Skip to main content Accessibility help
×
Home
Hostname: page-component-559fc8cf4f-rz424 Total loading time: 0.412 Render date: 2021-03-07T21:52:41.240Z Has data issue: true Feature Flags: { "shouldUseShareProductTool": true, "shouldUseHypothesis": true, "isUnsiloEnabled": true, "metricsAbstractViews": false, "figures": false, "newCiteModal": false, "newCitedByModal": true }

Cognitive ability as a moderator of the association between social disadvantage and psychological distress: evidence from a population-based sample

Published online by Cambridge University Press:  24 August 2018

Emma Bridger
Affiliation:
Department of Psychology, Faculty of Business, Law and Social Sciences, Birmingham City University, Birmingham B4 7BD, UK
Michael Daly
Affiliation:
Department of Psychology, Maynooth University, National University of Ireland, Maynooth, Co. Kildare, Ireland UCD Geary Institute, University College Dublin, Belfield, Dublin 4, Ireland
Corresponding
E-mail address:

Abstract

Background

Social disadvantage consistently predicts both self-reported distress and clinically diagnosed disorders such as depression. Yet, many individuals who are exposed to disadvantage do not report high levels of distress. This study extends our recent work showing that high cognitive ability may protect against the negative health consequences of exposure to disadvantaged backgrounds. We test whether this ‘buffer effect’ exists across clinically relevant indices of mental health in a population-representative sample.

Methods

In total, 27 985 participants were drawn from the UK Household Longitudinal Study (Understanding Society). Clinical diagnoses of depression and clinically relevant measures of psychological distress [i.e. Short Form-12 (SF-12) Mental Component, General Health Questionnaire (GHQ)] and trait neuroticism were assessed. Cognitive ability was derived from performance on word recall, verbal fluency and numerical ability tasks. Early-life disadvantage was gauged using family background measures assessing parental education and occupation at age 14.

Results

Background disadvantage predicted increased levels of reported psychological distress and neuroticism. These associations were moderated by cognitive ability. Across all available mental health measures, the negative association between early-life disadvantage and poor adult mental health was strongest at low (−1 s.d.) cognitive ability and was no longer evident at high (+1 s.d.) levels of cognitive ability.

Conclusions

The results provide support for a cognitive buffering hypothesis linking high cognitive ability to a decrease in the magnitude of the social gradient in mental health. Those disadvantaged by both low socioeconomic status and low cognitive ability may benefit from targeted prevention and treatment programmes aiming to reduce socioeconomic disparities in mental health.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2018 

Access options

Get access to the full version of this content by using one of the access options below.

References

Adler, NE, Boyce, T, Chesney, MA, Cohen, S, Folkman, S, Kahn, RL and Syme, SL (1994) Socioeconomic status and health: the challenge of the gradient. American Psychologist 49, 1524.CrossRefGoogle ScholarPubMed
Barnett, JH, Salmond, CH, Jones, PB and Sahakian, BJ (2006) Cognitive reserve in neuropsychiatry. Psychological Medicine 36, 10531064.CrossRefGoogle ScholarPubMed
Batty, GD, Lawlor, DA, Macintyre, S, Clark, H and Leon, DA (2005) Accuracy of adults’ recall of childhood social class: findings from the Aberdeen children of the 1950s study. Journal of Epidemiology and Community Healthy 59, 898903.CrossRefGoogle ScholarPubMed
Beier, ME and Ackerman, PL (2003) Determinants of health knowledge: an investigation of age, gender, abilities, personality, and interests. Journal of Personality and Social Psychology 84, 439448.CrossRefGoogle ScholarPubMed
Belsky, DW, Moffitt, TE, Corcoran, DL, Domingue, B, Harrington, H, Hogan, S, Houts, R, Ramrakha, S, Sugden, K, Williams, B, Poulton, R and Caspi, A (2016) The genetics of success: how single-nucleotide polymorphisms associated with educational attainment relate to life-course development. Psychological Science 27, 957972.CrossRefGoogle ScholarPubMed
Boyce, CJ, Wood, AM, Delaney, L and Ferguson, E (2017) How do personality and social structures interact with each other to predict important life outcomes? The importance of accounting for personality change. European Journal of Personality 31, 279290.CrossRefGoogle Scholar
Bridger, E and Daly, M (2017) Does cognitive ability buffer the link between childhood disadvantage and adult health? Health Psychology 36, 966976.CrossRefGoogle ScholarPubMed
Brown, M (2014) Assessing recall of early life circumstances: evidence from the National Child Development Study. Longitudinal and Life Course Studies 5, 6478.Google Scholar
Buck, N and McFall, S (2012) Understanding Society: design overview. Longitudinal and Life Course Studies 3, 517.Google Scholar
Chatterji, P, Alegría, M, Lu, M and Takeuchi, D (2007) Psychiatric disorders and labor market outcomes: evidence from the National Latino and Asian American Study. Health Economics 16, 1069e1090. http://dx.doi.org/10.1002/hec.1210.CrossRefGoogle ScholarPubMed
Daly, M, McMinn, D and Allan, JL (2014) A bidirectional relationship between physical activity and executive function in older adults. Frontiers in Human Neuroscience 8, 1044.Google ScholarPubMed
Delgadillo, J, Asaria, M, Ali, S and Gilbody, S (2016) On poverty, politics and psychology: the socioeconomic gradient of mental healthcare utilisation and outcomes. The British Journal of Psychiatry 209, 429430.CrossRefGoogle ScholarPubMed
Dohrenwend, BP, Levav, I, Shrout, PE, Schwartz, S, Naveh, G, Link, BG, Skodol, AE and Stueve, A (1992) Socioeconomic status and psychiatric disorders: the causation-selection issue. Science 255, 946952.CrossRefGoogle ScholarPubMed
Donnellan, MB and Lucas, RE (2008) Age differences in the Big Five across the life span: evidence from two national samples. Psychology and Aging 23, 558566.CrossRefGoogle ScholarPubMed
Egan, M, Daly, M and Delaney, L (2016) Adolescent psychological distress, unemployment, and the Great Recession: evidence from the National Longitudinal Study of Youth 1997. Social Science & Medicine 156, 98105.CrossRefGoogle ScholarPubMed
Engle, PL, Fernald, LC, Alderman, H, Behrman, J, O'Gara, C, Yousafzai, A, de Mello, MC, Hidrobo, M, Ulkuer, N, Ertem, I, Iltus, S, and the Global Child Development Steering Group. (2011) Strategies for reducing inequalities and improving developmental outcomes for young children in low-income and middle-income countries. The Lancet 378, 13391353.CrossRefGoogle ScholarPubMed
Fergusson, DM and Lynskey, MT (1996) Adolescent resiliency to family adversity. Journal of Child Psychology and Psychiatry 37, 281292.CrossRefGoogle ScholarPubMed
Fergusson, DM and Horwood, LJ (2003) Resilience to childhood adversity: results of a 21 year study. In Luthar, SS (ed), Resilience and Vulnerability: Adaptation in the Context of Childhood Adversities. Cambridge: Cambridge University Press, pp. 130155.CrossRefGoogle Scholar
Flouri, E, Mavroveli, S and Panourgia, C (2013) The role of general cognitive ability in moderating the relation of adverse life events to emotional and behavioural problems. British Journal of Psychology 104, 130139.CrossRefGoogle ScholarPubMed
Flouri, E, Midouhas, E and Joshi, H (2014) Family poverty and trajectories of children's emotional and behavioural problems: the moderating roles of self-regulation and verbal cognitive ability. Journal of Abnormal Child Psychology 42, 10431056.CrossRefGoogle ScholarPubMed
Galobardes, B, Lynch, JW and Davey-Smith, G (2008) Is the association between childhood socioeconomic circumstances and cause-specific mortality established? Update of a systematic review. Journal of Epidemiology and Community Health 62, 387390.CrossRefGoogle ScholarPubMed
Gill, SC, Butterworth, P, Rodgers, B and Mackinnon, A (2007) Validity of the mental health component scale of the 12-item Short-Form Health Survey (MCS-12) as measure of common mental disorders in the general population. Psychiatry Research 152, 6371.CrossRefGoogle ScholarPubMed
Gilman, SE, Kawachi, I, Fitzmaurice, GM and Buka, SL (2002) Socioeconomic status in childhood and the lifetime risk of major depression. International Journal of Epidemiology 31, 359367.CrossRefGoogle ScholarPubMed
Goldberg, DP, Gater, R, Sartorius, N, Ustun, TB, Piccinelli, M, Gureje, O and Rutter, C (1997) The validity of two version of the GHQ in the WHO study of mental illness in general health care. Psychological Medicine 27, 191197.CrossRefGoogle ScholarPubMed
Hakulinen, C, Elovainio, M, Pulkki-Råback, L, Virtanen, M, Kivimäki, M and Jokela, M (2015) Personality and depressive symptoms: individual-participant meta-analysis of 10 cohort studies. Depression and Anxiety 32, 461–460.CrossRefGoogle ScholarPubMed
Heberle, AE and Carter, AS (2015) Cognitive aspects of young children's experience of economic disadvantage. Psychological Bulletin 141, 723746.CrossRefGoogle ScholarPubMed
Henry, JD and Crawford, JR (2004) A meta-analytic review of verbal fluency performance following focal cortical lesions. Neuropsychology 18, 284295. doi: 10.1037/0894-4105.18.2.284.CrossRefGoogle ScholarPubMed
Jivraj, S, Goodman, A, Ploubidis, GB and de Oliveira, C (2017) Testing comparability between retrospective life history data and prospective birth cohort study data. Journals of Gerontology: Series B, 111. doi: 10.1093/geronb/gbx042.Google ScholarPubMed
Jylhä, P and Isometsä, E (2006) The relationship of neuroticism and extraversion to the symptoms of anxiety and depression in the general population. Depression and Anxiety 23, 281289.CrossRefGoogle ScholarPubMed
Kelly, MJ, Dunstan, FD, Lloyd, K and Fone, DL (2008) Evaluating cutpoints for the MHI-5 and MCS using the GHQ-12: a comparison of five different methods. BMC Psychiatry 8, 10. doi: 10.1186/1471-244X-8-10.CrossRefGoogle ScholarPubMed
Klebanov, PK, Brooks-Gunn, J and Duncan, GJ (1994) Does neighborhood and family poverty affect mothers’ parenting, mental health, and social support? Journal of Marriage and the Family 56, 441455.CrossRefGoogle Scholar
Knies, G (2017) Understanding Society–UK Household Longitudinal Study: Wave 1–6, 2009–2015, User Guide, Version 1.s2. Colchester: University of Essex.Google Scholar
Koenen, KC, Moffitt, TE, Roberts, AL, Martin, LT, Kubzansky, L, Harrington, H, Poulton, R and Caspi, C (2009) Childhood IQ and adult mental disorders: a test of the cognitive reserve hypothesis. American Journal of Psychiatry 166, 5057.CrossRefGoogle ScholarPubMed
Lang, FR, John, D, Lüdtke, O, Schupp, J and Wagner, GG (2011) Short assessment of the Big Five: robust across survey methods except telephone interviewing. Behavior Research Methods 43, 548567.CrossRefGoogle ScholarPubMed
Lawlor, DA, Sterne, JAC, Tynelius, P, Davey Smith, G and Rasmussen, F (2006) Association of childhood socioeconomic position with cause-specific mortality in a prospective record linkage study of 1839384 individuals. American Journal of Epidemiology 164, 907915.CrossRefGoogle Scholar
Legg, S and Hutter, M (2007) A collection of definitions of intelligence. Available at https://arxiv.org/pdf/0706.3639.pdf (Accessed on 18 November 2017).Google Scholar
Leventhal, T and Brooks-Gunn, J (2003) Moving to opportunity: an experimental study of neighborhood effects on mental health. American Journal of Public Health 93, 15761582.CrossRefGoogle ScholarPubMed
Lorant, V, Deliege, D, Eaton, , Robert, A, Philippot, P and Ansseau, M (2003) Socioeconomic inequalities in depression: a meta-analysis. American Journal of Epidemiology 157, 98112.CrossRefGoogle ScholarPubMed
Luthar, SS (2006) Resilience in development: a synthesis of research across five decades. In Cicchetti, D and Cohen, DJ (eds), Developmental Psychopathology, Vol 3. Risk, Disorder, and Adaptation, New York, NY: Wiley, pp. 739795.Google Scholar
Martin, LT, Kubzansky, LD, LeWinn, KZ, Lipsitt, LP, Satz, P and Buka, SL (2007) Childhood cognitive performance and risk of generalized anxiety disorder. International Journal of Epidemiology 36, 769775.CrossRefGoogle ScholarPubMed
Masten, A (2001) Ordinary magic: resilience processes in development. American Psychologist 56, 227238.CrossRefGoogle ScholarPubMed
Masten, A, Hubbard, JJ, Gest, SD, Tellegen, A, Garmezy, N and Ramirez, M (1999) Competence in the context of adversity: pathways to resilience and maladaptation from childhood to late adolescence. Development and Psychopathology 11, 143169.CrossRefGoogle ScholarPubMed
Matthews, KA and Gallo, L (2011) Psychological perspectives on pathways linking socioeconomic status and physical health. Annual Review of Psychology 62, 501530.CrossRefGoogle ScholarPubMed
Melchior, M, Moffitt, TE, Milne, BJ, Poulton, R and Caspi, A (2007) Why do children from socioeconomically disadvantaged families suffer from poor health when they reach adulthood? A life-course study. American Journal of Epidemiology 166, 966974.CrossRefGoogle ScholarPubMed
Melchior, M, Chastang, J-F, Head, J, Goldberg, M, Zins, M, Nabi, H and Younes, N (2013) Socioeconomic position predicts long-term depression trajectory: a 13-year follow-up of the GAZEL cohort study. Molecular Psychiatry 18, 112121.CrossRefGoogle ScholarPubMed
Molarius, A, Berglund, K, Eriksson, C, Eriksson, HG, Lindén-Boström, M, Nordström, E, Persson, C, Sahlqvist, L, Starrin, B and Ydreborg, B (2009) Mental health symptoms in relation to socio-economic conditions and lifestyle factors – a population-based study in Sweden. BMC Public Health 9, 302311.CrossRefGoogle ScholarPubMed
Monroe, SM and Simon, AD (1991) Diathesis-stress theories in the context of life stress research: implications for the depressive disorders. Psychological Bulletin 110, 406425.CrossRefGoogle ScholarPubMed
Navrady, LB, Ritchie, SJ, Chan, SWY, Kerr, DM, Adams, MJ, Hawkins, EH, Porteous, D, Deary, IJ, Gale, CR, Batty, GD and McIntosh, AM (2017) Intelligence and neuroticism in relation to depression and psychological distress: evidence from two large population cohorts. European Psychiatry 43, 5865.CrossRefGoogle ScholarPubMed
Nowak, C and Heinrichs, N (2008) A comprehensive meta-analysis of Triple P-Positive Parenting Program using hierarchical linear modeling: effectiveness and moderating variables. Clinical Child and Family Psychology Review 11, 114.CrossRefGoogle ScholarPubMed
Office of National Statistics – Standard Occupational Classification (2010) Volume 1 Structure and descriptions of unit groups. Available at https://www.ons.gov.uk/methodology/classificationsandstandards/standardoccupationalclassificationsoc/soc2010 (Accessed on 18 November 2017).Google Scholar
Pargas, RCM, Brennan, PA, Hammen, C and Le Brocque, R (2010) Resilience to maternal depression in young adulthood. Developmental Psychology 46, 805814.CrossRefGoogle ScholarPubMed
Power, C and Manor, O (1992) Explaining social class differences in psychological health among young adults: a longitudinal perspective. Social Psychiatry and Psychiatric Epidemiology 27, 284291.Google ScholarPubMed
Riglin, L, Collishaw, S, Shelton, KS, McManus, IC, NG-Knight, T, Sellers, R, Thapar, AK, Frederickson, N and Rice, F (2016) Higher cognitive ability buffers stress-related depressive symptoms in adolescent girls. Development and Psychopathology 28, 97109.CrossRefGoogle ScholarPubMed
Ritscher, JEB, Warner, V, Johnson, JG and Dohrenwend, BP (2001) Inter-generational longitudinal study of social class and depression: a test of social causation and social selection models. British Journal of Psychiatry 178(Suppl. 40), s84s90.CrossRefGoogle Scholar
Rutter, M (2013) Annual Research Review: resilience–clinical implications. Journal of Child Psychology and Psychiatry 54, 474487.CrossRefGoogle Scholar
Rutter, M, Tizard, J and Whitmore, K (1970) Education, Health and Behaviour. London, United Kingdom: Longman.Google Scholar
Schmeichel, BJ and Tang, D (2015) Individual differences in executive functioning and their relationship to emotional processes and responses. Current Directions in Psychological Science 24, 9398.CrossRefGoogle Scholar
Smith, J and Smith, G (2010) Long-term economic costs of psychological problems during childhood. Social Science and Medicine 71, 110e115. http://dx.doi.org/10.1016/j.socscimed.2010.02.046.CrossRefGoogle ScholarPubMed
Stansfield, SA, Clark, C, Rodgers, B, Caldwell, T and Power, C (2011) Repeated exposure to socioeconomic disadvantage and health selection as life course pathways to mid-life depressive and anxiety disorders. Social Psychiatry and Psychiatric Epidemiology 46, 549558.CrossRefGoogle Scholar
Stern, Y (2002) What is cognitive reserve? Theory and research application of the reserve concept. Journal of the International Neuropsychological Society 8, 448460.CrossRefGoogle ScholarPubMed
Vilagut, G, Forero, CG, Pinto-Meza, A, Haro, JM, de Graaf, R, Bruffaerts, R, Kovess, V, de Girolamo, G, Matschinger, H, Ferrer, M and Alonso, J (2013) The Mental Component of the Short-Form 12 Health Survey (SF-12) as a measure of depressive disorders in the general population: results with three alternative scoring methods. Value in Health 16, 564573.CrossRefGoogle ScholarPubMed
Ware, JE, Kosinski, M and Keller, SD (1996) A 12-item Short-Form Health Survey: construction of scales and preliminary tests of reliability and validity. Medical Care 34, 220233.CrossRefGoogle ScholarPubMed
Ware, JE, Kosinski, M, Turner-Bowker, DM and Gandek, B (2001) How to Score Version 2 of the SF-12® Health Survey (With a Supplement Documenting Version 1). Lincoln, RI: Quality Metric Incorporated.Google Scholar

Bridger and Daly supplementary material

Tables S1 and S2

File 30 KB

Altmetric attention score

Full text views

Full text views reflects PDF downloads, PDFs sent to Google Drive, Dropbox and Kindle and HTML full text views.

Total number of HTML views: 55
Total number of PDF views: 202 *
View data table for this chart

* Views captured on Cambridge Core between 24th August 2018 - 7th March 2021. This data will be updated every 24 hours.

Send article to Kindle

To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Cognitive ability as a moderator of the association between social disadvantage and psychological distress: evidence from a population-based sample
Available formats
×

Send article to Dropbox

To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

Cognitive ability as a moderator of the association between social disadvantage and psychological distress: evidence from a population-based sample
Available formats
×

Send article to Google Drive

To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

Cognitive ability as a moderator of the association between social disadvantage and psychological distress: evidence from a population-based sample
Available formats
×
×

Reply to: Submit a response


Your details


Conflicting interests

Do you have any conflicting interests? *