation and suggest that the antidepressant–diabetes
association is spurious. By contrast, the Diabetes Preven-
tion Program trial, which also used an oral glucose
tolerance test to detect diabetes, suggests that the link
may be ‘real’ [12]. The study recruited people at high risk
of diabetes (overweight and elevated blood glucose levels)
who did not meet the criteria for a diagnosis of diabetes.
Participants were randomly assigned to receive lifestyle
intervention, glucose-lowering medication (metformin) or
placebo [12]. The authors found that in the lifestyle and
placebo groups, participants who were consistently on
antidepressants during the study period were about twice
as likely as non-users to develop diabetes (no such pattern
was seen in the metformin group).
Taking these results together, at this stage we cannot
conclude that antidepressants increase the risk of diabetes,
but we have no strong grounds to exclude this possibility
either. Diabetes is a serious chronic disease that, because it
can cause a catastrophic failure of function in an array of
vital organs, especially the eyes, kidneys, nerves, heart, and
blood vessels, is the seventh leading cause of death in the
US [13]. If antidepressants really do have important
diabetogenic side effects, this would potentially have major
implications for the treatment of depression. In light of the
new findings reported in this issue of Diabetologia, a closer
evaluation of the safety and cost–benefit of antidepressants
is certainly needed.
Diabetologia (2012) 55:10–12 11
Duality of interest The authors declare that there is no duality of
interest associated with this manuscript.
Open Access This article is distributed under the terms of the
Creative Commons Attribution Noncommercial License which per-
mits any noncommercial use, distribution, and reproduction in any
medium, provided the original author(s) and source are credited.
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12 Diabetologia (2012) 55:10–12


Antidepressant medication use and risk of hyperglycaemia and diabetes mellitus—a non-causal association? Biol Psychiatry.

Antidepressant medication use, weight gain and risk of type 2 diabetes mellitus: a population-based study. Diabetes Care 33:2611–2616

Antidepressant medicine use and risk of developing diabetes during the Diabetes Prevention Program and Diabetes Prevention Program Outcomes Study. Diabetes Care 33:2549–2551

Depressive disorder and incident diabetes mellitus: the effect of characteristics of depression.

Disease Control and Prevention

Efficacy and effectiveness of antidepressants: current status of research.

Efficacy of antidepressants and benzodiazepines in minor depression: systematic review and meta-analysis.

Long-term use of antidepressants for depressive disorders and the risk of diabetes mellitus.

National patterns in antidepressant medication treatment.

No increased incidence of diabetes in antidepressant users.

Okereke OI et al (2011) Use of antidepressant medication and risk of type 2 diabetes: results from three cohorts of US adults.

Selective publication of antidepressant trials and its influence on apparent efficacy.

Type of antidepressant therapy and risk of type 2 diabetes in people with depression. Diab Res Clin Pract 79:61–67

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Antidepressant drug use and future diabetes risk

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