Comment on: Knol MJ, Twisk JWR, Beekman ATF, Heine RJ, Snoek FJ, Pouwer F. (2006) Depression as a risk factor for the onset of type 2 diabetes mellitus. A meta-analysis. Diabetologia; 49: 837–845

Article (PDF Available)inDiabetologia 49(11):2797-8; author reply 2799-800 · December 2006with38 Reads
DOI: 10.1007/s00125-006-0389-y · Source: PubMed
Comment on: Knol MJ, Twisk JWR, Beekman ATF, Heine
RJ, Snoek FJ, Pouwer F. (2006) Depression as a risk factor
for the onset of type 2 diabetes mellitus. A meta-analysis.
Diabetologia 49: 837845
P. de Jonge & J. G. M. Rosmalen
Received: 4 July 2006 / Accepted: 11 July 2006 / Published online: 18 August 2006
Springer-Verlag 2006
To the Editor:
We read the meta-analysis published by Knol and
colleagues in Diabetologia with much interest [1 ]. The
authors should be commended for their thorough work on
this complex issue. However, one aspect of their work
remains relatively poorly discussed, namely, the variety of
methods used to measure depression and diabetes in their
included studies. Although acknowledged as a study
limitation, this issue has at least two important consequen-
ces we would like to discuss.
First, with regard to depression, the authors admit that
the gold standard is a diagnostic interview schedule, but
studies using weaker methods, such as self-report depres-
sion data, self-report semi-depression data, and general
practitioners documented diagnosis of depression were
also included in the meta-analysis. Except for one study [2],
all used these relatively weak methods. Notably, the only
study on the effects of formally diagno sed depression on
diabetes incidence did not find a significantly raised risk
(relative risk 2.23; 95% CI 0.905.55). The potential bias of
not using a gold standard is easily illustrated: in a meta-
analysis on the prevalence of depression in diabetes [3], a
prevalence of depression of 11.4% was found when
psychiatric interview data were used, compared with
31.0% when self-report scales were used (p<0.0001).
Although the use of self-report instruments seems justified
when looking at their sensitivity and specificity, their use is
limited by the low positive predi ctive value of self-report
measures (between 30 and 50%) (for example, see [4]),
resulting in these overestimated prevalence rates. It remains
to be determined to what extent these prevalence rates
reflect treatable depression cases. Eventually, and as
expressed by the authors, one would like to answer the
question of whether preventing and/or treating depression
prevents or delays the onset of type 2 diabetes. Since
clinical guidelines and the intervention trials on depression
(for example, see [5]) are based on a formal psychiatric
diagnosis of depression, one may wonder whether the
results of the study by Knol et al. can be used to address
this issue.
Second, the authors tried to apply their findings to the
aetiology of depressiondiabetes comorbidity, and sugges t
several candidate mechanisms (e.g. increased activity of the
hypothalamicpituitaryadrenal axis, dysregulation of the
immune syst em, and a low intake or impaired metabolism of
omega-3 polyunsaturated fatty acids). However, in order to
study these mediators in sufficient detail, diabetes should be
scored on a continuous scale, e.g. using blood glucose levels,
rather than using a binary standard. The presence of diabetes
is nothing more than the crossing of a more-or-less arbitrary
cut-off value for insulin resistance, which may be important
for clinical purposes but is not very useful for aetiological
questions. Not only does artificial dichotomising result in a
loss of relevant inter-subject variation, but, as elegantly
shown by Babyak [6], it can also result in spuri ous findings.
As such, the meta-analysis provides an overview of the
existing literature on the possible link between depression
and diabetes, but by doing so it shows that much remains
unclear. Studies are urgently needed in which the methods
used to determine depression and diabetes are adjusted to
the question being addressed. The question, Can we
prevent d iabetes by treating depression? can only be
answered using diagnostic data on depression, and the
aetiological question, Can depression cause diabetes? can
only be addressed using blood glucose levels.
Diabetologia (2006) 49:27972798
DOI 10.1007/s00125-006-0389-y
P. de Jonge (*)
J. G. M. Rosmalen
Department of Psychiatry, University Medical Center Groningen,
University of Groningen,
P.O. Box 30.001, 9700 Groningen, The Netherlands
1. Knol MJ, Twisk JWR, Beekman ATF, Heine RJ, Snoek FJ, Pouwer
F (2006) Depression as a risk factor for the onset of type 2 diabetes
mellitus. A meta-analysis. Diabetologia 49:837845
2. Eaton WW, Armenian H, Gallo J, Pratt L, Ford DE (1996)
Depression and risk for onset of type II diabetes. A prospective
population-based study. Diabetes Care 19:10971102
3. Anderson RJ, Freedland KE, Clouse RE, Lustman PJ (2001) The
prevalence of comorbid depression in adults with diabetes: a meta-
analysis. Diabetes Care 24:10691078
4. Strik JJ, Honig A, Lousberg R, Denollet J (2001) Sensitivity and
specificity of observer and self-report questionnaires in major and
minor depression following myocardial infarction. Psychosomatics
5. Lustman PJ, Clouse RE, Nix BD et al (2006) Sertraline for
prevention of depression recurrence in diabetes mellitus: a
randomized, double-blind, placebo-controlled trial. Arch Gen
Psychiatry 63:521529
6. Babyak MA (2004) What you see may not be what you get: a brief,
nontechnical introduction to overfitting in regression-type models.
Psychosom Med 66:411421
2798 Diabetologia (2006) 49:27972798
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