Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Prevalence and stability of mental disorders among young adults: findings from a longitudinal study

Prevalence and stability of mental disorders among young adults: findings from a longitudinal study Background: Mental disorders often have onset early in life, contribute substantially to the global disease burden, and may interfere with young people’s ability to complete age-relevant tasks in important developmental periods. However, knowledge about prevalence and course of mental disorders in young adulthood is sparse. The aim of the current study was to estimate prevalence and stability of mental disorders from the twenties to the thirties/forties. Methods: DSM-IV mental disorders were assessed with the Composite International Diagnostic Interview in two waves (1999–2004 and 2010–2011) in 1623 young adult Norwegian twins (63.2% women, aged 19–29 years in wave 1). Results: In wave 1, the 12-month prevalence of any mental disorder among people in the twenties was 19.8% (men) and 32.4% (women), anxiety disorders: 9.6% (men) and 26.7% (women), anxiety disorders excluding specific phobias: 2.5% (men) and 6.9% (women), major depressive disorder (MDD): 4.4% (men) and 7.2% (women), and alcohol use disorder (AUD): 8.7% (men) and 4.4% (women). The prevalence of any mental disorder decreased from the twenties to the thirties/ forties. This was due to a decrease in AUD and specific phobias. Anxiety disorders in the twenties predicted anxiety disorders and MDD ten years later, even when controlling for the association between these disorders in the twenties. MDD in the twenties predicted MDD ten years later. At both ages, two-week and 12-month prevalence estimates differed markedly forMDD -indicatinganepisodiccourse. Conclusions: Common mental disorders are highly prevalent among young adults in the twenties, and somewhat less prevalent in the thirties/forties. Those who suffer from one mental disorder in the twenties are at considerably increased risk for suffering from a disorder ten years later as well. This may have significant implications for young people’s ability to attain education, establish a family, and participate in occupational life. Keywords: Mental disorders, Young adulthood, Health surveys, Prevalence, Stability Background disorders ranked ninth [2]. The high rankings were a re- Mental disorders are among the most prevalent health sult of both high prevalence and the disability associated problems affecting the adult population [1]. The Global with these disorders. Estimates of 12-month prevalence Burden of Disease Study 2015 (GBD 2015) estimated of mental disorders vary between 9.6 and 27.8% in the that seven of the top 25 causes of years lived with dis- general adult population [3–8]. Mood disorders, anxiety ability (YLD) globally were mental disorders, with major disorders (including specific phobias), and alcohol use depressive disorder (MDD) ranked second and anxiety disorders (AUD) are the most prevalent disorders and are included in all the above-mentioned studies. * Correspondence: krbr@fhi.no Department of mental disorders, Norwegian Institute of Public Health, Oslo, Young adulthood Norway 5 The shift in recent decades toward longer educations and Department of Psychology, University of Oslo, Oslo, Norway Full list of author information is available at the end of the article higher age when committing to stable relationships and © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Gustavson et al. BMC Psychiatry (2018) 18:65 Page 2 of 15 having children, has led researchers to aknowledge the age anxiety at one time point, have been found to have at between 18 and 29 as an important developmental period least one of these disorders 7 years later [27]. Having a [9]. It is characterized by changes in love and work life, disorder or mental health problems in adolescence in- and frequent residental change [9, 10]. Completing educa- creases the risk of such disorders/problems in early tion and building a stable life structure are important adulthood [18, 28–30]. Findings from the NCS follow- developmental tasks in this period, while raising children up (NCS-2) showed that having MDD or generalized is an important task for later periods [9, 10]. anxiety disorder (GAD) in the twenties and thirties Mental health problems are associated with poor predicted having any of these disorders eleven years educational attainment as well as work and interpersonal later [31]. Depression seems to be more episodic than problems [11–18]. Research results indicate that half of anxiety disorders among adolescents, as shown by US adolescents’ failure to complete secondary school is higher 12-month to 30-day prevalence ratios of mood attributable to mental disorders [19]. Mental disorders than anxiety disorders [22]. are also associated with maladaptive parenting behaviors, such as low affection toward the child and inconsistent Comorbidity enforcement of rules [20]. Because mental disorders may Comorbidity between mental disorders is extensive with interfere with developmental tasks in different periods, up to 50% of those who have one mental disorder also we need to increase our knowledge about the prevalence having at least one additional comorbid mental disorder and stability of such disorders at different ages to be able [4, 7, 32]. This is also reported among young people [33]. to correctly assess the magnitude of this problem. Comorbidity seems to a large degree to be due to com- mon liablity factors for several disorders [34, 35]and is Prevalence of mental disorders in young adulthood related to severity and chronicity [27, 33, 36, 37]. Hence, Findings from the New Zealand Mental Health Survey estimates of comorbidity in different developmental (NZMHS), the Dutch Tracking Adolescents’ Individual periods may increase our understanding of the potential Lives Survey (TRAILS), the US National Comorbidity effects of common mental disorders on young adults. Survey (NCS) and its replication (NCS-R), and the Children in the Community Study (CICS) from the US, show 12-month prevalence estiatmes of MDD between Need for further knowledge 8.3 and 12.4% among people between 18 and 33 years Current knowledge on prevalence and stability of mental [16, 21–23]. The 12-month prevalence was between 19.4 disorders among young adults relies heavily on results and 22.3% for anxiety disorders (including specific from the US and New Zealand. Longitudinal studies phobias), between 2.5 and 10.3% for acohol dependence, from several different countries are needed to inform and between 7.1 and 18.4% for alcohol abuse [21–23]. policy makers in different parts of the world and to estimate global disease burden in this age period. Stability of mental disorders in young adulthood Previous prevalence estiamtes of any mental disorder Previous studies indicate that the prevalence of depression or any anxiety disorder typically include specific phobias, is stable over the earliest part of adulthood, whereas AUD which by definiton involves imapirment in circum- decreases, and findings regarding anxiety disorders are scribed situations and can sometimes be treated in a mixed [21, 24]. In the Dunedin study from New Zealand, single therapy session [38]. Prevalence estiamtes both the 12-month prevalence of MDD was 16.8% at age including and excluding such phobias are therefore 21 years and 16.3% at 32 years [21]. The 12-month preva- needed to plan mental health services for young adults. lence of any anxiety disorder (including specific phobias) Findings are divergent with regards to whether or not was 20.3% at 21 years and 22.2% at 32 years. In the anxiety disorders become less prevalent during young Simmons Longitudinal Study from the US, prevalence adulthood. Previous studies have included different anx- estiamtes of MDD showed a weak and not statistically sig- iety disorders when examining this. There is a lack of nificant increase from age 21 to 30 (from 5.4 to 8.0%), studies tracking the episodic versus chronic nature of while there was a decline in the 12-month prevalence for MDD and anxiety disorders across young adulthood. If phobia (including specific phobias) (from 16.8 to 2.3%) depression tends to get more or less episodic over time, [24]. The prevalence of alcohol dependence declined the burden of recurrent depression will decrease or (from 18.4 to 8.1%) from age 21 to 32 in the Dunedin increase as people get older. More knowledge about the study, and the prevalence of AUD declined from 26.7 to stability of anxiety disorders and MDD from the twen- 6.0% in the Simmons Longituidnal Study [21, 24]. ties to the thirties/forties may increase our understand- Some people have long-lasting and/or recurrent epi- ing of the potential impact of such disorders on young sodes of mental disorders [25, 26]. In the general adult adult development. This is important for planning population, about 40% of those who have depression or mental health services for young adults. Gustavson et al. BMC Psychiatry (2018) 18:65 Page 3 of 15 A limitation in several previous studies of AUD is Compare 12-month to two-week prevalence estimates to different diagnostic criteria across waves and use of alcohol examine the episodic nature of disorders across these abuse as a screen for alcohol dependence [39]. This may two developmental periods, 4) Examine the degree to affect estimates of prevalence and stability of this disorder which those who have an anxiety disorder or MDD in [24, 39]. the twenties, are at increased risk of having these disor- To the best of our knowledge, no previous studies have ders ten years later, 5) Examine comorbidity of common examined prevalence and stablity in common mental dis- mental disorders among people in the twenties and ten orders by both: Following the same individuals from the years later. twenties to the thirties/forties, estimating prevalence of anxiety disorders at the different ages including as well as Methods excluding specific phobias, comparing the episodic versus Sample chronic nature of disorders at both ages, and examining Data came from the Norwegian Institute of Public comorbidity between disorders at both ages. Health Twin Panel (NIPHTP), which includes health questionnaires at two time points (Q1 and Q2), and Aims of the study diagnostic interviews at two later time points (wave 1 The overall aim of the current study was to address limi- and wave 2). The current study used data from the two tations in previous literature on prevalence and stability interviews. The NIPHTP is described thoroughly else- of common mental disorders from the twenties to the where [40–44], and recruitment is illustrated in Fig. 1. thirties/forties. More specifically, the aims were to: 1) The first wave of the interview study (wave 1) took place Estimate the 12-month prevalence of anxiety disorders between 1999 and 2004, and 2801 individuals (44% of the (with and without specific phobias), mood disorders, invited) were interviewed. All twins who had participated and AUD among people aged 19 to 29, 2) Compare in wave 1 were invited for a re-interview between 2010 these estimates to prevalence estimates ten years later, 3) and 2011 (wave 2). The follow-up participation rate from Fig. 1 Flow-chart of recruitment to the study. The current study used data from the two interview studies, indicated with bold font Gustavson et al. BMC Psychiatry (2018) 18:65 Page 4 of 15 wave 1 to wave 2 was 82.8% (n = 2284) [41]. Mean age was Manual of Mental Disorders, Fourth Edition (DSM-IV). 28.3 years (range 19–36 years) in wave 1 and 37.9 years The interview was mainly administered face-to-face in (range 30–44 years) in wave 2. Mean time between wave 1. For practical reasons, 231 interviews (8.3%) were interviews was 9.6 years (range 7–13 years). Participation conducted by telephone. To maximize response rate, all in wave 1 was predicted by increasing age and monozy- the interviews were conducted by telephone in wave 2. gosity, but not by any indicator of mental health [42]. Interviewers were mostly psychology graduate students Participation in wave 2 was predicted by high education, or experienced psychiatric nurses who had received female sex, and monozygosity. Neither the total number standardized training by certified instructors. Each twin of mental disorders nor any specific disorder in wave 1 in a pair was interviewed by a different interviewer. predicted participation in wave 2 [41]. Respondents answered one question about when they The current study aimed to examine mental disorders last experienced symptoms of each of the disorders. The in a specific developmental period (19–29 years of age) response categories were “Within the last two weeks”, and follow these individuals over time. Hence, only “Two weeks to less than a month”, “One to five months”, participants below age 30 in wave 1 were included in the “6 to 12 months”, “Last 12 months, but cannot remem- main analyses. This resulted in a sample of 597 men and ber exactly when”, and “More than one year”. Endorse- 1026 women in wave 1, and 457 men and 850 women in ment of the first option was used to estimate 2-week wave 2. Mean age in wave 1 was 25.4 years (range 19 to prevalence, endorsement of any of the first two options 29), and mean age in wave 2 was 35.3 years (range 30 to to estimate 4-week prevalence, endorsement of any of 42). Mean time between the two interviews was 9.6 years. the first three options to estimate 5(6) month- Prevalence estimates for the wider age range of the prevalence, and endorsement of any of the first five entire sample were also calculated and are presented in options to estimate 12-month-prevalence. Hence, Additional file 1: Tables S1 and S2, for readers who are individuals contributing to two-week prevalence esti- interested in prevalence of mental disorders in a wider mates were a sub-group of those contributing to all age group. other prevalence estimates of each disorder. Table 1 shows an overview of combined categories of Measures diagnoses. AUD consisted of alcohol abuse and alcohol A Norwegian version of the computerized Munich dependence. Any mood disorder consisted of MDD and Composite International Diagnostic Interview (M-CIDI), dysthymia. Any anxiety disorder W1 consisted of panic originally developed by the World Health Organization, disorder, agoraphobia without a history of panic dis- was employed in both interview waves [45]. Diagnoses order, specific phobias, social phobia, GAD, obsessive- were coded according to the Diagnostic and Statistical compulsive disorder (OCD), and post-traumatic stress Table 1 Overview of disorders included in the combined categories Combined category Includes Constructed for wave Any mood disorder MDD, Dysthymia 1 and 2 Any anxiety disorder W1 Panic disorder, Agoraphobia without a history of panic disorder, Specific phobias, Social 1 phobia, GAD, OCD, PTSD. Any Anxiety disorder W1–2 Panic disorder, Agoraphobia without a history of panic disorder, Specific phobias, Social 1 and 2 phobia, GAD. Any anxiety disorder W1–2 excluding Panic disorder, Agoraphobia without a history of panic disorder, Social phobia, GAD. 1 and 2 specific phobias AUD Alcohol abuse, Alcohol dependence. 1 and 2 Any mental disorder W1 Any mood disorder, Any anxiety disorder W1, AUD. 1 Any mental disorder W1–2 Any mood disorder, Any anxiety disorder W1–2, AUD. 1 and 2 Any mental disorder W1–2 excluding Any mood disorder, Any anxiety disorder W1–2 excluding specific phobias, AUD. 1 and 2 specific phobias Categories only presented in Supplementary table Drug use disorder Drug abuse, drug dependence. 1 Any substance use disorder Drug use disorder, AUD. 1 Any disorder W1- supplement Any mood disorder, Any anxiety disorder W1, Any substance use disorder 1 Legends: MDD Major depressive disorder, GAD Generalized anxiety disorder, OCD Obsessive-compulsive disorder, PTSD Post-traumatic stress disorder, AUD Alcohol use disorder W1 Wave 1, W2 wave 2 Gustavson et al. BMC Psychiatry (2018) 18:65 Page 5 of 15 disorder (PTSD). In wave 2, OCD and PTSD were not people who have a diagnosis across ages [48]. This was assessed. These two disorders are no longer classified as examined with logistic regression for MDD, Any anxiety anxiety disorders in DSM-5 [46]. Any anxiety disorder disorder W1–2, and AUD, adjusted for age in wave 1. W1–2 did not include these two disorders, and was con- We also examined the degree to which MDD in wave 1 structed for both waves to allow comparison of anxiety predicted having Any anxiety disorder W1–2 in wave 2, disorders across age. Any anxiety disorder W1–2 exclud- and vice versa, controlled for age. Because of low ing specific phobias consisted of all anxiety disorders number of cases and thus low statistical power, AUD measured in both waves except specific phobias. Any was not included. Men and women were collapsed in mental disorder W1 consisted of Any mood disorder, these analyses to increase statistical power. Any anxiety disorder W1, and AUD. Any mental disorder Comorbidity within each wave was examined with W1–2 consisted of Any mood disorder, Any anxiety dis- tetrachoric correlations between MDD, Any anxiety order W1–2, and AUD. Any mental disorder W1–2 disorders W1–2,and AUD. Comorbidity was also exam- excluding specific phobias consisted of Any mood ined by showing the proportion of people with one dis- disorder, Any anxiety disorder W1–2 excluding specific order, who also had another disorder, and by illustrating phobias, and AUD. how many of a hypothetical sample of 100 individuals Total as well as sex-stratified prevalence estimates are who would have either one disorder, or a combination of presented for MDD, Any mood disorder, Any anxiety two or three disorders. Men and women were collapsed. disorder (W1, W1–2, as well as W1–2 excluding specific The concordance between twins may affect results. phobias), AUD, and Any mental disorder (W1, W1–2, First, standard errors may be too small due to clustering and W1–2 excluding specific phobias). Prevalence effects [49–51]. This was adjusted for by drawing estimates for low frequent specific disorders (e.g. panic clusters (twin-pairs) rather than individuals in the disorders and dysthymia) are only presented for both bootstrapping/jackknife process and by using the robust genders together. Drug use disorders (drug addiction estimator for standard errors in logistic regression [49– and drug abuse) were only assess in wave 1, and are 51]. Second, sensitivity analyses were performed includ- presented in Additional file 1: Table S1. ing only one twin from each pair, to see if this affected We report 12-month and 2-week prevalence estimates. results. The other two measured prevalences (5(6)-month and four-week) are presented in Additional file 1: Tables S1 and S2. Interested readers may use those estimates to Results compare findings with other studies that have used Prevalence estimates estimates between 12-month and two-week (as for We report results for 597 men and 1026 women (63.2%) example [22, 47]). who participated in wave 1 (Table 2) and 457 men and 850 women (65.0%) who also participated in wave 2 Statistical analyses (Table 3). Analyses were performed in Stata version 15. Testing all In wave 1, when the participants were in the twen- the prevalence estimates for statistically significant ties, Any anxiety disorder W1 was the most prevalent gender differences would imply a large number of tests, combined category of disorders for both men and thus increasing the risk of random findings. Such testing women (see Table 2). The 12-month prevalence for was therefore only performed for the following Any anxiety disorder W1 was 9.6% (95% confidence estimates: 12-month Any mental disorder W1–2, 12- interval (CI) = 7.0–12.4) for men and 26.7% (95% CI = month Any mood disorder, 12-month Any anxiety 23.7–29.7) for women. For Any anxiety disorder W1– disorder W1–2, and 12-month AUD. 2, the 12-month prevalence was 9.3 (95% CI = 7.0– The 12-month and 2-week prevalence estimates were 12.3) for men and 26.0% (95% CI = 23.1–29.0) for compared for MDD and Any anxiety disorder W1–2. women. AUD ranked second among men (8.7% 12- Episodic disorders are expected to show higher 12- month prevalence, 95% CI = 6.5–11.3), and Any mood dis- month than 2-week prevalences whereas the prevalences order ranked second among women (8.7% 12-month are expected to be more similar for more chronic prevalence, 95% CI = 6.7–10.6). Specific phobias were disorders. highly prevalent among men and women (12-month Absolute stability was examined by comparing preva- prevalence = 7.6% with 95% CI = 5.5–10.2 for men and lence estimates at the two waves. Only those who partic- 22.3% with 95% CI = 19.5–25.0 for women). AUD and Any ipated in wave 2, were included in significance testing of mood disorder were the most common groups of disorders change in prevalence estimates, thus reducing the risk of for men, and Any mood disorder was the most common bias du to potential selective attrition. Relative stability group of disorders for women when specific phobias were refers to the degree to which it is the same or different excluded. Results from significance testing of gender Gustavson et al. BMC Psychiatry (2018) 18:65 Page 6 of 15 Table 2 Prevalence of mental disorders in wave 1 (age 19–29 years, n = 597 men and 1026 women) Men and women Men Women Ratio (women/men) of 12-month prevalence 12 month Two-week 12 month Two-week 12 month Two-week estimates (95% CI) prevalence prevalence prevalence prevalence prevalence prevalence (95% CI) (95% CI) (95% CI) (95% CI) (95% CI) (95% CI) MDD 6.2 1.3 4.4 0.8 7.2 1.6 5.0–7.4 0.7–1.8 2.8–6.3 0.2–1.6 5.5–8.8 0.9–2.4 Dysthymia 1.7 1.4 1.1–2.4 0.8–2.0 Any mood disorder 7.3 2.3 4.9 1.2 8.7 2.9 1.79*** 5.9–8.6 1.5–3.0 3.2–6.8 0.4–2.2 6.7–10.6 1.9–4.0 1.19–2.68 Any anxiety disorder W1 20.4 15.2 9.6 5.9 26.7 20.7 18.3–22.7 13.5–17.3 7.0–12.4 4.2–8.2 23.7–29.7 18.1–23.5 Any anxiety disorder W1–2 19.8 14.8 9.3 5.7 26.0 20.1 2.80*** 17.7–22.0 13.0–16.7 7.0–12.3 4.0–7.9 23.1–29.0 17.4–22.7 2.13–3.68 Any anxiety disorder W1–2 5.3 3.2 2.5 1.3 6.9 4.2 excluding specific phobias 4.2–6.6 2.3–4.1 1.3–4.2 0.5–2.6 5.3–8.7 3.0–5.7 Specific phobias 16.9 12.4 7.6 4.9 22.3 16.8 14.9–19.0 10.8–14.1 5.5–10.2 3.3–6.9 19.5–25.0 14.5–19.2 Panic disorder 1.5 0.4 1.0–2.2 0.1–0.7 Agoraphobia without panic 1.4 1.1 0.9–2.0 0.6–1.7 Social phobia 2.3 1.8 1.7–3.3 1.2–2.7 GAD 1.2 0.4 0.7–1.9 0.1–0.7 OCD 0.3 0.2 0.1–0.6 0.1–0.4 PTSD 1.2 0.7 0.7–1.8 0.4–1.2 Alcohol abuse 2.8 0.9 2.0–3.7 0.5–1.5 Alcohol Dependence 4.7 2.1 3.6–5.8 1.4–2.8 AUD 6.0 2.7 8.7 3.7 4.4 2.0 0.50*** 4.8–7.3 1.9–3.6 6.5–11.3 2.3–5.4 3.2–5.7 1.2–3.0 0.34–0.74 Gustavson et al. BMC Psychiatry (2018) 18:65 Page 7 of 15 Table 2 Prevalence of mental disorders in wave 1 (age 19–29 years, n = 597 men and 1026 women) (Continued) Men and women Men Women Ratio (women/men) of 12-month prevalence 12 month Two-week 12 month Two-week 12 month Two-week estimates (95% CI) prevalence prevalence prevalence prevalence prevalence prevalence (95% CI) (95% CI) (95% CI) (95% CI) (95% CI) (95% CI) Any mental disorder W1 27.8 18.6 19.8 9.7 32.4 23.8 25.4–30.3 16.7–20.6 16.4–23.4 7.3–12.4 29.4–35.7 21.1–26.6 Any mental disorder W1–2 27.6 18.2 19.8 9.5 32.2 23.3 1.63*** 25.3–30.2 16.2–20.1 16.4–23.4 7.1–12.2 29.2–35.4 20.7–26.0 1.35–1.96 Any mental disorder W1–2 15.3 7.3 14.3 5.6 15.9 8.3 excluding specific phobias 13.5–17.5 6.0–8.8 11.2–17.3 3.7–7.7 13.6–18.5 6.5–10.3 Legends: *** p < 0.001, MDD Major depressive disorder, GAD Generalized anxiety disorder, OCD Obsessive-compulsive disorder, PTSD Post-traumatic stress disorder, AUD Alcohol use disorders, i.e. alcohol dependence or alcohol abuse CI Confidence interval. 95% CIs are based on standard errors obtained from bootstrapping (1000 replications), bias corrected for skewness in the bootstrap distribution, and adjusted for cluster-effects among twins MDD and/or dysthymia Panic disorder, agoraphobia without panic, specific phobias, social phobia, GAD, OCD, and/or PTSD Panic disorder, agoraphobia without panic, specific phobias, social phobia and/or GAD Panic disorder, agoraphobia without panic, social phobia and/or GAD Any mood disorder, Any anxiety disorder W1, AUD Any mood disorder, Any anxiety disorder W1–2, AUD Any mood disorder, Any anxiety disorder W1–2 excluding specific phobias, AUD Gustavson et al. BMC Psychiatry (2018) 18:65 Page 8 of 15 Table 3 Prevalence of mental disorders in wave 2 (age 30–42 years, n = 457 men and 850 women) Men and women Men Women Ratio (women/men) of 12-month prevalence 12 month Two-week 12 month Two-week 12 month Two-week estimates (95% CI) prevalence prevalence prevalence prevalence prevalence prevalence (95% CI) (95% CI) (95% CI) (95% CI) (95% CI) (95% CI) MDD 5.0 1.1 3.3 0.9 5.9 1.2 3.8–6.3 0.6–1.7 1.9–5.2 0.2–1.9 4.3–7.5 0.6–2.0 Dysthymia 1.9 0.9 1.2–3.0 0.5–1.5 Any mood disorder 5.8 1.6 3.7 1.1 7.0 1.9 1.87** 4.6–7.3 1.0–2.4 2.3–5.9 0.2–2.3 5.3–8.7 1.1–3.0 1.10–3.17 Any anxiety disorder W1–2 16.1 8.3 5.9 2.9 21.6 11.2 3.63*** 13.9–18.4 6.8–9.7 4.0–8.2 1.5–4.7 18.6–24.6 9.0–13.2 2.46–5.35 Any anxiety disorder W1–2 6.5 2.6 2.6 0.9 8.5 3.5 excluding specific phobias 5.2–8.0 1.8–3.7 1.3–4.3 0.2–1.9 6.7–10.7 2.4–5.0 Specific phobias 12.3 6.5 4.1 2.2 16.8 8.8 10.3–14.3 5.2–7.9 2.4–6.1 1.0–3.9 14.1–19.5 6.9–10.8 Panic disorder 2.1 0.5 1.4–3.0 0.2–1.1 Agoraphobia without panic 1.2 0.6 0.6–1.9 0.2–1.2 Social phobia 3.9 1.4 2.9–5.2 0.7–2.1 GAD 1.5 0.5 0.9–2.2 0.2–0.9 AUD 2.7 1.2 5.3 2.4 1.3 0.5 0.25** 1.8–3.7 0.7–1.8 3.2–7.2 1.2–4.0 0.7–2.2 0.1–1.0 0.12–0.50 Any mental disorder W1–2 20.9 10.0 12.9 5.8 25.3 12.3 1.96*** 18.6–23.3 8.3–11.7 9.8–16.3 3.8–8.1 22.1–28.6 10.3–14.5 1.50–2.55 Any mental disorder W1–2 12.4 4.9 10.0 4.2 13.7 5.2 excluding specific phobias 10.5–14.4 3.6–6.2 7.3–12.6 2.5–6.2 11.4–16.3 3.7–6.9 Legends:** p < 0.01, *** p < 0.001, MDD Major depressive disorder, GAD Generalized anxiety disorder, AUD Alcohol use disorders, i.e. alcohol dependence or alcohol abuse CI Confidence interval. 95% CIs are based on standard errors obtained from bootstrapping (1000 replications), bias corrected for skewness in the bootstrap distribution and adjusted for cluster-effects among twins MDD and/or dysthymia Panic disorder, agoraphobia without panic, specific phobias, social phobia and/or GAD Panic disorder, agoraphobia without panic, social phobia and/or GAD Any mood disorder, Any anxiety disorder W1–2, AUD Any mood disorder, Any anxiety disorder W1–2 excluding specific phobias, AUD Gustavson et al. BMC Psychiatry (2018) 18:65 Page 9 of 15 difference showed that Any mental disorder W1–2, Any having these disorders ten years later. The results anxiety disorder W1–2,and Any mood disorder were more showed that Any anxiety disorder W1–2 in wave 1 pre- prevalent among women than men, while AUD was more dicted MDD in wave 2, even controlled for MDD in prevalent among men than women (see Table 2). wave 1. In wave 2, the 12-month prevalence of Any anxiety Despite relative stability from wave 1 to wave 2, 82.4% disorder W1–2 was 5.9% (95% CI = 4.0–8.2) for men and of those who had MDD, 54.9% of those who had Any 21.6% (95% CI = 18.6–24.6) for women (see Table 3). anxiety disorder W1–2, and 85.4% of those who had Again, this was mainly due to the high prevalence of AUD in Wave 1 (12-mont prevalence), did not have the specific phobias (12-month prevalence was 4.1% with same disorder in wave 2. 95% CI = 2.4–6.1 for men and 16.8% with 95% CI = 14.1–19.5 for women). Any mood disorder was the 12-month versus 2-week prevalence estimates second most prevalent group of disorders among The 12-month prevalence of MDD was significantly women (12-month prevalence 7.0% with 95% CI = higher than the 2-week prevalence in both waves. The 5.3–8.7), and AUD was the second most common dis- 12-month to two-week ratios for MDD was 4.8 (95% CI order among men (12-month prevalence = 5.3% with = 3.9–7.5) in wave 1 and 4.6 (95% CI = 3.1–8.6) in wave 95% CI = 3.2–7.2). Any mental disorder W1–2, Any 2. For Any anxiety disorder W1–2 the ratios were 1.3 mood disorder, and Any anxiety disorder W1–2, were (95% CI = 1.3–1.4) in wave 1 and 1.9 (95% CI = 1.7–2.2) more prevalent among women than men, and the re- in wave 2, indicating a more episodic nature of MDD verse was true for AUD (see Table 3). than anxiety disorders. Stability Therewas areduction in Any mental disorder W1–2, Comorbidity Specific phobias, and AUD from wave 1 to wave 2 Tetrachoric correlations between 12-month MDD, Any (95% CI for differences did not include zero). Estimates anxiety disorder W1–2, and AUD within each wave are were stable for MDD and Any anxiety disorder W1–2 presented in Table 5. There was a strong association be- excluding specific phobias (95% CI for difference included tween MDD and Any anxiety disorder W1–2 in both zero). waves. Relative stability was measured with logistic regression, Comorbidity was also examined by calculating how presented in Table 4. Having MDD, Any anxiety disorder many of those who had one disorder, also had another W1–2, or AUD in the twenties, increased the risk of disorder. The results are presented in Table 6. The co- morbidity numbers for AUD should be interpreted with Table 4 Relative stability in mental disorders from age 19–29 to caution in wave 2, as few people had this diagnosis. age 30–42 estimated with logistic regression Figure 2 shows the number of people with pure versus Disorder in W1 not MDD and Anxiety in comorbid MDD, Any anxiety disorder W1–2, and AUD adjusted for each W1 mutually adjusted other OR for each other OR in hypothetical samples of 100 men and 100 women in (95% CI) (95% CI) the twenties and in the thirties/forties. MDD in wave 2 Table 5 Tetrachoric correlations between different disorders at MDD in wave 1 3.56*** 2.60** (1.81–6.98) (1.31–5.17) wave 1 (age 19–29) and wave 2 (age 30–42) Anxiety in wave 1 2.61*** 2.18** Wave 1 Wave 2 (1.54–4.42) (1.26–3.75) MDD Anxiety AUD MDD Anxiety AUD a a W1–2 W1–2 Anxiety in wave 2 Wave 1 MDD 0.45*** 0.00 0.31** 0.38*** 0.16 MDD in wave 1 3.94*** 1.77 (2.36–6.60) (0.96–3.26) a Anxiety W1–2 0.10 0.26** 0.65*** 0.02 Anxiety in wave 1 9.01*** 8.33*** AUD 0.07 0.07 0.49*** (6.45–12.59) (5.90–11.78) Wave 2 MDD 0.54*** 0.12 AUD in wave 2 8.10*** Anxiety W1–2 0.03 AUD in wave 1 (3.69–17.76) AUD Legends: OR Odds ratio, CI Confidence interval, MDD Major depressive disorder, Anxiety = Any anxiety disorder W1–2(Panic disorder, agoraphobia without Legends: Panic disorder, agoraphobia without panic, specific phobias, social panic, specific phobias, social phobia and/or generalized anxiety disorder phobia and/or generalized anxiety disorder (GAD) (GAD)). Standard errors were obtained from the robust estimator in Stata, MDD Major depressive disorder. AUD Alcohol use disorders, i.e. alcohol accounting for cluster-effects among twins dependence or alcohol abuse. Standard errors were obtained from the Men and women were collapsed in the analyses to increase statistical power. jackknife estimator, accounting for cluster-effects among twins. **p < 0.01, All analyses were adjusted for age in wave 1 ***p < 0.001. Men and women were collapsed to increase statistical power Gustavson et al. BMC Psychiatry (2018) 18:65 Page 10 of 15 Table 6 Comorbidity wave 1 (age 19–29) and wave 2 (age 30–42) Men Women % with comorbid MDD % with comorbid % with comorbid % with comorbid % with comorbid % with comorbid a a Anxiety W1–2 AUD MDD Anxiety W1–2 AUD Wave 1 MDD 34.6 3.8 66.2 6.8 17.6–55.6 0–14.3 54.8–76.8 1.5–13.7 Anxiety W1–2 15.8 17.5 17.4 5.9 7.3–26.8 8.5–27.3 13.1–21.9 3.6–9.0 AUD 1.9 17.5 11.1 35.6 0–7.1 8.5–27.3 3.4–21.1 22.2–50.0 Wave 2 MDD 33.3 16.7 57.0 2.0 13.0–53.6 3.7–31.8 46.5–67.0 0.0–5.4 Anxiety W1–2 17.4 8.7 19.5 1.7 8.3–31.1 2.0–18.0 14.8–24.3 0.3–3.4 AUD 11.4 11.8 14.3 7.1 2.9–23.3 3.0–23.5 0.0–37.5 0.0–25.0 Legends: MDD Major depressive disorder, AUD Alcohol use disorders, i.e. alcohol dependence or alcohol abuse Panic disorder, agoraphobia without panic, specific phobias, social phobia and/or generalized anxiety disorder (GAD) Sensitivity analyses of concordance between twins W1 were estimated for a sub-sample where one twin As mentioned in the methods section, the use of twins was randomly chosen from each pair (see Table 7). The may have affected results, and sensitivity analyses were estimates were quite similar to estimates from both therefore performed. If one twin did not have any twins. The ratio of the results (estimates from the entire mental disorder during the last 12 months in wave 1, the sample/estimates from only one twin) varied between co-twin’s risk of having a mental disorder was 21.7% 1.00 and 1.04. (compared to 27.8% in the full sample). When one twin had a mental disorder, the co-twin’s risk was 43.7%. This Discussion concordance between twins was expressed in an intra- MDD, anxiety disorders, and AUD were highly prevalent class correlation of 0.21. Prevalence of MDD, Any at age 19–29. The prevalence of mental disorders was anxiety disorders W1, AUD, and Any mental disorder lower at age 30–42, and this was mainly due to decrease Fig. 2 Combinations of disorders in hypothetical groups of 100 men and 100 women at different ages. Legend: MDD = major depressive disorder, Anxiety = Any anxiety disorder W1–2 (Panic disorder, agoraphobia without panic, specific phobias, social phobia and/or generalized anxiety disorder (GAD)), AUD = alcohol use disorder (i.e. alcohol dependence and alcohol abuse) Gustavson et al. BMC Psychiatry (2018) 18:65 Page 11 of 15 Table 7 Prevalence estimates in wave 1 when using both twins versus one twin in each pair 12-month prevalence estimate 12-month prevalence estimate Ratio using both twins 95% CI only including one twin from Entire sample estimate/ each pair 95% C.I. Estimate using one twin from each pair MDD 6.2 6.2 1.00 5.0–7.4 4.5–8.0 Any anxiety disorder W1 20.4 19.6 1.04 18.3–22.7 17.2–22.5 AUD 6.0 5.8 1.03 4.8–7.3 4.4–7.5 Any mental disorder W1 27.8 27.8 1.00 25.4–30.3 24.7–31.0 Legends: CI Confidence interval, MDD Major depressive disorder Panic disorder, agoraphobia without panic, specific phobias, social phobia, generalized anxiety disorder (GAD), obsessive-compulsive disorder (OCD), and/or post-- traumatic stress disorder (PTSD) AUD Alcohol use disorders, i.e. alcohol dependence or alcohol abuse Any mental disorder W1 = Any mood disorder, Any anxiety disorder W1, AUD 95% CIs are based on standard errors obtained from bootstrapping (1000 replications), bias corrected for skewness in the bootstrap distribution, and adjusted for cluster-effects among twins in AUD and specific phobias. Prevalence estimates of very circumscrbied disorder and mental disorders that MDD and anxiety disorders excluding specific phobias affect people in more complex ways across different situa- were stable in this period. Individuals who had MDD, an tions (e.g. MDD, GAD, and AUD). anxiety disorder, or AUD in the twenties were of in- creased risk of having these disorders in the thirties/for- Stability ties compared to those who did not have these Mental disorders became less prevalent as participants diagnoses in the twenties. went from the twenties to the thirties/forties. Our results converge with findings from the Simmons Longitudinal Prevalence estimates study regarding a decrease in specific phobias and AUD The 12-month prevalence of depressive disorders in [24]. Other anxiety disorders did not become less preva- people in the twenties was lower in the current study lent in the current study. Findings from the Dunedin compared to young adults in the CICS [16], the Dunedin study showed a marked decrease in acohol dependence, study, NZMHS, NCS, and NCS-R [21, 23], but similar to and quite stable prevalence of MDD and anxiety disorders the prevalence among 26-year-olds in the Simmons longi- (including specific phobias, GAD, panic disorder, agora- tudinal study [24]. The current findings were very similar phobia, OCD, and PTSD) from age 21 to age 32 [21]. De- to results from these other studies with regard to preva- crease in AUD across young adulthood may reflect the lence of anxiety disorders in the twenties. In the Dunedin circumstances of people in the twenties, who often do not study, alcohol dependence among people aged 18 to have responsibility for children, and many are students. 32 years was more prevalent than the broader category of Results from a previous study indicate that a third of AUD in both waves in the current study [21]. Likewise, those who met diagnostic criteria for AUD in late ado- the narrower category alcohol abuse was more prevalent lescence, also met criteria for AUD at age 26 [54]. In the in TRAILS and NCS-R than AUD in the current sample current study, only about 15% of those who met diag- [22, 23]. In the Simmons longitudinal study, the preva- nostic criteria for AUD in the twenties also had AUD in lence of AUD was similar to the current results [24]. the thirties/forties. Hence, the course of AUD seems to Our findings are in line with previous studies showing be less chronic from the twenties to the thirties/forties that anxiety disorders tend to be the most prevalent than from late adolescence to age 26. Nevertheless, the group of disorders, both in the general adult population current results showed that those who had AUD in the and among young adults [21, 52]. The current results twenties, had increased risk of having AUD in the thir- are in line with previous Norwegian findings of higher ties/forties compared to those who did not have AUD in prevalence of specific phobias compared to international the twenties. studies [6, 53]. Previous studies have found that the majority of indi- The most prevalent groups of disorders were mood disor- viduals with anxiety and depressive disorders at one time ders and AUD among men and mood disorders among point are free from these disorders after three to 11 years women when specific phobias were excluded. Such phobias [25–27, 55]. This was also the case in the current study. are very common, but by definiton highly situation-specific. However, those who had MDD or anxiety disorders in The current results allowed differentiating between this the twenties, had increased risk of having these disorders Gustavson et al. BMC Psychiatry (2018) 18:65 Page 12 of 15 in the thirties/forties compared to those who did not results highlight the need to make adequate treatment have the disorders in the twenties. This is in line with easily available for young adults, to help them cope with previous findings from a wider age group of adults (age their developmental tasks (e.g. attain education and 18 to 65 at baseline) [56]. work experience). Easily available treatment is important Anxiety disorders in the twenties strongly predicted because of the high prevalence of mental disorders in MDD ten years later, even controlling for MDD in the the twenties and the thirties/forties, and because these twenties, in line with findings of stable and unspecific disorders were long lasting and/or recurrent across ten genetic risk of mental disorders [34, 35, 57]. The associ- years for a substantial number of young adults. ation between MDD in the twenties and anxiety The high prevalence of AUD between age 19 and 29 disorders in the thirties/forties, controlled for anxiety suggests that it is important to implement alcohol inter- disorders in the twenties, was not statistically significant, ventions particularly tailored to fit this age group and which may be due to low statistical power. However, their often-changing life circumstances. Specific phobias others have reported similar results by showing that may impose functional impairment only in particular baseline GAD predicted persistence of MDD, but not situations, but may be serious if those situations are the other way around among adolescents and young difficult to avoid. There seems to be a particularly high adults in the NCS-2 [31]. This is also in line with other need for efficient treatment of specific phobias for longitudinal findings from the general adult population, people in the twenties. showing that anxiety at one time point predicted depres- Other anxiety disorders and MDD did not become less sion at a later time to a stronger degree than the reverse prevalent with age. Anxiety disorders and MDD did not [58]. In the Netherlands Mental Health Survey and Inci- become more episodic from the twenties to the thirties/ dence Study (NEMESIS), mood disorder at follow-up forties, and comorbidity between them did not change was predicted by anxiety disorders three years earlier, during this period. Hence, mental health needs for other and incident anxiety disorder was predicted by previous disorders than AUD and specific phobias are stable from mood disorders [59]. In the US National Epidemiological the twenties to the thirties/forties, and many young Survey on Alcohol and Related Conditions (NESARC), adults will need treatment for more than one mental there was reciprocal longitudinal associations between disorder. incidence of MDD and GAD [60]. The Finnish Health As noted by Schaefer and colleagues, public knowledge 2011 study reported that baseline anxiety disorder about the very common nature of mental disorders may predicted new-onset MDD at 11-year follow-up [61]. contribute to reduced stigma [64]. In line with this, pub- Hence, anxiety disorders and MDD seem to have lic information about the current findings of high preva- common risk factors, but it is unclear whether anxiety is lence of mental disorders among young adults may a more robust predictor of later MDD than the reverse. contribute to reduced stigma in this age group. MDDseemedtobemoreepisodicinits naturethan anxiety disorders, in line with previous studies [22, 55]. Strengths and limitations There was no change toward a more or less chronic course The major strength of the present study is the large of any of these disorders when the participants got older. population-based sample, which has been assessed twice across 10 years for DSM-IV disorders by structured in- Comorbidity terviews. However, some limitations warrant consider- There was substantial comorbidity between disorders ation. First, the results may not be generalizable to other within each wave, in line with previous research [4, 7, age groups. Second, there may be bias in the results due 32, 37], and no evidence of increased or decreased co- to selection in recruitment and attrition at follow-up. morbidity between MDD and anxiety disorders from the People with mental health problems tend to be under- twenties to the thirties/forties. In both waves, more than represented in survey studies [65]. However, as discussed half of women and about one third of men with MDD, above, mental health variables did not predict participa- also had an anxiety disorder. Among those who had an tion in either of the interview waves [41, 42], and bias anxiety disorder, one in five or fewer, also had MDD. due to selective response may thus not be substantial. Young people with vulnerability of both MDD and anx- Third, the results are based on a sample of twins, iety, may at any time point have higher risk of experien- which may reduce generalizability to the general popula- cing a current anxiety disorder than current MDD tion. A study from the US compared self-reported symp- because the latter disorder tends to be more episodic. toms of depression, panic-phobia, somatization, and insomnia between twins and their non-twin relatives, Implications for policy makers and found that twins had significantly, but modestly, Previous research has shown that most people with higher scores on the panic-phobia factor, but reported mental disorders go untreated [62, 63]. The current similar levels of psychiatric symptoms as their non-twin Gustavson et al. BMC Psychiatry (2018) 18:65 Page 13 of 15 relatives on the other factors [66]. The authors con- Authors’ contributions KG: Contributed to the design of the study, conducted the analyses and cluded that “twins are typical for the general non-twin interpreted the results, authored the manuscript and approved of the final population in their risk for psychiatric symptoms and manuscript as submitted. AKK: Contributed to the design of the study, syndromes.” (p. 590). Nevertheless, the current findings interpretation of results, authored the manuscript and approved of the final manuscript as submitted. RN: Contributed to the design of the study, may be affected by the fact that two individuals from each interpretation of results, authored the manuscript and approved of the final family were recruited to the study. There was substantial manuscript as submitted. GPK: Contributed to the design of the study, the concordance between two twins in a pair regarding mental data collection, interpretation of results, reviewed and revised the manuscript, and approved of the final manuscript as submitted. SEV: disorders. Sensitivity analyses were performed with only Contributed to the design of the study, interpretation of results, reviewed one twin from each pair included, and results were very and revised the manuscript, and approved of the final manuscript as similar to the results from both twins. submitted. TR-K: Contributed to the design of the study, the data collection, the interpretation of results, reviewed and revised the manuscript and approved of the final manuscript as submitted. Conclusion Ethics approval and consent to participate Mental disorders are common among young people in Participants provided written informed consent. The name of the ethics the twenties and the thirties/forties, but AUD and review board that approved of our study is “The regional committee for specific phobias seem to become less prevalent over this medical and health research ethics, South East D”. (Reference number: 2010/767). age period. Nevertheless, some people are at enduring increased risk of impaired functioning due to mental Consent for publication disorders in consecutive developmental periods. Policy Not applicable. makers should ensure that mental health interventions Competing interests are available and tailored for young people to help them The authors declare that they have no competing interests. master their developmental tasks. Publisher’sNote Springer Nature remains neutral with regard to jurisdictional claims in Additional file published maps and institutional affiliations. Additional file 1: Tables S1 and S2. Prevalence estimates not shown Author details in the main files. (DOCX 30 kb) Department of mental disorders, Norwegian Institute of Public Health, Oslo, Norway. Centre for Disease Burden, Norwegian Institute of Public Health, Bergen, Norway. Department of Psychosocial Science, University of Bergen, Abbreviations Bergen, Norway. Nydalen DPS, Division of Mental Health and Addiction, AUD: Alcohol use disorders; CI: Confidence interval; CICS: Children in Oslo University Hospital, Oslo, Norway. Department of Psychology, Community Study; DSM-IV: Diagnostic and Statistical Manual of Mental University of Oslo, Oslo, Norway. Health Data and Digitalisation, Norwegian Disorders, Fourth Edition; GAD: Generalized anxiety disorder; GBD: Global Institute of Public Health, Oslo, Norway. Institute of Clinical Medicine, Burden of Disease; M-CIDI: Munich Composite International Diagnostic University of Oslo, Oslo, Norway. Interview; MDD: Major depressive disorder; NCS: US National Comorbidity Survey; NCS-2: US National Comorbidity Survey follow-up; NCS-R: US National Received: 3 May 2017 Accepted: 6 March 2018 Comorbidity Survey Replication; NEMESIS: Netherlands Mental Helath Survey and Incidence Study; NESARC: National Epidemiological Survey on Alcohol and Related Conditions; NIPHTP: Norwegian Institute of Public Health Twin References Panel; NZMHS: New Zealand Mental Health Survey; OCD: Obsessive- 1. Wang PS, Aguilar-Gaxiola S, Alonso J, Angermeyer MC, Borges G, Bromet EJ, compulsive disorder; PTSD: Post-traumatic stress disorder; Q1: Questionnaire Bruffaerts R, de Girolamo G, de Graaf R, Gureje O, et al. Use of mental health 1 in 1992; Q2: Questionnaire 2 in 1998; TRAILS: Tracking Adolescents’ services for anxiety, mood, and substance disorders in 17 countries in the Individual Lives Survey; YLD: Years lived with disability WHO world mental health surveys. Lancet. 2007;370(9590):841–50. 2. GBD 2015 Disease and Injury Incidence and Prevalence Collaborators. Acknowledgements Global, regional, and national incidence, prevalence, and years lived with Not applicable. disability for 310 diseases and injuries, 1990–2015: a systematic analysis for the global burden of disease study 2015. Lancet. 2016;388(10053):1545–602. Funding 3. Alonso J, Angermeyer MC, Bernert S, Bruffaerts R, Brugha TS, Bryson H, de Supported by Research Council of Norway grant 196148/V50. Previous Girolamo G, Graaf R, Demyttenaere K, Gasquet I, et al. Prevalence of mental collection and analysis of twin data from this project was in part supported disorders in Europe: results from the European study of the epidemiology of by grant MH-068643 from the National Institutes of Health and grants mental disorders (ESEMeD) project. Acta Psychiatr Scand Suppl. 2004;420:21–7. from the Norwegian Research Council, the Norwegian Foundation for 4. Kessler RC, Chiu WT, Demler O, Merikangas KR, Walters EE. Prevalence, Health and Rehabilitation, the Norwegian Council for Mental Health, the severity, and comorbidity of 12-month DSM-IV disorders in the National Borderline Foundation, and the European Commission. The funding bodies Comorbidity Survey Replication. Arch Gen Psychiatry. 2005;62(6):617–27. did not have any role in the design of the study, the collection, analysis, or 5. Kringlen E, Torgersen S, Cramer V. Mental illness in a rural area: a Norwegian interpretation of data, or in writing the manuscript. psychiatric epidemiological study. Soc Psychiatry Psychiatr Epidemiol. 2006; 41(9):713–9. Availability of data and materials 6. Kringlen E, Torgersen S, Cramer V. A Norwegian psychiatric epidemiological The raw data is confidential and cannot readily be shared. Data may be study. Am J Psychiatr. 2001;158(7):1091–8. shared with researchers obtaining permissions from The Norwegian Twin 7. Jacobi F, Hofler M, Strehle J, Mack S, Gerschler A, Scholl L, Busch MA, Hapke Registry and the Regional Committees for Medical and Health Research U, Maske U, Seiffert I, et al. Twelve-months prevalence of mental disorders Ethics. After permissions have been obtained, data can be made available in the German health interview and examination survey for adults - mental from The Norwegian Twin Registry, contact: Thomas S. Nilsen: health module (DEGS1-MH): a methodological addendum and correction. ThomasSevenius.Nilsen@fhi.no. Int J Methods Psychiatr Res. 2015;24(4):305–13. Gustavson et al. BMC Psychiatry (2018) 18:65 Page 14 of 15 8. de Graaf R, ten Have M, van Gool C, van Dorsselaer S. Prevalence of mental 29. Costello EJ, Copeland W, Angold A. The great Smoky Mountains study: disorders and trends from 1996 to 2009. Results from the Netherlands developmental epidemiology in the southeastern United States. Soc mental health survey and incidence Study-2. Soc Psychiatry Psychiatr Psychiatry Psychiatr Epidemiol. 2016;51(5):639–46. Epidemiol. 2012;47(2):203–13. 30. Johnson JG, Cohen P, Kasen S. Minor depression during adolescence and 9. Arnett JJ, Zukauskiene R, Sugimura K. The new life stage of emerging mental health outcomes during adulthood. Br J Psychiatry. 2009;195(3):264–5. adulthood at ages 18-29 years: implications for mental health. Lancet 31. Kessler RC, Gruber M, Hettema JM, Hwang I, Sampson N, Yonkers KA. Psychiatry. 2014;1(7):569–76. Co-morbid major depression and generalized anxiety disorders in the 10. Arnett JJ. Emerging adulthood. A theory of development from the late National Comorbidity Survey follow-up. Psychol Med. 2008;38(3):365–74. teens through the twenties. Am Psychol. 2000;55(5):469–80. 32. Alonso J, Angermeyer MC, Bernert S, Bruffaerts R, Brugha TS, Bryson H, de 11. Vander Stoep A, Beresford SAA, Weiss NS, McKnight B, Cauce AM, Cohen P. Girolamo G, Graaf R, Demyttenaere K, Gasquet I, et al. 12-month Community-based study of the transition to adulthood for adolescents with comorbidity patterns and associated factors in Europe: results from the psychiatric disorder. Am J Epidemiol. 2000;152(4):352–62. European study of the epidemiology of mental disorders (ESEMeD) project. 12. Kessler RC, Merikangas KR, Berglund P, Eaton WW, Koretz DS, Walters EE. Acta Psychiatr Scand Suppl. 2004;420:28–37. Mild disorders should not be eliminated from the DSM-V. Arch Gen 33. Newman DL, Moffitt TE, Caspi A, Magdol L, Silva PA, Stanton WR. Psychiatric Psychiatry. 2003;60(11):1117–22. disorder in a birth cohort of young adults: prevalence, comorbidity, clinical 13. Mojtabai R, Stuart EA, Hwang I, Eaton WW, Sampson N, Kessler RC. Long- significance, and new case incidence from ages 11 to 21. J Consult Clin term effects of mental disorders on marital outcomes in the National Psychol. 1996;64(3):552–62. Comorbidity Survey ten-year follow-up. Soc Psychiatry Psychiatr Epidemiol. 34. Krueger RF, Markon KE. Reinterpreting comorbidity: a model-based approach to understanding and classifying psychopathology. Annu Rev Clin 2017;52(10):1217–26. Psychol. 2006;2:111–33. 14. Mojtabai R, Stuart EA, Hwang I, Susukida R, Eaton WW, Sampson N, Kessler RC. Long-term effects of mental disorders on employment in the National 35. Kendler KS, Aggen SH, Knudsen GP, Roysamb E, Neale MC, Reichborn- Comorbidity Survey ten-year follow-up. Soc Psychiatry Psychiatr Epidemiol. Kjennerud T. The structure of genetic and environmental risk factors for 2015;50(11):1657–68. Syndromal and Subsyndromal common DSM-IV Axis I and all Axis II 15. Mojtabai R, Stuart EA, Hwang I, Eaton WW, Sampson N, Kessler RC. Long- disorders. Am J Psychiatr. 2011;168(1):29–39. term effects of mental disorders on educational attainment in the National 36. Lamers F, van Oppen P, Comijs HC, Smit JH, Spinhoven P, van Balkom AJ, Comorbidity Survey ten-year follow-up. Soc Psychiatry Psychiatr Epidemiol. Nolen WA, Zitman FG, Beekman AT, Penninx BW. Comorbidity patterns of 2015;50(10):1577–91. anxiety and depressive disorders in a large cohort study: the Netherlands 16. Crawford TN, Cohen P, First MB, Skodol AE, Johnson JG, Kasen S. Comorbid study of depression and anxiety (NESDA). J Clin Psychiatry. 2011;72(3):341–8. Axis I and Axis II disorders in early adolescence: outcomes 20 years later. 37. Merikangas KR, Zhang HP, Avenevoli S, Acharyya S, Neuenschwander M, Arch Gen Psychiatry. 2008;65(6):641–8. Angst J. Longitudinal trajectories of depression and anxiety in a prospective community study - the Zurich cohort study. Arch Gen Psychiatry. 2003; 17. Ormel J, Oerlemans AM, Raven D, Laceulle OM, Hartman CA, Veenstra R, 60(10):993–1000. Verhulst FC, Vollebergh W, Rosmalen JG, Reijneveld SA, et al. Functional outcomes of child and adolescent mental disorders. Current disorder most 38. Zlomke K, Davis TE 3rd. One-session treatment of specific phobias: a detailed important but psychiatric history matters as well. Psychol Med. 2017;47(7): description and review of treatment efficacy. Behav Ther. 2008;39(3):207–23. 1271–82. 39. Grant BF, Compton WM, Crowley TJ, Hasin DS, Helzer JE, Li TK, Rounsaville 18. Veldman K, Reijneveld SA, Ortiz JA, Verhulst FC, Bultmann U. Mental health BJ, Volkow ND, Woody GE. Errors in assessing DSM-IV substance use trajectories from childhood to young adulthood affect the educational and disorders. Arch Gen Psychiatry. 2007;64(3):379–80. author reply 381-372 employment status of young adults: results from the TRAILS study. J 40. Nilsen TS, Knudsen GP, Gervin K, Brandt I, Roysamb E, Tambs K, Orstavik R, Epidemiol Community Health. 2015;69(6):588–93. Lyle R, Reichborn-Kjennerud T, Magnus P, et al. The Norwegian twin registry 19. Vander Stoep A, Weiss NS, Kuo ES, Cheney D, Cohen P. What proportion of from a public health perspective: a research update. Twin Res Hum Genet. failure to complete secondary school in the US population is attributable to 2013;16(1):285–95. adolescent psychiatric disorder? J Behav Health Serv Res. 2003;30(1):119–24. 41. Reichborn-Kjennerud T, Czajkowski N, Ystrom E, Orstavik R, Aggen SH, Tambs K, Torgersen S, Neale MC, Roysamb E, Krueger RF, et al. A 20. Johnson JG, Cohen P, Kasen S, Smailes E, Brook JS. Association of longitudinal twin study of borderline and antisocial personality disorder maladaptive parental behavior with psychiatric disorder among parents and traits in early to middle adulthood. Psychol Med. 2015;45:1–11. their offspring. Arch Gen Psychiatry. 2001;58(5):453–60. 21. Moffitt TE, Caspi A, Taylor A, Kokaua J, Milne BJ, Polanczyk G, Poulton R. 42. Tambs K, Ronning T, Prescott CA, Kendler KS, Reichborn-Kjennerud T, How common are common mental disorders? Evidence that lifetime Torgersen S, Harris JR. The Norwegian Institute of Public Health Twin Study prevalence rates are doubled by prospective versus retrospective of mental health: examining recruitment and attrition Bias. Twin Res Hum ascertainment. Psychol Med. 2010;40(6):899–909. Genet. 2009;12(2):158–68. 22. Ormel J, Raven D, van Oort F, Hartman CA, Reijneveld SA, Veenstra R, 43. Nilsen TS, Brandt I, Magnus P, Harris JR. The Norwegian twin registry. Twin Vollebergh WA, Buitelaar J, Verhulst FC, Oldehinkel AJ. Mental health in Dutch Res Hum Genet. 2012;15(6):775–80. adolescents: a TRAILS report on prevalence, severity, age of onset, continuity 44. Harris JR, Magnus P, Tambs K. The Norwegian Institute of Public Health twin and co-morbidity of DSM disorders. Psychol Med. 2015;45(2):345–60. program of research: an update. Twin Res Hum Genet. 2006;9(6):858–64. 23. National Comorbidity Survey (NCS) [https://www.hcp.med.harvard.edu/ncs/ 45. Wittchen HU, Pfister H. DIA-X interviews (M-CIDI): manual fur screening- ftpdir/NCS-R_12-month_Prevalence_Estimates.pdf]. Verfahren und interview. Frankfurt: Swets & Zeitlinger; 1997. 24. Tanner JL, Reinherz HZ, Beardslee WR, Fitzmaurice GM, Leis JA, Berger SR. 46. American Psychiatric Association. Diagnostic and statistical manual of Change in prevalence of psychiatric disorders from ages 21 to 30 in a mental disorders. 5th ed. Washington: American Psychiatric Association; community sample. J Nerv Ment Dis. 2007;195(4):298–306. 2013. 25. Lamers F, Beekman AT, van Hemert AM, Schoevers RA, Penninx BW. Six-year 47. Copeland W, Shanahan L, Costello EJ, Angold A. Cumulative prevalence of longitudinal course and outcomes of subtypes of depression. Br J psychiatric disorders by young adulthood: a prospective cohort analysis Psychiatry. 2016;208(1):62–8. from the great Smoky Mountains study. J Am Acad Child Adolesc 26. Markkula N, Harkanen T, Nieminen T, Pena S, Mattila AK, Koskinen S, Saarni SI, Psychiatry. 2011;50(3):252–61. Suvisaari J. Prognosis of depressive disorders in the general population- results 48. Roberts BW, Wood D, Caspi A: The development of personality traits in from the longitudinal Finnish health 2011 study. J Affect Disord. 2016;190:687–96. adulthood. In: Handbook of personality theory and research. Third edn. Edited by John OP, Robins RW, Pervin LA. New York: Guilford; 27. Rhebergen D, Batelaan NM, de Graaf R, Nolen WA, Spijker J, Beekman AT, 2008: 375–398. Penninx BW. The 7-year course of depression and anxiety in the general population. Acta Psychiatr Scand. 2011;123(4):297–306. 49. Efron B, Tibshirani R. Bootstrap methods for standard errors, confidence 28. Copeland WE, Adair CE, Smetanin P, Stiff D, Briante C, Colman I, Fergusson intervals, and other measures of statistical accuracy. Stat Sci. 1986;1(1):54–75. D, Horwood J, Poulton R, Costello EJ, et al. Diagnostic transitions from 50. Singh K, Xie M. Bootstrap: a statistical method. In: Peterson P, Baker E, childhood to adolescence to early adulthood. J child Psychol Psychiatry. McGaw B, editors. International encyclopedia of education. Edn: Amsterdam: 2013;54(7):791–9. Rutgers University NJ: Elsevier Science; 2010. Gustavson et al. BMC Psychiatry (2018) 18:65 Page 15 of 15 51. Fitzmaurice GM, Laird NM, Ware JH. Applied longitudinal analysis. New Jersey: Wiley-interscience; 2004. 52. Kessler RC, Aguilar-Gaxiola S, Alonso J, Chatterji S, Lee S, Ormel J, Ustun TB, Wang PS. The global burden of mental disorders: an update from the WHO world mental health (WMH) surveys. Epidemiol Psichiatr Soc. 2009; 18(1):23–33. 53. Sandanger I, Nygard JF, Ingebrigtsen G, Sorensen T, Dalgard OS. Prevalence, incidence and age at onset of psychiatric disorders in Norway. Soc Psychiatry Psychiatr Epidemiol. 1999;34(11):570–9. 54. Copeland WE, Angold A, Shanahan L, Dreyfuss J, Dlamini I, Costello EJ. Predicting persistent alcohol problems: a prospective analysis from the great Smoky Mountain study. Psychol Med. 2012;42(9):1925–35. 55. Penninx BW, Nolen WA, Lamers F, Zitman FG, Smit JH, Spinhoven P, Cuijpers P, de Jong PJ, van Marwijk HW, van der Meer K, et al. Two-year course of depressive and anxiety disorders: results from the Netherlands study of depression and anxiety (NESDA). J Affect Disord. 2011; 133(1–2):76–85. 56. Lahey BB, Zald DH, Hakes JK, Krueger RF, Rathouz PJ. Patterns of heterotypic continuity associated with the cross-sectional correlational structure of prevalent mental disorders in adults. JAMA psychiatry. 2014;71(9):989–96. 57. Gillespie NA, Kirk KM, Evans DM, Heath AC, Hickie IB, Martin NG. Do the genetic or environmental determinants of anxiety and depression change with age? A longitudinal study of Australian twins. Twin Res. 2004; 7(1):39–53. 58. Fichter MM, Quadflieg N, Fischer UC, Kohlboeck G. Twenty-five-year course and outcome in anxiety and depression in the upper Bavarian longitudinal community study. Acta Psychiatr Scand. 2010;122(1):75–85. 59. de Graaf R, ten Have M, Tuithof M, van Dorsselaer S. First-incidence of DSM- IV mood, anxiety and substance use disorders and its determinants: results from the Netherlands mental health survey and incidence Study-2. J Affect Disord. 2013;149(1–3):100–7. 60. Grant BF, Goldstein RB, Chou SP, Huang B, Stinson FS, Dawson DA, Saha TD, Smith SM, Pulay AJ, Pickering RP, et al. Sociodemographic and psychopathologic predictors of first incidence of DSM-IV substance use, mood and anxiety disorders: results from the wave 2 National Epidemiologic Survey on alcohol and related conditions. Mol Psychiatry. 2009;14(11):1051–66. 61. Markkula N, Marola N, Nieminen T, Koskinen S, Saarni SI, Harkanen T, Suvisaari J. Predictors of new-onset depressive disorders - results from the longitudinal Finnish health 2011 study. J Affect Disord. 2017;208:255–64. 62. Torvik FA, Ystrom E, Gustavson K, Rosenstrom TH, Bramness JG, Gillespie N, Aggen SH, Kendler KS, Reichborn-Kjennerud T. Diagnostic and genetic overlap of three common mental disorders in structured interviews and health registries. Acta Psychiatr Scand. 2018;137(1):54–64. 63. Wang PS, Lane M, Olfson M, Pincus HA, Wells KB, Kessler RC. Twelve-month use of mental health services in the United States: results from the National Comorbidity Survey Replication. Arch Gen Psychiatry. 2005;62(6):629–40. 64. Schaefer JD, Caspi A, Belsky DW, Harrington H, Houts R, Horwood LJ, Hussong A, Ramrakha S, Poulton R, Moffitt TE. Enduring mental health: prevalence and prediction. J Abnorm Psychol. 2016;126:212–24. 65. Torvik FA, Rognmo K, Tambs K. Alcohol use and mental distress as predictors of non-response in a general population health survey: the HUNT study. Soc Psychiatry Psychiatr Epidemiol. 2012;47(5):805–16. 66. Kendler KS, Martin NG, Heath AC, Eaves LJ. Self-report psychiatric symptoms in twins and their nontwin relatives: are twins different? Am J Med Genet. 1995;60(6):588–91. Submit your next manuscript to BioMed Central and we will help you at every step: • We accept pre-submission inquiries � Our selector tool helps you to find the most relevant journal � We provide round the clock customer support � Convenient online submission � Thorough peer review � Inclusion in PubMed and all major indexing services � Maximum visibility for your research Submit your manuscript at www.biomedcentral.com/submit http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png BMC Psychiatry Springer Journals

Prevalence and stability of mental disorders among young adults: findings from a longitudinal study

Loading next page...
 
/lp/springer-journals/prevalence-and-stability-of-mental-disorders-among-young-adults-VdNLIHRTl0

References (70)

Publisher
Springer Journals
Copyright
Copyright © 2018 by The Author(s).
Subject
Medicine & Public Health; Psychiatry; Psychotherapy
eISSN
1471-244X
DOI
10.1186/s12888-018-1647-5
pmid
29530018
Publisher site
See Article on Publisher Site

Abstract

Background: Mental disorders often have onset early in life, contribute substantially to the global disease burden, and may interfere with young people’s ability to complete age-relevant tasks in important developmental periods. However, knowledge about prevalence and course of mental disorders in young adulthood is sparse. The aim of the current study was to estimate prevalence and stability of mental disorders from the twenties to the thirties/forties. Methods: DSM-IV mental disorders were assessed with the Composite International Diagnostic Interview in two waves (1999–2004 and 2010–2011) in 1623 young adult Norwegian twins (63.2% women, aged 19–29 years in wave 1). Results: In wave 1, the 12-month prevalence of any mental disorder among people in the twenties was 19.8% (men) and 32.4% (women), anxiety disorders: 9.6% (men) and 26.7% (women), anxiety disorders excluding specific phobias: 2.5% (men) and 6.9% (women), major depressive disorder (MDD): 4.4% (men) and 7.2% (women), and alcohol use disorder (AUD): 8.7% (men) and 4.4% (women). The prevalence of any mental disorder decreased from the twenties to the thirties/ forties. This was due to a decrease in AUD and specific phobias. Anxiety disorders in the twenties predicted anxiety disorders and MDD ten years later, even when controlling for the association between these disorders in the twenties. MDD in the twenties predicted MDD ten years later. At both ages, two-week and 12-month prevalence estimates differed markedly forMDD -indicatinganepisodiccourse. Conclusions: Common mental disorders are highly prevalent among young adults in the twenties, and somewhat less prevalent in the thirties/forties. Those who suffer from one mental disorder in the twenties are at considerably increased risk for suffering from a disorder ten years later as well. This may have significant implications for young people’s ability to attain education, establish a family, and participate in occupational life. Keywords: Mental disorders, Young adulthood, Health surveys, Prevalence, Stability Background disorders ranked ninth [2]. The high rankings were a re- Mental disorders are among the most prevalent health sult of both high prevalence and the disability associated problems affecting the adult population [1]. The Global with these disorders. Estimates of 12-month prevalence Burden of Disease Study 2015 (GBD 2015) estimated of mental disorders vary between 9.6 and 27.8% in the that seven of the top 25 causes of years lived with dis- general adult population [3–8]. Mood disorders, anxiety ability (YLD) globally were mental disorders, with major disorders (including specific phobias), and alcohol use depressive disorder (MDD) ranked second and anxiety disorders (AUD) are the most prevalent disorders and are included in all the above-mentioned studies. * Correspondence: krbr@fhi.no Department of mental disorders, Norwegian Institute of Public Health, Oslo, Young adulthood Norway 5 The shift in recent decades toward longer educations and Department of Psychology, University of Oslo, Oslo, Norway Full list of author information is available at the end of the article higher age when committing to stable relationships and © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Gustavson et al. BMC Psychiatry (2018) 18:65 Page 2 of 15 having children, has led researchers to aknowledge the age anxiety at one time point, have been found to have at between 18 and 29 as an important developmental period least one of these disorders 7 years later [27]. Having a [9]. It is characterized by changes in love and work life, disorder or mental health problems in adolescence in- and frequent residental change [9, 10]. Completing educa- creases the risk of such disorders/problems in early tion and building a stable life structure are important adulthood [18, 28–30]. Findings from the NCS follow- developmental tasks in this period, while raising children up (NCS-2) showed that having MDD or generalized is an important task for later periods [9, 10]. anxiety disorder (GAD) in the twenties and thirties Mental health problems are associated with poor predicted having any of these disorders eleven years educational attainment as well as work and interpersonal later [31]. Depression seems to be more episodic than problems [11–18]. Research results indicate that half of anxiety disorders among adolescents, as shown by US adolescents’ failure to complete secondary school is higher 12-month to 30-day prevalence ratios of mood attributable to mental disorders [19]. Mental disorders than anxiety disorders [22]. are also associated with maladaptive parenting behaviors, such as low affection toward the child and inconsistent Comorbidity enforcement of rules [20]. Because mental disorders may Comorbidity between mental disorders is extensive with interfere with developmental tasks in different periods, up to 50% of those who have one mental disorder also we need to increase our knowledge about the prevalence having at least one additional comorbid mental disorder and stability of such disorders at different ages to be able [4, 7, 32]. This is also reported among young people [33]. to correctly assess the magnitude of this problem. Comorbidity seems to a large degree to be due to com- mon liablity factors for several disorders [34, 35]and is Prevalence of mental disorders in young adulthood related to severity and chronicity [27, 33, 36, 37]. Hence, Findings from the New Zealand Mental Health Survey estimates of comorbidity in different developmental (NZMHS), the Dutch Tracking Adolescents’ Individual periods may increase our understanding of the potential Lives Survey (TRAILS), the US National Comorbidity effects of common mental disorders on young adults. Survey (NCS) and its replication (NCS-R), and the Children in the Community Study (CICS) from the US, show 12-month prevalence estiatmes of MDD between Need for further knowledge 8.3 and 12.4% among people between 18 and 33 years Current knowledge on prevalence and stability of mental [16, 21–23]. The 12-month prevalence was between 19.4 disorders among young adults relies heavily on results and 22.3% for anxiety disorders (including specific from the US and New Zealand. Longitudinal studies phobias), between 2.5 and 10.3% for acohol dependence, from several different countries are needed to inform and between 7.1 and 18.4% for alcohol abuse [21–23]. policy makers in different parts of the world and to estimate global disease burden in this age period. Stability of mental disorders in young adulthood Previous prevalence estiamtes of any mental disorder Previous studies indicate that the prevalence of depression or any anxiety disorder typically include specific phobias, is stable over the earliest part of adulthood, whereas AUD which by definiton involves imapirment in circum- decreases, and findings regarding anxiety disorders are scribed situations and can sometimes be treated in a mixed [21, 24]. In the Dunedin study from New Zealand, single therapy session [38]. Prevalence estiamtes both the 12-month prevalence of MDD was 16.8% at age including and excluding such phobias are therefore 21 years and 16.3% at 32 years [21]. The 12-month preva- needed to plan mental health services for young adults. lence of any anxiety disorder (including specific phobias) Findings are divergent with regards to whether or not was 20.3% at 21 years and 22.2% at 32 years. In the anxiety disorders become less prevalent during young Simmons Longitudinal Study from the US, prevalence adulthood. Previous studies have included different anx- estiamtes of MDD showed a weak and not statistically sig- iety disorders when examining this. There is a lack of nificant increase from age 21 to 30 (from 5.4 to 8.0%), studies tracking the episodic versus chronic nature of while there was a decline in the 12-month prevalence for MDD and anxiety disorders across young adulthood. If phobia (including specific phobias) (from 16.8 to 2.3%) depression tends to get more or less episodic over time, [24]. The prevalence of alcohol dependence declined the burden of recurrent depression will decrease or (from 18.4 to 8.1%) from age 21 to 32 in the Dunedin increase as people get older. More knowledge about the study, and the prevalence of AUD declined from 26.7 to stability of anxiety disorders and MDD from the twen- 6.0% in the Simmons Longituidnal Study [21, 24]. ties to the thirties/forties may increase our understand- Some people have long-lasting and/or recurrent epi- ing of the potential impact of such disorders on young sodes of mental disorders [25, 26]. In the general adult adult development. This is important for planning population, about 40% of those who have depression or mental health services for young adults. Gustavson et al. BMC Psychiatry (2018) 18:65 Page 3 of 15 A limitation in several previous studies of AUD is Compare 12-month to two-week prevalence estimates to different diagnostic criteria across waves and use of alcohol examine the episodic nature of disorders across these abuse as a screen for alcohol dependence [39]. This may two developmental periods, 4) Examine the degree to affect estimates of prevalence and stability of this disorder which those who have an anxiety disorder or MDD in [24, 39]. the twenties, are at increased risk of having these disor- To the best of our knowledge, no previous studies have ders ten years later, 5) Examine comorbidity of common examined prevalence and stablity in common mental dis- mental disorders among people in the twenties and ten orders by both: Following the same individuals from the years later. twenties to the thirties/forties, estimating prevalence of anxiety disorders at the different ages including as well as Methods excluding specific phobias, comparing the episodic versus Sample chronic nature of disorders at both ages, and examining Data came from the Norwegian Institute of Public comorbidity between disorders at both ages. Health Twin Panel (NIPHTP), which includes health questionnaires at two time points (Q1 and Q2), and Aims of the study diagnostic interviews at two later time points (wave 1 The overall aim of the current study was to address limi- and wave 2). The current study used data from the two tations in previous literature on prevalence and stability interviews. The NIPHTP is described thoroughly else- of common mental disorders from the twenties to the where [40–44], and recruitment is illustrated in Fig. 1. thirties/forties. More specifically, the aims were to: 1) The first wave of the interview study (wave 1) took place Estimate the 12-month prevalence of anxiety disorders between 1999 and 2004, and 2801 individuals (44% of the (with and without specific phobias), mood disorders, invited) were interviewed. All twins who had participated and AUD among people aged 19 to 29, 2) Compare in wave 1 were invited for a re-interview between 2010 these estimates to prevalence estimates ten years later, 3) and 2011 (wave 2). The follow-up participation rate from Fig. 1 Flow-chart of recruitment to the study. The current study used data from the two interview studies, indicated with bold font Gustavson et al. BMC Psychiatry (2018) 18:65 Page 4 of 15 wave 1 to wave 2 was 82.8% (n = 2284) [41]. Mean age was Manual of Mental Disorders, Fourth Edition (DSM-IV). 28.3 years (range 19–36 years) in wave 1 and 37.9 years The interview was mainly administered face-to-face in (range 30–44 years) in wave 2. Mean time between wave 1. For practical reasons, 231 interviews (8.3%) were interviews was 9.6 years (range 7–13 years). Participation conducted by telephone. To maximize response rate, all in wave 1 was predicted by increasing age and monozy- the interviews were conducted by telephone in wave 2. gosity, but not by any indicator of mental health [42]. Interviewers were mostly psychology graduate students Participation in wave 2 was predicted by high education, or experienced psychiatric nurses who had received female sex, and monozygosity. Neither the total number standardized training by certified instructors. Each twin of mental disorders nor any specific disorder in wave 1 in a pair was interviewed by a different interviewer. predicted participation in wave 2 [41]. Respondents answered one question about when they The current study aimed to examine mental disorders last experienced symptoms of each of the disorders. The in a specific developmental period (19–29 years of age) response categories were “Within the last two weeks”, and follow these individuals over time. Hence, only “Two weeks to less than a month”, “One to five months”, participants below age 30 in wave 1 were included in the “6 to 12 months”, “Last 12 months, but cannot remem- main analyses. This resulted in a sample of 597 men and ber exactly when”, and “More than one year”. Endorse- 1026 women in wave 1, and 457 men and 850 women in ment of the first option was used to estimate 2-week wave 2. Mean age in wave 1 was 25.4 years (range 19 to prevalence, endorsement of any of the first two options 29), and mean age in wave 2 was 35.3 years (range 30 to to estimate 4-week prevalence, endorsement of any of 42). Mean time between the two interviews was 9.6 years. the first three options to estimate 5(6) month- Prevalence estimates for the wider age range of the prevalence, and endorsement of any of the first five entire sample were also calculated and are presented in options to estimate 12-month-prevalence. Hence, Additional file 1: Tables S1 and S2, for readers who are individuals contributing to two-week prevalence esti- interested in prevalence of mental disorders in a wider mates were a sub-group of those contributing to all age group. other prevalence estimates of each disorder. Table 1 shows an overview of combined categories of Measures diagnoses. AUD consisted of alcohol abuse and alcohol A Norwegian version of the computerized Munich dependence. Any mood disorder consisted of MDD and Composite International Diagnostic Interview (M-CIDI), dysthymia. Any anxiety disorder W1 consisted of panic originally developed by the World Health Organization, disorder, agoraphobia without a history of panic dis- was employed in both interview waves [45]. Diagnoses order, specific phobias, social phobia, GAD, obsessive- were coded according to the Diagnostic and Statistical compulsive disorder (OCD), and post-traumatic stress Table 1 Overview of disorders included in the combined categories Combined category Includes Constructed for wave Any mood disorder MDD, Dysthymia 1 and 2 Any anxiety disorder W1 Panic disorder, Agoraphobia without a history of panic disorder, Specific phobias, Social 1 phobia, GAD, OCD, PTSD. Any Anxiety disorder W1–2 Panic disorder, Agoraphobia without a history of panic disorder, Specific phobias, Social 1 and 2 phobia, GAD. Any anxiety disorder W1–2 excluding Panic disorder, Agoraphobia without a history of panic disorder, Social phobia, GAD. 1 and 2 specific phobias AUD Alcohol abuse, Alcohol dependence. 1 and 2 Any mental disorder W1 Any mood disorder, Any anxiety disorder W1, AUD. 1 Any mental disorder W1–2 Any mood disorder, Any anxiety disorder W1–2, AUD. 1 and 2 Any mental disorder W1–2 excluding Any mood disorder, Any anxiety disorder W1–2 excluding specific phobias, AUD. 1 and 2 specific phobias Categories only presented in Supplementary table Drug use disorder Drug abuse, drug dependence. 1 Any substance use disorder Drug use disorder, AUD. 1 Any disorder W1- supplement Any mood disorder, Any anxiety disorder W1, Any substance use disorder 1 Legends: MDD Major depressive disorder, GAD Generalized anxiety disorder, OCD Obsessive-compulsive disorder, PTSD Post-traumatic stress disorder, AUD Alcohol use disorder W1 Wave 1, W2 wave 2 Gustavson et al. BMC Psychiatry (2018) 18:65 Page 5 of 15 disorder (PTSD). In wave 2, OCD and PTSD were not people who have a diagnosis across ages [48]. This was assessed. These two disorders are no longer classified as examined with logistic regression for MDD, Any anxiety anxiety disorders in DSM-5 [46]. Any anxiety disorder disorder W1–2, and AUD, adjusted for age in wave 1. W1–2 did not include these two disorders, and was con- We also examined the degree to which MDD in wave 1 structed for both waves to allow comparison of anxiety predicted having Any anxiety disorder W1–2 in wave 2, disorders across age. Any anxiety disorder W1–2 exclud- and vice versa, controlled for age. Because of low ing specific phobias consisted of all anxiety disorders number of cases and thus low statistical power, AUD measured in both waves except specific phobias. Any was not included. Men and women were collapsed in mental disorder W1 consisted of Any mood disorder, these analyses to increase statistical power. Any anxiety disorder W1, and AUD. Any mental disorder Comorbidity within each wave was examined with W1–2 consisted of Any mood disorder, Any anxiety dis- tetrachoric correlations between MDD, Any anxiety order W1–2, and AUD. Any mental disorder W1–2 disorders W1–2,and AUD. Comorbidity was also exam- excluding specific phobias consisted of Any mood ined by showing the proportion of people with one dis- disorder, Any anxiety disorder W1–2 excluding specific order, who also had another disorder, and by illustrating phobias, and AUD. how many of a hypothetical sample of 100 individuals Total as well as sex-stratified prevalence estimates are who would have either one disorder, or a combination of presented for MDD, Any mood disorder, Any anxiety two or three disorders. Men and women were collapsed. disorder (W1, W1–2, as well as W1–2 excluding specific The concordance between twins may affect results. phobias), AUD, and Any mental disorder (W1, W1–2, First, standard errors may be too small due to clustering and W1–2 excluding specific phobias). Prevalence effects [49–51]. This was adjusted for by drawing estimates for low frequent specific disorders (e.g. panic clusters (twin-pairs) rather than individuals in the disorders and dysthymia) are only presented for both bootstrapping/jackknife process and by using the robust genders together. Drug use disorders (drug addiction estimator for standard errors in logistic regression [49– and drug abuse) were only assess in wave 1, and are 51]. Second, sensitivity analyses were performed includ- presented in Additional file 1: Table S1. ing only one twin from each pair, to see if this affected We report 12-month and 2-week prevalence estimates. results. The other two measured prevalences (5(6)-month and four-week) are presented in Additional file 1: Tables S1 and S2. Interested readers may use those estimates to Results compare findings with other studies that have used Prevalence estimates estimates between 12-month and two-week (as for We report results for 597 men and 1026 women (63.2%) example [22, 47]). who participated in wave 1 (Table 2) and 457 men and 850 women (65.0%) who also participated in wave 2 Statistical analyses (Table 3). Analyses were performed in Stata version 15. Testing all In wave 1, when the participants were in the twen- the prevalence estimates for statistically significant ties, Any anxiety disorder W1 was the most prevalent gender differences would imply a large number of tests, combined category of disorders for both men and thus increasing the risk of random findings. Such testing women (see Table 2). The 12-month prevalence for was therefore only performed for the following Any anxiety disorder W1 was 9.6% (95% confidence estimates: 12-month Any mental disorder W1–2, 12- interval (CI) = 7.0–12.4) for men and 26.7% (95% CI = month Any mood disorder, 12-month Any anxiety 23.7–29.7) for women. For Any anxiety disorder W1– disorder W1–2, and 12-month AUD. 2, the 12-month prevalence was 9.3 (95% CI = 7.0– The 12-month and 2-week prevalence estimates were 12.3) for men and 26.0% (95% CI = 23.1–29.0) for compared for MDD and Any anxiety disorder W1–2. women. AUD ranked second among men (8.7% 12- Episodic disorders are expected to show higher 12- month prevalence, 95% CI = 6.5–11.3), and Any mood dis- month than 2-week prevalences whereas the prevalences order ranked second among women (8.7% 12-month are expected to be more similar for more chronic prevalence, 95% CI = 6.7–10.6). Specific phobias were disorders. highly prevalent among men and women (12-month Absolute stability was examined by comparing preva- prevalence = 7.6% with 95% CI = 5.5–10.2 for men and lence estimates at the two waves. Only those who partic- 22.3% with 95% CI = 19.5–25.0 for women). AUD and Any ipated in wave 2, were included in significance testing of mood disorder were the most common groups of disorders change in prevalence estimates, thus reducing the risk of for men, and Any mood disorder was the most common bias du to potential selective attrition. Relative stability group of disorders for women when specific phobias were refers to the degree to which it is the same or different excluded. Results from significance testing of gender Gustavson et al. BMC Psychiatry (2018) 18:65 Page 6 of 15 Table 2 Prevalence of mental disorders in wave 1 (age 19–29 years, n = 597 men and 1026 women) Men and women Men Women Ratio (women/men) of 12-month prevalence 12 month Two-week 12 month Two-week 12 month Two-week estimates (95% CI) prevalence prevalence prevalence prevalence prevalence prevalence (95% CI) (95% CI) (95% CI) (95% CI) (95% CI) (95% CI) MDD 6.2 1.3 4.4 0.8 7.2 1.6 5.0–7.4 0.7–1.8 2.8–6.3 0.2–1.6 5.5–8.8 0.9–2.4 Dysthymia 1.7 1.4 1.1–2.4 0.8–2.0 Any mood disorder 7.3 2.3 4.9 1.2 8.7 2.9 1.79*** 5.9–8.6 1.5–3.0 3.2–6.8 0.4–2.2 6.7–10.6 1.9–4.0 1.19–2.68 Any anxiety disorder W1 20.4 15.2 9.6 5.9 26.7 20.7 18.3–22.7 13.5–17.3 7.0–12.4 4.2–8.2 23.7–29.7 18.1–23.5 Any anxiety disorder W1–2 19.8 14.8 9.3 5.7 26.0 20.1 2.80*** 17.7–22.0 13.0–16.7 7.0–12.3 4.0–7.9 23.1–29.0 17.4–22.7 2.13–3.68 Any anxiety disorder W1–2 5.3 3.2 2.5 1.3 6.9 4.2 excluding specific phobias 4.2–6.6 2.3–4.1 1.3–4.2 0.5–2.6 5.3–8.7 3.0–5.7 Specific phobias 16.9 12.4 7.6 4.9 22.3 16.8 14.9–19.0 10.8–14.1 5.5–10.2 3.3–6.9 19.5–25.0 14.5–19.2 Panic disorder 1.5 0.4 1.0–2.2 0.1–0.7 Agoraphobia without panic 1.4 1.1 0.9–2.0 0.6–1.7 Social phobia 2.3 1.8 1.7–3.3 1.2–2.7 GAD 1.2 0.4 0.7–1.9 0.1–0.7 OCD 0.3 0.2 0.1–0.6 0.1–0.4 PTSD 1.2 0.7 0.7–1.8 0.4–1.2 Alcohol abuse 2.8 0.9 2.0–3.7 0.5–1.5 Alcohol Dependence 4.7 2.1 3.6–5.8 1.4–2.8 AUD 6.0 2.7 8.7 3.7 4.4 2.0 0.50*** 4.8–7.3 1.9–3.6 6.5–11.3 2.3–5.4 3.2–5.7 1.2–3.0 0.34–0.74 Gustavson et al. BMC Psychiatry (2018) 18:65 Page 7 of 15 Table 2 Prevalence of mental disorders in wave 1 (age 19–29 years, n = 597 men and 1026 women) (Continued) Men and women Men Women Ratio (women/men) of 12-month prevalence 12 month Two-week 12 month Two-week 12 month Two-week estimates (95% CI) prevalence prevalence prevalence prevalence prevalence prevalence (95% CI) (95% CI) (95% CI) (95% CI) (95% CI) (95% CI) Any mental disorder W1 27.8 18.6 19.8 9.7 32.4 23.8 25.4–30.3 16.7–20.6 16.4–23.4 7.3–12.4 29.4–35.7 21.1–26.6 Any mental disorder W1–2 27.6 18.2 19.8 9.5 32.2 23.3 1.63*** 25.3–30.2 16.2–20.1 16.4–23.4 7.1–12.2 29.2–35.4 20.7–26.0 1.35–1.96 Any mental disorder W1–2 15.3 7.3 14.3 5.6 15.9 8.3 excluding specific phobias 13.5–17.5 6.0–8.8 11.2–17.3 3.7–7.7 13.6–18.5 6.5–10.3 Legends: *** p < 0.001, MDD Major depressive disorder, GAD Generalized anxiety disorder, OCD Obsessive-compulsive disorder, PTSD Post-traumatic stress disorder, AUD Alcohol use disorders, i.e. alcohol dependence or alcohol abuse CI Confidence interval. 95% CIs are based on standard errors obtained from bootstrapping (1000 replications), bias corrected for skewness in the bootstrap distribution, and adjusted for cluster-effects among twins MDD and/or dysthymia Panic disorder, agoraphobia without panic, specific phobias, social phobia, GAD, OCD, and/or PTSD Panic disorder, agoraphobia without panic, specific phobias, social phobia and/or GAD Panic disorder, agoraphobia without panic, social phobia and/or GAD Any mood disorder, Any anxiety disorder W1, AUD Any mood disorder, Any anxiety disorder W1–2, AUD Any mood disorder, Any anxiety disorder W1–2 excluding specific phobias, AUD Gustavson et al. BMC Psychiatry (2018) 18:65 Page 8 of 15 Table 3 Prevalence of mental disorders in wave 2 (age 30–42 years, n = 457 men and 850 women) Men and women Men Women Ratio (women/men) of 12-month prevalence 12 month Two-week 12 month Two-week 12 month Two-week estimates (95% CI) prevalence prevalence prevalence prevalence prevalence prevalence (95% CI) (95% CI) (95% CI) (95% CI) (95% CI) (95% CI) MDD 5.0 1.1 3.3 0.9 5.9 1.2 3.8–6.3 0.6–1.7 1.9–5.2 0.2–1.9 4.3–7.5 0.6–2.0 Dysthymia 1.9 0.9 1.2–3.0 0.5–1.5 Any mood disorder 5.8 1.6 3.7 1.1 7.0 1.9 1.87** 4.6–7.3 1.0–2.4 2.3–5.9 0.2–2.3 5.3–8.7 1.1–3.0 1.10–3.17 Any anxiety disorder W1–2 16.1 8.3 5.9 2.9 21.6 11.2 3.63*** 13.9–18.4 6.8–9.7 4.0–8.2 1.5–4.7 18.6–24.6 9.0–13.2 2.46–5.35 Any anxiety disorder W1–2 6.5 2.6 2.6 0.9 8.5 3.5 excluding specific phobias 5.2–8.0 1.8–3.7 1.3–4.3 0.2–1.9 6.7–10.7 2.4–5.0 Specific phobias 12.3 6.5 4.1 2.2 16.8 8.8 10.3–14.3 5.2–7.9 2.4–6.1 1.0–3.9 14.1–19.5 6.9–10.8 Panic disorder 2.1 0.5 1.4–3.0 0.2–1.1 Agoraphobia without panic 1.2 0.6 0.6–1.9 0.2–1.2 Social phobia 3.9 1.4 2.9–5.2 0.7–2.1 GAD 1.5 0.5 0.9–2.2 0.2–0.9 AUD 2.7 1.2 5.3 2.4 1.3 0.5 0.25** 1.8–3.7 0.7–1.8 3.2–7.2 1.2–4.0 0.7–2.2 0.1–1.0 0.12–0.50 Any mental disorder W1–2 20.9 10.0 12.9 5.8 25.3 12.3 1.96*** 18.6–23.3 8.3–11.7 9.8–16.3 3.8–8.1 22.1–28.6 10.3–14.5 1.50–2.55 Any mental disorder W1–2 12.4 4.9 10.0 4.2 13.7 5.2 excluding specific phobias 10.5–14.4 3.6–6.2 7.3–12.6 2.5–6.2 11.4–16.3 3.7–6.9 Legends:** p < 0.01, *** p < 0.001, MDD Major depressive disorder, GAD Generalized anxiety disorder, AUD Alcohol use disorders, i.e. alcohol dependence or alcohol abuse CI Confidence interval. 95% CIs are based on standard errors obtained from bootstrapping (1000 replications), bias corrected for skewness in the bootstrap distribution and adjusted for cluster-effects among twins MDD and/or dysthymia Panic disorder, agoraphobia without panic, specific phobias, social phobia and/or GAD Panic disorder, agoraphobia without panic, social phobia and/or GAD Any mood disorder, Any anxiety disorder W1–2, AUD Any mood disorder, Any anxiety disorder W1–2 excluding specific phobias, AUD Gustavson et al. BMC Psychiatry (2018) 18:65 Page 9 of 15 difference showed that Any mental disorder W1–2, Any having these disorders ten years later. The results anxiety disorder W1–2,and Any mood disorder were more showed that Any anxiety disorder W1–2 in wave 1 pre- prevalent among women than men, while AUD was more dicted MDD in wave 2, even controlled for MDD in prevalent among men than women (see Table 2). wave 1. In wave 2, the 12-month prevalence of Any anxiety Despite relative stability from wave 1 to wave 2, 82.4% disorder W1–2 was 5.9% (95% CI = 4.0–8.2) for men and of those who had MDD, 54.9% of those who had Any 21.6% (95% CI = 18.6–24.6) for women (see Table 3). anxiety disorder W1–2, and 85.4% of those who had Again, this was mainly due to the high prevalence of AUD in Wave 1 (12-mont prevalence), did not have the specific phobias (12-month prevalence was 4.1% with same disorder in wave 2. 95% CI = 2.4–6.1 for men and 16.8% with 95% CI = 14.1–19.5 for women). Any mood disorder was the 12-month versus 2-week prevalence estimates second most prevalent group of disorders among The 12-month prevalence of MDD was significantly women (12-month prevalence 7.0% with 95% CI = higher than the 2-week prevalence in both waves. The 5.3–8.7), and AUD was the second most common dis- 12-month to two-week ratios for MDD was 4.8 (95% CI order among men (12-month prevalence = 5.3% with = 3.9–7.5) in wave 1 and 4.6 (95% CI = 3.1–8.6) in wave 95% CI = 3.2–7.2). Any mental disorder W1–2, Any 2. For Any anxiety disorder W1–2 the ratios were 1.3 mood disorder, and Any anxiety disorder W1–2, were (95% CI = 1.3–1.4) in wave 1 and 1.9 (95% CI = 1.7–2.2) more prevalent among women than men, and the re- in wave 2, indicating a more episodic nature of MDD verse was true for AUD (see Table 3). than anxiety disorders. Stability Therewas areduction in Any mental disorder W1–2, Comorbidity Specific phobias, and AUD from wave 1 to wave 2 Tetrachoric correlations between 12-month MDD, Any (95% CI for differences did not include zero). Estimates anxiety disorder W1–2, and AUD within each wave are were stable for MDD and Any anxiety disorder W1–2 presented in Table 5. There was a strong association be- excluding specific phobias (95% CI for difference included tween MDD and Any anxiety disorder W1–2 in both zero). waves. Relative stability was measured with logistic regression, Comorbidity was also examined by calculating how presented in Table 4. Having MDD, Any anxiety disorder many of those who had one disorder, also had another W1–2, or AUD in the twenties, increased the risk of disorder. The results are presented in Table 6. The co- morbidity numbers for AUD should be interpreted with Table 4 Relative stability in mental disorders from age 19–29 to caution in wave 2, as few people had this diagnosis. age 30–42 estimated with logistic regression Figure 2 shows the number of people with pure versus Disorder in W1 not MDD and Anxiety in comorbid MDD, Any anxiety disorder W1–2, and AUD adjusted for each W1 mutually adjusted other OR for each other OR in hypothetical samples of 100 men and 100 women in (95% CI) (95% CI) the twenties and in the thirties/forties. MDD in wave 2 Table 5 Tetrachoric correlations between different disorders at MDD in wave 1 3.56*** 2.60** (1.81–6.98) (1.31–5.17) wave 1 (age 19–29) and wave 2 (age 30–42) Anxiety in wave 1 2.61*** 2.18** Wave 1 Wave 2 (1.54–4.42) (1.26–3.75) MDD Anxiety AUD MDD Anxiety AUD a a W1–2 W1–2 Anxiety in wave 2 Wave 1 MDD 0.45*** 0.00 0.31** 0.38*** 0.16 MDD in wave 1 3.94*** 1.77 (2.36–6.60) (0.96–3.26) a Anxiety W1–2 0.10 0.26** 0.65*** 0.02 Anxiety in wave 1 9.01*** 8.33*** AUD 0.07 0.07 0.49*** (6.45–12.59) (5.90–11.78) Wave 2 MDD 0.54*** 0.12 AUD in wave 2 8.10*** Anxiety W1–2 0.03 AUD in wave 1 (3.69–17.76) AUD Legends: OR Odds ratio, CI Confidence interval, MDD Major depressive disorder, Anxiety = Any anxiety disorder W1–2(Panic disorder, agoraphobia without Legends: Panic disorder, agoraphobia without panic, specific phobias, social panic, specific phobias, social phobia and/or generalized anxiety disorder phobia and/or generalized anxiety disorder (GAD) (GAD)). Standard errors were obtained from the robust estimator in Stata, MDD Major depressive disorder. AUD Alcohol use disorders, i.e. alcohol accounting for cluster-effects among twins dependence or alcohol abuse. Standard errors were obtained from the Men and women were collapsed in the analyses to increase statistical power. jackknife estimator, accounting for cluster-effects among twins. **p < 0.01, All analyses were adjusted for age in wave 1 ***p < 0.001. Men and women were collapsed to increase statistical power Gustavson et al. BMC Psychiatry (2018) 18:65 Page 10 of 15 Table 6 Comorbidity wave 1 (age 19–29) and wave 2 (age 30–42) Men Women % with comorbid MDD % with comorbid % with comorbid % with comorbid % with comorbid % with comorbid a a Anxiety W1–2 AUD MDD Anxiety W1–2 AUD Wave 1 MDD 34.6 3.8 66.2 6.8 17.6–55.6 0–14.3 54.8–76.8 1.5–13.7 Anxiety W1–2 15.8 17.5 17.4 5.9 7.3–26.8 8.5–27.3 13.1–21.9 3.6–9.0 AUD 1.9 17.5 11.1 35.6 0–7.1 8.5–27.3 3.4–21.1 22.2–50.0 Wave 2 MDD 33.3 16.7 57.0 2.0 13.0–53.6 3.7–31.8 46.5–67.0 0.0–5.4 Anxiety W1–2 17.4 8.7 19.5 1.7 8.3–31.1 2.0–18.0 14.8–24.3 0.3–3.4 AUD 11.4 11.8 14.3 7.1 2.9–23.3 3.0–23.5 0.0–37.5 0.0–25.0 Legends: MDD Major depressive disorder, AUD Alcohol use disorders, i.e. alcohol dependence or alcohol abuse Panic disorder, agoraphobia without panic, specific phobias, social phobia and/or generalized anxiety disorder (GAD) Sensitivity analyses of concordance between twins W1 were estimated for a sub-sample where one twin As mentioned in the methods section, the use of twins was randomly chosen from each pair (see Table 7). The may have affected results, and sensitivity analyses were estimates were quite similar to estimates from both therefore performed. If one twin did not have any twins. The ratio of the results (estimates from the entire mental disorder during the last 12 months in wave 1, the sample/estimates from only one twin) varied between co-twin’s risk of having a mental disorder was 21.7% 1.00 and 1.04. (compared to 27.8% in the full sample). When one twin had a mental disorder, the co-twin’s risk was 43.7%. This Discussion concordance between twins was expressed in an intra- MDD, anxiety disorders, and AUD were highly prevalent class correlation of 0.21. Prevalence of MDD, Any at age 19–29. The prevalence of mental disorders was anxiety disorders W1, AUD, and Any mental disorder lower at age 30–42, and this was mainly due to decrease Fig. 2 Combinations of disorders in hypothetical groups of 100 men and 100 women at different ages. Legend: MDD = major depressive disorder, Anxiety = Any anxiety disorder W1–2 (Panic disorder, agoraphobia without panic, specific phobias, social phobia and/or generalized anxiety disorder (GAD)), AUD = alcohol use disorder (i.e. alcohol dependence and alcohol abuse) Gustavson et al. BMC Psychiatry (2018) 18:65 Page 11 of 15 Table 7 Prevalence estimates in wave 1 when using both twins versus one twin in each pair 12-month prevalence estimate 12-month prevalence estimate Ratio using both twins 95% CI only including one twin from Entire sample estimate/ each pair 95% C.I. Estimate using one twin from each pair MDD 6.2 6.2 1.00 5.0–7.4 4.5–8.0 Any anxiety disorder W1 20.4 19.6 1.04 18.3–22.7 17.2–22.5 AUD 6.0 5.8 1.03 4.8–7.3 4.4–7.5 Any mental disorder W1 27.8 27.8 1.00 25.4–30.3 24.7–31.0 Legends: CI Confidence interval, MDD Major depressive disorder Panic disorder, agoraphobia without panic, specific phobias, social phobia, generalized anxiety disorder (GAD), obsessive-compulsive disorder (OCD), and/or post-- traumatic stress disorder (PTSD) AUD Alcohol use disorders, i.e. alcohol dependence or alcohol abuse Any mental disorder W1 = Any mood disorder, Any anxiety disorder W1, AUD 95% CIs are based on standard errors obtained from bootstrapping (1000 replications), bias corrected for skewness in the bootstrap distribution, and adjusted for cluster-effects among twins in AUD and specific phobias. Prevalence estimates of very circumscrbied disorder and mental disorders that MDD and anxiety disorders excluding specific phobias affect people in more complex ways across different situa- were stable in this period. Individuals who had MDD, an tions (e.g. MDD, GAD, and AUD). anxiety disorder, or AUD in the twenties were of in- creased risk of having these disorders in the thirties/for- Stability ties compared to those who did not have these Mental disorders became less prevalent as participants diagnoses in the twenties. went from the twenties to the thirties/forties. Our results converge with findings from the Simmons Longitudinal Prevalence estimates study regarding a decrease in specific phobias and AUD The 12-month prevalence of depressive disorders in [24]. Other anxiety disorders did not become less preva- people in the twenties was lower in the current study lent in the current study. Findings from the Dunedin compared to young adults in the CICS [16], the Dunedin study showed a marked decrease in acohol dependence, study, NZMHS, NCS, and NCS-R [21, 23], but similar to and quite stable prevalence of MDD and anxiety disorders the prevalence among 26-year-olds in the Simmons longi- (including specific phobias, GAD, panic disorder, agora- tudinal study [24]. The current findings were very similar phobia, OCD, and PTSD) from age 21 to age 32 [21]. De- to results from these other studies with regard to preva- crease in AUD across young adulthood may reflect the lence of anxiety disorders in the twenties. In the Dunedin circumstances of people in the twenties, who often do not study, alcohol dependence among people aged 18 to have responsibility for children, and many are students. 32 years was more prevalent than the broader category of Results from a previous study indicate that a third of AUD in both waves in the current study [21]. Likewise, those who met diagnostic criteria for AUD in late ado- the narrower category alcohol abuse was more prevalent lescence, also met criteria for AUD at age 26 [54]. In the in TRAILS and NCS-R than AUD in the current sample current study, only about 15% of those who met diag- [22, 23]. In the Simmons longitudinal study, the preva- nostic criteria for AUD in the twenties also had AUD in lence of AUD was similar to the current results [24]. the thirties/forties. Hence, the course of AUD seems to Our findings are in line with previous studies showing be less chronic from the twenties to the thirties/forties that anxiety disorders tend to be the most prevalent than from late adolescence to age 26. Nevertheless, the group of disorders, both in the general adult population current results showed that those who had AUD in the and among young adults [21, 52]. The current results twenties, had increased risk of having AUD in the thir- are in line with previous Norwegian findings of higher ties/forties compared to those who did not have AUD in prevalence of specific phobias compared to international the twenties. studies [6, 53]. Previous studies have found that the majority of indi- The most prevalent groups of disorders were mood disor- viduals with anxiety and depressive disorders at one time ders and AUD among men and mood disorders among point are free from these disorders after three to 11 years women when specific phobias were excluded. Such phobias [25–27, 55]. This was also the case in the current study. are very common, but by definiton highly situation-specific. However, those who had MDD or anxiety disorders in The current results allowed differentiating between this the twenties, had increased risk of having these disorders Gustavson et al. BMC Psychiatry (2018) 18:65 Page 12 of 15 in the thirties/forties compared to those who did not results highlight the need to make adequate treatment have the disorders in the twenties. This is in line with easily available for young adults, to help them cope with previous findings from a wider age group of adults (age their developmental tasks (e.g. attain education and 18 to 65 at baseline) [56]. work experience). Easily available treatment is important Anxiety disorders in the twenties strongly predicted because of the high prevalence of mental disorders in MDD ten years later, even controlling for MDD in the the twenties and the thirties/forties, and because these twenties, in line with findings of stable and unspecific disorders were long lasting and/or recurrent across ten genetic risk of mental disorders [34, 35, 57]. The associ- years for a substantial number of young adults. ation between MDD in the twenties and anxiety The high prevalence of AUD between age 19 and 29 disorders in the thirties/forties, controlled for anxiety suggests that it is important to implement alcohol inter- disorders in the twenties, was not statistically significant, ventions particularly tailored to fit this age group and which may be due to low statistical power. However, their often-changing life circumstances. Specific phobias others have reported similar results by showing that may impose functional impairment only in particular baseline GAD predicted persistence of MDD, but not situations, but may be serious if those situations are the other way around among adolescents and young difficult to avoid. There seems to be a particularly high adults in the NCS-2 [31]. This is also in line with other need for efficient treatment of specific phobias for longitudinal findings from the general adult population, people in the twenties. showing that anxiety at one time point predicted depres- Other anxiety disorders and MDD did not become less sion at a later time to a stronger degree than the reverse prevalent with age. Anxiety disorders and MDD did not [58]. In the Netherlands Mental Health Survey and Inci- become more episodic from the twenties to the thirties/ dence Study (NEMESIS), mood disorder at follow-up forties, and comorbidity between them did not change was predicted by anxiety disorders three years earlier, during this period. Hence, mental health needs for other and incident anxiety disorder was predicted by previous disorders than AUD and specific phobias are stable from mood disorders [59]. In the US National Epidemiological the twenties to the thirties/forties, and many young Survey on Alcohol and Related Conditions (NESARC), adults will need treatment for more than one mental there was reciprocal longitudinal associations between disorder. incidence of MDD and GAD [60]. The Finnish Health As noted by Schaefer and colleagues, public knowledge 2011 study reported that baseline anxiety disorder about the very common nature of mental disorders may predicted new-onset MDD at 11-year follow-up [61]. contribute to reduced stigma [64]. In line with this, pub- Hence, anxiety disorders and MDD seem to have lic information about the current findings of high preva- common risk factors, but it is unclear whether anxiety is lence of mental disorders among young adults may a more robust predictor of later MDD than the reverse. contribute to reduced stigma in this age group. MDDseemedtobemoreepisodicinits naturethan anxiety disorders, in line with previous studies [22, 55]. Strengths and limitations There was no change toward a more or less chronic course The major strength of the present study is the large of any of these disorders when the participants got older. population-based sample, which has been assessed twice across 10 years for DSM-IV disorders by structured in- Comorbidity terviews. However, some limitations warrant consider- There was substantial comorbidity between disorders ation. First, the results may not be generalizable to other within each wave, in line with previous research [4, 7, age groups. Second, there may be bias in the results due 32, 37], and no evidence of increased or decreased co- to selection in recruitment and attrition at follow-up. morbidity between MDD and anxiety disorders from the People with mental health problems tend to be under- twenties to the thirties/forties. In both waves, more than represented in survey studies [65]. However, as discussed half of women and about one third of men with MDD, above, mental health variables did not predict participa- also had an anxiety disorder. Among those who had an tion in either of the interview waves [41, 42], and bias anxiety disorder, one in five or fewer, also had MDD. due to selective response may thus not be substantial. Young people with vulnerability of both MDD and anx- Third, the results are based on a sample of twins, iety, may at any time point have higher risk of experien- which may reduce generalizability to the general popula- cing a current anxiety disorder than current MDD tion. A study from the US compared self-reported symp- because the latter disorder tends to be more episodic. toms of depression, panic-phobia, somatization, and insomnia between twins and their non-twin relatives, Implications for policy makers and found that twins had significantly, but modestly, Previous research has shown that most people with higher scores on the panic-phobia factor, but reported mental disorders go untreated [62, 63]. The current similar levels of psychiatric symptoms as their non-twin Gustavson et al. BMC Psychiatry (2018) 18:65 Page 13 of 15 relatives on the other factors [66]. The authors con- Authors’ contributions KG: Contributed to the design of the study, conducted the analyses and cluded that “twins are typical for the general non-twin interpreted the results, authored the manuscript and approved of the final population in their risk for psychiatric symptoms and manuscript as submitted. AKK: Contributed to the design of the study, syndromes.” (p. 590). Nevertheless, the current findings interpretation of results, authored the manuscript and approved of the final manuscript as submitted. RN: Contributed to the design of the study, may be affected by the fact that two individuals from each interpretation of results, authored the manuscript and approved of the final family were recruited to the study. There was substantial manuscript as submitted. GPK: Contributed to the design of the study, the concordance between two twins in a pair regarding mental data collection, interpretation of results, reviewed and revised the manuscript, and approved of the final manuscript as submitted. SEV: disorders. Sensitivity analyses were performed with only Contributed to the design of the study, interpretation of results, reviewed one twin from each pair included, and results were very and revised the manuscript, and approved of the final manuscript as similar to the results from both twins. submitted. TR-K: Contributed to the design of the study, the data collection, the interpretation of results, reviewed and revised the manuscript and approved of the final manuscript as submitted. Conclusion Ethics approval and consent to participate Mental disorders are common among young people in Participants provided written informed consent. The name of the ethics the twenties and the thirties/forties, but AUD and review board that approved of our study is “The regional committee for specific phobias seem to become less prevalent over this medical and health research ethics, South East D”. (Reference number: 2010/767). age period. Nevertheless, some people are at enduring increased risk of impaired functioning due to mental Consent for publication disorders in consecutive developmental periods. Policy Not applicable. makers should ensure that mental health interventions Competing interests are available and tailored for young people to help them The authors declare that they have no competing interests. master their developmental tasks. Publisher’sNote Springer Nature remains neutral with regard to jurisdictional claims in Additional file published maps and institutional affiliations. Additional file 1: Tables S1 and S2. Prevalence estimates not shown Author details in the main files. (DOCX 30 kb) Department of mental disorders, Norwegian Institute of Public Health, Oslo, Norway. Centre for Disease Burden, Norwegian Institute of Public Health, Bergen, Norway. Department of Psychosocial Science, University of Bergen, Abbreviations Bergen, Norway. Nydalen DPS, Division of Mental Health and Addiction, AUD: Alcohol use disorders; CI: Confidence interval; CICS: Children in Oslo University Hospital, Oslo, Norway. Department of Psychology, Community Study; DSM-IV: Diagnostic and Statistical Manual of Mental University of Oslo, Oslo, Norway. Health Data and Digitalisation, Norwegian Disorders, Fourth Edition; GAD: Generalized anxiety disorder; GBD: Global Institute of Public Health, Oslo, Norway. Institute of Clinical Medicine, Burden of Disease; M-CIDI: Munich Composite International Diagnostic University of Oslo, Oslo, Norway. Interview; MDD: Major depressive disorder; NCS: US National Comorbidity Survey; NCS-2: US National Comorbidity Survey follow-up; NCS-R: US National Received: 3 May 2017 Accepted: 6 March 2018 Comorbidity Survey Replication; NEMESIS: Netherlands Mental Helath Survey and Incidence Study; NESARC: National Epidemiological Survey on Alcohol and Related Conditions; NIPHTP: Norwegian Institute of Public Health Twin References Panel; NZMHS: New Zealand Mental Health Survey; OCD: Obsessive- 1. Wang PS, Aguilar-Gaxiola S, Alonso J, Angermeyer MC, Borges G, Bromet EJ, compulsive disorder; PTSD: Post-traumatic stress disorder; Q1: Questionnaire Bruffaerts R, de Girolamo G, de Graaf R, Gureje O, et al. Use of mental health 1 in 1992; Q2: Questionnaire 2 in 1998; TRAILS: Tracking Adolescents’ services for anxiety, mood, and substance disorders in 17 countries in the Individual Lives Survey; YLD: Years lived with disability WHO world mental health surveys. Lancet. 2007;370(9590):841–50. 2. GBD 2015 Disease and Injury Incidence and Prevalence Collaborators. Acknowledgements Global, regional, and national incidence, prevalence, and years lived with Not applicable. disability for 310 diseases and injuries, 1990–2015: a systematic analysis for the global burden of disease study 2015. Lancet. 2016;388(10053):1545–602. Funding 3. Alonso J, Angermeyer MC, Bernert S, Bruffaerts R, Brugha TS, Bryson H, de Supported by Research Council of Norway grant 196148/V50. Previous Girolamo G, Graaf R, Demyttenaere K, Gasquet I, et al. Prevalence of mental collection and analysis of twin data from this project was in part supported disorders in Europe: results from the European study of the epidemiology of by grant MH-068643 from the National Institutes of Health and grants mental disorders (ESEMeD) project. Acta Psychiatr Scand Suppl. 2004;420:21–7. from the Norwegian Research Council, the Norwegian Foundation for 4. Kessler RC, Chiu WT, Demler O, Merikangas KR, Walters EE. Prevalence, Health and Rehabilitation, the Norwegian Council for Mental Health, the severity, and comorbidity of 12-month DSM-IV disorders in the National Borderline Foundation, and the European Commission. The funding bodies Comorbidity Survey Replication. Arch Gen Psychiatry. 2005;62(6):617–27. did not have any role in the design of the study, the collection, analysis, or 5. Kringlen E, Torgersen S, Cramer V. Mental illness in a rural area: a Norwegian interpretation of data, or in writing the manuscript. psychiatric epidemiological study. Soc Psychiatry Psychiatr Epidemiol. 2006; 41(9):713–9. Availability of data and materials 6. Kringlen E, Torgersen S, Cramer V. A Norwegian psychiatric epidemiological The raw data is confidential and cannot readily be shared. Data may be study. Am J Psychiatr. 2001;158(7):1091–8. shared with researchers obtaining permissions from The Norwegian Twin 7. Jacobi F, Hofler M, Strehle J, Mack S, Gerschler A, Scholl L, Busch MA, Hapke Registry and the Regional Committees for Medical and Health Research U, Maske U, Seiffert I, et al. Twelve-months prevalence of mental disorders Ethics. After permissions have been obtained, data can be made available in the German health interview and examination survey for adults - mental from The Norwegian Twin Registry, contact: Thomas S. Nilsen: health module (DEGS1-MH): a methodological addendum and correction. ThomasSevenius.Nilsen@fhi.no. Int J Methods Psychiatr Res. 2015;24(4):305–13. Gustavson et al. BMC Psychiatry (2018) 18:65 Page 14 of 15 8. de Graaf R, ten Have M, van Gool C, van Dorsselaer S. Prevalence of mental 29. Costello EJ, Copeland W, Angold A. The great Smoky Mountains study: disorders and trends from 1996 to 2009. Results from the Netherlands developmental epidemiology in the southeastern United States. Soc mental health survey and incidence Study-2. Soc Psychiatry Psychiatr Psychiatry Psychiatr Epidemiol. 2016;51(5):639–46. Epidemiol. 2012;47(2):203–13. 30. Johnson JG, Cohen P, Kasen S. Minor depression during adolescence and 9. Arnett JJ, Zukauskiene R, Sugimura K. The new life stage of emerging mental health outcomes during adulthood. Br J Psychiatry. 2009;195(3):264–5. adulthood at ages 18-29 years: implications for mental health. Lancet 31. Kessler RC, Gruber M, Hettema JM, Hwang I, Sampson N, Yonkers KA. Psychiatry. 2014;1(7):569–76. Co-morbid major depression and generalized anxiety disorders in the 10. Arnett JJ. Emerging adulthood. A theory of development from the late National Comorbidity Survey follow-up. Psychol Med. 2008;38(3):365–74. teens through the twenties. Am Psychol. 2000;55(5):469–80. 32. Alonso J, Angermeyer MC, Bernert S, Bruffaerts R, Brugha TS, Bryson H, de 11. Vander Stoep A, Beresford SAA, Weiss NS, McKnight B, Cauce AM, Cohen P. Girolamo G, Graaf R, Demyttenaere K, Gasquet I, et al. 12-month Community-based study of the transition to adulthood for adolescents with comorbidity patterns and associated factors in Europe: results from the psychiatric disorder. Am J Epidemiol. 2000;152(4):352–62. European study of the epidemiology of mental disorders (ESEMeD) project. 12. Kessler RC, Merikangas KR, Berglund P, Eaton WW, Koretz DS, Walters EE. Acta Psychiatr Scand Suppl. 2004;420:28–37. Mild disorders should not be eliminated from the DSM-V. Arch Gen 33. Newman DL, Moffitt TE, Caspi A, Magdol L, Silva PA, Stanton WR. Psychiatric Psychiatry. 2003;60(11):1117–22. disorder in a birth cohort of young adults: prevalence, comorbidity, clinical 13. Mojtabai R, Stuart EA, Hwang I, Eaton WW, Sampson N, Kessler RC. Long- significance, and new case incidence from ages 11 to 21. J Consult Clin term effects of mental disorders on marital outcomes in the National Psychol. 1996;64(3):552–62. Comorbidity Survey ten-year follow-up. Soc Psychiatry Psychiatr Epidemiol. 34. Krueger RF, Markon KE. Reinterpreting comorbidity: a model-based approach to understanding and classifying psychopathology. Annu Rev Clin 2017;52(10):1217–26. Psychol. 2006;2:111–33. 14. Mojtabai R, Stuart EA, Hwang I, Susukida R, Eaton WW, Sampson N, Kessler RC. Long-term effects of mental disorders on employment in the National 35. Kendler KS, Aggen SH, Knudsen GP, Roysamb E, Neale MC, Reichborn- Comorbidity Survey ten-year follow-up. Soc Psychiatry Psychiatr Epidemiol. Kjennerud T. The structure of genetic and environmental risk factors for 2015;50(11):1657–68. Syndromal and Subsyndromal common DSM-IV Axis I and all Axis II 15. Mojtabai R, Stuart EA, Hwang I, Eaton WW, Sampson N, Kessler RC. Long- disorders. Am J Psychiatr. 2011;168(1):29–39. term effects of mental disorders on educational attainment in the National 36. Lamers F, van Oppen P, Comijs HC, Smit JH, Spinhoven P, van Balkom AJ, Comorbidity Survey ten-year follow-up. Soc Psychiatry Psychiatr Epidemiol. Nolen WA, Zitman FG, Beekman AT, Penninx BW. Comorbidity patterns of 2015;50(10):1577–91. anxiety and depressive disorders in a large cohort study: the Netherlands 16. Crawford TN, Cohen P, First MB, Skodol AE, Johnson JG, Kasen S. Comorbid study of depression and anxiety (NESDA). J Clin Psychiatry. 2011;72(3):341–8. Axis I and Axis II disorders in early adolescence: outcomes 20 years later. 37. Merikangas KR, Zhang HP, Avenevoli S, Acharyya S, Neuenschwander M, Arch Gen Psychiatry. 2008;65(6):641–8. Angst J. Longitudinal trajectories of depression and anxiety in a prospective community study - the Zurich cohort study. Arch Gen Psychiatry. 2003; 17. Ormel J, Oerlemans AM, Raven D, Laceulle OM, Hartman CA, Veenstra R, 60(10):993–1000. Verhulst FC, Vollebergh W, Rosmalen JG, Reijneveld SA, et al. Functional outcomes of child and adolescent mental disorders. Current disorder most 38. Zlomke K, Davis TE 3rd. One-session treatment of specific phobias: a detailed important but psychiatric history matters as well. Psychol Med. 2017;47(7): description and review of treatment efficacy. Behav Ther. 2008;39(3):207–23. 1271–82. 39. Grant BF, Compton WM, Crowley TJ, Hasin DS, Helzer JE, Li TK, Rounsaville 18. Veldman K, Reijneveld SA, Ortiz JA, Verhulst FC, Bultmann U. Mental health BJ, Volkow ND, Woody GE. Errors in assessing DSM-IV substance use trajectories from childhood to young adulthood affect the educational and disorders. Arch Gen Psychiatry. 2007;64(3):379–80. author reply 381-372 employment status of young adults: results from the TRAILS study. J 40. Nilsen TS, Knudsen GP, Gervin K, Brandt I, Roysamb E, Tambs K, Orstavik R, Epidemiol Community Health. 2015;69(6):588–93. Lyle R, Reichborn-Kjennerud T, Magnus P, et al. The Norwegian twin registry 19. Vander Stoep A, Weiss NS, Kuo ES, Cheney D, Cohen P. What proportion of from a public health perspective: a research update. Twin Res Hum Genet. failure to complete secondary school in the US population is attributable to 2013;16(1):285–95. adolescent psychiatric disorder? J Behav Health Serv Res. 2003;30(1):119–24. 41. Reichborn-Kjennerud T, Czajkowski N, Ystrom E, Orstavik R, Aggen SH, Tambs K, Torgersen S, Neale MC, Roysamb E, Krueger RF, et al. A 20. Johnson JG, Cohen P, Kasen S, Smailes E, Brook JS. Association of longitudinal twin study of borderline and antisocial personality disorder maladaptive parental behavior with psychiatric disorder among parents and traits in early to middle adulthood. Psychol Med. 2015;45:1–11. their offspring. Arch Gen Psychiatry. 2001;58(5):453–60. 21. Moffitt TE, Caspi A, Taylor A, Kokaua J, Milne BJ, Polanczyk G, Poulton R. 42. Tambs K, Ronning T, Prescott CA, Kendler KS, Reichborn-Kjennerud T, How common are common mental disorders? Evidence that lifetime Torgersen S, Harris JR. The Norwegian Institute of Public Health Twin Study prevalence rates are doubled by prospective versus retrospective of mental health: examining recruitment and attrition Bias. Twin Res Hum ascertainment. Psychol Med. 2010;40(6):899–909. Genet. 2009;12(2):158–68. 22. Ormel J, Raven D, van Oort F, Hartman CA, Reijneveld SA, Veenstra R, 43. Nilsen TS, Brandt I, Magnus P, Harris JR. The Norwegian twin registry. Twin Vollebergh WA, Buitelaar J, Verhulst FC, Oldehinkel AJ. Mental health in Dutch Res Hum Genet. 2012;15(6):775–80. adolescents: a TRAILS report on prevalence, severity, age of onset, continuity 44. Harris JR, Magnus P, Tambs K. The Norwegian Institute of Public Health twin and co-morbidity of DSM disorders. Psychol Med. 2015;45(2):345–60. program of research: an update. Twin Res Hum Genet. 2006;9(6):858–64. 23. National Comorbidity Survey (NCS) [https://www.hcp.med.harvard.edu/ncs/ 45. Wittchen HU, Pfister H. DIA-X interviews (M-CIDI): manual fur screening- ftpdir/NCS-R_12-month_Prevalence_Estimates.pdf]. Verfahren und interview. Frankfurt: Swets & Zeitlinger; 1997. 24. Tanner JL, Reinherz HZ, Beardslee WR, Fitzmaurice GM, Leis JA, Berger SR. 46. American Psychiatric Association. Diagnostic and statistical manual of Change in prevalence of psychiatric disorders from ages 21 to 30 in a mental disorders. 5th ed. Washington: American Psychiatric Association; community sample. J Nerv Ment Dis. 2007;195(4):298–306. 2013. 25. Lamers F, Beekman AT, van Hemert AM, Schoevers RA, Penninx BW. Six-year 47. Copeland W, Shanahan L, Costello EJ, Angold A. Cumulative prevalence of longitudinal course and outcomes of subtypes of depression. Br J psychiatric disorders by young adulthood: a prospective cohort analysis Psychiatry. 2016;208(1):62–8. from the great Smoky Mountains study. J Am Acad Child Adolesc 26. Markkula N, Harkanen T, Nieminen T, Pena S, Mattila AK, Koskinen S, Saarni SI, Psychiatry. 2011;50(3):252–61. Suvisaari J. Prognosis of depressive disorders in the general population- results 48. Roberts BW, Wood D, Caspi A: The development of personality traits in from the longitudinal Finnish health 2011 study. J Affect Disord. 2016;190:687–96. adulthood. In: Handbook of personality theory and research. Third edn. Edited by John OP, Robins RW, Pervin LA. New York: Guilford; 27. Rhebergen D, Batelaan NM, de Graaf R, Nolen WA, Spijker J, Beekman AT, 2008: 375–398. Penninx BW. The 7-year course of depression and anxiety in the general population. Acta Psychiatr Scand. 2011;123(4):297–306. 49. Efron B, Tibshirani R. Bootstrap methods for standard errors, confidence 28. Copeland WE, Adair CE, Smetanin P, Stiff D, Briante C, Colman I, Fergusson intervals, and other measures of statistical accuracy. Stat Sci. 1986;1(1):54–75. D, Horwood J, Poulton R, Costello EJ, et al. Diagnostic transitions from 50. Singh K, Xie M. Bootstrap: a statistical method. In: Peterson P, Baker E, childhood to adolescence to early adulthood. J child Psychol Psychiatry. McGaw B, editors. International encyclopedia of education. Edn: Amsterdam: 2013;54(7):791–9. Rutgers University NJ: Elsevier Science; 2010. Gustavson et al. BMC Psychiatry (2018) 18:65 Page 15 of 15 51. Fitzmaurice GM, Laird NM, Ware JH. Applied longitudinal analysis. New Jersey: Wiley-interscience; 2004. 52. Kessler RC, Aguilar-Gaxiola S, Alonso J, Chatterji S, Lee S, Ormel J, Ustun TB, Wang PS. The global burden of mental disorders: an update from the WHO world mental health (WMH) surveys. Epidemiol Psichiatr Soc. 2009; 18(1):23–33. 53. Sandanger I, Nygard JF, Ingebrigtsen G, Sorensen T, Dalgard OS. Prevalence, incidence and age at onset of psychiatric disorders in Norway. Soc Psychiatry Psychiatr Epidemiol. 1999;34(11):570–9. 54. Copeland WE, Angold A, Shanahan L, Dreyfuss J, Dlamini I, Costello EJ. Predicting persistent alcohol problems: a prospective analysis from the great Smoky Mountain study. Psychol Med. 2012;42(9):1925–35. 55. Penninx BW, Nolen WA, Lamers F, Zitman FG, Smit JH, Spinhoven P, Cuijpers P, de Jong PJ, van Marwijk HW, van der Meer K, et al. Two-year course of depressive and anxiety disorders: results from the Netherlands study of depression and anxiety (NESDA). J Affect Disord. 2011; 133(1–2):76–85. 56. Lahey BB, Zald DH, Hakes JK, Krueger RF, Rathouz PJ. Patterns of heterotypic continuity associated with the cross-sectional correlational structure of prevalent mental disorders in adults. JAMA psychiatry. 2014;71(9):989–96. 57. Gillespie NA, Kirk KM, Evans DM, Heath AC, Hickie IB, Martin NG. Do the genetic or environmental determinants of anxiety and depression change with age? A longitudinal study of Australian twins. Twin Res. 2004; 7(1):39–53. 58. Fichter MM, Quadflieg N, Fischer UC, Kohlboeck G. Twenty-five-year course and outcome in anxiety and depression in the upper Bavarian longitudinal community study. Acta Psychiatr Scand. 2010;122(1):75–85. 59. de Graaf R, ten Have M, Tuithof M, van Dorsselaer S. First-incidence of DSM- IV mood, anxiety and substance use disorders and its determinants: results from the Netherlands mental health survey and incidence Study-2. J Affect Disord. 2013;149(1–3):100–7. 60. Grant BF, Goldstein RB, Chou SP, Huang B, Stinson FS, Dawson DA, Saha TD, Smith SM, Pulay AJ, Pickering RP, et al. Sociodemographic and psychopathologic predictors of first incidence of DSM-IV substance use, mood and anxiety disorders: results from the wave 2 National Epidemiologic Survey on alcohol and related conditions. Mol Psychiatry. 2009;14(11):1051–66. 61. Markkula N, Marola N, Nieminen T, Koskinen S, Saarni SI, Harkanen T, Suvisaari J. Predictors of new-onset depressive disorders - results from the longitudinal Finnish health 2011 study. J Affect Disord. 2017;208:255–64. 62. Torvik FA, Ystrom E, Gustavson K, Rosenstrom TH, Bramness JG, Gillespie N, Aggen SH, Kendler KS, Reichborn-Kjennerud T. Diagnostic and genetic overlap of three common mental disorders in structured interviews and health registries. Acta Psychiatr Scand. 2018;137(1):54–64. 63. Wang PS, Lane M, Olfson M, Pincus HA, Wells KB, Kessler RC. Twelve-month use of mental health services in the United States: results from the National Comorbidity Survey Replication. Arch Gen Psychiatry. 2005;62(6):629–40. 64. Schaefer JD, Caspi A, Belsky DW, Harrington H, Houts R, Horwood LJ, Hussong A, Ramrakha S, Poulton R, Moffitt TE. Enduring mental health: prevalence and prediction. J Abnorm Psychol. 2016;126:212–24. 65. Torvik FA, Rognmo K, Tambs K. Alcohol use and mental distress as predictors of non-response in a general population health survey: the HUNT study. Soc Psychiatry Psychiatr Epidemiol. 2012;47(5):805–16. 66. Kendler KS, Martin NG, Heath AC, Eaves LJ. Self-report psychiatric symptoms in twins and their nontwin relatives: are twins different? Am J Med Genet. 1995;60(6):588–91. Submit your next manuscript to BioMed Central and we will help you at every step: • We accept pre-submission inquiries � Our selector tool helps you to find the most relevant journal � We provide round the clock customer support � Convenient online submission � Thorough peer review � Inclusion in PubMed and all major indexing services � Maximum visibility for your research Submit your manuscript at www.biomedcentral.com/submit

Journal

BMC PsychiatrySpringer Journals

Published: Mar 12, 2018

There are no references for this article.