Serious Mental Illness, Neighborhood Disadvantage, and Type 2 Diabetes Risk: A Systematic Review of the Literature

Aim of the Study: This review aims to systematically synthesize the body of literature examining the association between neighborhood socioeconomic disadvantage and serious mental illness (SMI)-type 2 diabetes (T2D) co-occurrence. Methods: We conducted an electronic search of four databases: PubMed, Scopus, Medline, and Web of Science. Studies were considered eligible if they were published in English, peer reviewed, quantitative, and focused on the association between neighborhood disadvantage and SMI-T2D comorbidity. Study conduct and reporting complied with PRISMA guidelines, and the protocol is made available at PROSPERO (CRD42017083483). Results: The one eligible study identified reported a higher burden of T2D in persons with SMI but provided only a tentative support for the association between neighborhood disadvantage and SMI-T2D co-occurrence. Conclusion: Research into neighborhood effects on SMI-T2D comorbidity is still in its infancy and the available evidence inconclusive. This points to an urgent need for attention to the knowledge gap in this important area of public health. Further research is needed to understand the health resource implications of the association between neighborhood deprivation and SMI-T2D comorbidity and the casual pathways linking them

Comorbidity of serious mental illness and type 2 diabetes: do neighbourhoods matter?

Background: Serious mental illness (SMI) refers to mental disorders that are severe in degree, persistent and produce considerable functional impairment, and include conditions such as schizophrenia, bipolar disorder or major depression. Type 2 diabetes (T2D) is 2 - 4 times more prevalent in people with SMI and contributes significantly to the increased morbidity and mortality experienced by this group. Even though antipsychotic medication is recognised as a major risk factor for T2D in individuals with SMI, there are likely additional biopsychosocial mechanisms involved that may independently contribute to SMI-T2D comorbidity. One possible correlate that has not been adequately investigated in this context is the neighbourhood environment. There is strong evidence that people with SMI are more likely to live in socioeconomically disadvantaged neighbourhoods with poorer resources and infrastructure. These neighbourhood influences have been associated with traditional risk factors of diabetes such as inactive lifestyle, unhealthy food choices and obesity. Despite the plausibility, little evidence is available on the associations of neighbourhood contextual factors with SMI-T2D comorbidity. Aims: The principal aims of this thesis were threefold. First, to describe the geography of SMI-T2D comorbidity in the Illawarra-Shoalhaven region of NSW, Australia. Second, to explore the cross-sectional association between neighbourhood-level socioeconomic disadvantage and SMI-T2D comorbidity. Third, to identify the specific features of disadvantaged neighbourhood environments that are associated with SMI-T2D comorbidity

The relationship between environment and mental health: how does geographic information systems (GIS) help?

Dear Sir, The role of physical and social environment on mental health cannot be ignored. While this relationship is adequately explored in mental health research, analysing and assimilating them in mental health planning still remains a road less travelled. Computer-based mapping technology called geographic information systems (GIS) has presented mental health researchers with many new possibilities in this direction. GIS-based spatial mapping and analysis can provide a better insight into illness patterns, causes, interactions and service needs. This can in turn help in evaluating interventions and guide evidence-based health care policies. The aim of this letter is to inform us of the opportunities and usefulness of GIS in mental health research, planning and delivery

Food deserts and its impact on mental health

Background: Areas with limited access to healthy, reasonably priced, nutritious food are often referred to as food deserts. These areas are often concentrated in lower socioeconomic neighbourhoods where mental health disorders are most prevalent as well. Unhealthy food choices are increasingly identified as a risk factor that promote mental illness and impede its management. Mentally ill can be adversely affected by this differential access to healthy food due to their lower income, inability to travel, physical and psychological limitations for food shopping. The objective of this study is to assess the potential impact of food deserts on mental illness. Methods: Published literature was reviewed in order to assess the burden of food deserts on mental illness using databases like Scopus and Medline. Results: Inequity in food access has been reported to contribute to disparity in eating habits and health outcomes. While food deserts have been studied extensively in the context of obesity and diabetes, its impact on mental illness still remains unexplored. One challenge in this direction would be to delineate the impact due to food access from other socioeconomic determinants affecting mental health. Conclusions: Further research is needed to understand the impact of food desert on mental illness

Usefulness of Geographic Information Systems (GIS) in mental health research

Role of environment on mental health cannot be ignored. Computer based mapping technology called Geographical Information Systems (GIS) has presented mental health researchers with many new possibilities to explore these relationships. The main aim of this literature review is to identify the emerging applications of GIS in mental health research. The use of GIS in mental health has faltered compared to other health care sectors and has started gaining momentum only in the recent years. There is great scope for GIS to be applied in mental health epidemiology, evaluating inequalities in health care access, determining spatial variation in service utilisation and planning health care delivery and community integration. The technology is bound to find many more innovative applications in the mental health care sector in the coming years

Exploring the geography of serious mental illness and type 2 diabetes comorbidity in Illawarra-Shoalhaven, Australia (2010 -2017)

Objectives The primary aim of this study was to describe the geography of serious mental illness (SMI)-type 2 diabetes comorbidity (T2D) in the Illawarra-Shoalhaven region of NSW, Australia. The Secondary objective was to determine the geographic concordance if any, between the comorbidity and the single diagnosis of SMI and diabetes. Methods Spatial analytical techniques were applied to clinical data to explore the above objectives. The geographic variation in comorbidity was determined by Moran\u27s I at the global level and the local clusters of significance were determined by Local Moran\u27s I and spatial scan statistic. Choropleth hotspot maps and spatial scan statistics were generated to assess the geographic convergence of SMI, diabetes and their comorbidity. Additionally, we used bivariate LISA (Local Indicators of Spatial Association) and multivariate spatial scan to identify coincident areas with higher rates of both SMI and T2D. Results The study identified significant geographic variation in the distribution of SMI-T2D comorbidity in Illawarra Shoalhaven. Consistently higher burden of comorbidity was observed in some urban suburbs surrounding the major metropolitan city. Comparison of comorbidity hotspots with the hotspots of single diagnosis SMI and T2D further revealed a geographic concordance of high-risk areas again in the urban areas outside the major metropolitan city. Conclusion The identified comorbidity hotspots in our study may serve as a basis for future prioritisation and targeted interventions. Further investigation is required to determine whether contextual environmental factors, such as neighbourhood socioeconomic disadvantage, may be explanatory. Implications for public health Ours is the first study to explore the geographic variations in the distribution of SMI and T2D comorbidity. Findings highlight the importance of considering the role of neighbourhood environments in influencing the T2D risk in people with SMI

What types of green space disrupt a lonelygenic environment? A cohort study

Introduction: Associations between green space type and social loneliness (a scarcity of people one feels they can depend on) were investigated in city-living participants in the Sax Institute’s 45 and Up Study. Methods: Availability of green space, tree canopy and open grass were measured as a percentage of land-use within 1.6 km road−network distance buffers using high-resolution data. Multilevel logistic regressions adjusted for confounding tested associations between each green space indicator with the odds of social loneliness at baseline (prevalence) and follow-up (incidence), adjusted for demographic and socioeconomic confounders. Results: The prevalence of social loneliness at baseline was 5.3% (n = 5627 /105,498). Incidence of social loneliness at follow-up was 3.4% (n = 1772/51,365). Adjusted regressions indicated reduced odds of prevalent (OR = 0.95, 95%CI = 0.92–0.98) and incident social loneliness with 10% more green space (OR = 0.92, 95%CI = 0.90– 0.96). Similar associations were found with a 10% increase in tree canopy for both prevalent (OR = 0.92, 95%CI = 0.88–0.95) and incident social loneliness (OR = 0.92, 95%CI = 0.88–0.97). Two-way interaction terms indicated effect modification by sex but not couple status. Among women, a 10% increase in total green space was associated with lower odds of prevalent (OR = 0.95, 0.91–0.95) and incident (OR = 0.89, 0.85–0.95) social loneliness. A 10% increase in tree canopy among women was associated with lower odds of prevalent (OR = 0.89, 085–0.92) and incident (OR = 0.85, 0.80–0.92) social loneliness. Meanwhile, a 10% increase in open grass among women was associated with higher odds of prevalent (OR = 1.08, 1.01–1.15) and incident (OR = 1.19, 1.03–1.35) social loneliness. Associations for men were statistically significant for a 10% increase in total green space (OR = 0.96, 0.92–0.99) and tree canopy (OR = 0.93, 0.90–0.97) for prevalent social loneliness only. Conclusion: Urban greening and tree canopy restoration may reduce risks of social loneliness, perhaps especially in women

Neighborhood Environment and Type 2 Diabetes Comorbidity in Serious Mental Illness

Aim: The aim of this study was to examine the association between neighborhood characteristics and type 2 diabetes (T2D) comorbidity in serious mental illness (SMI). We investigated associations of neighborhood-level crime, accessibility to health care services, availability of green spaces, neighborhood obesity, and fast food availability with SMI-T2D comorbidity. Method: A series of multilevel logistic regression models accounting for neighborhood-level clustering were used to examine the associations between 5 neighborhood variables and SMI-T2D comorbidity, sequentially adjusting for individual-level variables and neighborhood-level socioeconomic disadvantage. Results: Individuals with SMI residing in areas with higher crime rates per 1000 population had 2.5 times increased odds of reporting T2D comorbidity compared to the individuals with SMI residing in lower crime rate areas after controlling for individual and areal level factors (95% CI 0.91-6.74). There was no evidence of association between SMI-T2D comorbidity and other neighborhood variables investigated. Conclusion: Public health strategies to reduce SMI-T2D comorbidity might benefit by targeting on individuals with SMI living in high-crime neighborhoods. Future research incorporating longitudinal designs and/or mediation analysis are warranted to fully elucidate the mechanisms of association between neighborhoods and SMI-T2D comorbidity

Examining the association between neighbourhood socioeconomic disadvantage and type 2 diabetes comorbidity in serious mental illness

This study examined the association between neighbourhood socioeconomic disadvantage and serious mental illness (SMI)-type 2 diabetes (T2D) comorbidity in an Australian population using routinely collected clinical data. We hypothesised that neighbourhood socioeconomic disadvantage is positively associated with T2D comorbidity in SMI. The analysis considered 3816 individuals with an SMI living in the Illawarra and Shoalhaven regions of NSW, Australia, between 2010 and 2017. Multilevel logistic regression models accounting for suburb (neighbourhood) level clustering were used to assess the association between neighbourhood disadvantage and SMI -T2D comorbidity. Models were adjusted for age, sex, and country of birth. Compared with the most advantaged neighbourhoods, residents in the most disadvantaged neighbourhoods had 3.2 times greater odds of having SMI-T2D comorbidity even after controlling for confounding factors (OR 3.20, 95% CI 1.42-7.20). The analysis also revealed significant geographic variation in the distribution of SMI -T2D comorbidity in our sample (Median Odds Ratio = 1.35) Neighbourhood socioeconomic disadvantage accounted for approximately 17.3% of this geographic variation. These findings indicate a potentially important role for geographically targeted initiatives designed to enhance prevention and management of SMI-T2D comorbidity in disadvantaged communities