Social determinants of mental health: a review of the evidence

Manuela Silva^a; Adriana Loureiro^b and Graça Cardoso^a

^a Chronic Diseases Research Centre (CEDOC), NOVA Medical School Faculdade de Ciências Médicas, Universidade Nova de Lisboa. Portugal
^b Centre of Studies on Geography and Spatial Planning (CEGOT), University of Coimbra. Portugal

This study was developed within the scope of the investigation project PTDC/ATP-GEO/ 4101/2012, SMAILE, Mental Health - Evaluation of the Local and Economic Determinants, funded by the Science and Technology Foundation (STF) and the European Regional Development Fund (ERDF), through the COMPETE - Operational Competitiveness Program and the doctoral fellowship SFRH/ BD/92369/2013.

Correspondence

ABSTRACT

Background and Objectives: The aim of this study is to present a non-systematic narrative review of the published evidence on the association between mental health and sociodemographic and economic factors at individual- and at area-level.
Methods: A literature search of PubMed and Web of Science was carried out to identify studies published between 2004 and 2014 on the impact of sociodemographic and economic individual or contextual factors on psychiatric symptoms, mental disorders or suicide. The results and methodological factors were extracted from each study.
Results Seventy-eight studies assessed associations between individual-level factors and mental health. The main individual factors shown to have a statistically significant independent association with worse mental health were low income, not living with a partner, lack of social support, female gender, low level of education, low income, low socioeconomic status, unemployment, financial strain, and perceived discrimination. Sixty-nine studies reported associations between area-level factors and mental health, namely neighbourhood socioeconomic conditions, social capital, geographical distribution and built environment, neighbourhood problems and ethnic composition.
Conclusions Most of the 150 studies included reported associations between at least one sociodemographic or economic characteristic and mental health outcomes. There was large variability between studies concerning methodology, study populations, variables, and mental illness outcomes, making it difficult to draw more than some general qualitative conclusions. This review highlights the importance of social factors in the initiation and maintenance of mental illness and the need for political action and effective interventions to improve the conditions of everyday life in order to improve population's mental health.

Keywords: Neighbourhood; Socioeconomic status; Depression; Anxiety; Suicide.

Introduction

"Mental or psychological well-being is influenced not only by individual characteristics or attributes, but also by the socioeconomic circumstances in which persons find themselves and the broader environment in which they live"³. There is a growing interest in documenting the role of social factors on the aetiology and evolution of mental disorders, such as the relation between socioeconomic status (SES) and mental health. Also an increasing number of studies has focused on the impact of contextual characteristics (defined as neighbourhoods, workplaces, regions, states) on individual mental health and in producing health inequalities.

The aim of this study is to review the studies that examined the association between individual and community demographic and socioeconomic factors and psychiatric symptoms, mental disorders or suicide, focusing on the findings and limitations of the existing studies. Identifying the factors that influence mental health is critical for tailoring interventions and programmes that can improve mental health. This knowledge is particularly important in times of economic crisis, when the living and working conditions are substantially worsened, and social factors may have a higher negative impact on the population's mental health.

This paper intends to review empirical studies and systematic reviews assessing: (a) inequalities in the prevalence and incidence of psychiatric symptoms or common mental disorders related to sociodemographic and economic individual or contextual factors; (b) the association between suicide and sociodemographic and economic individual or contextual factors.

Methods

Data sources and search strategy

A literature search was conducted in Pub-Med and Web of Science to identify the studies related to mental health (depression, anxiety and suicide) and social determinants (education, income, socioeconomic status, unemployment and neighbourhood/neighbourhood). Search was opened to studies developed in any region of the world, written in English, French, Portuguese or Spanish and published between 2004 and 2014.

More detailed information on the literature search is provided in Fig. 1.

Study selection

Title screening was first conducted to exclude irrelevant and duplicated studies. The abstracts of potential articles were reviewed by two reviewers (MS, GC). Studies were excluded if they were: (a) Opinion papers, letters to the editor, editorials, or comments; (b) Studies dealing with people below 18 years old; (c) Experimental studies about interventions addressed to reduce health inequalities; (d) Studies dealing with mental health issues among some specific populations (participants with medical conditions, in post-disaster situations, veterans, homeless...); (e) Studies in which the main health outcome variable was other than psychological distress, depression, anxiety or suicide (such as self-harm and suicide ideation, health care and services utilization or any other variables); (f) Theoretical studies or studies of validation of questionnaires; (g) Studies written in other language than English, French, Portuguese or Spanish.

Articles were reviewed in full when the abstract did not provide enough detail to make a decision. More articles were excluded in this phase if: (a) A validated screening or diagnostic instrument was not used; (b) Methodological flaws were detected (no statistical analysis described; outcome not clearly defined); (c) The sample was too small (fewer than 50 participants); (d) We did not have access to the full paper.

Data collection

The results and methodological factors, including objective(s), definition of sample, location and follow-up period, study design, mental health instrument used or source of data, outcome variable, determinant measured and, statistical methods were extracted from each study. A table with the results was constructed (Table 1). The determinant measured was categorized into two types: individual factor (demographic or socioeconomic) and neighbourhood characteristic. The outcome variable was categorized into three types: mental health or mental disorders, common mental disorders, and suicide.

Official, ethical approval was not requested in view of the nature of this study.

The electronic search identified 1228 titles and 150 documents were accepted. We categorized studies according to the outcome measure, and divided them in studies examining the association of social factors with mental health or mental disorders (34 studies), common mental disorders (94 studies), and suicide (22 studies). We grouped the studies according to the independent variable (individual demographic and socioeconomic factors or neighbourhood characteristics). Thirtynine studies were conducted in Europe, 67 in North America, 9 in South America, 5 in Africa, 18 in Asia, 8 in Australia, and one in multiple continents. Three of the studies were systematic reviews.

Findings by exposure are briefly summarized below and notable findings are highlighted.

Review of studies on the social determinants of mental health

We included in this category 34 studies whose outcome measure was "psychological distress", "poor mental health" or "mental disorder". The independent variables were indicators of individual socioeconomic status or characteristics of the context. The size of the samples varied between n = 143 and n = 4.5 million. Thirteen studies were conducted in Europe, 12 in North America, 1 in Africa, 4 in Asia, and 3 in Australia. One was a systematic review. Five studies used the WHO-5 Well-being Index, 3 the CIDI, 3 the SF-36, and 3 used the GHQ, among other mental health instruments. Most of the studies performed multivariable statistical analysis, with adjustment for covariates, and some of them used multilevel models.

Individual demographic and socioeconomic factors

Cross-sectional panel surveys or nationally representative epidemiological surveys identified risk factors for mental health problems or mental disorders: female gender⁴, younger age⁴, lower socioeconomic status^5-7, lower income^5,8,9, lower job satisfaction⁹, food insufficiency¹⁰, being an immigrant from a low- or middle-income country⁸, interpersonal adversity in childhood⁷, feeling powerlessness⁸, negative life events^8,11, lack of social/emotional support^5,7,8,11,12, and living alone⁴ were found to be associated with mental health problems or mental disorders, although the directionality of the association is unclear. In the study conducted by Mundt et al.⁴ in disadvantaged urban areas, background of migration, low income and educational level were not associated with poor mental health.

Cross-sectional studies cannot distinguish whether these risk factors are associated with the development of new episodes of mental disorders, with increased duration of episodes, or both. Measurement of incidence eliminates the chronicity, selection, and drift interpretation, allowing focus on aetiology, but only a few longitudinal studies were found on this issue.

In the longitudinal studies reviewed the factors associated with worse psychological health over time were female gender¹³, lower job satisfaction¹³, age lower than 55 years¹³, living in common-law relationships or being widowed¹³, lower socioeconomic status¹⁴, lower income¹³, and financial concerns^14,15. Caron et al.¹³, in Canada, found that participants whose primary language was neither French nor English were less at risk than Fran-cophones or Anglophones for developing affective (OR = 0.43) and anxiety disorders (OR = 0.40), or for any disorders (OR = 0.45), with the exception of substance dependence.

Some of the studies reviewed aimed to understand if associations between neighbourhood sociodemographic characteristics and individual symptoms or disorders reflect the characteristics of the individuals who reside in the neighbourhood (compositional) or the neighbourhood characteristics themselves (contextual). The results are conflicting: a cross-sectional study concluded that the chief determinants of current mental health and well-being were those reflecting individual level attributes and perceptions¹¹, while others suggested that the places in which people live affect their mental health^9,16-18.

Socioeconomic composition

In other studies, neighbourhood deprivation predicted mental health status, particularly on poorer individuals¹⁶, or predicted psychosis and depression, particularly paranoid ideation¹⁹. On the contrary, Gale et al.¹⁸ found no association between area-level deprivation and mental wellbeing. Fone et al.¹⁷ found that the adverse effect of income inequality on mental health starts to operate at the larger regional level, and that income inequality at neighbourhood level was associated with better mental health in low-deprivation neighbourhoods. An ecological study²⁰ concluded that in neighbourhoods with less social contacts and with a higher proportion of jobless persons the admission rates for schizophrenia and depression increased.

Some prospective studies also explored the impact of context on mental disorders. Neighbourhood deprivation was associated with worse mental health¹⁴, increasing psychiatric medication prescription²¹, and higher risk of being hospitalised for mental disorder²², independent of individual-level sociodemographic characteristics. Hamoudi and Dowd²³ concluded that housing market volatility may influence the psychological and cognitive health of older adults. Another study²⁴ provided little support for social causation in neighbourhood health associations and suggested that correlations between neighbourhoods and health may develop via selective residential mobility.

We found one systematic review on the associations between ethnic density and mental disorders²⁵. The "ethnic density hypothesis" is a proposition that members of ethnic minority groups may have better mental health when they live in areas with higher proportions of people of the same ethnicity. Shaw et al.²⁵ concluded that protective associations between ethnic density and diagnosis of mental disorders were most consistent in older US ecological studies of admission rates. Among more recent multilevel studies, there was some evidence of ethnic density being protective against depression and anxiety for African American people and Hispanic adults in the USA. However, Hispanic, Asian-American and Canadian "visible minority" adolescents have higher levels of depression at higher ethnic densities. Studies in the UK showed mixed results, with evidence for protective associations most consistent for psychoses.

• Social environment

Social capital is defined as the resources available to individuals and to society through social relationships²⁶, "the features of social organization, such as civic participation, norms of reciprocity, and trust in others, that facilitate cooperation for mutual benefit"²⁷.

Some of the empirical studies reviewed assessed the association between social capital and mental health. Social capital may affect mental health in different ways, through its "structural" (connectedness, membership of organisations) or "cognitive" (trust, sense of belonging, and shared values) components. High levels of structural social capital^28-31 and high levels of cognitive social capital^18,30 were associated with lower risk of mental health distress or disorder after taking into account potential individual confounders. People who reported fewer neighbourhood problems had higher levels of mental wellbeing, independently of individual factors¹⁸. The perception of severe problems in the community^28,32, exposure to violence and negative life events³³, and high frequency levels of discrimination³⁴ were associated with higher levels of psychological distress. Perceived neighbourhood satisfaction³⁵ and stress-buffering mechanisms in the neighbourhood³³ were associated with a lower likelihood of disorders. Higher workplace social capital was associated with lower odds of poor mental health in a study among Chinese employees³⁶.

Physical environment / geographical location

Review of studies on the social determinants of common mental disorders

We grouped in this category 94 studies whose outcome was assessed using a validated screening or diagnostic instrument allowing a common mental disorder (depressive or anxiety disorder) diagnosis to be made. The size of the samples ranged between n = 112 and n = 237,469. Sixteen studies were conducted in Europe, 52 in North America, 7 in South America, 4 in Africa, 10 in Asia, 2 in Australia, and one in multiple continents. Two of the studies were systematic reviews. Most of the studies used the CES-D (41), and others used the CIDI (8), the GDS-30 (8), the GHQ (5), the BDI (3), or the HADS (3), among other mental health instruments. Almost all the studies performed multivariable statistical analysis, with adjustment for covariates, and some of them used multilevel models.

Individual demographic and socioeconomic factors

We found a systematic mapping of research on postnatal depression and poverty in low- and lower middle-income countries⁴⁰. The authors state that research is limited, but has recently expanded, and that it is dominated by studies that consider whether poverty is a risk factor for postnatal depression. They found that income, socio-economic status and education are all inconsistent risk factors for postnatal depression. Coast et al.⁴⁰ argue that to understand the scale and implications of postnatal depression in low- and lower middle-income countries research has to take into account neighbourhoods, communities, and localities.

Several cross-sectional studies assessed which individual demographic and socioeconomic factors were associated with an increased prevalence of common mental disorders. Female gender^41-48, not being married^{41,42,44,46,48-52}, being married⁴⁵, higher age^42,52, household food insufficiency^53,54, less favourable housing condition^54,55, low social position^43,56, lower education^56-58, unemployment^52,58-60, low income^{42,44,45,49,52,55,57,58,61-64}, financial strain⁴⁹, less income stability⁵⁶, negative subjective health^48,52,59,62, lower overall health status⁴², having functional impairment⁶², rural residency^47,52,65, no religiosity⁵², lower social stability⁶⁶, being a victim of sexual violence⁵⁹, psychological violence during childhood⁵⁹, lack of support network^{49,59,61,67,68}, poorer quality of life⁴², perceived discrimination (racial or other)^54,69, perceived stress⁵⁸, a poor sense of mastery/ control^63,70, and feeling more lonely^47,55 were variables that remained significantly associated with an increased prevalence of common mental disorders after adjustments. St John et al.⁶² found no rural-urban differences associated with depressive symptoms. Depression is a severe problem in the unemployed population, particularly among the long-term unemployed⁶⁰. In a population-based register study in Finland, among those with no previous inpatient or antidepressant treatment, all measures of low social position and not living with a partner predicted admission for depression⁷¹.

Some cross-sectional studies focused specifically in identifying protective and risk factors associated with common mental disorders in immigrants. Two studies conducted in the US compared native-born and immigrant groups: the first found that, controlling for other predictors, the likelihood of depression was much higher among black women who were US born than among black women who were African born or Caribbean born⁷², and the second showed that a native-born Mexican American group was not significantly different from an immigrant group on measures of depression, health status, life satisfaction, or self-esteem⁷³. Another study, conducted among Gujarati-speaking immigrants in Atlanta⁷⁴, concluded that poorer health and a more traditional ethnic identity were related to depressive symptoms.

In prospective studies the following factors were independently associated with higher rates of common mental disorders: female gender⁷⁵, socioeconomic disadvantage⁷⁶, low level of education⁷⁵, lower subjective social status⁷⁷, mortgage delinquency⁷⁸, home foreclosure⁷⁹, financial strain⁸⁰, marital conflict and marital disruption⁸¹, and perceived discrimination^82-84. Depressed individuals with low socioeconomic status appear disproportionately likely to experience multiple risk factors of long-term depression⁸⁵. In one study, only subjective financial difficulties at baseline were independently associated with depression at follow-up, supporting the view that apart from objective measures of socio-economic position, more subjective measures might be equally important from an aetiological or clinical perspective⁸⁶.

A study in the US suggested that the rise in the prevalence of depression in the prior quarter century among middle-aged females is due to increasing chronicity⁸⁷. Another study suggests that the causal relationship hypothesized in prior studies -that perceived social position affects health- does not necessarily hold in empirical models of reciprocal relationships⁸⁸. Higher SES prior to job loss is not uniformly associated with fewer depressive symptoms: higher education and lower prestige appear to buffer the health impacts of job loss, while financial indicators do not⁸⁹.

We found a systematic review of the published literature on the associations between neighbourhood characteristics (neighbourhood socioeconomic status, physical conditions, services/amenities, social capital, social disorder) and depression in adults⁹⁰. Evidence generally supports harmful effects of social disorder and, to a lesser extent, suggests protective effects for neighbourhood socioeconomic status. Few investigations have explored the relations for neighbourhood physical conditions, services/amenities, and social capital, and less consistently point to salutary effects. Kim⁹⁰ argues that the unsupportive findings may be attributed to the lack of representative studies within and across societies or to methodological gaps, including lack of control for other neighbourhood/non-neighbourhood exposures and lack of implementation of more rigorous methodological approaches.

Socioeconomic composition

Some cross-sectional studies suggest that neighbourhood low-SES^49,91, material deprivation^92,93, living in an area with high unemployment⁹⁴, residential mobility⁹², residential stability⁹⁵, higher population density⁹⁶, urban neighbourhoods⁹⁷, perceived traffic stress⁹⁸, neighbourhood walkability⁹⁹, poor quality built environment^100,101, village infrastructure deficiency¹⁰², neighbourhood violent crime and poorer perceptions of neigh-bourhood safety¹⁰³ are associated with increased depressive symptoms or depression, independent of individual level characteristics. However, other studies suggest that individual level characteristics explain away the association between neighbourhood level factors and depression^{48,57,95,96,104}. Higher household income may help to reduce symptoms of depression by reducing financial stress and strengthening social support even within neighbourhoods with high concentrations of poverty, but it does not protect those residing in a high poverty community from distress associated with neighbourhood disorder or experiences of discrimination¹⁰⁵.

In an ecological study, the significant risk factors found for hospitalization included unemployment, poverty, physician supply, and hospital bed supply, and the significant protective factors were rurality, economic dependence, and housing stress¹⁰⁶.

Two cross-sectional studies included in this review^107,108 demonstrated that living in a neighbourhood with a higher percentage of residents of the same ethnicity was associated with depression.

Data from some prospective studies indicate socioeconomic status of neighbourhood of residence to be associated with incidence or worsening of depression independent of individual socioeconomic status and other individual covariates¹⁰⁹, while others did not support this association^110,111. In multivariable models that adjusted for individual-level covariates, the neighbourhood characteristics shown to represent risk factors for common mental disorders were increases in neighbourhood-level foreclosure¹¹², economic disadvantage/deprivation^113-116, exposure to neighbourhood unemployment earlier in life¹¹⁷, perceived community violence¹¹³, social disorder¹¹⁴, and urban neighbourhoods¹¹⁸. In another study, living in a socially advantaged neighbourhood, with cultural services, near a park and having a local health service nearby were associated with lower risk of depression¹¹⁹.

Some studies examined the impact of income inequality on mental health. One cross-sectional study found significant associations between neighbourhood inequality and depression¹²⁰, and another found higher depressive symptoms in countries with greater income inequality and with less individualistic cultures⁶³, independently of individual level effects. A longitudinal study found that income inequality did not correlate significantly with the presence of depressive symptoms¹¹⁵.

Social environment

Cross-sectional studies suggest that neighbourhood-level social capital^121,122 and its dimensions of availability and satisfaction with community services^102,123, high collective efficacy¹²⁴ and community participation¹²⁴ reduce the likelihood of depressive symptoms. One study found that major depression was not associated with social capital¹²⁵. In an instance of the "dark side" of social capital, Takagi et al.¹²⁶ found that stronger social cohesion increased depressive symptoms for residents whose hometown of origin differed from the communities where they currently resided. Both neighbourhood disorder and community cohesion were related to PTSD symptoms after controlling for trauma exposure¹²⁷. Life events mediate the relation between neighbourhood characteristics and depression¹²⁸. Teychenne et al.¹²⁹investigated the contribution of perceived neighbourhood factors in mediating the relationship between education and women's risk of depression, and they found that interpersonal trust was the only neighbourhood characteristic which partly mediated this relationship.

Review of studies on the social determinants of suicide

In this category we included 22 studies. 10 of these studies were conducted in Europe, 3 in North America, 2 in South America, 4 in Asia, and 3 in Australia. The studies consisted of individual-level evidence (case-control or cohort studies) or aggregate (ecological) studies.

Individual demographic and socioeconomic factors

Individual-level evidence shows that risk factors for suicide are male gender¹³⁴, older age^134,135, being unmarried/divorced/widowed¹³⁶, low education^137-139, socioeconomic disadvantage^138,140,141, unemployment¹³⁵, increasing levels of firearm availability¹³⁵, and immigration¹⁴². In a study describing the characteristics of elderly suicide victims¹³⁹, suicide was associated with living in a one-person household (OR = 2.4, p < 0.01), not having economic troubles (OR = 6.1, p < 0.01), having seen a doctor in the past month (OR = 2.4, P < 0.01) and living in a residential facility (OR = 2.6, p < 0.05).

Neighbourhood characteristics

Some studies have shown associations between suicide rates and indices of area deprivation^137,143-145. However, O'Reilly et al.¹⁴¹ suggested that differences in rates of suicide between areas are predominantly due to population characteristics rather than to area-level factors.

Individual-level and population-based evidence suggested that low social capital^146,147, low linking social capital¹⁴⁸, unemployment rate¹⁴⁹, the proportion of indigenous population¹⁴⁹, the proportion of population with low individual income¹⁴⁹ and income inequality¹⁵⁰, particularly for those aged 15-60¹⁵¹ were significantly and positively associated with suicide. Another study found no statistically significant independent association of a structural measure of neighbourhood social capital (volunteerism) with suicide¹⁵².

In the studies reviewed on the geographical distribution, suicide rates were higher in rural areas^134,137,140. In a study in the US, rural decedents were less likely to be receiving mental health care and more likely to use firearms to commit suicide¹⁵³. A study in England and Wales¹⁵⁴ found higher rates of suicide in inner cities, but largely explained by the socioeconomic characteristics of these areas, and in coastal regions, particularly those in more remote regions. In Croatia, Karlović et al.¹⁵⁵ found a higher average suicide rate in the continental area than in the Mediterranean area.

Discussion

Main findings

The systematic reviews included in this study showed a) mixed results on the associations between ethnic density and mental disorders, b) limited research on the association between poverty and postnatal depression in low- and lower middle-income countries, with inconsistent results, and c) support for the harmful effect of neighbourhood social disorder and, to a lesser extent, protective effect of neighbourhood socioeconomic status on depression.

This non-systematic narrative review documents a growing body of literature investigating the social determinants of mental health: 47 of the 150 studies included (31,3%) were published in 2013 and 2014, with only 17 (11,3%) of the studies published in 2004 and 2005, the two first years of this review.

Seventy-eight studies reported associations between individual-level factors and mental health. Given the large number of exposures considered in this review, some exposure-outcome pairs were examined by only a single study. The main factors shown to have a statistically significant independent association with worse mental health were low income (17 studies), marital status/not living with a partner (16 studies), lack of emotional/social support (10), female gender (9), low level of education (9), low socioeconomic status (7), unemployment (5), financial strain (5), perceived discrimination (5), negative subjective health (4), loneliness (4), low subjective social status (3), deteriorated housing (3), higher age (3) and negative life events (3). Level of education, parenthood, rural-urban differences, low socioeconomic position and race were not associated with mental health outcomes in one study for each determinant.

Sixty-nine studies reported associations between area-level factors and mental health, 23 focusing on social capital, 36 on neighbourhood socioeconomic conditions, 15 on geographical distribution and built environment, 9 on exposure to neighbourhood problems, and 2 on ethnic composition. The large majority (12 of 14-86%) of the studies assessing "structural" aspects of social capital found a statistically significant association between measures of low social capital and poor mental health. Ninety-two percent (12 of 13) of the studies assessing "cognitive" aspects of social capital found a statistically significant association between low social capital and poor mental health. Statistically significant positive associations were found in 24 (82.8%) of the 29 studies assessing the relationship between measures of neighbourhood economic disadvantage and psychological distress, depression and suicide. Income inequality was a risk factor for suicide in 2 studies, but results on the association with poor mental health and depression were conflicting. Unemployment rate emerged as a risk factor for poor mental health and suicide in 6 studies. Being exposed to neighbourhood problems was associated with higher levels of psychological distress, depression and suicide in 11 studies, while the presence of stress-buffering mechanisms was statistically significantly and negatively associated with mental disorders. Urban neighbourhoods were associated with depression in 4 studies, but rural areas were associated with higher suicide rates than urban areas in other 4 studies. Poor quality built environment also emerged as a risk factor for depression in 3 studies, while neighbourhood walkability and living near a park were protective factors.

Limitations

This review has some limitations, at review-level and at study- and outcome-level.

Literature search was limited to articles focusing on individual and contextual determinants, and this search strategy may have contributed to an incomplete retrieval of studies. Several exclusion criteria were established in order to reduce the heterogeneity of studies and to make it possible to extract some conclusions, and this further narrowed the studies included. We had no access to 31 of the 266 articles assessed for eligibility, and that was a reason for exclusion.

There was large heterogeneity between studies concerning study design and populations, determinants, outcome and instruments used. This heterogeneity only allows a few descriptive findings.

Future research direction

Further empirical studies on social inequalities in health are needed to make sense of the mixed research findings, to understand the pathways through which they influence health, and to find out ways of reducing their magnitude.

Two main mechanisms have been posited in understanding the link between mental illness and poor social circumstances: social causation and social selection. According to the social causation hypothesis, socioeconomic standing has a causal role in determining health or emotional problems. Social selection hypothesis posits that genetically predisposed individuals with worse physical or emotional health may "drift down" the socioeconomic hierarchy or fail to rise in socioeconomic standing as would be expected on the basis of familial origins or changes in societal affluence. Longitudinal studies, with multiple time point measures, are much needed in the future to clarify the causal direction between social determinants and mental health.

The study of the associations between contextual SES and mental health also needs more powerful studies, using multilevel analyses and establishing mediating pathways and effect-modifying factors, in order to disentangle the individual effect from the neighbourhood effect on health.

Conclusion

The goal of this literature review was to identify the relevant published evidence on the associations between social determinants and mental health. These disorders are highly prevalent, have severe consequences, and it is particularly important to improve our understanding of modifiable risk factors that may help to advance preventive efforts.

For many decades, studies have shown that mental health is the complex outcome of numerous biological, psychological and social factors, involving contextual factors beyond the individual. Despite changes in concepts and methods used to define cases and measure socioeconomic status, the studies reviewed suggest that exposure to a wide range of social stressors continues to play an important role in the aetiology and the course of mental health problems and disorders. Higher rates of mental disorders are associated with social disadvantage, especially with low income, limited education, occupational status and financial strain. Lack of social support, high-demand or low control over work, critical life events, unemployment, adverse neighbourhood characteristics, and income inequality were also identified as psychosocial risks that increase the chances of poor mental health. Importantly, this review highlighted some important protective factors: having trust in people, feeling safe in the community, and having social reciprocity is associated with lower risk of mental health distress.

Acknowledgements

We thank the researchers and consultants of the project SMAILE, Study on Mental Health - Assessment of the Impact of Local and Economic Conditioners (PTDC/ATP-GEO/4101/2012) - Benedetto Saraceno, Carla Nunes, Cláudia Costa, Joana Lima, João Ferrão, José Miguel Caldas de Almeida, Maria do Rosário Partidário, Paula Santana, and Pedro Pita Barros - for their contributions during the development of the project.

Declaration of interest

The authors report no conflicts of interests. The authors alone are responsible for the content and writing of the paper.

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Correspondence:
Manuela Silva
Chronic Diseases Research Center (CEDOC)
NOVA Medical School
Faculdade de Ciências Médicas
UNL, Campo dos Mártires da Pátria, 130
1169-056 Lisboa Portugal ]]> Tel: +351 218 803 046
Fax: +351 218 803 079
E-mail: manuela.silva@gmail.com

Received: 20 February 2016
Revised: 11 June 2016
Accepted: 29 September 2016