Hostname: page-component-cd9895bd7-dk4vv Total loading time: 0 Render date: 2024-12-25T08:35:56.676Z Has data issue: false hasContentIssue false
  • English
  • Français

Taking an intersectional approach to define latent classes of socioeconomic status, ethnicity and migration status for psychiatric epidemiological research

Published online by Cambridge University Press:  10 April 2017

L. Goodwin ,
B. Gazard ,
L. Aschan ,
S. MacCrimmon ,
M. Hotopf  and
S. L. Hatch
L. Goodwin
Affiliation:
King's College London, Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, 10 Cutcombe Road, London, UK Department of Psychological Sciences, University of Liverpool, Liverpool, UK
B. Gazard*
Affiliation:
King's College London, Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, 10 Cutcombe Road, London, UK
L. Aschan
Affiliation:
King's College London, Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, 10 Cutcombe Road, London, UK
S. MacCrimmon
Affiliation:
King's College London, Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, 10 Cutcombe Road, London, UK
M. Hotopf
Affiliation:
King's College London, Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, 10 Cutcombe Road, London, UK South London and Maudsley NHS Foundation Trust, London, UK
S. L. Hatch
Affiliation:
King's College London, Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, 10 Cutcombe Road, London, UK
*
*Address for correspondence: B. Gazard, Psychological Medicine, Weston Education Centre, Cutcombe Road, London, SE5 9RJ, UK. (Email: [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

Aims.

Inequalities in mental health are well documented using individual social statuses such as socioeconomic status (SES), ethnicity and migration status. However, few studies have taken an intersectional approach to investigate inequalities in mental health using latent class analysis (LCA). This study will examine the association between multiple indicator classes of social identity with common mental disorder (CMD).

Methods.

Data on CMD symptoms were assessed in a diverse inner London sample of 1052 participants in the second wave of the South East London Community Health study. LCA was used to define classes of social identity using multiple indicators of SES, ethnicity and migration status. Adjusted associations between CMD and both individual indicators and multiple indicators of social identity are presented.

Results.

LCA identified six groups that were differentiated by varying levels of privilege and disadvantage based on multiple SES indicators. This intersectional approach highlighted nuanced differences in odds of CMD, with the economically inactive group with multiple levels of disadvantage most likely to have a CMD. Adding ethnicity and migration status further differentiated between groups. The migrant, economically inactive and White British, economically inactive classes both had increased odds of CMD.

Conclusions.

This is the first study to examine the intersections of SES, ethnicity and migration status with CMD using LCA. Results showed that both the migrant, economically inactive and the White British, economically inactive classes had a similarly high prevalence of CMD. Findings suggest that LCA is a useful methodology for investigating health inequalities by intersectional identities.

Keywords

Epidemiologymental healthresearch design and methodspopulation surveycommunity mental health
Type
Original Articles
Information
Epidemiology and Psychiatric Sciences , Volume 27 , Issue 6 , December 2018 , pp. 589 - 600
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.)

Footnotes

†

Joint first authors.

References

Akaike, H (1987). Factor analysis and AIC. Psychometrika 52, 317–332.Google Scholar
Anderson, B, Blinder, S (2011). Who Counts as a Migrant? Definitions and Their Consequences. Briefing, The Migration Observatory at the University of Oxford: Oxford, UK.Google Scholar
Bauer, GR (2014). Incorporating intersectionality theory into population health research methodology: challenges and the potential to advance health equity. Social Science and Medicine 110, 10–17.Google Scholar
Butterworth, P, Leach, L, McManus, S, Stansfeld, S (2013). Common mental disorders, unemployment and psychosocial job quality: is a poor job better than no job at all? Psychological Medicine 43, 1763–1772.Google Scholar
Casey, MM, Call, KT, Klingner, JM (2001). Are rural residents less likely to obtain recommended preventive healthcare services? American Journal of Preventive Medicine 21, 182–188.Google Scholar
Castles, S (2003). Towards a sociology of forced migration and social transformation. Sociology 37, 13–34.Google Scholar
Collins, LM, Lanza, ST (2013). Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences. John Wiley & Sons: Hoboken, NJ.Google Scholar
Collins, PH (2000). Gender, black feminism, and black political economy. Annals of the American Academy of Political and Social Science 568, 41–53.Google Scholar
Crenshaw, K (1991). Mapping the margins: intersectionality, identity politics, and violence against women of color. Stanford Law Review, 1241–1299.Google Scholar
Cutler, DM, Lleras-Muney, A (2006). Education and Health: Evaluating Theories and Evidence. National Bureau of Economic Research: Cambridge, MA.Google Scholar
Darlington, F, Geography, H, Norman, P, Exeter, DJ (2015). Exploring ethnic inequalities in health: evidence from the Health Survey for England, 1998–2011.Google Scholar
Das-Munshi, J, Becares, L, Dewey, ME, Stansfeld, SA, Prince, MJ (2010). Understanding the effect of ethnic density on mental health: multi-level investigation of survey data from England. BMJ 341, 5367.Google Scholar
Dey, AN, Lucas, JW (2006). Physical and Mental Health Characteristics of US-and Foreign-born Adults, United States, 1998–2003. US Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Health Statistics: Washington, DC.Google Scholar
Fairley, L, Cabieses, B, Small, N, Petherick, ES, Lawlor, DA, Pickett, KE, Wright, J (2014). Using latent class analysis to develop a model of the relationship between socioeconomic position and ethnicity: cross-sectional analyses from a multi-ethnic birth cohort study. BMC Public Health 14, 835.Google Scholar
Feldman, DC (1996). The nature, antecedents and consequences of underemployment. Journal of Management 22, 385–407.Google Scholar
Ford, E, Clark, C, McManus, S, Harris, J, Jenkins, R, Bebbington, P, Brugha, T, Meltzer, H, Stansfeld, S (2010). Common mental disorders, unemployment and welfare benefits in England. Public Health 124, 675–681.Google Scholar
Fryers, T, Melzer, D, Jenkins, R (2003). Social inequalities and the common mental disorders – a systematic review of the evidence. Social Psychiatry and Psychiatric Epidemiology 38, 229–237.Google Scholar
Fuller-Rowell, TE, Evans, GW, Ong, AD (2012). Poverty and health the mediating role of perceived discrimination. Psychological Science 23, 734–739.Google Scholar
Galea, S, Freudenberg, N, Vlahov, D (2005). Cities and population health. Social Science and Medicine 60, 1017–1033.Google Scholar
Garnett, BR, Masyn, KE, Austin, SB, Miller, M, Williams, DR, Viswanath, K (2014). The intersectionality of discrimination attributes and bullying among youth: an applied latent class analysis. Journal of Youth and Adolescence 43, 1225–1239.Google Scholar
Gazard, B, Frissa, S, Nellums, L, Hotopf, M, Hatch, SL (2014). Challenges in researching migration status, health and health service use: an intersectional analysis of a South London community. Ethnicity and Health, 1–30.Google Scholar
Geyer, S, Hemström, Ö, Peter, R, Vågerö, D (2006). Education, income, and occupational class cannot be used interchangeably in social epidemiology. Empirical evidence against a common practice. Journal of Epidemiology and Community Health 60, 804–810.Google Scholar
Gideon, S (1978). Estimating the dimension of a model. Annals of Statistics 6, 461–464.Google Scholar
Grollman, EA (2014). Multiple disadvantaged statuses and health the role of multiple forms of discrimination. Journal of Health and Social Behavior 55, 3–19.Google Scholar
Hagenaars, JA, McCutcheon, AL (2002). Applied Latent Class Analysis. Cambridge University Press: Cambridge, UK.Google Scholar
Hatch, S, Gazard, B, Williams, D, Frissa, S, Goodwin, L, Hotopf, M, Team, SS (2016). Discrimination and common mental disorder among migrant and ethnic groups: findings from a South East London Community sample. Social Psychiatry and Psychiatric Epidemiology, 1–13.Google Scholar
Hatch, SL, Frissa, S, Verdecchia, M, Stewart, R, Fear, NT, Reichenberg, A, Morgan, C, Kankulu, B, Clark, J, Gazard, B, Medcalf, R, Team, S, Hotopf, M (2011). Identifying socio-demographic and socioeconomic determinants of health inequalities in a diverse London community: the South East London Community Health (SELCoH) study. BMC Public Health, 861.Google Scholar
Ibrahim, AK, Kelly, SJ, Adams, CE, Glazebrook, C (2013). A systematic review of studies of depression prevalence in university students. Journal of Psychiatric Research 47, 391–400.Google Scholar
Jenkins, R, Bhugra, D, Bebbington, P, Brugha, T, Farrell, M, Coid, J, Fryers, T, Weich, S, Singleton, N, Meltzer, H (2008). Debt, income and mental disorder in the general population. Psychological Medicine 38, 1485–1493.Google Scholar
Karlsen, S, Nazroo, JY (2002). Relation between racial discrimination, social class, and health among ethnic minority groups. American Journal of Public Health 92, 624–631.Google Scholar
Lewis, G, Pelosi, AJ, Araya, R, Dunn, G (1992). Measuring psychiatric disorder in the community: a standardized assessment for use by lay interviewers. Psychological Medicine 22, 465–486.Google Scholar
Lo, Y, Mendell, NR, Rubin, DB (2001). Testing the number of components in a normal mixture. Biometrika 88, 767–778.Google Scholar
Lorant, V, Deliège, D, Eaton, W, Robert, A, Philippot, P, Ansseau, M (2003). Socioeconomic inequalities in depression: a meta-analysis. American Journal of Public Health 157, 98–112.Google Scholar
Malmusi, D, Borrell, C, Benach, J (2010). Migration-related health inequalities: showing the complex interactions between gender, social class and place of origin. Social Science and Medicine 71, 1610–1619.Google Scholar
Maydeu-Olivares, A, Joe, H (2006). Limited information goodness-of-fit testing in multidimensional contingency tables. Psychometrika 71, 713–732.Google Scholar
McFadden, E, Luben, R, Bingham, S, Wareham, N, Kinmonth, A-L, Khaw, K-T (2009). Self-rated health does not explain the socioeconomic differential in mortality: a prospective study in the EPIC-Norfolk cohort. Journal of Epidemiology and Community Health 63, 329–331.Google Scholar
Muthén, LK, Muthén, BO (2012). Mplus. Comprehensive Modelling Program for Applied Researchers: User's Guide. Muthén & Muthén: Los Angeles, CA.Google Scholar
Nash, JC (2008). Re-thinking intersectionality. Feminist Review 89, 1–15.Google Scholar
Nazroo, JY (2003). The structuring of ethnic inequalities in health: economic position, racial discrimination, and racism. American Journal of Public Health 93, 277–284.Google Scholar
Nylund, KL, Asparouhov, T, Muthén, BO (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: a Monte Carlo simulation study. Structural equation modeling 14, 535–569.Google Scholar
Office for National Statistics (2011). Census 2011. Retrieved 20 January 2017 from http://www.nomisweb.co.ukGoogle Scholar
Office of Population Cencuses and Surveys (1980). Classification of Occupations. Office for National Statistics: London, UK.Google Scholar
Psaki, SR, Seidman, JC, Miller, M, Gottlieb, M, Bhutta, ZA, Ahmed, T, Ahmed, AS, Bessong, P, John, SM, Kang, G (2014). Measuring socioeconomic status in multicountry studies: results from the eight-country MAL-ED study. Population Health Metrics 12, 8.Google Scholar
Ramaswamy, V, DeSarbo, WS, Reibstein, DJ, Robinson, WT (1993). An empirical pooling approach for estimating marketing mix elasticities with PIMS data. Marketing Science 12, 103–124.Google Scholar
Rosenfield, S (2012). Triple jeopardy? Mental health at the intersection of gender, race, and class. Social Science and Medicine 74, 1791–1801.Google Scholar
Savage, M, Devine, F, Cunningham, N, Taylor, M, Li, Y, Hjellbrekke, J, Le Roux, B, Friedman, S, Miles, A (2013). A new model of social class? Findings from the BBC's Great British Class Survey experiment. Sociology 47, 219–250.Google Scholar
Schofield, P, Ashworth, M, Jones, R (2011). Ethnic isolation and psychosis: re-examining the ethnic density effect. Psychological Medicine 41, 1263–1269.Google Scholar
Sclove, SL (1987). Application of model-selection criteria to some problems in multivariate analysis. Psychometrika 52, 333–343.Google Scholar
Smith, NR, Kelly, YJ, Nazroo, JY (2009). Intergenerational continuities of ethnic inequalities in general health in England. Journal of Epidemiology and Community Health 63, 253–258.Google Scholar
Statacorp (2009). Stata Statistical Software: Release 11. Statacorp: College Station, TX.Google Scholar
Vyas, S & Kumaranayake, L (2006). Constructing socio-economic status indices: how to use principal components analysis. Health Policy and Planning 21, 459–468.Google Scholar
Weich, S, Nazroo, J, Sproston, K, McMANUS, S, Blanchard, M, Erens, B, Karlsen, S, King, M, Lloyd, K, Stansfeld, S (2004). Common mental disorders and ethnicity in England: the EMPIRIC study. Psychological Medicine 34, 1543–1551.Google Scholar
Williams, DR (1999). Race, socioeconomic status, and health the added effects of racism and discrimination. Annals of the New York Academy of Sciences 173–188.Google Scholar
Williams, DR, Yu, Y, Jackson, JS, Anderson, NB (1997). racial differences in physical and mental health socio-economic status, stress and discrimination. Journal of Health Psychology 2, 335–351.Google Scholar
Supplementary material: File

Goodwin supplementary material

Tables S1-S3

Download Goodwin supplementary material(File)
File 56.6 KB