It is clear that mental disorders in treatment settings are associated with a higher incidence of chronic physical conditions, but whether this is true of mental disorders in the community, and how generalized (across a range of physical health outcomes) these associations are, is less clear. This information has important implications for mental health care and the primary prevention of chronic physical disease.
To investigate associations of 16 temporally prior DSM-IV mental disorders with the subsequent onset or diagnosis of 10 chronic physical conditions.
Design, Setting, and Participants
Eighteen face-to-face, cross-sectional household surveys of community-dwelling adults were conducted in 17 countries (47 609 individuals; 2 032 942 person-years) from January 1, 2001, to December 31, 2011. The Composite International Diagnostic Interview was used to retrospectively assess the lifetime prevalence and age at onset of DSM-IV–identified mental disorders. Data analysis was performed from January 3, 2012, to September 30, 2015.
Main Outcomes and Measures
Lifetime history of physical conditions was ascertained via self-report of physician’s diagnosis and year of onset or diagnosis. Survival analyses estimated the associations of temporally prior first onset of mental disorders with subsequent onset or diagnosis of physical conditions.
Most associations between 16 mental disorders and subsequent onset or diagnosis of 10 physical conditions were statistically significant, with odds ratios (ORs) (95% CIs) ranging from 1.2 (1.0-1.5) to 3.6 (2.0-6.6). The associations were attenuated after adjustment for mental disorder comorbidity, but mood, anxiety, substance use, and impulse control disorders remained significantly associated with onset of between 7 and all 10 of the physical conditions (ORs [95% CIs] from 1.2 [1.1-1.3] to 2.0 [1.4-2.8]). An increasing number of mental disorders experienced over the life course was significantly associated with increasing odds of onset or diagnosis of all 10 types of physical conditions, with ORs (95% CIs) for 1 mental disorder ranging from 1.3 (1.1-1.6) to 1.8 (1.4-2.2) and ORs (95% CIs) for 5 or more mental disorders ranging from 1.9 (1.4-2.7) to 4.0 (2.5-6.5). In population-attributable risk estimates, specific mental disorders were associated with 1.5% to 13.3% of physical condition onsets.
Conclusions and Relevance
These findings suggest that mental disorders of all kinds are associated with an increased risk of onset of a wide range of chronic physical conditions. Current efforts to improve the physical health of individuals with mental disorders may be too narrowly focused on the small group with the most severe mental disorders. Interventions aimed at the primary prevention of chronic physical diseases should optimally be integrated into treatment of all mental disorders in primary and secondary care from early in the disorder course.
Much evidence has accrued from record linkage and clinical studies attesting to the higher incidence of chronic physical conditions and associated earlier mortality among individuals with severe mental illness,1-3 as well as among those with common mental disorders.4-7 However, the findings of these studies are limited to those who receive treatment,1 so it is less clear whether mental disorders in the community (untreated and treated) might be linked with subsequent risk of chronic physical conditions. It also remains unclear as to how generalized these associations might be across a range of physical health outcomes. This information has important implications for mental health care and the primary prevention of chronic physical disease.
Ideally, associations between mental disorders in the general population and subsequent physical conditions should be investigated in studies with prospective designs. However, to examine associations between a wide range of mental disorders and physical conditions prospectively is challenging because it requires very large cohorts with information on both mental and physical disorders to be followed over many decades. As an interim approach, we have investigated mental-physical sequential associations using retrospectively collected data from the World Mental Health (WMH) surveys. The collection of information on age at onset of mental disorders and age at onset or diagnosis of chronic physical conditions in these surveys allows the use of survival analysis to examine predictive associations between temporally prior mental disorders and the subsequent onset or diagnosis of physical conditions. Previous publications have reported on associations between mental disorders and specific physical conditions.8-12 The present study provides a broader overview by describing associations between mental disorders and a wide range of physical condition outcomes collectively. It is from this broader perspective that important clinical and public health implications emerge.
This study used all WMH surveys with the requisite data conducted in 17 countries (Table 1). Translation protocols and measures taken to ensure data accuracy, cross-national consistency, and protection of respondents are described in detail elsewhere.14 All respondents provided written informed consent, and the study was approved by the institutional review boards in each country; there was no financial compensation.14 The study was conducted from January 1, 2001, to December 31, 2011.
A stratified, multistage, clustered-area, probability-sampling strategy was used to select adult respondents (≥18 years) in most WMH countries. Most of the surveys were based on nationally representative household samples; Colombia, Mexico, and Shenzhen were based on nationally representative household samples in urbanized areas. In most countries, internal subsampling was used to reduce respondent burden by dividing the interview into 2 parts. All respondents completed part 1, which included the core diagnostic assessment of most mental disorders. All part 1 respondents who met lifetime criteria for any mental disorder and a probability sample of respondents without mental disorders were given part 2 of the instrument (at the same interview), which assessed the remaining mental disorders and collected information on physical conditions and covariates. Data acquired from the part 2 respondents were weighted by the inverse of their probability of selection to adjust for differential sampling.14
Analyses in this article are based on the weighted part 2 subsample (47 609 individuals; 2 032 942 person-years). Additional weighting was used to adjust for differential probabilities of selection within households, to adjust for nonresponse, and to match the samples to population sociodemographic distributions.
All surveys used the WMH-Composite International Diagnostic Interview (CIDI, 3.014), a fully structured interview, to assess lifetime history of mental disorders. Disorders were evaluated using the definitions and criteria of the DSM-IV. Age-at-onset reports (obtained in connection with the first onset of clusters of symptoms indicative of the disorder) were obtained using a probing strategy that experimental research15 has shown yields responses with a more plausible age-at-onset distribution than the standard CIDI questionnaire. Clinical reappraisal interviews using the Structured Clinical Interview for DSM Disorders (SCID) in several WMH countries documented generally good CIDI-SCID concordance, with the CIDI being conservative compared with the SCID for lifetime estimates.16
Chronic Physical Conditions
Respondents were asked whether a health professional had ever told them they had any of a series of medical conditions (eg, heart disease, stroke, cancer, diabetes mellitus, hypertension, asthma, other chronic lung disease, and peptic ulcer) or whether they had a lifetime history of a chronic symptomatic condition (eg, arthritis, chronic back or neck pain, chronic or severe headaches, and any other chronic pain). Respondents were asked how old they were when the condition was first diagnosed (for the medical conditions) or first experienced the condition (for the symptomatic conditions). This year is referred to herein as the age at onset of these conditions, although it is recognized that the underlying disease process of many of these conditions usually develops over many years. For all but 2 of these conditions (chronic pain and ulcer), people with childhood onset (aged <21 years) of the physical condition were excluded from analyses because early onset of these conditions is likely to be congenital.
Data analysis was performed from January 3, 2012, to September 30, 2015. Discrete-time survival analyses17 with person-year as the unit of analysis were used to investigate associations between temporally prior lifetime history of a mental disorder and the subsequent onset of a physical condition. Separate models were estimated for each physical condition. Initial models included each of the 16 mental disorders as predictors, but given the similarity in the pattern of findings across mental disorders, mental disorder classes (any mood disorder, anxiety disorder, substance use disorder, and impulse control disorder) were included as predictors in subsequent models. For these analyses, a person-year data set was created with each year in the life of each respondent treated as a separate observational record up to and including the age at onset of the physical condition or their age at interview (whichever came first), with the year of physical condition onset coded as 1 and earlier years coded as 0 on a dichotomous outcome variable. Mental disorders were coded as 1 from the year after first onset of each mental disorder. This time lag ensured that first onsets of a mental disorder in the same year as the physical condition did not count as a predictor. Only person-years up to the diagnosis or onset of the physical condition were analyzed so that only mental disorder episodes occurring before the onset of the physical condition were included in the predictor set. Survival coefficients are presented as odds ratios (ORs), indicating the relative odds of the physical condition onset for a person with the mental disorder compared with people without that disorder (including those without a history of any mental disorder).
A series of bivariate and multivariate models were developed, including the predictor mental disorder (or disorder class), plus covariates. Covariates included in the statistical models were age cohorts (18-29, 30-44, 45-59, and ≥60 years), sex, person-years, country, educational level (low, low-average, high-average, and high based on the number of years of education), and smoking history (current, ever, or never). Multivariate models included controls for other mental disorders and also investigated associations between the number of mental disorders experienced over the life course and the onset of the physical condition.
Evaluation of whether associations varied by age at physical condition onset or diagnosis was undertaken by including interaction terms between person-years (coded as a continuous variable) and mental disorder classes in the multivariate models. Population-attributable risk proportions (PARPs) calculated the proportion of the outcome variables associated with the predictor mental disorders in the bivariate models (eTable 1 in the Supplement reports the method). Country variation in the associations was evaluated in 2 ways. First, the I2 level was calculated to describe the percentage of total variation in multivariate associations across countries that is due to heterogeneity rather than chance.18 For most models, significant (P < .05) heterogeneity was not observed (eTable 2 in the Supplement), but 2 examples of where country variation was significant (in the associations of mood and anxiety disorders with heart disease) are shown in funnel plots in eFigure 1 and eFigure 2 in the Supplement. Second, interaction terms of mental disorders with individual countries were included in the multivariate models; most of the interaction coefficients were not significant (eTable 3 in the Supplement). All further analyses were conducted on the pooled all-countries data set. Because the WMH data are both clustered and weighted, the design-based Taylor series linearization19 implemented in version 10 of the SUDAAN software system was used to estimate SEs and evaluate the statistical significance of coefficients.
Bivariate Associations of Specific Mental Disorders
After adjustment for age, sex, country, smoking, and educational level, a history of depressive disorder was associated with an increased odds of subsequent onset of arthritis (OR, 1.6; 95% CI, 1.5-1.8) (Table 2). Most associations between the 16 mental disorders and the subsequent onset/diagnosis of the 10 physical conditions were statistically significant. Depression, some of the anxiety disorders (panic disorder, specific phobia, and posttraumatic stress disorder), and alcohol abuse were associated with all 10 physical conditions; bipolar disorder, social phobia, intermittent explosive disorder, and alcohol dependence were associated with 9 of 10 physical conditions. Significant associations ranged from a low OR of 1.2 (95% CI, 1.0-1.5) between depression and subsequent cancer to a high OR of 3.6 (95% CI, 2.0-6.6) between bulimia nervosa and subsequent diabetes mellitus, with the ORs for most associations falling between 1.5 and 2.0.
Bivariate and Multivariate Associations of Mental Disorder Classes
The bivariate models reported in Table 3 include the same controls as the models in Table 2 to allow comparison with the results for individual disorders. All mental disorder classes were associated with all of the physical condition outcomes, with ORs ranging from 1.2 to 2.6. The single physical condition most strongly associated with temporally prior mental disorders was chronic lung disease, with ORs (95% CIs) ranging from 1.7 (1.3-2.3) (anxiety disorder) to 2.6 (1.7-3.8) (impulse control disorder). Cancer had the weakest associations with mental disorders, with ORs (95% CIs) from 1.2 (1.0-1.4) for anxiety disorder to 1.6 (1.2-2.1) for impulse control disorder. Mental disorder comorbidity was not taken into account in these associations.
Analysis using multivariate models demonstrated associations from models adjusting for mental disorder comorbidity, with the effect that the magnitude of associations was reduced by approximately 50%. This finding indicates that some of the strength of the bivariate associations was the result of the multiple disorders that many individuals experience over the life course rather than to one disorder. The multivariate ORs (95% CIs) ranged from 1.2 (1.0-1.4) for the association of mood disorder with subsequent heart disease and 1.2 (1.1-1.3) for the association of substance use disorder with subsequent chronic pain to 2.0 (1.4-2.8) for the association of substance use disorders with subsequent stroke. Substance use disorders remained significantly associated with all 10 of the physical condition outcomes, mood disorders remained associated with 8 of the physical condition outcomes, and anxiety disorders and impulse control disorders remained associated with 7 outcomes. Mood and anxiety disorders were no longer significantly associated with cancer after comorbidity adjustment.
Associations between an increasing number of mental disorders experienced over the life course and subsequent onset or diagnosis of chronic physical conditions were demonstrated (Table 3). Associations (ORs [95% CI]) for 1 mental disorder ranged from lows of 1.3 (1.0-1.5; 1.1-1.6) for cancer and asthma, respectively, to highs of 1.8 (1.7-1.9; 1.4-2.2) for chronic pain and chronic lung disease, respectively. Associations (ORs [95% CI]) with 5 or more disorders ranged from 1.9 (1.4-2.7) with cancer to 4.0 (2.5-6.5) with chronic lung disease. For all physical conditions (except cancer), a dose-response pattern was evident; even for cancer, the association (OR; 95% CI) with 5 or more disorders was stronger (1.9; 1.4-2.7) than the association with 1 disorder (1.3; 1.0-1.5).
Variation of Associations by Age at Physical Condition Onset or Diagnosis
For mood disorders (eTable 4 in the Supplement), the ORs for the mood disorder × person-year interactions were all less than 1.0, with 8 of 10 of the ORs being significant. This finding indicates that the association between mood disorder and the physical condition outcomes was stronger among people with younger (relative to older) age at onset or diagnosis of the physical condition. This finding could be a substantive effect (such that the potential for mental health to affect physical health diminishes as the deleterious effects of aging increase) or an artifact of survival bias in these samples. This same pattern was evident for a few of the physical outcomes in associations with the other 3 classes of mental disorders.
We calculated population-level associations of mental disorders (unadjusted for comorbidity) with physical outcomes. Mood disorders were predictors of 3.0% to 13.3% of physical condition onsets, with corresponding ranges of 3.2% to 11.6% for anxiety disorders, 1.5% to 4.6% for impulse control disorders, and 2.2% to 10.7% for substance use disorders (Table 4). The variation in magnitude of these PARPs reflects, in part, the variation in the prevalence of mental disorders (highest for anxiety disorders and lowest for impulse control disorders).
This investigation of mental-physical sequential associations in multiple countries yielded 4 main findings. First, most of the matrix of possible associations between 16 mental disorders and subsequent onset or diagnosis of 10 physical conditions were statistically significant after controlling for covariates. Second, associations were reduced in magnitude after controlling for mental disorder comorbidity, but all mental disorder classes (mood, anxiety, impulse control, and substance use) remained associated with between 7 and 10 of the physical condition outcomes. Third, increasing numbers of mental disorders experienced over the life course were associated with increasing odds of subsequent onset or diagnosis of all 10 physical conditions. Fourth, specific mental disorders were associated with between 1.5% and 13.3% of chronic physical condition onsets. To put the PARPS in context, high body mass index, which has similarities to mental disorders in being a prevalent risk factor associated with multiple outcomes, is associated with 13% to 15% of cardiometabolic deaths.20 The PARPs in the present study were modest, but they were based on specific types of mental disorders in the general population, including both remitted and unremitted disorders, and so may substantially underestimate the effect of the more severe and comorbid disorders typically seen in treatment settings.
The study design limitations need to be considered. Retrospective recall of age at onset of mental disorders is subject to bias, and, although the probing strategy used in the WMH surveys has been shown to reduce some types of bias (telescoping), it is likely that some inaccuracy in onset timing remains. Recall of age at onset of physical conditions may be more reliable,21 but the retrospective recall of event timing for both mental and physical conditions remains a significant limitation of this study. The cross-sectional design also raises the possibility of spurious or inflated associations through mental disorders at the time of interview affecting self-report of physical conditions; however, sensitivity analyses excluding individuals with mental disorders at the time of the interview found no meaningful alteration in associations.9
Retrospective assessment is known to lead to underreporting of mental disorders and, to a lesser extent, of physical conditions.22 The assessment of physical conditions in the present study was less rigorous than the assessment of mental disorders, and self-report of physician-assigned diagnoses will miss some conditions that are asymptomatic in the early stages. These limitations will undoubtedly have resulted in some individuals with a history of mental disorder and/or physical condition being misclassified as noncases; this kind of misclassification tends to bias associations toward the null, making the results conservative. Survival bias may also contribute to the conservative nature of these findings. In addition, the associations were based on disorders ranging in severity and across remitted and unremitted disorders; therefore, the strength of associations is probably understimated in individuals with severe or recurrent disorders.
Although observational studies cannot determine whether these mental-physical sequential associations reflect causal links, we note that the dose-response pattern in the association of number of mental disorders with risk of physical condition onset is consistent with a causal interpretation. Moreover, many plausible causal mechanisms have been identified including biological,23,24 behavioral,25 effects of psychotropic medications,26 and inequities in health care provision.27 However, some potential common underlying determinants of comorbid mental and physical ill health in adulthood have not yet been fully explored, such as genetics, diet, low birth weight, and predicators of early adverse circumstances.28
Even with the limitations of the retrospective method, the findings of this study are worthy of note. Although evidence for specific mental-physical associations will gradually accumulate from prospective studies, the resulting piecemeal perspective may obscure our study’s broader message that mental disorders of all types are associated with increased odds of a wide range of chronic physical conditions. Current efforts to address health inequalities among the mentally ill are almost entirely focused on those with severe mental illness, who make up a very small proportion of those with mental disorders.
The study findings need to be confirmed in prospective designs, but they suggest that the deleterious effects of mental disorders on physical health (if causal) accumulate over the life course and increase with mental disorder comorbidity. If this is the case, then given the early onset of most mental disorders and the similarly early etiopathogenesis of many chronic physical conditions,29 treatment of all mental disorders should optimally incorporate attention to physical health and health behaviors, with this parallel focus on physical health beginning as early in the course of the mental disorder as possible. Disappointing outcomes from depression treatment trials in patients with heart disease30 may indicate that mental-physical comorbidity could be better addressed by an early focus on the physical health of those with mental disorders rather than a later focus on the mental health of those with chronic physical conditions. Existing programs have proved effective in improving health behaviors of individuals with mental disorders.31 Psychological interventions could be augmented to include a focus on health behaviors. In addition, much could be done in primary care to optimize chronic disease prevention approaches for individuals with mental disorders so that these approaches are more effective than they are at the present time.32 Movement toward the primary prevention of chronic physical conditions among people with mental disorders would do much to enhance their quality and quantity of life.
Corresponding Author: Kate M. Scott, MA(ClinPsych), PhD, Department of Psychological Medicine, University of Otago, PO Box 913, Dunedin, New Zealand (firstname.lastname@example.org).
Submitted for Publication: June 22, 2015; final revision received and accepted October 28, 2015.
Published Online: December 23, 2015. doi:10.1001/jamapsychiatry.2015.2688.
Author Contributions: Dr Scott had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Scott.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: Scott.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Scott, Lim, Kessler.
Obtained funding: Scott, Alonso, Caldas-de-Almeida, Kawakami, Medina-Mora, Moskalewicz, Navarro-Mateu, Posada-Villa, Torres.
Administrative, technical, or material support: Caldas-de-Almeida, Hu, de Jonge, O’Neill, Posada-Villa.
Study supervision: Scott.
Conflict of Interest Disclosures: Dr Kessler reported being a consultant for Analysis Group, GlaxoSmithKline Inc, Kaiser Permanente, Merck & Co Inc, Ortho-McNeil Janssen Scientific Affairs, Pfizer Inc, Sanofi Group, Shire US Inc, SRA International, Inc, Takeda Global Research & Development, Transcept Pharmaceuticals Inc, Wellness and Prevention Inc, and Wyeth-Ayerst; serving on advisory boards for Eli Lilly & Company, Mindsite, and Wyeth-Ayerst; and receiving research support for his epidemiologic studies from Analysis Group Inc, Bristol-Myers Squibb, Eli Lilly & Company, EPI-Q, Ortho-McNeil Janssen Scientific Affairs, Pfizer Inc, Sanofi Group, and Shire US Inc. He reported owning stock in Datastat Inc. No other disclosures were reported.
Funding/Support: The World Health Organization World Mental Health (WMH) Survey Initiative is supported by the National Institute of Mental Health (NIMH; R01 MH070884), the John D. and Catherine T. MacArthur Foundation, the Pfizer Foundation, the US Public Health Service (R13-MH066849, R01-MH069864, and R01 DA016558), the Fogarty International Center (FIRCA R03-TW006481), the Pan American Health Organization, Eli Lilly & Company, Ortho-McNeil Pharmaceutical,GlaxoSmithKline, and Bristol-Myers Squibb. The Colombian National Study of Mental Health was supported by the Ministry of Social Protection, with supplemental support from the Saldarriaga Concha Foundation. The European surveys were funded by the European Commission (Contracts QLG5-1999-01042, SANCO 2004123, and EAH 20081308), the Piedmont Region (Italy), Fondo de Investigación Sanitaria, Instituto de Salud Carlos III, Spain (FIS 00/0028), Ministerio de Ciencia y Tecnología, Spain (SAF 2000-158-CE), Departament de Salut, Generalitat de Catalunya, Spain, Instituto de Salud Carlos III (CIBER CB06/02/0046, RETICS RD06/0011 REM-TAP), and other local agencies and by an unrestricted educational grant from GlaxoSmithKline. The WMH Japan Survey was supported by the Grant for Research on Psychiatric and Neurological Diseases and Mental Health (H13-SHOGAI-023, H14-TOKUBETSU-026, and H16-KOKORO-013) from the Japan Ministry of Health, Labour, and Welfare. The Mexican National Comorbidity Survey was supported by the National Institute of Psychiatry Ramon de la Fuente (INPRFMDIES 4280) and by the National Council on Science and Technology (CONACyT-G30544- H), with supplemental support from the Pan American Health Organization. The Peruvian WMH Study was funded by the National Institute of Health of the Ministry of Health of Peru. The Polish project Epidemiology of Mental Health and Access to Care–EZOP Poland was funded by the Norwegian Financial Mechanism and the European Economic Area Mechanism as well as the Polish Ministry of Health. No support from pharmaceutical industry or other commercial sources was received. The Shenzhen Mental Health Survey was supported by the Shenzhen Bureau of Health and the Shenzhen Bureau of Science, Technology, and Information. The Iraq Mental Health Survey received funding from both the Japanese and European Funds through United Nations Development Group Iraq Trust Fund. The Israel National Health Survey was funded by the Ministry of Health with support from the Israel National Institute for Health Policy and Health Services Research and the National Insurance Institute of Israel. Te Rau Hinengaro: The New Zealand Mental Health Survey was supported by the New Zealand Ministry of Health, Alcohol Advisory Council, and Health Research Council. The Portuguese Mental Health Study was funded by the Champalimaud Foundation, Gulbenkian Foundation, Foundation for Science and Technology, and Ministry of Health. The Romania WMH study projects—Policies in Mental Health Area and National Study Regarding Mental Health and Services Use—were funded by the Ministry of Public Health (former Ministry of Health), with supplemental support of Eli Lilly Romania SRL. The US National Comorbidity Survey Replication is supported by the NIMH (U01-MH60220), with supplemental support from the National Institute of Drug Abuse, the Substance Abuse and Mental Health Services Administration, the Robert Wood Johnson Foundation (grant 044708), and the John W. Alden Trust. Work on this article was partially funded by grant 11/200 from the Health Research Council of New Zealand (Dr Scott).
Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Additional Contributions: We thank the staff of the WMH Data Collection and Data Analysis Coordination Centres for assistance with instrumentation, fieldwork, and consultation on data analysis. The Polish Project Epidemiology of Mental Health and Access to Care was carried out by the Institute of Psychiatry and Neurology in Warsaw in consortium with the Department of Psychiatry, Medical University in Wroclaw and the National Institute of Public Health, National Institute of Hygiene in Warsaw and in partnership with Psykiatrist Institut Vinderen, Universitet, Oslo, Norway. Implementation of the Iraq Mental Health Survey and data entry were carried out by the staff of the Iraqi Ministry of Health and Ministry of Planning. The Portuguese Mental Health Study was carried out by the Department of Mental Health, Faculty of Medical Sciences, NOVA University of Lisbon, with collaboration of the Portuguese Catholic University. The Romania WMH study projects—Policies in Mental Health Area and National Study Regarding Mental Health and Services Use—were carried out by the National School of Public Health & Health Services Management, Bucharest (former National Institute for Research & Development in Health), with technical support of Metro Media Transilvania, the National Institute of Statistics–National Centre for Training in Statistics, SC Cheyenne Services SRL, and Statistics Netherlands. A complete list of all within-country and cross-national WMH publications can be found at http://www.hcp.med.harvard.edu/wmh/.
J. The epidemiology of excess mortality in people with mental illness. Can J Psychiatry
. 2010;55(12):752-760.PubMedGoogle Scholar
TM. Outcomes of Nordic mental health systems: life expectancy of patients with mental disorders. Br J Psychiatry
. 2011;199(6):453-458.PubMedGoogle ScholarCrossref
K, van Winkel
W, De Hert
M. Prevalence of metabolic syndrome and metabolic abnormalities in schizophrenia and related disorders—a systematic review and meta-analysis. Schizophr Bull
. 2013;39(2):306-318.PubMedGoogle ScholarCrossref
S. The gap in life expectancy from preventable physical illness in psychiatric patients in Western Australia: retrospective analysis of population based registers. BMJ
. 2013;346:f2539.PubMedGoogle ScholarCrossref
S. Premature mortality in adults using New Zealand psychiatric services. N Z Med J
. 2014;127(1394):31-41.PubMedGoogle Scholar
et al. Mortality and cause of death among psychiatric patients: a 20-year case-register study in an area with a community-based system of care. Psychol Med
. 2009;39(11):1875-1884.PubMedGoogle ScholarCrossref
S. Mortality in individuals who have had psychiatric treatment: population-based study in Nova Scotia. Br J Psychiatry
. 2005;187(6):552-558.PubMedGoogle ScholarCrossref
KM, de Jonge
et al. Associations between DSM-IV
mental disorders and subsequent heart disease onset: beyond depression. Int J Cardiol
. 2013;168(6):5293-5299.PubMedGoogle ScholarCrossref
J, de Jonge
et al. Associations between DSM-IV
mental disorders and onset of self-reported peptic ulcer in the World Mental Health Surveys. J Psychosom Res
. 2013;75(2):121-127.PubMedGoogle ScholarCrossref
et al. Associations between DSM-IV
mental disorders and diabetes mellitus: a role for impulse control disorders and depression. Diabetologia
. 2014;57(4):699-709.PubMedGoogle ScholarCrossref
J, de Jonge
et al. Association between mental disorders and subsequent adult onset asthma. J Psychiatr Res
. 2014;59:179-188.PubMedGoogle ScholarCrossref
et al. The associations between preexisting mental disorders and subsequent onset of chronic headaches: a worldwide epidemiologic perspective. J Pain
. 2015;16(1):42-52.PubMedGoogle ScholarCrossref
TB, eds. The WHO World Mental Health Surveys: Global Perspectives on the Epidemiology of Mental Disorders. New York, NY: Cambridge University Press; 2008.
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.Google ScholarCrossref
et al. Concordance of the Composite International Diagnostic Interview Version 3.0 (CIDI 3.0) with standardized clinical assessments in the WHO World Mental Health surveys. Int J Methods Psychiatr Res
. 2006;15(4):167-180.PubMedGoogle ScholarCrossref
JB. It’s about time: using discrete-time survival analysis to study duration and the timing of events. J Educ Stat
. 1993;18:155-195.Google ScholarCrossref
BV. Linearization methods of variance estimation. In: Armitage P, Colton T, eds. Encyclopedia of Biostatistics. Chichester, England: John Wiley & Sons; 1998:2276-2279.
Global Burden of Metabolic Risk Factors for Chronic Diseases Collaboration. Cardiovascular disease, chronic kidney disease, and diabetes mortality burden of cardiometabolic risk factors from 1980 to 2010: a comparative risk assessment. Lancet Diabetes Endocrinol
. 2014;2(8):634-647.PubMedGoogle ScholarCrossref
J, de Marco
R. Using the age at onset may increase the reliability of longitudinal asthma assessment. J Clin Epidemiol
. 2007;60(7):704-711.PubMedGoogle ScholarCrossref
R. Accuracy of reports of lifetime mental and physical disorders: results from the Baltimore Epidemiological Catchment Area study. JAMA Psychiatry
. 2014;71(3):273-280.PubMedGoogle ScholarCrossref
GE. Depression and hypothalamic-pituitary-adrenal activation: a quantitative summary of four decades of research. Psychosom Med
. 2011;73(2):114-126.PubMedGoogle ScholarCrossref
et al. Association of antidepressant medications with carotid intima media thickness in middle aged veteran twins. J Am Coll Cardiol
. 2011;57(14)(suppl):E1588.Google ScholarCrossref
S. Inequalities in healthcare provision for people with severe mental illness. J Psychopharmacol
. 2010;24(4)(suppl):61-68.PubMedGoogle ScholarCrossref
A, ed. Depression and Physical Illness. Cambridge, UK: Cambridge University Press; 2007.
M. When to prevent cardiovascular disease? as early as possible: lessons from prospective cohorts beginning in childhood. Curr Opin Cardiol
. 2013;28(5):561-568.PubMedGoogle ScholarCrossref
et al; Enhancing Recovery in Coronary Heart Disease Patients Investigators (ENRICHD). Effects of treating depression and low perceived social support on clinical events after myocardial infarction: the Enhancing Recovery in Coronary Heart Disease Patients (ENRICHD) Randomized Trial. JAMA
. 2003;289(23):3106-3116.PubMedGoogle ScholarCrossref
D. Health behaviour interventions to improve physical health in individuals diagnosed with a mental illness: a systematic review. Int J Ment Health Nurs
. 2012;21(3):236-247.PubMedGoogle ScholarCrossref
KM. Prevention of cardiovascular disease in depression. In: Baune
PJ, eds. Cardiovascular Diseases and Depression: Treatment and Prevention in Psychocardiology. Heidelberg, Germany: Springer; in press.