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The quality of severe mental disorder diagnoses in a national health registry as compared to research diagnoses based on structured interview.

https://arctichealth.org/en/permalink/ahliterature284123
Source
BMC Psychiatry. 2017 Mar 14;17(1):93
Publication Type
Article
Date
Mar-14-2017
Author
Ragnar Nesvåg
Erik G Jönsson
Inger Johanne Bakken
Gun Peggy Knudsen
Thomas D Bjella
Ted Reichborn-Kjennerud
Ingrid Melle
Ole A Andreassen
Source
BMC Psychiatry. 2017 Mar 14;17(1):93
Date
Mar-14-2017
Language
English
Publication Type
Article
Keywords
Adult
Bipolar Disorder - diagnosis - psychology
Diagnostic and Statistical Manual of Mental Disorders
Female
Humans
International Classification of Diseases
Male
Norway
Psychometrics - statistics & numerical data
Psychotic Disorders - diagnosis - psychology
Registries
Research Design
Schizophrenia - diagnosis
Abstract
Utilization of diagnostic information from national patient registries rests on the quality of the registered diagnoses. We aimed to investigate the agreement and consistency of diagnoses of psychotic and bipolar disorders in the Norwegian Patient Registry (NPR) compared to structured interview-based diagnoses given as part of a clinical research project.
Diagnostic data from NPR were obtained for the period 01.01.2008-31.12.2013 for all patients who had been included in the Thematically Organized Psychosis (TOP) study between 18.10.2002 and 01.09.2014 with a Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) diagnosis of schizophrenia (n?=?537), delusional disorder (n?=?48), schizoaffective disorder (n?=?118) or bipolar disorder (n?=?408). Diagnostic agreement between the primary DSM-IV diagnosis in TOP and the International Classification of Diseases, 10th revision (ICD-10) diagnoses in NPR was evaluated using Cohen's unweighted nominal kappa (?). Diagnostic consistency was calculated as the proportion of all registered severe mental disorder diagnoses in NPR that were equivalent to the primary diagnosis given in the TOP study.
The proportion of patients registered with the equivalent ICD-10 diagnosis as the primary DSM-IV diagnosis given in TOP was 84.2% for the schizophrenia group, 68.8% for the delusional disorder group, 76.3% for the schizoaffective disorder group, and 78.4% for the bipolar disorder group. Diagnostic agreement was good for schizophrenia (??=?0.74) and bipolar disorder (??=?0.72), fair for schizoaffective disorder (??=?0.63), and poor for delusional disorder (??=?0.39). Among patients with DSM-IV schizophrenia, 4.7% were diagnosed with ICD-10 bipolar disorder, and among patients with DSM-IV bipolar disorder, 2.5% were diagnosed with ICD-10 schizophrenia. Diagnostic consistency was 84.9% for schizophrenia, 59.1% for delusional disorder, 65.9% for schizoaffective disorder, and 91.0% for bipolar disorder.
When compared to research-based diagnoses, clinical diagnoses of schizophrenia and bipolar disorder in the NPR are accurate and consistent, with minimal diagnostic overlap between the two disorders.
Notes
Cites: Pediatrics. 2012 Jul;130(1):e152-822711729
Cites: Gen Hosp Psychiatry. 2014 Nov-Dec;36(6):709-1525307514
Cites: Psychopathology. 2006;39(6):286-9516960467
Cites: BMC Public Health. 2011 Jun 09;11:45021658213
Cites: Soc Psychiatry Psychiatr Epidemiol. 2002 Nov;37(11):527-3112395142
Cites: Nord J Psychiatry. 2008;62(3):198-20318609031
Cites: Schizophr Res. 2012 Mar;135(1-3):187-9122260965
Cites: Nord J Psychiatry. 2005;59(3):209-1216195122
Cites: Am J Psychiatry. 1994 May;151(5):650-78166304
Cites: Schizophr Bull. 2010 Jul;36(4):830-519176474
Cites: Eur Psychiatry. 1998;13(2):57-6219698600
Cites: Soc Psychiatry Psychiatr Epidemiol. 2015 Aug;50(8):1267-7625680837
Cites: Soc Psychiatry Psychiatr Epidemiol. 1997 Jul;32(5):303-89257522
Cites: BMC Psychiatry. 2012 Feb 29;12:1322373296
Cites: Nord J Psychiatry. 2005;59(6):457-6416316898
PubMed ID
28292279 View in PubMed
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Socioeconomic status and sick leave granted for mental and somatic disorders: a prospective study of young adult twins.

https://arctichealth.org/en/permalink/ahliterature267197
Source
BMC Public Health. 2015;15:134
Publication Type
Article
Date
2015
Author
Fartein Ask Torvik
Eivind Ystrom
Nikolai Czajkowski
Kristian Tambs
Espen Røysamb
Ragnhild Ørstavik
Gun Peggy Knudsen
Kenneth S Kendler
Ted Reichborn-Kjennerud
Source
BMC Public Health. 2015;15:134
Date
2015
Language
English
Publication Type
Article
Keywords
Adult
Female
Humans
Male
Mental disorders
Norway
Prospective Studies
Psychophysiologic Disorders
Sick Leave - statistics & numerical data
Social Class
Time Factors
Twins, Dizygotic - psychology
Twins, Monozygotic - psychology
Abstract
Low socioeconomic status (SES), indicated by low income and education, has consistently been found to be a strong predictor of sick leave. Several possible pathways from SES to sick leave have been described in previous literature, but there are also evidence indicating that the association can be confounded by common underlying factors. This study utilizes a population-based sample of employed young adult twins to estimate (i) the degree to which education and income are prospectively related to sick leave granted for mental, somatic, and any disorder, and (ii) whether these associations are confounded by familial factors.
Registry data on educational attainment and income at age 30 and subsequent sick leave were available for 6,103 employed young adult twins, among which there were 2,024 complete twin pairs. The average follow-up time was 6.57?years. Individual-level associations and fixed effects within twin pairs were estimated.
Low education and income were associated with sick leave granted for both mental and somatic disorders, and with sick leave granted for any disorder. Associations were attenuated within dizygotic twin pairs and reduced to non-significance within monozygotic twin pairs, suggesting influence of familial factors on the associations between SES and sick leave.
Low SES is associated with a higher level of sick leave granted for both mental and somatic disorders among young adults, but these associations are confounded by factors that are common to co-twins. Education and income are therefore not likely to strongly affect sick leave in young adulthood.
Notes
Cites: PLoS One. 2011;6(8):e2314321850258
Cites: Proc Natl Acad Sci U S A. 2011 Feb 15;108(7):2693-821262822
Cites: Epidemiology. 2012 Sep;23(5):713-2022781362
Cites: Twin Res Hum Genet. 2012 Oct;15(5):642-822931554
Cites: J Occup Environ Med. 2012 Nov;54(11):1330-623090159
Cites: Soc Psychiatry Psychiatr Epidemiol. 2012 Dec;47(12):1999-200922430867
Cites: Span J Psychol. 2012 Nov;15(3):1272-8223156931
Cites: BMC Public Health. 2013;13:54523738703
Cites: Scand J Work Environ Health. 2013 Jul;39(4):351-6023248027
Cites: Twin Res Hum Genet. 2013 Aug;16(4):759-6623743022
Cites: Int Arch Occup Environ Health. 2013 Aug;86(6):619-2722772397
Cites: BMC Musculoskelet Disord. 2013;14:26824040914
Cites: Ann N Y Acad Sci. 1999;896:3-1510681884
Cites: Psychol Bull. 2000 Mar;126(2):309-3710748645
Cites: Ann N Y Acad Sci. 2001 Dec;954:118-3911797854
Cites: Soc Sci Med. 2004 Apr;58(8):1543-5314759697
Cites: Scand J Public Health Suppl. 2004;63:49-10815513654
Cites: Lancet. 1991 Jun 8;337(8754):1387-931674771
Cites: Soc Sci Med. 1994 May;38(9):1257-788016690
Cites: Soc Sci Med. 1997 Oct;45(7):1111-209257402
Cites: J Epidemiol Community Health. 2005 Apr;59(4):268-7315767378
Cites: Am J Public Health. 2005 Jul;95(7):1206-1215933236
Cites: Int J Epidemiol. 2005 Oct;34(5):1089-9916087687
Cites: BMJ. 2006 Mar 11;332(7541):580-416452104
Cites: Twin Res Hum Genet. 2006 Dec;9(6):858-6417254421
Cites: Int J Epidemiol. 2007 Feb;36(1):77-8317251245
Cites: J Epidemiol Community Health. 2008 Feb;62(2):181-318192608
Cites: Health Psychol. 2008 Jul;27(4):482-918643006
Cites: PLoS One. 2008;3(10):e340218923678
Cites: Int J Epidemiol. 2009 Oct;38(5):1310-2219528192
Cites: Scand J Public Health. 2009 Nov;37(8):839-4519726527
Cites: Ann N Y Acad Sci. 2010 Feb;1186:102-2420201870
Cites: JAMA. 2010 Mar 24;303(12):1159-6620332401
Cites: J Epidemiol Community Health. 2010 Sep;64(9):802-719778907
Cites: Psychol Sci. 2010 Sep;21(9):1266-7320679521
Cites: BMC Public Health. 2010;10:64320973979
Cites: BMC Public Health. 2011;11:1221210992
Cites: J Occup Environ Med. 2012 Jan;54(1):10-622157805
PubMed ID
25884296 View in PubMed
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Health problems account for a small part of the association between socioeconomic status and disability pension award. Results from the Hordaland Health Study.

https://arctichealth.org/en/permalink/ahliterature138096
Source
BMC Public Health. 2011;11:12
Publication Type
Article
Date
2011
Author
Kristian Amundsen Østby
Ragnhild E Ørstavik
Ann Kristin Knudsen
Ted Reichborn-Kjennerud
Arnstein Mykletun
Author Affiliation
Department of Mental Health, Norwegian Institute of Public Health, Oslo, Norway. kroe@fhi.no
Source
BMC Public Health. 2011;11:12
Date
2011
Language
English
Publication Type
Article
Keywords
Adult
Disabled Persons
Educational Status
Female
Humans
Insurance, Disability
Logistic Models
Male
Norway
Odds Ratio
Pensions - statistics & numerical data
Social Class
Abstract
Low socioeconomic status is a known risk factor for disability pension, and is also associated with health problems. To what degree health problems can explain the increased risk of disability pension award associated with low socioeconomic status is not known.
Information on 15,067 participants in the Hordaland Health Study was linked to a comprehensive national registry on disability pension awards. Level of education was used as a proxy for socioeconomic status. Logistic regression analyses were employed to examine the association between socioeconomic status and rates of disability pension award, before and after adjusting for a wide range of somatic and mental health factors. The proportion of the difference in disability pension between socioeconomic groups explained by health was then calculated.
Unadjusted odds ratios for disability pension was 4.60 (95% CI: 3.34-6.33) for the group with elementary school only (9 years of education) and 2.03 (95% CI 1.49-2.77) for the group with high school (12 years of education) when compared to the group with higher education (more than 12 years). When adjusting for somatic and mental health, odds ratios were reduced to 3.87 (2.73-5.47) and 1.81 (1.31-2.52). This corresponds to health explaining only a marginal proportion of the increased level of disability pension in the groups with lower socioeconomic status.
There is a socioeconomic gradient in disability pension similar to the well known socioeconomic gradient in health. However, health accounts for little of the socioeconomic gradient in disability pension. Future studies of socioeconomic gradients in disability pension should focus on explanatory factors beyond health.
Notes
Cites: Acta Psychiatr Scand. 1983 Jun;67(6):361-706880820
Cites: Scand J Public Health Suppl. 2004;63:49-10815513654
Cites: Scand J Work Environ Health. 1991;17 Suppl 1:75-811792534
Cites: Am J Public Health. 1992 Jun;82(6):816-201585961
Cites: Scand J Soc Med. 1993 Jun;21(2):116-98367676
Cites: Soc Sci Med. 1997 Mar;44(6):809-199080564
Cites: Tidsskr Nor Laegeforen. 1997 Jun 30;117(17):2449-539265303
Cites: Occup Environ Med. 1998 Feb;55(2):91-89614392
Cites: Am J Psychiatry. 2006 Aug;163(8):1412-816877655
Cites: BMC Public Health. 2006;6:21916939642
Cites: Scand J Public Health. 2006;34(6):623-3117132596
Cites: Scand J Public Health. 2007;35(2):157-6317454919
Cites: Occup Environ Med. 2008 Nov;65(11):769-7318940958
Cites: Br J Psychiatry. 2009 Mar;194(3):220-319252149
Cites: Psychosom Med. 2009 Apr;71(3):353-6019321853
Cites: Int J Obes (Lond). 2010 Apr;34(4):726-3220101246
Cites: J Psychosom Res. 2010 Jul;69(1):59-6720630264
Cites: Occup Med (Lond). 2010 Aug;60(5):362-820308262
Cites: Am J Epidemiol. 2010 Dec 1;172(11):1306-1420843863
Cites: J Epidemiol Community Health. 2005 Jun;59(6):450-415911638
Cites: Ann N Y Acad Sci. 1999;896:3-1510681884
Cites: N Engl J Med. 2001 Jul 12;345(2):134-611450663
Cites: J Psychosom Res. 2002 Feb;52(2):69-7711832252
Cites: Eur J Epidemiol. 2001;17(11):991-912380710
Cites: Int J Epidemiol. 2002 Dec;31(6):1183-9112540720
Cites: Int J Epidemiol. 2002 Dec;31(6):1192-9; discussion 1199-20012540721
Cites: Ugeskr Laeger. 2003 Aug 25;165(35):3315-914531369
Cites: Soc Sci Med. 2004 May;58(10):1837-4815020001
Cites: Br J Ind Med. 1987 Feb;44(2):101-103814541
PubMed ID
21210992 View in PubMed
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The Norwegian Twin Registry from a public health perspective: a research update.

https://arctichealth.org/en/permalink/ahliterature118628
Source
Twin Res Hum Genet. 2013 Feb;16(1):285-95
Publication Type
Article
Date
Feb-2013
Author
Thomas S Nilsen
Gun Peggy Knudsen
Kristina Gervin
Ingunn Brandt
Espen Røysamb
Kristian Tambs
Ragnhild Orstavik
Robert Lyle
Ted Reichborn-Kjennerud
Per Magnus
Jennifer R Harris
Author Affiliation
Division of Epidemiology, Norwegian Institute of Public Health, Oslo, Norway.
Source
Twin Res Hum Genet. 2013 Feb;16(1):285-95
Date
Feb-2013
Language
English
Publication Type
Article
Keywords
Biological Specimen Banks
Biomedical research
Child
Cohort Studies
Diseases in Twins - epidemiology - genetics
Female
Gene-Environment Interaction
Genome-Wide Association Study
Humans
Male
Norway - epidemiology
Patient Selection
Public Health
Registries
Twins, Dizygotic - genetics
Twins, Monozygotic - genetics
Abstract
We describe the importance of the Norwegian Twin Registry (NTR) for research in public health and provide examples from several programs of twin research at the Norwegian Institute of Public Health (NIPH), including the Nordic Twin Study of Cancer, our epigenetics platform, and our large program of research in mental health. The NTR has become an integral component of a national strategy for maximizing the research potential from Norwegian registries and biobank-based studies. The information provided herein builds upon and complements our recent report describing the establishment of the NTR and the cohorts comprising it. Although Norway has a long tradition in twin research, the centralization and administration of the twin data through a single register structure is fairly recent. The NTR was established in 2009 and currently includes 47,989 twins covering birth years 1895-1960 and 1967-1979; 31,440 of these twins have consented to participate in medical research (comprising 5,439 monozygotic pairs, 6,702 dizygotic same-sexed pairs, and 1,655 dizygotic opposite-sexed pairs). DNA from approximately 4,800 twins is banked at the NIPH biobank and new studies continuously add new data to the registry. The value of NTR data is greatly enhanced through record linkage possibilities offered by Norway's many nation-wide registries (medical, demographic, and socio-economic) and several studies are already taking advantage of these linkage opportunities for research.
PubMed ID
23186607 View in PubMed
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Personality disorders are important risk factors for disability pensioning.

https://arctichealth.org/en/permalink/ahliterature264500
Source
Soc Psychiatry Psychiatr Epidemiol. 2014 Dec;49(12):2003-11
Publication Type
Article
Date
Dec-2014
Author
Kristian Amundsen Østby
Nikolai Czajkowski
Gun Peggy Knudsen
Eivind Ystrom
Line C Gjerde
Kenneth S Kendler
Ragnhild E Ørstavik
Ted Reichborn-Kjennerud
Source
Soc Psychiatry Psychiatr Epidemiol. 2014 Dec;49(12):2003-11
Date
Dec-2014
Language
English
Publication Type
Article
Keywords
Adult
Diagnostic and Statistical Manual of Mental Disorders
Disabled Persons - psychology - statistics & numerical data
Female
Humans
Interview, Psychological
Male
Mental Disorders - diagnosis
Norway
Odds Ratio
Pensions
Personality Disorders - diagnosis
Risk factors
Young Adult
Abstract
To determine whether personality disorders (PDs) are associated with increased risk of disability pensioning in young adults, independent of other common mental disorders.
2,770 young adults from the general population were assessed for PDs by the Structured Interview for DSM-IV Personality, and for common mental disorders by the Composite of International Diagnostic Interview. These data were linked to the Norwegian National Insurance Administration's recordings of disability benefits for a 10-year period. Logistic regression analyses were applied to investigate the association between PDs and disability pensioning. The analyses were conducted for three types of PD measures: categorical diagnoses (any PD), dimensional scores of individual PDs and higher order components retrieved by principal component analyses.
Having any PD was strongly associated with disability pensioning, regardless of disability diagnosis. The estimated odds ratio (OR) was substantially higher for PDs [OR 4.69 (95% confidence interval (CI) 2.6-8.5)] than for mood disorders [OR 1.3 (CI 0.7-2.3)] and anxiety disorders [OR 2.3 (CI 1.3-4.3)]. Measured dimensionally, all PD traits except antisocial traits were significantly associated with disability pensioning. After adjusting for co-occurring traits of other PDs, only schizoid, dependent and borderline PD traits showed a significant positive association with disability pension, while antisocial traits showed a significant negative association. The principal component analyses showed that negative affectivity, psychoticism, and detachment was associated with an increased risk of disability pensioning, while antagonism/disinhibition and obsessivity were not.
PDs are strongly associated with disability pensioning in young adults, and might be more important predictors of work disability than anxiety and depressive disorders. Certain aspects of pathologic personalities are particularly important predictors of disability.
Notes
Cites: Twin Res. 2002 Oct;5(5):415-2312613498
Cites: J Clin Psychiatry. 2004 Jul;65(7):948-5815291684
Cites: Am J Psychiatry. 1992 Feb;149(2):213-201734742
Cites: J Epidemiol Community Health. 2005 Jan;59(1):70-415598730
Cites: J Pers Soc Psychol. 2005 Jan;88(1):139-5715631580
Cites: Br J Psychiatry. 2006 May;188:423-3116648528
Cites: Am J Psychiatry. 2006 Aug;163(8):1412-816877655
Cites: Compr Psychiatry. 2007 Jul-Aug;48(4):329-3617560953
Cites: Psychol Med. 2007 Jul;37(7):983-9417121690
Cites: J Clin Psychiatry. 2008 Feb;69(2):259-6518363454
Cites: J Clin Psychiatry. 2008 Apr;69(4):533-4518426259
Cites: J Clin Psychiatry. 2008 Jul;69(7):1033-4518557663
Cites: Nord J Psychiatry. 2008;62(4):294-30118622882
Cites: Twin Res Hum Genet. 2009 Apr;12(2):158-6819335186
Cites: Psychosom Med. 2009 Apr;71(3):353-6019321853
Cites: Br J Psychiatry. 2009 Jul;195(1):46-5319567896
Cites: J Psychosom Res. 2010 Jul;69(1):59-6720630264
Cites: Psychol Med. 2010 Sep;40(9):1475-8419917148
Cites: Lancet. 2011 Jan 1;377(9759):74-8421195251
Cites: J Pers Disord. 2011 Apr;25(2):136-6921466247
Cites: Psychol Med. 2012 Dec;42(12):2631-4022565011
Cites: Soc Psychiatry Psychiatr Epidemiol. 2014 Feb;49(2):327-3523835577
Cites: J Pers Disord. 2000 Spring;14(1):17-2910746202
Cites: Twin Res. 2001 Dec;4(6):464-7711780939
Cites: Twin Res. 2002 Apr;5(2):125-3111931690
PubMed ID
24791656 View in PubMed
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The joint structure of DSM-IV Axis I and Axis II disorders.

https://arctichealth.org/en/permalink/ahliterature101854
Source
J Abnorm Psychol. 2011 Feb;120(1):198-209
Publication Type
Article
Date
Feb-2011
Author
Espen Røysamb
Kenneth S Kendler
Kristian Tambs
Ragnhild E Orstavik
Michael C Neale
Steven H Aggen
Svenn Torgersen
Ted Reichborn-Kjennerud
Author Affiliation
Norwegian Institute of Public Health and University of Oslo, Norway. espen.roysamb@psykologi.uio.no
Source
J Abnorm Psychol. 2011 Feb;120(1):198-209
Date
Feb-2011
Language
English
Publication Type
Article
Keywords
Adult
Diagnostic and Statistical Manual of Mental Disorders
Diseases in Twins - classification - diagnosis - psychology
Factor Analysis, Statistical
Female
Humans
Male
Mental Disorders - classification - diagnosis - psychology
Models, Psychological
Norway
Personality Assessment
Psychometrics
Questionnaires
Twins - psychology
Abstract
The Diagnostic and Statistical Manual (4th ed. [DSM-IV]; American Psychiatric Association, 1994) distinction between clinical disorders on Axis I and personality disorders on Axis II has become increasingly controversial. Although substantial comorbidity between axes has been demonstrated, the structure of the liability factors underlying these two groups of disorders is poorly understood. The aim of this study was to determine the latent factor structure of a broad set of common Axis I disorders and all Axis II personality disorders and thereby to identify clusters of disorders and account for comorbidity within and between axes. Data were collected in Norway, through a population-based interview study (N = 2,794 young adult twins). Axis I and Axis II disorders were assessed with the Composite International Diagnostic Interview (CIDI) and the Structured Interview for DSM-IV Personality (SIDP-IV), respectively. Exploratory and confirmatory factor analyses were used to investigate the underlying structure of 25 disorders. A four-factor model fit the data well, suggesting a distinction between clinical and personality disorders as well as a distinction between broad groups of internalizing and externalizing disorders. The location of some disorders was not consistent with the DSM-IV classification; antisocial personality disorder belonged primarily to the Axis I externalizing spectrum, dysthymia appeared as a personality disorder, and borderline personality disorder appeared in an interspectral position. The findings have implications for a meta-structure for the DSM.
PubMed ID
21319931 View in PubMed
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The structure of genetic and environmental risk factors for syndromal and subsyndromal common DSM-IV axis I and all axis II disorders.

https://arctichealth.org/en/permalink/ahliterature140022
Source
Am J Psychiatry. 2011 Jan;168(1):29-39
Publication Type
Article
Date
Jan-2011
Author
Kenneth S Kendler
Steven H Aggen
Gun Peggy Knudsen
Espen Røysamb
Michael C Neale
Ted Reichborn-Kjennerud
Author Affiliation
Virginia Institute for Psychiatric and Behavioral Genetics, the Department of Psychiatry, Virginia Commonwealth University, Richmond, 23298-0126, USA. kendler@vcu.edu
Source
Am J Psychiatry. 2011 Jan;168(1):29-39
Date
Jan-2011
Language
English
Publication Type
Article
Keywords
Adult
Diagnostic and Statistical Manual of Mental Disorders
Diseases in Twins - classification - diagnosis - genetics
Environment
Genetic Predisposition to Disease
Humans
Mental Disorders - classification - diagnosis - genetics
Models, Genetic
Norway
Risk factors
Twin Studies as Topic - statistics & numerical data
Abstract
The authors sought to clarify the structure of the genetic and environmental risk factors for 22 DSM-IV disorders: 12 common axis I disorders and all 10 axis II disorders.
The authors examined syndromal and subsyndromal axis I diagnoses and five categories reflecting number of endorsed criteria for axis II disorders in 2,111 personally interviewed young adult members of the Norwegian Institute of Public Health Twin Panel.
Four correlated genetic factors were identified: axis I internalizing, axis II internalizing, axis I externalizing, and axis II externalizing. Factors 1 and 2 and factors 3 and 4 were moderately correlated, supporting the importance of the internalizing-externalizing distinction. Five disorders had substantial loadings on two factors: borderline personality disorder (factors 3 and 4), somatoform disorder (factors 1 and 2), paranoid and dependent personality disorders (factors 2 and 4), and eating disorders (factors 1 and 4). Three correlated environmental factors were identified: axis II disorders, axis I internalizing disorders, and externalizing disorders versus anxiety disorders.
Common axis I and II psychiatric disorders have a coherent underlying genetic structure that reflects two major dimensions: internalizing versus externalizing, and axis I versus axis II. The underlying structure of environmental influences is quite different. The organization of common psychiatric disorders into coherent groups results largely from genetic, not environmental, factors. These results should be interpreted in the context of unavoidable limitations of current statistical methods applied to this number of diagnostic categories.
Notes
Cites: Behav Genet. 1994 May;24(3):239-587945154
Cites: J Abnorm Psychol. 1998 May;107(2):216-279604551
Cites: Soc Psychiatry Psychiatr Epidemiol. 1998 Nov;33(11):568-789803825
Cites: Arch Gen Psychiatry. 1999 Oct;56(10):921-610530634
Cites: Behav Genet. 2004 Nov;34(6):593-61015520516
Cites: J Pers Disord. 2005 Apr;19(2):110-3015899712
Cites: Acta Psychiatr Scand. 2005 Sep;112(3):208-1416095476
Cites: J Pers Disord. 2005 Jun;19(3):233-6116175735
Cites: Am J Psychiatry. 2005 Oct;162(10):1919-2516199839
Cites: Am J Psychiatry. 2005 Oct;162(10):1941-716199842
Cites: J Abnorm Psychol. 2005 Nov;114(4):494-50416351373
Cites: Compr Psychiatry. 2006 May-Jun;47(3):178-8416635645
Cites: Psychol Med. 2006 Jul;36(7):955-6216650346
Cites: Am J Psychiatry. 2006 Jul;163(7):1138-4616816216
Cites: Psychol Med. 2006 Nov;36(11):1593-60016882356
Cites: Psychol Med. 2006 Nov;36(11):1583-9116893481
Cites: Twin Res Hum Genet. 2006 Dec;9(6):858-6417254421
Cites: Psychol Med. 2007 May;37(5):645-5317134532
Cites: Psychol Med. 2007 May;37(5):655-6517224098
Cites: Am J Psychiatry. 2007 Nov;164(11):1722-817974938
Cites: Am J Psychiatry. 2007 Dec;164(12):1866-72; quiz 192418056242
Cites: Psychol Med. 2008 Nov;38(11):1617-2518275631
Cites: Arch Gen Psychiatry. 2008 Dec;65(12):1438-4619047531
Cites: Curr Psychiatry Rep. 2009 Feb;11(1):89-9319187715
Cites: Psychol Med. 2009 Mar;39(3):463-7318485259
Cites: Twin Res Hum Genet. 2009 Apr;12(2):158-6819335186
Cites: Am J Psychiatry. 2009 May;166(5):540-5619339359
Cites: Br J Psychiatry. 2009 Oct;195(4):301-719794197
Cites: Harv Rev Psychiatry. 2000 Dec;8(6):283-9711133823
Cites: Am J Med Genet. 2000 Oct 9;96(5):684-9511054778
Cites: Arch Gen Psychiatry. 2001 Jun;58(6):590-611386989
Cites: Arch Gen Psychiatry. 2001 Jun;58(6):597-60311386990
Cites: Am J Psychiatry. 2001 Jul;158(7):1091-811431231
Cites: Eur Addict Res. 2003 Jan;9(1):8-1712566793
Cites: Twin Res. 2002 Oct;5(5):415-2312613498
Cites: Twin Res. 2003 Jun;6(3):235-912855073
Cites: Arch Gen Psychiatry. 2003 Sep;60(9):929-3712963675
Cites: J Pers Disord. 2000 Spring;14(1):17-2910746202
Cites: Arch Gen Psychiatry. 2004 Sep;61(9):922-815351771
Cites: Am J Psychiatry. 1970 Jan;126(7):983-75409569
Cites: J Psychiatr Res. 1994 Jan-Feb;28(1):57-848064641
Comment In: Am J Psychiatry. 2011 Jan;168(1):1-321205810
PubMed ID
20952461 View in PubMed
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Measurement non-invariance of DSM-IV narcissistic personality disorder criteria across age and sex in a population-based sample of Norwegian twins.

https://arctichealth.org/en/permalink/ahliterature100526
Source
Int J Methods Psychiatr Res. 2010 Sep;19(3):156-66
Publication Type
Article
Date
Sep-2010
Author
Thomas S Kubarych
Steven H Aggen
Kenneth S Kendler
Sven Torgersen
Ted Reichborn-Kjennerud
Michael C Neale
Author Affiliation
Department of Psychiatry, Virginia Commonwealth University, P.O. Box 980126, Richmond, VA 23298-0126, USA. tkubarych@gmail.com
Source
Int J Methods Psychiatr Res. 2010 Sep;19(3):156-66
Date
Sep-2010
Language
English
Publication Type
Article
Keywords
Adult
Age Distribution
Community Health Planning
Diagnostic and Statistical Manual of Mental Disorders
Factor Analysis, Statistical
Female
Humans
Male
Norway - epidemiology
Personality Assessment - statistics & numerical data
Personality Disorders - diagnosis - epidemiology
Retrospective Studies
Sex Distribution
Young Adult
Abstract
We investigated measurement non-invariance of DSM-IV narcissistic personality disorder (NPD) criteria across age and sex in a population-based cohort sample of 2794 Norwegian twins. Age had a statistically significant effect on the factor mean for NPD. Sex had a statistically significant effect on the factor mean and variance. Controlling for these factor level effects, item-level analysis indicated that the criteria were functioning differently across age and sex. After correcting for measurement differences at the item level, the latent factor mean effect for age was no longer statistically significant. The mean difference for sex remained statistically significant after correcting for item threshold effects. The results indicate that DSM-IV NPD criteria perform differently in males and females and across age. Differences in diagnostic rates across groups may not be valid without correcting for measurement non-invariance.
PubMed ID
20632257 View in PubMed
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Personality disorders and long-term sick leave: a population-based study of young adult Norwegian twins.

https://arctichealth.org/en/permalink/ahliterature105329
Source
Twin Res Hum Genet. 2014 Feb;17(1):1-9
Publication Type
Article
Date
Feb-2014
Author
Line C Gjerde
Espen Røysamb
Nikolai Czajkowski
Gun Peggy Knudsen
Kristian Ostby
Kristian Tambs
Kenneth S Kendler
Ted Reichborn-Kjennerud
Ragnhild E Orstavik
Author Affiliation
Department of Mental Health, Norwegian Institute of Public Health, Oslo, Norway.
Source
Twin Res Hum Genet. 2014 Feb;17(1):1-9
Date
Feb-2014
Language
English
Publication Type
Article
Keywords
Adult
Diagnostic and Statistical Manual of Mental Disorders
Diseases in Twins - diagnosis - genetics
Female
Humans
Interview, Psychological
Male
Norway
Personality Disorders - diagnosis - genetics - psychology
Population - genetics
Questionnaires
Sick Leave
Twins - genetics - psychology
Abstract
Personality disorders (PDs) reduce global functioning, are associated with high levels of work disability, and are thus also likely to influence long-term sick leave (LTSL). Previous research has indicated significant genetic influence on both DSM-IV PDs and LTSL. To what degree genes contributing to PDs also influence LTSL has not been investigated. The aims of the current study were to investigate which PDs were significantly associated with LTSL, to what extent the genetic contributions to these PDs account for the heritability of LTSL, and to explore the hypothesis of a causal association between PDs and LTSL. The sample consisted of 2,771 young, adult Norwegian twins, born 1967-1979. PDs were assessed using the Structured Interview for DSM-IV Personality (SIDP-IV). The age range for the interview was 20-32. The data were subsequently linked to public records of LTSL (sick leave >16 days) up to 11 years later. The odds ratio for being in the highest LTSL category (>15% sick leave) when fulfilling the DSM-IV criteria for any PD diagnosis was 2.6 (1.8-3.8, 95% CI). Dimensional representations of schizotypal, paranoid, and borderline PD were independently and significantly associated with LTSL. The heritability of LTSL was 0.50. Genetic factors shared with the PDs accounted for 20% of this. The association between PDs and LTSL was due to shared genetic and not environmental influences, and was mainly explained by one common genetic factor. The hypothesis of a causal association was not supported, indicating that the association is explained by overlapping genetic liability between PDs and LTSL.
PubMed ID
24417773 View in PubMed
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Major depression and life satisfaction: a population-based twin study.

https://arctichealth.org/en/permalink/ahliterature120281
Source
J Affect Disord. 2013 Jan 10;144(1-2):51-8
Publication Type
Article
Date
Jan-10-2013
Author
Ragnhild B Nes
Nikolai O Czajkowski
Espen Røysamb
Ragnhild E Orstavik
Kristian Tambs
Ted Reichborn-Kjennerud
Author Affiliation
Division of Mental Health, The Norwegian Institute of Public Health, Oslo, Norway. Ragnhild.bang.nes@fhi.no
Source
J Affect Disord. 2013 Jan 10;144(1-2):51-8
Date
Jan-10-2013
Language
English
Publication Type
Article
Keywords
Adolescent
Adult
Depressive Disorder, Major - diagnosis - epidemiology
Diagnostic and Statistical Manual of Mental Disorders
Diseases in Twins - diagnosis - epidemiology
Female
Humans
Interview, Psychological
Male
Norway - epidemiology
Personal Satisfaction
Prevalence
Questionnaires
Risk factors
Young Adult
Abstract
The extent to which positive and negative indicators of mental health share etiological influences has been studied to a limited degree only. This study examines the genetic and environmental influences on association between liability to lifetime DSM-IV Major Depressive Disorder (MDD) and dispositional life satisfaction (LS).
Two-wave questionnaire data on LS (assessed 6 years apart) and lifetime MDD obtained by structured clinical interviews in a population-based sample of adult twins were analysed using structural equation modelling in Mx.
The prevalence of lifetime MDD was estimated to be 11.1% and 15.8% in males and females, respectively. Individuals fulfilling the criteria for MDD reported significantly lower levels of LS. The co-variation in MDD and dispositional LS was found to be accounted for by genetic and unique environmental influences only. The phenotypic correlation was estimated to be 0.36, of which genetic influences accounted for 74% and environmental factors the remaining 26%. The correlation between genetic factors for MDD and LS was estimated to be -0.55 and the correlation between unique environmental factors to be -0.22. Heritability was estimated to 0.34 and 0.72 for MDD and LS, respectively.
The sample consists of twins only and there are limitations associated with the twin design.
Whereas genetic influences on vulnerability to lifetime MDD are considerably shared with liability to (low) LS, environmental influences are more distinct. Thus, environmental factors associated with risk of MDD do not strongly impact on dispositional LS, and conversely, environmental factors influencing dispositional LS do not strongly buffer against MDD.
Notes
Cites: Annu Rev Clin Psychol. 2006;2:111-3317716066
Cites: Am J Psychiatry. 2007 Dec;164(12):1866-72; quiz 192418056242
Cites: Psychol Sci. 2008 Mar;19(3):205-1018315789
Cites: J Affect Disord. 2007 Apr;99(1-3):133-817023051
Cites: J Pers Soc Psychol. 2008 Nov;95(5):1045-6218954193
Cites: Twin Res Hum Genet. 2009 Apr;12(2):158-6819335186
Cites: Behav Genet. 2009 May;39(3):277-8419360463
Cites: Behav Genet. 2009 Nov;39(6):605-1519728071
Cites: Psychol Med. 2010 May;40(5):801-619732485
Cites: J Consult Clin Psychol. 2010 Apr;78(2):169-8320350028
Cites: Behav Genet. 2010 Sep;40(5):577-9020440640
Cites: Am J Public Health. 2010 Dec;100(12):2379-8420966361
Cites: Arch Gen Psychiatry. 2011 Jan;68(1):90-10021199968
Cites: J Hum Genet. 2011 Jun;56(6):456-921562513
Cites: Behav Genet. 2011 Sep;41(5):641-5021451959
Cites: Am J Psychiatry. 2000 Oct;157(10):1552-6211007705
Cites: Am Psychol. 2001 Mar;56(3):218-2611315248
Cites: Psychiatry Res. 2001 May 10;102(1):73-8511368842
Cites: J Pers Soc Psychol. 2001 May;80(5):804-1311374751
Cites: Twin Res. 2002 Oct;5(5):415-2312613498
Cites: Soc Psychiatry Psychiatr Epidemiol. 2003 May;38(5):244-812719839
Cites: Mol Psychiatry. 2003 May;8(5):471-8412808427
Cites: JAMA. 2003 Jun 18;289(23):3095-10512813115
Cites: Arch Gen Psychiatry. 2003 Sep;60(9):929-3712963675
Cites: Psychol Med. 2004 Feb;34(2):221-814982128
Cites: Am J Med Genet B Neuropsychiatr Genet. 2004 May 15;127B(1):85-915108187
Cites: J Psychosom Res. 2004 Jul;57(1):35-4315256293
Cites: Clin Genet. 1983 Aug;24(2):103-126577993
Cites: Acta Psychiatr Scand. 1993 May;87(5):364-78517178
Cites: Science. 1996 Nov 29;274(5292):1527-318929413
Cites: Am J Psychiatry. 1997 Jan;154(1):99-1058988966
Cites: Psychol Med. 1997 May;27(3):539-479153675
Cites: Am J Psychiatry. 1998 Mar;155(3):373-99501748
Cites: Soc Psychiatry Psychiatr Epidemiol. 1998 Nov;33(11):568-789803825
Cites: Am J Psychiatry. 1999 Jun;156(6):837-4110360120
Cites: Arch Gen Psychiatry. 1999 Oct;56(10):921-610530634
Cites: Soc Psychiatry Psychiatr Epidemiol. 2004 Dec;39(12):994-915583908
Cites: Am J Psychiatry. 2005 Jun;162(6):1171-815930066
Cites: Am Psychol. 2005 Oct;60(7):678-8616221001
Cites: J Pers Soc Psychol. 2005 Sep;89(3):395-40616248721
Cites: J Affect Disord. 2005 Dec;89(1-3):79-8916249035
Cites: Psychol Bull. 2005 Nov;131(6):803-5516351326
Cites: Am J Psychiatry. 2006 Jan;163(1):109-1416390897
Cites: Am J Psychiatry. 2006 May;163(5):857-6416648327
Cites: Psychol Med. 2006 Jul;36(7):1033-4216749947
Cites: Twin Res Hum Genet. 2006 Aug;9(4):481-916899154
Cites: Twin Res Hum Genet. 2006 Dec;9(6):858-6417254421
PubMed ID
23021825 View in PubMed
Less detail

The heritability of Cluster B personality disorders assessed both by personal interview and questionnaire.

https://arctichealth.org/en/permalink/ahliterature117609
Source
J Pers Disord. 2012 Dec;26(6):848-66
Publication Type
Article
Date
Dec-2012
Author
Svenn Torgersen
John Myers
Ted Reichborn-Kjennerud
Espen Røysamb
Thomas S Kubarych
Kenneth S Kendler
Author Affiliation
Center for Child and Adolescent Mental Health Eastern and Southern Norway, PO Box 4623, Nydalen, NO-0405 Oslo, Norway. svenn.torgersen@psykologi.uio.no
Source
J Pers Disord. 2012 Dec;26(6):848-66
Date
Dec-2012
Language
English
Publication Type
Article
Keywords
Adult
Diagnostic and Statistical Manual of Mental Disorders
Diseases in Twins - diagnosis - genetics
Female
Humans
Interview, Psychological
Male
Norway
Personality - genetics
Personality Disorders - diagnosis - genetics
Questionnaires
Self Report
Social Environment
Twins - genetics
Abstract
Whereas the heritability of common personality traits has been firmly established, the results of the few published studies on personality disorders (PDs) are highly divergent, with some studies finding high heredity and others very low. A problem with assessing personality disorders by means of interview is errors connected with interviewer bias. A way to overcome the problem is to use self-report questionnaires in addition to interviews. This study used both interview and questionnaire for assessing DSM-IV Cluster B personality disorders: antisocial personality disorder (APD), borderline (BPD), narcissistic (NPD), and histrionic (HPD). We assessed close to 2,800 twins from the Norwegian Institute of Public Health Twin Panel using a self-report questionnaire and, a few years later, the Structured Interview for DSM-IV Personality (SIDP-IV). Items from the self-report questionnaire that best predicted the PDs captured by the interview were then selected. Measurement models combining questionnaire and interview information were applied and were fitted using Mx. Whereas the heritability of Cluster B PDs assessed by interview was around .30, and around .40-.50 when assessed by self-report questionnaire, the heritability of the convergent latent factor, including information from both interview and self-report questionnaire was .69 for APD, .67 for BPD, .71 for NPD, and .63 for HPD. As is usually found for personality, the effect of shared-in families (familial) environment was zero. In conclusion, when both interview and self-report questionnaire are taken into account, the heritability of Cluster B PD appears to be in the upper range of previous findings for mental disorders.
Notes
Cites: Clin Psychol Rev. 2008 Dec;28(8):1326-4218708274
Cites: Arch Gen Psychiatry. 2008 Dec;65(12):1438-4619047531
Cites: Twin Res Hum Genet. 2009 Apr;12(2):158-6819335186
Cites: J Pers Disord. 2002 Aug;16(4):317-3112224125
Cites: Twin Res. 2003 Jun;6(3):235-912855073
Cites: Clin Psychol Rev. 2004 Jan;23(8):1055-8514729423
Cites: J Pers Disord. 2004 Aug;18(4):379-9315342324
Cites: Arch Gen Psychiatry. 1966 Jun;14(6):624-305934871
Cites: J Nerv Ment Dis. 1980 Jul;168(7):428-357400793
Cites: Arch Gen Psychiatry. 1980 Nov;37(11):1272-77192083
Cites: Acta Genet Med Gemellol (Roma). 1980;29(3):193-2077196669
Cites: Am J Psychiatry. 1985 May;142(5):627-303985201
Cites: Compr Psychiatry. 1988 May-Jun;29(3):304-83378417
Cites: Acta Genet Med Gemellol (Roma). 1991;40(1):7-201950353
Cites: Arch Gen Psychiatry. 1994 Mar;51(3):225-458122959
Cites: J Pers. 1996 Sep;64(3):577-918776880
Cites: Acta Psychiatr Scand. 1996 Dec;94(6):438-449020996
Cites: Acta Psychiatr Scand. 1997 Apr;95(4):336-429150829
Cites: J Pers Soc Psychol. 1998 Apr;74(4):985-959569654
Cites: Psychol Med. 1998 Jul;28(4):857-709723141
Cites: Br J Psychol. 1998 Nov;89 ( Pt 4):647-619854807
Cites: Curr Psychiatry Rep. 2005 Mar;7(1):51-615717987
Cites: J Pers Disord. 2005 Aug;19(4):440-6116178684
Cites: Am J Psychiatry. 2005 Oct;162(10):1941-716199842
Cites: Am J Psychiatry. 2006 May;163(5):827-3216648323
Cites: Psychol Med. 2006 Nov;36(11):1583-9116893481
Cites: Psychol Med. 2007 May;37(5):645-5317134532
Cites: Psychol Med. 2007 May;37(5):655-6517224098
Cites: J Affect Disord. 2008 Mar;106(3):229-4017692389
Cites: Compr Psychiatry. 2000 May-Jun;41(3):206-1510834630
Cites: Compr Psychiatry. 2000 Nov-Dec;41(6):416-2511086146
Cites: Behav Genet. 2000 May;30(3):223-3311105396
Cites: J Pers Disord. 2000 Winter;14(4):300-1511213788
Cites: J Pers Disord. 2001 Feb;15(1):33-4011236813
Cites: Arch Gen Psychiatry. 2001 Jun;58(6):590-611386989
Cites: Arch Gen Psychiatry. 2001 Nov;58(11):1005-1411695946
Cites: J Abnorm Psychol. 2002 Aug;111(3):411-2412150417
Cites: Annu Rev Clin Psychol. 2008;4:247-7417716041
Cites: Psychol Med. 2008 Nov;38(11):1617-2518275631
PubMed ID
23281671 View in PubMed
Less detail

Genetic and Environmental Structure of DSM-IV Criteria for Antisocial Personality Disorder: A Twin Study.

https://arctichealth.org/en/permalink/ahliterature288056
Source
Behav Genet. 2017 May;47(3):265-277
Publication Type
Article
Date
May-2017
Author
Tom Rosenström
Eivind Ystrom
Fartein Ask Torvik
Nikolai Olavi Czajkowski
Nathan A Gillespie
Steven H Aggen
Robert F Krueger
Kenneth S Kendler
Ted Reichborn-Kjennerud
Source
Behav Genet. 2017 May;47(3):265-277
Date
May-2017
Language
English
Publication Type
Article
Keywords
Adult
Antisocial Personality Disorder - genetics
Diagnostic and Statistical Manual of Mental Disorders
Diseases in Twins - genetics
Environment
Female
Genotype
Humans
Male
Norway
Phenotype
Twins, Dizygotic - genetics
Twins, Monozygotic - genetics
Young Adult
Abstract
Results from previous studies on DSM-IV and DSM-5 Antisocial Personality Disorder (ASPD) have suggested that the construct is etiologically multidimensional. To our knowledge, however, the structure of genetic and environmental influences in ASPD has not been examined using an appropriate range of biometric models and diagnostic interviews. The 7 ASPD criteria (section A) were assessed in a population-based sample of 2794 Norwegian twins by a structured interview for DSM-IV personality disorders. Exploratory analyses were conducted at the phenotypic level. Multivariate biometric models, including both independent and common pathways, were compared. A single phenotypic factor was found, and the best-fitting biometric model was a single-factor common pathway model, with common-factor heritability of 51% (95% CI 40-67%). In other words, both genetic and environmental correlations between the ASPD criteria could be accounted for by a single common latent variable. The findings support the validity of ASPD as a unidimensional diagnostic construct.
Notes
Cites: Psychol Methods. 2012 Jun;17(2):228-4322309957
Cites: Twin Res. 2003 Jun;6(3):235-912855073
Cites: Dev Psychopathol. 2012 Aug;24(3):969-8322781866
Cites: Behav Genet. 1997 Mar;27(2):113-209145549
Cites: Biol Psychiatry. 2012 Feb 1;71(3):247-5321762879
Cites: Personal Disord. 2010 Jan;1(1):22-3722448603
Cites: Behav Genet. 2014 Nov;44(6):591-60424162101
Cites: Twin Res Hum Genet. 2009 Apr;12(2):158-6819335186
Cites: Int J Law Psychiatry. 2009 Jan-Feb;32(1):10-719064289
Cites: Am J Med Genet B Neuropsychiatr Genet. 2016 Jul;171(5):562-7226087016
Cites: Psychometrika. 1965 Jun;30:179-8514306381
Cites: Psychometrika. 2011 Apr 1;76(2):306-31723258944
Cites: Psychol Med. 2006 Nov;36(11):1571-8116836795
Cites: Am J Psychiatry. 2006 Jul;163(7):1138-4616816216
Cites: Am J Psychiatry. 2005 Oct;162(10):1941-716199842
Cites: Transl Psychiatry. 2015 Apr 28;5:e55825918995
Cites: PLoS One. 2012;7(10):e4508623077488
Cites: Neurosci Biobehav Rev. 2011 Jun;35(7):1562-9221145350
Cites: J Pers Disord. 1997 Summer;11(2):168-769203111
Cites: Am J Psychiatry. 2016 Sep 1;173(9):903-1027056607
Cites: Personal Disord. 2016 Jul;7(3):229-3926914324
Cites: Arch Gen Psychiatry. 2008 Dec;65(12):1438-4619047531
Cites: J Pers Disord. 2005 Apr;19(2):131-5515899713
Cites: Dev Psychopathol. 2002 Spring;14(2):395-41612030698
Cites: Psychol Med. 2008 Nov;38(11):1617-2518275631
Cites: Psychol Med. 2007 Jan;37(1):15-2617049102
Cites: J Abnorm Psychol. 2006 May;115(2):221-3016737387
Cites: Twin Res Hum Genet. 2005 Dec;8(6):553-6816354497
Cites: JAMA Psychiatry. 2013 Nov;70(11):1206-1424048243
Cites: Twin Res Hum Genet. 2006 Aug;9(4):481-916899154
Cites: Psychol Med. 1992 Feb;22(1):85-1001574568
Cites: J Pers. 2015 Dec;83(6):678-9225181550
Cites: Twin Res. 2002 Oct;5(5):415-2312613498
Cites: Arch Gen Psychiatry. 2001 Jun;58(6):590-611386989
Cites: Multivariate Behav Res. 2014 Nov-Dec;49(6):518-4326735356
Cites: Psychol Bull. 2002 May;128(3):490-52912002699
Cites: Psychol Methods. 2013 Sep;18(3):406-3323834420
Cites: Evol Med Public Health. 2016 Feb 28;2016(1):52-6626929090
Cites: J Stat Softw. 2011 Mar 1;39(8):1-3021572908
Cites: Psychol Med. 2015 Oct;45(14 ):3121-3126050739
Cites: Behav Res Methods. 2013 Sep;45(3):782-9123307573
Cites: JAMA Psychiatry. 2013 Jan;70(1):78-8623117573
Cites: Compr Psychiatry. 2006 Jul-Aug;47(4):289-9716769304
Cites: Stat Med. 2011 Nov 10;30(25):3050-621805487
Cites: Behav Genet. 2014 Sep;44(5):427-4424902785
Cites: Psychol Med. 2014 Apr;44(5):1005-1323834781
Cites: Compr Psychiatry. 2010 Jul-Aug;51(4):426-3320579518
Cites: J Abnorm Psychol. 2007 Feb;116(1):166-7517324027
Cites: Behav Genet. 2004 Nov;34(6):593-61015520516
Cites: J Pers Disord. 2012 Dec;26(6):848-6623281671
Cites: Psychol Med. 2002 Jul;32(5):829-4212171377
Cites: Psychol Rev. 2006 Oct;113(4):842-6117014305
PubMed ID
28108863 View in PubMed
Less detail

Structure of genetic and environmental risk factors for dimensional representations of DSM-IV anxiety disorders.

https://arctichealth.org/en/permalink/ahliterature148257
Source
Br J Psychiatry. 2009 Oct;195(4):301-7
Publication Type
Article
Date
Oct-2009
Author
Kristian Tambs
Nikolai Czajkowsky
Espen Røysamb
Michael C Neale
Ted Reichborn-Kjennerud
Steven H Aggen
Jennifer R Harris
Ragnhild E Ørstavik
Kenneth S Kendler
Author Affiliation
Department of Mental Health, Norwegian Institute of Public Health, Box 4404 Nydalen, 0403 Oslo 3, Norway. kristian.tambs@fhi.no
Source
Br J Psychiatry. 2009 Oct;195(4):301-7
Date
Oct-2009
Language
English
Publication Type
Article
Keywords
Adult
Anxiety Disorders - diagnosis - epidemiology - genetics
Comorbidity
Data Interpretation, Statistical
Diagnostic and Statistical Manual of Mental Disorders
Diseases in Twins - epidemiology - genetics
Female
Genetic Predisposition to Disease
Humans
Male
Norway
Phenotype
Questionnaires
Risk factors
Social Environment
Statistics as Topic
Twin Studies as Topic
Twins, Dizygotic - genetics - psychology
Twins, Monozygotic - genetics - psychology
Young Adult
Abstract
Twin data permit decomposition of comorbidity into genetically and environmentally derived correlations. No previous twin study includes all major forms of anxiety disorder.
To estimate the degree to which genetic and environmental risk factors are shared rather than unique to dimensionally scored panic disorder, generalised anxiety disorder, phobias, obsessive-compulsive disorder and post-traumatic stress disorder.
Data obtained from 2801 young-adult Norwegian twins by means of the Composite International Diagnostic Interview were analysed with the Mx program.
A multivariate common factor model fitted best. The latent liability to all anxiety disorders was substantially more heritable (54%) than the individual disorders (23% to 40%). Most of the genetic effect was common to the disorders. Genes contributed just over 50% to the covariance between liabilities.
The five anxiety disorders all share genetic and environmental risk factors. This has implications for the revision of the anxiety disorder section in DSM-V.
Notes
Cites: CNS Spectr. 2007 Nov;12(11):806-917984853
Cites: Arch Gen Psychiatry. 1999 Oct;56(10):921-610530634
Cites: Arch Gen Psychiatry. 2001 Mar;58(3):257-6511231833
Cites: Arch Gen Psychiatry. 2005 Feb;62(2):182-915699295
Cites: Twin Res Hum Genet. 2005 Oct;8(5):450-816212834
Cites: Twin Res Hum Genet. 2005 Dec;8(6):609-1516354503
Cites: Am J Psychiatry. 2006 Jan;163(1):109-1416390897
Cites: Psychol Med. 2006 Jul;36(7):955-6216650346
Cites: Cell Tissue Res. 2006 Nov;326(2):505-1616937111
Cites: Psychol Med. 2006 Nov;36(11):1593-60016882356
Cites: Am J Med Genet B Neuropsychiatr Genet. 2008 Jul 5;147B(5):586-9318040986
Cites: Arch Gen Psychiatry. 2001 Jun;58(6):597-60311386990
Cites: Psychol Med. 2001 Aug;31(6):989-100011513384
Cites: Psychiatry Res. 2001 Sep 20;103(2-3):133-4511549402
Cites: Am J Psychiatry. 2001 Oct;158(10):1568-7811578982
Cites: Behav Genet. 2002 May;32(3):221-712141783
Cites: Twin Res. 2002 Oct;5(5):415-2312613498
Cites: Scand J Psychol. 2003 Apr;44(2):97-10612778977
Cites: J Anxiety Disord. 2004;18(6):799-80715474853
Cites: Arch Gen Psychiatry. 1989 Dec;46(12):1093-1012589923
Cites: Arch Gen Psychiatry. 1992 Sep;49(9):716-221514877
Cites: Acta Psychiatr Scand. 1993 May;87(5):364-78517178
Cites: Acta Psychiatr Scand. 1993 Aug;88(2):85-928213211
Cites: J Psychiatr Res. 1995 Mar-Apr;29(2):95-1107666382
Cites: Psychol Med. 1995 Sep;25(5):1037-498588001
Cites: J Abnorm Psychol. 1998 May;107(2):216-279604551
Cites: Psychol Med. 1999 May;29(3):539-5310405076
Cites: Psychol Med. 2007 Mar;37(3):453-6217121688
PubMed ID
19794197 View in PubMed
Less detail

Genetically Informative Mediation Modeling Applied to Stressors and Personality-Disorder Traits in Etiology of Alcohol Use Disorder.

https://arctichealth.org/en/permalink/ahliterature299458
Source
Behav Genet. 2019 01; 49(1):11-23
Publication Type
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Twin Study
Date
01-2019
Author
Tom Rosenström
Nikolai Olavi Czajkowski
Eivind Ystrom
Robert F Krueger
Steven H Aggen
Nathan A Gillespie
Espen Eilertsen
Ted Reichborn-Kjennerud
Fartein Ask Torvik
Author Affiliation
Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway. tom.rosenstrom@helsinki.fi.
Source
Behav Genet. 2019 01; 49(1):11-23
Date
01-2019
Language
English
Publication Type
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Twin Study
Keywords
Adult
Adverse Childhood Experiences
Alcoholism - etiology - genetics
Biometry
Child
Diagnostic and Statistical Manual of Mental Disorders
Diseases in Twins
Female
Gene-Environment Interaction
Humans
Life Change Events
Male
Models, Statistical
Norway
Personality
Personality Disorders - complications - genetics
Phenotype
Risk factors
Twins - genetics - psychology
Abstract
A statistical mediation model was developed within a twin design to investigate the etiology of alcohol use disorder (AUD). Unlike conventional statistical mediation models, this biometric mediation model can detect unobserved confounding. Using a sample of 1410 pairs of Norwegian twins, we investigated specific hypotheses that DSM-IV personality-disorder (PD) traits mediate effects of childhood stressful life events (SLEs) on AUD, and that adulthood SLEs mediate effects of PDs on AUD. Models including borderline PD traits indicated unobserved confounding in phenotypic path coefficients, whereas models including antisocial and impulsive traits did not. More than half of the observed effects of childhood SLEs on adulthood AUD were mediated by adulthood antisocial and impulsive traits. Effects of PD traits on AUD 5?10 years later were direct rather than mediated by adulthood SLEs. The results and the general approach contribute to triangulation of developmental origins for complex behavioral disorders.
PubMed ID
30536213 View in PubMed
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Potentially traumatic event exposure, posttraumatic stress disorder, and Axis I and II comorbidity in a population-based study of Norwegian young adults.

https://arctichealth.org/en/permalink/ahliterature122725
Source
Soc Psychiatry Psychiatr Epidemiol. 2013 Feb;48(2):215-23
Publication Type
Article
Date
Feb-2013
Author
Ananda B Amstadter
Steven H Aggen
Gun Peggy Knudsen
Ted Reichborn-Kjennerud
Kenneth S Kendler
Author Affiliation
Department of Psychiatry, Virginia Institute of Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA 23298-0126, USA. abamstadter@vcu.edu
Source
Soc Psychiatry Psychiatr Epidemiol. 2013 Feb;48(2):215-23
Date
Feb-2013
Language
English
Publication Type
Article
Keywords
Adult
Borderline Personality Disorder - diagnosis - epidemiology - psychology
Comorbidity
Cross-Sectional Studies
Diagnostic and Statistical Manual of Mental Disorders
Female
Humans
Interviews as Topic
Life Change Events
Logistic Models
Male
Norway - epidemiology
Population Surveillance
Prevalence
Psychiatric Status Rating Scales
Questionnaires
Sex Distribution
Socioeconomic Factors
Stress Disorders, Post-Traumatic - diagnosis - epidemiology - psychology
Young Adult
Abstract
Epidemiologic research on traumatic stress is limited in Norway. Prevalence and correlates of exposure to potentially traumatic events (PTEs) and posttraumatic stress disorder (PTSD), and patterns of comorbidity with DSM-IV Axis I and II disorders were examined in an epidemiologic sample.
Demographics, PTEs and resulting PTSD, and comorbid DSM-IV diagnoses were assessed in 2,794 members of the Norwegian Institute of Public Health Twin Panel. The sample comprised 37% male, with an average age of 28.2 years (SD = 3.9).
Approximately, one-quarter of participants had lifetime PTE exposure; most PTEs were more common in men than in women. Lifetime prevalence of PTSD was 2.6%, and was significantly more common in women than men. Being female and type of PTE (both interpersonal and accidental traumatic events) were associated with increased PTSD symptoms, whereas higher education was associated with lower symptoms. PTSD was related to increased odds of most Axis I and II conditions.
PTE exposure and PTSD prevalence were lower than in the USA, but comparable to other European countries. Sex differences replicated previous research. The relationship between PTSD and borderline personality disorder was significantly stronger than the relationship between PTSD and any other Axis II conditions.
Notes
Cites: Arch Gen Psychiatry. 2008 Dec;65(12):1438-4619047531
Cites: J Anxiety Disord. 2011 Apr;25(3):411-2121131171
Cites: J Anxiety Disord. 2011 Apr;25(3):456-6521168991
Cites: J Pers Disord. 2011 Aug;25(4):448-6221838561
Cites: Int J Psychiatry Clin Pract. 2011 Nov;15(4):275-922122002
Cites: Acta Psychiatr Scand. 2000 Jan;101(1):46-5910674950
Cites: Arch Gen Psychiatry. 2001 Jun;58(6):590-611386989
Cites: Psychiatry Res. 2001 Sep 20;103(2-3):133-4511549402
Cites: Psychol Med. 2001 Oct;31(7):1237-4711681550
Cites: Psychol Bull. 2003 Jan;129(1):52-7312555794
Cites: Twin Res. 2002 Oct;5(5):415-2312613498
Cites: J Consult Clin Psychol. 2003 Aug;71(4):692-70012924674
Cites: Acta Psychiatr Scand Suppl. 2004;(420):28-3715128385
Cites: Arch Gen Psychiatry. 1991 Mar;48(3):216-221996917
Cites: J Consult Clin Psychol. 1993 Dec;61(6):984-918113499
Cites: J Psychiatr Res. 1994 Jan-Feb;28(1):57-848064641
Cites: Arch Gen Psychiatry. 1995 Dec;52(12):1048-607492257
Cites: Soc Psychiatry Psychiatr Epidemiol. 1998 Nov;33(11):568-789803825
Cites: Ann N Y Acad Sci. 2004 Dec;1032:104-1615677398
Cites: Psychiatry Res. 2005 Apr 15;134(2):169-7915840418
Cites: Arch Gen Psychiatry. 2005 Jun;62(6):593-60215939837
Cites: Am J Psychiatry. 2005 Oct;162(10):1941-716199842
Cites: Am J Psychiatry. 2006 May;163(5):857-6416648327
Cites: Psychol Med. 2006 Nov;36(11):1583-9116893481
Cites: Psychol Med. 2007 May;37(5):645-5317134532
Cites: Biol Psychiatry. 2007 Sep 15;62(6):553-6417217923
Cites: Depress Anxiety. 2007;24(8):577-8517136754
Cites: Compr Psychiatry. 2008 May-Jun;49(3):297-30418396190
Cites: Psychol Med. 2008 Nov;38(11):1617-2518275631
Cites: J Trauma Stress. 2008 Oct;21(5):455-6218956444
Cites: Clin Psychol Rev. 2008 Dec;28(8):1326-4218708274
Cites: Acta Psychiatr Scand Suppl. 2004;(420):8-2015128383
Cites: J Anxiety Disord. 2009 Mar;23(2):240-618774260
Cites: Twin Res Hum Genet. 2009 Apr;12(2):158-6819335186
Cites: Trauma Violence Abuse. 2009 Jul;10(3):198-21019406860
Cites: PLoS Med. 2009 Aug;6(8):e100012319668361
Cites: J Trauma Stress. 2009 Aug;22(4):259-6719645050
Cites: Am J Psychiatry. 2011 Jan;168(1):29-3920952461
Cites: Acta Psychiatr Scand Suppl. 2004;(420):21-715128384
PubMed ID
22782308 View in PubMed
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Psychiatric and medical symptoms in binge eating in the absence of compensatory behaviors.

https://arctichealth.org/en/permalink/ahliterature9364
Source
Obes Res. 2004 Sep;12(9):1445-54
Publication Type
Article
Date
Sep-2004
Author
Ted Reichborn-Kjennerud
Cynthia M Bulik
Patrick F Sullivan
Kristian Tambs
Jennifer R Harris
Author Affiliation
Division of Epidemiology, The Norwegian Institute of Public Health, P.O. Box 4404 Nydalen, N-0403 Oslo, Norway. ted.reichborn-kjennerud@fhi.no.
Source
Obes Res. 2004 Sep;12(9):1445-54
Date
Sep-2004
Language
English
Publication Type
Article
Keywords
Adult
Anxiety - epidemiology
Behavior
Body mass index
Bulimia - physiopathology - psychology
Depression - epidemiology
Female
Health status
Humans
Longitudinal Studies
Male
Norway
Obesity - epidemiology
Personal Satisfaction
Research Support, Non-U.S. Gov't
Abstract
OBJECTIVE: To explore the extent to which binge eating in the absence of compensatory behaviors (BE) is associated with psychiatric and medical symptoms in men and women and to control for the independent effects of BMI. RESEARCH METHODS AND PROCEDURES: A series of regression models was applied to questionnaire data on 8045 twins, 18 to 31 years old, from a population-based Norwegian registry. RESULTS: BE was significantly associated with elevated obesity, overweight, symptoms of eating disorders, symptoms of anxiety and depression, panic attacks, depressive episodes, and reduced life satisfaction in both men and women. In women, BE was independently associated with insomnia and early menarche. In men, BE was independently associated with specific phobia, daily smoking, alcohol use, use of pain medication, impairment due to mental health, neck-shoulder, lower back, and chronic muscular pain, and impairment due to physical health. Both men and women with BE reported higher rates of psychiatric treatment. DISCUSSION: Our results indicate that there is substantial comorbidity between BE and psychiatric symptoms independently of BMI for both men and women. Medical symptoms co-occur less frequently than previously reported from treatment-seeking populations in women. Across all domains, the array of symptoms exhibited by men with BE was broader than that observed in women with BE. This observation suggests the importance of considering gender differences in future studies of psychiatric and medical morbidity, binge eating, and obesity.
PubMed ID
15483209 View in PubMed
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Maternal Symptoms of Anxiety and Depression and Child Nocturnal Awakenings at 6 and 18 Months.

https://arctichealth.org/en/permalink/ahliterature291902
Source
J Pediatr Psychol. 2017 Nov 01; 42(10):1156-1164
Publication Type
Journal Article
Date
Nov-01-2017
Author
Eivind Ystrom
Mari Hysing
Leila Torgersen
Hilde Ystrom
Ted Reichborn-Kjennerud
Børge Sivertsen
Author Affiliation
Department of Mental Disorders, Norwegian Institute of Public Health.
Source
J Pediatr Psychol. 2017 Nov 01; 42(10):1156-1164
Date
Nov-01-2017
Language
English
Publication Type
Journal Article
Keywords
Adult
Anxiety - psychology
Crying - psychology
Depression - psychology
Female
Humans
Infant
Longitudinal Studies
Male
Mothers - psychology
Norway
Postpartum Period - psychology
Siblings
Sleep
Sleep Deprivation - psychology
Sleep Wake Disorders - psychology
Abstract
We aim to estimate the pathways between maternal symptoms of anxiety and depression and child nocturnal awakenings via structural equation modeling using a sibling design.
Structural equation modeling on data from 14,926 sibling dyads or triads from the Norwegian Mother and Child Cohort Study.
At 6?months, we estimated the association between maternal symptoms of anxiety and child nocturnal awakenings to be owing to several nonsignificant pathways. Child nocturnal awakenings at 18?months, however, were influenced by concurrent maternal symptoms of anxiety (ß?=?.10) and depression (ß?=?.12). Neither maternal symptoms of anxiety (ß?=?.04) nor depression (ß?=?-.00) was influenced by concurrent child nocturnal awakenings.
Our findings suggest that maternal mental health influences child sleep behavior at 18?months after birth, and not vice versa. This is in support of hypotheses on maternal mental health influencing child sleep during toddlerhood.
Notes
Cites: Pediatrics. 1998 Nov;102(5 Suppl E):1298-304 PMID 9794973
Cites: Soc Sci Med. 2013 Feb;79:101-8 PMID 22858167
Cites: Pediatrics. 2008 Sep;122(3):e621-7 PMID 18762495
Cites: Pediatrics. 2012 Feb;129(2):e276-84 PMID 22218837
Cites: Pediatrics. 1991 Apr;87(4):500-4 PMID 2011427
Cites: Sleep Med. 2009 Aug;10(7):771-9 PMID 19285450
Cites: JAMA Pediatr. 2015 Jun;169(6):575-82 PMID 25867179
Cites: Am J Orthopsychiatry. 1985 Apr;55(2):237-251 PMID 3993753
Cites: Child Care Health Dev. 1994 Mar-Apr;20(2):89-100 PMID 8033332
Cites: Sleep Med Rev. 2010 Apr;14(2):89-96 PMID 19631566
Cites: Acta Psychiatr Scand. 1993 May;87(5):364-7 PMID 8517178
Cites: Pediatrics. 2013 Jun;131(6):e1874-80 PMID 23713101
Cites: Child Dev. 2012 May-Jun;83(3):939-53 PMID 22506917
Cites: Pediatrics. 2003 Mar;111(3):e203-7 PMID 12612272
Cites: BMC Med Res Methodol. 2014 Dec 17;14:133 PMID 25519494
Cites: J Child Psychol Psychiatry. 2017 Jul;58(7):779-786 PMID 28229455
Cites: J Fam Psychol. 2010 Jun;24(3):307-15 PMID 20545404
Cites: J Abnorm Child Psychol. 1988 Jun;16(3):299-315 PMID 3403812
Cites: Child Dev. 1991 Oct;62(5):918-29 PMID 1756667
Cites: Dev Psychobiol. 2013 May;55(4):334-51 PMID 22488245
Cites: Pediatrics. 2014 Feb;133(2):e346-54 PMID 24394682
Cites: Child Dev. 2009 May-Jun;80(3):860-74 PMID 19489908
Cites: J Paediatr Child Health. 1998 Jun;34(3):260-2 PMID 9633974
Cites: Child Dev. 1983 Apr;54(2):424-35 PMID 6683622
Cites: BMJ. 2002 May 4;324(7345):1062-5 PMID 11991909
Cites: Dev Psychopathol. 2006 Winter;18(1):1-16 PMID 16478549
Cites: Infant Behav Dev. 2011 Feb;34(1):1-14 PMID 20970195
Cites: Clin Psychol Rev. 2000 Aug;20(5):561-92 PMID 10860167
Cites: J Fam Psychol. 2007 Mar;21(1):67-73 PMID 17371111
Cites: Psychol Bull. 2014 Jul;140(4):1138-73 PMID 24749497
Cites: Sleep. 2009 May;32(5):599-606 PMID 19480226
Cites: Int J Epidemiol. 2011 Apr;40(2):345-9 PMID 21450688
Cites: Int J Epidemiol. 2016 Apr;45(2):382-8 PMID 27063603
Cites: J Paediatr Child Health. 2007 Jan-Feb;43(1-2):66-73 PMID 17207059
Cites: J Dev Behav Pediatr. 2014 Jun;35(5):309-16 PMID 24906032
Cites: BMC Public Health. 2012 Oct 29;12:918 PMID 23107281
Cites: Paediatr Perinat Epidemiol. 2009 Nov;23(6):597-608 PMID 19840297
Cites: J Child Psychol Psychiatry. 1987 Nov;28(6):917-28 PMID 3436997
Cites: J Child Psychol Psychiatry. 2012 Jul;53(7):806-14 PMID 22309313
PubMed ID
28369506 View in PubMed
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A population based family study of symptoms of anxiety and depression The HUNT study.

https://arctichealth.org/en/permalink/ahliterature96876
Source
J Affect Disord. 2010 May 21;
Publication Type
Article
Date
May-21-2010
Author
Nikolai Czajkowski
Espen Røysamb
Ted Reichborn-Kjennerud
Kristian Tambs
Author Affiliation
The Norwegian Institute of Public Health, Division of Mental Health, Oslo, Norway.
Source
J Affect Disord. 2010 May 21;
Date
May-21-2010
Language
English
Publication Type
Article
Abstract
OBJECTIVE: To estimate an upper limit on the heritability of self-reported symptoms of anxiety and depression in a large and population representative nuclear family sample. METHOD: The ten-item symptom checklist (SCL-10) was administered as part of a health survey in a Norwegian county. The SCL-10 is a shortened version of the SCL-25, assessing symptoms of anxiety and depression. In all, 46,064 people responded, and with data from Statistics Norway, responses of first-degree relatives could be linked. Polychoric correlations between family members score on SCL-10 were calculated, and a structural equation model was fitted to these correlations using the software package R. RESULTS: All correlations between nuclear family members were in the range of 0.12 to 0.16, indicating small but significant familial influences on SCL-10. In the best fitting model, heritability was estimated at 0.25 (95% CI=0.22-0.27), and sibling specific environmental effects could be discarded. CONCLUSIONS: The estimated upper level heritability for SCL-10 in our sample was lower than what has been reported in twin studies of similar measures.
PubMed ID
20494447 View in PubMed
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Schizophrenia susceptibility and age of diagnosis--a frailty approach.

https://arctichealth.org/en/permalink/ahliterature115118
Source
Schizophr Res. 2013 Jun;147(1):140-6
Publication Type
Article
Date
Jun-2013
Author
Elisabeth Svensson
Maria Rogvin
Christina M Hultman
Ted Reichborn-Kjennerud
Sven Sandin
Tron A Moger
Author Affiliation
Division of Mental Health, Norwegian Institute of Public Health, Norway. elisabeth.svensson@dce.au.dk
Source
Schizophr Res. 2013 Jun;147(1):140-6
Date
Jun-2013
Language
English
Publication Type
Article
Keywords
Adolescent
Adult
Age Factors
Disease Susceptibility
Female
Humans
Incidence
Male
Middle Aged
Models, Theoretical
Risk factors
Schizophrenia - diagnosis - epidemiology
Sweden - epidemiology
Young Adult
Abstract
Using a frailty model approach, we aim to evaluate the effect of early-life risk factors on susceptibility and age at diagnosis of schizophrenia. We assume paternal age and familial schizophrenia influence the susceptibility, while these and several early risk factors influence the age of diagnosis.
Schizophrenia incidence data were derived from the population-based Swedish Patient Registry; including individuals aged 18 to 45 years, diagnosed between 1974 and 2008. Data were analyzed by a frailty model, a random effects model in survival analysis, using a compound Poisson model.
15,340 incident schizophrenia cases were included. For individuals without familial schizophrenia, a protective effect was seen across most ages of diagnosis for females, low paternal age, born in rural areas, and being born in later cohorts. For individuals with familial schizophrenia, a protective effect is found for females diagnosed between ages 18 and 30 years, corresponding values were 18-25 years for low paternal age. Being born in rural areas and in the last birth cohort was protective for all. The estimated proportion of susceptible was 5% for those without familial schizophrenia and 18% for individuals with familial schizophrenia. There was no statistically significant effect of paternal age on the proportion of susceptible.
To our knowledge, this is the first regression modeling of time to schizophrenia diagnosis allowing for a non-susceptible fraction of the population, including age dependent modeling of covariate effects and an interaction. Applying frailty model to schizophrenia provide etiological clues, elucidating patterns of susceptibility and age-at-diagnosis for which early-life factors are of importance.
PubMed ID
23541033 View in PubMed
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Inhibition and working memory in young preschool children with symptoms of ADHD and/or oppositional-defiant disorder.

https://arctichealth.org/en/permalink/ahliterature257454
Source
Child Neuropsychol. 2014;20(5):607-24
Publication Type
Article
Date
2014
Author
Annette Holth Skogan
Pål Zeiner
Jens Egeland
Nina Rohrer-Baumgartner
Anne-Grethe Urnes
Ted Reichborn-Kjennerud
Heidi Aase
Author Affiliation
a Oslo University Hospital, Child and Adolescent Mental Health Research Unit , Oslo , Norway.
Source
Child Neuropsychol. 2014;20(5):607-24
Date
2014
Language
English
Publication Type
Article
Keywords
Adult
Attention Deficit Disorder with Hyperactivity - psychology
Attention Deficit and Disruptive Behavior Disorders - psychology
Child, Preschool
Cohort Studies
Comorbidity
Confounding Factors (Epidemiology)
Executive Function
Female
Humans
Inhibition (Psychology)
Male
Memory, Short-Term
Norway
Research Design
Abstract
Early symptoms of attention deficit/hyperactivity disorder (ADHD) and oppositional-defiant disorder (ODD) are associated with deficits in cognitive self-regulatory processes or executive functions (EF)s. However, the hypothesis that neurocognitive deficits underlying the two disorders are already evident during early preschool years still has limited empirical support. The present study investigated associations between symptoms of ADHD and/or ODD and two core EFs, inhibition and working memory, in a large nonclinical sample of 3-year old children.
Participants were 1045 children (554 boys, age 37-47 months), recruited from the population based Norwegian Mother and Child Cohort Study (MoBa). Relations between behavioral symptoms and measures of inhibition and working memory were studied both categorically and dimensionally.
Children with co-occurring symptoms of ADHD and ODD performed at a significantly lower level than typically developing children in 4 out of 5 EF measures. Symptoms of ADHD, both alone and in combination with ODD, were associated with reduced performance on tests of inhibition in the group comparisons. Dimensional analyses showed that performance within both EF domains contributed to variance primarily in ADHD symptom load. The associations between test results and behavioral symptoms remained significant after gender and verbal skills had been controlled.
Young preschoolers show the same pattern of relations between EF and behavioral symptoms of ADHD and/or ODD as previously described in older children diagnosed with ADHD and/or ODD. Effect sizes were generally small, indicating that measures of EF have limited clinical utility at this stage in development.
PubMed ID
24053105 View in PubMed
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