Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-25T09:18:00.511Z Has data issue: false hasContentIssue false

Investigating ‘place effects’ on mental health: implications for population-based studies in psychiatry

Published online by Cambridge University Press:  26 November 2014

T. Astell-Burt*
Affiliation:
School of Science and Health, University of Western Sydney, Australia School of Geography and Geosciences, University of St Andrews, UK
X. Feng
Affiliation:
School of Health and Society, University of Wollongong, Australia Boden Institute of Obesity, Nutrition, Exercise and Eating Disorders, University of Sydney Menzies Centre for Health Policy, University of Sydney
*
*Address for correspondence: Dr Thomas Astell-Burt, School of Science and Health, University of Western Sydney, Australia; School of Geography and Geosciences, University of St Andrews, UK. (Email: [email protected])

Abstract

Background.

Interest in features of our local environments that may promote better mental health and wellbeing continues to rise among decision makers. Our purpose was to highlight a selection of these challenges and some promising avenues for enhancing the quality of evidence.

Method.

An analysis of approximately 267, 000 people was used to test the local relative deprivation hypothesis, wherein the shortfall of a person's socioeconomic circumstances from their neighbours is said to impact negatively upon mental health. This case was used to anchor further discussion of challenges to identifying and interpreting genuine ‘place effects’ from spurious correlations.

Results.

A Median Odds Ratio of 1.29 computed via multilevel logistic regression showed that the odds of experiencing psychological distress (as measured by the Kessler score) varied by geographical area. Approximately 67% of this was attributed to a cross-classified measure of household income and neighbourhood deprivation. Compared to people on high incomes living in affluent neighbourhoods, the odds ratio of psychological distress for people on low incomes in affluent areas was 4.73 (95% confidence interval (95% CI) 4.39, 5.09), whereas that for people on low incomes in deprived areas was significantly higher at 5.83 (95% CI 5.41, 6.28).

Conclusions.

While no evidence was found to support local relative deprivation hypothesis, the pattern suggests that more affluent areas may contain features that are conducive to better mental health. Selection of bespoke geographical boundaries, use of directed acyclic graphs and more evaluations of natural experiments are likely to be important in taking the field of enquiry onwards.

Type
Special Article
Copyright
Copyright © Cambridge University Press 2014 

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

45 and up Study Collaborators (2008) Cohort profile: the 45 and up study. International Journal of Epidemiology 37, 941947.Google Scholar
Antonovsky, A (1996) The salutogenic model as a theory to guide health promotion. Health Promotion International 11, 1118.Google Scholar
Astell-Burt, T, Feng, X & Kolt, GS (2013). Mental health benefits of neighbourhood green space are stronger among physically active adults in middle-to-older age: evidence from 260,061 Australians. Preventive Medicine 57, 601606.CrossRefGoogle ScholarPubMed
Astell-Burt, T, Mitchell, R, Hartig, T (2014). The association between green space and mental health varies across the lifecourse. A longitudinal study. Journal of Epidemiology and Community Health 68, 578583.Google Scholar
Australian Government (2011). Our Cities Our Future: A National Urban Policy for a Productive, Sustainable and Liveable Future. Department of Infrastructure and Transport: Canberra.Google Scholar
Bond, L, Sautkina, E, Kearns, A (2010). Mixed messages about mixed tenure: do reviews tell the real story? Housing Studies, 126.Google Scholar
Boyle, P, Norman, P, Rees, P (2004 a) Changing places. Do changes in the relative deprivation of areas influence limiting long-term illness and mortality among non-migrant people living in non-deprived households? Social Science and Medicine 58, 24592471.Google Scholar
Boyle, P, Norman, P, Popham, F (2009). Social mobility: evidence that it can widen health inequalities. Social Science and Medicine 68, 18351842.CrossRefGoogle ScholarPubMed
Boyle, PJ, Gatrell, AC, Duke-Williams, O (2004 b). Limiting long-term illness and locality deprivation in England and Wales: Acknowledging the ‘socio-spatial context’. In The Geographies of Health Inequality in the Developed World (ed. Boyle, PJ, Curtis, S, Graham, E and Moore, E). Ashgate: London, 293308.Google Scholar
Branas, CC, Cheney, RA, Macdonald, JM, Tam, VW, Jackson, TD, Ten Have, TR (2011). A difference-in-differences analysis of health, safety, and greening vacant urban space. American Journal of Epidemiology kwr273.Google Scholar
Chaix, B, Merlo, J, Subramanian, S, Lynch, J, Chauvin, P (2005). Comparison of a spatial perspective with the multilevel analytical approach in neighborhood studies: the case of mental and behavioral disorders due to psychoactive substance use in Malmö, Sweden, 2001. American Journal of Epidemiology 162, 171182.Google Scholar
Chaix, B, Leal, C, Evans, D (2010). Neighborhood-level confounding in epidemiologic studies: unavoidable challenges, uncertain solutions. Epidemiology 21, 124127.Google Scholar
Cheshire, P (2007). Segregated Neighbourhoods and Mixed Communities: A Critical Analysis. Joseph Rowntree Foundation: York.Google Scholar
Clark, C, Myron, R, Stansfeld, S, Candy, B (2007). A systematic review of the evidence on the effect of the built and physical environment on mental health. Journal of Public Mental Health 6, 1427.Google Scholar
Cohen, DA, Golinelli, D, Williamson, S, Sehgal, A, Marsh, T, Mckenzie, TL (2009). Effects of park improvements on park use and physical activity: policy and programming implications. American Journal of Preventive Medicine 37, 475480.Google Scholar
Cohen, DA, Marsh, T, Williamson, S, Golinelli, D, Mckenzie, TL (2012). Impact and cost-effectiveness of family Fitness Zones: a natural experiment in urban public parks. Health and Place 18, 3945.Google Scholar
Commission on Social Determinants of Health (2008). Closing the Gap in a Generation: Health Equity through Action on the Social Determinants of Health: Final Report of the Commission on Social Determinants of Health. World Health Organization: Geneva, Switzerland.Google Scholar
Corburn, J (2007). Reconnecting with our roots. American urban planning and public health in the twenty-first century. Urban Affairs Review 42, 688713.Google Scholar
Cox, M, Boyle, PJ, Davey, PG, Feng, Z, Morris, AD (2007). Locality deprivation and Type 2 diabetes incidence: a local test of relative inequalities. Social Science and Medicine 65, 19531964.Google Scholar
Craig, P, Cooper, C, Gunnell, D, Haw, S, Lawson, K, Macintyre, S, Ogilvie, D, Petticrew, M, Reeves, B, Sutton, M (2012). Using natural experiments to evaluate population health interventions: new Medical Research Council guidance. Journal of Epidemiology and Community Health 66, 11821186.Google Scholar
Cummins, S, Petticrew, M, Higgins, C, Findlay, A, Sparks, L (2005). Large scale food retailing as an intervention for diet and health: quasi-experimental evaluation of a natural experiment. Journal of Epidemiology and Community Health 59, 10351040.CrossRefGoogle ScholarPubMed
Cummins, S, Flint, E, Matthews, SA (2014). New neighborhood grocery store increased awareness of food access but did not alter dietary habits or obesity. Health Affairs 33, 283291.Google Scholar
De Vries, R, Blane, D, Netuveli, G (2014). Long-term exposure to income inequality: implications for physical functioning at older ages. European Journal of Ageing 11, 1929.CrossRefGoogle ScholarPubMed
Diez Roux, AV (2004). Estimating neighborhood health effects: the challenges of causal inference in a complex world. Social Science and Medicine 58, 19531960.Google Scholar
Dorling, D, Smith, G, Noble, M, Wright, G, Burrows, R, Bradshaw, J, Joshi, H, Pattie, C, Mitchell, R, Green, AE (2001). How much does place matter?. Environment and Planning A 33, 335–69.Google Scholar
Durlauf, SN (2004). Neighborhood effects. In Handbook of Regional and Urban Economics (ed. Henderson, SV and Thisse, J-F). Elsevier: Amsterdam, 21732242.Google Scholar
Edwards, B, Gray, M, Wise, S, Hayes, A, Katz, I, Muir, K, Patulny, R (2011). Early impacts of Communities for Children on children and families: findings from a quasi-experimental cohort study. Journal of Epidemiology and Community Health 65, 909914.CrossRefGoogle ScholarPubMed
Egan, M, Katikireddi, SV, Kearns, A, Tannahill, C, Kalacs, M, Bond, L (2013). Health effects of neighborhood demolition and housing improvement: a prospective controlled study of 2 natural experiments in Urban Renewal. American Journal of Public Health 103, e47e53.CrossRefGoogle ScholarPubMed
Faris, REL, Dunham, HW (1939). Mental Disorders in Urban Areas. University of Chicago Press: Chicago.Google Scholar
Fleischer, N, Diez-Roux, A (2008). Using directed acyclic graphs to guide analyses of neighbourhood health effects: an introduction. Journal of Epidemiology and Community Health 62, 842846.Google Scholar
Flowerdew, R, Manley, DJ, Sabel, CE (2008). Neighbourhood effects on health: does it matter where you draw the boundaries? Social Science and Medicine 66, 12411255.Google Scholar
Fone, D, Greene, G, Farewell, D, White, J, Kelly, M, Dunstan, F (2013). Common mental disorders, neighbourhood income inequality and income deprivation: small-area multilevel analysis. British Journal of Psychiatry 202, 286293.Google Scholar
Furukawa, TA, Kessler, RC, Slade, T, Andrews, G (2003). The performance of the K6 and K10 screening scales for psychological distress in the Australian National Survey of Mental Health and Well-Being. Psychological Medicine 33, 357362.Google Scholar
Galster, G (2001). On the nature of neighbourhood. Urban Studies 38, 21112124.Google Scholar
Galster, G, Hedman, L (2013). Measuring neighbourhood effects non-experimentally: how much do alternative methods matter? Housing Studies 28, 473498.CrossRefGoogle Scholar
Galster, GC (2008). Quantifying the effect of neighbourhood on individuals: challenges, alternative approaches, and promising directions. Schmollers Jahrbuch 128, 748.CrossRefGoogle Scholar
Gatrell, AC (1997). Structures of geographical and social space and their consequences for human health. Geografiska Annaler: Series B, Human Geography 79, 141154.Google Scholar
Granovetter, M (1973). The strength of weak ties. American Journal of Sociology 78, 13601380.Google Scholar
Greenland, S, Pearl, J, Robins, JM (1999). Causal diagrams for epidemiologic research. Epidemiology 3748.Google Scholar
Henderson, C, Diez Roux, A, Jacobs, D, Kiefe, C, West, D, Williams, D (2005). Neighbourhood characteristics, individual level socioeconomic factors, and depressive symptoms in young adults: the CARDIA study. Journal of Epidemiology and Community Health 59, 322.Google Scholar
Jackson, RJ, Dannenberg, AL, Frumkin, H (2013). Health and the built environment: 10 years after. American Journal of Public Health 103, 15421544.Google Scholar
Jencks, C, Mayer, S (1990). The social consequences of growing up in a poor neighborhood. In Inner-city poverty in the United States (ed. Lynn, LE and Mcgeary, MFH). National Academy Press: Washington, DC, 186.Google Scholar
Jones, K, Duncan, C (1996). People and places: the multilevel model as a general framework for the quantitative analysis of geographical data. Spatial Analysis: Modelling in a GIS Environment 79104.Google Scholar
Katz, L, Kling, J, Liebman, J (2001). Moving to opportunity in Boston: early results of a randomized mobility experiment. Quarterly Journal of Economics 116, 607654.Google Scholar
Kent, JL, Thompson, S (2014). The three domains of urban planning for health and well-being. Journal of Planning Literature, 0885412214520712.Google Scholar
Kim, D (2008). Blues from the neighborhood? Neighborhood characteristics and depression. Epidemiologic Reviews 30, 101117.Google Scholar
Kling, J, Liebman, J, Katz, L (2007). Experimental analysis of neighborhood effects. Econometrica 75, 83119.Google Scholar
Kling, J, Kessler, R, Ludwig, J, Sanbonmatsu, L, Liebman, J, Duncan, G, Katz, L (2008). What can we learn about neighborhood effects from the moving to opportunity experiment? American Journal of Sociology 114, 144188.Google Scholar
Kondo, N, Sembajwe, G, Kawachi, I, Van Dam, RM, Subramanian, S, Yamagata, Z (2009). Income inequality, mortality, and self rated health: meta-analysis of multilevel studies. BMJ 339.Google Scholar
Kwan, M-P (2012). How GIS can help address the uncertain geographic context problem in social science research. Annals of GIS 18, 245255.Google Scholar
Leventhal, T, Brooks-Gunn, J (2003). Moving to opportunity: an experimental study of neighborhood effects on mental health. American Journal of Public Health 93, 15761582.Google Scholar
Losert, C, SCHMAUß, M, Becker, T, Kilian, R (2012). Area characteristics and admission rates of people with schizophrenia and affective disorders in a German rural catchment area. Epidemiology and Psychiatric Sciences 21, 371379.Google Scholar
Ludwig, J, Sanbonmatsu, L, Gennetian, L, Adam, E, Duncan, GJ, Katz, LF, Kessler, RC, Kling, JR, Lindau, ST, Whitaker, RC (2011). Neighborhoods, obesity, and diabetes—a randomized social experiment. New England Journal of Medicine 365, 15091519.Google Scholar
Ludwig, J, Duncan, GJ, Gennetian, LA, Katz, LF, Kessler, RC, Kling, JR, Sanbonmatsu, L (2012). Neighborhood effects on the long-term well-being of low-income adults. Science 337, 15051510.Google Scholar
Lynch, J, Davey Smith, G (2002). Commentary: income inequality and health: the end of the story? International Journal of Epidemiology 31, 549551.Google Scholar
Macintyre, S (2007). Deprivation amplification revisited; or, is it always true that poorer places have poorer access to resources for healthy diets and physical activity? International Journal of Behavioral Nutrition and Physical Activity 4, 32.Google Scholar
Macintyre, S (2011). Good intentions and received wisdom are not good enough: the need for controlled trials in public health. Journal of Epidemiology and Community Health 65, 564567.Google Scholar
Macintyre, S, Ellaway, A, Cummins, S (2002). Place effects on health: how can we conceptualise, operationalise and measure them? Social Science and Medicine 55, 125139.CrossRefGoogle Scholar
Mair, C, Roux, A, Galea, S (2008). Are neighbourhood characteristics associated with depressive symptoms? A review of evidence. Journal of Epidemiology and Community Health 62, 940.Google Scholar
Marmot, M, Wilkinson, RG (2001). Psychosocial and material pathways in the relation between income and health: a response to Lynch et al. British Medical Journal 322, 1233.Google Scholar
Marmot, MG (2006). Status syndrome. Journal of the American Medical Association 295, 13041307.Google Scholar
Massey, DS, Gross, AB, Eggers, ML (1991). Segregation, the concentration of poverty, and the life chances of individuals. Social Science Research 20, 397420.CrossRefGoogle Scholar
Mclafferty, SL (2003). GIS and health care. Annual Review of Public Health 24, 2542.Google Scholar
Melhuish, E, Belsky, J, Leyland, AH, Barnes, J (2008). Effects of fully-established Sure Start Local Programmes on 3-year-old children and their families living in England: a quasi-experimental observational study. Lancet 372, 16411647.Google Scholar
Merlo, J, Chaix, B (2006). Neighbourhood effects and the real world beyond randomized community trials: a reply to Michael J Oakes. International Journal of Epidemiology 35, 13611363.Google Scholar
Merlo, J, Chaix, B, Ohlsson, H, Beckman, A, Johnell, K, Hjerpe, P, Råstam, L, Larsen, K (2006). A brief conceptual tutorial of multilevel analysis in social epidemiology: using measures of clustering in multilevel logistic regression to investigate contextual phenomena. Journal of Epidemiology and Community Health 60, 290297.CrossRefGoogle ScholarPubMed
Muntaner, C, Lynch, J (1999). Income inequality, social cohesion, and class relations: a critique of Wilkinson's neo-Durkheimian research program. International Journal of Health Services 29, 5982.CrossRefGoogle ScholarPubMed
Murayama, H, Fujiwara, Y, Kawachi, I (2012). Social capital and health: a review of prospective multilevel studies. Journal of Epidemiology 22, 179.Google Scholar
Nilsson, K, Sangster, M, Konijnendijk, CC (2011). Introduction. In Forests, Trees and Human Health (ed.Nilsson, K, Sangster, M, Gallis, C, Hartig, T, De Vries, S, Seeland, K and Schipperijn, J). Springer: Netherlands.Google Scholar
Oakes, JM (2004). The (mis) estimation of neighborhood effects: causal inference for a practicable social epidemiology. Social Science and Medicine 58, 19291952.Google Scholar
Oakes, JM (2013). Invited commentary: paths and pathologies of social epidemiology. American Journal of Epidemiology 178, 850851.Google Scholar
Openshaw, S, Taylor, PJ (1981). The modifiable areal unit problem. In Quantitative Geography: A British View (ed. Wrigley, N and Bennet, RJ). Routledge and Kegan Paul: London.Google Scholar
Ostendorf, W, Musterd, S, De Vos, S (2001). Social mix and the neighbourhood effect. Policy ambitions and empirical evidence. Housing Studies 16, 371380.Google Scholar
Pabayo, R, Kawachi, I, Gilman, SE (2013). Income inequality among American states and the incidence of major depression. Journal of Epidemiology and Community Health, jech-2013-203093.Google Scholar
Pearl, J (1995). Causal diagrams for empirical research. Biometrika 82, 669688.Google Scholar
Pink, B (2011). Technical Paper: Socio-Economic Indexes for Areas (SEIFA). Australian Bureau of Statistics: Canberra.Google Scholar
Putnam, RD (2007). E Pluribus Unum: diversity and community in the twenty-first century the 2006 Johan Skytte prize lecture. Scandinavian Political Studies 30, 137.Google Scholar
Rasbash, J, Browne, W, Goldstein, H, Yang, M, Plewis, I, Healy, M, Woodhouse, G, Draper, D, Langford, I, Lewis, T (2000). A user's Guide to MLwiN. Institute of Education: London, p. 286.Google Scholar
Runciman, WG (1966). Relative Deprivation and Social Justice. Routledge: London.Google Scholar
Rydin, Y, Bleahu, A, Davies, M, Dávila, JD, Friel, S, De Grandis, G, Groce, N, Hallal, PC, Hamilton, I, Howden-Chapman, P (2012). Shaping cities for health: complexity and the planning of urban environments in the 21st century. Lancet 379, 2079.Google Scholar
Sampson, R (2008). Moving to inequality: neighborhood effects and experiments Mmeet social structure. American Journal of Sociology 114, 189231.Google Scholar
Sharkey, P, Elwert, F (2011). The legacy of disadvantage: multigenerational neighborhood effects on cognitive ability. American Journal of Sociology 116, 1934.CrossRefGoogle ScholarPubMed
Slater, T (2013). Your life chances affect where you live: a critique of the ‘cottage industry’ of neighbourhood effects research. International Journal of Urban and Regional Research.CrossRefGoogle Scholar
Stafford, M, Chandola, T, Marmot, M (2007). Association between fear of crime and mental health and physical functioning. American Journal of Public Health 97.Google Scholar
Subramanian, S, Kawachi, I (2004). Income inequality and health: what have we learned so far? Epidemiologic Reviews 26, 7891.Google Scholar
Subramanian, S, O'malley, AJ (2010). Modeling neighborhood effects: the futility of comparing mixed and marginal approaches. Epidemiology (Cambridge, MA) 21, 475.Google Scholar
Subramanian, SV, Jones, K, Kaddour, A, Krieger, N (2009). Revisiting Robinson: the perils of individualistic and ecologic fallacy. International Journal of Epidemiology 38, 342360.CrossRefGoogle ScholarPubMed
Truong, KD, Ma, S (2006). A systematic review of relations between neighborhoods and mental health. Journal of Mental Health Policy and Economics 9, 137.Google Scholar
Turney, K, Kissane, R, Edin, K (2013). After moving to opportunity how moving to a low-poverty neighborhood improves mental health among African American women. Society and Mental Health 3, 121.Google Scholar
Vanderweele, TJ (2010). Direct and indirect effects for neighborhood-based clustered and longitudinal data. Sociological Methods and Research 38, 515544.Google Scholar
Veitch, J, Ball, K, Crawford, D, Abbott, GR, Salmon, J (2012). Park improvements and park activity: a natural experiment. American Journal of Preventive Medicine 42, 616619.Google Scholar
Wight, RG, Aneshensel, CS, Miller-Martinez, D, Botticello, AL, Cummings, JR, Karlamangla, AS, Seeman, TE (2006). Urban neighborhood context, educational attainment, and cognitive function among older adults. American Journal of Epidemiology 163, 10711078.Google Scholar
Wilkinson, R, Pickett, K (2009). The Spirit Level: Why More Equal Societies Almost Always Do Better. Penguin (Allen Lane): London.Google Scholar
Wilkinson, RG (1999). Income inequality, social cohesion, and health: clarifying the theory–a reply to Muntaner and Lynch. International Journal of Health Services 29, 525544.Google Scholar
Wilson, A (2014). Budget cuts risk halting Australia's progress in preventing chronic disease. Medical Journal of Australia 200, 558.Google Scholar
Wilson, WJ (1987). The Truly Disadvantaged: The Inner City, the Underclass, and Public Policy. University of Chicago Press: Chicago.Google Scholar
Wrigley, N, Warm, D, Margetts, B (2003). Deprivation, diet, and food-retail access: findings from the Leeds food deserts' study. Environment and Planning A 35, 151188.Google Scholar