Abstract
Keywords
Mental disorders that are severe in degree, persistent in duration and produce significant functional impairment are referred to as serious mental illness (SMI). 1 Individuals with SMI have higher risk of premature mortality and a reduced life expectancy of approximately 10 to 30 years compared with the general population.2-4 A large proportion of this excess mortality experienced by people with SMI is the consequence of cardiovascular diseases for which type 2 diabetes (T2D) is a major risk factor.4-6
The prevalence of T2D in people with SMI is two to four times higher than the general population with estimates ranging from 1% to 68%.7-11 In those with SMI, a comorbid diabetes diagnosis not only confers a higher cardiovascular risk and increased mortality but is also associated with increased hospitalizations, greater number of emergency department visits, nonadherence to treatments, higher health care utilization costs and decreased quality of life.7,9,10,12-14 Studies have reported that people with both schizophrenia and type 2 diabetes have worse cognitive deficit than schizophrenia without diabetes or diabetes alone, which can significantly impede their social rehabilitation and lead to poor clinical and functional outcomes.15,16
Numerous studies have established that people who live in disadvantaged environments have worse mental and physical health outcomes than people living in more advantaged areas.17-25 This phenomenon is commonly referred to as the social gradient of health 26 and is expected to be heightened for people with SMI because of their complex needs. 27 People with mental illness often live in disadvantaged neighborhoods. 28 Lack of adequate health care facilities, decreased access to healthy foods and an unsafe environment in these neighborhoods are often associated with adverse health outcomes such as sedentary life, unhealthy food, choices and obesity,29-33 which are the major risk factors for T2D.34-36 It is also proposed that the economic uncertainties associated with deprivation can induce chronic stress, which can result in altered immune system response and activate the hypothalamic-pituitary-adrenal axis leading to diabetes.10,37 An association between neighborhoods and comorbid diagnosis of SMI and T2D is highly plausible, given what is known about the underlying complex mechanisms that drive these two disorders.
Neighborhood disadvantage has been associated with SMI and T2D.22-25,38,39 However, only a few studies have examined the associations between neighborhood disadvantage and chronic disease comorbidities.40,41 There is increasing interest in recent years to address diseases that occur concurrently rather than as separate conditions; that is, are comorbid. Moreover, “syndemics,” which is gaining broad recognition in public health literature, also calls for a holistic approach that considers the biological and social interactions of two or more synergistic diseases rather than treating them as separate entities independent of the social context in which they are found. 42
Given the importance and the degree of public health burden imposed by SMI-T2D comorbidity and the plausibility of an association with neighborhood deprivation, it is imperative to understand the evidence available on the association between neighborhood socioeconomic disadvantage and SMI-T2D comorbidity. Understanding these relationships would be useful in developing evidence based holistic interventions, health care policies and would even help us in designing healthier life spaces. Accordingly, this review aims to synthesize the body of literature examining the association between neighborhood socioeconomic disadvantage and SMI-T2D comorbidity.
Methods
Design
This systematic review followed the Preferred Reporting Items for Systematic review and meta-analysis (PRISMA) format. Research question, inclusion and exclusion criteria and search strategy were developed before the review process based on the PICO (Population, Indicator, Comparison and Outcome) approach. The protocol for this systematic review was registered on PROSPERO (CRD42017083483) and can be accessed at https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=83483.
Search Strategy
Relevant literature was identified through a systematic search of four databases: PubMed, Scopus, Medline, and Web of Science. These databases were selected due to their relative strengths and coverage in medical and social sciences. An initial text search was carried out on PubMed to identify all the possible synonyms of the main concepts and keywords included in the study.
The search strategy consisted of three themes: neighborhoods (neighborhoods, neighbourhoods, residence characteristics, community, small area, context or geography); type 2 diabetes (type 2 diabetes, type 2 diabetes mellitus, non-insulin dependent diabetes mellitus); and serious mental illness (serious mental illness, psychosis, schizophrenia, bipolar disorder, major depression, affective disorders, psychotic disorders) (see Table 1). The reference lists of retrieved articles were hand searched to identify relevant articles that may have been missed in the electronic search. No geographic, date, or study design restrictions were imposed.
Search Terms and Subject Headings in PubMed Format (Modified in Other Search Engines).
Study Selection
Journal articles that met the following criteria were included in the study: published in English, peer reviewed, quantitative and focusing on the neighborhood disadvantage and SMI-T2D comorbidity. Studies reporting SMI and T2D independently and not as comorbid conditions were excluded from the review. Similarly, studies pertaining to neighborhood features other than disadvantage were also not included.
A 3-step study selection process was employed. In the first step, articles were screened and duplicates were removed. In the second step, the titles and abstracts of remaining articles were reviewed for their eligibility for inclusion. In the third step, eligible articles identified were examined in full for their inclusion in the review. Two reviewers (RW and RT) independently performed all three stages. Study selection procedures are summarized in Figure 1.
Flowchart of literature search process and the results.
Data Extraction
Information extracted from the eligible studies included the following: author, publication date, country of data origin, study population, study design, measures of neighborhood disadvantage, measures of T2D, method of analysis and major findings.
Data Analysis
As the focus of this review was to describe the association between neighborhood disadvantage and SMI-T2D comorbidity, the data analysis concentrated on this association. Meta-analysis was thought to be inappropriate because of the heterogeneity expected between the study populations, design and neighborhood measures. Hence, a descriptive review was conducted.
Results
The literature search retrieved a total of 99 potentially relevant records. After excluding 40 duplicates, the remaining 59 articles were screened for their broad eligibility, and a further 58 ineligible articles were excluded. The one remaining article and the additional one retrieved from reference lists were reviewed in full. One article was excluded after full text review leaving one eligible study for inclusion in the review. Study selection outcomes at each stage of the review are summarized in Figure 1.
The one study meeting the selection criteria examined the association between neighborhood disadvantage, major depression and T2D risk among 336 340 adults from Sweden (Table 2). The study relied on identified incident diabetes in those individuals with clinically diagnosed major depression and had a follow-up period of seven years. The measure of neighborhood disadvantage used in the study was a computed index based on four variables: income, education, unemployment and social service assistance. Multilevel logistic regression models were used to assess the relationship between disadvantage and comorbidity.
Summary of Studies on Neighborhood Disadvantage and Serious Mental Illness–Type 2 Diabetes (SMI-T2D) Comorbidity.
After accounting for demographic and individual characteristics, such as age, gender, family income, educational attainment and immigration status, the interaction between neighborhood disadvantage and comorbidity risk was found to be nonsignificant (β = 0.01, 95% confidence interval [CI] −0.06 to 0.06, P = .573) indicating that the association between major depression and T2D is similar across different levels of neighborhood disadvantage. Although there was no evidence of synergistic interaction, the attributable risk of T2D due to depression (Diabetes incidencedepression – Diabetes incidencewithout depression) was increased in high deprivation areas (16.4) compared with lower deprivation areas (8.2). The study also highlighted that the individual socioeconomic indicators were not strongly related to T2D risk after controlling for neighborhood factors, indicating the role that contextual factors may play in the development of comorbid association.
Discussion
Our review indicates a paucity of evidence in the research literature investigating the associations between socioeconomic disadvantage and comorbidity of SMI and T2D despite the plausibility of such an association and its implications for health. The only research available reports a nonsignificant association between socioeconomic disadvantage and SMI-T2D cooccurrence. 43 However, the above study focused entirely on major depression, which is often claimed to be under-detected especially in the primary care settings, 44 and did not take into account other forms of SMI such as schizophrenia or bipolar disorder. The study, however, provides indicative evidence of higher attributable risk of T2D in disadvantaged neighborhoods, signaling the focus needed on high deprivation areas in order to reduce the risk of T2D in SMI patients. Furthermore, the study provides an impetus to explore potential neighborhood contextual pathways linking neighborhood deprivation with SMI-T2D comorbidity.
Previous research examining the association between neighborhood disadvantage and T2D risk as an independent condition has established a consistent positive association, whereby increased neighborhood deprivation is associated with increased T2D risk.45-47 Research has also shown that multimorbidity is common among populations living in deprived neighborhoods. 40 Although this large cohort study provides only a tentative support for the association between neighborhood socioeconomic disadvantage and SMI-T2D comorbidity, it is consistent with observations showing a high burden of T2D in persons with SMI. More research is needed under different settings and including different forms of SMI to confirm the above results.
Another limitation in the evidence base is that the available study focused mainly on the social aspect of neighborhood disadvantage and used a computed index of disadvantage based on income, education, unemployment and social service assistance and did not focus on the contextual factors of the neighborhoods which might play a significant role. For example, deprived neighborhoods often lack access to fresh produce, and may be dominated by fast food and convenience stores, making the latter the easily available food option. 18 Similarly, deprived neighborhoods might lack an environment conducive to physical activity. 13 The presence of such unobserved moderating or mediating factors might have also contributed to the nonsignificant association between the 2 in the above study.
The lack of a conclusive evidence base makes it difficult to make firm policy recommendations based on our review. Further research is needed to capture the completeness of association between neighborhood deprivation and SMI-T2D comorbidity and the causal pathways linking them. Future research should also focus more on the modifiable contextual or physical aspects of the area that could potentially mediate or moderate the association between deprivation and T2D-SMI comorbidity. Sound knowledge of the factors that are modifiable by interventions will turn out to be more useful and informative for developing policy solutions and interventions.
Conclusions
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 population 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. Multilevel study designs can generate more evidence in this direction as it can be useful in analyzing the moderating and mediating processes between neighborhood and individual level variables. Identifying the relationship and connecting processes will help policy makers to develop efficient intervention strategies to curb the syndemics of SMI and T2D.
Footnotes
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was conducted with the support of Australian Government Research Training program scholarship and Illawarra Shoalhaven Local Health District–University of Wollongong combined scholarship.