Nature and Extent of Physical Comorbidities Among Korean Patients With Mental Illnesses: Pairwise and Network Analysis Based on Health Insurance Claims Data
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Objective The nature of physical comorbidities in patients with mental illness may differ according to diagnosis and personal characteristics. We investigated this complexity by conventional logistic regression and network analysis.Methods A health insurance claims data in Korea was analyzed. For every combination of psychiatric and physical diagnoses, odds ratios were calculated adjusting age and sex. From the patient-diagnosis data, a network of diagnoses was constructed using Jaccard coefficient as the index of comorbidity.Results In 1,017,024 individuals, 77,447 (7.6%) were diagnosed with mental illnesses. The number of physical diagnoses among them was 11.2, which was 1.6 times higher than non-psychiatric groups. The most noticeable associations were 1) neurotic illnesses with gastrointestinal/pain disorders and 2) dementia with fracture, Parkinson’s disease, and cerebrovascular accidents. Unexpectedly, the diagnosis of metabolic syndrome was only scarcely found in patients with severe mental illnesses (SMIs). However, implicit associations between metabolic syndrome and SMIs were suggested in comorbidity networks.Conclusion Physical comorbidities in patients with mental illnesses were more extensive than those with other disease categories. However, the result raised questions as to whether the medical resources were being diverted to less serious conditions than more urgent conditions in patients with SMIs.
Abstract
Objective The nature of physical comorbidities in patients with mental illness may differ according to diagnosis and personal characteristics. We investigated this complexity by conventional logistic regression and network analysis.Methods A health insurance claims data in Korea was analyzed. For every combination of psychiatric and physical diagnoses, odds ratios were calculated adjusting age and sex. From the patient-diagnosis data, a network of diagnoses was constructed using Jaccard coefficient as the index of comorbidity.Results In 1,017,024 individuals, 77,447 (7.6%) were diagnosed with mental illnesses. The number of physical diagnoses among them was 11.2, which was 1.6 times higher than non-psychiatric groups. The most noticeable associations were 1) neurotic illnesses with gastrointestinal/pain disorders and 2) dementia with fracture, Parkinson’s disease, and cerebrovascular accidents. Unexpectedly, the diagnosis of metabolic syndrome was only scarcely found in patients with severe mental illnesses (SMIs). However, implicit associations between metabolic syndrome and SMIs were suggested in comorbidity networks.Conclusion Physical comorbidities in patients with mental illnesses were more extensive than those with other disease categories. However, the result raised questions as to whether the medical resources were being diverted to less serious conditions than more urgent conditions in patients with SMIs.
참고문헌 (60)
- Sartorius N, "Comorbidity of mental and physical disorders: a key problem for medicine in the 21st century", Acta Psychiatr Scand, 137, pp.369~370 (2018)
- Plana-Ripoll O, "Exploring comorbidity within mental disorders among a Danish national population", JAMA Psychiatry, 76, pp.259~270 (2019)
- ji-hyun kim, "Mental-Physical Comorbidity in Korean Adults: Results from a Nationwide General Population Survey in Korea", PSYCHIATRY INVESTIGATION, 13(5), pp.496~503 (2016), 대한신경정신의학회[DOI]
- Momen NC, "Association between mental disorders and subsequent medical conditions", N Engl J Med, 382, pp.1721~1731 (2020)
- Smith DJ, "Schizophrenia is associated with excess multiple physical-health comorbidities but low levels of recorded cardiovascular disease in primary care: crosssectional study", BMJ Open, 3, pp.e002808~ (2013)
- Nelis SM, "The impact of co-morbidity on the quality of life of people with dementia:findings from the IDEAL study", Age Ageing, 48, pp.361~367 (2019)
- Yang C, "Physical Comorbidities are independently associated with higher rates of psychiatric readmission in a Chinese Han population", Neuropsychiatr Dis Treat, 16, pp.2073~2082 (2020)
- Walker ER, "Mortality in mental disorders and global disease burden implications: a systematic review and meta-analysis", JAMA Psychiatry, 72, pp.334~341 (2015)
- Pan YJ, "Excess mortality and shortened life expectancy in people with major mental illnesses in Taiwan", Epidemiol Psychiatr Sci, 29, pp.e156~ (2020)
- Firth J, "The Lancet Psychiatry Commission: a blueprint for protecting physical health in people with mental illness", Lancet Psychiatry, 6, pp.675~712 (2019)
- Jansen L, "Healtheconomic outcomes in hospital patients with medical-psychiatric comorbidity:a systematic review and meta-analysis", PLoS One, 13, pp.e0194029~ (2018)
- Park S, "Physical comorbidity according to diagnoses and sex among psychiatric inpatients in South Korea", Int J Environ Res Public Health, 18, pp.4187~ (2021)
- Carney CP, "Medical comorbidity in women and men with schizophrenia: a population-based controlled study", J Gen Intern Med, 21, pp.1133~1137 (2006)
- Crawford MJ, "Assessment and treatment of physical health problems among people with schizophrenia: national cross-sectional study", Br J Psychiatry, 205, pp.473~477 (2014)
- Scott KM, "Association of mental disorders with subsequent chronic physical conditions: world mental health surveys from 17 countries", JAMA Psychiatry, 73, pp.150~158 (2016)
- Katon WJ, "Clinical and health services relationships between major depression, depressive symptoms, and general medical illness", Biol Psychiatry, 54, pp.216~226 (2003)
- Vancampfort D, "The relationship between chronic physical conditions, multimorbidity and anxiety in the general population: a global perspective across 42 countries", Gen Hosp Psychiatry, 45, pp.1~6 (2017)
- Romain AJ, "Impact of obesity and mood disorders on physical comorbidities, psychological well-being, health behaviours and use of health services", J Affect Disord, 225, pp.381~388 (2018)
- Hu JX, "Network biology concepts in complex disease comorbidities", Nat Rev Genet, 17, pp.615~629 (2016)
- Klabunde CN, "Assessing comorbidity using claims data: an overview", Med Care, 40(8 Suppl), pp.IV-26~IV-35 (2002)
- Klabunde CN, "A refined comorbidity measurement algorithm for claims-based studies of breast, prostate, colorectal, and lung cancer patients", Ann Epidemiol, 17, pp.584~590 (2007)
- Steffen A, "Mental and somatic comorbidity of depression: a comprehensive cross-sectional analysis of 202 diagnosis groups using German nationwide ambulatory claims data", BMC Psychiatry, 20, pp.142~ (2020)
- Summer G, "cy-Neo4j: connecting Neo4j and Cytoscape", Bioinformatics, 31, pp.3868~3869 (2015)
- Balaur I, "Recon2Neo4j:applying graph database technologies for managing comprehensive genome-scale networks", Bioinformatics, 33, pp.1096~1098 (2017)
- Shoshi A, "GenCoNet–a graph database for the analysis of comorbidities by gene networks", J Integr Bioinform, 15, pp.20180049~ (2018)
- Kim JH, "Network analysis of human diseases using Korean nationwide claims data", J Biomed Inform, 61, pp.276~282 (2016)
- Tabarés-Seisdedos R, "The importance of negative comorbidity", J Clin Psychiatry, 70, pp.1191~1192 (2009)
- Pavlopoulos GA, "Bipartite graphs in systems biology and medicine: a survey of methods and applications", Gigascience, 7, pp.1~31 (2018)
- Jeong E, "Network-based analysis of diagnosis progression patterns using claims data", Sci Rep, 7, pp.15561~ (2017)
- Fotouhi B, "Statistical methods for constructing disease comorbidity networks from longitudinal inpatient data", Appl Netw Sci, 3, pp.46~ (2018)
- Cramer AO, "Comorbidity:a network perspective", Behav Brain Sci, 33, pp.137~150 (2010)
- Goh KI, "The human disease network", Proc Natl Acad Sci U S A, 104, pp.8685~8690 (2007)
- Hidalgo CA, "A dynamic network approach for the study of human phenotypes", PLoS Comput Biol, 5, pp.e1000353~ (2009)
- Jiang Y, "An epidemiological human disease network derived from disease co-occurrence in Taiwan", Sci Rep, 8, pp.4557~ (2018)
- García Del Valle EP, "Disease networks and their contribution to disease understanding: a review of their evolution, techniques and data sources", J Biomed Inform, 94, pp.103206~ (2019)
- Ni P, "Constructing disease similarity networks based on disease module theory", IEEE, 2020, pp.17, 906~915
- Nocaj A, "Untangling the hairballs of multicentered, small-world online social media networks", J Graph Algorithms Appl, 19, pp.595~618 (2015)
- Ko Y, "Identification of disease comorbidity through hidden molecular mechanisms", Sci Rep, 6, pp.39433~ (2016)
- Ehlert U, "Psychoneuroendocrinological contributions to the etiology of depression, posttraumatic stress disorder, and stress-related bodily disorders: the role of the hypothalamus-pituitaryadrenal axis", Biol Psychol, 57, pp.141~152 (2001)
- Cameron OG, "Anxious and depressive disorders and their comorbidity: effect on central nervous system noradrenergic function", Biol Psychiatry, 56, pp.875~883 (2004)
- Bremmer MA, "Inflammatory markers in late-life depression: results from a population-based study", J Affect Disord, 106, pp.249~255 (2008)
- Söderquist F, "A cross-sectional study of gastrointestinal symptoms, depressive symptoms and trait anxiety in young adults", BMC Psychiatry, 20, pp.535~ (2020)
- Larson SL, "Depressive disorder as a long-term antecedent risk factor for incident back pain: a 13-year follow-up study from the Baltimore Epidemiological Catchment Area sample", Psychol Med, 34, pp.211~219 (2004)
- Seto H, "Relationships between catastrophic thought, bodily sensations and physical symptoms", Biopsychosoc Med, 11, pp.28~ (2017)
- Boeckle M, "Neural correlates of somatoform disorders from a meta-analytic perspective on neuroimaging studies", Neuroimage Clin, 11, pp.606~613 (2016)
- Köteles F, "Somatosensory amplification - An old construct from a new perspective", J Psychosom Res, 101, pp.1~9 (2017)
- Wittchen HU, "Mental disorders in primary care", Dialogues Clin Neurosci, 5, pp.115~128 (2003)
- Maxwell M, "A qualitative study of primary care professionals’ views of case finding for depression in patients with diabetes or coronary heart disease in the UK", BMC Fam Pract, 14, pp.46~ (2013)
- Zimmerman M, "A review of 20 years of research on overdiagnosis and underdiagnosis in the Rhode Island Methods to Improve Diagnostic Assessment and Services (MIDAS) project", Can J Psychiatry, 61, pp.71~79 (2016)
- Bijl RV, "Psychiatric morbidity, service use, and need for care in the general population: results of The Netherlands Mental Health Survey and Incidence Study", Am J Public Health, 90, pp.602~607 (2000)
- Boerema AM, "Determinants of help-seeking behavior in depression: a cross-sectional study", BMC Psychiatry, 16, pp.78~ (2016)
- Heinig I, "Help-seeking behavior and treatment barriers in anxiety disorders: results from a representative German community survey", Community Ment Health J, 57, pp.1505~1517 (2021)
- Crump C, "Comorbidities and mortality in persons with schizophrenia: a Swedish national cohort study", Am J Psychiatry, 170, pp.324~333 (2013)
- Haussleiter I, "The somatic care situation of people with mental illness", Health Sci Rep, 4, pp.e226~ (2021)
- Park S, "Association between screening and the thyroid cancer “epidemic” in South Korea:evidence from a nationwide study", BMJ, 355, pp.i5745~ (2016)
- Heo YC, "Mental health system at the community level in Korea: development, recent reforms and challenges", Int J Ment Health Syst, 13, pp.9~ (2019)
- Sung-Wan Kim, "Physical Health Literacy and Health-related Behaviors in Patients with Psychosis", Clinical Psychopharmacology and Neuroscience, 17(2), pp.279~287 (2019), 대한정신약물학회[DOI]
- Marx P, "Comorbidities in the diseasome are more apparent than real: what Bayesian filtering reveals about the comorbidities of depression", PLoS Comput Biol, 13, pp.e1005487~ (2017)
- Khan A, "Comorbidity network for chronic disease:a novel approach to understand type 2 diabetes progression", Int J Med Inform, 115, pp.1~9 (2018)
- Aguado A, "Morbi-Net: multimorbidity networks in adult general population. Analysis of type 2 diabetes mellitus comorbidity", Sci Rep, 10, pp.2416~ (2020)
