Examining the Association between Neighbourhood Socioeconomic Disadvantage and Type 2 Diabetes Comorbidity in Serious Mental Illness
Abstract
1. Introduction
2. Materials and Methods
2.1. Study Design and Sample
2.2. Measures
2.3. Statistical Analysis
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- WHO. Obesity and Overweight; Fact sheet N 311; WHO: Geneva, Switzerland, 2012. [Google Scholar]
- Holt, R.I.; Mitchell, A.J. Diabetes mellitus and severe mental illness: Mechanisms and clinical implications. Nat. Rev. Endocrinol. 2015, 11, 79–89. [Google Scholar] [CrossRef] [PubMed]
- Ward, M.; Druss, B. The epidemiology of diabetes in psychotic disorders. Lancet Psychiatry 2015, 2, 431–451. [Google Scholar] [CrossRef]
- De Hert, M.; Correll, C.U.; Bobes, J.; Cetkovich-Bakmas, M.A.R.C.E.L.O.; Cohen, D.A.N.; Asai, I.; Detraux, J.; Gautam, S.; Möller, H.J.; Ndetei, D.M.; et al. Physical illness in patients with severe mental disorders. I. Prevalence, impact of medications and disparities in health care. World Psychiatry 2011, 10, 52–77. [Google Scholar] [CrossRef] [PubMed]
- Wändell, P.; Ljunggren, G.; Wahlström, L.; Carlsson, A.C. Diabetes and psychiatric illness in the total population of Stockholm. J. Psychosom. Res. 2014, 77, 169–173. [Google Scholar] [CrossRef]
- Ribe, A.R.; Laursen, T.M.; Sandbaek, A.; Charles, M.; Nordentoft, M.; Vestergaard, M. Long-term mortality of persons with severe mental illness and diabetes: A population-based cohort study in Denmark. Psychol. Med. 2014, 44, 3097–3107. [Google Scholar] [CrossRef]
- Tirupati, S.; Chua, L.E. Obesity and metabolic syndrome in a psychiatric rehabilitation service. Aust. N. Z. J. Psychiatry 2007, 41, 606–610. [Google Scholar] [CrossRef]
- Šprah, L.; Dernovšek, M.Z.; Wahlbeck, K.; Haaramo, P. Psychiatric readmissions and their association with physical comorbidity: A systematic literature review. BMC Psychiatry 2017, 17, 2. [Google Scholar] [CrossRef]
- Kurdyak, P.; Vigod, S.; Duchen, R.; Jacob, B.; Stukel, T.; Kiran, T. Diabetes quality of care and outcomes: Comparison of individuals with and without schizophrenia. Gen. Hosp. Psychiatry 2017, 46, 7–13. [Google Scholar] [CrossRef]
- Zhang, B.H.; Han, M.; Zhang, X.Y.; Hui, L.; Jiang, S.R.; De Yang, F.; Tan, Y.L.; Wang, Z.R.; Li, J.; Huang, X.F. Gender differences in cognitive deficits in schizophrenia with and without diabetes. Compr. Psychiatry 2015, 63, 1–9. [Google Scholar] [CrossRef]
- Han, M.; Huang, X.-F.; Chen, D.C.; Xiu, M.; Kosten, T.R.; Zhang, X.Y. Diabetes and cognitive deficits in chronic schizophrenia: A case-control study. PLoS ONE 2013, 8, e66299. [Google Scholar] [CrossRef]
- Almog, M.; Curtis, S.; Copeland, A.; Congdon, P. Geographical variation in acute psychiatric admissions within New York City 1990–2000: Growing inequalities in service use? Soc. Sci. Med. 2004, 59, 361–376. [Google Scholar] [CrossRef] [PubMed]
- Kirkbride, J.B.; Jones, P.B.; Ullrich, S.; Coid, J.W. Social Deprivation, Inequality, and the Neighborhood-Level Incidence of Psychotic Syndromes in East London. Schizophr. Bull. 2014, 40, 169–180. [Google Scholar] [CrossRef] [PubMed]
- Astell-Burt, T.; Feng, X.; Kolt, G. Identification of the impact of crime on physical activity depends upon neighbourhood scale: Multilevel evidence from 203,883 Australians. Health Place 2015, 31, 120–123. [Google Scholar] [CrossRef] [PubMed]
- Jacka, F.N.; Cherbuin, N.; Anstey, K.J.; Butterworth, P. Dietary patterns and depressive symptoms over time: Examining the relationships with socioeconomic position, health behaviours and cardiovascular risk. PLoS ONE 2014, 9, e87657. [Google Scholar] [CrossRef]
- Kirkbride, J.B.; Boydell, J.; Ploubidis, G.B.; Morgan, C.; Dazzan, P.; McKenzie, K.; Murray, R.M.; Jones, P.B. Testing the association between the incidence of schizophrenia and social capital in an urban area. Psychol. Med. 2008, 38, 1083–1094. [Google Scholar] [CrossRef]
- Galea, S.; Ahern, J.; Nandi, A.; Tracy, M.; Beard, J.; Vlahov, D. Urban Neighborhood Poverty and the Incidence of Depression in a Population-Based Cohort Study. Ann. Epidemiol. 2007, 17, 171–179. [Google Scholar] [CrossRef]
- Cox, M.; Boyle, P.J.; Davey, P.G.; Feng, Z.; Morris, A.D. Locality deprivation and Type 2 diabetes incidence: A local test of relative inequalities. Soc. Sci. Med. 2007, 65, 1953–1964. [Google Scholar] [CrossRef]
- Cubbin, C.; Sundquist, K.; Ahlén, H.; Johansson, S.-E.; Winkleby, M.A.; Sundquist, J. Neighborhood deprivation and cardiovascular disease risk factors: Protective and harmful effects. Scand. J. Public Health 2006, 34, 228–237. [Google Scholar] [CrossRef]
- Walsan, R.; Bonney, A.; Mayne, D.J.; Pai, N.; Feng, X.; Toms, R. Serious Mental Illness, Neighborhood Disadvantage, and Type 2 Diabetes Risk: A Systematic Review of the Literature. J. Prim. Care Community Health 2018, 9, 2150132718802025. [Google Scholar] [CrossRef]
- Mezuk, B.; Chaikiat, Å.; Li, X.; Sundquist, J.; Kendler, K.S.; Sundquist, K. Depression, neighborhood deprivation and risk of type 2 diabetes. Health Place 2013, 23, 63–69. [Google Scholar] [CrossRef]
- Walsan, R.; Bonney, A.; Mayne, D.J.; Pai, N.; Feng, X. Geographic inequalities in the distribution of serious mental illness-type 2 diabetes comorbidity. In Proceedings of the International Medical Geography Symposium, Queenstown, New Zealand, 30 June–5 July 2019. [Google Scholar]
- Rose, G. Sick individuals and sick populations. Int. J. Epidemiol. 2001, 30, 427–432. [Google Scholar] [CrossRef] [PubMed]
- Australian Bureau of Statistics. Population by Age, Sex, Regions of Australia; Australian Bureau of Statistics: Canberra, Australia, 2011.
- Ghosh, A.; Charlton, K.E.; Girdo, L.; Batterham, M. Using data from patient interactions in primary care for population level chronic disease surveillance: The Sentinel Practices Data Sourcing (SPDS) project. BMC Public Health 2014, 14, 557. [Google Scholar] [CrossRef] [PubMed]
- Australian Bureau of Statistics. A Introduction to Socioeconomic Indexex of the Areas (SEIFA); ABS, Ed.; Australian Bureau of Statistics: Canberra, Australia, 2011.
- ABS; Australian Statistical Geography Standard (ASGS). Non ABS Structures 2016, Australian Bureau of Statistics; Australian Bureau of Statistics: Canberra, Australia, 2016.
- Waller, L.A.; Gotway, C.A. Applied Spatial Statistics for Public Health Data; Wiley Series in Probability and Statistics; John Wiley & Sons: Hoboken, NJ, USA, 2004. [Google Scholar]
- ABS; Standard Australian Classification of Countries (SACC). Australian Bureau of Statistics; Australian Bureau of Statistics: Canberra, Australia, 2016.
- Snijders, T.A.B.; Bosker, R.J. Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling; SAGE: Newcastle upon Tyne, UK, 1999. [Google Scholar]
- Merlo, J.; Chaix, B.; Ohlsson, H.; Beckman, A.; Johnell, K.; Hjerpe, P.; Råstam, L.; Larsen, K. A brief conceptual tutorial of multilevel analysis in social epidemiology: Using measures of clustering in multilevel logistic regression to investigate contextual phenomena. J. Epidemiol. Community Health 2006, 60, 290–297. [Google Scholar] [CrossRef] [PubMed]
- Austin, P.C.; Merlo, J. Intermediate and advanced topics in multilevel logistic regression analysis. Stat. Med. 2017, 36, 3257–3277. [Google Scholar] [CrossRef] [PubMed]
- Larsen, K.; Merlo, J. Appropriate Assessment of Neighborhood Effects on Individual Health: Integrating Random and Fixed Effects in Multilevel Logistic Regression. Am. J. Epidemiol. 2005, 161, 81–88. [Google Scholar] [CrossRef]
- Team, R.C. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2013. [Google Scholar]
- Diez Roux, A.V. Estimating neighborhood health effects: The challenges of causal inference in a complex world. Soc. Sci. Med. 2004, 58, 1953–1960. [Google Scholar] [CrossRef]
- Diez Roux, A.V. Neighborhoods and Health: What Do We Know? What Should We Do? Am. J. Public Health 2016, 106, 430. [Google Scholar] [CrossRef]
- Dauncey, K.; Giggs, J.; Baker, K.; Harrison, G. Schizophrenia in Nottingham: Lifelong Residential Mobility of a Cohort. Br. J. Psychiatry 1993, 163, 613–619. [Google Scholar] [CrossRef]
- Bonney, A.D.; Mayne, D.J.; Caputi, P.; Weston, K.M.; Magee, C.A.; Ghosh, A. Area level socioeconomic disadvantage and diabetes control in the SIMLR Study cohort: Implications for health service planning. PLoS ONE 2015, 10, e0137261. [Google Scholar]
- Astell-Burt, T.; Feng, X.; Kolt, G.S.; McLean, M.; Maberly, G. Understanding geographical inequities in diabetes: Multilevel evidence from 114,755 adults in Sydney, Australia. Diabetes Res. Clin. Pract. 2014, 106, e68–e73. [Google Scholar] [CrossRef]
- Mair, C.; Roux, A.V.D.; Galea, S. Are neighbourhood characteristics associated with depressive symptoms? A review of evidence. J. Epidemiol. Community Health 2008, 62, 940–946. [Google Scholar] [PubMed]
- Dendup, T.; Feng, X.; Clingan, S.; Astell-Burt, T. Environmental Risk Factors for Developing Type 2 Diabetes Mellitus: A Systematic Review. Int. J. Environ. Res. Public Health 2018, 15, 78. [Google Scholar] [CrossRef] [PubMed]
- Suvisaari, J.; Perälä, J.; Saarni, S.I.; Härkänen, T.; Pirkola, S.; Joukamaa, M.; Koskinen, S.; Lönnqvist, J.; Reunanen, A. Type 2 diabetes among persons with schizophrenia and other psychotic disorders in a general population survey. Eur. Arch. Psychiatry Clin. Neurosci. 2008, 258, 129–136. [Google Scholar] [CrossRef]
- Sun, L.; Getz, M.; Daboul, S.; Jay, M.; Sherman, S.; Rogers, E.; Aujero, N.; Rosedale, M.; Goetz, R.R.; Weissman, J.; et al. Independence of diabetes and obesity in adults with serious mental illness: Findings from a large urban public hospital. J. Psychiatr. Res. 2018, 99, 159–166. [Google Scholar] [CrossRef] [PubMed]
- Cubbin, C. Where We Live Matters for Our Health:Neighborhoods and Health in ISSUE BRIEF 3: Neighborhoods and Health; Commission on Health.Org, Robert Wood Johnson Foundation: Princeton, NJ, USA, 2008. [Google Scholar]
- Morgan, V.A.; Waterreus, A.; Jablensky, A.; MacKinnon, A.; McGrath, J.J.; Carr, V.; Bush, R.; Castle, D.; Cohen, M.; Harvey, C.; et al. People living with psychotic illness in 2010: The second Australian national survey of psychosis. Aust. N. Z. J. Psychiatry 2012, 46, 735–752. [Google Scholar] [CrossRef]
Variables | Individuals with SMI n = 3816 | Individuals with SMI–T2D Comorbidity n = 463 | % of Individuals with SMI who Also Have Comorbidity (95% Cl) |
---|---|---|---|
Individual variables | |||
Gender | |||
Female | 1848 (48%) | 245 (53%) | 13.3 (11.8–14.9) |
Male | 1968 (52%) | 218 (47%) | 11.1 (9.7–12.5) |
Age, years (Mean (SD)) | |||
Age, years | 43.6 (18.5) | 58.8 (15.7) | |
18–44 | 1961 (51%) | 92 (20%) | 4.7 (03.8–05.7) |
45–65 | 1213 (32%) | 193 (42%) | 15.9 (13.9–18.0) |
65+ | 642 (17%) | 178 (38%) | 27.7 (24.3–31.2) |
Country of birth | |||
Australia | 3104 (81%) | 339 (73%) | 10.9 (9.9–12.1) |
Oceania excluding Australia | 74 (2%) | 12 (3%) | 16.2 (9.5–26.2) |
UK & Ireland | 212 (6%) | 35 (8%) | 16.5 (12.1–22.1) |
Western Europe | 137 (4%) | 29 (6%) | 21.2 (15.2–28.8) |
Eastern and Central Europe | 125 (3%) | 29 (6%) | 23.2 (16.7–31.3) |
North East Asia | 17 (0%) | 0 (0%) | 0.0 (0–18.4) |
South East Asia | 51 (1%) | 6 (1%) | 11.8 (5.5–23.4) |
Central and South Asia | 16 (0%) | 3 (1%) | 18.8 (6.6–43.0) |
Middle East and North Africa | 39 (1%) | 9 (2%) | 23.1 (12.7–38.3) |
Sub-Saharan Africa | 20 (1%) | 0 (0%) | 0.0 (0–16.1) |
Americas | 21 (1%) | 1 (0%) | 4.8 (0.9–22.7) |
Neighbourhood level variables | |||
IRSD as quintiles | |||
Q1 (Highest) | 1752 (46 %) | 229 (49%) | 13.1 (11.6–14.7) |
Q2 | 943 (25 %) | 120 (26%) | 12.7 (10.7–14.9) |
Q3 | 620 (16 %) | 75 (16%) | 12.1 (9.8–14.9) |
Q4 | 362 (10 %) | 34 (7%) | 9.4 (6.8–12.8) |
Q5 (Lowest) | 139 (4 %) | 7 (2%) | 5.1 (2.5–10.0) |
Variable | Model 1 | Model 2 | Model 3 |
---|---|---|---|
OR (95% Cl) | OR (95% Cl) | OR (95% Cl) | |
Individual variables | |||
Gender | p = 0.658 | p = 0.687 | |
Female | 1.00 | 1.00 | |
Male | 0.95 (0.78–1.17) | 0.96 (0.78–1.17) | |
Age | p < 0.05 | p < 0.05 | |
18–44 | 1.00 | ||
45–65 | 3.79 (2.91–4.93) | 3.78 (2.90–4.92) | |
65+ | 7.68 (5.77–10.23) | 7.82 (5.87–10.42) | |
Country of birth | p = 0.137 | p = 0.149 | |
Australia | 1.00 | 1.00 | |
Oceania excluding Australia | 1.57 (0.81–3.03) | 1.53 (0.79–2.97) | |
UK & Ireland | 0.84 (0.57–1.26) | 0.88 (0.59–1.31) | |
Western Europe | 0.99 (0.63–1.54) | 0.97 (0.62–1.52) | |
Eastern and Central Europe | 1.30 (0.82–2.05) | 1.30 (0.82–2.06) | |
South East Asia | 1.30 (0.53–3.19) | 1.30 (0.52–3.19) | |
Central and South Asia | 2.03 (0.53–7.82) | 2.13 (0.56–8.10) | |
Middle East and North Africa | 1.84 (0.83–4.09) | 1.87 (0.84–4.16) | |
Americas | 0.42 (0.06–3.25) | 0.41 (0.05–3.15) | |
Neighbourhood Variable | |||
IRSD quintiles | p <0.05 | ||
Q5 (Least disadvantaged) | 1.00 | ||
Q4 | 1.87 (0.77–4.53) | ||
Q3 | 2.67 (1.14–6.15) | ||
Q2 | 2.92 (1.28–6.67) | ||
Q1 (Most disadvantaged) | 3.20 (1.42–7.20) | ||
Variance of random effects | |||
T2 | 0.098 | 0.073 | 0.056 |
PCV | Ref | 25.5% | 42.9% |
ICC | 0.029 | 0.0217 | 0.017 |
MOR | 1.347 | 1.293 | 1.252 |
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Walsan, R.; Mayne, D.J.; Feng, X.; Pai, N.; Bonney, A. Examining the Association between Neighbourhood Socioeconomic Disadvantage and Type 2 Diabetes Comorbidity in Serious Mental Illness. Int. J. Environ. Res. Public Health 2019, 16, 3905. https://doi.org/10.3390/ijerph16203905
Walsan R, Mayne DJ, Feng X, Pai N, Bonney A. Examining the Association between Neighbourhood Socioeconomic Disadvantage and Type 2 Diabetes Comorbidity in Serious Mental Illness. International Journal of Environmental Research and Public Health. 2019; 16(20):3905. https://doi.org/10.3390/ijerph16203905
Chicago/Turabian StyleWalsan, Ramya, Darren J Mayne, Xiaoqi Feng, Nagesh Pai, and Andrew Bonney. 2019. "Examining the Association between Neighbourhood Socioeconomic Disadvantage and Type 2 Diabetes Comorbidity in Serious Mental Illness" International Journal of Environmental Research and Public Health 16, no. 20: 3905. https://doi.org/10.3390/ijerph16203905
APA StyleWalsan, R., Mayne, D. J., Feng, X., Pai, N., & Bonney, A. (2019). Examining the Association between Neighbourhood Socioeconomic Disadvantage and Type 2 Diabetes Comorbidity in Serious Mental Illness. International Journal of Environmental Research and Public Health, 16(20), 3905. https://doi.org/10.3390/ijerph16203905