RESEARCH ARTICLE

Chronology of Onset of Mental Disorders

and Physical Diseases in Mental-Physical
Comorbidity - A National Representative
Survey of Adolescents
Marion Tegethoff1*, Esther Stalujanis1, Angelo Belardi1, Gunther Meinlschmidt2,3
1 Division of Clinical Psychology and Psychiatry, Department of Psychology, University of Basel, Basel,
Switzerland, 2 Division of Clinical Psychology and Epidemiology, Department of Psychology, University of
a11111 Basel, Basel, Switzerland, 3 Faculty of Medicine, Ruhr-University Bochum, Bochum, Germany

* marion.tegethoff@unibas.ch

Abstract
OPEN ACCESS

Citation: Tegethoff M, Stalujanis E, Belardi A,

Meinlschmidt G (2016) Chronology of Onset of Background
Mental Disorders and Physical Diseases in Mental- The objective was to estimate temporal associations between mental disorders and physi-
Physical Comorbidity - A National Representative
cal diseases in adolescents with mental-physical comorbidities.
Survey of Adolescents. PLoS ONE 11(10):
e0165196. doi:10.1371/journal.pone.0165196

Editor: Soraya Seedat, Stellenbosch University,

Methods
SOUTH AFRICA
This article bases upon weighted data (N = 6483) from the National Comorbidity Survey
Received: May 25, 2016
Adolescent Supplement (participant age: 13–18 years), a nationally representative United
Accepted: October 8, 2016
States cohort. Onset of Diagnostic and Statistical Manual of Mental Disorders, Fourth Edi-
Published: October 21, 2016 tion lifetime mental disorders was assessed with the fully structured World Health Organi-
Copyright: © 2016 Tegethoff et al. This is an open zation Composite International Diagnostic Interview, complemented by parent report.
access article distributed under the terms of the Onset of lifetime medical conditions and doctor-diagnosed diseases was assessed by self-
Creative Commons Attribution License, which
report.
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Results
Data Availability Statement: Data were obtained
from the Interuniversity Consortium for Political The most substantial temporal associations with onset of mental disorders preceding onset
and Social Research (ICPSR) repository. According of physical diseases included those between affective disorders and arthritis (hazard ratio
to ICPSR data policy, the authors are not allowed to (HR) = 3.36, 95%-confidence interval (CI) = 1.95 to 5.77) and diseases of the digestive sys-
share these data publicly. None of the authors are
affiliated with the ICPSR. Co-authorship of ICPSR
tem (HR = 3.39, CI = 2.30 to 5.00), between anxiety disorders and skin diseases (HR =
members or any other researcher, including 1.53, CI = 1.21 to 1.94), and between substance use disorders and seasonal allergies
scientists that collected the data, has not been (HR = 0.33, CI = 0.17 to 0.63). The most substantial temporal associations with physical
required in order to gain access to the data set.
diseases preceding mental disorders included those between heart diseases and anxiety
There are no specific barriers for access to the data
by the ICPSR. For further details, please refer to the disorders (HR = 1.89, CI = 1.41 to 2.52), epilepsy and eating disorders (HR = 6.27, CI =
ICPSR website (http://www.icpsr.umich.edu/ 1.58 to 24.96), and heart diseases and any mental disorder (HR = 1.39, CI = 1.11 to 1.74).

PLOS ONE | DOI:10.1371/journal.pone.0165196 October 21, 2016 1 / 19

 Mental-Physical Comorbidity: Chronology

icpsrweb/HMCA/studies/28581). When the authors Conclusions

applied for access to the data set, they had to
complete the application form including Findings suggest that mental disorders are antecedent risk factors of certain physical dis-
information on the scope of the research project, eases in early life, but also vice versa. Our results expand the relevance of mental disorders
the principal investigators, and the need for the beyond mental to physical health care, and vice versa, supporting the concept of a more
restricted data. Furthermore, they had to prepare a
data protection plan in which they specified how
integrated mental-physical health care approach, and open new starting points for early dis-
data would be handled to prevent unauthorized ease prevention and better treatments, with relevance for various medical disciplines.
persons from gaining access to the data. The
principal investigators had to sign a restricted data
use agreement specifying the terms of the use of
the data. Further research staff with access to the
data had to sign a supplemental agreement. All
researchers who would be working on the project Introduction
had to provide their curriculum vitae. Additionally, As the health of young people contributing to future population health and global economic
on the website of the ICPSR it is stated that
development has been neglected yet, it has now become a ‘pressing issue’ [1]. The World
researchers who want to apply for restricted data
need to have an appointment at a research Health Organization (WHO) and key medical journals such as the Lancet are dealing with the
institution and an academic degree (possibly challenges that non-communicable diseases and mental disorders are imposing on the health
doctorate). ICPSR is a large and well-established care systems, and it has been claimed that these conditions need to be considered in global
institution specifically aimed at providing long-term efforts in improvements of health, social policy, and health-care delivery [2–4].
data access. Therefore, data storage at ICPSR
The relevance of the integration of mental and physical health arises from adult studies doc-
ensures that data are well-documented and
accessible in the foreseeable future. In the rare
umenting the systematic co-occurrence of mental disorders and physical diseases [3, 5–10].
case of modifications to data in the repository (e.g. Findings from longitudinal studies suggest that depression may be a risk factor for the develop-
due to corrections), which may hamper the ment of cardiovascular diseases such as high blood pressure and coronary heart disease [11–
possibility to precisely replicate the results in the 13], autoimmune diseases such as type 1 diabetes, Crohn’s disease, and psoriasis [14], asthma,
publication, the ICPSR user support can be back pain, and migraines [12]. Temporal associations between depression and rheumatoid
contacted to acquire a former version of the data.
arthritis as well as respiratory diseases seem to be bidirectional [12, 15, 16]. Furthermore, post-
The contact information is as follows: Peter
Granda: peterg@icpsr.umich.edu; Alon Axelrod: traumatic stress disorder has been found to precede coronary heart disease [17], type II diabe-
alon@icpsr.umich.edu. tes [18], and respiratory diseases [19], whereas irritable bowel syndrome may be an antecedent
risk factor of epilepsy [20]. The healthcare significance of mental-physical comorbidity is
Funding: This project was financed by the Swiss
National Science Foundation (SNSF, to MT, project underlined by diminished quality of life and unfavorable course of disease [21], substantial
no. PZ00P1_137023; http://www.snf.ch/en/). healthcare costs, higher treatment demand, longer treatment duration, and impaired treatment
Additionally, MT and GM receive funding from the response in persons with mental-physical comorbidity [22, 23]. Integrating mental and physi-
Korea Research Foundation (http://www.nrf.re.kr/ cal health has gained attention and advanced into the focus of major journals, current strategic
nrf_eng_cms/) within the Global Research Network
research goals and task forces [24–26].
Program under project no. 2013S1A2A2035364,
and GM receives SNSF funding under project no.
Despite this relevance, the understanding of mental-physical comorbidity in children and
100014_135328. The funding sources had no adolescents is scarce, even though some studies support a relationship between mental disor-
involvement in study design; in the collection, ders and physical diseases already during childhood or adolescence [27–35]. First evidence
analysis, and interpretation of the data; in the from longitudinal studies suggest that epilepsy may be a risk factor for the development of
writing of the report; and in the decision to submit attention-deficit/hyperactivity disorder [36], that asthma may precede affective and anxiety
the article for publication. The National Comorbidity
disorders [37, 38], and that eating disorders may be an antecedent risk factor of a variety of
Survey Replication Adolescent Supplement (NCS-
A) was funded by: United States Department of physical diseases [31]. These studies, however, mostly used clinical samples and focused on
Health and Human Services. National Institutes of selected mental or physical problems, and it has been suggested to further develop the life
Health. National Institute of Mental Health (U01- course perspective [39].
MH60220); United States Department of Health The current understanding of the etiology of mental-physical comorbidity is largely based
and Human Services. National Institutes of Health.
on theoretical models attempting to explain how mental disorders and physical diseases come
National Institute on Drug Abuse (R01-DA12058-
05); United States Department of Health and
to be comorbid. These theories suppose that one condition operates as risk factor for the other,
Human Services. Substance Abuse and Mental or that shared risk factors underlie both mental disorders and physical diseases [5, 40]. How-
Health Services Administration; Robert Wood ever, studies providing implications regarding trajectories in the development of mental-physi-
Johnson Foundation (Grant 044780); John W. cal comorbidity are lacking. Therefore, knowledge on the temporal course of conditions has
Alden Trust. been claimed as highly relevant [41, 42].

PLOS ONE | DOI:10.1371/journal.pone.0165196 October 21, 2016 2 / 19

 Mental-Physical Comorbidity: Chronology

Competing Interests: I have read the journal’s To better understand the developmental trajectories of mental-physical comorbidity, the
policy and the authors of this manuscript have the main objective of this study was to estimate in adolescents with mental-physical comorbidity
following competing interests: GM is a consultant
the temporal association of mental disorders and physical diseases, using data on the age of
for Janssen Research & Development, LLC.,
receiving a moderate personal fee. This does not onset of a wide range of mental and physical morbidities from a representative national cohort
alter our adherence to PLOS ONE policies on study.
sharing data and materials.

Methods
Study sample
We based this study on data of the National Comorbidity Survey Replication Adolescent Sup-
plement (NCS-A), a national representative survey of initially 10148 United States (US) adoles-
cents (ages 13–18), of which 10123 were students at the time of the survey. Data collection took
place between February 2001 and January 2004 [43–45]. Further details on the study protocol
of the NCS-A have been described previously [34, 43, 44, 46]. We based our analyses on a sub-
sample of 6483 NCS-A participants for which parents or guardians completed a Self Adminis-
tered Questionnaire (SAQ), as described previously [34]. Details on the subsample for which
no parent report was available, and differences between these two subsamples, are available in
supplementary Table 1 of a previous publication that was based on the same dataset [35]. Ado-
lescent and parent provided written informed consent, and the study protocol was approved by
the Human Subjects Committee of Harvard Medical School and the University of Michigan.

Diagnostic Assessment
Mental disorders. To assess lifetime mental disorders, trained interviewers administered a
computer-assisted version of the WHO Composite International Diagnostic Interview (CIDI)
Version 3.0 [45, 46]; details have been described previously [43, 47]. Additional information
on adolescents’ mental health was collected from parents or guardians based on the SAQ focus-
ing on attention-deficit/hyperactivity disorder, conduct disorder, oppositional defiant disorder,
major depressive disorder, and dysthymic disorder, because collecting information from
parents about those disorders has been found to be diagnostically valuable [48–50]. Informa-
tion from adolescents and parents was combined. A mental disorder was considered present
when diagnostic criteria were met either based on information obtained from adolescent or
parent, and, in case of discrepancies, the earlier age was used as age of onset.
We grouped specific mental disorders into the following disorder categories: Any affective
disorder (major depressive disorder, dysthymia, and bipolar I or II disorder), any anxiety disor-
der (agoraphobia, generalized anxiety disorder, social phobia, specific phobia, panic disorder,
posttraumatic stress disorder, and separation anxiety disorder), any behavior disorder (atten-
tion deficit hyperactivity disorder, oppositional defiant disorder, and conduct disorder), any
substance use disorder (alcohol abuse or dependency and drug abuse or dependency), any eat-
ing disorder (anorexia nervosa, bulimia nervosa, and binge eating disorder). If an adolescent,
based on either adolescent or parent report, fulfilled diagnostic criteria for more than one dis-
order with a certain disorder category, we used the earliest age as age of onset of the respective
disorder category.
Physical diseases. The lifetime presence (‘yes’, ‘no’) and the age of onset of physical dis-
eases were assessed solely with adolescent self-report, based on a checklist on chronic condi-
tions, which has been applied in the US National Health Interview Survey in similar form [51].
Checklists have been extensively used in national studies [51–54]. It has been shown that chil-
dren are able to reliably and validly report on their health already at early life stages [55–57]. In
this respect, self-report and medical records show good concordance [58], with checklists

PLOS ONE | DOI:10.1371/journal.pone.0165196 October 21, 2016 3 / 19

 Mental-Physical Comorbidity: Chronology

Table 1. Sociodemographic characteristics of the study sample* (N = 6483).

Sociodemographic factor Category n Weighted %
Sex Female 3333 48.76
Male 3150 51.24
Age 13–14 y 2611 35.92
15–16 y 2528 41.88
17–18 y 1344 22.20
Race Hispanic 758 14.38
Afro-American 1097 15.07
Other 371 4.99
Caucasian 4257 65.55
Parental education (highest level of either parent) Less than high school 746 12.32
High school 1852 29.33
Some college 1364 21.31
College grad 2521 37.04
Poverty index ratio** 1.5 (poor) 925 14.59
3 1218 19.26
6 2139 32.65
>6 2201 33.51
Region Northeast 1273 18.15
Midwest 2081 23.27
South 2100 36.02
West 1029 22.56
Urbanicity† Metropolitan area 2645 45.68
Other urban area 2242 39.48
Rural area 1596 14.83
Number of biological parents living with the adolescent 0 528 8.86
1 2284 36.46
2 3671 54.68
Birth order Oldest 2314 38.81
Youngest 1947 28.42
Others 2222 32.77
Number of siblings 0 323 5.24
1 1853 29.30
2 1745 27.44
3 or more 2562 38.02

Abbreviations: y, years
*Subsample of the National Comorbidity Survey-Adolescent Supplement (NCS-A) including all participants providing self- and parent-reported information
on mental disorders.
**Poverty index ratio: The ratio of family income to the poverty threshold of the family, for which the poverty threshold depends on family size [62].
†Urbanicity was categorized based on the classification criteria of the US Census Bureau of 2000: ‘Metropolitan’ corresponds to 1000 or more people per
square mile, ‘Other urban area’ corresponds to at least 500 people per square mile, ‘Rural area’ corresponds to other regions [64].

doi:10.1371/journal.pone.0165196.t001

being superior to data obtained from routine data sources in terms of completeness and accu-
racy [59].
Physical diseases included in our study can be seen in Figs 1 and 2, and further details have
been described previously [34].

PLOS ONE | DOI:10.1371/journal.pone.0165196 October 21, 2016 4 / 19

 Mental-Physical Comorbidity: Chronology

Fig 1. Adjusted discrete-time proportional hazard models estimating the temporal associations of
mental disorders predicting subsequent physical diseases. Note: We based our analyses on completer
sample sizes* of the total study sample (N = 6483), and adjusted for sociodemographic variables shown in
Table 1. The strength of the associations (hazard ratios (HR) is illustrated by the circle diameter, given in the
circles, and 95% confidence intervals, given below the circles). Blue color of the circle (and HRs provided in
small standard type font) represent p0.05 in the total study sample; orange color of the circle and HRs
provided in medium-sized bold type font represent p<0.05 in the total study sample and in less than two
independent subsamples; red color of the circle and HRs provided in large bold and italic type font represent
p<0.05 in the total study sample and in at least two independent subsamples. * Due to missing information
on physical diseases from adolescent self-report, sizes of the completer samples are as follows: arthritis:
n = 6473, seasonal allergy: n = 6475, skin disease: n = 6479, heart disease: n = 6481, asthma: n = 6477,
diabetes/high blood sugar: n = 6481, disease of the digestive system: n = 6481, epilepsy or seizures:
n = 6481, any physical disease: n = 6469.
doi:10.1371/journal.pone.0165196.g001

Statistical analyses
We used weighted data in all statistical analyses, which were conducted with STATA/MP 11
(Stata Corporation, College Station, Texas). Weights were provided with the NCS-A dataset,
and had been calculated based on a wide range of sociodemographic variables with regard to
[43, 44] to ensure representativeness of the NCS-A study sample with the US adolescent popu-
lation. We estimated temporal relationships between mental disorders and physical diseases by
calculating separate discrete-time proportional hazard models with a non-parametric baseline
hazard function using complementary log-log regression, with one of the major classes of men-
tal disorders or ‘any mental disorder’ and one physical disease or ‘any physical disease’ defined
as outcome and as time-varying predictor, respectively, and vice versa [60]. We present hazard
ratios and their 95% confidence intervals. If diagnostic criteria for more than one mental

PLOS ONE | DOI:10.1371/journal.pone.0165196 October 21, 2016 5 / 19

 Mental-Physical Comorbidity: Chronology

Fig 2. Adjusted discrete-time proportional hazard models estimating the temporal associations of
physical diseases predicting subsequent mental disorders. Note: We based our analyses on completer
sample sizes* of the total study sample (N = 6483), and adjusted for sociodemographic variables shown in
Table 1. The strength of the associations (hazard ratios (HR) is illustrated by the circle diameter, given in the
circles, with 95% confidence intervals, given below the circles). Blue color of the circle (and HRs provided in
small standard type font) represent p0.05 in the total study sample; orange color of the circle and HRs
provided in medium-sized bold type font represent p<0.05 in the total study sample and in less than two
independent subsamples; red color of the circle and HRs provided in large bold and italic type font represent
p<0.05 in the total study sample and in at least two independent subsamples. * Due to missing information on
physical diseases from adolescent self-report, sizes of the completer samples are as follows: arthritis:
n = 6473, seasonal allergy: n = 6475, skin disease: n = 6479, heart disease: n = 6481, asthma: n = 6477,
diabetes/high blood sugar: n = 6481, disease of the digestive system: n = 6481, epilepsy or seizures: n = 6481,
any physical disease: n = 6469.
doi:10.1371/journal.pone.0165196.g002

disorder were fulfilled within a mental disorder class, we used the age of onset of the first men-
tal disorder in this class as age of onset of the total class. As we had to deal with complex survey
data, we applied the Taylor series linearization method. In accordance with previous studies
[61, 62], we included sociodemographic variables shown in Table 1 in our analyses to control
for potential confounding. Adjusted results are presented. To account for the large number of
pairwise test, we used an internal subsampling strategy, as previously described [34, 63].
For a low number of subjects information on physical diseases from adolescent self-report
was missing. We restricted each analysis to subjects with complete data (see Figs 1 and 2 for
completer sample sizes according to each physical disease category). We defined statistical sig-
nificance at 0.05 and two-sided tests were applied.

PLOS ONE | DOI:10.1371/journal.pone.0165196 October 21, 2016 6 / 19

 Mental-Physical Comorbidity: Chronology

Results
Study cohort descriptives
Table 1 summarizes the study cohort’s sociodemographic characteristics (N = 6483).

Temporal prediction of physical diseases by mental disorders

Results of the adjusted discrete-time proportional hazard models estimating the temporal asso-
ciations between physical diseases and mental disorders, with mental disorders preceding phys-
ical diseases, in the total sample are presented in Fig 1 (results from subsamples available on
request). The most substantial associations included those of affective disorders with arthritis
and diseases of the digestive system, between anxiety disorders and skin diseases, and between
substance use disorders and seasonal allergies. In support of transparency, results of the crude
regression models are presented in S1 Table.

Temporal prediction of mental disorders by physical diseases

2 presents results of the adjusted discrete-time proportional hazard models of the associations
between mental disorder classes and physical diseases, with physical diseases preceding mental
disorders, in the total sample (results from subsamples available on request). The most sub-
stantial associations included those of heart diseases with any mental disorder and anxiety dis-
orders, and between epilepsy and eating disorders. In support of transparency, results of the
crude regression models are presented in S2 Table.
We provide information on age of onset intervals between the temporal relations of our
most robust findings in S3 Table.

Discussion
This article provides temporal association estimates of lifetime mental disorders and physical
diseases, based on data from 6483 adolescents of a nationally representative cohort. The most
substantial results indicate that affective disorders are a risk factor of arthritis and diseases of
the digestive system, that anxiety disorders are a risk factor of skin diseases, and that substance
use disorders are a protective factor of seasonal allergies. Vice versa, heart diseases may indicate
a risk of anxiety disorders and any mental disorder, and epilepsy a risk of eating disorders.
Our results contribute to previous findings on mental-physical comorbidity mostly resulting
from association studies in clinical or population-based samples in adults and documenting
comprising relationships between mental disorders and physical diseases [3, 5, 6], including
the comorbidity patterns observed in the present study [65–70]. However, as yet, there has
been no evidence suggesting a link between substance use disorders and allergies [71], and
even though comorbidity between epilepsy and mental disorders has been described in chil-
dren [28, 30], epidemiological data on the co-occurrence of epilepsy and eating disorders are
lacking.
There is rare evidence from adult intervention trials providing insight into the developmen-
tal trajectories of co-occurring mental disorders and physical diseases. A contribution of
depression in arthritis is supported by a study demonstrating benefits of improved depression
care that extended beyond reduced depressive symptoms and included decreased pain in older
adults with arthritis and comorbid depression [72]. That anxiety may precede the onset of skin
diseases is elucidated by studies of patients with atopic dermatitis reporting improvement in
anxiety levels and skin conditions after psychotherapy [73, 74]. For eating disorders and epi-
lepsy, it has been hypothesized based on case reports, that epilepsy arising from a right hemi-
spheric focus and right frontal intracerebral lesions–with their close relationship to the limbic

PLOS ONE | DOI:10.1371/journal.pone.0165196 October 21, 2016 7 / 19

 Mental-Physical Comorbidity: Chronology

system–could play a role in the development of eating disorders [75, 76]. This view is sup-
ported by the emerging importance of antiepileptic drugs in the treatment of eating disorders
[77]. Finally, for affective disorders preceding diseases of the digestive system, our findings are
in line with positive associations between current depression and subsequent disease activity in
adult patients with Crohn’s disease or the development of ulcers in previously ulcer-free sub-
jects [78, 79].
In contrast to findings from meta-analyses of studies in adults [80, 81], our data do not sug-
gest anxiety as a risk factor of heart diseases, which may be due to the young age of subjects, as
anxiety-induced pathophysiological processes might take decades to develop. Vice versa, the
prognostic relevance of cardiovascular diseases for anxiety disorders is less clear in the adult lit-
erature. Even though there is some evidence for increased anxiety levels after myocardial
infarction [82–84], prospective data providing pre-infarction information is mostly not avail-
able, and studies addressing causality are lacking.
Different biological, behavioral, cognitive, and social pathways mediating the relationships
between mental disorders and physical diseases have been proposed, but even though study
designs to inform about developmental trajectories have already been applied successfully [85],
specific comorbidity patterns remain to be determined [5, 40, 86]. Until then, the available data
may help to generate hypotheses on the nature of these pathways.
With regard to depression and arthritis, previous work documents the pain-enhancing
potential of brain circuits that may be disturbed in depression [87] and, vice versa, the analgesic
effects of antidepressants [88], indicating that depression-related brain networks might con-
tribute to the etiology of arthritis. Further pathway candidates are the immune system and the
hypothalamic-pituitary-adrenal (HPA) axis, as local inflammation, followed by a systemic
reaction, and inappropriately low secretion of cortisol are typical features of arthritis [89, 90],
and disturbances of the immune system and the HPA axis have been described in persons with
depression [91, 92].
Regarding depression-related onset of diseases of the digestive system, the pathophysiology
of the brain-gut axis, involving the corticotropin-releasing factor system [93] may play a role
[94], as experimental and clinical studies have demonstrated that acute and chronic stress have
impacts on the gastrointestinal system, being permissive in the development of gut diseases
[95].
In terms of potential mechanisms underlying the observed prediction of skin diseases by
anxiety disorders, it is of note that psychological stress has not only been associated with atopic
dermatitis symptom severity [96], but also with various skin health-relevant immune alter-
ations, including slowed wound healing and augmented induction of inflammatory processes
and immunoglobulin E (IgE) production [97, 98]. To date, there is only preliminary evidence
on the psychoneuroimmunology of anxiety disorders, suggesting that high levels of anxiety
might be associated with impaired cellular immunity and IgE synthesis [99, 100].
The reduced risk of seasonal allergy related to substance use disorders in our study may be a
consequence of increased consumption of certain substances, for example alcohol, and related
immunological changes [101–103], but such positive consequences should be interpreted with
caution as it is well established that substance use disorders are associated with increased risk
of morbidity and mortality [104].
Body perception and interoceptive conditioning may contribute to the heart disease-related
increased risk of anxiety disorders [105]: Heartbeat sensitivity has been shown to be increased
in persons suffering from congenital heart diseases compared to healthy controls [106] and
studies using heartbeat perception tasks in anxiety disorders support the notion of higher inter-
oceptive sensitivity towards the heartbeat as etiological factor in anxiety diseases [107].
Changes in neuronal structure and function resulting from epileptic seizures [108], possibly

PLOS ONE | DOI:10.1371/journal.pone.0165196 October 21, 2016 8 / 19

 Mental-Physical Comorbidity: Chronology

contribute to the risk of eating disorders related with epilepsy. A systematic review of case
reports concluded that although simple changes in appetite and eating behavior occurred with
hypothalamic and brain stem lesions, the characteristic psychopathology of eating disorders
was associated with right frontal and temporal lobe damage [109]. On a molecular level, it has
been documented that 5-hydroxytryptamine (serotonin) receptor 2C, G protein-coupled
(HTR2C)-receptor-deficient mice showed disturbed feeding behavior and were prone to spon-
taneous death from seizures, suggesting that 5-HT2C receptors may play a role in linking eat-
ing disorders and epilepsy [110].
Strengths of our study include the large nationally representative sample [43], the broadness
of mental disorders and physical diseases included, the use of a fully structured diagnostic
interview for the assessment of mental disorders, with good quality criteria [43, 47], and the
integration of child and parent information [50]. Good response rate and the minimal amount
of missing data make it unlikely that loss of subjects has introduced selection bias. Still, the
results of this study should be interpreted in light of several limitations; some have been dis-
cussed previously, including self-report measures of physical diseases [34], the cross-sectional
design, and the use of retrospective data, involving the risk of recall bias [46, 111]. Specifically,
the wording of the questions in the physical diseases checklist in the CIDI ("Did a doctor or
other health professional ever tell you that you had any of the following illnesses. . .") might have
led to underestimated values, because to positively answer any of these questions the adolescent
must have sought a health professional and recalled the diagnosis.
However, a suitable longitudinal dataset allowing studying the chronology of onset of men-
tal disorders and physical diseases in mental-physical comorbidity patterns is lacking while
needed to corroborate our findings. Until then, these findings are important to guide future
research by providing hypotheses, not least given the novel probing strategy of the National
Comorbidity Surveys that has been shown to increase the accuracy of age of onset reports
[112]. Moreover, the young and relatively homogenous age range of NCS-A participants within
the peak-onset period of mental disorders [113] diminishes the risk of potential bias by age-
related impairment in the recall of age of illness onset [114]. Furthermore, lifetime prevalence
estimates (reported by our group for the main categories of mental disorders and for physical
diseases in [34] and in [62] for specific mental disorders) and age of onset distributions of men-
tal disorders and physical diseases (see S4 Table) are generally in line with previous findings
[115–134]. Still, participants could have been rather young at disease onset that could have
occurred a decade or more prior to the assessment. This might have introduced recall bias.
However, as already mentioned, previous work demonstrated that children’s self-reports on
their health are largely reliable and valid [55–57].
Moreover, according to the risk-factor concept by Kraemer and colleagues [135] and due to
the cross-sectional design of the study, the presented findings cannot inform about ‘causal risk
factors’ but rather about ‘risk factors’ defined as factors preceding the outcome. Besides the
temporal relationship, other aspects suggesting causality [136] may be considered, including
the strengths of the relationships, for example those between affective disorders and arthritis,
with HRs > 3, the specificity of associations, their mechanistic plausibility as discussed above,
as well as evidence from the few intervention trials or consistency with the few prospective
studies depicted above. Finally, we restricted our analyses to the main categories of mental dis-
orders and physical diseases instead of focusing on subcategories. This hampered integration
of results into the literature but ensured sufficient number of cases for each comorbidity pat-
tern, thereby complying with statistical assumptions.
Given the high lifetime prevalence of some comorbidity patterns [34, 35], the partly sub-
stantial temporal relationships between lifetime mental disorders and physical diseases, and
the high burden for the individual and health economics [21–23, 66], our findings carry

PLOS ONE | DOI:10.1371/journal.pone.0165196 October 21, 2016 9 / 19

 Mental-Physical Comorbidity: Chronology

relevance for psychiatric and medical health care and the roles of psychiatrists and other medi-
cal specialists in patient management [26], and they can inform research priorities and guide
task forces, health policy plans and medical education [137]. In line with current strategic
research goals [24, 25, 138], our results may pave the way to improve diagnostic approaches,
prevention and treatment of mental-physical comorbidity, for example by considering that
treatment of a mental disorder may have implications for a physical disease, and vice versa
[139].
A large body of evidence from the WHO World Mental Health Survey documented that the
epidemiology of mental-physical comorbidity in adults is comparable worldwide [5], suggest-
ing that the temporal course of onset of mental disorders and physical diseases in adolescents
might as well be similar worldwide. However, generalizability of our findings from an adoles-
cent sample on an adult population might be limited, for instance, due to the increasing influ-
ence of lifestyle-related factors across the lifespan and, hence, the rather late onset of certain
physical disorders [140–142].
Future studies should, besides surveying longitudinal data, include subclinical manifesta-
tions of mental disorders and physical diseases, for example using non-invasive measures of
arterial structure and function for heart diseases, that occur before the onset of symptoms, in
order to better understand the temporal sequence of the relationships. Additionally, it may be
worth scrutinizing the comorbidity of mental and physical conditions with regard to the rele-
vance of age of onset, duration of the conditions, and temporal distance between ages of onset
(in future studies). Moreover, randomized-controlled intervention trials in representative pop-
ulations and animal models would be important to shed light on the causality and underlying
biological, psychological and behavioral mechanisms of the relationships between mental dis-
orders and physical diseases that we revealed, to foster the development of interdisciplinary
preventive approaches and interventions, including the development of clinical guidelines deal-
ing simultaneously with mental disorders and physical diseases [143].
To the best of our knowledge, this is the first comprehensive study of the temporal associa-
tion of mental disorders and physical diseases in adolescents with mental-physical comorbidity
in a nationally representative survey, based on data from 6483 subjects. The most substantial
results indicate that affective disorders may increase the risk of arthritis and diseases of the
digestive system, that anxiety disorders may increase the risk of skin diseases, and that sub-
stance use disorders may decrease the risk of seasonal allergies. Vice versa, heart diseases may
indicate a risk of anxiety disorders and any mental disorder, and epilepsy a risk of eating disor-
ders. The clear temporal relationships between mental disorders and physical diseases for spe-
cific comorbidity patterns suggest that certain mental disorders may be risk factors of certain
physical diseases at early life stages, and vice versa. These results predominantly expand the rel-
evance of mental disorders in adolescence beyond mental health care to physical health care,
and vice versa, supporting the concept of integrative care, and open new starting-points for
early disease prevention and better treatments, which is relevant for various medical
disciplines.

Supporting Information
S1 Table. Discrete-time proportional hazard models for lifetime mental disorders (time-
varying) predicting physical diseases (crude models).
(XLS)
S2 Table. Discrete-time proportional hazard models for lifetime physical diseases (time-
varying) predicting mental disorders (crude models).
(XLS)

PLOS ONE | DOI:10.1371/journal.pone.0165196 October 21, 2016 10 / 19

 Mental-Physical Comorbidity: Chronology

S3 Table. Age of onset intervals of temporal associations between mental disorders preced-
ing physical diseases and vice versa in participants reporting both conditions.
(XLS)
S4 Table. Ages of onset by physical disease/mental disorder category.
(XLS)

Acknowledgments
Disclaimer: Hereby, we acknowledge that the original collector of the data, ICPSR, and the rel-
evant funding agency bear no responsibility for use of the data or for interpretations or infer-
ences based upon such uses.

Author Contributions
Conceptualization: MT GM.
Data curation: MT ES AB GM.
Formal analysis: MT AB GM.
Funding acquisition: MT.
Investigation: MT ES GM.
Methodology: MT AB GM.
Project administration: MT ES GM.
Software: MT AB GM.
Supervision: MT GM.
Validation: MT ES AB GM.
Visualization: MT ES GM.
Writing – original draft: MT.
Writing – review & editing: MT ES AB GM.

References
1. Mokdad AH, Forouzanfar MH, Daoud F, Mokdad AA, El Bcheraoui C, Moradi-Lakeh M, et al. Global
burden of diseases, injuries, and risk factors for young people’s health during 1990–2013: a system-
atic analysis for the Global Burden of Disease Study 2013. Lancet. 2016; 387(10036):2383–401. doi:
10.1016/S0140-6736(16)00648-6 PMID: 27174305.
2. Beaglehole R, Ebrahim S, Reddy S, Voute J, Leeder S. Prevention of chronic diseases: a call to
action. Lancet. 2007; 370(9605):2152–7. Epub 2007/12/08. doi: 10.1016/S0140-6736(07)61700-0
PMID: 18063026.
3. Prince M, Patel V, Saxena S, Maj M, Maselko J, Phillips MR, et al. No health without mental health.
Lancet. 2007; 370(9590):859–77. Epub 2007/09/07. S0140-6736(07)61238-0 [pii] doi: 10.1016/
S0140-6736(07)61238-0 PMID: 17804063.
4. World Health Organization. WHO. Global status report on noncommunicable diseases 2010: descrip-
tion of the global burden of NCDs, their risk factors and determinants. Geneva: World Health Organi-
zation; 2011.
5. Von Korff MR, Scott KM, Gureje O. Global perspectives on mental-physical comorbidity in the WHO
World Mental Health Surveys: Cambridge University Press; 2009.

PLOS ONE | DOI:10.1371/journal.pone.0165196 October 21, 2016 11 / 19

 Mental-Physical Comorbidity: Chronology

6. Iacovides A, Siamouli M. Comorbid mental and somatic disorders: an epidemiological perspective.

Curr Opin Psychiatry. 2008; 21(4):417–21. Epub 2008/06/04. doi: 10.1097/YCO.0b013e328303ba42
00001504-200807000-00022 [pii]. PMID: 18520749.
7. Mayer EA, Craske M, Naliboff BD. Depression, anxiety, and the gastrointestinal system. J Clin Psy-
chiatry. 2001; 62 Suppl 8:28–36; discussion 7. Epub 2002/07/11. PMID: 12108819.
8. Scott KM, Von Korff M, Ormel J, Zhang MY, Bruffaerts R, Alonso J, et al. Mental disorders among
adults with asthma: results from the World Mental Health Survey. Gen Hosp Psychiatry. 2007; 29
(2):123–33. Epub 2007/03/06. S0163-8343(06)00253-2 [pii] doi: 10.1016/j.genhosppsych.2006.12.
006 PMID: 17336661; PubMed Central PMCID: PMC1913936.
9. Bruffaerts R, Demyttenaere K, Kessler RC, Tachimori H, Bunting B, Hu C, et al. The associations
between preexisting mental disorders and subsequent onset of chronic headaches: a worldwide epi-
demiologic perspective. J Pain. 2015; 16(1):42–52. doi: 10.1016/j.jpain.2014.10.002 PMID:
25451620.
10. Scott KM, Lim C, Al-Hamzawi A, Alonso J, Bruffaerts R, Caldas-de-Almeida JM, et al. Association of
Mental Disorders With Subsequent Chronic Physical Conditions: World Mental Health Surveys From
17 Countries. JAMA Psychiatry. 2016; 73(2):150–8. doi: 10.1001/jamapsychiatry.2015.2688 PMID:
26719969.
11. Patten SB, Williams JV, Lavorato DH, Campbell NR, Eliasziw M, Campbell TS. Major depression as a
risk factor for high blood pressure: epidemiologic evidence from a national longitudinal study. Psycho-
som Med. 2009; 71(3):273–9. doi: 10.1097/PSY.0b013e3181988e5f PMID: 19196807.
12. Patten SB, Williams JV, Lavorato DH, Modgill G, Jette N, Eliasziw M. Major depression as a risk factor
for chronic disease incidence: longitudinal analyses in a general population cohort. Gen Hosp Psychi-
atry. 2008; 30(5):407–13. doi: 10.1016/j.genhosppsych.2008.05.001 PMID: 18774423.
13. Wu Q, Kling JM. Depression and the Risk of Myocardial Infarction and Coronary Death: A Meta-Anal-
ysis of Prospective Cohort Studies. Medicine (Baltimore). 2016; 95(6):e2815. doi: 10.1097/MD.
0000000000002815 PMID: 26871852; PubMed Central PMCID: PMCPMC4753948.
14. Andersson NW, Gustafsson LN, Okkels N, Taha F, Cole SW, Munk-Jorgensen P, et al. Depression
and the risk of autoimmune disease: a nationally representative, prospective longitudinal study. Psy-
chol Med. 2015; 45(16):3559–69. doi: 10.1017/S0033291715001488 PMID: 26271451.
15. Goodwin RD, Scheckner B, Pena L, Feldman JM, Taha F, Lipsitz JD. A 10-year prospective study of
respiratory disease and depression and anxiety in adulthood. Ann Allergy Asthma Immunol. 2014;
113(5):565–70. doi: 10.1016/j.anai.2014.08.003 PMID: 25216970.
16. Rathbun AM, Reed GW, Harrold LR. The temporal relationship between depression and rheumatoid
arthritis disease activity, treatment persistence and response: a systematic review. Rheumatology
(Oxford). 2013; 52(10):1785–94. doi: 10.1093/rheumatology/kes356 PMID: 23236191.
17. Vaccarino V, Goldberg J, Rooks C, Shah AJ, Veledar E, Faber TL, et al. Post-traumatic stress disor-
der and incidence of coronary heart disease: a twin study. J Am Coll Cardiol. 2013; 62(11):970–8. doi:
10.1016/j.jacc.2013.04.085 PMID: 23810885; PubMed Central PMCID: PMCPMC3823367.
18. Roberts AL, Agnew-Blais JC, Spiegelman D, Kubzansky LD, Mason SM, Galea S, et al. Posttrau-
matic stress disorder and incidence of type 2 diabetes mellitus in a sample of women: a 22-year longi-
tudinal study. JAMA Psychiatry. 2015; 72(3):203–10. doi: 10.1001/jamapsychiatry.2014.2632 PMID:
25565410; PubMed Central PMCID: PMCPMC4522929.
19. Kotov R, Bromet EJ, Schechter C, Broihier J, Feder A, Friedman-Jimenez G, et al. Posttraumatic
stress disorder and the risk of respiratory problems in World Trade Center responders: longitudinal
test of a pathway. Psychosom Med. 2015; 77(4):438–48. doi: 10.1097/PSY.0000000000000179
PMID: 25919367.
20. Chen CH, Lin CL, Kao CH. Irritable Bowel Syndrome Increases the Risk of Epilepsy: A Population-
Based Study. Medicine (Baltimore). 2015; 94(36):e1497. doi: 10.1097/MD.0000000000001497
PMID: 26356716; PubMed Central PMCID: PMCPMC4616652.
21. Beutel ME, Schulz H. [Comorbid psychological disorders in patients with chronic somatic diseases].
Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz. 2011; 54(1):15–21. Epub 2011/
01/20. doi: 10.1007/s00103-010-1191-z PMID: 21246324.
22. Hochlehnert A, Niehoff D, Wild B, Junger J, Herzog W, Lowe B. Psychiatric comorbidity in cardiovas-
cular inpatients: costs, net gain, and length of hospitalization. J Psychosom Res. 2011; 70(2):135–9.
Epub 2011/01/26. doi: 10.1016/j.jpsychores.2010.09.010 PMID: 21262415.
23. Lehnert T, Konnopka A, Riedel-Heller S, Konig HH. [Health economic aspects of physical-mental
comorbidity]. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz. 2011; 54(1):120–
7. Epub 2011/01/20. doi: 10.1007/s00103-010-1187-8 PMID: 21246337.

PLOS ONE | DOI:10.1371/journal.pone.0165196 October 21, 2016 12 / 19

 Mental-Physical Comorbidity: Chronology

24. Collins PY, Patel V, Joestl SS, March D, Insel TR, Daar AS, et al. Grand challenges in global mental
health. Nature. 2011; 475(7354):27–30. Epub 2011/07/08. doi: 10.1038/475027a PMID: 21734685;
PubMed Central PMCID: PMC3173804.
25. Foy JM. Enhancing pediatric mental health care: report from the American Academy of Pediatrics
Task Force on Mental Health. Introduction. Pediatrics. 2010; 125 Suppl 3:S69–74. Epub 2010/06/11.
doi: 10.1542/peds.2010-0788C PMID: 20519564.
26. Sharpe M. Somatic symptoms: beyond ’medically unexplained’. Br J Psychiatry. 2013; 203:320–1.
Epub 2013/11/05. doi: 10.1192/bjp.bp.112.122523 PMID: 24187064.
27. Angel RJ, Angel JL. Physical comorbidity and medical care use in children with emotional problems.
Public Health Rep. 1996; 111(2):140–5. Epub 1996/03/01. PMID: 8606912; PubMed Central PMCID:
PMC1381720.
28. Davies S, Heyman I, Goodman R. A population survey of mental health problems in children with epi-
lepsy. Dev Med Child Neurol. 2003; 45(5):292–5. Epub 2003/05/06. PMID: 12729141.
29. Erhart M, Weimann A, Bullinger M, Schulte-Markwort M, Ravens-Sieberer U. [Psychological comor-
bidity in children and adolescents with chronic somatic diseases]. Bundesgesundheitsblatt Gesund-
heitsforschung Gesundheitsschutz. 2011; 54(1):66–74. Epub 2011/01/20. doi: 10.1007/s00103-010-
1190-0 PMID: 21246331.
30. Freilinger M, Reisel B, Reiter E, Zelenko M, Hauser E, Seidl R. Behavioral and emotional problems in
children with epilepsy. J Child Neurol. 2006; 21(11):939–45. Epub 2006/11/10. PMID: 17092458.
31. Johnson JG, Cohen P, Kasen S, Brook JS. Eating disorders during adolescence and the risk for phys-
ical and mental disorders during early adulthood. Arch Gen Psychiatry. 2002; 59(6):545–52. Epub
2002/06/05. PMID: 12044197.
32. Seng JS, Graham-Bermann SA, Clark MK, McCarthy AM, Ronis DL. Posttraumatic stress disorder
and physical comorbidity among female children and adolescents: results from service-use data.
Pediatrics. 2005; 116(6):e767–76. Epub 2005/12/03. doi: 10.1542/peds.2005-0608 PMID: 16322133.
33. Tsai MC, Lin HK, Lin CH, Fu LS. Prevalence of attention deficit/hyperactivity disorder in pediatric
allergic rhinitis: a nationwide population-based study. Allergy Asthma Proc. 2011; 32(6):41–6. Epub
2012/01/10. doi: 10.2500/aap.2011.32.3489 PMID: 22221429.
34. Tegethoff M, Belardi A, Stalujanis E, Meinlschmidt G. Association between mental disorders and
physical diseases in adolescents from a nationally representative cohort. Psychosom Med. 2015; 77
(3):319–32. doi: 10.1097/PSY.0000000000000151 PMID: 25851547.
35. Tegethoff M, Belardi A, Stalujanis E, Meinlschmidt G. Comorbidity of mental disorders and chronic
pain: chronology of onset in adolescents of a national representative cohort. J Pain. 2015; 16
(10):1054–64. doi: 10.1016/j.jpain.2015.06.009 PMID: 26168877.
36. Bertelsen EN, Larsen JT, Petersen L, Christensen J, Dalsgaard S. Childhood Epilepsy, Febrile Sei-
zures, and Subsequent Risk of ADHD. Pediatrics. 2016; 138(2). doi: 10.1542/peds.2015-4654 PMID:
27412639.
37. Chen MH, Su TP, Chen YS, Hsu JW, Huang KL, Chang WH, et al. Higher risk of developing major
depression and bipolar disorder in later life among adolescents with asthma: a nationwide prospective
study. J Psychiatr Res. 2014; 49:25–30. doi: 10.1016/j.jpsychires.2013.10.015 PMID: 24275549.
38. Hasler G, Gergen PJ, Kleinbaum DG, Ajdacic V, Gamma A, Eich D, et al. Asthma and panic in young
adults: a 20-year prospective community study. Am J Respir Crit Care Med. 2005; 171(11):1224–30.
doi: 10.1164/rccm.200412-1669OC PMID: 15764721; PubMed Central PMCID: PMCPMC2718460.
39. Taylor AW, Price K, Gill TK, Adams R, Pilkington R, Carrangis N, et al. Multimorbidity—not just an
older person’s issue. Results from an Australian biomedical study. BMC Public Health. 2010; 10:718.
Epub 2010/11/26. doi: 10.1186/1471-2458-10-718 PMID: 21092218; PubMed Central PMCID:
PMC3001730.
40. Valderas JM, Starfield B, Sibbald B, Salisbury C, Roland M. Defining comorbidity: implications for
understanding health and health services. Ann Fam Med. 2009; 7(4):357–63. Epub 2009/07/15. doi:
10.1370/afm.983 PMID: 19597174; PubMed Central PMCID: PMC2713155.
41. Demyttenaere K, Bruffaerts R, Lee S, Posada-Villa J, Kovess V, Angermeyer MC, et al. Mental disor-
ders among persons with chronic back or neck pain: results from the World Mental Health Surveys.
Pain. 2007; 129(3):332–42. Epub 2007/03/14. doi: 10.1016/j.pain.2007.01.022 PMID: 17350169.
42. Szigethy E. Psychiatry and Pediatrics: New Necessary Directions to Better Treat Adolescents. J Am
Acad Child Adolesc Psychiatry. 2016; 55(5):357–8. doi: 10.1016/j.jaac.2016.02.011 PMID:
27126848.
43. Kessler RC, Avenevoli S, Costello EJ, Green JG, Gruber MJ, Heeringa S, et al. National comorbidity
survey replication adolescent supplement (NCS-A): II. Overview and design. J Am Acad Child

PLOS ONE | DOI:10.1371/journal.pone.0165196 October 21, 2016 13 / 19

 Mental-Physical Comorbidity: Chronology

Adolesc Psychiatry. 2009; 48(4):380–5. Epub 2009/02/27. doi: 10.1097/CHI.0b013e3181999705

S0890-8567(09)60045-9 [pii]. PMID: 19242381; PubMed Central PMCID: PMC2718678.
44. Kessler RC, Avenevoli S, Costello EJ, Green JG, Gruber MJ, Heeringa S, et al. Design and field pro-
cedures in the US National Comorbidity Survey Replication Adolescent Supplement (NCS-A). Int J
Methods Psychiatr Res. 2009; 18(2):69–83. Epub 2009/06/10. doi: 10.1002/mpr.279 PMID:
19507169; PubMed Central PMCID: PMC2774712.
45. Kessler RC, Merikangas KR. The National Comorbidity Survey Replication (NCS-R): background and
aims. Int J Methods Psychiatr Res. 2004; 13(2):60–8. Epub 2004/08/07. PMID: 15297904.
46. Merikangas K, Avenevoli S, Costello J, Koretz D, Kessler RC. National comorbidity survey replication
adolescent supplement (NCS-A): I. Background and measures. J Am Acad Child Adolesc Psychiatry.
2009; 48(4):367–9. Epub 2009/02/27. doi: 10.1097/CHI.0b013e31819996f1 S0890-8567(09)60044-7
[pii]. PMID: 19242382; PubMed Central PMCID: PMC2736858.
47. Kessler RC, Avenevoli S, Green J, Gruber MJ, Guyer M, He Y, et al. National comorbidity survey rep-
lication adolescent supplement (NCS-A): III. Concordance of DSM-IV/CIDI diagnoses with clinical
reassessments. J Am Acad Child Adolesc Psychiatry. 2009; 48(4):386–99. Epub 2009/03/03. doi: 10.
1097/CHI.0b013e31819a1cbc S0890-8567(09)60046-0 [pii]. PMID: 19252450.
48. Cantwell DP, Lewinsohn PM, Rohde P, Seeley JR. Correspondence between adolescent report and
parent report of psychiatric diagnostic data. J Am Acad Child Adolesc Psychiatry. 1997; 36(5):610–9.
Epub 1997/05/01. doi: 10.1097/00004583-199705000-00011 PMID: 9136495.
49. De Los Reyes A, Kazdin AE. Informant discrepancies in the assessment of childhood psychopathol-
ogy: a critical review, theoretical framework, and recommendations for further study. Psychol Bull.
2005; 131(4):483–509. Epub 2005/08/03. doi: 10.1037/0033-2909.131.4.483 PMID: 16060799.
50. Grills AE, Ollendick TH. Issues in parent-child agreement: the case of structured diagnostic inter-
views. Clin Child Fam Psychol Rev. 2002; 5(1):57–83. Epub 2002/05/08. PMID: 11993545.
51. Schoenborn CA, Adams PF, Schiller JS. Summary health statistics for the U.S. population: National
Health Interview Survey, 2000. Vital Health Stat 10. 2003;(214: ):1–83. Epub 2005/03/25. PMID:
15786609.
52. Buist-Bouwman MA, De Graaf R, Vollebergh WA, Alonso J, Bruffaerts R, Ormel J, et al. Functional
disability of mental disorders and comparison with physical disorders: a study among the general pop-
ulation of six European countries. Acta Psychiatr Scand. 2006; 113(6):492–500. doi: 10.1111/j.1600-
0447.2005.00684.x PMID: 16677226.
53. Merikangas KR, Ames M, Cui L, Stang PE, Ustun TB, Von Korff M, et al. The impact of comorbidity of
mental and physical conditions on role disability in the US adult household population. Arch Gen Psy-
chiatry. 2007; 64(10):1180–8. doi: 10.1001/archpsyc.64.10.1180 PMID: 17909130; PubMed Central
PMCID: PMC2248275.
54. Ormel J, Petukhova M, Chatterji S, Aguilar-Gaxiola S, Alonso J, Angermeyer MC, et al. Disability and
treatment of specific mental and physical disorders across the world. Br J Psychiatry. 2008; 192
(5):368–75. doi: 10.1192/bjp.bp.107.039107 PMID: 18450663; PubMed Central PMCID:
PMC2681238.
55. Lee JJ, Colman RJ, Mitchell PD, Atmadja ML, Bousvaros A, Lightdale JR. Agreement between
patient- and physician-completed Pediatric Ulcerative Colitis Activity Index scores. J Pediatr Gastro-
enterol Nutr. 2011; 52(6):708–13. doi: 10.1097/MPG.0b013e3182099018 PMID: 21593644.
56. Olson LM, Radecki L, Frintner MP, Weiss KB, Korfmacher J, Siegel RM. At what age can children
report dependably on their asthma health status? Pediatrics. 2007; 119(1):e93–102. doi: 10.1542/
peds.2005-3211 PMID: 17200264.
57. Riley AW. Evidence that school-age children can self-report on their health. Ambul Pediatr. 2004; 4(4
Suppl):371–6. doi: 10.1367/A03-178R.1 PMID: 15264962.
58. Baumeister H, Kriston L, Bengel J, Harter M. High agreement of self-report and physician-diagnosed
somatic conditions yields limited bias in examining mental-physical comorbidity. J Clin Epidemiol.
2010; 63(5):558–65. Epub 2009/12/05. S0895-4356(09)00240-6 [pii] doi: 10.1016/j.jclinepi.2009.08.
009 PMID: 19959329.
59. Knight M, Stewart-Brown S, Fletcher L. Estimating health needs: the impact of a checklist of condi-
tions and quality of life measurement on health information derived from community surveys. J Public
Health Med. 2001; 23(3):179–86. Epub 2001/10/05. PMID: 11585189.
60. Willett JB, Singer JD. Discrete-time survival analysis. In: Kaplan D, editor. The SAGE Handbook of
Quantitative Methodology for the Social Sciences. Thousand Oaks, London, New Delhi: Sage Publi-
cations, Inc.; 2004.
61. Kessler RC, Avenevoli S, Costello EJ, Georgiades K, Green JG, Gruber MJ, et al. Prevalence, persis-
tence, and sociodemographic correlates of DSM-IV disorders in the National Comorbidity Survey

PLOS ONE | DOI:10.1371/journal.pone.0165196 October 21, 2016 14 / 19

 Mental-Physical Comorbidity: Chronology

Replication Adolescent Supplement. Arch Gen Psychiatry. 2012; 69(4):372–80. Epub 2011/12/08.
archgenpsychiatry.2011.160 [pii] doi: 10.1001/archgenpsychiatry.2011.160 PMID: 22147808.
62. Merikangas KR, He JP, Burstein M, Swanson SA, Avenevoli S, Cui L, et al. Lifetime prevalence of
mental disorders in U.S. adolescents: results from the National Comorbidity Survey Replication—
Adolescent Supplement (NCS-A). J Am Acad Child Adolesc Psychiatry. 2010; 49(10):980–9. Epub
2010/09/22. doi: 10.1016/j.jaac.2010.05.017 PMID: 20855043; PubMed Central PMCID:
PMC2946114.
63. Kessler RC, Ormel J, Petukhova M, McLaughlin KA, Green JG, Russo LJ, et al. Development of life-
time comorbidity in the World Health Organization world mental health surveys. Arch Gen Psychiatry.
2011; 68(1):90–100. Epub 2011/01/05. 68/1/90 [pii] doi: 10.1001/archgenpsychiatry.2010.180 PMID:
21199968.
64. U.S. Census Bureau. Census 2000 Urban and Rural Classification 2000 [cited June 13, 2014]. Avail-
able from: http://www.census.gov/geo/reference/ua/urban-rural-2000.html.
65. He Y, Zhang M, Lin EH, Bruffaerts R, Posada-Villa J, Angermeyer MC, et al. Mental disorders among
persons with arthritis: results from the World Mental Health Surveys. Psychol Med. 2008; 38
(11):1639–50. Epub 2008/02/27. doi: 10.1017/S0033291707002474 PMID: 18298879; PubMed Cen-
tral PMCID: PMC2736852.
66. Kessler RC, Ormel J, Demler O, Stang PE. Comorbid mental disorders account for the role
impairment of commonly occurring chronic physical disorders: results from the National Comorbidity
Survey. J Occup Environ Med. 2003; 45(12):1257–66. Epub 2003/12/11. doi: 10.1097/01.jom.
0000100000.70011.bb PMID: 14665811.
67. Hemingway H, Marmot M. Evidence based cardiology: psychosocial factors in the aetiology and prog-
nosis of coronary heart disease. Systematic review of prospective cohort studies. Bmj. 1999; 318
(7196):1460–7. Epub 1999/05/27. PMID: 10346775; PubMed Central PMCID: PMC1115843.
68. Picardi A, Pasquini P. Toward a biopsychosocial approach to skin diseases. Adv Psychosom Med.
2007; 28:109–26. Epub 2007/08/09. doi: 10.1159/0000106800 PMID: 17684322.
69. Ormel J, Von Korff M, Burger H, Scott K, Demyttenaere K, Huang YQ, et al. Mental disorders among
persons with heart disease—results from World Mental Health surveys. Gen Hosp Psychiatry. 2007;
29(4):325–34. Epub 2007/06/27. doi: 10.1016/j.genhosppsych.2007.03.009 PMID: 17591509;
PubMed Central PMCID: PMC2048744.
70. Rodic D, Meyer AH, Meinlschmidt G. The association between depressive symptoms and physical
diseases in Switzerland: a cross-sectional general population study. Front Public Health. 2015; 3:47.
doi: 10.3389/fpubh.2015.00047 PMID: 25853116; PubMed Central PMCID: PMC4370044.
71. Patten SB, Williams JV. Self-reported allergies and their relationship to several Axis I disorders in a
community sample. Int J Psychiatry Med. 2007; 37(1):11–22. Epub 2007/07/25. PMID: 17645194.
72. Lin EH, Katon W, Von Korff M, Tang L, Williams JW Jr., Kroenke K, et al. Effect of improving depres-
sion care on pain and functional outcomes among older adults with arthritis: a randomized controlled
trial. JAMA. 2003; 290(18):2428–9. Epub 2003/11/13. doi: 10.1001/jama.290.18.2428 PMID:
14612479.
73. Linnet J, Jemec GB. Anxiety level and severity of skin condition predicts outcome of psychotherapy in
atopic dermatitis patients. Int J Dermatol. 2001; 40(10):632–6. Epub 2001/12/12. PMID: 11737422.
74. Ehlers A, Stangier U, Gieler U. Treatment of atopic dermatitis: a comparison of psychological and der-
matological approaches to relapse prevention. J Consult Clin Psychol. 1995; 63(4):624–35. Epub
1995/08/01. PMID: 7673540.
75. Trummer M, Eustacchio S, Unger F, Tillich M, Flaschka G. Right hemispheric frontal lesions as a
cause for anorexia nervosa report of three cases. Acta Neurochir (Wien). 2002; 144(8):797–801; dis-
cussion Epub 2002/08/16. doi: 10.1007/s00701-002-0934-5 PMID: 12181689.
76. Levine R, Lipson S, Devinsky O. Resolution of eating disorders after right temporal lesions. Epilepsy
Behav. 2003; 4(6):781–3. Epub 2003/12/31. PMID: 14698720.
77. McElroy SL, Guerdjikova AI, Martens B, Keck PE Jr., Pope HG, Hudson JI. Role of antiepileptic drugs
in the management of eating disorders. CNS Drugs. 2009; 23(2):139–56. Epub 2009/01/29. doi: 10.
2165/00023210-200923020-00004 PMID: 19173373.
78. Levenstein S, Kaplan GA, Smith MW. Psychological predictors of peptic ulcer incidence in the Ala-
meda County Study. J Clin Gastroenterol. 1997; 24(3):140–6. Epub 1997/04/01. PMID: 9179731.
79. Mardini HE, Kip KE, Wilson JW. Crohn’s disease: a two-year prospective study of the association
between psychological distress and disease activity. Dig Dis Sci. 2004; 49(3):492–7. Epub 2004/05/
14. PMID: 15139504.

PLOS ONE | DOI:10.1371/journal.pone.0165196 October 21, 2016 15 / 19

 Mental-Physical Comorbidity: Chronology

80. Roest AM, Martens EJ, de Jonge P, Denollet J. Anxiety and risk of incident coronary heart disease: a
meta-analysis. J Am Coll Cardiol. 2010; 56(1):38–46. Epub 2010/07/14. doi: 10.1016/j.jacc.2010.03.
034 PMID: 20620715.
81. Thurston RC, Rewak M, Kubzansky LD. An anxious heart: anxiety and the onset of cardiovascular
diseases. Prog Cardiovasc Dis. 2013; 55(6):524–37. Epub 2013/04/30. doi: 10.1016/j.pcad.2013.03.
007 PMID: 23621962.
82. Lane D, Carroll D, Ring C, Beevers DG, Lip GY. The prevalence and persistence of depression and
anxiety following myocardial infarction. Br J Health Psychol. 2002; 7(Pt 1):11–21. Epub 2003/11/05.
doi: 10.1348/135910702169321 PMID: 14596714.
83. Bjerkeset O, Nordahl HM, Mykletun A, Holmen J, Dahl AA. Anxiety and depression following myocar-
dial infarction: gender differences in a 5-year prospective study. J Psychosom Res. 2005; 58(2):153–
61. Epub 2005/04/12. doi: 10.1016/j.jpsychores.2004.07.011 PMID: 15820843.
84. Hanssen TA, Nordrehaug JE, Eide GE, Bjelland I, Rokne B. Anxiety and depression after acute myo-
cardial infarction: an 18-month follow-up study with repeated measures and comparison with a refer-
ence population. Eur J Cardiovasc Prev Rehabil. 2009; 16(6):651–9. Epub 2009/08/27. doi: 10.1097/
HJR.0b013e32832e4206 PMID: 19707149.
85. Goodwin RD, Galea S, Perzanowski M, Jacobi F. Impact of allergy treatment on the association
between allergies and mood and anxiety in a population sample. Clin Exp Allergy. 2012; 42
(12):1765–71. Epub 2012/11/28. doi: 10.1111/j.1365-2222.2012.04042.x PMID: 23181792.
86. Cohen S, Rodriquez MS. Pathways linking affective disturbances and physical disorders. Health Psy-
chol. 1995; 14(5):374–80. Epub 1995/09/01. PMID: 7498107.
87. Fields HL. Pain modulation: expectation, opioid analgesia and virtual pain. Prog Brain Res. 2000;
122:245–53. Epub 2000/03/29. PMID: 10737063.
88. Lynch ME. Antidepressants as analgesics: a review of randomized controlled trials. J Psychiatry Neu-
rosci. 2001; 26(1):30–6. Epub 2001/02/24. PMID: 11212591; PubMed Central PMCID:
PMC1408040.
89. Choy EH, Panayi GS. Cytokine pathways and joint inflammation in rheumatoid arthritis. N Engl J
Med. 2001; 344(12):907–16. Epub 2001/03/22. doi: 10.1056/NEJM200103223441207 PMID:
11259725.
90. Straub RH, Cutolo M. Involvement of the hypothalamic—pituitary—adrenal/gonadal axis and the
peripheral nervous system in rheumatoid arthritis: viewpoint based on a systemic pathogenetic role.
Arthritis Rheum. 2001; 44(3):493–507. Epub 2001/03/27. doi: 10.1002/1529-0131(200103)
44:3<493::AID-ANR95>3.0.CO;2-U PMID: 11263762.
91. Raedler TJ. Inflammatory mechanisms in major depressive disorder. Curr Opin Psychiatry. 2011; 24
(6):519–25. Epub 2011/09/08. doi: 10.1097/YCO.0b013e32834b9db6 PMID: 21897249.
92. Pariante CM, Lightman SL. The HPA axis in major depression: classical theories and new develop-
ments. Trends Neurosci. 2008; 31(9):464–8. Epub 2008/08/05. doi: 10.1016/j.tins.2008.06.006
PMID: 18675469.
93. Tache Y, Martinez V, Wang L, Million M. CRF1 receptor signaling pathways are involved in stress-
related alterations of colonic function and viscerosensitivity: implications for irritable bowel syndrome.
Br J Pharmacol. 2004; 141(8):1321–30. Epub 2004/04/22. doi: 10.1038/sj.bjp.0705760 PMID:
15100165; PubMed Central PMCID: PMC1574904.
94. Konturek PC, Brzozowski T, Konturek SJ. Stress and the gut: pathophysiology, clinical conse-
quences, diagnostic approach and treatment options. J Physiol Pharmacol. 2011; 62(6):591–9. Epub
2012/02/09. PMID: 22314561.
95. Gareau MG, Silva MA, Perdue MH. Pathophysiological mechanisms of stress-induced intestinal dam-
age. Curr Mol Med. 2008; 8(4):274–81. Epub 2008/06/10. PMID: 18537635.
96. Buske-Kirschbaum A, Geiben A, Hellhammer D. Psychobiological aspects of atopic dermatitis: an
overview. Psychother Psychosom. 2001; 70(1):6–16. Epub 2001/01/11. 56219. PMID: 11150933.
doi: 56219
97. Glaser R, Kiecolt-Glaser JK. Stress-induced immune dysfunction: implications for health. Nat Rev
Immunol. 2005; 5(3):243–51. Epub 2005/03/02. doi: 10.1038/nri1571 PMID: 15738954.
98. Wright RJ, Finn P, Contreras JP, Cohen S, Wright RO, Staudenmayer J, et al. Chronic caregiver
stress and IgE expression, allergen-induced proliferation, and cytokine profiles in a birth cohort pre-
disposed to atopy. J Allergy Clin Immunol. 2004; 113(6):1051–7. Epub 2004/06/23. doi: 10.1016/j.
jaci.2004.03.032 PMID: 15208584.
99. Hou R, Baldwin DS. A neuroimmunological perspective on anxiety disorders. Hum Psychopharmacol.
2012; 27(1):6–14. Epub 2012/01/04. doi: 10.1002/hup.1259 PMID: 22213434.

PLOS ONE | DOI:10.1371/journal.pone.0165196 October 21, 2016 16 / 19

 Mental-Physical Comorbidity: Chronology

100. Hashizume H, Horibe T, Ohshima A, Ito T, Yagi H, Takigawa M. Anxiety accelerates T-helper 2-tilted
immune responses in patients with atopic dermatitis. Br J Dermatol. 2005; 152(6):1161–4. Epub
2005/06/14. doi: 10.1111/j.1365-2133.2005.06449.x PMID: 15948976.
101. Romeo J, Warnberg J, Nova E, Diaz LE, Gomez-Martinez S, Marcos A. Moderate alcohol consump-
tion and the immune system: a review. Br J Nutr. 2007; 98 Suppl 1:S111–5. Epub 2007/11/21. doi:
10.1017/S0007114507838049 PMID: 17922947.
102. Beulens JW, Rimm EB, Ascherio A, Spiegelman D, Hendriks HF, Mukamal KJ. Alcohol consumption
and risk for coronary heart disease among men with hypertension. Ann Intern Med. 2007; 146(1):10–
9. Epub 2007/01/04. PMID: 17200217.
103. Kallberg H, Jacobsen S, Bengtsson C, Pedersen M, Padyukov L, Garred P, et al. Alcohol consump-
tion is associated with decreased risk of rheumatoid arthritis: results from two Scandinavian case-
control studies. Ann Rheum Dis. 2009; 68(2):222–7. Epub 2008/06/07. doi: 10.1136/ard.2007.
086314 PMID: 18535114; PubMed Central PMCID: PMC2937278.
104. Room R, Babor T, Rehm J. Alcohol and public health. Lancet. 2005; 365(9458):519–30. Epub 2005/
02/12. doi: 10.1016/S0140-6736(05)17870-2 PMID: 15705462.
105. Bouton ME, Mineka S, Barlow DH. A modern learning theory perspective on the etiology of panic dis-
order. Psychol Rev. 2001; 108(1):4–32. Epub 2001/02/24. PMID: 11212632.
106. Rietveld S, Karsdorp PA, Mulder BJ. Heartbeat sensitivity in adults with congenital heart disease. Int
J Behav Med. 2004; 11(4):203–11. Epub 2005/01/20. doi: 10.1207/s15327558ijbm1104_3 PMID:
15657020.
107. Domschke K, Stevens S, Pfleiderer B, Gerlach AL. Interoceptive sensitivity in anxiety and anxiety dis-
orders: an overview and integration of neurobiological findings. Clin Psychol Rev. 2010; 30(1):1–11.
Epub 2009/09/16. doi: 10.1016/j.cpr.2009.08.008 PMID: 19751958.
108. Holopainen IE. Seizures in the developing brain: cellular and molecular mechanisms of neuronal
damage, neurogenesis and cellular reorganization. Neurochem Int. 2008; 52(6):935–47. Epub 2007/
12/21. doi: 10.1016/j.neuint.2007.10.021 PMID: 18093696.
109. Uher R, Treasure J. Brain lesions and eating disorders. J Neurol Neurosurg Psychiatry. 2005; 76
(6):852–7. Epub 2005/05/18. doi: 10.1136/jnnp.2004.048819 PMID: 15897510; PubMed Central
PMCID: PMC1739667.
110. Tecott LH, Sun LM, Akana SF, Strack AM, Lowenstein DH, Dallman MF, et al. Eating disorder and
epilepsy in mice lacking 5-HT2c serotonin receptors. Nature. 1995; 374(6522):542–6. Epub 1995/04/
06. doi: 10.1038/374542a0 PMID: 7700379.
111. Kessler RC, Avenevoli S, McLaughlin KA, Green JG, Lakoma MD, Petukhova M, et al. Lifetime co-
morbidity of DSM-IV disorders in the US National Comorbidity Survey Replication Adolescent Supple-
ment (NCS-A). Psychol Med. 2012; 42(9):1997–2010. Epub 2012/01/26. doi: 10.1017/
S0033291712000025 PMID: 22273480; PubMed Central PMCID: PMC3448706.
112. Knäuper B, Cannell CF, Schwarz N, Bruce ML, Kessler RC. Improving accuracy of major depression
age-of-onset reports in the US National Comorbidity Survey. Int J Methods Psychiatr Res. 1999; 8
(1):39–48.
113. Kessler RC, Berglund P, Demler O, Jin R, Merikangas KR, Walters EE. Lifetime prevalence and age-
of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Arch Gen
Psychiatry. 2005; 62(6):593–602. doi: 10.1001/archpsyc.62.6.593 PMID: 15939837.
114. Simon GE, VonKorff M. Recall of psychiatric history in cross-sectional surveys: implications for epide-
miologic research. Epidemiol Rev. 1995; 17(1):221–7. PMID: 8521941.
115. Costello EJ, Egger H, Angold A. 10-year research update review: the epidemiology of child and ado-
lescent psychiatric disorders: I. Methods and public health burden. J Am Acad Child Adolesc Psychia-
try. 2005; 44(10):972–86. Epub 2005/09/22. S0890-8567(09)61759-7 [pii] doi: 10.1097/01.chi.
0000172552.41596.6f PMID: 16175102.
116. Costello EJ, Mustillo S, Erkanli A, Keeler G, Angold A. Prevalence and development of psychiatric
disorders in childhood and adolescence. Arch Gen Psychiatry. 2003; 60(8):837–44. doi: 10.1001/
archpsyc.60.8.837 PMID: 12912767.
117. Lewinsohn PM, Striegel-Moore RH, Seeley JR. Epidemiology and natural course of eating disorders
in young women from adolescence to young adulthood. J Am Acad Child Adolesc Psychiatry. 2000;
39(10):1284–92. doi: 10.1097/00004583-200010000-00016 PMID: 11026183.
118. Merikangas KR, Nakamura EF, Kessler RC. Epidemiology of mental disorders in children and adoles-
cents. Dialogues Clin Neurosci. 2009; 11(1):7–20. PMID: 19432384; PubMed Central PMCID:
PMC2807642.

PLOS ONE | DOI:10.1371/journal.pone.0165196 October 21, 2016 17 / 19

 Mental-Physical Comorbidity: Chronology

119. Anandan C, Nurmatov U, van Schayck OC, Sheikh A. Is the prevalence of asthma declining? System-
atic review of epidemiological studies. Allergy. 2010; 65(2):152–67. doi: 10.1111/j.1398-9995.2009.
02244.x PMID: 19912154.
120. Duncan GE. Prevalence of diabetes and impaired fasting glucose levels among US adolescents:
National Health and Nutrition Examination Survey, 1999–2002. Arch Pediatr Adolesc Med. 2006; 160
(5):523–8. doi: 10.1001/archpedi.160.5.523 PMID: 16651496.
121. Forsgren L, Beghi E, Oun A, Sillanpaa M. The epidemiology of epilepsy in Europe—a systematic
review. Eur J Neurol. 2005; 12(4):245–53. doi: 10.1111/j.1468-1331.2004.00992.x PMID: 15804240.
122. Mortz CG, Lauritsen JM, Bindslev-Jensen C, Andersen KE. Prevalence of atopic dermatitis, asthma,
allergic rhinitis, and hand and contact dermatitis in adolescents. The Odense Adolescence Cohort
Study on Atopic Diseases and Dermatitis. Br J Dermatol. 2001; 144(3):523–32. PMID: 11260009.
123. Newacheck PW, Taylor WR. Childhood chronic illness: prevalence, severity, and impact. Am J Public
Health. 1992; 82(3):364–71. Epub 1992/03/01. PMID: 1536351; PubMed Central PMCID:
PMC1694379.
124. Costello EJ, Erkanli A, Federman E, Angold A. Development of psychiatric comorbidity with sub-
stance abuse in adolescents: effects of timing and sex. J Clin Child Psychol. 1999; 28(3):298–311.
doi: 10.1207/S15374424jccp280302 PMID: 10446679.
125. Hudson JI, Hiripi E, Pope HG Jr., Kessler RC. The prevalence and correlates of eating disorders in
the National Comorbidity Survey Replication. Biol Psychiatry. 2007; 61(3):348–58. doi: 10.1016/j.
biopsych.2006.03.040 PMID: 16815322; PubMed Central PMCID: PMC1892232.
126. Kessler RC, Amminger GP, Aguilar-Gaxiola S, Alonso J, Lee S, Ustun TB. Age of onset of mental dis-
orders: a review of recent literature. Curr Opin Psychiatry. 2007; 20(4):359–64. doi: 10.1097/YCO.
0b013e32816ebc8c PMID: 17551351; PubMed Central PMCID: PMC1925038.
127. Lewinsohn PM, Rohde P, Seeley JR. Major depressive disorder in older adolescents: prevalence,
risk factors, and clinical implications. Clin Psychol Rev. 1998; 18(7):765–94. PMID: 9827321.
128. Fagot-Campagna A, Pettitt DJ, Engelgau MM, Burrows NR, Geiss LS, Valdez R, et al. Type 2 diabe-
tes among North American children and adolescents: an epidemiologic review and a public health
perspective. J Pediatr. 2000; 136(5):664–72. PMID: 10802501.
129. Gollnick HP, Finlay AY, Shear N, Global Alliance to Improve Outcomes in A. Can we define acne as a
chronic disease? If so, how and when? Am J Clin Dermatol. 2008; 9(5):279–84. PMID: 18717602.
130. Hermann B, Seidenberg M, Bell B, Rutecki P, Sheth R, Ruggles K, et al. The neurodevelopmental
impact of childhood-onset temporal lobe epilepsy on brain structure and function. Epilepsia. 2002; 43
(9):1062–71. PMID: 12199732.
131. Lindberg E, Lindquist B, Holmquist L, Hildebrand H. Inflammatory bowel disease in children and ado-
lescents in Sweden, 1984–1995. J Pediatr Gastroenterol Nutr. 2000; 30(3):259–64. PMID:
10749408.
132. Ravelli A, Martini A. Juvenile idiopathic arthritis. Lancet. 2007; 369(9563):767–78. doi: 10.1016/
S0140-6736(07)60363-8 PMID: 17336654.
133. Skoner DP. Allergic rhinitis: definition, epidemiology, pathophysiology, detection, and diagnosis. J
Allergy Clin Immunol. 2001; 108(1 Suppl):S2–8. PMID: 11449200.
134. Yunginger JW, Reed CE, O’Connell EJ, Melton LJ, 3rd, O’Fallon WM, Silverstein MD. A community-
based study of the epidemiology of asthma. Incidence rates, 1964–1983. Am Rev Respir Dis. 1992;
146(4):888–94. doi: 10.1164/ajrccm/146.4.888 PMID: 1416415.
135. Kraemer HC, Kazdin AE, Offord DR, Kessler RC, Jensen PS, Kupfer DJ. Coming to terms with the
terms of risk. Arch Gen Psychiatry. 1997; 54(4):337–43. Epub 1997/04/01. PMID: 9107150.
136. Hill AB. The Environment and Disease: Association or Causation? Proc R Soc Med. 1965; 58:295–
300. Epub 1965/05/01. PMID: 14283879; PubMed Central PMCID: PMC1898525.
137. Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B. Epidemiology of multimorbidity and
implications for health care, research, and medical education: a cross-sectional study. Lancet. 2012;
380(9836):37–43. Epub 2012/05/15. doi: 10.1016/S0140-6736(12)60240-2 PMID: 22579043.
138. Guthrie B, Saultz JW, Freeman GK, Haggerty JL. Continuity of care matters. Bmj. 2008; 337:a867.
Epub 2008/08/09. doi: 10.1136/bmj.a867 PMID: 18687724.
139. Pizzi C, Rutjes AW, Costa GM, Fontana F, Mezzetti A, Manzoli L. Meta-analysis of selective serotonin
reuptake inhibitors in patients with depression and coronary heart disease. Am J Cardiol. 2011; 107
(7):972–9. Epub 2011/01/25. doi: 10.1016/j.amjcard.2010.11.017 PMID: 21256471.
140. Alamanos Y, Drosos AA. Epidemiology of adult rheumatoid arthritis. Autoimmun Rev. 2005; 4
(3):130–6. doi: 10.1016/j.autrev.2004.09.002 PMID: 15823498.

PLOS ONE | DOI:10.1371/journal.pone.0165196 October 21, 2016 18 / 19

 Mental-Physical Comorbidity: Chronology

141. Berry JD, Dyer A, Cai X, Garside DB, Ning H, Thomas A, et al. Lifetime risks of cardiovascular dis-
ease. N Engl J Med. 2012; 366(4):321–9. doi: 10.1056/NEJMoa1012848 PMID: 22276822; PubMed
Central PMCID: PMCPMC3336876.
142. Hillier TA, Pedula KL. Characteristics of an adult population with newly diagnosed type 2 diabetes:
the relation of obesity and age of onset. Diabetes Care. 2001; 24(9):1522–7. PMID: 11522693.
143. Boyd CM, Darer J, Boult C, Fried LP, Boult L, Wu AW. Clinical practice guidelines and quality of care
for older patients with multiple comorbid diseases: implications for pay for performance. JAMA. 2005;
294(6):716–24. Epub 2005/08/11. doi: 10.1001/jama.294.6.716 PMID: 16091574.

PLOS ONE | DOI:10.1371/journal.pone.0165196 October 21, 2016 19 / 19

Reproduced with permission of the copyright owner. Further reproduction prohibited without
permission.