Hostname: page-component-cd9895bd7-gvvz8 Total loading time: 0 Render date: 2024-12-22T23:57:31.609Z Has data issue: false hasContentIssue false
  • English
  • Français

Who pays the price for high neuroticism? Moderators of longitudinal risks for depression and anxiety

Published online by Cambridge University Press:  14 February 2017

J. R. Vittengl
J. R. Vittengl*
Affiliation:
Department of Psychology, Truman State University, Kirksville, MO, USA
*
*Address for correspondence: J. R. Vittengl, Department of Psychology, Truman State University, 100 East Normal Street, Kirksville, MO 63501-4221, USA. (Email: [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

High neuroticism is a well-established risk for present and future depression and anxiety, as well as an emerging target for treatment and prevention. The current analyses tested the hypothesis that physical, social and socio-economic disadvantages each amplify risks from high neuroticism for longitudinal increases in depression and anxiety symptoms.

Method

A national sample of adults (n = 7108) provided structured interview and questionnaire data in the Midlife Development in the United States Survey. Subsamples were reassessed roughly 9 and 18 years later. Time-lagged multilevel models predicted changes in depression and anxiety symptom intensity across survey waves.

Results

High neuroticism predicted increases in a depression/anxiety symptom composite across retest intervals. Three disadvantage dimensions – physical limitations (e.g. chronic illness, impaired functioning), social problems (e.g. less social support, more social strain) and low socio-economic status (e.g. less education, lower income) – each moderated risks from high neuroticism for increases in depression and anxiety symptoms. Collectively, high scores on the three disadvantage dimensions amplified symptom increases attributable to high neuroticism by 0.67 standard deviations. In contrast, neuroticism was not a significant risk for increases in symptoms among participants with few physical limitations, few social problems or high socio-economic status.

Conclusions

Risks from high neuroticism are not shared equally among adults in the USA. Interventions preventing or treating depression or anxiety via neuroticism could be targeted toward vulnerable subpopulations with physical, social or socio-economic disadvantages. Moreover, decreasing these disadvantages may reduce mental health risks from neuroticism.

Keywords

Anxietydepressionmoderatorsneuroticismrisk factors
Type
Original Articles
Information
Psychological Medicine , Volume 47 , Issue 10 , July 2017 , pp. 1794 - 1805
Copyright
Copyright © Cambridge University Press 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Alley, DE, Asomugha, CN, Conway, PH, Sanghavi, DM (2016). Accountable health communities: addressing social needs through Medicare and Medicaid. New England Journal of Medicine 374, 8–11.CrossRefGoogle ScholarPubMed
American Psychiatric Association (1987). Diagnostic and Statistical Manual of Mental Disorders, 3rd edn., revised. American Psychiatric Association: Washington, DC.Google Scholar
Barlow, DH, Ellard, KK, Sauer-Zavala, S, Bullis, JR, Carl, JR (2014 a). The origins of neuroticism. Perspectives on Psychological Science 9, 481–496.Google Scholar
Barlow, DH, Sauer-Zavala, S, Carl, J, Bullis, JR, Ellard, KK (2014 b). The nature, diagnosis, and treatment of neuroticism: back to the future. Clinical Psychological Science 2, 344–365.CrossRefGoogle Scholar
Blanco, C, Rubio, J, Wall, M, Wang, S, Jiu, CJ, Kendler, KS (2014). Risk factors for anxiety disorders: common and specific effects in a national sample. Depression and Anxiety 31, 756–764.Google Scholar
Brim, OG, Baltes, PB, Bumpass, LL, Cleary, PD, Featherman, DL, Shweder, RA (2010). National Survey of Midlife Development in the United States (MIDUS), 1995–1996. Inter-university Consortium for Political and Social Research: Ann Arbor, MI.Google Scholar
Brown, TA, Rosellini, AJ (2011). The direct and interactive effects of neuroticism and life stress on the severity and longitudinal course of depressive symptoms. Journal of Abnormal Psychology 120, 844–856.Google Scholar
Caska, CM, Renshaw, KD (2013). Personality traits as moderators of the associations between deployment experiences and PTSD symptoms in OEF/OIF service members. Anxiety, Stress and Coping: An International Journal 26, 36–51.Google Scholar
Clark, LA, Watson, D (1991). Tripartite model of anxiety and depression: psychometric evidence and taxonomic implications. Journal of Abnormal Psychology 100, 316–336.Google Scholar
Cole, MG, Dendukuri, N (2003). Risk factors for depression among elderly community subjects: a systematic review and meta-analysis. American Journal of Psychiatry 160, 1147–1156.Google Scholar
Cox, BJ, Taylor, S, Clara, IP, Roberts, L, Enns, MW (2008). Anxiety sensitivity and panic-related symptomatology in a representative community-based sample: a 1-year longitudinal analysis. Journal of Cognitive Psychotherapy 22, 48–56.Google Scholar
Cuthbert, BN, Insel, TR (2013). Toward the future of psychiatric diagnosis: the seven pillars of RDoC. BMC Medicine 11, 126.Google Scholar
de Beurs, E, Comijs, H, Twisk, JR, Sonnenberg, C, Beekman, AF, Deeg, D (2005). Stability and change of emotional functioning in late life: modelling of vulnerability profiles. Journal of Affective Disorders 84, 53–62.Google Scholar
Garg, A, Boynton-Jarrett, R, Dworkin, PH (2016). Avoiding the unintended consequences of screening for social determinants of health. JAMA 316, 813–814.Google Scholar
Hakulinen, C, Elovainio, M, Pulkki-Råback, L, Virtanen, M, Kivimäki, M, Jokela, M (2015). Personality and depressive symptoms: individual participant meta-analysis of 10 cohort studies. Depression and Anxiety 32, 461–470.Google Scholar
Ilieva, I (2015). Enhancement of healthy personality through psychiatric medication: the influence of SSRIs on neuroticism and extraversion. Neuroethics 8, 127–137.CrossRefGoogle Scholar
Jain, FA, Hunter, AM, Brooks, JO, Leuchter, AF (2013). Predictive socioeconomic and clinical profiles of antidepressant response and remission. Depression and Anxiety 30, 624–630.Google Scholar
Kazdin, AE, Blase, SL (2011). Rebooting psychotherapy research and practice to reduce the burden of mental illness. Perspectives on Psychological Science 6, 21–37.Google Scholar
Kelly, JM, Jakubovski, E, Bloch, MH (2015). Prognostic subgroups for remission and response in the Coordinated Anxiety Learning and Management (CALM) trial. Journal of Clinical Psychiatry 76, 267–278.Google Scholar
Kendler, KS, Gardner, CO (2016). Depressive vulnerability, stressful life events and episode onset of major depression: a longitudinal model. Psychological Medicine 46, 1865–1874.CrossRefGoogle ScholarPubMed
Kendler, KS, Kuhn, J, Prescott, CA (2004). The interrelationship of neuroticism, sex, and stressful life events in the prediction of episodes of major depression. American Journal of Psychiatry 161, 631–636.Google Scholar
Kennedy, SJ, Rapee, RM, Edwards, SL (2009). A selective intervention program for inhibited preschool-aged children of parents with an anxiety disorder: effects on current anxiety disorders and temperament. Journal of the American Academy of Child and Adolescent Psychiatry 48, 602–609.Google Scholar
Kessler, RC, Andrews, G, Mroczek, D, Ustun, B, Wittchen, H-U (1998). The World Health Organization Composite International Diagnostic Interview short-form (CIDI-SF). International Journal of Methods in Psychiatric Research 7, 171–185.CrossRefGoogle Scholar
Kotov, R, Gamez, W, Schmidt, F, Watson, D (2010). Linking ‘big’ personality traits to anxiety, depressive, and substance use disorders: a meta-analysis. Psychological Bulletin 136, 768–821.Google Scholar
Lachman, ME, Weaver, SL (1997). The Midlife Development Inventory (MIDI) Personality Scales: Scale Construction and Scoring. Technical report. Brandeis University, Department of Psychology: Waltham, MA.Google Scholar
Lahey, BB (2009). Public health significance of neuroticism. American Psychologist 64, 241–256.CrossRefGoogle ScholarPubMed
Lawton, MP, Brody, EM (1969). Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist 9, 179–186.Google Scholar
Lengel, GJ, Helle, AC, DeShong, HL, Meyer, NA, Mullins-Sweatt, SN (2016). Translational applications of personality science for the conceptualization and treatment of psychopathology. Clinical Psychology: Science and Practice 23, 288–308.Google Scholar
Lorenzo-Seva, U, ten Berge, JF (2006). Tucker's congruence coefficient as a meaningful index of factor similarity. Methodology: European Journal of Research Methods for the Behavioral and Social Sciences 2, 57–64.CrossRefGoogle Scholar
Luger, TM, Suls, J, Weg, MV (2014). How robust is the association between smoking and depression in adults? A meta-analysis using linear mixed-effects models. Addictive Behaviors 39, 1418–1429.Google Scholar
Luppino, FS, de Wit, LM, Bouvy, PF, Stijnen, T, Cuijpers, P, Penninx, BH, Zitman, FG (2010). Overweight, obesity, and depression: a systematic review and meta-analysis of longitudinal studies. Archives of General Psychiatry 67, 220–229.Google Scholar
Monroe, SM, Simons, AD (1991). Diathesis–stress theories in the context of life stress research: implications for the depressive disorders. Psychological Bulletin 110, 406–425.Google Scholar
Moreno-Peral, P, Conejo-Cerón, S, Motrico, E, Rodríguez-Morejón, A, Fernández, A, Ángel Bellón, J (2014). Risk factors for the onset of panic and generalised anxiety disorders in the general adult population: a systematic review of cohort studies. Journal of Affective Disorders 168, 337–348.CrossRefGoogle ScholarPubMed
Oddone, CG, Hybels, CF, McQuoid, DR, Steffens, DC (2011). Social support modifies the relationship between personality and depressive symptoms in older adults. American Journal of Geriatric Psychiatry 19, 123–131.Google Scholar
Ryff, C, Almeida, D, Ayanian, J, Binkley, N, Carr, D, Williams, D (2016). National Survey of Midlife Development in the United States (MIDUS 3), 2013–2014. Inter-university Consortium for Political and Social Research: Ann Arbor, MI.Google Scholar
Ryff, C, Almeida, DM, Ayanian, J, Carr, DS, Cleary, PD, Williams, D (2012). National Survey of Midlife Development in the United States (MIDUS II), 2004–2006. Inter-University Consortium for Political and Social Research: Ann Arbor, MI.Google Scholar
Schafer, JL, Graham, JW (2002). Missing data: our view of the state of the art. Psychological Methods 7, 147–177.Google Scholar
Schuster, TL, Kessler, RC, Aseltine, RH (1990). Supportive interactions, negative interactions, and depressed mood. American Journal of Community Psychology 18, 423–438.CrossRefGoogle ScholarPubMed
Shoham, V, Insel, TR (2011). Rebooting for whom?: portfolios, technology, and personalized intervention. Perspectives on Psychological Science 6, 478–482.Google Scholar
Slavich, GM, Irwin, MR (2014). From stress to inflammation and major depressive disorder: a social signal transduction theory of depression. Psychological Bulletin 140, 774–815.Google Scholar
Stiles-Shields, C, Corden, ME, Kwasny, MJ, Schueller, SM, Mohr, DC (2015). Predictors of outcome for telephone and face-to-face administered cognitive behavioral therapy for depression. Psychological Medicine 45, 3205–3215.Google Scholar
Tabachnick, BG, Fidell, LS (2013). Understanding Multivariate Statistics, 6th edn. Pearson: Boston, MA.Google Scholar
Vink, D, Aartsen, MJ, Schoevers, RA (2008). Risk factors for anxiety and depression in the elderly: a review. Journal of Affective Disorders 106, 29–44.CrossRefGoogle ScholarPubMed
Williams, DR, Yan, Y, Jackson, JS, Anderson, NB (1997). Racial differences in physical and mental health: socioeconomic status, stress and discrimination. Journal of Health Psychology 2, 335–351.Google Scholar
World Health Organization (2008). Waist Circumference and Waist–hip Ratio: Report of a WHO Expert Consultation. World Health Organization: Geneva, Switzerland.Google Scholar
Supplementary material: File

Vittengl supplementary material

Tables S1-S4

Download Vittengl supplementary material(File)
File 155.1 KB