How Do Maternal Employment and Life in Dual-earner Families Affect Childrenã¢â‚¬â„¢s Development

• Systematic review
• Open Access
• Published: 06 Dec 2018

How do macro-level structural determinants bear on inequalities in mental health? – a systematic review of the literature

• South. Fritzell^1,2,
• Thousand. Almroth¹,
• Fifty. Harber-Aschan¹,
• South. Larsson¹ &
• B. Burström¹

International Journal for Equity in Wellness book 17, Article number:180 (2018) Cite this article

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Abstruse

Groundwork

In Europe and elsewhere there is rising concern about inequality in wellness and increased prevalence of mental ill-wellness. Structural determinants such as welfare country arrangements may touch on levels of mental wellness and social inequalities. This systematic review aims to assess the current testify on whether structural determinants are associated with inequalities in mental health outcomes.

Methods

Nosotros conducted a systematic review of quantitative studies published between 1996 and 2022 based on search results from the following databases Medline, Embase, PsychInfo, Spider web of Scientific discipline, Sociological Abstracts and Eric. Studies were included if they focused on inequalities (measured past socio-economic position and gender), structural determinants (i.e. public policies affecting the whole population) and showed a alter or comparison in mental wellness status in one (or more) of the Organisation for Economical Cooperation and Development (OECD) countries. All studies were assessed for inclusion and report quality by ii independent reviewers. Data were extracted and synthesised using narrative analysis.

Results

Twenty-one articles (17 studies) met the inclusion criteria. Studies were heterogeneous with regards to methodology, mental health outcomes and policy settings. More comprehensive and gender inclusive welfare states (e.m. Nordic welfare states) had improve mental wellness outcomes, especially for women, and less gender-related inequality. Nordic welfare regimes may likewise decrease inequalities between lone and couple mothers. A potent welfare land does not buffer against socio-economic inequalities in mental health outcomes. Austerity measures tended to worsen mental health and increase inequalities. Expanse-based initiatives and educational policy are understudied.

Conclusion

Although the literature on structural determinants and inequalities in mental wellness is limited, our review shows some evidence supporting the causal effects of structural determinants on mental health inequalities. The lack of bear witness should not exist interpreted every bit lack of issue. Futurity studies should apply innovative methods to overcome the inherent methodological challenges in this area, every bit structural determinants potentially impact both levels of mental health and social inequalities.

Introduction

The burden and prevalence of mental ill-health and mental illnesses are increasing [1]. Enquiry shows that there are many explanations for this such equally better sensation and diagnosis, environmental factors, structural factors and changes in public policy [2]. In this review, nosotros focus on the structural, defining structural determinants as public policies affecting the whole population [three], we propose vi master domains of welfare states, family unit policy, employment policy, income support and social insurance policy, area-based initiatives and education policy (see further explanation beneath). The Swedish Regime commissioned The Public Health Agency of Sweden to increase the noesis on mental health inequalities and their underlying determinants, this study is part of this larger project. Against this background, the main focus of the review was on studies of structural determinants and policies in Western welfare states. Nosotros define mental health broadly including positive mental health, mental sick-health and diagnoses of mental illnesses. Overall, we aim to investigate whether structural determinants are associated with mental health outcomes and if these determinants differentially bear on on mental wellness outcomes past socio-economic condition (SES) and gender.

The following provides a farther explanation of inequalities in mental wellness and structural determinants of mental health.

What are inequalities in mental health?

The burden of mental illness is not equally distributed in the population. Epidemiological show consistently demonstrates an inverse association betwixt SES and psychiatric morbidity, such that more than disadvantaged groups are affected by mental disease to a greater extent [iv]. Also, demographic factors such as gender and ethnicity (although not in themselves modifiable) may further modify the adventure of mental disorder, depending in plough on how wealth, power and resources are distributed by gender and ethnicity (run across for example [5, six]). This further suggests that distributions of mental illness are systematically shaped by social, economic as well as physical environments throughout the life-course [vii], putting more than disadvantaged population sub-groups at greater adventure for mental illnesses through exposure to unfavourable social and economic circumstances.

How are structural determinants related to mental health?

Nosotros propose that structural determinants affect the distribution of resources and accept the potential to influence mental health inequalities. Previous research shows that welfare state arrangements, social and economic policy may influence the distribution of wellness betwixt social groups [3, viii,9,x,11,12]. We used this literature to deconstruct structural determinants into half-dozen public policy domains: welfare states, family unit policy, employment policy, income support and social insurance policy, area-based initiatives and pedagogy policy (see Table one). Borrell, et al. [iii] suggest that such policy domains are drivers of the social structure and power relations that ultimately generate social inequalities in health. We suggest that these policy domains may mitigate or reduce the chance of poor mental health that provides the conditions for everyday life and influence the opportunities available to people across the life form. Nosotros also acknowledge the importance of healthcare policies in shaping access to services, and that these are likely to contribute to mental wellness inequalities. Still, nosotros practice not asses these in this review as we conceptualise these as downstream factors influencing the treatment of mental illnesses, every bit opposed to broader structural determinants of mental illness.

Table 1 Policy domains and examples

Full size tabular array

We included all welfare typologies in our review. Nosotros suggest, that regardless of the typology, examining welfare regimes provides insight into the values and norms that influence structural determinants. To illustrate, nosotros utilize Korpi'south [13] family model regime typology. The dual-earner/carer models (e.g. Denmark, Sweden, Norway, Republic of finland) are characterised by providing universalistic public policies to encourage labour force participation and gender equality. In contrast, the market-oriented model (e.g. Australia, the Great britain and the The states) provides limited social protection mostly towards those considered 'deserving' through ways-tested benefits. In this welfare regime, the market, rather than public policy determines gender roles. In traditional family models, (e.g. Kingdom of belgium, kingdom of the netherlands, Kingdom of spain), policies are organised around the family with men ofttimes viewed as the 'breadwinner'. Unpaid labour is seen every bit a responsibility of the family rather than the state which leads to low support for female labour force participation.

While social determinants of mental affliction have long been recognised [7, 14], only recently have they received more attention, peculiarly in the wake of the recent economical crisis [15]. However, almost empirical research focuses on proximal, "down-stream" determinants and few focus on broader, "upstream", what we define as structural determinants and how these might affect social distributions of mental illness. To the best of our knowledge, no systematic review of the literature exists on structural determinants and their impact on mental health outcomes. We specifically sought to respond the post-obit:

1. 1.

   Which structural determinants (i.east. public policies) are associated with inequalities in mental wellness outcomes?

2. 2.

   In what context have these policies been implemented?

3. 3.

   What social differentials (across socio-economical groups and between men and women) be regarding mental wellness outcomes?

Methods

This review was structured in accord with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [16], with additional focus on disinterestedness using the PRISMA-Due east 2012 [17].

Information sources and search strategy

We searched for eligible articles in the post-obit databases: Medline (Ovid), Embase (Embase.com), PsycINFO (Ovid), Web of Science, Sociological Abstracts (ProQuest) and ERIC (ProQuest). The Karolinska Institutet Library completed the initial search on 16 March 2022 and an updated search on 7 November 2017.

We also reviewed publications of recognised experts in this expanse equally well equally other relevant studies and projects such equally Evaluating the Impact of Structural Policies on Health Inequalities (SOPHIE) [18]. Two reviewers besides screened the bibliographies of all relevant reviews. See Additional file ane for a detailed search strategy. Ethical approving was not required every bit results are based on previously published papers.

Eligibility criteria

Articles were considered eligible if they were (1) Original, peer-reviewed, written in English and published between 1996 and 2017. (ii) Quantitative studies showing a change or comparison in mental health status (i.east. mental disorder diagnosis, positive (self-rated) mental wellness, suicide rate) using a validated mental wellness measure, and (3) Examined i of the policy domains (Table 1) in at to the lowest degree i of the Organisation for Economic Cooperation and Development (OECD) countries. See Boosted file 2 for more than information well-nigh the inclusion and exclusion criteria used in the selection process.

Study selection

We employed ii levels of screening to identify relevant studies. All screening tools were airplane pilot tested earlier each level of screening. In the following section, we briefly describe each level:

Level 1 – Title and abstract screening

Virtually articles were excluded at this level because the title and abstruse did not focus on mental health and/or one of the policy domains. This was primarily conducted by SL. Another reviewer (AM) independently applied the criteria for inclusion and exclusion to fourteen% of the title and abstracts (350 references). Any disagreements betwixt SL and AM were resolved later on discussions.

Level 2 – Full-text screening

The option criteria were clarified and rewritten for the Level two – Full-text screening. Four reviewers participated in Level 2 screening. All articles were reviewed by at to the lowest degree two reviewers. The review squad discussed articles where there were disagreements on final decisions (30%). If the team could non agree, then the article was reviewed by a third member of the review squad. AM was responsible for making all final decisions.

Written report quality assessment and run a risk of bias

All included articles were assessed using the "Health Evidence Bulletin, Wales: Questions to help with the disquisitional appraisal of an observational report" (hereto referred to as HEB – Wales Tool) [19]. The HEB – Wales Tool is ane of the few quality assessment tools that is designed to fairly appraise different written report designs. The tool has been endorsed by Sanderson, et al. [20] for its ability to be used to appraise cohort, case-control and cross-sectional report designs; transparency regarding development; applicability for future apply; and apply of a checklist system which we used to develop a rating scale. Nosotros adapted the tool so that questions were most relevant to our study aims (meet Additional file 3).

While the HEB – Wales Tool was designed as a checklist rather than a scoring tool, we agreed on a scoring system (a priori) where the report was given a score of two if the criteria for the particular was met. If information technology was unclear and so a score of one was given, and if it clearly did not meet the criteria then a score of zero was given. Each study was given a total score out of thirty possible points. If a written report had a score of more than 23 points (the authors met at least 80% of the items), then it was classified as high quality. Medium quality studies had a cut-off score between 18 to 23 points and depression-quality studies scored 17 points or less (the authors simply met 60% of the items). All articles were quality appraised by 2 reviewers. The final score is an boilerplate of the 2 reviewers' scores (run into Boosted file four for a summary of the scores).

We assessed the take a chance of bias in individual studies using Part B of the HEB – Wales Tool entitled "Do I trust it?" In this section, we assessed whether the written report blueprint and study population was appropriate, confounding and bias were considered in the written report, and in that location was a long plenty follow-up time. Most of the risk of bias was assessed at the pattern rather than event level.

Data extraction strategy

A data extraction template was created and piloted past SF and AM. Using this template, we extracted data from all articles that were marked as 'included' in Level 2 screening. Four reviewers completed this phase, with two reviewers assigned to each article to excerpt information. AM then compared the results and completed a summary table. Any discrepancies were resolved through word between the ii reviewers.

Data items

Table 2 summarises the data items extracted from each article.

Table two Data items from each article

Total size table

Data synthesis

We used narrative analysis to synthesise the data. Categorising the policy domains and focusing on the ii specific types of inequalities (gender and SES), were deliberate strategies intended to make the data synthesis clearer. Furthermore, other data items extracted such as study pattern, population, and setting were intentional measures to assist with comparing heterogeneity in the studies. The implementation of the HEB-Wales Tool as well fabricated information technology possible to systematically compare the quality of the studies.

Results

Study selection

The search strategy and other sources produced 3394 papers which were assessed for inclusion in the review. Data were extracted from 21 papers that met our eligibility criteria. Effigy 1 shows a PRISMA flow diagram of the selection process.

Fig. ane

PRISMA Menses Diagram [15]

Full size epitome

Written report characteristics

The 21 selected manufactures were representative of 17 different studies or data sources. The majority investigated European countries, including 10 articles involving Sweden. Five articles, however, included data from Australia, Canada, the USA and Japan. Twelve of the studies compared two or more countries, while the remaining nine focused on a single country. One study focused on adolescents and the remaining twenty involved a working age population ^{Footnote 1}.

Thirteen manufactures used cross-sectional methods and 10 used longitudinal methods, two of which used a natural policy experiment design.

The manufactures measured constructs of positive mental health, mental ill-health and diagnoses of mental illnesses. Positive mental wellness constructs were represented in 11 articles and included mental health functioning, mental well-being and social-emotional development. Mental distress, poor mental health, depression, suicide rates, psychiatric diagnosis and anti-depressant prescription stand for the negative aspects of mental health and diagnoses of mental illnesses measured in ten of the studies. Several validated mental health measures were used including the World Health Organization Well-Being Alphabetize (WHO-5), the Global Health Questionnaire (GHQ-12), the Short Course Health Survey (SF36 and SF12), the Middle for Epidemiological Studies Depression Scale (CES-D8), Mental Health Inventory (MHI-5), Ages and Stages Questionnaire (ASQ-SE), Health Behaviour in School Age Children (HBSC), Self-Reported Health in the Quarterly Labour Force Survey, suicide statistics and annals data for psychiatric diagnoses.

V articles focused just on gender inequalities in mental health, and 12 manufactures measured only SES inequalities, with iv investigating both types of inequalities. Table 3 summarizes the results from the 21 included manufactures.

Tabular array three Summary of results

Full size table

As results showed that the type of welfare regime strongly influenced the direction of some policy domains, the dimensions of employment policies, family policies and income support and social insurance policies, were added equally sub-domains to the welfare state domain. The following section outlines the results by each policy domain or sub-domain.

Welfare states

9 articles focused on the policy domain of overall welfare states [21,22,23,24,25,26,27,28,29], significant that comparisons were made by categorising European countries into welfare regime types, such every bit the Nordic dual earner/carer model, family oriented, and marketplace-oriented models. Four of the nine articles addressed gender inequalities, three addressed SES inequalities and ii addressed gender and SES. Ii articles, (Sekine, et al. [26] and Sekine, et al. [27]) were based on the same written report, but the former focused on SES inequalities while the latter focused on gender inequalities. Just one study focused on social expenditures [29] and the other eight focused on employment or piece of work characteristics within different welfare regimes.

A dual-earner model where both partners contribute to wage earning and care responsibilities (typically in the Nordic countries) seems to be associated with meliorate mental health outcomes for women while the market place-oriented model (e.g. the Uk) was associated with worse mental health outcomes for women [21,22,23, 27, 28]. There also appears to be less of a gap between men and women when information technology comes to mental wellness functioning in the dual-earner model [23]. Furthermore, greater investment in social spending and family focused welfare models were associated with better mental wellness outcomes for women [29].

Family policy

4 articles focused on the policy sub-domain of family [xxx,31,32,33]. One of these focused-on gender inequality while the other three focused on SES inequality. Findings from Huang, et al. [32] and Rathmann, et al. [33] had opposing conclusions in that Huang, et al. [32] found that cash benefits reduced mental health inequalities betwixt children of lone and couple mothers, and Rathmann, et al. [33] ended that an increment in family benefits actually led to a greater gap in SES inequality in mental wellness outcomes. The limited evidence mostly suggests that investment in family benefits leads to overall meliorate mental health outcomes but may not reduce the gap in inequalities in mental health outcomes.

Employment policy

Only one commodity focused on the policy sub-domain of employment and addressed gender and SES inequality [34]. As such, nosotros cannot conclude well-nigh inequalities in mental wellness outcomes related to this domain. However, given the quality of the study design and the large sample size, we should consider that in this case, austerity measures contributed to worse mental health outcomes amidst lower SES groups [34].

Income support and social insurance

4 studies focused on the policy sub-domain of income back up, all of which analysed SES inequalities rather than gender inequalities [35,36,37,38]. Three of these manufactures focused on austerity measures and found that mental health inequalities increased, and especially vulnerable groups experienced greater mental health bug. Van der Wel, et al. [38] constitute that mental wellness inequalities were smaller in countries with more generous sickness benefits. It is unclear if these furnishings are a direct result of the policies or if they work through other mechanisms. For instance, Barr, et al. [36] propose that austerity measures may have contributed to increased suicide rates and other mental wellness problems while Blomqvist, et al. [37] conclude that inequalities in mental health amidst women could be due to stricter eligibility criteria and decrease in do good levels only there is no definitive bear witness that policy change (i.due east. tightening eligibility criteria and reduced benefit levels) leads to mental distress. The limited testify shows that more generous welfare benefits are associated with ameliorate mental health outcomes and austerity measures are associated with poorer mental health outcomes including increased suicide rates. Additionally, austerity measures seem to contribute to widening the social inequalities gap.

Surface area-based initiatives

Three articles focused on the policy domain of area-based initiatives, or interventions in a specific geographical location [39,40,41]. Two studies focused on the New Deal for Communities initiative in England [twoscore, 41] with both focusing on SES inequality. Mohan, et al. [39] studied a different surface area-based initiative and focused on gender and SES inequality. Limited results regarding area-based initiatives show that these interventions can forbid or reduce the gap in social inequalities of mental health, or at least prevent the widening of this gap in the targeted areas, and that neighbourhood renewals in more disadvantaged areas provide some improvement to women's mental well-being.

Education

We did non find any manufactures focused on the policy domain of educational activity which met our criteria. We therefore cannot draw any conclusions related to educational policy and mental health inequalities.

Word

Nosotros synthesised the literature examining the impact of structural determinants on mental health inequalities, specifically focusing on economical and social policies underpinning the welfare state, and prevailing societal norms (see Table four). Of the 21 inquiry manufactures identified, well-nigh were observational studies, and only ii studies used a natural policy experiment study design. Of the policy domains examined, welfare states were the about comprehensively researched. We should notation that near included studies focusing on welfare states used a regime approach (e.g. Korpi's [13]) simply equally Bergqvist, et al. [42] argue at that place are other ways to examine welfare states such as through an institutional or expenditure approach. Other approaches may provide culling perspectives on our research question.

Table 4 Summary of changes in inequality by policy domain

Full size tabular array

This review indicates that more than comprehensive and gender inclusive welfare states atomic number 82 to better mental health outcomes especially for women, but there is picayune evidence that this reduces socio-economical inequalities. Nosotros discuss these issues separately below.

Gender inequalities and mental health

Evidence from the welfare land domain indicated that dual-earner models (typically found in the Nordic countries) were associated with better mental wellness outcomes and less prominent mental health inequalities past gender, compared to other welfare regimes particularly bones-security/market place welfare states [21, 23, 26,27,28]. These findings align with findings of Borrell, et al. [3] that in dual-earner models, public policies support women'southward employment while imposing more equitable sharing of domestic work leading to better wellness outcomes.

Three studies examined the intersection between gender and relationship condition [28, 30, 32], highlighting a socially and economically vulnerable grouping of women; alone mothers. Van de Velde, et al. [28] found that, in general, lone mothers' mental wellness seems to exist worse than cohabitating mothers, aligning with other studies (run across for example [43,44,45,46]. Included studies looked at welfare state arrangements and tested specific measures to lessen fiscal strain. Van de Velde, et al. [28] conclude that welfare regimes may moderate inequalities in mental health between lonely and cohabitating mothers, finding smaller inequalities in Sweden (i.e. Nordic welfare authorities) than Britain (i.e. Marketplace-oriented welfare government). Huang, et al. [32] suggests that cash benefits to lone mothers are ane style to reduce the gap in mental health between children of solitary and cohabitating mothers. Yet, Bergqvist, et al. [42] notes that reducing inequalities takes a combination of generous family benefits and supporting women in the labour market. On the other hand, Whitehead, et al. [44] constitute that the pressure for lone mothers to work in Sweden could contribute to worse health outcomes. Many studies show that family unit policies facilitate the piece of work-family balance and decrease financial strain, both factors are associated with better wellness amongst lonely mothers (see for instance [44,45,46], however, many of these studies mostly focus on mothers' general wellness, rather than mental health outcomes.

While outside the scope of our article, some included studies [23, 26, 27] emphasised the function that job quality plays in gender differences. For instance, De Moortel, et al. [23] purposes that differential exposure to bad quality employment (due east.g. non-permanent contracts, depression wage, lack of matrimony representation) is partly explained by welfare regimes.

Socio-economical inequalities and mental health

While the Nordic countries seem to produce amend mental health outcomes for women, our results practise non back up that this approach reduces socio-economic inequalities in mental wellness outcomes. Rather, our results back up Mackenbach's [47] conclusions that potent welfare states such as in Sweden exercise not buffer against socio-economic inequalities in health.

We found that the evidence on welfare states and socio-economic inequalities was inconsistent. On the i hand, Niedzwiedz, et al. [24] suggests that higher spending on active labour market programmes reduced inequalities, specifically by improving mental wellness outcomes among those with the everyman education. Nevertheless, Rathmann, et al. [33] constitute that higher spending on social protection, particularly during the recent recession, is not enough to reduce the socio-economic inequalities in the mental health of adolescents. Rather, the authors suggest that a combination of social spending and programs directly targeting adolescents could exist more constructive [33]. Hewitt, et al. [31] also institute that increased spending on paid parental leave, improved overall maternal mental health but did not subtract the gap betwixt mothers with low SES and high SES.

Contrasting these studies, Nordenmark, et al. [25] notation that socio-economic inequalities could be wider in Sweden than the United kingdom because of a 'levelling down' process that happens with those in higher SES in the UK. The authors explain that persons with higher SES experience greater economic strain receiving flat-charge per unit benefits (i.e. the UK) as their drib in income is larger, compared to countries with income replacement (i.e. Sweden), leading to poorer mental health outcomes on flat-rate benefits than persons with lower SES [25].

Thrift measures associated with poor mental health outcomes

Four of the included studies [34,35,36,37] showed an association betwixt poor mental wellness outcomes and austerity measures – reducing government spending, due east.grand. by cutting programs and reducing do good levels. A growing body of literature on the straight and indirect health effects of austerity measures support our findings (see for example [15, 48]). More generous public policies like those in Nordic welfare states are associated with meliorate overall mental health outcomes, even if they do not reduce socio-economic inequalities.

Why so little on education policy?

We propose that the absence of studies focused on education policy is in part because most school policy and schoolhouse intervention research focus on academic outcomes rather than mental health outcomes. Academic outcomes are more attainable to researchers given that children are already assessed based on their school performances. Academic achievement is closely related to mental wellness, and the 2 are associated throughout the life course [49], nevertheless, more inquiry is warranted to uncrease some of these mechanisms. Furthermore, school is often seen as a neutral environment that is supposed to 'level the playing field' to some extent. The focus of inequality is often based on students' background characteristics rather than what actually happens at school, or how these factors interact [l]. Other studies examine much older policy changes and practise non explicitly focus on mental health outcomes (encounter for example [51]). Further research on school-level determinants of mental health outcomes and investigation of school systems which have undergone changes in educational policy may assistance elucidate some of these questions.

Limitations

Readers should interpret results from this review with circumspection, given the heterogeneity of the literature with regards to methodology, mental health outcomes and policy settings. Other methodological limitations included inconsistencies in pick of comparison groups, and datasets often lacking sufficient information to comprehensively adjust for confounding factors, both at the individual and area-level.

The generalizability of our study is also somewhat express by the definitions used. Our mental health definition included all aspects of mental health significant that our analysis did not capture the nuanced differences, for example, between different mental illnesses or psychiatric comorbidity as opposed to mental well-being [52]. Our definition of structural determinants was also wide encompassing many policies, making policy conclusions challenging. Whitehead, et al. [44] advise that a better arroyo is to focus on specific groups in the population and particular policies. We deliberately took a broad approach to get an overview, given that no systematic review has examined structural determinants and inequalities of mental health before.

Health inequalities is a growing field of research. Given the potential importance of structural determinants of mental illness, information technology is surprising that we did non notice more research manufactures assessing this research question. There are clearly methodological challenges in designing studies in this surface area. We must also note that important variations in study context mean that other factors, such every bit economical trends, migration trends, and the political climate may have played a role. Furthermore, information technology is of import to acknowledge the time lag from policy implementation to observing any associated effects on mental wellness [53].

Implications

To the best of our knowledge, this is the start review to examine structural determinants in inequalities in mental wellness. Additionally, our study is one of the few that focuses specifically on mental health outcomes rather than inequalities focused on cocky-rated health outcomes. Our study provides an overview of what express evidence is available in this field and identifies areas of futurity enquiry and policy directions.

Inquiry

In this review, we identified important gaps in the literature for future research. Area-based initiatives and educational policy for example are understudied. Studies should specifically inquiry inequalities, if we are to increase cognition in this expanse. Methodologically, nosotros need more natural policy experiments and more studies utilising historical cohort data to examine effects of structural determinants over a longer fourth dimension frame. Studies drawing on the life-class approach would also strengthen this area of research, given that the take a chance of mental illnesses may start equally early on every bit in childhood and may accumulate over fourth dimension. Finally, nosotros must acknowledge that the health intendance system may be a possible mediator. However, given that most mental health policy research focuses on health care access we intentionally excluded the health care domain from this review to focus on other of import policy domains. Futurity research should integrate the health policy domain.

Research comparing welfare states is important, but nosotros must also compare inside welfare states (e.yard. [43]) and follow change over time. For instance, although the Nordic countries share an overall ethos of equality and a strong focus on gender equality, there are differences between policy designs in each country [46]. As such, more case study inquiry on the dissimilar policy designs of Nordic countries are needed before we tin conclude that all Nordic countries promote better mental health outcomes for women.

Policy

The findings from this review bear some relevance to policy. For instance, our results indicate that austerity measures are associated with poor mental wellness outcomes and possibly increased suicides [29, 36]. Our findings should be a cautionary tale for governments wanting to shrink welfare states.

Our review also indicates that improving mental wellness outcomes may present policy-makers with a trade-off between reducing socio-economic inequalities or improving overall mental health outcomes. We demand more innovative policy solutions that reduce the adventure of this merchandise-off.

Conclusion

In Europe and elsewhere, rise business organization well-nigh inequality in health and increased prevalence of mental ill-health, means that ignoring the structural policies that may contribute to inequalities in mental health is no longer an option. This review provides knowledge to policy-makers and researchers when considering reforming policies to reduce inequalities in mental wellness outcomes. While, this review shows express evidence supporting the causal effects of structural determinants on socio-economic inequalities in mental wellness, we establish some show that policy may bear on gender inequalities. The lack of prove should not be interpreted as lack of effect. To strengthen the show base within the structural determinants of mental wellness inequalities research field and inform policies to reduce inequalities in mental health, futurity studies should seek to apply innovative methods to overcome the inherent methodological challenges in this surface area.

Notes

1. The study by Huang et al. 2022 included mothers as participants merely measured mental health on the child level. Thus the exposure was on the adult level and the outcome was on the kid level.

Abbreviations

ALMP:

Active Labour Market Policies

ASQ-SE:

Ages and Stages Questionnaire

CDA:

Child Development Accounts

CES-D8:

Centre for Epidemiological Studies Depression Scale

GHQ-12:

Global Health Questionnaire

HBSC:

Health Behaviour in School-Historic period Children

HEB-Wales Tool:

Health Show Message, Wales

MCS:

Mental Health Component Score

MH:

Mental Health

MHI-5:

Mental Health Inventory

MWB :

Mental Well-Being

NDC :

New Deal for Communities

NMSC:

Neo-Marxian Social Form

OECD:

Organization for Economical Co-operation and Development

PPL:

Paid Parental Exit

PRISMA:

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

SES:

Socio-Economical Status

SF:

Short Form Health Survey

SF-36:

Short Grade Health Survey (36 items)

SOPHIE:

Evaluating the Touch on of Structural Policies on Wellness Inequalities

WHO:

Earth Health Organization

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Acknowledgements

We would like to thank Nadja Trygg for comments on previous drafts of the report.

Funding

This work was funded past the Public Health Agency of Sweden as part of governmental initiative to increase the knowledge on mental wellness inequalities and their underlying determinants.

Availability of information and materials

Not applicative. However, to demonstrate transparency, we have provided supplementary files documenting the search process.

Author data

Affiliations

1. Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden

   A. McAllister, Due south. Fritzell, M. Almroth, L. Harber-Aschan, S. Larsson & B. Burström

2. The Public Health Agency of Sweden, Stockholm, Sweden

   S. Fritzell

Contributions

AM and SF designed the study. SL conducted initial screening and AM quality checked. AM, SF, SL and MA conducted level two screening, quality assessment and data extraction. AM, SF, MA, LHA and BB contributed to presentation of analysis. AM wrote the first typhoon of the manuscript with contribution from MA, LHA, SF and BB. All authors read and approved the final manuscript.

Corresponding writer

Correspondence to A. McAllister.

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McAllister, A., Fritzell, South., Almroth, M. et al. How do macro-level structural determinants touch on inequalities in mental health? – a systematic review of the literature. Int J Equity Wellness 17, 180 (2018). https://doi.org/10.1186/s12939-018-0879-9

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• Received: 06 June 2018

• Accepted: 22 October 2018

• Published: 06 December 2018

• DOI : https://doi.org/ten.1186/s12939-018-0879-9

Keywords

• Mental wellness
• Structural determinants
• Systematic review
• Inequalities
• Gender
• Socio-economic
• Equity

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